Search results for: magnetic data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26336

Search results for: magnetic data

23336 Collagen Hydrogels Cross-Linked by Squaric Acid

Authors: Joanna Skopinska-Wisniewska, Anna Bajek, Marta Ziegler-Borowska, Alina Sionkowska

Abstract:

Hydrogels are a class of materials widely used in medicine for many years. Proteins, such as collagen, due to the presence of a large number of functional groups are easily wettable by polar solvents and can create hydrogels. The supramolecular network capable to swelling is created by cross-linking of the biopolymers using various reagents. Many cross-linking agents has been tested for last years, however, researchers still are looking for a new, more secure reactants. Squaric acid, 3,4-dihydroxy 3-cyclobutene 1,2- dione, is a very strong acid, which possess flat and rigid structure. Due to the presence of two carboxyl groups the squaric acid willingly reacts with amino groups of collagen. The main purpose of this study was to investigate the influence of addition of squaric acid on the chemical, physical and biological properties of collagen materials. The collagen type I was extracted from rat tail tendons and 1% solution in 0.1M acetic acid was prepared. The samples were cross-linked by the addition of 5%, 10% and 20% of squaric acid. The mixtures of all reagents were incubated 30 min on magnetic stirrer and then dialyzed against deionized water. The FTIR spectra show that the collagen structure is not changed by cross-linking by squaric acid. Although the mechanical properties of the collagen material deteriorate, the temperature of thermal denaturation of collagen increases after cross-linking, what indicates that the protein network was created. The lyophilized collagen gels exhibit porous structure and the pore size decreases with the higher addition of squaric acid. Also the swelling ability is lower after the cross-linking. The in vitro study demonstrates that the materials are attractive for 3T3 cells. The addition of squaric acid causes formation of cross-ling bonds in the collagen materials and the transparent, stiff hydrogels are obtained. The changes of physicochemical properties of the material are typical for cross-linking process, except mechanical properties – it requires further experiments. However, the results let us to conclude that squaric acid is a suitable cross-linker for protein materials for medicine and tissue engineering.

Keywords: collagen, squaric acid, cross-linking, hydrogel

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23335 The Implementation of Educational Partnerships for Undergraduate Students at Yogyakarta State University

Authors: Broto Seno

Abstract:

This study aims to describe and examine more in the implementation of educational partnerships for undergraduate students at Yogyakarta State University (YSU), which is more focused on educational partnerships abroad. This study used descriptive qualitative approach. The study subjects consisted of a vice-rector, two staff education partnerships, four vice-dean, nine undergraduate students and three foreign students. Techniques of data collection using interviews and document review. Validity test of the data source using triangulation. Data analysis using flow models Miles and Huberman, namely data reduction, data display, and conclusion. Results of this study showed that the implementation of educational partnerships abroad for undergraduate students at YSU meets six of the nine indicators of the success of strategic partnerships. Six indicators are long-term, strategic, mutual trust, sustainable competitive advantages, mutual benefit for all the partners, and the separate and positive impact. The indicator has not been achieved is cooperative development, successful, and world class / best practice. These results were obtained based on the discussion of the four formulation of the problem, namely: 1) Implementation and development of educational partnerships abroad has been running good enough, but not maximized. 2) Benefits of the implementation of educational partnerships abroad is providing learning experiences for students, institutions of experience in comparison to each faculty, and improving the network of educational partnerships for YSU toward World Class University. 3) The sustainability of educational partnerships abroad is pursuing a strategy of development through improved management of the partnership. 4) Supporting factors of educational partnerships abroad is the support of YSU, YSU’s partner and society. Inhibiting factors of educational partnerships abroad is not running optimally management.

Keywords: partnership, education, YSU, institutions and faculties

Procedia PDF Downloads 334
23334 Effect of Citric Acid on Hydrogen-Bond Interactions and Tensile Retention Properties of Citric Acid Modified Thermoplastic Starch Biocomposites

Authors: Da-Wei Wang, Liang Yang, Xuan-Long Peng, Mei-Chuan Kuo, Jen-Taut Yeh

Abstract:

