Search results for: Markov fields

Authors: Daniel N. L. Alves, Marcelo C. Rodrigues, Jose G. de Almeida

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The search for structural efficiency in mechanical systems has been strongly exerted with aim of economic optimization and structural safety. As soon, to understand the response of materials when submitted to adverse conditions is essential to design a safety project. This work investigates the presence of cracks in dissimilar welded joints (DWJ). Its fracture toughness responses depend upon the heterogeneity present in these joints. Thus, this work aim analyzing the behavior of the crack tip zone located in a buttery dissimilar welded joint (ASTM A-36, Inconel, and AISI 8630 M) used in the union of pipes present in the offshore oil production lines. The crack was placed 1 mm from fusion line (FL) Inconel-AISI 8630 M toward the AISI 8630 M. Finite Element Method (FEM) was used to analyze stress and strain fields generated during the loading imposed on the specimen. It was possible observing critical stress area by the numerical tool as well as a preferential plastic flow was also observed in the sample of dissimilar welded joint, which can be considered a harbinger of the crack growth path. The results obtained through numerical analysis showed a convergent behavior in relation to the plastic flow, qualitatively and quantitatively, in agreement with previous performed.

Keywords: crack, dissimilar welded joint, numerical analysis, strain field, the stress field

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Authors: Ismael Zamora, Elisabeth Ortega, Tatiana Radchenko, Guillem Plasencia

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The structure elucidation based on Mass Spectra (MS) data of unknown substances is an unresolved problem that affects many different fields of application. The recent overview of software available for structure elucidation of small molecules has shown the demand for efficient computational tool that will be able to perform structure elucidation of unknown small molecules and peptides. We developed an algorithm for De-Novo fragment analysis based on MS data that proposes a set of scored and ranked structures that are compatible with the MS and MSMS spectra. Several different algorithms were developed depending on the initial set of fragments and the structure building processes. Also, in all cases, several scores for the final molecule ranking were computed. They were validated with small and middle databases (DB) with the eleven test set compounds. Similar results were obtained from any of the databases that contained the fragments of the expected compound. We presented an algorithm. Or De-Novo fragment analysis based on only mass spectrometry (MS) data only that proposed a set of scored/ranked structures that was validated on different types of databases and showed good results as proof of concept. Moreover, the solutions proposed by Mass Spectrometry were submitted to the prediction of NMR spectra in order to elucidate which of the proposed structures was compatible with the NMR spectra collected.

Keywords: De Novo, structure elucidation, mass spectrometry, NMR

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Authors: Subhra Prosun Paul, Shruti Aggarwal

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Now a days Routing Protocol in Wireless Sensor Network has become a promising technique in the different fields of the latest computer technology. Routing in Wireless Sensor Network is a demanding task due to the different design issues of all sensor nodes. Network architecture, no of nodes, traffic of routing, the capacity of each sensor node, network consistency, service value are the important factor for the design and analysis of Routing Protocol in Wireless Sensor Network. Additionally, internal energy, the distance between nodes, the load of sensor nodes play a significant role in the efficient routing protocol. In this paper, our intention is to analyze the research trends in different routing protocols of Wireless Sensor Network in terms of different parameters. In order to explain the research trends on Routing Protocol in Wireless Sensor Network, different data related to this research topic are analyzed with the help of Web of Science and Scopus databases. The data analysis is performed from global perspective-taking different parameters like author, source, document, country, organization, keyword, year, and a number of the publication. Different types of experiments are also performed, which help us to evaluate the recent research tendency in the Routing Protocol of Wireless Sensor Network. In order to do this, we have used Web of Science and Scopus databases separately for data analysis. We have observed that there has been a tremendous development of research on this topic in the last few years as it has become a very popular topic day by day.

Keywords: analysis, routing protocol, research trends, wireless sensor network

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Authors: Souhila Terfi, Fatma Hassaine-Sadi

