Search results for: tolerance analysis

Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

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Authors: Ren Junn Hwang, Chung-Chien Lu, Jain-Shing Wu

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Cloud outsource storage is one of important services in cloud computing. Cloud users upload data to cloud servers to reduce the cost of managing data and maintaining hardware and software. To ensure data confidentiality, users can encrypt their files before uploading them to a cloud system. However, retrieving the target file from the encrypted files exactly is difficult for cloud server. This study proposes a protocol for performing multikeyword searches for encrypted cloud data by applying k-nearest neighbor technology. The protocol ranks the relevance scores of encrypted files and keywords, and prevents cloud servers from learning search keywords submitted by a cloud user. To reduce the costs of file transfer communication, the cloud server returns encrypted files in order of relevance. Moreover, when a cloud user inputs an incorrect keyword and the number of wrong alphabet does not exceed a given threshold; the user still can retrieve the target files from cloud server. In addition, the proposed scheme satisfies security requirements for outsourced data storage.

Keywords: fault-tolerance search, multi-keywords search, outsource storage, ranked search, searchable encryption

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Authors: Dong Wook Lee, Adrian Mistreanu

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The authors have studied a method for analyzing containment and penetration using an explicit nonlinear Finite Element Analysis. This method may be used in the stage of concept design for the protection of external configurations or components of aircraft engines and nuclear power plant structures. This paper consists of the modeling method, the results obtained from the method and the comparison of the results with those calculated from simple analytical method. It shows that the containment capability obtained by proposed method matches well with analytically calculated containment capability.

Keywords: computer aided engineering, containment analysis, finite element analysis, impact analysis, penetration analysis

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Anuta Mukherjee, Saswati Mukherjee

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Data is growing everyday. Social networking sites such as Twitter are becoming an integral part of our daily lives, contributing a large increase in the growth of data. It is a rich source especially for sentiment detection or mining since people often express honest opinion through tweets. However, although sentiment analysis is a well-researched topic in text, this analysis using Twitter data poses additional challenges since these are unstructured data with abbreviations and without a strict grammatical correctness. We have employed collision theory to achieve sentiment analysis in Twitter data. We have also incorporated discourse analysis in the collision theory based model to detect accurate sentiment from tweets. We have also used the retweet field to assign weights to certain tweets and obtained the overall weightage of a topic provided in the form of a query. Hadoop has been exploited for speed. Our experiments show effective results.

Keywords: sentiment analysis, twitter, collision theory, discourse analysis

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Authors: Razan Salem

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Men and women are different, and so their investment behaviors may also vary. To the author’s best knowledge, women's investment behavior and its association with demographic factors have not been explored directly in the behavioral finance literature, however, particularly in respect to the Arab region. Thus, this study extends the literature by focusing on examining the association of demographic factors (age, annual income, and education) with Arab women’s investment behavior. To achieve the study’s aim, the researcher distributed 600 close-ended online questionnaires to a sample of Arab male and female individual investors in both Saudi Arabia and Jordan; using Kruskal-Wallis H Test and the Mann-Whitney U Test to analyze the data. The findings reveal that age, education, and level of income are associated with Arab women’s investment behavior. Educational level and level of income are positively associated with Arab women investment confidence level. On the contrary, age is negatively associated with Arab women financial risk tolerance. According to annual income, Arab women with lower incomes have lower confidence and investment literacy levels. Overall, the study concludes that age, income, and education are important demographic factors that must be considered when investigating the investment behavior of women in the Arab region.

Keywords: Arab region, demographic factors, investment behavior, women investors

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Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

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In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation (RADTRAD), symbolic nuclear analysis package (SNAP), dose, PWR

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Authors: Michael Gidey Gebru

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Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

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Authors: Aboul-Nasr Amal, Sabry Soraya, Sabra Mayada

