Search results for: statistical process control

Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

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Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Slawomir Wnuk

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Due to widespread implementation of the renewable energy development programs the, solar energy use increasing constantlyacross the world. Accordingly to REN21, in 2020, both on-grid and off-grid solar photovoltaic systems installed capacity reached 760 GWDCand increased by 139 GWDC compared to previous year capacity. However, the photovoltaic solar cells used for primary solar energy conversion into electrical energy has exhibited significant drawbacks. The fundamentaldownside is unstable andlow efficiencythe energy conversion being negatively affected by a rangeof factors. To neutralise or minimise the impact of those factors causing energy losses, researchers have come out withvariedideas. One ofpromising technological solutionsoffered by researchers is PV-MTEG multilayer hybrid system combiningboth photovoltaic cells and thermoelectric generators advantages. A series of experiments was performed on Glasgow Caledonian University laboratory to investigate such a system in operation. In the experiments, the solar simulator Sol3A series was employed as a stable solar irradiation source, and multichannel voltage and temperature data loggers were utilised for measurements. The two layer proposed hybrid systemsimulation model was built up and tested for its energy conversion capability under a variety of the exposure angles to the solar irradiation with a concurrent examination of the temperature distribution inside proposed PV-MTEG structure. The same series of laboratory tests were carried out for a range of various loads, with the temperature and voltage generated being measured and recordedfor each exposure angle and load combination. It was found that increase of the exposure angle of the PV-MTEG structure to an irradiation source causes the decrease of the temperature gradient ΔT between the system layers as well as reduces overall system heating. The temperature gradient’s reduction influences negatively the voltage generation process. The experiments showed that for the exposureangles in the range from 0° to 45°, the ‘generated voltage – exposure angle’ dependence is reflected closely by the linear characteristics. It was also found that the voltage generated by MTEG structures working with the optimal load determined and applied would drop by approximately 0.82% per each 1° degree of the exposure angle increase. This voltage drop occurs at the higher loads applied, getting more steep with increasing the load over the optimal value, however, the difference isn’t significant. Despite of linear character of the generated by MTEG voltage-angle dependence, the temperature reduction between the system structure layers andat tested points on its surface was not linear. In conclusion, the PV-MTEG exposure angle appears to be important parameter affecting efficiency of the energy generation by thermo-electrical generators incorporated inside those hybrid structures. The research revealedgreat potential of the proposed hybrid system. The experiments indicated interesting behaviour of the tested structures, and the results appear to provide valuable contribution into thedevelopment and technological design process for large energy conversion systems utilising similar structural solutions.

Keywords: photovoltaic solar systems, hybrid systems, thermo-electrical generators, renewable energy

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Authors: Elaid Bouchetob, Bouchra Nadji

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This research paper compares the efficiency and reliability (R(t)) of SiC-based and Si-based DC-DC buck converters in thin layer PV systems with an AI-based MPPT controller. Using Simplorer/Simulink simulations, the study assesses their performance under varying conditions. Results show that the SiC-based converter outperforms the Si-based one in efficiency and cost-effectiveness, especially in high temperature and low irradiance conditions. It also exhibits superior reliability, particularly at high temperature and voltage. Reliability calculation (R(t)) is analyzed to assess system performance over time. The SiC-based converter demonstrates better reliability, considering factors like component failure rates and system lifetime. The research focuses on the buck converter's role in charging a Lithium battery within the PV system. By combining the SiC-based converter and AI-based MPPT controller, higher charging efficiency, improved reliability, and cost-effectiveness are achieved. The SiC-based converter proves superior under challenging conditions, emphasizing its potential for optimizing PV system charging. These findings contribute insights into the efficiency, reliability, and reliability calculation of SiC-based and Si-based converters in PV systems. SiC technology's advantages, coupled with advanced control strategies, promote efficient and sustainable energy storage using Lithium batteries. The research supports PV system design and optimization for reliable renewable energy utilization.

Keywords: efficiency, reliability, artificial intelligence, sic device, thin layer, buck converter

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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Authors: Yong Bum Shin

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This case focuses on Weighted additive difference, Conjunctive, Disjunctive, and Elimination by aspects methodologies in consumer decision-making models and the Simple additive weighting (SAW) approach in the multi-criteria decision-making (MCDM) area. Most decision-making models illustrate that the rank reversal phenomenon is unpreventable. This paper presents that rank reversal occurs in popular managerial methods such as Weighted Additive Difference (WAD), Conjunctive Method, Disjunctive Method, Elimination by Aspects (EBA) and MCDM methods as well as such as the Simple Additive Weighting (SAW) and finally Unified Commensurate Multiple (UCM) models which successfully addresses these rank reversal problems in most popular MCDM methods in decision-making area.