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In the present study, wet digestion with HCl and HNO3 mixture was used to extract the heavy metals (copper (Cu), chromium (Cr), zinc (Zn), lead (Pb) and cadmium (Cd)) from the leaves, the stems and the roots of Malva sylvestris L., which were subsequently analyzed by AAS. The samples (soil and parts of species) were collected from different sites: the industrial area (IA) (Rouiba), the rubbish dump area (RDA) (Boudouaou), the residential area (RA) with large open fields and construction activities (Blida), the Montaigne area (MA) (Chrea) and the high plateau area (HPA) (Berouaguia). The study showed differences in metal concentrations according to the analysed parts and the different sampling locations. In the contaminated site of the industrial area (IA), high content of the toxic heavy metals (Cd: 3.18 µg/g DW and Pb: 34.48 µg/g DW) were found in the leaves of Malva sylvestris L. This finding suggests that the consumers of this species could be exposed to a risk associated with this higher level of these toxic metals. It was found that Malva sylvestris L. is rich by Zn and Cu in some sites, which are considered to be the essential elements for the human health. The obtained results with the control site (Montaigne area) suggest that this species can be applicable in both the health and food, feasible alternatives as medicinal plant without any risk.

Keywords: Malva sylvestris L., toxic heavy metal, medicinal plant, impact on human health

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Authors: Setenay Nil Doğan, Ece Oztan

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Research and development (R&D) as a term denotes the innovative studies conducted systematically to increase knowledge and its practices. As R&D intensity of Turkey (0,84%) is quite below the EU average intensity score, it has displayed a continuous increase since the 2000s. Also, the development of human capital in R&D has been one of the basic aims of National Strategy of Science, Technology, and Innovation, and National Innovation System 2023 of Turkey. R&D is considered to one of the fields in which the gender gap is wide. The reflections of the analogy of leaky pipeline, a term used for vertical differentiation in academy can also be observed in those scientific activities related with the private sector. In the private sector, the gender gap becomes wider: the percentage of female researchers in the universities (41%) decreases to 24% in the private sector. Though half of the undergraduates and gradutes are female in Turkey, a widening gender gap is observed in terms of employment in R&D. Given this background, this paper will focus on gendered dynamics of careers in R&D through the interviews conducted with 25 female and 25 male employees, working in a university technopark and some of the large RD centers in Turkey working in several sectors such as electronics, automotive etc. Focusing on some aspects of gender differences in terms of career experiences in R&D and innovation, mobility, participation to the projects, patents and inclusion to other innovatory activities, home-work balance, it aims to explore the relationships between science, technology, innovation and gender.

Keywords: gender, innovation, R&D, science, technology

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Authors: Mario Pérez-Won, Anais Palma-Acevedo, Luis González-Cavieres, Roberto Lemus-Mondaca, Gipsy Tabilo-Munizaga

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The Chilean abalone (Concholepas Concholepas) is a gastropod mollusk; it has a high commercial value due to the qualities of its meat, especially hardness, as a critical acceptance parameter. However, its main problem is its short shelf-life which is usually extended using traditional technologies with high energy consumption. Therefore, applying different technologies for the pre-treatment and drying process is necessary. In this research, pulsed electric field (PEF) was used as a pre-treatment for vacuum microwave drying (VMD), freeze-drying (FD), and hot-air drying (HAD). Drying conditions and characteristics were set according to previous experiments. The Drying samples were analyzed in terms of physical quality (color, texture, microstructure, and rehydration capacity), protein quality (degree of hydrolysis and computer protein efficiency ratio), and energy parameters. Regarding quality, the treatment that obtained lower harness was PEF+FD (195 N ± 10), the lowest change of color was for treatment PEF+VMD (ΔE: 17 ± 1.5), and the best rehydration capacity was for treatment PEF+VMD (1.2 h for equilibrium). For protein quality, the highest Computer-Protein Efficiency Ratio was the sample 2.0 kV/ cm of PEF (index of 4.18 ± 0.26 at the end of the digestion). Moreover, about energetic consumption, results show that VMD decreases the drying process by 97% whether PEF was used or not. Consequently, it is possible to conclude that using PEF as a pre-treatment for VMD and FD treatments has advantages that must be used following the consumer’s needs or preferences.

Keywords: chilean abalone, freeze-drying, proteins, pulsed electric fields

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Authors: D. Shakirah Shukor, A. Aminudin, Hashim U. A., Waziralilah N. Fathiah, T. Vikneshvaran

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The interior noise control is essential to be explored due to the interior acoustic analysis is significant in the systems such as automobiles, aircraft, air-handling system and diesel engine exhausts system. In this research, experimental work was undertaken for canceling an active noise in the rectangular enclosure. The rectangular enclosure was fabricated with multiple speakers and microphones inside the enclosure. A software program using digital signal processing is implemented to evaluate the proposed method. Experimental work was conducted to obtain the acoustic behavior and characteristics of the rectangular enclosure and noise cancellation based on active noise control in low-frequency range. Noise is generated by using multispeaker inside the enclosure and microphones are used for noise measurements. The technique for noise cancellation relies on the principle of destructive interference between two sound fields in the rectangular enclosure. One field is generated by the original or primary sound source, the other by a secondary sound source set up to interfere with, and cancel, that unwanted primary sound. At the end of this research, the result of output noise before and after cancellation are presented and discussed. On the basis of the findings presented in this research, an active noise cancellation in the rectangular enclosure is worth exploring in order to improve the noise control technologies.

