Search results for: food distribution networks

Authors: Allal Bedlaoui, Hamid Boutoutaou

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Due to its superior economics, shrink-fit assembly is one of the best mechanical assembly methods. There are simply two components, the axis and hub. It is used in many different industries, including the production of trains, cars, and airplanes. The outer radius of the inner cylinder must be greater than the inner radius of the outer cylinder for this operation; this difference is referred to as the "interference" between the two cylinders. There are three ways to accomplish this: heating the outer cylinder to cause it to expand; cooling the cylinder's inside to cause it to contract; and third, finishing the fitting under a press. At the intersection of the two matched parts, a contact pressure and friction force are generated. We consider interference and form defects in this article because they prevent the connection between the axis and the hub from having a perfect form surface and because we will be looking at how they affect the assembly. Numerical simulation is used to ascertain if interference and form defects have a beneficial or negative influence in the distribution of stresses, assembly resistance, and plasticity.

Keywords: shrink-fit, interference, form defect, plasticity, extraction force

Procedia PDF Downloads 83

Authors: Aklilu Zeleke

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A cross-sectional study was conducted in order to understand the effect of wet and dry seasons on the free residual chlorine and bacteriological contamination of the Addis Ababa (Ethiopia) water supply system. Water samples were taken at 30 selected distribution points and analyzed for Free Residual Chlorine and bacteriological analysis total coliforms and fecal coliform). It was found that some of the bacteriological data and Free Residual Chlorine levels are below the recommended values and beyond the maximum tolerable limits recommended by World Health Organization and Ethiopian National Standards. Water quality during the dry season is better than that of the wet season. There is a strong relationship between Free Residual Chlorine levels in drinking water and its bacteriological quality.

Keywords: addis ababa, wet season, dry season, free residual chlorine

Procedia PDF Downloads 83

Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

Procedia PDF Downloads 199

Authors: Vivek Rangarajan, Kim G. Klarke

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With overpopulation threatening the world’s ability to feed itself, food production and protection has become a major issue, especially in developing countries. Almost one-third of the food produced for human consumption, around 1.3 billion tonnes, is either wasted or lost annually. Postharvest decay in particular constitutes a major cause of crop loss with about 20% of fruits and vegetables produced lost during postharvest storage, mainly due to fungal disease. Some of the major phytopathogenic fungi affecting postharvest fruit crops in South Africa include Aspergillus, Botrytis, Penicillium, Alternaria and Sclerotinia spp. To date control of fungal phytopathogens has primarily been dependent on synthetic chemical fungicides, but these chemicals pose a significant threat to the environment, mainly due to their xenobiotic properties and tendency to generate resistance in the phytopathogens. Here, an environmentally benign alternative approach to control postharvest fungal phytopathogens in perishable fruit crops has been presented, namely the application of a bio-fungicide in the form of lipopeptide molecules. Lipopeptides are biosurfactants produced by Bacillus spp. which have been established as green, nontoxic and biodegradable molecules with antimicrobial properties. However, since the Bacillus are capable of producing a large number of lipopeptide homologues with differing efficacies against distinct target organisms, the lipopeptide production conditions and strategy are critical to produce the maximum lipopeptide concentration with homologue ratios to specification for optimum bio-fungicide efficacy. Process conditions, and their impact on Bacillus lipopeptide production, were evaluated in fully instrumented laboratory scale bioreactors under well-regulated controlled and defined environments. Factors such as the oxygen availability and trace element and nitrate concentrations had profound influences on lipopeptide yield, productivity and selectivity. Lipopeptide yield and homologue selectivity were enhanced in cultures where the oxygen in the sparge gas was increased from 21 to 30 mole%. The addition of trace elements, particularly Fe2+, increased the total concentration of lipopeptides and a nitrate concentration equivalent to 8 g/L ammonium nitrate resulted in optimum lipopeptide yield and homologue selectivity. Efficacy studies of the culture supernatant containing the crude lipopeptide mixture were conducted using phytopathogens isolated from fruit in the field, identified using genetic sequencing. The supernatant exhibited antifungal activity against all the test-isolates, namely Lewia, Botrytis, Penicillium, Alternaria and Sclerotinia spp., even in this crude form. Thus the lipopeptide product efficacy has been confirmed to control the main diseases, even in the basic crude form. Future studies will be directed towards purification of the lipopeptide product and enhancement of efficacy.