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The effects of phosphorus amendments and arbuscular mycorrhizal (AM) fungi Glomus intraradices on the sweet basil (Ocimum basilicum L.), chemical composition and percent of volatile oil, and metal accumulation in plants and its availability in soil were investigated in field experiment at two seasons 2012 and 2013 under contaminated soil with Pb and Cu. The content of essential oil and shoot and root dry weights of sweet basil was increased by the application of mineral phosphorus as compared to control. Inoculation with AM fungi reduced the metal concentration in shoot, recording a lowest value of (33.24, 18.60 mg/kg) compared to the control (46.49, 23.46 mg/kg) for Pb and Cu, respectively. Availability of Pb and Cu in soil were decreased after cultivation in all treatments compared to control. However, metal root concentration increased with the inoculation, with highest values of (30.15, 39.25 mg/kg)compared to control (22.01, 33.57mg/kg) for Pb and Cu, respectively. The content of linalool and methyl chavicol in basil oil was significantly increased in all treatments compared to control. We can thus conclude that the AM-sweet basil symbiosis could be employed as an approach to bioremediate polluted soils and enhance the yield and maintain the quality of volatile oil of sweet basil plants.

Keywords: arbuscular mycorrhizal fungus, heavy metals, sweet basil, oil composition

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Authors: Sie Long Kek, Wah June Leong, Kok Lay Teo

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Linear quadratic Gaussian model is a standard mathematical model for the stochastic optimal control problem. The combination of the linear quadratic estimation and the linear quadratic regulator allows the state estimation and the optimal control policy to be designed separately. This is known as the separation principle. In this paper, an efficient computational method is proposed to solve the linear quadratic Gaussian problem. In our approach, the Hamiltonian function is defined, and the necessary conditions are derived. In addition to this, the output error is defined and the least-square optimization problem is introduced. By determining the first-order necessary condition, the gradient of the sum squares of output error is established. On this point of view, the stochastic approximation approach is employed such that the optimal control policy is updated. Within a given tolerance, the iteration procedure would be stopped and the optimal solution of the linear-quadratic Gaussian problem is obtained. For illustration, an example of the linear-quadratic Gaussian problem is studied. The result shows the efficiency of the approach proposed. In conclusion, the applicability of the approach proposed for solving the linear quadratic Gaussian problem is highly demonstrated.

Keywords: iteration procedure, least squares solution, linear quadratic Gaussian, output error, stochastic approximation

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Authors: Komon Paisal

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The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: constructivism, learning management, mathematics analysis courses, learning activity

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Authors: Rawichar Chaipojjana, Suttipong Phosuksirikul, Arunsri Leejeerajumnean

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The objective of the study was to select the survival of probiotic strains when exposed to acidic and bile salts condition. Four probiotic strains (Lactobacillus casei subsp. rhamnosus TISTR 047, Lactobacillus casei TISTR 1500, Lactobacillus acidophilus TISTR 1338 and Lactobacillus plantarum TISTR 1465) were cultured in MRS broth and incubated at 35ºC for 15 hours before being inoculated into acidic condition (5 M HCl, pH 2) for 2 hours and bile salt (0.3%, pH 5.8) for 8 hour. The survived probiotics were counted in MRS agar. Among four stains, Lactobacillus casei subsp. rhamnosus TISTR 047 was the highest tolerance specie. Lactobacillus casei subsp. rhamnosus TISTR 047 reduced 6.74±0.07 log CFU/ml after growing in acid and 5.52±0.05 log CFU/ml after growing in bile salt. Then, double emulsion of microorganisms was chosen to encapsulate before spray drying. Spray drying was done with the inlet temperature 170ºC and outlet temperature 80ºC. The results showed that the survival of encapsulated Lactobacillus casei subsp. rhamnosus TISTR 047 after spray drying decreased from 9.63 ± 0.32 to 8.31 ± 0.11 log CFU/ml comparing with non-encapsulated, 9.63 ± 0.32 to 4.06 ± 0.08 log CFU/ml. Therefore, Lactobacillus casei subsp. rhamnosus TISTR 047 would be able to survive in gastrointestinal and spray drying condition.

Keywords: probiotic, acid, bile salt, spray drying

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Authors: Felipe Magalhaes Lemos

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Functional behavior analysis is a procedure that has been studied for several decades by behavior analysts. In Brazil, we still have few studies in the area, so it was decided to carry out a systematic review of the articles published in the area by Brazilians. A search was done on the following scientific article registration sites: PsycINFO, ERIC, ISI Web of Science, Virtual Health Library. The research includes (a) peer-reviewed studies that (b) have been carried out in Brazil containing (c) functional assessment as a pre-treatment through (d) experimental procedures, direct or indirect observation and measurement of behavior problems (e) demonstrating a relationship between environmental events and behavior. During the review, 234 papers were found; however, only 9 were included in the final analysis. Of the 9 articles extracted, only 2 presented functional analysis procedures with manipulation of environmental variables, while the other 7 presented different procedures for a descriptive behavior assessment. Only the two studies using "functional analysis" used graphs to demonstrate the prevalent function of the behavior. Other studies described procedures and did not make clear the causal relationship between environment and behavior. There is still confusion in Brazil regarding the terms "functional analysis", "descriptive assessment" and "contingency analysis," which are generally treated in the same way. This study shows that few articles are published with a focus on functional analysis in Brazil.