Keywords: active noise control, digital signal processing, noise cancellation, rectangular enclosure

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Authors: Seyedehfatemeh Golrizgashti, Seyedali Dalil

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The goal of this paper is proposing a supply chain value dashboard in home appliance manufacturing firms to create more value for all stakeholders via balanced scorecard approach. Balanced scorecard is an effective approach that managers have used to evaluate supply chain performance in many fields but there is a lack of enough attention to all supply chain stakeholders, improving value creation and, defining correlation between value indicators and performance measuring quantitatively. In this research the key stakeholders in home appliance supply chain, value indicators with respect to create more value for stakeholders and the most important metrics to evaluate supply chain value performance based on balanced scorecard approach have been selected via literature review. The most important indicators based on expert’s judgment acquired by in survey focused on creating more value for. Structural equation modelling has been used to disclose relations between value indicators and balanced scorecard metrics. The important result of this research is identifying effective value dashboard to create more value for all stakeholders in the supply chain via balanced scorecard approach and based on an empirical study covering ten home appliance manufacturing firms in Iran. Home appliance manufacturing firms can increase their stakeholder's satisfaction by using this value dashboard.

Keywords: supply chain management, balanced scorecard, value, structural modeling, stakeholders

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Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

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Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

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Authors: Manjunatha Bangeppagari, Lee Sang Joon

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Recently, graphene-related nanomaterials are receiving fast-increasing attention with augmented applications in various fields. Especially, graphene-related materials have been widely applied to the biomedical field in the past years. In the present study, we evaluated the adverse effects of pristine graphene (pG) in zebrafish (Danio rerio) embryos in various aspects, such as mortality rate, heart rate, hatching rate, cardiotoxicity, cardiovascular defect, cardiac looping, apoptosis, and globin expression. For various trace concentrations of pG (1, 5, 10, 15, 20, 25, 30, 35, 40, 45, and 50 μg/L), early life-stage parameters were observed at 24, 48, 72, and 96 hpf. As a result, pG induces significant developmental defects including yolk sac edema, pericardial edema, embryonic mortality, delayed hatching, heartbeat, several morphological defects, pericardial toxicity, and bradycardia. Moreover, the exposure to pG was found to be a potential risk factor to the cardiovascular system of zebrafish embryos. However, further study on their properties which vary according to production methods and surface functionalization is essentially required. In addition, the possible risks of pG flakes to aquatic animals, and public health should be evaluated before releasing them to the surrounding environment.

Keywords: apoptosis, cardiovascular toxicity, globin expression, pristine graphene, zebrafish embryos

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Authors: Daniel Ngusha Chile

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The rapid advancement of communication and information technology has significantly transformed how organisations engage in strategic communication. As the world becomes increasingly interconnected, leveraging the convergence of these fields is essential for driving impact and fostering innovation. This study examines the integration of communication, information technology, and strategic communication, exploring how their synergy enhances message delivery, audience engagement, and organisational effectiveness. Using a mixed-methods approach, the research employs surveys and case studies to investigate the adoption of digital tools and platforms in strategic communication practices across various industries. Quantitative data were analysed to identify trends in technology use, while qualitative insights were drawn from interviews with communication professionals to understand challenges and best practices. The findings reveal that organisations which strategically integrate communication and information technology experience improved message clarity, wider audience reach, and stronger brand positioning. However, the study also highlights barriers such as gaps in technological literacy and ethical concerns regarding data privacy. In conclusion, the convergence of communication, information technology, and strategic communication is pivotal in shaping the future of organisational success. Embracing these advancements enables more effective engagement, adaptability, and resilience in a rapidly evolving digital landscape.