Keywords: multiple criteria decision making, rank inconsistency, unified commensurate multiple, analytic hierarchy process

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Authors: Mehdi Nasr-Esfahani, Leila Mohammad Bagheri, Ava Nasr-Esfahani

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Root and collar rot disease caused by Phytophthora capsici (Leonian) is one of the most serious diseases in pepper, Capsicum annuum L. In this study, a diverse collection of 37 commercial edible and ornamental pepper genotypes infected with P. capsici were investigated for biomass parameters and enzymatic activity of peroxidase or peroxide reductases (EC), superoxide dismutase (SOD), polyphenol oxidase (PPOs), catalase (CAT) and phenylalanine ammonia-lyase (PAL). Seven candidate DEG genes were also evaluated on resistant and susceptible pepper cultivars, through measuring product formation, using spectrophotometry and real-time polymerase chain reaction. All the five enzymes and seven defense-gene candidates were up-regulated in all inoculated pepper accessions to P. capsici. But, the enzymes and DEG genes were highly expressed in resistant cv. 19OrnP-PBI, 37ChillP-Paleo, and “23CherryP-Orsh". The expression level of enzymes were 1.5 to 5.6-fold higher in the resistant peppers, than the control non-inoculated genotypes. Also, the transcriptional levels of related candidate DEG genes were 3.16 to 5.90-fold higher in the resistant genotypes. There was a direct and high correlation coefficient between resistance, bio-mass parameters, enzymatic activity, and resistance gene expression. The related enzymes and candidate genes expressed herein will provide a basis for further gene cloning and functional verification studies, and also will aid in an understanding of the regulatory mechanism of pepper resistance to P. capsici.

Keywords: AP2/ERF, cDNA, enzymes, MIP gene, q-RTPCR, XLOC

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Authors: Saeb Ahmadi, Mohsen Vafaie Sefti, Mohammad Mahdi Shadman, Ebrahim Tangestani

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Carbon nanotube has shown great potential for the removal of various inorganic and organic components due to properties such as large surface area and high adsorption capacity. Central composite design is widely used method for determining optimal conditions. Also due to the economic reasons and wide application, the rare earth elements are important components. The analyses of cerium (Ce(III)) adsorption as one of the Rare Earth Elements (REEs) adsorption on Multiwall Carbon Nanotubes (MWCNTs) have been studied. The optimization process was performed using Response Surface Methodology (RSM). The optimum amount conditions were pH of 4.5, initial Ce (III) concentration of 90 mg/l and MWCNTs dosage of 80 mg. Under this condition, the optimum adsorption percentage of Ce (III) was obtained about 96%. Next, at the obtained optimum conditions the kinetic and isotherm studied and result showed the pseudo-second order and Langmuir isotherm are more fitted with experimental data than other models.

Keywords: cerium, rare earth element, MWCNTs, adsorption, optimization

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Authors: Abderrahmane Mousstain, Ez-Zohra Belkadi

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Many authors support more participatory and inclusive place branding practices that empower stakeholders’ participation. According to this participatory point of view, the effectiveness of place branding strategies cannot be achieved without citizen involvement. However, the role of all residents as key participants in the city branding process has not been widely discussed. The aim of this paper was to determine how citizens’ involvement impacts their perceptions of the city's image, using a multivariate model. To test our hypotheses hypothetical-deductive reasoning by the quantitative method was chosen. Our investigation is based on data collected through a survey among 200 citizens of Casablanca. Results show that the more citizens are involved, the more they tend to evaluate the image of the brand positively. Additionally, the degree of involvement seems to impact satisfaction and a sense of belonging. As well, the more citizen develops a sense of belonging to the city, the more favorable his or her perception of the brand image is. Ultimately, the role of citizens shouldn’t be limited to reception. They are also Co-creators of the brand, who ensure the correlation of the brand with authentic place roots.