Keywords: antifungal efficacy, biocontrol, lipopeptide production, perishable crops

Procedia PDF Downloads 406

Authors: Danny Alexander R. Moreno, Gustavo L. Sartorello, Yuli Andrea P. Bermudez, Richard R. Lobo, Ives Claudio S. Bueno, Augusto H. Gameiro

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Meat production is a significant sector for Brazil's economy; however, the agricultural segment has suffered censure regarding the negative impacts on the environment, which consequently results in climate change. Therefore, it is essential the implementation of nutritional strategies that can improve the environmental performance of livestock. This research aimed to estimate the environmental impact and profitability of the use of yerba mate extract (Ilex paraguariensis) as an additive in the feeding of feedlot lamb. Thirty-six castrated male lambs (average weight of 23.90 ± 3.67 kg and average age of 75 days) were randomly assigned to four experimental diets with different levels of inclusion of yerba mate extract (0, 1, 2, and 4 %) based on dry matter. The animals were confined for fifty-three days and fed with 60:40 corn silage to concentrate ratio. As an indicator of environmental impact, the carbon footprint (CF) was measured as kg of CO₂ equivalent (CO₂-eq) per kg of body weight produced (BWP). The greenhouse gas (GHG) emissions such as methane (CH₄) generated from enteric fermentation, were calculated using the sulfur hexafluoride gas tracer (SF₆) technique; while the CH₄, nitrous oxide (N₂O - emissions generated by feces and urine), and carbon dioxide (CO₂ - emissions generated by concentrate and silage processing) were estimated using the Intergovernmental Panel on Climate Change (IPCC) methodology. To estimate profitability, the gross margin was used, which is the total revenue minus the total cost; the latter is composed of the purchase of animals and food. The boundaries of this study considered only the lamb fattening system. The enteric CH₄ emission from the lamb was the largest source of on-farm GHG emissions (47%-50%), followed by CH₄ and N₂O emissions from manure (10%-20%) and CO₂ emission from the concentrate, silage, and fossil energy (17%-5%). The treatment that generated the least environmental impact was the group with 4% of yerba mate extract (YME), which showed a 3% reduction in total GHG emissions in relation to the control (1462.5 and 1505.5 kg CO₂-eq, respectively). However, the scenario with 1% YME showed an increase in emissions of 7% compared to the control group. In relation to CF, the treatment with 4% YME had the lowest value (4.1 kg CO₂-eq/kg LW) compared with the other groups. Nevertheless, although the 4% YME inclusion scenario showed the lowest CF, the gross margin decreased by 36% compared to the control group (0% YME), due to the cost of YME as a food additive. The results showed that the extract has the potential for use in reducing GHG. However, the cost of implementing this input as a mitigation strategy increased the production cost. Therefore, it is important to develop political strategies that help reduce the acquisition costs of input that contribute to the search for the environmental and economic benefit of the livestock sector.

Keywords: meat production, natural additives, profitability, sheep

Procedia PDF Downloads 145

Authors: Xiaohan Bookman, Xiaoyan Zhu

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Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

Procedia PDF Downloads 350

Authors: I. Boroňová, J. Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, S. Mačeková, J. Poráčová, M. M. Blaščáková

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Osteoporosis is a common multifactorial disease with a strong genetic component characterized by reduced bone mass and increased risk of fractures. Genetic factors play an important role in the pathogenesis of osteoporosis. The aim of our study was to identify the genotype and allele distribution of T245G polymorphism in OPG gene in Slovak postmenopausal women. A total of 200 unrelated Slovak postmenopausal women with diagnosed osteoporosis and 200 normal controls were genotyped for T245G (rs3134069) polymorphism of OPG gene. Genotyping was performed using the Custom Taqman®SNP Genotyping assays. Genotypes and alleles frequencies showed no significant differences (p=0.5551; p=0.6022). The results of the present study confirm the importance of T245G polymorphism in OPG gene in the pathogenesis of osteoporosis.