Keywords: behavior, contingency, descriptive assessment, functional analysis

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Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

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The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

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Authors: Duy M. P. Vo, Cornelia Sennewald, Gerald Hoffmann, Chokri Cherif

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The development of solutions to improve the resistance of buildings to short-term dynamic loads, particularly impact load, is driven by the urgent demand worldwide on securing human life and critical infrastructures. The research training group GRK 2250/1 aims to develop mineral-bonded composites that allow the fabrication of thin-layered strengthening layers providing available concrete members with enhanced impact resistance. This paper presents the development of 3D woven wire cellular structures that can be used as innovative reinforcement for targeted composites. 3D woven wire cellular structures are truss-like architectures that can be fabricated in an automatized process with a great customization possibility. The specific architecture allows this kind of structures to have good load bearing capability and forming behavior, which is of great potential to give strength against impact loading. An appropriate combination of topology and material enables an optimal use of thin-layered reinforcement in concrete constructions.

Keywords: 3D woven cellular structures, ductile behavior, energy absorption, fiber-based reinforced concrete, impact resistant

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Authors: V. V. Povoroznyuk, Lar. P. Martynyuk, N. I. Dzerovych, Lil. P. Martyntyuk

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Objective: Menopause-related changes in female body are associated with the greater risk of metabolic syndrome (MS), which includes obesity, dyslipidemia, impaired glucose tolerance, hypertension. The aim of our study was to reveal peculiarities of fat and lean mass distribution between postmenopausal women with abdominal obesity and with MS. Materials and Methods: The sample consisted of 43 postmenopausal 60 – 69 years old women (age: mean = 64,8; S.D. = 0,4); duration of menopause: mean = 14,5; S.D.= 0,9). The diagnosis of MS was considered according to IDF (2005 yr) criteria. Lean and fat mass distrubution were measured by dual-energy X-ray absortiometry, and were compared for the cohorts with and without MS. Data were analyzed using Statistical Package 6.0 (Statsoft). Results: Findings revealed that 24 (55,8 %) of postmenopausal women had MS. In patients with and without MS compared, fat mass was higher in the former group (41248,25±2263,89 and 29817,68±2397,78 respectively; F=11,9; p=0,001) and at different body regions also: gynoid fat (6563,72±348,19 and 5115,21±392,43 respectively; F=7,6; p=0,008), android fat (3815,45±200,8128 and 2798,15±282,79 respectively; F=9,06; p=0,004. Lean mass comparing didn’t show significant differences in female with and without MS (42548,0±1239,18 and 40667,53±1223,78 respectively; F=1,1; p=0,29) and at different body regions also. Conclusion: These findings suggest that in postmenopausal women with MS there is prevalence of fat mass without increasing of lean mass quantity in compare to female with abdominal obesity without MS.

Keywords: lean mass, fat mass, овesity, metabolic syndrome, women, postmenopausal period

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: predictive analysis, big data, predictive analysis algorithms, CART algorithm

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Authors: Barbara Urasinska-Wojcik, Neil Chilton, Peter Todd, Christopher Elsworthy, Gregory J. Gibbons

