Search results for: Artificial Neural Network (ANNs)

Authors: Sonia Ben Hamza, Sabra Habli, Nejla Mahjoub Saïd, Hervé Bournot, Georges Le Palec

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This paper spots light on the effect of a point source pollution on streams, stemming out from intentional release caused by unconscious facts. The consequences of such contamination on ecosystems are very serious. Accordingly, effective tools are highly demanded in this respect, which enable us to come across an accurate progress of pollutant and anticipate different measures to be applied in order to limit the degradation of the environmental surrounding. In this context, we are eager to model a pollutant dispersion of a free surface flow which is ejected by an outfall sewer of an urban sewerage network in coastal water taking into account the influence of climatic parameters on the spread of pollutant. Numerical results showed that pollutant dispersion is merely due to the presence of vortices and turbulence. Hence, it was realized that the pollutant spread in seawater is strongly correlated with climatic conditions in this region.

Keywords: coastal waters, numerical simulation, pollutant dispersion, turbulent flows

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Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar

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Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).

Keywords: air pollution, AODV, re-scheduling, WSNs

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Authors: Mario C. Nierras

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This study aimed to determine the extension services’ needs of small farmers in Biliran province, Philippines. It also sought to find out other issues/concerns of the small farmers. Extension services’ needs of small farmers were gathered through personal interviewing and observational analysis of randomly-selected small farmers in Biliran, Philippines. Biliran small farmers extension services’ needs include: raising fruits, raising legumes, raising vegetables, raising swine, raising cattle, and raising chicken (as priority broad skills). For the specific skills, diagnosing symptoms on fertilizer deficiencies, controlling plant pests and diseases, diagnosing signs on specific pest and disease damage, controlling animal pests and diseases, and doing artificial insemination were the priority skills. They considered an on-farm trial of new technology as most needed to be coupled with industry and quality-orientedness, as positive behaviors needed in farming success. The farmers still adhere to the so-called wait-and-see attitude, thus they are more convinced to follow a particular technology if they see a concrete result of the introduced changes. Technical needs prioritization of Biliran small farmers showed that they have a real need for crop and animal production skills to include the other issues/concerns. Extension service program planning for small farmers should be patterned after their technical needs giving due attention to some issues/concerns so that extension work could deliver the right skills for the right needs of the farmers.

Keywords: extension, extension service, extension service needs, extension service program, farmers, small farmers, marginal farmers

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Authors: Anisuzzaman Khan, A. J. K. Masud

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Bangladesh is the largest delta in the world predominantly comprising large network of rives and wetlands. Wetlands in Bangladesh are represented by inland freshwater, estuarine brakishwater and tidal salt-water coastal wetlands. Bangladesh possesses enormous area of wetlands including rivers and streams, freshwater lakes and marshes, haors, baors, beels, water storage reservoirs, fish ponds, flooded cultivated fields and estuarine systems with extensive mangrove swamps. The past, present, and future of Bangladesh, and its people’s livelihoods are intimately connected to its relationship with water and wetlands. More than 90% of the country’s total area consists of alluvial plains, crisscrossed by a complex network of rivers and their tributaries. Floodplains, beels (low-lying depressions in the floodplain), haors (deep depression) and baors (oxbow lakes) represent the inland freshwater wetlands. Over a third of Bangladesh could be termed as wetlands, considering rivers, estuaries, mangroves, floodplains, beels, baors and haors. The country’s wetland ecosystems also offer critical habitats for globally significant biological diversity. Of these the deeply flooded basins of north-east Bangladesh, known as haors, are a habitat of wide range of wild flora and fauna unique to Bangladesh. The haor basin lies within the districts of Sylhet, Sunamgonj, Netrokona, Kishoregonj, Habigonj, Moulvibazar, and Brahmanbaria in the Northeast region of Bangladesh comprises the floodplains of the Meghna tributaries and is characterized by the presence of numerous large, deeply flooded depressions, known as haors. It covers about around 8,568 km2 area of Bangladesh. The topography of the region is steep at around foothills in the north and slopes becoming mild and milder gradually at downstream towards south. Haor is a great reservoir of aquatic biological resources and acts as the ecological safety net to the nature as well as to the dwellers of the haor. But in reality, these areas are considered as wastelands and to make these wastelands into a productive one, a one sided plan has been implementing since long. The programme is popularly known as Flood Control, Drainage and Irrigation (FCDI) which is mainly devoted to increase the monoculture rice production. However, haor ecosystem is a multiple-resource base which demands an integrated sustainable development approach. The ongoing management approach is biased to only rice production through FCDI. Thus this primitive mode of action is diminishing other resources having more economic potential ever thought.