Keywords: OPG gene, T245G polymorphism, osteoporosis, T245G polymorphism, real-time PCR

Procedia PDF Downloads 414

Authors: Claudio Burguez, María Castelló, Mikaela Pisani, Marcos Umpiérrez

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BIOFEEDBACK exhibition offers a unique experience for each visitor, combining art, neuroscience, and technology in an interactive way. Using a headband that captures the bioelectric activity of the brain, the visitors are able to generate sound and images in a sequence loop, making them an integral part of the artwork. Through this interactive exhibit, visitors gain a deeper appreciation of the beauty and complexity of the brain. As a special takeaway, visitors will receive an NFT as a present, allowing them to continue their engagement with the exhibition beyond the physical space. We used the EEG Biofeedback technique following a closed-loop neuroscience approach, transforming EEG data captured by a Muse S headband in real-time into audiovisual stimulation. PureData is used for sound generation and Generative Adversarial Networks (GANs) for image generation. Thirty participants have experienced the exhibition. For some individuals, it was easier to focus than others. Participants who said they could focus during the exhibit stated that at one point, they felt that they could control the sound, while images were more abstract, and they did not feel that they were able to control them.

Keywords: art, audiovisual, biofeedback, EEG, NFT, neuroscience, technology

Procedia PDF Downloads 76

Authors: Taksina Bunbut, Kevin Wongleedee

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The purposes of this research were to study factors influencing the decision of international tourists to revisit Bangkok, Thailand. A random 200 samples was collected. Half the sample group was male and the other half was female. A questionnaire was used to collect data and small in-depth interviews were also used to get their opinions about importance of tourist decision making factors. The findings revealed that the majority of respondents rated these factors at medium level of importance. The ranking showed that the first three important factors were a safe place to stay, friendly people, and clean food. The three least important factors were a convenience transportation, clean country, and child friendly. In addition there was no significance difference between male and female in their ratings of the factors of influencing the decision of international tourists to revisit Bangkok, Thailand.

Keywords: factors, international tourists, revisit, Thailand

Procedia PDF Downloads 331

Authors: Arash Ahmadi, Amirreza Kavousizadeh, Sanaz Heidarzadeh

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Stage-discharge curve is one of the conventional methods for continuous river flow measurement. In this paper, an innovative approach is proposed for predicting the stage-discharge relationship using the application of isovel contours. Using the proposed method, it is possible to estimate the stage-discharge curve in the whole section with only using discharge information from just one arbitrary water level. For this purpose, multivariate relationships are used to determine the mean velocity in a cross-section. The unknown exponents of the proposed relationship have been obtained by using the second version of the Strength Pareto Evolutionary Algorithm (SPEA2), and the appropriate equation was selected by applying the TOPSIS (Technique for Order Preferences by Similarity to an Ideal Solution) approach. Results showed a close agreement between the estimated and observed data in the different cross-sections.

Keywords: rating curves, SPEA2, natural rivers, bed roughness distribution

Procedia PDF Downloads 163

Authors: Stefania Fortino, Petr Hradil, Timo Avikainen

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Timber bridges have an excellent environmental performance, are economical, relatively easy to build and can have a long service life. However, the durability of these bridges is the main problem because of their exposure to outdoor climate conditions. The moisture content accumulated in wood for long periods, in combination with certain temperatures, may cause conditions suitable for timber decay. In addition, moisture content variations affect the structural integrity, serviceability and loading capacity of timber bridges. Therefore, the monitoring of the moisture content in wood is important for the durability of the material but also for the whole superstructure. The measurements obtained by the usual sensor-based techniques provide hygro-thermal data only in specific locations of the wood components. In this context, the monitoring can be assisted by numerical modelling to get more information on the hygro-thermal response of the bridges. This work presents a hygro-thermal model based on a multi-phase moisture transport theory to predict the distribution of moisture content, relative humidity and temperature in wood. Below the fibre saturation point, the multi-phase theory simulates three phenomena in cellular wood during moisture transfer, i.e., the diffusion of water vapour in the pores, the sorption of bound water and the diffusion of bound water in the cell walls. In the multi-phase model, the two water phases are separated, and the coupling between them is defined through a sorption rate. Furthermore, an average between the temperature-dependent adsorption and desorption isotherms is used. In previous works by some of the authors, this approach was found very suitable to study the moisture transport in uncoated and coated stress-laminated timber decks. Compared to previous works, the hygro-thermal fluxes on the external surfaces include the influence of the absorbed solar radiation during the time and consequently, the temperatures on the surfaces exposed to the sun are higher. This affects the whole hygro-thermal response of the timber component. The multi-phase model, implemented in a user subroutine of Abaqus FEM code, provides the distribution of the moisture content, the temperature and the relative humidity in a volume of the timber deck. As a case study, the hygro-thermal data in wood are collected from the ongoing monitoring of the stress-laminated timber deck of Tapiola Bridge in Finland, based on integrated humidity-temperature sensors and the numerical results are found in good agreement with the measurements. The proposed model, used to assist the monitoring, can contribute to reducing the maintenance costs of bridges, as well as the cost of instrumentation, and increase safety.

