Search results for: unified theory of acceptance and use of technology (UTAUT) model

Authors: James Newman

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Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.

Keywords: blockchain, process mining, memory optimization, protocol

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Authors: Khomsan Laosillapacharoen

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This research paper was aimed to analyze the current situation of the furniture industry and embark a plan to enhance the export volume of Thai furniture. This is a qualitative research which utilized meta-analysis and focus group. A total of 24 experts in both government and private sectors were interviewed. The findings revealed that Thai furniture had some advantages of access to raw material, high quality of labors, and have a unique skill. However, the threat included a tendency to have more foreign competitors in domestic market. In addition, the strategies to enhance the level of export included increase the standard quality of Thai furniture, offer new and modern designs, use marketing on the internet, use modern technology, and gain tax incentive from the government.

Keywords: export, furniture, strategies, marketing

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Authors: Yasin Tadayonrad

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

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Authors: Derradji Chebli, Abdallah Bouguettoucha, Abdelbaki Reffas Khalil Guediri, Abdeltif Amrane

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The removal of Methyl Green dye (MG) from aqueous solutions using modified P-brutia cones (PBH and PBN), has been investigated work. The physical parameters such as pH, temperature, initial MG concentration, ionic strength are examined in batch experiments on the sorption of the dye. Adsorption removal of MG was conducted at natural pH 4.5 because the dye is only stable in the range of pH 3.8 to 5. It was observed in experiments that the P-brutia cones treated with NaOH (PBN) exhibited high affinity and adsorption capacity compared to the MG P-brutia cones treated with HCl (PBH) and biosorption capacity of modified P-brutia cones (PBN and PBH) was enhanced by increasing the temperature. This is confirmed by the thermodynamic parameters (ΔG° and ΔH°) which show that the adsorption of MG was spontaneous and endothermic in nature. The positive values of ΔS° suggested an irregular increase in the randomness for both adsorbent (PBN and PBH) during the adsorption process. The kinetic model pseudo-first order, pseudo-second order, and intraparticle diffusion coefficient were examined to analyze the sorption process; they showed that the pseudo-second-order model is the one that best describes the adsorption process (MG) on PBN and PBH with a correlation coefficient R²> 0.999. The ionic strength has shown that it has a negative impact on the adsorption of MG on two supports. A reduction of 68.5% of the adsorption capacity for a value Ce=30 mg/L was found for the PBH, while the PBN did not show a significant influence of the ionic strength on adsorption especially in the presence of NaCl. Among the tested isotherm models, the Langmuir isotherm was found to be the most relevant to describe MG sorption onto modified P-brutia cones with a correlation factor R²>0.999. The capacity adsorption of P-brutia cones, was confirmed for the removal of a dye, MG, from aqueous solution. We note also that P-brutia cones is a material very available in the forest and low-cost biomaterial

Keywords: adsorption, p-brutia cones, forest wastes, dyes, isotherm

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Authors: Hanan F. Aly, Fateheya M. Metwally, Hanaa H. Ahmed

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The current study is undertaken to elucidate a possible neuroprotective role of dehydroepiandrosterone (DHEA) against the development of Alzheimer’s disease in experimental rat model. Alzheimer’s disease was produced in young female ovariectomized rats by intraperitoneal administration of AlCl3 (4.2 mg/kg body weight) daily for 12 weeks. Half of these animals also received orally DHEA (250 mg/kg body weight, three times weekly) for 18 weeks. Control groups of animals received either DHAE alone, or no DHEA, or were not ovariectomized. After such treatment the animals were analyzed for oxidative stress biomarkers such as hydrogen peroxide, nitric oxide and malondialdehyde, total antioxidant capacity, reduced glutathione, glutathione peroxidase, glutathione reductase, superoxide dismutase and catalase activities, antiapoptotic marker Bcl-2 and brain derived neurotrophic factor. Also, brain cholinergic markers (acetylcholinesterase and acetylcholine) were determined. The results revealed significant increase in oxidative stress parameters associated with significant decrease in the antioxidant enzyme activities in Al-intoxicated ovariectomized rats. Significant depletion in brain Bcl-2 and brain-derived neurotrophic factor levels were also detected. Moreover, significant elevations in brain acetylcholinesterase activity accompanied with significant reduction in acetylcholine level were recorded. Significant amelioration in all investigated parameters was detected as a result of treatment of Al-intoxicated ovariectomized rats with DHEA. These results were confirmed by histological examination of brain sections. These results clearly indicate a neuroprotective effect of DHEA against Alzheimer’s disease.