Keywords: freshwater wetlands, biological diversity, biological resources, conservation and sustainable development

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Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed

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In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.

Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless

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Authors: Kai Zhu, Shanhua He, Yujiao Chang

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This paper explores the virtual linguistic landscape of an emerging virtual language community in TikTok, a language community realizing immediate and non-immediate communication without a precise Spatio-temporal domain or a specific socio-cultural boundary or interpersonal network. This kind of language community generates a large number and various forms of virtual linguistic landscape, with which we conducted a virtual ethnographic survey together with telephone interviews to collect data from coping. We have been following two language communities in TikTok for several months so that we can illustrate the composition of the two language communities and some typical virtual language landscapes in both language communities first. Then we try to explore the reasons why and how they are formed through the organization, transcription, and analysis of the interviews. Our analysis reveals the richness and diversity of the virtual linguistic landscape, and finally, we summarize some of the characteristics of this language community.

Keywords: virtual linguistic landscape, virtual language community, virtual ethnographic survey, TikTok

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Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

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Authors: Prakher Mishra, Dikshant Bodana, Saloni Desai, Sudhanshu Dixit, Sopan Agarwal, Shriraj Patel

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Railways are sometimes lifeline of nations as they consist of huge network of rail lines and bridges. Reportedly many of the bridges are aging, weak, distressed and accident prone. It becomes a really challenging task for Engineers and workers to keep up a regular maintenance schedule for proper functioning which itself is quite a hard hitting job. In this paper we have come up with an innvovative wireless system of maintenance called BriMAIN. In this system we have installed two types of sensors, first one is called a force sensor which will continously analyse the readings of pressure at joints of the bridges and secondly an MPU-6050 triaxial gyroscope+accelerometer which will analyse the deflection of the deck of the bridge. Apart from this a separate database is also being made at the server room so that the data can be visualized by the engineers and a warning can be issued in case reading of the sensors goes above threshold.

Keywords: Accelerometer, B-MAIN, Gyroscope, MPU-6050

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

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Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov

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It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.

Keywords: dispersed systems, models, hydraulic network, algorithms

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Authors: Chul Lee, Seoae Cho, Erich D. Jarvis, Heebal Kim

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Vocal learning, the ability to imitate vocalizations based on auditory experience, is a homoplastic character state observed in different independent lineages of animals such as songbirds, parrots, hummingbirds and human. It has now become possible to perform genome-wide molecular analyses across vocal learners and vocal non-learners with the recent expansion of avian genome data. It was analyzed the whole genomes of human and 48 avian species including those belonging to the three avian vocal learning lineages, to determine if behavior and neural convergence are associated with molecular convergence in divergent species of vocal learners. Analyses of 8295 orthologous genes across bird species revealed 141 genes with amino acid substitutions specific to vocal learners. Out of these, 25 genes have vocal learner specific genetic homoplasies, and their functions were enriched for learning. Several sites in these genes are estimated under convergent evolution and positive selection. A potential role for a subset of these genes in vocal learning was supported by associations with gene expression profiles in vocal learning brain regions of songbirds and human disease that cause language dysfunctions. The key candidate gene with multiple independent lines of the evidences specific to vocal learners was DRD5. Our findings suggest cAMP-based learning pathway in avian vocal learners, indicating molecular homoplastic changes associated with a complex behavioral trait, vocal learning.