Keywords: moisture content, multi-phase models, solar radiation, timber decks, FEM

Procedia PDF Downloads 178

Authors: Hemant Kumar Pathak

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In 1994, Matthews (S.G. Matthews, Partial metric topology, in: Proc. 8th Summer Conference on General Topology and Applications, in: Ann. New York Acad. Sci., vol. 728, 1994, pp. 183-197) introduced the concept of a partial metric as a part of the study of denotational semantics of data flow networks. He gave a modified version of the Banach contraction principle, more suitable in this context. In fact, (complete) partial metric spaces constitute a suitable framework to model several distinguished examples of the theory of computation and also to model metric spaces via domain theory. In this paper, we introduce the concept of almost partial Hausdorff metric. We prove a fixed point theorem for multi-valued mappings on partial metric space using the concept of almost partial Hausdorff metric and prove an analogous to the well-known Nadler’s fixed point theorem. In the sequel, we derive a homotopy result as an application of our main result.

Keywords: fixed point, partial metric space, homotopy, physical sciences

Procedia PDF Downloads 447

Authors: Awet Araya

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Cochliobolus sativus ((anamorphic stage: Bipolaris sorokiniana (synonyms: Helminthosporium sorokinianum, Drechslera sorokiniana, and Helminthosporium sativum)) is an important pathogen of cereal crops. Many other grass species are also hosts for this fungus. Yield losses have been reported from many regions, especially where barley and wheat are commercially cultivated. The fungus has a worldwide distribution. The pathogen causes root rot, seedling blight, spot blotch, head blight, and black point. Environmental conditions affect disease development. Most of the time, fungus survives as mycelia and conidia. Pseudothecium of the fungus is not commonly encountered and probably not important in the epidemiology of the disease. The fungus can be in seed, soil, or in plant parts. Crop rotation, proper fertilization, reducing other stress factors, fungicide treatments, and resistant cultivars may be used for the control of the disease.

Keywords: Cochliobolus sativus, barley, cultivars, root rot

Procedia PDF Downloads 236

Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

Procedia PDF Downloads 283

Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

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The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

Procedia PDF Downloads 422

Authors: K. Shahril, M. Ridzuan, M. Sabri

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The disc rotor is solid, ventilated or drilled. The ventilated type disc rotor consists of a wider disc with cooling fins cast through the middle to ensure good cooling. The disc brakes use pads that are pressed axially against a rotor or disc. Solid and ventilated disc design are same which it free with any form, unless inside the ventilated disc has several ventilation holes. Different with drilled disc has some construction on the surface which is has six lines of drill hole penetrate the disc and a little bit deep twelve curves. From the thermal analysis that was conducted by using ANSYS Software, temperature distribution and heat transfer rate on the disc were obtained on each design. Temperature occurred on the drilled disc was lowest than ventilated and solid disc, it is 66% better than ventilated while ventilated is 21% good than solid disc.