Keywords: Alzheimer’s disease, oxidative stress, apoptosis, dehydroepiandrosterone

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Authors: Tytus Tulwin, Ksenia Siadkowska, Rafał Sochaczewski

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A high power radial reciprocating engine is characterized by a large displacement volume of a combustion chamber. Choosing the right moment for ignition is important for a high performance or high reliability and ignition certainty. This work shows methods of simulating ignition process and its impact on engine parameters. For given conditions a flame speed is limited when a deflagration combustion takes place. Therefore, a larger length scale of the combustion chamber compared to a standard size automotive engine makes combustion take longer time to propagate. In order to speed up the mixture burn-up time the second spark is introduced. The transient Computational Fluid Dynamics model capable of simulating multicycle engine processes was developed. The CFD model consists of ECFM-3Z combustion and species transport models. A relative ignition timing difference for the both spark sources is constant. The temperature distribution on engine walls was calculated in the separate conjugate heat transfer simulation. The in-cylinder pressure validation was performed for take-off power flight conditions. The influence of ignition timing on parameters like in-cylinder temperature or rate of heat release was analyzed. The most advantageous spark timing for the highest power output was chosen. The conditions around the spark plug locations for the pre-ignition period were analyzed. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: CFD, combustion, ignition, simulation, timing

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Authors: Tianjie Zhang, Bingqian Cheng, Peng Zeng

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Engineering science and technology progress and innovation have become an important engine to promote social development. The reform exploration of "new engineering" in China has drawn extensive attention around the world, with its connotation as "to cultivate future diversified, innovative and outstanding engineering talents by taking ‘fostering character and civic virtue’ as the guide, responding to changes and shaping the future as the construction concept, and inheritance and innovation, crossover and fusion, coordination and sharing as the principal approach". In this context, Tianjin University, as a traditional Chinese university with advantages in engineering, further launched the CCII (Coherent-Collaborative-Interdisciplinary-Innovation) program, raising the cultivation idea of integrating new liberal arts education, multidisciplinary engineering education and personalized professional education. As urban planning practice in China has undergone the evolution of "physical planning -- comprehensive strategic planning -- resource management-oriented planning", planning education has also experienced the transmutation process of "building foundation -- urban scientific foundation -- multi-disciplinary integration". As a characteristic and advantageous discipline of Tianjin University, the major of Urban and Rural Planning, in accordance with the "CCII Program of Tianjin University", aims to build China's top and world-class major, and implements the following educational reform measures: 1. Adding corresponding English courses, such as advanced course on GIS Analysis, courses on comparative studies in international planning involving ecological resources and the sociology of the humanities, etc. 2. Holding "Academician Forum", inviting international academicians to give lectures or seminars to track international frontier scientific research issues. 3. Organizing "International Joint Workshop" to provide students with international exchange and design practice platform. 4. Setting up a business practice base, so that students can find problems from practice and solve them in an innovative way. Through these measures, the Urban and Rural Planning major of Tianjin University has formed a talent training system with multi-disciplinary cross integration and orienting to the future science and technology.

Keywords: China, higher education reform, innovation, new engineering education, rural and urban planning, Tianjin University

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Pavel Svoboda, Oldřich Müller

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The paper contains a screening of the opinions of helping professional workers working in a home for seniors with individuals with neurocognitive disorders and compares them with the opinions of a younger generation of students who are just preparing for this work. The authors carried out a comparative questionnaire survey with both target groups, focusing on the analysis and comparison of possible differences in their knowledge in the field of care for elderly people with neurocognitive disorders. Specifically, they focused on knowledge and experience with approaches, methods and tools applicable within the framework of music therapy interventions, as they are understood in practice in comparison with the theoretical knowledge of secondary school students focused on social work. The questionnaire was mainly aimed at assessing the knowledge of the possibilities of effective memory stimulation of the elderly and their communication skills using the means of music. The conducted investigation was based on the research of studies dealing with so-called non-pharmacological approaches to the given clientele; for professional caregivers, it followed music therapy lessons, which the authors regularly implemented from the beginning of 2022. Its results will, among other things, serve as the basis for an upcoming study with a scoping design review.

Keywords: neurocognitive disorders, seniors, music therapy intervention, melody, rhythm, text, memory stimulation, communication skills

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Authors: Lin Tang, Xiaoxia Guo, Lingling Zhang

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Recent vaccine scandals overshadowed China’s accomplishment of public health, triggering discussions on the causes of vaccine incidents. Through legal interpretation of selected vaccine incidents and analysis of systemic vulnerabilities in vaccine circulation and lot release, a panoramic review of legislative progresses in the vaccine administration sheds the light on this debate. In essence, it is the combination of the lagging legal system and the absence of information technology infrastructure in the process of vaccine administration reform that has led to the recurrence of vaccine incidents. These findings have significant implications for further improvement of vaccine administration and China’s participation in global healthcare.