Keywords: amino acid substitutions, convergent evolution, positive selection, vocal learning

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

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Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Nada Souissi, Mourad Mroua

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The main purpose of this study is to examine the interaction between financial asset volatility, economic factors and investor's behavioral indicators related to both the company's and the markets stocks for the period from January 2000 to January2020. Using multiple linear regression and Bayesian Networks modeling, results show a positive and negative relationship between investor's psychology index, economic factors and predicted stock market return. We reveal that the application of the Bayesian Discrete Network contributes to identify the different cause and effect relationships between all economic, financial variables and psychology index.

Keywords: Financial asset return predictability, Economic factors, Investor's psychology index, Bayesian approach, Probabilistic networks, Parametric learning

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Authors: Vivek Hokam, Vishrut Landge

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An ideal maintenance program for an industrial road network is one that would maintain all sections at a sufficiently high level of functional and structural conditions. However, due to various constraints such as budget, manpower and equipment, it is not possible to carry out maintenance on all the needy industrial road sections within a given planning period. A rational and systematic priority scheme needs to be employed to select and schedule industrial road sections for maintenance. Priority analysis is a multi-criteria process that determines the best ranking list of sections for maintenance based on several factors. In priority setting, difficult decisions are required to be made for selection of sections for maintenance. It is more important to repair a section with poor functional conditions which includes uncomfortable ride etc. or poor structural conditions i.e. sections those are in danger of becoming structurally unsound. It would seem therefore that any rational priority setting approach must consider the relative importance of functional and structural condition of the section. The maintenance priority index and pavement performance models tend to focus mainly on the pavement condition, traffic criteria etc. There is a need to develop the model which is suitably used with respect to limited budget provisions for maintenance of pavement. Linear programming is one of the most popular and widely used quantitative techniques. A linear programming model provides an efficient method for determining an optimal decision chosen from a large number of possible decisions. The optimum decision is one that meets a specified objective of management, subject to various constraints and restrictions. The objective is mainly minimization of maintenance cost of roads in industrial area. In order to determine the objective function for analysis of distress model it is necessary to fix the realistic data into a formulation. Each type of repair is to be quantified in a number of stretches by considering 1000 m as one stretch. A stretch considered under study is having 3750 m length. The quantity has to be put into an objective function for maximizing the number of repairs in a stretch related to quantity. The distress observed in this stretch are potholes, surface cracks, rutting and ravelling. The distress data is measured manually by observing each distress level on a stretch of 1000 m. The maintenance and rehabilitation measured that are followed currently are based on subjective judgments. Hence, there is a need to adopt a scientific approach in order to effectively use the limited resources. It is also necessary to determine the pavement performance and deterioration prediction relationship with more accurate and economic benefits of road networks with respect to vehicle operating cost. The infrastructure of road network should have best results expected from available funds. In this paper objective function for distress model is determined by linear programming and deterioration model considering overloading is discussed.