Keywords: citybranding, sense of belonging, satisfaction, impact, brand’s image

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Authors: Ali Bolat, Ali Bayat, Mustafa Gullu

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Maize can be cultivated both under main and second crop conditions in Turkey. Main pests of maize under second crop conditions are Sesamia nonagrioides Lefebvre (Lepidoptera: Noctuidae) and Ostrinia nubilalis Hübner (Lepidoptera: Crambidae). Aerial spraying applications to control these two main maize pests can be carried out until 2006 in Turkey before it was banned due to environmental concerns like drifting of sprayed pestisides and low biological efficiency. In this context, pulverizers which can spray tall maize plants ( > 175 cm) from the ground have begun to be used. However, the biological efficiency of these sprayers is unknown. Some methods have been tested to increase the success of ground spraying in field experiments conducted in second crop maize in 2008 and 2009. For this aim, 6 spraying methods (air assisted spraying with TX cone jet, domestic cone nozzles, twinjet nozzles, air induction nozzles, standard domestic cone nozzles and tail booms) were used at two application rates (150 and 300 l.ha-1) by a sprayer. In the study, biological efficacy evaluations of each methods were measured in each parcel. Biological efficacy evaluations included counts of number of insect damaged plants, number of holes in stems and live larvae and pupa in stems of selected plants. As a result, the highest biological efficacy value (close to 70%) was obtained from Air Assisted Spraying method at 300 l / ha application volume.

Keywords: air assisted sprayer, drift nozzles, biological efficiency, maize plant

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Authors: Samira Karimi-Mansoub, Rahem Abri

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Currently, users expect high quality and personalized information from search results. To satisfy user’s needs, personalized approaches to web search have been proposed. These approaches can provide the most appropriate answer for user’s needs by using user context and incorporating information about query provided by combining search technologies. To carry out personalized web search, there is a need to make different techniques on whole of user search process. There are the number of possible deployment of personalized approaches such as personalized web search, personalized recommendation, personalized summarization and filtering systems and etc. but the common feature of all approaches in various domains is that user modeling is utilized to provide personalized information from the Web. So the most important work in personalized approaches is user model mining. User modeling applications and technologies can be used in various domains depending on how the user collected information may be extracted. In addition to, the used techniques to create user model is also different in each of these applications. Since in the previous studies, there was not a complete survey in this field, our purpose is to present a survey on applications and techniques of user modeling from the viewpoint of improvement in search results by considering the existing literature and researches.

Keywords: filtering systems, personalized web search, user modeling, user search behavior

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Authors: Petr Gurný

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One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the credit-scoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.

Keywords: credit-scoring models, multidimensional subordinated Lévy model, probability of default

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Authors: Amirreza Razzaghipour, Mahdi Khalili

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References from the World Health Organization and the Center for Disease Control for deceleration the spread of the Novel COVID-19, comprises social estrangement, frequent handwashing, and covering your mouth when around others. As hearing healthcare specialists, the influence of existenceinvoluntary to boundary social interactions on persons with hearing impairment was significant for us to understand. We found ourselves delaying cochlear implant (CI) surgeries. All children, and chiefly those with hearing loss, are susceptible to reductions in spoken communication. Hearing plans, such as cochlear implants, provide children with hearing loss access to spoken communication and provision language development. when provided early and used consistently, these supplies help children with hearing loss to engage in spoken connections. Cochlear implant (CI) is a standard medical-surgical treatment for bilateral severe to profound hearing loss with no advantage with the hearing aid. Hearing is one of the most important senses in humans. Pediatric hearing loss establishes one of the most important public health challenges. Children with hearing loss are recognized early and habilitated via hearing aids or with cochlear implants (CIs). Suitable care and maintenance as well as continuous auditory verbal therapy (AVT) are also essential in reaching for the successful attainment of language acquisition. Children with hearing loss posture important challenges to their parents, particularly when there is limited admission to their hearing care providers. The disruption in the routine of their hearing and therapy follow-up services has had substantial effects on the children as well as their parents.