Keywords: legislation, lot release, public health, reform, vaccine administration, vaccine circulation

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Authors: Chien-Ju Chen, Chia-Jui Yu, Jyun-Hao Liao, Chia-Ching Wu, Meng-Chyi Wu

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A 64 × 64 GaN-based micro-light-emitting diode array (μLEDA) with 20 μm in pixel size and 40 μm in pitch by flip-chip bonding (FCB) is demonstrated in this study. Besides, an underfilling (UF) technology is applied to the process for improving the uniformity of device. With those configurations, good characteristics are presented, operation voltage and series resistance of a pixel in the 450 nm flip chip μLEDA are 2.89 V and 1077Ω (4.3 mΩ-cm²) at 25 A/cm², respectively. The μLEDA can sustain higher current density compared to conventional LED, and the power of the device is 9.5 μW at 100 μA and 0.42 mW at 20 mA.

Keywords: GaN, micro-light-emitting diode array(μLEDA), flip-chip bonding, underfilling

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Authors: Lucjan Setlak, Emil Ruda

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The subject of this paper is to review, comparative analysis and simulation of selected components of power electronic systems (PES), consistent with the concept of a more electric aircraft (MEA). Comparative analysis and simulation in software environment MATLAB / Simulink were carried out based on a group of representatives of civil aircraft (B-787, A-380) and military (F-22 Raptor, F-35) in the context of multi-pulse converters used in them (6- and 12-pulse, and 18- and 24-pulse), which are key components of high-tech electronics on-board power systems of autonomous power systems (ASE) of modern aircraft (airplanes of the future).

Keywords: converters, electric machines, MEA (more electric aircraft), PES (power electronics systems)

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Authors: Milica Lilic, Marina Rosales Martínez

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Academic research cannot be oblivious to social problems and needs, so projects that have the capacity for transformation and impact should have the opportunity to go beyond the University circles and bring benefit to society. Apart from patents and R&D research contracts, this opportunity can be achieved through entrepreneurship as one of the most direct tools to turn knowledge into a tangible product. Thus, as an example of good practices, it is intended to analyze the case of an institutional entrepreneurship program carried out at the University of Seville, aimed at researchers interested in assessing the business opportunity of their research and expanding their knowledge on procedures for the commercialization of technologies used at academic projects. The program is based on three pillars: training, teamwork sessions and networking. The training includes aspects such as product-client fit, technical-scientific and economic-financial feasibility of a spin-off, institutional organization and decision making, public and private fundraising, and making the spin-off visible in the business world (social networks, key contacts, corporate image and ethical principles). On the other hand, the teamwork sessions are guided by a mentor and aimed at identifying research results with potential, clarifying financial needs and procedures to obtain the necessary resources for the consolidation of the spin-off. This part of the program is considered to be crucial in order for the participants to convert their academic findings into a business model. Finally, the networking part is oriented to workshops about the digital transformation of a project, the accurate communication of the product or service a spin-off offers to society and the development of transferable skills necessary for managing a business. This blended program results in the final stage where each team, through an elevator pitch format, presents their research turned into a business model to an experienced jury. The awarded teams get a starting capital for their enterprise and enjoy the opportunity of formally consolidating their spin-off company at the University. Studying the results of the program, it has been shown that many researchers have basic or no knowledge of entrepreneurship skills and different ways to turn their research results into a business model with a direct impact on society. Therefore, the described program has been used as an example to highlight the importance of knowledge transfer at the University and the role that this institution should have in providing the tools to promote entrepreneurship within it. Keeping in mind that the University is defined by three main activities (teaching, research and knowledge transfer), it is safe to conclude that the latter, and the entrepreneurship as an expression of it, is crucial in order for the other two to comply with their purpose.