Keywords: budget, maintenance, deterioration, priority

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Authors: Ellis D. Cooper

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“Circularchy” is supposed to be an adjustable formal framework with enough expressive power to articulate biological theory about Earthly Life in the sense of multi-scale biological autonomy constrained by non-equilibrium thermodynamics. “Formal framework” means specifically a multi-sorted first-order-theorywithequality (for each sort). Philosophically, such a theory is one kind of “microlect,” which means a “way of speaking” (or, more generally, a “way of behaving”) for overtly expressing a “mental model” of some “referent.” Other kinds of microlect include “natural microlect,” “diagrammatic microlect,” and “behavioral microlect,” with examples such as “political theory,” “Euclidean geometry,” and “dance choreography,” respectively. These are all describable in terms of a vocabulary conforming to grammar. As aspects of human culture, they are possibly reminiscent of Ernst Cassirer’s idea of “symbolic form;” as vocabularies, they are akin to Richard Rorty’s idea of “final vocabulary” for expressing a mental model of one’s life. A formal microlect is presented by stipulating sorts, variables, calculations, predicates, and postulates. Calculations (a.k.a., “terms”) may be composed to form more complicated calculations; predicates (a.k.a., “relations”) may be logically combined to form more complicated predicates; and statements (a.k.a., “sentences”) are grammatically correct expressions which are true or false. Conclusions are statements derived using logical rules of deduction from postulates, other assumed statements, or previously derived conclusions. A circularchy is a formal microlect constituted by two or more sub-microlects, each with its distinct stipulations of sorts, variables, calculations, predicates, and postulates. Within a sub-microlect some postulates or conclusions are equations which are statements that declare equality of specified calculations. An equational bond between an equation in one sub-microlect and an equation in either the same sub-microlect or in another sub-microlect is a predicate that declares equality of symbols occurring in a side of one equation with symbols occurring in a side of the other equation. Briefly, a circularchy is a network of equational bonds between sub-microlects. A circularchy is solvable if there exist solutions for all equations that satisfy all equational bonds. If a circularchy is not solvable, then a challenge would be to discover the obstruction to solvability and then conjecture what adjustments might remove the obstruction. Adjustment means changes in stipulated ingredients (sorts, etc.) of sub-microlects, or changes in equational bonds between sub-microlects, or introduction of new sub-microlects and new equational bonds. A circularchy is modular insofar as each sub-microlect is a node in a network of equation bonds. Solvability of a circularchy may be conjectured. Efforts to prove solvability may be thwarted by a counter-example or may lead to the construction of a solution. An automated theorem-proof assistant would likely be necessary for investigating a substantial circularchy, such as one purported to represent Earthly Life. Such investigations (chains of statements) would be concurrent with and no substitute for simulations (chains of numbers).

Keywords: autonomy, first-order theory, mathematics, thermodynamics

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Authors: Alessandra N. Santos, Max P. Ferreira, Alexandra R. P. Silva, Agda A. R. de Oliveira, Marivalda M. Pereira

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The literature describes experiments, in which ceria nanoparticles in the bioactive glass significantly improve differentiation of stem cells into osteoblasts and increase production of collagen. It is not known whether this effect observed due to the presence of nanoceria can be also observed in the presence of cerium in the bioactive glass network. The effect of cerium into bioactive glasses using the sol–gel route is the focus of this work, with the goal to develop a material for tissue engineering with the potential to enhance osteogenesis. A bioactive glass composition based on 70% SiO2–30% CaO is produced with the addition of cerium. The analyses XRD, FTIR, SEM/EDS, BET/BJH, in vitro bioactivity test and the Cell viability assay were performed. The results show that cerium remains in the bioactive glass structure. The obtained material present in vitro bioactivity and promote the cell viability.

Keywords: bioactive glass, bioactivity, cerium salt, material characterization, sol-gel method

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Authors: Seung Ju Yeon, Seul Ki Min, Jun Sang Park, Yeo Seon Kwon, Hoo Cheol Lee, Hyun Jung Shim, Il-Doo Kim, Ja Kyeong Lee, Hwa Sung Shin

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In brain injury, depleting oxidative stress is the most effective way to reduce the brain infarct size. C-phycocyanin (C-Pc) is a well-known antioxidant protein that has neuroprotective effects obtained from green microalgae. Astrocyte is glial cell that supports the nerve cell such as neuron, which account for a large portion of the brain. In brain injury, such as ischemia and reperfusion, astrocyte has an important rule that overcomes the oxidative stress and protect from brain reactive oxygen species (ROS) injury. However little is known about how C-Pc regulates the anti-oxidants effects of astrocyte. In this study, when the C-Pc was treated in oxidized astrocyte, we confirmed that inflammatory factors Interleukin-6 and Interleukin-3 were increased and antioxidants enzyme, Superoxide dismutase (SOD) and catalase was upregulated, and neurotrophic factors, brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) was alleviated. Also, it was confirmed to reduce infarct size of the brain in ischemia and reperfusion because C-Pc has anti-oxidant effects in middle cerebral artery occlusion (MCAO) animal model. These results show that C-Pc can help astrocytes lead neuroprotective activities in the oxidative stressed environment of the brain. In summary, the C-PC protects astrocytes from oxidative stress and has anti-oxidative, anti-inflammatory, neurotrophic effects under ischemic situations.