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The recent increase in the application of Additive Manufacturing (AM) of products has resulted in new demands on capability. The ability to integrate both form and function within printed objects is the next frontier in the 3D printing area. To move beyond prototyping into low volume production, we demonstrate a UK-designed and built AM hybrid system that combines polymer based structural deposition with digital deposition of electrically conductive elements. This hybrid manufacturing system is based on a multi-planar build approach to improve on many of the limitations associated with AM, such as poor surface finish, low geometric tolerance, and poor robustness. Specifically, the approach involves a multi-planar Material Extrusion (ME) process in which separated build stations with up to 5 axes of motion replace traditional horizontally-sliced layer modeling. The construction of multi-material architectures also involved using multiple print systems in order to combine both ME and digital deposition of conductive material. To demonstrate multi-material 3D printing, three thermoplastics, acrylonitrile butadiene styrene (ABS), polyamide 6,6/6 copolymers (CoPA) and polyamide 12 (PA) were used to print specimens, on top of which our high viscosity Ag-particulate ink was printed in a non-contact process, during which drop characteristics such as shape, velocity, and volume were assessed using a drop watching system. Spectroscopic analysis of these 3D printed materials in the IR region helped to determine the optimum in-situ curing system for implementation into the AM system to achieve improved adhesion and surface refinement. Thermal Analyses were performed to determine the printed materials glass transition temperature (Tg), stability and degradation behavior to find the optimum annealing conditions post printing. Electrical analysis of printed conductive tracks on polymer surfaces during mechanical testing (static tensile and 3-point bending and dynamic fatigue) was performed to assess the robustness of the electrical circuits. The tracks on CoPA, ABS, and PA exhibited low electrical resistance, and in case of PA resistance values of tracks remained unchanged across hundreds of repeated tensile cycles up to 0.5% strain amplitude. Our developed AM printer has the ability to fabricate fully functional objects in one build, including complex electronics. It enables product designers and manufacturers to produce functional saleable electronic products from a small format modular platform. It will make 3D printing better, faster and stronger.

Keywords: additive manufacturing, conductive tracks, hybrid 3D printer, integrated manufacture

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Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: Bashaiar Alsana

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Never has a revolution influenced all aspects of humanity as the communication revolution during the past two decades. This revolution, with all its advances and utilities, swept the world thus becoming an integral part of our lives, hence giving way to emerging applications at the social, economic, political, and educational levels. More specifically, such applications have changed the delivery system through which learning is acquired by students. Interaction with educators, accessibility to content, and creative delivery options are but a few facets of the new learning experience now being offered through the use of technology in the educational field. With different success rates, third world countries have tried to pace themselves with use of educational technology in advanced parts of the world. One such country is the small rich-oil state of Kuwait which has tried to adopt the e-educational model, however, an evaluation of such trial is yet to be done. This study aims to fill the void of research conducted around that topic. The study explores teachers’ acceptance of incorporating communication technologies in higher education in Kuwait. Teachers’ responses to survey questions present an overview of the e-learning experience in this country, and draw a framework through which implications and suggestions for future research can be discussed to better serve the advancement of e-education in developing countries.

Keywords: communication technologies, e-learning, Kuwait, social media

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Authors: Mariam Jaber, Abdullah Yahya, Mohammad Alkhedher

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The shift toward sustainable energy solutions increasingly focuses on hydrogen, recognized for its potential as a clean energy carrier. Despite its benefits, hydrogen storage poses significant challenges, primarily due to its low energy density and high volatility. Among the various solutions, pressure vessels designed for hydrogen storage range from Type I to Type V, each tailored for specific needs and benefits. Notably, Type V vessels, with their all-composite, liner-less design, significantly reduce weight and costs while optimizing space and decreasing maintenance demands. This study focuses on optimizing Type V hydrogen storage tanks by examining how different shapes affect performance in drop tests—a crucial aspect of achieving ISO 15869 certification. This certification ensures that if a tank is dropped, it will fail in a controlled manner, ideally by leaking before bursting. While cylindrical vessels are predominant in mobile applications due to their manufacturability and efficient use of space, spherical vessels offer superior stress distribution and require significantly less material thickness for the same pressure tolerance, making them advantageous for high-pressure scenarios. However, spherical tanks are less efficient in terms of packing and more complex to manufacture. Additionally, this study introduces toroidal vessels to assess their performance relative to the more traditional shapes, noting that the toroidal shape offers a more space-efficient option. The research evaluates how different shapes—spherical, cylindrical, and toroidal—affect drop test outcomes when combined with various composite materials and layup configurations. The ultimate goal is to identify optimal vessel geometries that enhance the safety and efficiency of hydrogen storage systems. For our materials, we selected high-performance composites such as Carbon T-700/Epoxy, Kevlar/Epoxy, E-Glass Fiber/Epoxy, and Basalt/Epoxy, configured in various orientations like [0,90]s, [45,-45]s, and [54,-54]. Our tests involved dropping tanks from different angles—horizontal, vertical, and 45 degrees—with an internal pressure of 35 MPa to replicate real-world scenarios as closely as possible. We used finite element analysis and first-order shear deformation theory, conducting tests with the Abaqus Explicit Dynamics software, which is ideal for handling the quick, intense stresses of an impact. The results from these simulations will provide valuable insights into how different designs and materials can enhance the durability and safety of hydrogen storage tanks. Our findings aim to guide future designs, making them more effective at withstanding impacts and safer overall. Ultimately, this research will contribute to the broader field of lightweight composite materials and polymers, advancing more innovative and practical approaches to hydrogen storage. By refining how we design these tanks, we are moving toward more reliable and economically feasible hydrogen storage solutions, further emphasizing hydrogen's role in the landscape of sustainable energy carriers.