Keywords: good practice, knowledge transfer, a spin-off company, university

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Authors: Natalia Kasatkina

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In an ever-increasing globalization, one’s grasp of diversity and tolerance has never been more indispensable, and it is a vital duty for all those in the field of foreign language teaching to help children cultivate such values. The present study explores the role of DIVERSITY and TOLERANCE in the language classroom and elementary, middle, and high school students’ perceptions of these two concepts. It draws on several theoretical domains of language acquisition, cultural awareness, and school psychology. Relying on these frameworks, the major findings are synthesized, and a paradigm of teaching tolerance through language-teaching is formulated. Upon analysing how tolerant our children are with ‘others’ in and outside the classroom, we have concluded that intolerance and aggression towards the ‘other’ increase with age, and that a feeling of supremacy over migrants and a sense of fear towards them begin to manifest more apparently when the students are in high school. In addition, we have also found that children in elementary school do not exhibit such prejudiced thoughts and behavior, which leads us to the believe that tolerance as well as intolerance are learned. Therefore, it is within our reach to teach our children to be open-minded and accepting. We have used the novel ‘Uncle Tom’s Cabin’ by Harriet Beecher Stowe as a springboard for lessons which are not only targeted at shedding light on the role of language in the modern world, but also aim to stimulate an awareness of cultural diversity. We equally strive to conduct further cross-cultural research in order to solidify the theory behind this study, and thus devise a language-based curriculum which would encourage tolerance through the examination of various literary texts.

Keywords: literary text, tolerance, EFL classroom, word-association test

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Authors: Ahmed Abada, Kadda Amara, Said Hiadsi, Bouhalouane Amrani

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Half-metallic properties of new predicted Mn2-based full Heusler alloys Mn2ZrSi and Mn2ZrGe have been studied by first-principles full-potential linearized augmented plane wave plus local orbital (FP-LAPW+lo) method based on density functional theory (DFT). Our investigation is focused on the structural, elastic, electronic and magnetic properties of these compounds. The AlCu2Mn-type structure is found to be energetically more favorable than the CuHg2Ti-type structure for both compounds and are half-metallic ferrimagnets (HMFIs) with total magnetic moments of 2.000 µB per formula unit, well consistent with Slater-Pauling rule (Mtot = ( 24 – Ztot ) µB). Calculations show that both the alloys have an indirect band gaps, in the majority-spin channel, with values of 0.505 eV and 0.278 eV for Mn2ZrSi and Mn2ZrGe, respectively. It was found that Mn2ZrSi and Mn2ZrGe preserved their half-metallicity for lattice constants range of 5.85–6.38 Å and 6.05–6.38 Å, respectively, and kept a 100% of spin polarization at the Fermi level. Moreover, the calculated formation energies and elastic constants confirm that these compounds are stable chemically and mechanically, and the good crystallographic compatibility with the lattice of semiconductors used industrially makes them promising magnetic materials in spintronic applications.

Keywords: first-principles calculations, full Heusler structure, half-metallic ferrimagnets, elastic properties

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Authors: Jiayue Guo, Lili You

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Background: Children and adolescent health are crucial for both personal well-being and the nation's future health landscape. Health Literacy (HL) is important in enabling adolescents to self-manage their health, a fundamental step towards health empowerment. However, there are limited tools for assessing HL among elementary and junior high school students. This study aims to construct and validate a test-based HL scale for Chinese students, offering a scientific reference for cross-cultural HL tool development. Methods: We conducted a cross-sectional online survey. Participants were recruited from a stratified cluster random sampling method, a total of 4189 Chinese in-school primary and secondary students. The development of the scale was completed by defining the concept of HL, establishing the item indicator system, screening items (7 health content dimensions), and evaluating reliability and validity. Delphi method expert consultation was used to screen items, the Rasch model was conducted for quality analysis, and Cronbach’s alpha coefficient was used to examine the internal consistency. Results: We developed four versions of the HL scale, each with a total score of 100, encompassing seven key health areas: hygiene, nutrition, physical activity, mental health, disease prevention, safety awareness, and digital health literacy. Each version measures four dimensions of health competencies: knowledge, skills, motivation, and behavior. After the second round of expert consultation, the average importance score of each item by experts is 4.5–5.0, and the coefficient of variation is 0.000–0.174. The knowledge and skills dimensions are judgment-based and multiple-choice questions, with the Rasch model confirming unidimensionality at a 5.7% residual variance. The behavioral and motivational dimensions, measured with scale-type items, demonstrated internal consistency via Cronbach's alpha and strong inter-item correlation with KMO values of 0.924 and 0.787, respectively. Bartlett's test of sphericity, with p-values <0.001, further substantiates the scale's reliability. Conclusions: The new test-based scale, designed to evaluate competencies within a multifaceted framework, aligns with current international adolescent literacy theories and China's health education policies, focusing not only on knowledge acquisition but also on the application of health-related thinking and behaviors. The scale can be used as a comprehensive tool for HL evaluation and a reference for other countries.