The tensile retention and waterproof properties of thermoplastic starch (TPS) resins were significantly enhanced by modifying with proper amounts of citric acid (CA) and by melt-blending with poly(lactic acid) (PLA), although no distinguished chemical reaction occurred between CA and starch molecules. As evidenced by Fourier transform infrared spectroscopy and Solid-state 13C Nuclear Magnetic Resonance analyses, disruption of intra and interhydrogen-bondings within starch molecules did occur during the modification processes of CA modified TPS (i.e. TPS100CAx) specimens. The tensile strength (σf) retention values of TPS specimens reduced rapidly from 27.8 to 20.5 and 0.4 MPa, respectively, as the conditioning time at 20°C/50% relative humidity (RH) increased from 0 to 7 and 70 days, respectively. While the elongation at break (εf) retention values of TPS specimens increased rapidly from 5.9 to 6.5 and 34.8%, respectively, as the conditioning time increased from 0 to 7 and 70 days. After conditioning at 20°C/50% RH for 70 days, the σf and εf retention values of the best prepared (TPS100CA0.1)30PLA70 specimen are equivalent to 85% and 167% of its initial σf and εf values, respectively, and are more than 105 times higher but 48% lower than those of TPS specimens conditioned at 20°C/50% RH for the same amount of time. Demarcated diffraction peaks, new melting endotherms of recrystallized starch crystals and distinguished ductile characteristics with drawn debris were found for many conditioned TPS specimens, however, only slight retrogradation effect and much less drawn debris was found for most conditioned TPS100CAx and/or (TPS100CA0.1)xPLAy specimens. The significantly improved water proof, tensile retention properties and relatively unchanged in retrogradation effect found for most conditioned TPS100CAx and/or (TPS100CA0.1)xPLAy specimens are apparently due to the efficient blocking of the moisture-absorbing hydroxyl groups (free or hydrogen bonded) by hydrogen-bonding CA with starch molecules during their modification processes.

Keywords: thermoplastic starch, hydrogen-bonding, water proof, strength retention

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23333 A Review on the Comparison of EU Countries Based on Research and Development Efficiencies

Authors: Yeliz Ekinci, Raife Merve Ön

Abstract:

Nowadays, technological progress is one of the most important components of economic growth and the efficiency of R&D activities is particularly essential for countries. This study is an attempt to analyze the R&D efficiencies of EU countries. The indicators related to R&D efficiencies should be determined in advance in order to use DEA. For this reason a list of input and output indicators are derived from the literature review. Considering the data availability, a final list is given for the numerical analysis for future research.

Keywords: data envelopment analysis, economic growth, EU countries, R&D efficiency

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23332 Study on Wireless Transmission for Reconnaissance UAV with Wireless Sensor Network and Cylindrical Array of Microstrip Antennas

Authors: Chien-Chun Hung, Chun-Fong Wu

Abstract:

It is important for a commander to have real-time information to aware situations and to make decision in the battlefield. Results of modern technique developments have brought in this kind of information for military purposes. Unmanned aerial vehicle (UAV) is one of the means to gather intelligence owing to its widespread applications. It is still not clear whether or not the mini UAV with short-range wireless transmission system is used as a reconnaissance system in Taiwanese. In this paper, previous experience on the research of the sort of aerial vehicles has been applied with a data-relay system using the ZigBee modulus. The mini UAV developed is expected to be able to collect certain data in some appropriate theaters. The omni-directional antenna with high gain is also integrated into mini UAV to fit the size-reducing trend of airborne sensors. Two advantages are so far obvious. First, mini UAV can fly higher than usual to avoid being attacked from ground fires. Second, the data will be almost gathered during all maneuvering attitudes.

Keywords: mini UAV, reconnaissance, wireless transmission, ZigBee modulus

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23331 Optimal Design of Step-Stress Partially Life Test Using Multiply Censored Exponential Data with Random Removals

Authors: Showkat Ahmad Lone, Ahmadur Rahman, Ariful Islam

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The major assumption in accelerated life tests (ALT) is that the mathematical model relating the lifetime of a test unit and the stress are known or can be assumed. In some cases, such life–stress relationships are not known and cannot be assumed, i.e. ALT data cannot be extrapolated to use condition. So, in such cases, partially accelerated life test (PALT) is a more suitable test to be performed for which tested units are subjected to both normal and accelerated conditions. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests using progressive failure-censored hybrid data with random removals. The life data of the units under test is considered to follow exponential life distribution. The removals from the test are assumed to have binomial distributions. The point and interval maximum likelihood estimations are obtained for unknown distribution parameters and tampering coefficient. An optimum test plan is developed using the D-optimality criterion. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: binomial distribution, d-optimality, multiple censoring, optimal design, partially accelerated life testing, simulation study