Keywords: hydrogen storage, drop test, composite materials, type V tanks, finite element analysis

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Authors: Jenq-Shyong Chen, Ben-Fong Yu

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CNC(computer numerical control) machining centers have been widely used for machining different metal components for various industries. For a specific CNC machine, its everyday job is assigned to cut different products with quite different attributes such as material type, workpiece weight, geometry, tooling, and cutting conditions. Theoretically, the dynamic characteristics of the CNC machine should be properly tuned match each machining job in order to get the optimal machining performance. However, most of the CNC machines are set with only a standard set of CNC parameters. In this study, we have developed an auto-tuning system which can automatically change the CNC parameters and in hence change the machine dynamic characteristics according to the selection of machining modes which are set by the mixed combination of three machine performance indexes: the HO (high surface quality) index, HP (high precision) index and HS (high speed) index. The acceleration, jerk, corner error tolerance, oscillation and dynamic bandwidth of machine’s feed axes have been changed according to the selection of the machine performance indexes. The proposed auto-tuning system of the CNC parameters has been implemented on a PC-based CNC controller and a three-axis machining center. The measured experimental result have shown the promising of our proposed auto-tuning system.

Keywords: auto-tuning, CNC parameters, machining mode, high speed, high accuracy, high surface quality

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Authors: Michelle Maurer, Antonia Last, Mark S. Gresnigt, Bernhard Hube, Alexander S. Mosig

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The intestinal epithelium forms an essential barrier to prevent translocation of microorganisms, toxins or other potentially harmful molecules into the bloodstream. In particular, dendritic cells of the intestinal epithelium orchestrate an adapted response of immune tolerance to commensals and immune defense against invading pathogens. Systemic inflammation is typically associated with a dysregulation of this adapted immune response and is accompanied by a disruption of the epithelial and endothelial gut barrier which enables dissemination of pathogens within the human body. To understand the pathophysiological mechanisms underlying the inflammation-associated gut barrier breakdown, it is crucial to elucidate the complex interplay of the host and the intestinal microbiome. A microfluidically perfused three-dimensional intestine-on-chip model was established to emulate these processes in the presence of immune cells, commensal bacteria, and facultative pathogens. Multi-organ tissue flow (MOTiF) biochips made from polystyrene were used for microfluidic perfusion of the intestinal tissue model. The biochips are composed of two chambers separated by a microporous membrane. Each chamber is connected to inlet and outlet channels allowing independent perfusion of the individual channels and application of microfluidic shear stress. Human umbilical vein endothelial cells (HUVECs), monocyte-derived macrophages and intestinal epithelial cells (Caco-2) were assembled on the biochip membrane. Following 7 – 14 days of growth in the presence of physiological flow conditions, the epithelium was colonized with the commensal bacterium Lactobacillus rhamnosus, while the endothelium was perfused with peripheral blood mononuclear cells (PBMCs). Additionally, L. rhamnosus was co-cultivated with the opportunistic fungal pathogen Candida albicans. Within one week of perfusion, the epithelial cells formed self-organized and well-polarized villus- and crypt-like structures that resemble essential morphological characteristics of the human intestine. Dendritic cells were differentiated in the epithelial tissue that specifically responds to bacterial lipopolysaccharide (LPS) challenge. LPS is well-tolerated at the luminal epithelial side of the intestinal model without signs of tissue damage or induction of an inflammatory response, even in the presence of circulating PBMC at the endothelial lining. In contrast, LPS stimulation at the endothelial side of the intestinal model triggered the release of pro-inflammatory cytokines such as TNF, IL-1β, IL-6, and IL-8 via activation of macrophages residing in the endothelium. Perfusion of the endothelium with PBMCs led to an enhanced cytokine release. L. rhamnosus colonization of the model was tolerated in the immune competent tissue model and was demonstrated to reduce damage induced by C. albicans infection. A microfluidic intestine-on-chip model was developed to mimic a systemic infection with a dysregulated immune response under physiological conditions. The model facilitates the colonization of commensal bacteria and co-cultivation with facultative pathogenic microorganisms. Both, commensal bacteria alone and facultative pathogens controlled by commensals, are tolerated by the host and contribute to cell signaling. The human intestine-on-chip model represents a promising tool to mimic microphysiological conditions of the human intestine and paves the way for more detailed in vitro studies of host-microbiota interactions under physiologically relevant conditions.