Keywords: adolescent health, Chinese, health literacy, rasch model, scale development

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Authors: Asma Mosbah, Hanane Khither, Kamelia Mosbah, Noreddine Kacem Chaouche, Mustapha Benboubetra

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In the present investigation, total oil (TO) and its neutral lipid fraction (NLF) extracted from the seed of the well know studied medicinal plant Nigella sativa were tested for their therapeutically effect on alcohol-induced liver injury in rat model. Male Albino rats were divided into five groups of eight animals each and fed a Lieber–DeCarli liquid diet containing 5% ethanol for experimental groups and dextran for control group, for a period of six weeks. Afterwards, rats received, orally, treatments with Nigella sativa extracts (TO, NLF) and N- acetylcysteine (NAC) as a positive control for four weeks. Activities of antioxidant enzymes; superoxide dismutase (SOD) and catalase (CAT), as well as malondialdehyde (MDA) and reduced glutathione (GSH). Biochemical parameters for kidney and liver functions, in treated and non treated rats, were evaluated throughout the time course of an experiment. Liver histological changes were taken into account. Enzymatic activities of both SOD and CAT increased significantly in rats treated with NLF and TO. While MDA level decreased in TO and NLF treated rats, GSH level increased significantly in TO and NLF treated rats. We noted equally a decrease in liver enzymes AST, ALT, and ALP. Microscopic observation of slides from the liver of ethanol treated rats showed a severe hepatotoxicity with lesions. Treatment with fractions leads to an improvement in liver lesions and a marked reduction in necrosis and infiltration. As a conclusion, both extracts of Nigella sativa seeds, TO and NLF, possess an important therapeutic protective potential against ethanol-induced hepatotoxicity in rats.

Keywords: alcohol-induced hepatotoxicity, antioxidant enzymes, Nigella sativa seeds, oil fractions

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Authors: Hongjian Jia

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A finite-length cylindrical shell with a spherical cap is a typical engineering approximation model of actual underwater targets. The research on the omni-directional acoustic scattering characteristics of this target model can provide a favorable basis for the detection and identification of actual underwater targets. The elastic resonance characteristics of the target are the results of the comprehensive effect of the target length, shell-thickness ratio and materials. Under the conditions of different materials and geometric dimensions, the coincidence resonance characteristics of the target have obvious differences. Aiming at this problem, this paper obtains the omni-directional acoustic scattering field of the underwater hemispherical cylindrical shell by numerical calculation and studies the influence of target geometric parameters (length, shell-thickness ratio) and material parameters on the coincidence resonance characteristics of the target in turn. The study found that the formant interval is not a stable value and changes with the incident angle. Among them, the formant interval is less affected by the target length and shell-thickness ratio and is significantly affected by the material properties, which is an effective feature for classifying and identifying targets of different materials. The quadratic polynomial is utilized to fully fit the change relationship between the formant interval and the angle. The results show that the three fitting coefficients of the stainless steel and aluminum targets are significantly different, which can be used as an effective feature parameter to characterize the target materials.

Keywords: hemispherical cylindrical shell;, fine echo characteristics;, geometric and material parameters;, formant interval

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Authors: Yuli Widiana

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The study of implicature which is one of the discussions of pragmatics is an interesting and challenging topic to discuss. Implicature is a meaning which is implied in an utterance which is not the same as its literal meaning. The rapid development of information technology results in social networks as media to broadcast messages. The broadcast messages may be in the form of jokes which contain implicature. The research applies the pragmatic equivalent method to analyze the topics of jokes based on the implicatures contained in them. Furthermore, the method is also applied to reveal the purpose of creating implicature in jokes. The findings include the kinds of implicature found in jokes which are classified into conventional implicature and conversational implicature. Then, in detailed analysis, implicature in jokes is divided into implicature related to gender, culture, and social phenomena. Furthermore, implicature in jokes may not only be used to give entertainment but also to soften criticisms or satire so that it does not sound rude and harsh.