Keywords: communication, information technology, strategic communication, digital transformation

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Authors: Karima Tayaa, Amina Bouaziz

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The rapid expansion in the scientific fields and the growth of communication technology increased the use of English as international language in the world. Hence, over the past few decades, many researchers have been emphasizing on how the teaching and learning of English as a foreign or as an additional language can best help students to perform successfully. English for specific purpose is today quite literally regarded as the most global language discipline which existed practically in every country in the world. ESP (English for Specific Purposes) involves teaching and learning the specific skills and language needed by particular learners for a particular purpose. The P in ESP is always a professional purpose which is a set of skills that learners currently need in their work or will need in their professional careers. It has had an early origin since 1960’s and has grown to become one of the most prominent of English language teaching today. Moreover, ESP learners are usually adults who have some quittances with English and learn the language so as to communicate and perform particular profession. Related activities are based on specific purposes and needs. They are integrated into subject matter area important to the learners. Unlike general English which focuses on teaching general language courses and all four language skills are equally stressed, ESP and practically needs analysis determine which language skills are the most needed by the learners and syllabus designed accordingly. This paper looked into the origin, characteristics, development of ESP, the difference between ESP and general English. Finally, the paper critically reviews the role of needs analysis in the ESP.

Keywords: English language teaching, English for general purposes, English for specific purposes, needs analysis

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Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

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Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

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Authors: M. Bevilacqua, F. E. Ciarapica, G. Marcucci

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Supply Chain Resilience has been broadly studied during the last decade, focusing the research on many aspects of Supply Chain performance. Consequently, different definitions of Supply Chain Resilience have been developed by the research community, drawing inspiration also from other fields of study such as ecology, sociology, psychology, economy et al. This way, the definitions so far developed in the extant literature are therefore very heterogeneous, and many authors have pointed out a lack of consensus in this field of analysis. The aim of this research is to find common points between these definitions, through the development of a framework of study: the Resilience Triangle. The Resilience Triangle is a tool developed in the field of civil engineering, with the objective of modeling the loss of resilience of a given structure during and after the occurrence of a disruption such as an earthquake. The Resilience Triangle is a simple yet powerful tool: in our opinion, it can summarize all the features that authors have captured in the Supply Chain Resilience definitions over the years. This research intends to recapitulate within this framework all these heterogeneities in Supply Chain Resilience research. After collecting a various number of Supply Chain Resilience definitions present in the extant literature, the methodology approach provides a taxonomy step with the scope of collecting and analyzing all the data gathered. The next step provides the comparison of the data obtained with the plotting of a disruption profile, in order to contextualize the Resilience Triangle in the Supply Chain context. The tool and the results developed in this research will allow to lay the foundation for future Supply Chain Resilience modeling and measurement work.

Keywords: supply chain resilience, resilience definition, supply chain resilience triangle

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Authors: Rochelle Elva

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Faculty in Higher Education today are faced with the challenge of convincing their students of the importance of learning and mastery of skills. This is because most students often have a single motivation -to get high grades. If it appears that this goal will not be met, they lose their motivation, and their academic efforts wane. This is true even for students in the competitive fields of STEM, including Computer Science majors. As educators, we have to understand our students and leverage what motivates them to achieve our learning outcomes. This paper presents a case study that utilizes cognitive psychology’s Expectancy Value Theory and Motivation Theory to investigate the effect of sustained expectancy for success on students’ learning outcomes. In our case study, we explore how students’ motivation and persistence in their academic efforts are impacted by providing them with an unexpected possible path to success that continues to the end of the semester. The approach was tested in an undergraduate computer science course with n = 56. The results of the study indicate that when presented with the real possibility of success, despite existing low grades, both low and high-scoring students persisted in their efforts to improve their performance. Their final grades were, on average, one place higher on the +/-letter grade scale, with some students scoring as high as three places above their predicted grade.

Keywords: expectancy for success and persistence, motivation and performance, computer science education, motivation and performance in computer science

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: Avram Irina, Coiciu Eugenia-Mihaela, Popovici Mara-Georgiana, Mitu Iani Octavian

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ELI-NP stands as a cutting-edge facility globally, hosting unique radiological setups. It conducts experiments leveraging high-power lasers capable of producing extremely brief 10 PW pulses on two fronts. Moreover, it houses an exceptional gamma beam system with distinctive spectral characteristics. The facility hosts various experiments across designated experimental areas, encompassing ultra-short high-power laser tests, high-intensity gamma beam trials, and combined experiments utilizing both setups. The facility hosts a dosimetry laboratory, which recently obtained accreditation, where the radiation safety group employs a host of different types of detectors for monitoring the personnel, environment, and public exposure to ionizing radiation generated in experiments performed. ELI-NP's design was shaped by radiological protection assessments conducted through Monte Carlo simulations. The poster exemplifies an assessment conducted using the FLUKA code in an experimental area where a high-power laser system is implemented, and the future diagnostic system for variable energy gamma beams will soon be operational.