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23330 A Real Time Development Study for Automated Centralized Remote Monitoring System at Royal Belum Forest

Authors: Amri Yusoff, Shahrizuan Shafiril, Ashardi Abas, Norma Che Yusoff

Abstract:

Nowadays, illegal logging has been causing much effect to our forest. Some of it causes a flash flood, avalanche, global warming, and etc. This comprehensibly makes us wonder why, what, and who has made it happened. Often, it already has been too late after we have known the cause of it. Even the Malaysian Royal Belum forest has not been spared from land clearing or illegal activity by the natives although this area has been gazetted as a protected area preserved for future generations. Furthermore, because of its sizeable and wide area, these illegal activities are difficult to monitor and to maintain. A critical action must be called upon to prevent all of these unhealthy activities from recurrence. Therefore, a remote monitoring device must be developed in order to capture critical real-time data such as temperature, humidity, gaseous, fire, and rain detection which indicates the current and preserved natural state and habitat in the forest. Besides, this device location can be detected via GPS by showing the latitudes and longitudes of its current location and then to be transmitted by SMS via GSM system. All of its readings will be sent in real-time for data management and analysis. This result will be benefited to the monitoring bodies or relevant authority in keeping the forest in the natural habitat. Furthermore, this research is to gather a unified data and then will be analysed for its comparison with an existing method.

Keywords: remote monitoring system, forest data, GSM, GPS, wireless sensor

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23329 Exploring the Inter-firm Collaborating and Supply Chain Innovation in the Pharmaceutical Industry

Authors: Fatima Gouiferda

Abstract:

Uncertainty and competitiveness are changing firm’s environment to become more complicated. The competition is moving to supply chain’s level, and firms need to collaborate and innovate to survive. In the current economy, common efforts between organizations and developing new capacities mutually are the key resources in gaining collaborative advantage and enhancing supply chain performance. The purpose of this paper is to explore different practices of collaboration activities that exist in the pharmaceutical industry of Morocco. Also, to inquire how these practices affect supply chain performance. The exploration is based on interpretativism research paradigm. Data were collected through semi-structured interviews from supply chain practitioners. Qualitative data was analyzed via Iramuteq software to explore different themes of the study.The findings include descriptive analysis as a result of data processing using Iramuteq. It also encompasses the content analysis of the themes extracted from interviews.

Keywords: inter-firm relationships, collaboration, supply chain innovation, morocco

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23328 Grid and Market Integration of Large Scale Wind Farms using Advanced Predictive Data Mining Techniques

Authors: Umit Cali

Abstract:

The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

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23327 Climate Change and Its Impact on Water Security and Health in Coastal Community: A Gender Outlook

Authors: Soorya Vennila

Abstract:

The present study answers the questions; how does climate change affect the water security in drought prone Ramanathapuram district? and what has water insecurity done to the health of the coastal community? The study area chosen is Devipattinam in Ramanathapuram district. Climate change evidentially wreaked havoc on the community with saltwater intrusion, water quality degradation, water scarcity and its eventual economic, social like power inequality within family and community and health hazards. The climatological data such as rainfall, minimum temperature and maximum temperature were statistically analyzed for trend using Mann-Kendall test. The test was conducted for 14 years (1989-2002) of rainfall data, maximum and minimum temperature and the data were statistically analyzed. At the outset, the water quality samples were collected from Devipattinam to test its physical and chemical parameters and their spatial variation. The results were derived as shown in ARC GIS. Using the water quality test water quality index were framed. And finally, key Informant interview, questionnaire were conducted to capture the gender perception and problem. The data collected were thereafter interpreted using SPSS software for recommendations and suggestions to overcome water scarcity and health problems.

Keywords: health, watersecurity, water quality, climate change

Procedia PDF Downloads 79
23326 Communication of Sensors in Clustering for Wireless Sensor Networks

Authors: Kashish Sareen, Jatinder Singh Bal

Abstract:

The use of wireless sensor networks (WSNs) has grown vastly in the last era, pointing out the crucial need for scalable and energy-efficient routing and data gathering and aggregation protocols in corresponding large-scale environments. Wireless Sensor Networks have now recently emerged as a most important computing platform and continue to grow in diverse areas to provide new opportunities for networking and services. However, the energy constrained and limited computing resources of the sensor nodes present major challenges in gathering data. The sensors collect data about their surrounding and forward it to a command centre through a base station. The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) as they are very useful in target detecting and other applications. However, hierarchical clustering protocols have maximum been used in to overall system lifetime, scalability and energy efficiency. In this paper, the state of the art in corresponding hierarchical clustering approaches for large-scale WSN environments is shown.