Keywords: implicature, broadcast messages, conventional implicature, conversational implicature

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Authors: Xufei Liu, Shouxiang Lu, Kim Meow Liew

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Because a relatively small fire could potentially cause damage by smoke corrosion far exceed thermal fire damage, it has been realized that the corrosion of metal exposed to smoke atmospheres is a significant fire hazard, except for toxicity or evacuation considerations. For the burning materials in an actual fire may often be the mixture of combustible matters, a quantitative study on the corrosivity of smoke produced by the combustion of mixture is more conducive to the application of the basic theory to the actual engineering. In this paper, carbon steel samples were exposed to smoke generated by polyvinyl chloride and polypropylene, two common combustibles in industrial plants, with different mixing ratios in high humidity for 120 hours. The separate and combined corrosive effects of smoke were examined subsequently by weight loss measurement, scanning electron microscope, energy dispersive spectroscopy and X-ray diffraction. It was found that, although the corrosivity of smoke from polypropylene was much smaller than that of smoke from polyvinyl chloride, smoke from polypropylene enhanced the major corrosive effect of smoke from polyvinyl chloride to carbon steel. Furthermore, the corrosion kinetics of carbon steel under smoke were found to obey the power function. Possible corrosion mechanisms were also proposed. All the analysis helps to provide basic information for the determination of smoke damage and timely rescue after fire.

Keywords: corrosion kinetics, corrosion mechanism, mixed combustible, SEM/EDS, smoke corrosivity, XRD

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Authors: P. Okoro Ugo Chigozie, P. A. Igbojekwe, E. N. Ukabuilu

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Tourism and terrorism experiences are best viewed as dynamic, complex systems with extreme diverse consequences on any nation’s economy. Tourism is one of the biggest industries in the world and one of the economical sectors which grows rapidly; tourism has positive impact on the nation’s economy. Terrorism is the method or the theory behind the method whereby an organized group or party seeks to achieve its avowed aims chiefly through the systematic use of violence; the consequences of terrorism on tourist destinations are inescapable and can be profound. Especially, it threatens the attractiveness of a tourist destination and strips the competitiveness of that destination. Destination’s vulnerability to politically motivated violence not only retracts tourists, but threatens sustainable tourism development. This paper examines the activities of the Jamaata Ahlis Sunna Liddaawati -an Islamic sect popularly known as Boko Haram – and its impact on sustainable tourism development in the Nigeria state. Possible triggers of this insurgency and potentially evolving measure against its influence on sustainable tourism including, strong image management of the tourism industry, feasible tourist safety policy, viable anti-terrorism measures, proactive respond to the challenge of terrorism, reinforcement of the legitimate frameworks and irrevocable penalty against menace of corruption; are discussed in this paper, as limiting the effects of insurgency on the attractiveness of Nigeria as safe tourists destination.

Keywords: Nigeria, terrorism, sustainable tourism development, corruption and competitiveness

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Authors: Jakub Adamec, Svatava Janouskova, Tomas Hak

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The necessity of sustainable housing is explicitly embedded in ‘The 2030 agenda for sustainable development’, in particular, goal 11 ‘sustainable cities and communities’. Every UN member state is obligated to implement strategies from the agenda, including a strategy for sustainable housing into the practice in the local context. As shown in many countries, the lack of knowledge represses the adaptation process of sustainable strategies by governments. Hence, this study explores the concept of sustainable housing within the Czech Republic. The research elaborates on this term, and its current definition concerning ‘Geneva UN Charter on Sustainable Housing’. To this day, the charter represents the most comprehensive framework for a sustainable housing concept. Researchers conducted a comparative analysis of 38 international and 195 Czech national strategic documents. As a result, the charter‘s and strategic documents‘ goals were interconnected, identifying the most represented targets (e.g. improved environmental and energy performance of dwellings, resilient urban settlements which use renewable energy, and sustainable and integrated transport systems). The research revealed, even though the concept of sustainable housing is still dominated by environmental aspects, that social aspects significantly increased its importance. Additionally, this theoretical framework will serve as a foundation for the sustainable housing index development for the Czech Republic.

Keywords: comparative analysis, Czech national strategy, Geneva un charter, sustainable housing, urban theory