Keywords: radiation protection, Monte Carlo simulation, FLUKA, dosimetry

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Authors: Fatemeh Noughani, Seyd Mehdi Sadat

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Medical tourism or travel therapy is travelling from one country to another to be under medical treatment, utilizing the health factors of natural sector like mineral water springs and so on. From 1990s medical tourism around the world developed and grew because of different factors like globalization and free trade in the fields of health services, changes in exchange rates in the world economy (which caused the desirability of Asian countries as a medical tourist attraction) in a way that currently there is a close competition in this field among famous countries in medical services to make them find a desirable place in medical tourism market of the world as a complicated and growing industry in a short time. Perhaps tourism is an attractive industry and a good support for the economy of Iran, if we try to merge oil earnings and tourism industry it would be better and more constructive than putting them in front of each other. Moving from oil toward tourism economy especially medical tourism, must be one of the prospects of Iran's government for the oil industry to provide a few percent of the yearly earnings of the country. Among the achievements in medical tourism we can name the prevention of brain drain to other countries and an increase in employment rate for healthcare staff, increase in foreign exchange earnings of the country because of the tourists' staying and followed by increasing the quality of life and cultural transmission as well as empowering the medical human resources.

Keywords: developing countries, health tourism, quality of life, cultural transmission

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Authors: A. D. Tayal

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The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.

Keywords: data, innovation, renewable, solar

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Authors: Sérgio J. Teixeira, João J. Ferreira

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Tourism frequently gets identified as one of the sectors with the greatest potential for expansion on a global scale and hence conveying the importance of attempting to better understand the regional factors of competitiveness prevailing in this sector. This study’s objective essentially strives to provide a mapping of the scientific publications and the intellectual knowledge therein contained while conveying past research trends and identifying potential future lines of research in the fields of regional competitiveness and tourism innovation. This correspondingly deploys a systematic review of the literature in keeping with the bibliometric approach based upon VOSviewer software, with a particular focus on drafting maps for visualising the underlying intellectual structure. This type of analysis encapsulates the number of articles published and their annual number of citations for the period between 1900 and 2016 as registered by the Web of Science database. The results demonstrate how the intellectual structure on regional competitiveness divides essentially into three major categories: regional competitiveness, tourism innovation, and tourism clusters. Thus, the main contribution of this study arises out of identifying the main research trends in this field and the respective shortcomings and specific needs for future scientific research in the field of regional competitiveness and innovation in tourism.

Keywords: regional competitiveness, tourism cluster, bibliometric studies, tourism innovation, systematic review

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Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

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Authors: Li-Ju Chen, Hsiang-Lin Chan, Hsin-Yi Kathy Cheng, Hui-Ju Chen

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Stereotype behavior is one of the maladaptive syndromes of the individuals with autism. Most of the previous researches focused on the stereotype behavior with stimulating type, while less on the stereotype behavior about cognition (This research names it cognitive stereotype behavior; CSB). This research explored CSB and the rationality to explain CSB with imprinting phenomenon. After excluding the samples without CSB described, the data that came from 271 individuals with autism were recruited and analyzed with quantitative and qualitative analyses. This research discovers that : (1) Most of the individuals with autism originally came out CSB at 3 years old and more than a half of them appeared before 4 years old; The average age which firstly came out CSB was 6.10 years old, the average time insisting or ossifying CSB was 31.71 minutes each time and the average longest time which they last was 358.35 minutes (5.97 hours). (2) CSB demonstrates various aspects, this research classified them into 4 fields with 26 categories. They were categorized into sudden CSB or habitual CSB by imprinting performance. (3) Most of the autism commented that their CSBs were not necessary but they could not control them well. One-third of them appeared CSB suddenly and the first occurrence accompanied a strong emotional or behavioral response. (4) Whether respondent is the person with autism himself/herself or not was the critical element: on the awareness of the severity degree, disturbance degree, and the emotional /behavioral intensity at the first-time CSB happened. This study concludes imprinting could reasonably explain the phenomenon CSB forms. There are implications leading the individuals with autism and their family to develop coping strategies to promote individuals with autism having a better learning accomplishment and life quality in their future.