Keywords: disc brakes, drilled disc, thermal analysis, ANSYS software

Procedia PDF Downloads 390

Authors: Birgit A. A. Solem, Kristin Bentsen

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Scholarly attention in entrepreneurship is currently directed towards understanding entrepreneurial venture creation as a process -the journey of new economic activities from nonexistence to existence often studied through flow- or network models. To complement existing research on entrepreneurial venture creation with more interactivity-based research of organized activities, this study examines two pop-up stores as anchor events involving on-site activities of fifteen participating entrepreneurs launching their new ventures. The pop-up stores were arranged in two middle-sized Norwegian cities and contained different brand stores that brought together actors of sub-networks and communities executing venture creation activities. The pop-up stores became on-site arenas for the entrepreneurs to create, maintain, and rejuvenate their networks, at the same time as becoming venues for temporal coordination of activities involving existing and potential customers in their venture creation. In this work, we apply a conceptual framework based on frequently addressed dilemmas within entrepreneurship theory (discovery/creation, causation/effectuation) to further shed light on the broad aspect of on-site anchor event activities and their venture creation outcomes. The dilemma-based concepts are applied as an analytic toolkit to pursue answers regarding the nature of anchor event activities typically found within entrepreneurial venture creation and how these anchor event activities affect entrepreneurial venture creation outcomes. Our study combines researcher participation with 200 hours of observation and twenty in-depth interviews. Data analysis followed established guidelines for hermeneutic analysis and was intimately intertwined with ongoing data collection. Data was coded and categorized in NVivo 12 software, and iterated several times as patterns were steadily developing. Our findings suggest that core anchor event activities typically found within entrepreneurial venture creation are; a concept- and product experimentation with visitors, arrangements to socialize (evening specials, auctions, and exhibitions), store-in-store concepts, arranged meeting places for peers and close connection with municipality and property owners. Further, this work points to four main entrepreneurial venture creation outcomes derived from the core anchor event activities; (1) venture attention, (2) venture idea-realization, (3) venture collaboration, and (4) venture extension. Our findings show that, depending on which anchor event activities are applied, the outcomes vary. Theoretically, this study offers two main implications. First, anchor event activities are both discovered and created, following the logic of causation, at the same time as being experimental, based on “learning by doing” principles of effectuation during the execution. Second, our research enriches prior studies on venture creation as a process. In this work, entrepreneurial venture creation activities and outcomes are understood through pop-up stores as on-site anchor event arenas, particularly suitable for interactivity-based research requested by the entrepreneurship field. This study also reveals important managerial implications, such as that entrepreneurs should allow themselves to find creative physical venture creation arenas (e.g., pop-up stores, showrooms), as well as collaborate with partners when discovering and creating concepts and activities based on new ideas. In this way, they allow themselves to both strategically plan for- and continually experiment with their venture.

Keywords: anchor event, interactivity-based research, pop-up store, entrepreneurial venture creation

Procedia PDF Downloads 96

Authors: Seyed Mohammadbagher Jafari, Elahe Mahdizadeh, Masomeh Ghahremani

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Nowadays almost all organizations depend on information systems to run their businesses. Investment on information systems and their maintenance to keep them always in best situation to support firm business is one of the main issues for every organization. The new concept of cloud computing was developed as a technical and economic model to address this issue. In cloud computing the computing resources, including networks, applications, hardwares and services are configured as needed and are available at the moment of request. However, migration to cloud is not an easy task and there are many issues that should be taken into account. This study tries to provide a comprehensive model to assess a firm readiness to implement cloud computing. By conducting a systematic literature review, four dimensions of readiness were extracted which include technological, human, organizational and environmental dimensions. Every dimension has various criteria that have been discussed in details. This model provides a framework for cloud computing readiness assessment. Organizations that intend to migrate to cloud can use this model as a tool to assess their firm readiness before making any decision on cloud implementation.

Keywords: cloud computing, human readiness, organizational readiness, readiness assessment model

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

Procedia PDF Downloads 213

Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

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This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system. Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, fault location, underground cable, wavelet transform

Procedia PDF Downloads 518

Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager

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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.

Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF

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Authors: Dmitry V. Fomichev, Vladimir V. Solonin

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This paper presents the findings from a numerical simulation of the flow in 37-rod fuel assembly models spaced by a double-wire trapezoidal wrapping as applied to the BREST-OD-300 experimental nuclear reactor. Data on a high static pressure distribution within the models, and equations for determining the fuel bundle flow friction factors have been obtained. Recommendations are provided on using the closing turbulence models available in the ANSYS Fluent. A comparative analysis has been performed against the existing empirical equations for determining the flow friction factors. The calculated and experimental data fit has been shown. An analysis into the experimental data and results of the numerical simulation of the BREST-OD-300 fuel rod assembly hydrodynamic performance are presented.