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Authors: Ahmad Rabby

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The demographic trend analyses of Bombay-duck from time series catch data using CMSY and BSM for the first time in Bangladesh. During 2000-2018, CMSY indicates average lowest production in 2000 and highest in 2018. This has been used in the estimation of prior biomass by the default rules. Possible 31030 viable trajectories for 3422 r-k pairs were found by the CMSY analysis and the final estimates for intrinsic rate of population increase (r) was 1.19 year-1 with 95% CL= 0.957-1.48 year-1. The carrying capacity(k) of Bombay-duck was 283×103 tons with 95% CL=173×103 - 464×103 tons and MSY was 84.3×103tons year-1, 95% CL=49.1×103-145×103 tons year-1. Results from Bayesian state-space implementation of the Schaefer production model (BSM) using catch & CPUE data, found catchabilitiy coefficient(q) was 1.63 ×10-6 from lcl=1.27×10-6 to ucl=2.10×10-6 and r= 1.06 year-1 with 95% CL= 0.727 - 1.55 year-1, k was 226×103 tons with 95% CL=170×103-301×103 tons and MSY was 60×103 tons year-1 with 95% CL=49.9 ×103- 72.2 ×103 tons year-1. Results for Bombay-duck fishery management based on BSM assessment from time series catch data illustrated that, Fmsy=0.531 with 95% CL =0.364 - 0.775 (if B > 1/2 Bmsy then Fmsy =0.5r); Fmsy=0.531 with 95% CL =0.364-0.775 (r and Fmsy are linearly reduced if B < 1/2Bmsy). Biomass in 2018 was 110×103 tons with 2.5th to 97.5th percentile=82.3-155×103 tons. Relative biomass (B/Bmsy) in last year was 0.972 from 2.5th percentile to 97.5th percentile=0.728 -1.37. Fishing mortality in last year was 0.738 with 2.5th-97.5th percentile=0.525-1.37. Exploitation F/Fmsy was 1.39, from 2.5th to 97.5th percentile it was 0.988 -1.86. The biological reference points of B/BMSY was smaller than 1.0, while F/FMSY was higher than 1.0 revealed an over-exploitation of the fishery, indicating that more conservative management strategies are required for Bombay-duck fishery.

Keywords: biological reference points, catchability coefficient, carrying capacity, intrinsic rate of population increase

Procedia PDF Downloads 122

Authors: Smita Krishnan, Krittika Chandran, Chandra Mohan Sinnathambi

Abstract:

Produced water and its treatment and management are growing challenges in all producing regions. This water is generally considered as a nonrevenue product, but it can have significant value in enhanced oil recovery techniques if it meets the required quality standards. There is also an interest in the beneficial uses of produced water for agricultural and industrial applications. Advanced Oxidation Process is a chemical technology that has been growing recently in the wastewater treatment industry, and it is highly recommended for non-easily removal of organic compounds. The efficiency of AOPs is compound specific, therefore, the optimization of each process should be done based on different aspects.

Keywords: advanced oxidation process, photochemical processes, degradation, organic contaminants

Procedia PDF Downloads 498

Authors: Marcin Szlachetka, Mateusz Paszko, Grzegorz Baranski

Abstract:

This paper discusses the AVL EXCITE Designer simulation research into loads applied to main and crank bearings in the compression-ignition two-stroke engine. There was created a model of engine lubrication system which covers the part of this system related to particular nodes of a bearing system, i.e. a connection of main bearings in an engine block with a crankshaft, a connection of crank pins with a connecting rod. The analysis focused on the load given as a distribution of hydrodynamic oil film pressure corresponding different values of radial internal clearance. There was also studied the impact of gas force on minimal oil film thickness in main and crank bearings versus crankshaft rotational speed. Our model calculates oil film parameters, an oil film pressure distribution, an oil temperature change and dimensions of bearings as well as an oil temperature distribution on surfaces of bearing seats. Accordingly, it was possible to select, for example, a correct clearance for each of the node bearings. The research was performed for several values of engine crankshaft speed ranging from 800 RPM to 4000 RPM. Bearing oil pressure was changed according to engine speed ranging between 1 bar and 5 bar and an oil temperature of 90°C. The main bearing clearances made initially for the calculation and research were: 0.015 mm, 0.025 mm, 0.035 mm, 0.05 mm, 0.1 mm. The oil used for the research corresponded the SAE 5W-40 classification. The paper presents the selected research results referring to certain specific operating points and bearing radial internal clearances. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A. and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: crank bearings, diesel engine, oil film, two-stroke engine

Procedia PDF Downloads 206

Authors: Carlos Tarmeño Noriega, Igor Aguilar Alonso

Abstract:

Fungal diseases are common in vineyards; they cause a decrease in the quality of the products that can be sold, generating distrust of the customer towards the seller when buying fruit. Currently, technology allows the classification of fruits according to their characteristics thanks to artificial intelligence. This study proposes the implementation of a control system that allows the identification of the main fungal diseases present in the Italia grape, making use of a convolutional neural network (CNN), OpenCV, and TensorFlow. The methodology used was based on a collection of 20 articles referring to the proposed research on quality control, classification, and recognition of fruits through artificial vision techniques.