Keywords: clustering, DLCC, MLCC, wireless sensor networks

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23325 Democratic Political Culture of the 5th and 6th Graders under the Authority of Dusit District Office, Bangkok

Authors: Vilasinee Jintalikhitdee, Phusit Phukamchanoad, Sakapas Saengchai

Abstract:

This research aims to study the level of democratic political culture and the factors that affect the democratic political culture of 5th and 6th graders under the authority of Dusit District Office, Bangkok by using stratified sampling for probability sampling and using purposive sampling for non-probability sampling to collect data toward the distribution of questionnaires to 300 respondents. This covers all of the schools under the authority of Dusit District Office. The researcher analyzed the data by using descriptive statistics which include arithmetic mean, standard deviation, and inferential statistics which are Independent Samples T-test (T-test) and One-Way ANOVA (F-test). The researcher also collected data by interviewing the target groups, and then analyzed the data by the use of descriptive analysis. The result shows that 5th and 6th graders under the authority of Dusit District Office, Bangkok have exposed to democratic political culture at high level in overall. When considering each part, it found out that the part that has highest mean is “the constitutional democratic governmental system is suitable for Thailand” statement. The part with the lowest mean is “corruption (cheat and defraud) is normal in Thai society” statement. The factor that affects democratic political culture is grade levels, occupations of mothers, and attention in news and political movements.

Keywords: democratic, political culture, political movements, democratic governmental system

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23324 Saudi Human Awareness Needs: A Survey in How Human Causes Errors and Mistakes Leads to Leak Confidential Data with Proposed Solutions in Saudi Arabia

Authors: Amal Hussain Alkhaiwani, Ghadah Abdullah Almalki

Abstract:

Recently human errors have increasingly become a very high factor in security breaches that may affect confidential data, and most of the cyber data breaches are caused by human errors. With one individual mistake, the attacker will gain access to the entire network and bypass the implemented access controls without any immediate detection. Unaware employees will be vulnerable to any social engineering cyber-attacks. Providing security awareness to People is part of the company protection process; the cyber risks cannot be reduced by just implementing technology; the human awareness of security will significantly reduce the risks, which encourage changes in staff cyber-awareness. In this paper, we will focus on Human Awareness, human needs to continue the required security education level; we will review human errors and introduce a proposed solution to avoid the breach from occurring again. Recently Saudi Arabia faced many attacks with different methods of social engineering. As Saudi Arabia has become a target to many countries and individuals, we needed to initiate a defense mechanism that begins with awareness to keep our privacy and protect the confidential data against possible intended attacks.

Keywords: cybersecurity, human aspects, human errors, human mistakes, security awareness, Saudi Arabia, security program, security education, social engineering

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23323 The Quality of Food and Drink Product Labels Translation from Indonesian into English

Authors: Rudi Hartono, Bambang Purwanto

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The translation quality of food and drink labels from Indonesian into English is poor because the translation is not accurate, less natural, and difficult to read. The label translation can be found in some cans packages of food and drink products produced and marketed by several companies in Indonesia. If this problem is left unchecked, it will lead to a misunderstanding on the translation results and make consumers confused. This study was conducted to analyze the translation errors on food and drink products labels and formulate the solution for the better translation quality. The research design was the evaluation research with a holistic criticism approach. The data used were words, phrases, and sentences translated from Indonesian to English language printed on food and drink product labels. The data were processed by using Interactive Model Analysis that carried out three main steps: collecting, classifying, and verifying data. Furthermore, the data were analyzed by using content analysis to view the accuracy, naturalness, and readability of translation. The results showed that the translation quality of food and drink product labels from Indonesian to English has the level of accuracy (60%), level of naturalness (50%), and level readability (60%). This fact needs a help to create an effective strategy for translating food and drink product labels later.