Keywords: healthcare, covid-19, cochlear implants, spoken communication, hearing loss

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Authors: O. Casasayas, M. Vigo, R. Navarro, P. Ragazzi, P. Alvarez, A. Perez-Bellmunt

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Introduction: The blood flow restriction training (BFR) is a method of muscle training that allows increasing the stress of muscle tissue to enhance the muscle cross-section and strength. This type of training has clear benefits in the rehabilitation field since it can improve muscle strength using low mechanical loads. The aim of this study is to know in which knee pathologies BFR has been used, what methodology was used and what were the obtained results. Study design: We performed a systematic literature search using strategies for the concepts of “blood flow restriction OR blood flow restriction training AND knee” in Medline. Articles were screened by authors and included if they used the blood flow restriction training in pathology of the knee. Results: The pathology more frequently treated by BFR was knee osteoarthritis and the variables most analyzed were strength and pain. The vascular occlusion used was 80% in the major part of studies. The groups of BFR obtained an increase of strength with less pain but not always the results are statistically significant. The evidence levels are poor in the high number of studies because in some cases there is not a control group or the evaluators were not blinded. Conclusion: The use of BFR is useful to improve muscle strength in knee pathology since it does not increase the pain, but more studies are needed to see (comprehend) if this type of treatment obtains better results than a conventional therapy. No studies have been found that compare the different occlusion effects in both the strength improvement and the pain reduction. Neither studies that analyse the effects of BFR on the muscle contractile parameters have been found.

Keywords: blood flow restriction training, knee, arthroscopy knee, physical therapy

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Authors: Ming Ze Kao

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Static magnetic fields (SMF) are widely used in several medical applications, especially in diagnosis of tumors. However, biological effects of the SMFs on modulating cell physiology through the Lorentz force, which is highly frequency and magnitude dependent, remain to be elucidated. Specific patterns from SMFs of static MF, delivered by means of Halbach array magnets with a gradient increment of 6.857mT/mm from center to border, were found to have profound inhibitory effect on the growth rate of human cell line derived from Nasopharyngeal carcinoma patients. The SMFs, which were shown to be noncontact, selectively impact rapid dividing cells while quiescent cells stay intact. The phenomenon acts in two modes: the arrest of cell proliferation in the G2/M phase and destruction of cell mitosis in cell division. First mode is manifested by impacting the proper formation of mitotic spindle, whereas the second results in disintegration of the cancer cell. Both modes are demonstrated when SMF was applied for 24 hours to cancer cells, the results revealed that metaphase arrest during mitosis due to activation of DNA damage response (DDR), resulting in high expression of ATM-NBS1-CHEK signaling pathways and higher G2/M phase ratio compared with control group. Here, experimental data suggest that the SMFs cause activation of cell cycle checkpoints, which implies the MFs as a potential therapeutic modality as a sensitizer for radiotherapy or chemotherapy.

Keywords: static magnetic field, DNA damage response, Halbach array, magnetic therapy

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Authors: Fariba Ebrahimi, Mehdi Ghorbani

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Achieving to integrated Water management fundamentally needs to effective relation, coordination, collaboration and synergy among various actors who have common but different responsibilities. In this sense, the foundation of comprehensive and integrated management is not compatible with centralization and top-down strategies. The aim of this paper is analysis institutional network of water relevant stakeholders and water policy monitoring in Shemiranat. In this study collaboration networks between informal and formal institutions co-management process have been investigated. Stakeholder network analysis as a quantitative method has been implicated in this research. The results of this study indicate that institutional cohesion is medium; sustainability of institutional network is about 40 percent (medium). Additionally the core-periphery index has measured in this study according to reciprocity index. Institutional capacities for integrated natural resource management in regional level are measured in this study. Furthermore, the necessity of centrality reduction and promote stakeholders relations and cohesion are emphasized to establish a collaborative natural resource governance.

Keywords: policy monitoring, water management, social network, stakeholder, shemiranat

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Authors: Mohsun Rasim Alizada, Azar Inshalla Ahmdov