Keywords: c-phycocyanin, astrocyte, reactive oxygen species, ischemia and reperfusion, neuroprotective effect

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Authors: Ayhan Eymirli, Sila N. Usta

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The aim of this study is the comparison of the cyclic fatigue resistance of EndoArt Gold (EAG, Inci Dental, Istanbul, Turkey), EndoArt Blue (EAB, Inci Dental, Istanbul, Turkey), ProTaper Universal (PTU, Dentsply Tulsa Dental Specialties), and ProTaper Gold (PTG, Dentsply Tulsa Dental Specialties) files at body temperature. Twelve instruments of each EAG, EAB, PTU, PTG file system were included in this study. All selected files were rotated in the artificial canals, which have a 60° angle and a 5-mm radius of curvature until fracture occurred. The time to fracture (Ttf) was measured in seconds by a chronometer in the control panel that presents in the cyclic fatigue testing device when a fracture was detected visually and/or audibly. The lengths of the fractured fragments (FL) were also measured with a digital microcaliper. The data of Ttf and FL were analyzed using Kruskal-Wallis, one-way ANOVA and post hoc Bonferroni tests at the 5% significance level. There was a statistically significant difference among the file systems (p < 0.05). EAB had the statistically highest fatigue resistance, and PTU had the statistically lowest fatigue resistance (p < 0.05). PTG system had a statistically higher FL means than EAB and PTU file systems (p < 0.05). EAB had the greatest cyclic fatigue resistance amongst the other file systems. It can be stated that heat treatments may be a factor that increases fatigue resistance.

Keywords: cyclic fatigue resistance, Endo art blue, Endo art gold, pro taper gold, pro taper universal

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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

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Authors: Park, Yoon Hong, Wang, Jung Kab, Choi Seong-Won, Kim, Hong Kyu

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Itaewon-Ro is a special place where the Seoul Metropolitan city designated as the fist are of tourism, specially with the commercial supremacy that foreigners may like. It is the place that grew with regional specialty. Study on the vitalization factors of commercialist were analyzed on consumer shop choice factor, Physical environment based on commercial supremacy vitalization, Functional side of the road and regional specialty. However, since Itaewon seemed to take great place in the cultural factor, Because of its regional specialty, Research was processed. This study is the analysis on the vitalization of Itaewon commercialist that looked for important factors with AHP analysis on consumers use as commercialist. Based on the field study and preceded study, top three factors were distinguished with physical factor, cultural factor, landscape factor, and thirteen detail contents were found. This study focused on the choice of the consumer and with a consumer-based questionnaire, we analyzed the importance of vitalization factors. Results of the research are shown in the following paragraphs. In the Itaewon commercial market, mostly women in the 20~30s were the main consumers for meeting and hopping. Vitalization category that the consumer thinks it most importantly was 'attraction', 'various businesses', and 'convenience of transportation'. 'Attraction that cannot be seen in other places', Which was chosen as the most important factor was judged that Itaewon holds cultural identity that is shown in the process of development, Instead of showing artificial and physical composition.

Keywords: commercialist, vitalization factor, regional specialty, cultural factor, AHP analysis

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Authors: Yan Huang

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Event-related potentials (ERPs) technique helps researchers to make continuous measures on the whole process of language comprehension, with an excellent temporal resolution at the level of milliseconds. The research on sentence processing has developed from the behavioral level to the neuropsychological level, which brings about a variety of sentence processing theories and models. However, the applicability of these models to L2 learners is still under debate. Therefore, the present study aims to investigate the neural mechanisms underlying English subjunctive mood processing by Chinese ESL learners. To this end, English subject clauses with subjunctive moods are used as the stimuli, all of which follow the same syntactic structure, “It is + adjective + that … + (should) do + …” Besides, in order to examine the role that language proficiency plays on L2 processing, this research deals with two groups of Chinese ESL learners (18 males and 22 females, mean age=21.68), namely, high proficiency group (Group H) and low proficiency group (Group L). Finally, the behavioral and neurophysiological data analysis reveals the following findings: 1) Syntax and semantics interact with each other on the SECOND phase (300-500ms) of sentence processing, which is partially in line with the Three-phase Sentence Model; 2) Language proficiency does affect L2 processing. Specifically, for Group H, it is the syntactic processing that plays the dominant role in sentence processing while for Group L, semantic processing also affects the syntactic parsing during the THIRD phase of sentence processing (500-700ms). Besides, Group H, compared to Group L, demonstrates a richer native-like ERPs pattern, which further demonstrates the role of language proficiency in L2 processing. Based on the research findings, this paper also provides some enlightenment for the L2 pedagogy as well as the L2 proficiency assessment.