Keywords: translation quality, food and drink product labels, a holistic criticism approach, interactive model, content analysis

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23322 Supervised Machine Learning Approach for Studying the Effect of Different Joint Sets on Stability of Mine Pit Slopes Under the Presence of Different External Factors

Authors: Sudhir Kumar Singh, Debashish Chakravarty

Abstract:

Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

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23321 A Patent Trend Analysis for Hydrogen Based Ironmaking: Identifying the Technology’s Development Phase

Authors: Ebru Kaymaz, Aslı İlbay Hamamcı, Yakup Enes Garip, Samet Ay

Abstract:

The use of hydrogen as a fuel is important for decreasing carbon emissions. For the steel industry, reducing carbon emissions is one of the most important agendas of recent times globally. Because of the Paris Agreement requirements, European steel industry studies on green steel production. Although many literature reviews have analyzed this topic from technological and hydrogen based ironmaking, there are very few studies focused on patents of decarbonize parts of the steel industry. Hence, this study focus on technological progress of hydrogen based ironmaking and on understanding the main trends through patent data. All available patent data were collected from Questel Orbit. The trend analysis of more than 900 patent documents has been carried out by using Questel Orbit Intellixir to analyze a large number of data for scientific intelligence.

Keywords: hydrogen based ironmaking, DRI, direct reduction, carbon emission, steelmaking, patent analysis

Procedia PDF Downloads 145
23320 The Effect of Primary Treatment on Histopathological Patterns and Choice of Neck Dissection in Regional Failure of Nasopharyngeal Carcinoma Patients

Authors: Ralene Sim, Stefan Mueller, N. Gopalakrishna Iyer, Ngian Chye Tan, Khee Chee Soo, R. Shetty Mahalakshmi, Hiang Khoon Tan

Abstract:

Background: Regional failure in nasopharyngeal carcinoma (NPC) is managed by salvage treatment in the form of neck dissection. Radical neck dissection (RND) is preferred over modified radical neck dissection (MRND) since it is traditionally believed to offer better long-term disease control. However, with the advent of more advanced imaging modalities like high-resolution Magnetic Resonance Imaging, Computed Tomography, and Positron Emission Tomography-CT scans, earlier detection is achieved. Additionally, concurrent chemotherapy also contributes to reduced tumour burden. Hence, there may be a lesser need for an RND and a greater role for MRND. With this retrospective study, the primary aim is to ascertain whether MRND, as opposed to RND, has similar outcomes and hence, whether there would be more grounds to offer a less aggressive procedure to achieve lower patient morbidity. Methods: This is a retrospective study of 66 NPC patients treated at Singapore General Hospital between 1994 to 2016 for histologically proven regional recurrence, of which 41 patients underwent RND and 25 who underwent MRND, based on surgeon preference. The type of ND performed, primary treatment mode, adjuvant treatment, and pattern of recurrence were reviewed. Overall survival (OS) was calculated using Kaplan-Meier estimate and compared. Results: Overall, the disease parameters such as nodal involvement and extranodal extension were comparable between the two groups. Comparing MRND and RND, the median (IQR) OS is 1.76 (0.58 to 3.49) and 2.41 (0.78 to 4.11) respectively. However, the p-value found is 0.5301 and hence not statistically significant. Conclusion: RND is more aggressive and has been associated with greater morbidity. Hence, with similar outcomes, MRND could be an alternative salvage procedure for regional failure in selected NPC patients, allowing similar salvage rates with lesser mortality and morbidity.

Keywords: nasopharyngeal carcinoma, neck dissection, modified neck dissection, radical neck dissection

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23319 Fuzzy Logic Classification Approach for Exponential Data Set in Health Care System for Predication of Future Data

Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

Abstract:

Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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23318 Evaluation of Symptoms, Laboratory Findings, and Natural History of IgE Mediated Wheat Allergy

Authors: Soudeh Tabashi, Soudabeh Fazeli Dehkordy, Masood Movahedi, Nasrin Behniafard

Abstract:

Introduction: Food allergy has increased in three last decades. Since wheat is one of the major constituents of daily meal in many regions throughout the world, wheat allergy is one of the most important allergies ranking among the 8 most common types of food allergies. Our information about epidemiology and etiology of food allergies are limited. Therefore, in this study we sought to evaluate the symptoms and laboratory findings in children with wheat allergy. Materials and methods: There were 23 patients aged up to 18 with the diagnosis of IgE mediated wheat allergy that were included enrolled in this study. Using a questionnaire .we collected their information and organized them into 4 groups categories of: demographic data identification, signs and symptoms, comorbidities, and laboratory data. Then patients were followed up for 6 month and their lab data were compared together. Results: Most of the patients (82%) presented the symptoms of wheat allergy in the first year of their life. The skin and the respiratory system were the most commonly involved organs with an incidence of 86% and 78% respectively. Most of the patients with wheat allergy were also sensitive to the other type of foods and their sensitivity to egg were most common type (47%). in 57% of patients, IgE levels were decreased during the 6 month follow-up period. Conclusion: We do not have enough information about data on epidemiology and response to therapy of wheat allergy and to best of our knowledge no study has addressed this issue in Iran so far. This study is the first source of information about IgE mediated wheat allergy in Iran and It can provide an opening for future studies about wheat allergy and its treatments.