Keywords: host-microbiota interaction, immune tolerance, microfluidics, organ-on-chip

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Authors: Zaideth Zobeida Ponce Alonso, Laura Emilia Fierro Lopez, Maria del Rocio Dominguez Gaona

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The present study is part of the Master in Modern Languages at the Universidad Autónoma de Baja California, and it aims to analyze how the sociocultural background might influence the development of learner autonomy in foreign language education in order to propose some strategies to overcome such challenges. Given the lack of research on the sociocultural barriers in learner autonomy in a Mexican context and the need to hear teachers’ voices about this issue, qualitative data was obtained from semi-structured interviews with six language teachers on their perspectives on learner autonomy, its application to the language classroom, and their experiences with Mexican and foreign learners/contexts in order to find out differences regarding learner autonomy. The results suggest three main sociocultural characteristics: preference for an authority figure, tendency towards collectivism, and low tolerance of ambiguity. Finally, nine strategies were proposed in order to help language teachers to deal with such sociocultural characteristics when fostering learner autonomy in the border city of Mexicali, where this study was carried out.

Keywords: learner autonomy, Mexican context, sociocultural influence, teachers' perspectives, teaching strategies

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Authors: Pei-Ru Yang, Yu-Chen Lin, Jia-Min Wu

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Background: A 58-year-old man with a history of osteoporosis and diabetes presented with chronic pain in his left knee due to severe knee joint degeneration. The knee replacement surgery was recommended by the doctor. But the patient suffered from low pain tolerance and wondered if virtual reality could relieve acute postoperative wound pain. Methods: We used the PICO (patient, intervention, comparison, and outcome) approach to generate indexed keywords and searched systematic review articles from 2017 to 2021 on the Cochran Library, PubMed, and Clinical Key databases. Results: The initial literature results included 38 articles, including 12 Cochrane library articles and 26 PubMed articles. One article was selected for further analysis after removing duplicates and off-topic articles. The eight trials included in this article were published between 2013 and 2019 and recruited a total of 723 participants. The studies, conducted in India, Lebanon, Iran, South Korea, Spain, and China, included adults who underwent hemorrhoidectomy, dental surgery, craniotomy or spine surgery, episiotomy repair, and knee surgery, with a mean age (24.1 ± 4.1 to 73.3 ± 6.5). Virtual reality is an emerging non-drug postoperative analgesia method. The findings showed that pain control was reduced by a mean of 1.48 points (95% CI: -2.02 to -0.95, p-value < 0.0001) in minor surgery and 0.32 points in major surgery (95% CI: -0.53 to -0.11, p-value < 0.03), and the overall postoperative satisfaction has improved. Discussion: Postoperative pain is a common clinical problem in surgical patients. Research has confirmed that virtual reality can create an immersive interactive environment, communicate with patients, and effectively relieve postoperative pain. However, virtual reality requires the purchase of hardware and software and other related computer equipment, and its high cost is a disadvantage. We selected the best literature based on clinical questions to answer the patient's question and used share decision making (SDM) to help the patient make decisions based on the clinical situation after knee replacement surgery to improve the quality of patient-centered care.