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Prompt photons are perhaps the most versatile tools for studying the dynamics of relativistic collisions of heavy ions. The study of photon radiation is of interest that in most hadron interactions, photons fly out as a background to other studied signals. The study of the birth of prompt photons in nucleon-nucleon collisions was previously carried out in experiments on Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). Due to the large energy of colliding nucleons, in addition to prompt photons, many different elementary particles are born. However, the birth of additional elementary particles makes it difficult to determine the accuracy of the effective section of the birth of prompt photons. From this point of view, the experiments planned on the Nuclotron-based Ion Collider Facility (NICA) complex will have a great advantage, since the energy obtained for colliding heavy ions will reduce the number of additionally born elementary particles. Of particular importance is the study of the processes of birth of prompt photons to determine the gluon leaving hadrons since the photon carries information about a rigid subprocess. At present, paper production of prompt photon in Compton scattering of quark-gluon and annihilation of quark–antiquark processes is investigated. The matrix elements Compton scattering of quark-gluon and annihilation of quark-antiquark pair processes has been written. The Square of matrix elements of processes has been calculated in FeynCalc. The phase volume of subprocesses has been determined. Expression to calculate the differential cross-section of subprocesses has been obtained: Given the resulting expressions for the square of the matrix element in the differential section expression, we see that the differential section depends not only on the energy of colliding protons, but also on the mass of quarks, etc. Differential cross-section of subprocesses is estimated. It is shown that the differential cross-section of subprocesses decreases with the increasing energy of colliding protons. Asymmetry coefficient with polarization of colliding protons is determined. The calculation showed that the squares of the matrix element of the Compton scattering process without and taking into account the polarization of colliding protons are identical. The asymmetry coefficient of this subprocess is zero, which is consistent with the literary data. It is known that in any single polarization processes with a photon, squares of matrix elements without taking into account and taking into account the polarization of the original particle must coincide, that is, the terms in the square of the matrix element with the degree of polarization are equal to zero. The coincidence of the squares of the matrix elements indicates that the parity of the system is preserved. The asymmetry coefficient of annihilation of quark–antiquark pair process linearly decreases from positive unit to negative unit with increasing the production of the polarization degrees of colliding protons. Thus, it was obtained that the differential cross-section of the subprocesses decreases with the increasing energy of colliding protons. The value of the asymmetry coefficient is maximal when the polarization of colliding protons is opposite and minimal when they are directed equally. Taking into account the polarization of only the initial quarks and gluons in Compton scattering does not contribute to the differential section of the subprocess.

Keywords: annihilation of a quark-antiquark pair, coefficient of asymmetry, Compton scattering, effective cross-section

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Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

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The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

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Authors: Mehrji Khosravan, Mostafa Fathali-Sianib, Davood Soudbar, Sasan Talebnezhad, Mohammad-Reza Ebrahimi

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The late transition metal catalyst of the end group of transition metals in the periodic table as Ni, Fe, Co, and Pd was grown up rapidly in polyolefin industries recently. These metals with suitable ligands exhibited special characteristic properties and appropriate activities in the production of polyolefins. The ligand 1,4-bis (2,6-diisopropyl phenyl) acenaphthene was synthesized by reaction of 2,6-diisopropyl aniline and acenaphthenequinone. The ligand was added to nickel (II) dibromide salt for synthesis the 1,4-bis (2,6 diisopropylphenyl) acenaphthene nickel (II) dibromide catalyst. The structure of the ligand characterized by IR technique. The catalyst then deposited on graphene and graphene oxide by vander walss-attachment for use in Ethylene slurry polymerization process in the presence of catalyst activator such as methylaluminoxane (MAO) in hexane solvent. The structure of the catalyst characterized by IR and TEM techniques and some of the polymers were characterized by DSC. The highest activity was achieved at 600 C for catalyst.

Keywords: α-diimine nickel (II) complex, graphene as supported catalyst, late transition metal, ethylene polymerization

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Authors: Bayan Alqassem, Israa A. Othman, Mohammed Abu Haija, Fawzi Banat

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The treatment of wastewater from highly toxic pollutants is one of the most challenging issues for humanity. In this study, the advanced oxidation process (AOP) was employed to study the catalytic degradation of phenol using different ferrite catalysts which are CoFe₂O₄, CrFe₂O₄, CuFe₂O₄, MgFe₂O₄, MnFe₂O₄, NiFe₂O₄ and ZnFe₂O₄. The ferrite catalysts were prepared via sol-gel and co-precipitation methods. Different ferrite composites were also prepared either by varying the metal ratios or incorporating chemically reduced graphene oxide in the ferrite cluster. The effect of phosphoric acid treatment on the copper ferrite activity. All of the prepared catalysts were characterized using infrared spectroscopy (IR), X-ray diffraction (XRD) and scanning electron microscopy (SEM). The ferrites catalytic activities were tested towards phenol degradation using high performance liquid chromatography (HPLC). The experimental results showed that ferrites prepared through sol-gel route were more active than those of the co-precipitation method towards phenol degradation. In both cases, CuFe₂O₄ exhibited the highest degradation of phenol compared to the other ferrites. The photocatalytic properties of the ferrites were also investigated.