Keywords: wheat allergy, food allergy, IgE, food allergy

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23317 Development of a Low-Cost Smart Insole for Gait Analysis

Authors: S. M. Khairul Halim, Mojtaba Ghodsi, Morteza Mohammadzaheri

Abstract:

Gait analysis is essential for diagnosing musculoskeletal and neurological conditions. However, current methods are often complex and expensive. This paper introduces a methodology for analysing gait parameters using a smart insole with a built-in accelerometer. The system measures stance time, swing time, step count, and cadence and wirelessly transmits data to a user-friendly IoT dashboard for centralized processing. This setup enables remote monitoring and advanced data analytics, making it a versatile tool for medical diagnostics and everyday usage. Integration with IoT enhances the portability and connectivity of the device, allowing for secure, encrypted data access over the Internet. This feature supports telemedicine and enables personalized treatment plans tailored to individual needs. Overall, the approach provides a cost-effective (almost 25 GBP), accurate, and user-friendly solution for gait analysis, facilitating remote tracking and customized therapy.

Keywords: gait analysis, IoT, smart insole, accelerometer sensor

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23316 Comparison between Some of Robust Regression Methods with OLS Method with Application

Authors: Sizar Abed Mohammed, Zahraa Ghazi Sadeeq

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The use of the classic method, least squares (OLS) to estimate the linear regression parameters, when they are available assumptions, and capabilities that have good characteristics, such as impartiality, minimum variance, consistency, and so on. The development of alternative statistical techniques to estimate the parameters, when the data are contaminated with outliers. These are powerful methods (or resistance). In this paper, three of robust methods are studied, which are: Maximum likelihood type estimate M-estimator, Modified Maximum likelihood type estimate MM-estimator and Least Trimmed Squares LTS-estimator, and their results are compared with OLS method. These methods applied to real data taken from Duhok company for manufacturing furniture, the obtained results compared by using the criteria: Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Sum of Absolute Error (MSAE). Important conclusions that this study came up with are: a number of typical values detected by using four methods in the furniture line and very close to the data. This refers to the fact that close to the normal distribution of standard errors, but typical values in the doors line data, using OLS less than that detected by the powerful ways. This means that the standard errors of the distribution are far from normal departure. Another important conclusion is that the estimated values of the parameters by using the lifeline is very far from the estimated values using powerful methods for line doors, gave LTS- destined better results using standard MSE, and gave the M- estimator better results using standard MAPE. Moreover, we noticed that using standard MSAE, and MM- estimator is better. The programs S-plus (version 8.0, professional 2007), Minitab (version 13.2) and SPSS (version 17) are used to analyze the data.

Keywords: Robest, LTS, M estimate, MSE

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23315 Tree Resistance to Wind Storm: The Effects of Soil Saturation on Tree Anchorage of Young Pinus pinaster

Authors: P. Defossez, J. M. Bonnefond, D. Garrigou, P. Trichet, F. Danjon

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Windstorm damage to European forests has ecological, social and economic consequences of major importance. Most trees during storms are uprooted. While a large amount of work has been done over the last decade on understanding the aerial tree response to turbulent wind flow, much less is known about the root-soil interface, and the impact of soil moisture and root-soil system fatiguing on tree uprooting. Anchorage strength is expected to be reduced by water-logging and heavy rain during storms due to soil strength decrease with soil water content. Our paper is focused on the maritime pine cultivated on sandy soil, as a representative species of the Forêt des Landes, the largest cultivated forest in Europe. This study aims at providing knowledge on the effects of soil saturation on root anchorage. Pulling experiments on trees were performed to characterize the resistance to wind by measuring the critical bending moment (Mc). Pulling tests were performed on 12 maritime pines of 13-years old for two unsaturated soil conditions that represent the soil conditions expected in winter when wind storms occur in France (w=11.46 to 23.34 % gg⁻¹). A magnetic field digitizing technique was used to characterize the three-dimensional architecture of root systems. The soil mechanical properties as function of soil water content were characterized by laboratory mechanical measurements as function of soil water content and soil porosity on remolded samples using direct shear tests at low confining pressure ( < 15 kPa). Remarkably Mc did not depend on w but mainly on the root system morphology. We suggested that the importance of soil water conditions on tree anchorage depends on the tree size. This study gives a new insight on young tree anchorage: roots may sustain by themselves anchorage, whereas adhesion between roots and surrounding soil may be negligible in sandy soil.