Keywords: autism, cognitive stereotype behavior, constructivism, imprinting, stereotype

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Authors: Jayanth C., Anirudh Sai Yetikuri, Kavitha S. N.

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This paper explores the development and application of computer vision and machine learning techniques for real-time pose detection, facial recognition, and number plate extraction. Utilizing MediaPipe for pose estimation, the research presents methods for detecting hand raises and ducking postures through real-time video analysis. Complementarily, facial recognition is employed to compare and verify individual identities using the face recognition library. Additionally, the paper demonstrates a robust approach for extracting and storing vehicle number plates from images, integrating Optical Character Recognition (OCR) with a database management system. The study highlights the effectiveness and versatility of these technologies in practical scenarios, including security and surveillance applications. The findings underscore the potential of combining computer vision techniques to address diverse challenges and enhance automated systems for both individual and vehicular identification. This research contributes to the fields of computer vision and machine learning by providing scalable solutions and demonstrating their applicability in real-world contexts.

Keywords: computer vision, pose detection, facial recognition, number plate extraction, machine learning, real-time analysis, OCR, database management

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Authors: Reda Abdel-Aziz

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Agricultural activities in Egypt generate annually around 35 million tons of waste. Composting is one of the most promising technologies to turnover waste in a more economical way, for many centuries. Composting has been used as a mean of recycling organic matter back into the soil to improve soil structure and fertility. Field experiments were conducted in two governorates, Giza and Al-Monofia, to find out the effect of compost with different rates of chemical fertilizers on growth and yield of corn (Zea mays L.) during two constitutive seasons of 2012 and 2013. The experiment, laid out in a randomized complete block design (RCBD), was carried out on five farmers’ fields in each governorate. The treatments were: unfertilized control, full dose of NPK (120, 30, and 50 kg/acre, respectively), compost at rate of 20 ton/acre, compost at rate of 10 ton/acre + 25% of chemical fertilizer, compost at rate of 10 ton/acre + 50% of chemical fertilizer and compost at rate of 10 ton/acre + 75% of chemical fertilizer. Results revealed a superiority of the treatment of compost at rate of 10 ton/acre + 50% of NPK that caused significant improvement in growth, yield and nutrient uptakes of corn in the two governorates during the two constitutive seasons. Results showed that agricultural waste could be composted into value added soil amendment to enhance efficiency of chemical fertilizer. Composting of agricultural waste could also reduce the chemical fertilizers potential hazard to the environment.

Keywords: agricultural waste, compost, chemical fertilizers, corn production, environment

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Authors: Noa Shriki, Atara Shriki

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Lifelong learning is considered as essential for teacher's professional development, which in turn has implications for the improvement of the entire education system. In recent years, many programs designed to support teachers' professional development are criticized for not achieving their goal. A variety of reasons have been proposed for the purpose of explaining the causes of the ineffectiveness of such programs. In this study, we put to test the possibility that teachers do not change as a result of their participation in professional programs due to a gap between the contents and approaches included in them and teacher's beliefs about teaching and learning. Eighteen elementary school mathematics teachers participated in the study. These teachers were involved in collaborating with their students in inquiring mathematical ideas, while implementing action research. Employing educational theories, the results indicated that this experience had a positive effect on teacher's professional development. In particular, there was an evident change in their beliefs regarding their role as mathematics teachers. However, while employing a different perspective for analyzing the data, the lens of Kurt Lewin's theory of re-education, we realized that this change of beliefs must be questioned. Therefore, it is suggested that analysis of educational processes should be carried out not only through common educational theories, but also on the basis of social and organizational theories. It is assumed that both the field of education and the fields of social studies and organizational consulting will benefit from the multifocal viewpoint

Keywords: educational theories, professional development, re-education, teachers' beliefs

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

Abstract:

Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: Li-Jun Zheng

Abstract:

The use of drums as an accompanying instrument is a common phenomenon in traditional Chinese folk rituals and musical culture. Especially, some folk rituals construct ritual-related sounds and give them ritual-specific symbolic and meaningful systems through the combination and use of multiple percussion instruments. The Yue drum(岳鼓), an asymmetrically shaped thin waist drum, is currently used in Han Chinese Shigong（师公）rituals in Guangxi, China, and is an important ritual instrument in Shigong rituals. This paper examines the use of the Yue drum and other percussion instruments in Han Chinese Shigong rituals in Guangxi, China, and shows the current status of combining instrumental accompaniment forms with human voices in Shigong rituals. Through further analysis of the musical and dance forms of Han Chinese Shigong rituals, this paper shows how Han Chinese Shigong ritual performers construct the ritual field through "sound-human-dance" and further explains the relationship between the existing and fictitious performance fields in the rituals. In addition, this paper demonstrates the relationship between Han Chinese Shigong rituals and the religious beliefs they involve, such as Taoism and Buddhism. And it further explores how performers in Han Chinese Shigong rituals use Yue drums for the dual purpose of "entertaining the gods" and "entertaining the people".