Keywords: BREST-OD-300, ware-spaces, fuel assembly, computation fluid dynamics

Procedia PDF Downloads 386

Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

Procedia PDF Downloads 184

Authors: Malee Santikunaporn, Neera Wongtyanuwat, Channarong Asavatesanupap

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Pyrolysis of waste oil is an effective process to produce high quality liquid fuels. In this work, pyrolysis experiments of waste oil over Y zeolite were carried out in a semi-batch reactor under a flow of nitrogen at atmospheric pressure and at different reaction temperatures (350-450 ^oC). The products were gas, liquid fuel, and residue. Only liquid fuel was further characterized for its composition and properties by using gas chromatography, thermogravimetric analyzer, and bomb calorimeter. Experimental results indicated that the pyrolysis reaction temperature significantly affected both yield and composition distribution of pyrolysis oil. An increase in reaction temperature resulted in increased fuel yield, especially gasoline fraction. To obtain high amount of fuel, the optimal reaction temperature should be higher than 350 ^oC. A presence of Y zeolite in the system enhanced the cracking activity. In addition, the pyrolysis oil yield is proportional to the catalyst quantity.

Keywords: gasoline, diesel, pyrolysis, waste oil, Y zeolite

Procedia PDF Downloads 201

Authors: Anubhav Shrivastava Shivarudraswamy, Bhat Lakshya

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Distributed generation has indeed become a major area of interest in recent years. Distributed generation can address a large number of loads in a power line and hence has better efficiency over the conventional methods. However, there are certain drawbacks associated with it, an increase in voltage being the major one. This paper addresses the voltage control at the buses for an IEEE 30 bus system by regulating reactive power. For carrying out the analysis, the suitable location for placing distributed generators (DG) is identified through load flow analysis and seeing where the voltage profile is dipping. MATLAB programming is used to regulate the voltage at all buses within +/- 5% of the base value even after the introduction of DGs. Three methods for regulation of voltage are discussed. A sensitivity based analysis is then carried out to determine the priority among the various methods listed in the paper.

Keywords: distributed generators, distributed system, reactive power, voltage control, sensitivity analysis

Procedia PDF Downloads 662

Authors: Niloufar Yadgari

Abstract:

GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.

Keywords: GAN, pathology, generative adversarial network, neuro imaging

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Authors: Mohadese Oghbaee, Borna Firouzi

Abstract:

The emergence of the Internet and more specifically the formation of social media has provided the ground for paying attention to new types of content dissemination. In recent years, Social media users share information, communicate with others, and exchange opinions on social events in this space. Many of the information published in this space are suspicious and produced with the intention of deceiving others. These contents are often called "fake news". Fake news, by disrupting the circulation of the concept and similar concepts such as fake news with correct information and misleading public opinion, has the ability to endanger the security of countries and deprive the audience of the basic right of free access to real information; Competing governments, opposition elements, profit-seeking individuals and even competing organizations, knowing about this capacity, act to distort and overturn the facts in the virtual space of the target countries and communities on a large scale and influence public opinion towards their goals. This process of extensive de-truthing of the information space of the societies has created a wave of harm and worries all over the world. The formation of these concerns has led to the opening of a new path of research for the timely containment and reduction of the destructive effects of fake news on public opinion. In addition, the expansion of this phenomenon has the potential to create serious and important problems for societies, and its impact on events such as the 2016 American elections, Brexit, 2017 French elections, 2019 Indian elections, etc., has caused concerns and led to the adoption of approaches It has been dealt with. In recent years, a simple look at the growth trend of research in "Scopus" shows an increasing increase in research with the keyword "false information", which reached its peak in 2020, namely 524 cases, reached, while in 2015, only 30 scientific-research contents were published in this field. Considering that one of the capabilities of social media is to create a context for the dissemination of news and information, both true and false, in this article, the classification of strategies for spreading fake news in social networks was investigated in social events. To achieve this goal, thematic analysis research method was chosen. In this way, an extensive library study was first conducted in global sources. Then, an in-depth interview was conducted with 18 well-known specialists and experts in the field of news and media in Iran. These experts were selected by purposeful sampling. Then by analyzing the data using the theme analysis method, strategies were obtained; The strategies achieved so far (research is in progress) include unrealistically strengthening/weakening the speed and content of the event, stimulating psycho-media movements, targeting emotional audiences such as women, teenagers and young people, strengthening public hatred, calling the reaction legitimate/illegitimate. events, incitement to physical conflict, simplification of violent protests and targeted publication of images and interviews were introduced.