Keywords: Chinese ESL learners, English subjunctive mood, ERPs, L2 processing

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Authors: Jaime E. Fernandez, Pablo J. Valverde

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This paper presents a methodological approach that aims to contrast/validate theoretical results from a corruption network game through probabilistic analysis of simulated microdata using Bayesian Networks (BNs). The research develops a public corruption model in a game theory framework. Theoretical results suggest a series of 'optimal settings' of model's exogenous parameters that boost the emergence of corruption. The paper contrasts these outcomes with probabilistic inference results based on BNs adjusted over simulated microdata. Principal findings indicate that probabilistic reasoning based on BNs significantly improves parameter specification and causal analysis in a public corruption game.

Keywords: Bayesian networks, probabilistic reasoning, public corruption, theoretical games

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Authors: Salma Krafessi

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The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.

Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models

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Authors: Suzanne Ahmed

Abstract:

Nanomotors, also commonly referred to as nanorobotics or nanomachines, have garnered considerable research attention due to their numerous potential applications in biomedicine, including drug delivery and microsurgery. Nanomotors typically consist of inorganic or polymeric particles that are powered to undergo motion. These artificial, man-made nanoscale motors operate in the low Reynolds number regime and typically have no moving parts. Several methods have been developed to actuate the motion of nanomotors including magnetic fields, electrical fields, electromagnetic waves, and chemical fuel. Since their introduction in 2012, ultrasonically powered nanomotors have been explored in biocompatible fluids and even within living cells. Due to the common use of ultrasound within the biomedical community for both imaging and therapeutics, the introduction of ultrasonically propelled nanomotors holds significant potential for biomedical applications. In this work, metallic nanomotors are electrochemically plated within porous anodic alumina templates to have a diameter of 300 nm and a length that is 2-4 µm. Nanomotors are placed within an acoustic chamber capable of producing bulk acoustic waves in the ultrasonic range. The motion of nanomotors within biomimetic confines is explored. The control over nanomotor motion is exerted by virtue of the properties of the acoustic signal within these biomimetic confines to control speed, modes of motion and directionality of motion. To expand the range of control over nanorod motion within biomimetic confines, external forces from biocompatible magnetic fields, are exerted onto the acoustically propelled nanomotors.

Keywords: nanomotors, nanomachines, nanorobots, ultrasound

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Authors: Jayant Kumar, Aarcha Jayachandran Sasikala, Barry Adrian Shepherd

Abstract:

Public Distribution System is a flagship welfare programme of the Government of India with both historical and political significance. Targeted at lower sections of society,it is one of the largest supply chain networks in the world. There has been several studies by academics and planning commission about the effectiveness of the system. Our study focuses on applying predictive analytics to aid the central body to keep track of the problem of breach of service level agreement between the two echelons of food supply chain. Each shop breach is leading to a potential additional inventory carrying cost. Thus, through this study, we aim to show that aided with such analytics, the network can be made more cost effective. The methods we illustrate in this study are applicable to other commercial supply chains as well.

Keywords: PDS, analytics, cost effectiveness, Karnataka, inventory cost, service level JEL classification: C53

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Authors: Semih Demir, Anil Celebi

Abstract:

Circuit switched networks widely used until the end of the 20^th century have been transformed into packages switched networks. Time Division Multiplexing over Internet Protocol (TDMoIP) is a system that enables Time Division Multiplexing (TDM) traffic to be carried over packet switched networks (PSN). In TDMoIP systems, devices that send TDM data to the PSN and receive it from the network must operate with the same clock frequency. In this study, it was aimed to implement clock synchronization process in Field Programmable Gate Array (FPGA) chips using time information attached to the packages received from PSN. The designed hardware is verified using the datasets obtained for the different carrier types and comparing the results with the software model. Field tests are also performed by using the real time TDMoIP system.