Keywords: sound research, the Han Chinese Shigong ritual, the thin waist drum, folk beliefs, ritual music

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Authors: Anita Sadat Sadati Rostami, Reza Almasi Ghaleh

Abstract:

Surface electromyography (sEMG) offers important insights into muscle activation and has applications in fields including rehabilitation and human-computer interaction. The purpose of this work is to predict the degree of activation of two joints in the index finger using an LSTM-Transformer architecture trained on sEMG data from the Ninapro DB8 dataset. We apply advanced preprocessing techniques, such as multi-band filtering and customizable rectification methods, to enhance the encoding of sEMG data into features that are beneficial for regression tasks. The processed data is converted into spike patterns and simulated using Leaky Integrate-and-Fire (LIF) neuron models, allowing for neuromorphic-inspired processing. Our findings demonstrate that adjusting filtering parameters and neuron dynamics and employing the LSTM-Transformer model improves joint angle prediction performance. This study contributes to the ongoing development of deep learning frameworks for sEMG analysis, which could lead to improvements in motor control systems.

Keywords: surface electromyography, LSTM-transformer, spiking neural networks, hand kinematics, leaky integrate-and-fire neuron, band-pass filtering, muscle activity decoding

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Authors: Xiao Zhang, Wensheng Xiao, Junguo Cui, Hongmin Wang

Abstract:

Submersible permanent magnet linear synchronous motors (SPMLSMs) are electromagnetic devices, which can directly drive plunger pump to obtain the crude oil. Those motors have been gradually applied in oil fields due to high thrust force density and high efficiency. Since the force performance closely depends on the concrete structural parameters, the seven different structural parameters are investigated in detail. This paper presents an optimum design of an SPMLSM to minimize the detent force and maximize the thrust by using design of experiment (DOE) and genetic algorithm (GA). The three significant structural parameters (air-gap length, slot width, pole-arc coefficient) are separately screened using 27 1/16 fractional factorial design (FFD) to investigate the significant effect of seven parameters used in this research on the force performance. Response surface methodology (RSM) is well adapted to make analytical model of thrust and detent force with constraints of corresponding significant parameters and enable objective function to be easily created, respectively. GA is performed as a searching tool to search for the Pareto-optimal solutions. By finite element analysis, the proposed PMLSM shows merits in improving thrust and reducing the detent force dramatically.

Keywords: optimization, force performance, design of experiment (DOE), genetic algorithm (GA)

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Authors: Violina R. Angelova, Radka V. Ivanova, Givko M. Todorov, Krasimir I. Ivanov

Abstract:

A field study was conducted to evaluate the efficacy of Salvia sclarea L. for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The content of heavy metals in different parts of Salvia sclarea L. (roots, stems, leaves and inflorescences) was determined by ICP. The essential oil of the Salvia sclarea L. was obtained by steam distillation in laboratory conditions and was analyzed for heavy metals and its chemical composition was determined. Salvia sclarea L. is a plant which is tolerant to heavy metals and can be grown on contaminated soils. Based on the obtained results and using the most common criteria, Salvia sclarea L. can be classified as Pb hyperaccumulator and Cd and Zn accumulators, therefore, this plant has suitable potential for the phytoremediation of heavy metal contaminated soils. Favorable is also the fact that heavy metals do not influence the development of the Salvia sclarea L., as well as on the quality and quantity of the essential oil. For clary sage oil obtained from the processing of clary sage grown on highly contaminated soils, its key odour-determining ingredients meet the quality requirements of the European Pharmacopoeia and BS ISO 7609 regarding Bulgarian clary sage oil and/or have values that are close to the limits of these standards. The possibility of further industrial processing will make Salvia sclarea L. an economically interesting crop for farmers of phytoextraction technology.

Keywords: clary sage, heavy metals, phytoremediation, polluted soils

Procedia PDF Downloads 218