Keywords: fake news, social network, social events, thematic analysis

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Authors: Iman Abu-Rub

Abstract:

This research paper examines if Artificial Intelligence is, in fact, racist or not. Different studies from all around the world, and covering different communities were analyzed to further understand AI’s true implications over different communities. The black community, Asian community, and Muslim community were all analyzed and discussed in the paper to figure out if AI is biased or unbiased towards these specific communities. It was found that the biggest problem AI faces is the biased distribution of data collection. Most of the data inserted and coded into AI are of a white male, which significantly affects the other communities in terms of reliable cultural, political, or medical research. Nonetheless, there are various research was done that help increase awareness of this issue, but also solve it completely if done correctly. Governments and big corporations are able to implement different strategies into their AI inventions to avoid any racist results, which could cause hatred culturally but also unreliable data, medically, for example. Overall, Artificial Intelligence is not racist per se, but the data implementation and current racist culture online manipulate AI to become racist.

Keywords: social media, artificial intelligence, racism, discrimination

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Authors: Wiem Gadri

Abstract:

This study delves into the intriguing properties of Pisot and Salem numbers within the framework of formal Laurent series over finite fields, a domain where these numbers’ spectral charac-teristics, Λm(β) and lm(β), have yet to be fully explored. Utilizing a methodological approach that combines algebraic number theory with the analysis of power series, we extend the foundational work of Erdos, Joo, and Komornik to this new setting. Our research uncovers bounds for lm(β), revealing how these depend on the degree of the minimal polynomial of β and thus offering a novel characterization of Pisot and Salem formal power series. The findings significantly contribute to our understanding of these numbers, highlighting their distribution and properties in the context of formal power series. This investigation not only bridges number theory with formal power series analysis but also sets the stage for further interdisciplinary research in these areas.

Keywords: Pisot numbers, Salem numbers, formal power series, over a finite field

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Authors: Anna V. Zaporozhchenko, Dmytro Kutnyakhov, Katherina Medjanik, Christian Tusche, Hans-Joachim Elmers, Olena Fedchenko, Sergey Chernov, Martin Ellguth, Sergej A. Nepijko, Gerd Schoenhense

Abstract:

Graphene reveals a unique electronic structure that predetermines many intriguing properties such as massless charge carriers, optical transparency and high velocity of fermions at the Fermi level, opening a wide horizon of future applications. Hence, a detailed investigation of the electronic structure of graphene is crucial. The method of choice is angular resolved photoelectron spectroscopy ARPES. Here we present experiments using time-of-flight (ToF) momentum microscopy, being an alternative way of ARPES using full-field imaging of the whole Brillouin zone (BZ) and simultaneous acquisition of up to several 100 energy slices. Unlike conventional ARPES, k-microscopy is not limited in simultaneous k-space access. We have recorded the whole first BZ of graphene on Ir(111) including all six Dirac cones. As excitation source we used synchrotron radiation from BESSY II (Berlin) at the U125-2 NIM, providing linearly polarized (both polarizations p- and s-) VUV radiation. The instrument uses a delay-line detector for single-particle detection up the 5 Mcps range and parallel energy detection via ToF recording. In this way, we gather a 3D data stack I(E,kx,ky) of the full valence electronic structure in approx. 20 mins. Band dispersion stacks were measured in the energy range of 14 eV up to 23 eV with steps of 1 eV. The linearly-dispersing graphene bands for all six K and K’ points were simultaneously recorded. We find clear features of hybridization with the substrate, in particular in the linear dichroism in the angular distribution (LDAD). Recording of the whole Brillouin zone of graphene/Ir(111) revealed new features. First, the intensity differences (i.e. the LDAD) are very sensitive to the interaction of graphene bands with substrate bands. Second, the dark corridors are investigated in detail for both, p- and s- polarized radiation. They appear as local distortions of photoelectron current distribution and are induced by quantum mechanical interference of graphene sublattices. The dark corridors are located in different areas of the 6 Dirac cones and show chirality behaviour with a mirror plane along vertical axis. Moreover, two out of six show an oval shape while the rest are more circular. It clearly indicates orientation dependence with respect to E vector of incident light. Third, a pattern of faint but very sharp lines is visible at energies around 22eV that strongly remind on Kikuchi lines in diffraction. In conclusion, the simultaneous study of all six Dirac cones is crucial for a complete understanding of dichroism phenomena and the dark corridor.

Keywords: band structure, graphene, momentum microscopy, LDAD

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