Keywords: knee replacement surgery, postoperative pain, share decision making, virtual reality

Procedia PDF Downloads 48

Authors: Farid Shekari

Abstract:

Salicylic Acid (SA) is a plant hormone that improves some physiological responses of plants under stress conditions. Seeds of two desi type chickpea cultivars, viz., Kaka and Pirooz, primed with 250, 500, 750, and 1000 μM of SA and a group of seeds without any treating (as control) were evaluated under rain fed conditions. Seed priming in both cultivars led to higher efficiency compare to non-primed treatments. In general, seed priming with 500 and 750 μM of SA had appropriate effects; however the cultivars responses were different in this regard. Kaka showed better performance both in primed and non-primed seed than Pirooz. Results of this study revealed that not only yield quantity but also yield quality, as seed protein amounts, could positively affect by SA treatments. It seems that SA by enhancing of soluble sugars and proline amounts enhanced total water potential (ψ) and RWC. The increment in RWC led to rose of chlorophyll content of plants chlorophyll stability. In general, SA increased water use efficiency, both in biologic and seed yield base, and drought tolerance of chickpea plants. HI was a little decreased in SA treatments and it shows that SA more effective in biomass production than seed yield.

Keywords: chlorophyll, harvest index, proline, seed protein, soluble sugar, water use efficiency, yield component

Procedia PDF Downloads 403

Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

Abstract:

Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

Procedia PDF Downloads 286

Authors: Shashank Mukkoti, Mainak Majumder, Srinivasan Venkatraman

Abstract:

Owing to the land scarcity in the modern-day, most of the construction activities are carried out closed to the existing buildings. Most of the high-rise buildings are constructed on pile foundations to transfer the design loads to a strong stratum below the ground surface. Due to the proximity of the new and existing structures, noise disturbances are prominent during the pile installation. Installation of vibratory piles is most suitable in urban areas. The ground vibrations developed due to the vibratory pile driving may cause many detrimental effects on the surrounding structures based on the proximity of the sources and nature of the structures. In the present study, an attempt has been made to study the severity of ground vibrations induced by vibratory pile driving. For this purpose, a three-dimensional finite element model has been developed in the ABAQUS/ Explicit finite element program. The couple finite/infinite element method has been employed for the capturing of propagating waves due to the pile installation. The geometry of the pile foundations, frequency of the pile driving, length of the pile has been considered for the parametric study. The results show that vibrations generated due to the vibratory pile installation are either very close or more than the thresholds tolerance limits set by different guidelines.

Keywords: FE model, pile driving, free field vibrations, wave propagation

Procedia PDF Downloads 281

Authors: Renu Yadav, Sanjeev Kumar

Abstract:

In northern India, chickpea (Cicer arietinum L.) come across with terminal high-temperature stress during reproductive stage which leads to reduced yield. Hence, stable production of chickpea will depend on the development of new methods like ‘priming’ which allow improved adaptation to the drought and heat stress. In the present experiment, 11-day chickpea seedling was primed with mild drought stress and put on recovery stage by irrigating and finally 30-day seedlings were exposed to heat stress 38°C (4 hours), 35°C (8 hours) and 32°C (12 hours). To study the effect of combinatorial stress, heat and drought stress was applied simultaneously. Analyses of various physiological parameters like membrane damage assay, photosynthetic pigments, antioxidative enzyme, total sugars were estimated at all stages. To study the effect of heat stress on the metabolites of the plants, GC-MS and HPLC were performed, while at transcriptional level Real-Time PCR of predicted heat stress-related genes was done. It was concluded that the heat stress significantly affected the chickpea plant at physiological and molecular level in all the five varieties. Results also show less damaging effect in primed plants by increasing the activity of antioxidative enzymes and increased expression of heat shock proteins and heat shock factors.

Keywords: chickpea, combinatorial stress, heat stress, oxidative stress, priming, RT-PCR

Procedia PDF Downloads 144

Authors: Boo-Sung Koh, Seung-Eock Kim

Abstract:

In this paper, a direct design using a nonlinear inelastic analysis is suggested. Also, this paper compares the load carrying capacity obtained by a nonlinear inelastic analysis with experiment results to verify the accuracy of the results. The allowable stress design results of a railroad through a plate girder bridge and the safety factor of the nonlinear inelastic analysis were compared to examine the safety performance. As a result, the load safety factor for the nonlinear inelastic analysis was twice as high as the required safety factor under the allowable stress design standard specified in the civil engineering structure design standards for urban magnetic levitation railways, which further verified the advantages of the proposed direct design method.

Keywords: direct design, nonlinear inelastic analysis, residual stress, initial geometric imperfection

Procedia PDF Downloads 518