Keywords: ferrite catalyst, ferrite composites, phenol degradation, photocatalysis

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Authors: Yuhanis Yusof, Zuriani Mustaffa, Siti Sakira Kamaruddin

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Data mining is a fundamental technique in identifying patterns from large data sets. The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical. Prior to that, data are consolidated so that the resulting mining process may be more efficient. This study investigates the effect of different data normalization techniques, which are Min-max, Z-score, and decimal scaling, on Swarm-based forecasting models. Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC). Forecasting models are later developed to predict the daily spot price of crude oil and gasoline. Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max. Nevertheless, the GWO is more superior that ABC as its model generates the highest accuracy for both crude oil and gasoline price. Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.

Keywords: artificial bee colony, data normalization, forecasting, Grey Wolf optimizer

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Authors: Anzor Abralava, Ketevan Kokrashvili, Rusudan Kutateladze, Nino Pailodze, Ketevan Kutateladze, Giorgi Sulashvili

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Nowadays when the integration of states is growing fast, it is urgent to study the rules of behavior which they resort to in case of conflicts and disagreements. The reason of disagreement in many ways is the Foreign policy carried out by separate countries, as the market participants define production and export capacity and structure as well as level of international division of labor due to the competition among them. We can say over and over again that outbreak of conflicts in Georgia displays the serious controversy between political and economic powerhouses. However, to tell the truth existence of the unsolved conflicts in Georgia is the result of weakness and inadequacy of Georgian politics. Today the main task of political quarters in Georgia should be a direction to Caucasus, as to the region burdened with the most complicated problems which blockade the settlement of conflicts and farther development of our country (or vice versa). In this situation rehabilitation of our authority, leading role and hegemony; expansion and consolidation of peacekeeping and other missions are considered as the exact activities for accomplishing all Georgian economic and political goals.

Keywords: Awara Group, political centers, administrative services, dynamic process

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Authors: K. Petcharaporn

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The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

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Authors: Nabhan H. N. Al-Harrasi

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Action Research (AR) plays an important role in improving the problematical situation. It is a process that enhances thinking and practise and bridges the gap between abstract and concrete thinking. Nowadays, AR as a methodology is wildly used to implement projects based on understanding the needs of owners, considering the organizational culture, meeting the requirements, encouraging partnership, representing different viewpoints, and building the project. This research describes the whole processes of digitizing Post-graduate theses and all articles published in 6 Journals at Sultan Qaboos University. AR implemented to respond to the university needs to enhance accessibilities to its information resources and make them available through the national repository. In order to prepare the action plan, the library administration met to discuss several points related to the proposed project, the most important of which are: • Providing digitalization devices. • Locating a specific part of the Library as a Digitization Unit. • Choosing a team. • Defining tasks. • Implementing the proposed project and evaluating the whole processes.

Keywords: action research, digitization, Theses, Journal articles, open access, Oman

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Authors: Yong-Jie Lin, Yi-Feng Lin

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In this study, scandium-doped yttria-stabilized zirconia (ScYSZ) and In2O3 nanoparticles (NPs) with cubic crystalline structures were successfully prepared using a facile hydrothermal process. ScYSZ films were prepared by the pressing of ScYSZ NPs and were further used for the electrolyte of solid oxide fuel cells (SOFCs). To increase the ionic conductivity of the ScYSZ electrolyte, different amounts of In2O3 NPs [0 wt% (X(In2O3)=0), 0.21 wt% (X(In2O3)=0.001) and 1.13 wt% (X(In2O3)=0.005)] were doped in the ScYSZ films to increase their oxygen vacancy. The result shows In2O3 NP/ScYSZ films with 1.13 wt% (X(In2O3 )=0.005) In2O3 NPs doping are with largest ionic conductivity of 0.057Ω-1 cm-1 at 900oC, which is 1.6 and 1.8 times higher than YSZ and In2O3 NP/ScYSZ films with 0.21 wt% (X(In2O3)=0.001) In2O3 NPs doping, respectively.