Keywords: clock recovery on TDMoIP, FPGA, MATLAB reference model, clock synchronization

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

Abstract:

The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: Anna Daskalaki, Andreas Ashikalis

Abstract:

This is a conceptual project that suggests an alternative type of summer camp in the forest of Rouvas in the island of Crete. Taking into account some feasts that are organised by the locals or mountaineering clubs near the church of St. John, we created a network of lightweight timber structures that serve the needs of the visitor. These structures are transformable and satisfy the need for rest, food, and sleep – this means a seat, a table and a tent are embodied in each structure. These structures blend in with the environment as they are being installed according to the following parameters: (a) the local relief, (b) the clusters of trees, and (c) the existing paths. Each timber structure could be considered as a module that could be totally independent or part of a bigger construction. The design showcases the advantages of a timber structure as it can be quite adaptive to the needs of the project, but also it is a sustainable and environmentally friendly material that can be recycled. Finally, it is important to note that the basic goal of this project is the minimum alteration of the natural environment.

Keywords: lightweight structures, timber, transformable, tent

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Authors: Antonio J. Melendez-Martinez

Abstract:

Beyond their role as natural colorants, some carotenoids are provitamins A and may be involved in health-promoting biological actions and contribute to reducing the risk of developing non-communicable diseases, including several types of cancer, cardiovascular disease, eye conditions, skin disorders or metabolic disorders. Given the versatility of carotenoids, the COST-funded European network to advance carotenoid research and applications in agro-food and health (EUROCAROTEN) is aimed at promoting health through the diet and increasing well-being by means. Stakeholders from 38 countries participate in this network, and one of its main objectives is to promote research on little-studied carotenoids. In this contribution, recent advances of our research group and collaborators in the study of two such understudied carotenoids, namely phytoene and phytofluene, the colorless carotenoids, are outlined. The study of these carotenoids is important as they have been largely neglected despite they are present in our diets, fluids, and tissues, and evidence is accumulating that they may be involved in health-promoting actions. More specifically, studies on their levels in diverse tomato and orange varieties were carried out as well as on their potential bioavailability from different dietary sources. Furthermore, the potential effect of these carotenoids on an animal model subjected to oxidative stress was evaluated. The tomatoes were grown in research greenhouses, and some of them were subjected to regulated deficit irrigation, a sustainable agronomic practice. The citrus samples were obtained from an experimental field. The levels of carotenoids were assessed using HPLC according to routine methodologies followed in our lab. Regarding the potential bioavailability (bioaccessibility) studies, different products containing colorless carotenoids, like fruits, juices, were subjected to simulated in vitro digestions, and their incorporation into mixed micelles was assessed. The effect of the carotenoids on oxidative stress was evaluated on the Caenorhabditis elegans model. For that purpose, the worms were subjected to oxidative stress by means of a hydrogen peroxide challenge. In relation to the presence of colorless carotenoids in tomatoes and orange varieties, it was observed that they are widespread in such products and that there are mutants with very high quantities of them, for instance, the Cara Cara or Pinalate mutant oranges. The studies on their bioaccessibility revealed that, in general, phytoene and phytofluene are more bioaccessible than other common dietary carotenoids, probably due to their distinctive chemical structure. About the in vivo antioxidant capacity of phytoene and phytofluene, it was observed that they both exerted antioxidant effects at certain doses. In conclusion, evidence on the importance of phytoene and phytofluene as dietary easily bioavailable and antioxidant carotenoids has been obtained in recent studies from our group, which can be important shortly to innovate in health-promotion through the development of functional foods and related products.

Keywords: carotenoids, health, functional foods, nutrition, phytoene, phytofluene

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