Keywords: computer vision, convolutional neural networks, quality control, fruit market, OpenCV, TensorFlow

Procedia PDF Downloads 74

Authors: Hamide Farshad, Mohammadreza Javidi Abdollah Zadeh Aval

Abstract:

As a result of the growing penetration of the media into human life, a new role under the title of "audience" is defined in the social life .A kind of role which is dramatically changed since its formation. This article aims to define the audience position in the new media equations which is concluded to the transformation of the media role. By using the Library and Attributive method to study the history, the evolutionary outlook to the audience and the recognition of the audience and the media relation in the new media context is studied. It was perceived in past that public communication would result in receiving the audience. But after the emergence of the interactional media and transformation in the audience social life, a new kind of public communication is formed, and also the imaginary picture of the audience is replaced by the audience impact on the communication process. Part of this impact can be seen in the form of feedback which is one of the public communication elements. In public communication, the audience feedback is completely accepted. But in many cases, and along with the audience feedback, the media changes its direction; this direction shift is known as media feedback. At this state, the media and the audience are both doers and consistently change their positions in an interaction. With the greater number of the audience and the media, this process has taken a new role, and the role of this doer is sometimes taken by an audience while influencing another audience, or a media while influencing another media. In this article, this multiple public communication process is shown through representing a model under the title of ”The bilateral influence of the audience and the media.” Based on this model, the audience and the media power are not the two sides of a coin, and as a result, by accepting these two as the doers, the bilateral power of the audience and the media will be complementary to each other. Also more, the compatibility between the media and the audience is analyzed in the bilateral and interactional relation hypothesis, and by analyzing the action law hypothesis, the dos and don’ts of this role are defined, and media is obliged to know and accept them in order to be able to survive. They also have a determining role in the strategic studies of a media.

Keywords: audience, effect, media, interaction, action laws

Procedia PDF Downloads 481

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 114

Authors: G. Singh, H.Schuster, U. Füssel

Abstract:

The stability of electric arc and durability of electrode tip used in Tungsten Inert Gas (TIG) welding demand a metallurgical study about the chemical transport mechanism of emitter oxide particles in tungsten electrode during its real welding conditions. The tungsten electrodes doped with emitter oxides of rare earth oxides such as La₂O₃, Th₂O₃, Y₂O₃, CeO₂ and ZrO₂ feature a comparatively lower work function than tungsten and thus have superior emission characteristics due to lesser surface temperature of the cathode. The local change in concentration of these emitter particles in tungsten electrode due to high temperature diffusion (chemical transport) can change its functional properties like electrode temperature, work function, electron emission, and stability of the electrode tip shape. The resulting increment in tip surface temperature results in the electrode material loss. It was also observed that the tungsten recrystallizes to large grains at high temperature. When the shape of grain boundaries are granular in shape, the intergranular diffusion of oxide emitter particles takes more time to reach the electrode surface. In the experimental work, the microstructure of the used electrode's tip surface will be studied by scanning electron microscope and reflective X-ray technique in order to gauge the extent of the diffusion and chemical reaction of emitter particles. Besides, a simulated model is proposed to explain the effect of oxide particles diffusion on the electrode’s microstructure, electron emission characteristics, and electrode tip erosion. This model suggests metallurgical modifications in tungsten electrode to enhance its erosion resistance.

Keywords: rare-earth emitter particles, temperature-dependent diffusion, TIG welding, Tungsten electrode

Procedia PDF Downloads 179

Authors: Christiana Ebobo

Abstract:

Cybercrime consists of numerous crimes that are perpetrated on the internet on daily basis. The forms include but not limited to Identity theft, Pretentious dating, Desktop counterfeiting, Internet chat room, Cyber harassment, Fraudulent electronic mails, Automated Teller Machine Spoofing, Pornography, Piracy, Hacking, Credit card frauds, Phishing and Spamming. The general term used among the youths for this type of crime in Nigeria is ‘Yahoo Yahoo’. Cybercrime is on the increase among the youths at all levels as such this study aims at examining the impact of cybercrime on youth development in Nigeria. The study examines the impact of cybercrime on youths’ academic performance, integrity, employment and religious practices. The study is a survey which made use of questionnaire and focus group discussion among 150 randomly selected youths in Gwagwalada LCDA, Federal Capital Territory, Nigeria. The study adopts the systems theory as its theoretical framework. The study also adopts the simple frequency table and percentage for its data analysis. The study reveals that cybercrime has eaten deep into the minds of some youths and some of them are practicing diabolic means to succeed in it. It is also reveals that majority (68%) of the respondents believe that cybercrime impacts negatively on youths’ academic performance in Nigeria. The major recommendation of this study is that cybercrime offenders should be treated like armed robbers in order to discourage other youths from getting involved in it.

Keywords: armed robber, cybercrime, integrity, youth

Procedia PDF Downloads 512