Keywords: indium oxide/scandium doping Yttria-stabilized zirconia, solid oxide fuel cells, scandium-doped yttria-stabilized zirconia, indium oxide

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

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Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

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Authors: Esra Topcuoglu, Seyhmus Baloglu

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This research investigates the effects of online hotel sales promotion fit (SP fit) on traveler purchase intention (PI) and word-of-mouth (WOM). It examines these relationships based on the need for cognition (NFC), intention to travel (TI), promotional attractiveness (PA), and demographics within resource matching theory (RMT). One factor (SP: Fit presence for monetary and nonmonetary vs. Fit absence for monetary and nonmonetary) design was employed to test the effects of SP fit on traveler behaviors. Data collection was conducted from 300 subjects through Qualtrics. One-way MANOVA was performed to test the main effects of SP fit, and PROCESS simple moderation test for the interaction effects. Results revealed promotional fit increased the effectiveness of monetary and nonmonetary sales promotions. “F&B discount card at the hotel” was the most preferred deal. Fit absence for monetary sales promotion (MSP) and fit presence for nonmonetary sales promotion (NMSP) yielded significant results. The participants were involved in their intention to travel and perceptions of promotional attractiveness to value the promotions.

Keywords: need for cognition, promotional attractiveness, sales promotion fit, travel intention

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Authors: H. Shokouhmand, A. Ghanami

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Heat pipe is simple heat transfer device which combines the conduction and phase change phenomena to control the heat transfer without any need for external power source. At hot surface of heat pipe, the liquid phase absorbs heat and changes to vapor phase. The vapor phase flows to condenser region and with the loss of heat changes to liquid phase. Due to gravitational force the liquid phase flows to evaporator section. In HVAC systems the working fluid is chosen based on the operating temperature. The heat pipe has significant capability to reduce the humidity in HVAC systems. Each HVAC system which uses heater, humidifier or dryer is a suitable nominate for the utilization of heat pipes. Generally heat pipes have three main sections: condenser, adiabatic region and evaporator.Performance investigation and optimization of heat pipes operation in order to increase their efficiency is crucial. In present article, a parametric study is performed to improve the heat pipe performance. Therefore, the heat capacity of heat pipe with respect to geometrical and confining parameters is investigated. For the better observation of heat pipe operation in HVAC systems, a CFD simulation in Eulerian- Eulerian multiphase approach is also performed. The results show that heat pipe heat transfer capacity is higher for water as working fluid with the operating temperature of 340 K. It is also showed that the vertical orientation of heat pipe enhances it’s heat transfer capacity used in the abstract.

Keywords: heat pipe, HVAC system, grooved heat pipe, CFD simulation

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Authors: Mengjie Liu

Abstract:

This essay aims at responding to the Kant arguments on how to fit the self-caused subject into the deterministic object which follows the natural laws. This essay mainly adopts the approach abstracted from Fichte’s “Wissenshaftslehre” (Doctrine of Science) to picture a possible solution to the conciliation of Kantian dualism. The Fichte approach is based on the unity of the theoretical and practical reason, which can be understood as a philosophical abstraction from ordinary experience combining both subject and object. This essay will discuss the general Kantian dualism problem and Fichte’s unity approach in the first part. Then the essay will elaborate on the achievement of this unity of the subject and object through Fichte’s “the I posits itself” process in the second section. The following third section is related to the ethical unity of subject and object based on the Fichte approach. The essay will also discuss the limitation of Fichte’s approach from two perspectives: (1) the theoretical possibility of the existence of the pure I and (2) Schelling’s statement that the Absolute I is a result rather than the originating act. This essay demonstrates a possible approach to unifying the subject and object supported by Fichte’s “Absolute I” and ethical theories and also points out the limitations of Fichte’s theories.

Keywords: Fichte, identity, Kantian dualism, Wissenshaftslehre

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Authors: Bahia Braktia, Belkacem Braktia

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Collaborative writing is now an established pedagogical technique in higher education. Since most educators do not have training in the design, execution, and evaluation of writing assignments, implementing such tasks has proven difficult. This paper firstly proposes a framework for a collaborative writing assignment based on a literature study and adopting a writing-to-learn concept. It then describes the research undertaken and shows how this framework is implemented in an economics course, at an Algerian university, with undergraduate students. Finally, using a mixed methods design, it examines the students’ perceptions of what they have learned about collaborative writing. Preliminary results show that group assignments will always be a challenge, but with careful planning and structure, a collaborative writing assignment can be used effectively to help students improve their analytical and critical thinking abilities, research and group work skills, as well as writing proficiency. Students have a positive experience of working in a team and identified a wide variety of different team skills that they have learned through the process.

Keywords: collaborative writing, research assignment, students’ perception, survey

Procedia PDF Downloads 186