Keywords: roots, sandy soil, shear strength, tree anchorage, unsaturated soil

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23314 Hybrid Fuzzy Weighted K-Nearest Neighbor to Predict Hospital Readmission for Diabetic Patients

Authors: Soha A. Bahanshal, Byung G. Kim

Abstract:

Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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23313 The Comparison of Joint Simulation and Estimation Methods for the Geometallurgical Modeling

Authors: Farzaneh Khorram

Abstract:

This paper endeavors to construct a block model to assess grinding energy consumption (CCE) and pinpoint blocks with the highest potential for energy usage during the grinding process within a specified region. Leveraging geostatistical techniques, particularly joint estimation, or simulation, based on geometallurgical data from various mineral processing stages, our objective is to forecast CCE across the study area. The dataset encompasses variables obtained from 2754 drill samples and a block model comprising 4680 blocks. The initial analysis encompassed exploratory data examination, variography, multivariate analysis, and the delineation of geological and structural units. Subsequent analysis involved the assessment of contacts between these units and the estimation of CCE via cokriging, considering its correlation with SPI. The selection of blocks exhibiting maximum CCE holds paramount importance for cost estimation, production planning, and risk mitigation. The study conducted exploratory data analysis on lithology, rock type, and failure variables, revealing seamless boundaries between geometallurgical units. Simulation methods, such as Plurigaussian and Turning band, demonstrated more realistic outcomes compared to cokriging, owing to the inherent characteristics of geometallurgical data and the limitations of kriging methods.

Keywords: geometallurgy, multivariate analysis, plurigaussian, turning band method, cokriging

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23312 Preparation Nanocapsules of Chitosan Modified With Selenium Extracted From the Lactobacillus Acidophilus and Their Anticancer Properties

Authors: Akbar Esmaeili, Mahnoosh Aliahmadi

Abstract:

This study synthesized a modified imaging of gallium@deferoxamine/folic acid/chitosan/polyaniline/polyvinyl alcohol (Ga@DFA/FA/CS/PANI/PVA). It contains Morus nigra extract by selenium nanoparticles prepared from Lactobacillus acidophilus. Using the impregnation method, Se nanoparticles were then deposited on (Ga@DFA/FA/ CS/PANI/PVA). The modified contrast agents were mixed with M. nigra extract, and investigated their antibacterial activities by applying to L929 cell lines. The influence of variable factors, including 1. surfactant, 2. solvent, 3. aqueous phase, 4. pH, 5. buffer, 6. minimum Inhibitory concentration (MIC), 7. minimum bactericidal concentration (MBC), 8. cytotoxicity on cancer cells., 9. antibiotic, 10. antibiogram, 11. release and loading, 12. the emotional effect, 13. the concentration of nanoparticles, 14. olive oil, and 15. they have investigated thermotical methods. The structure and morphology of the synthesized contrast agents were characterized by zeta potential sizer analysis (ZPS), X-Ray diffraction (XRD), Fourier-transform infrared (FT-IR), energy dispersive X-ray (EDX), ultraviolet–visible (UV–Vis) spectra, and scanning electron microscope (SEM). The experimental section was conducted and monitored by response surface methods (RSM), MTT, MIC, MBC, and cancer cytotoxic conversion assay. Antibiogram testing of NCs on Pseudomonas aeruginosa bacteria was successful and obtained MIC = 2 factors with less harmful effect. All experimental sections confirmed that our synthesized particles have potent antioxidant properties. Antibiogram testing revealed that NPS could kill P. aeruginosa and P. aeruginosa. A variety of synthetic conditions were done by diffusion emulsion method by varying parameters, the optimum state of DFA release Ga@DFA/FA/CS/PANI/PVA NPs (6 ml) with pH = 5.5, time = 3 h, NCs and DFA (3 mg), and achieved buffer (20 ml). DFA in Ga@DFA/FA/ CS/PANI/PVA was released and showed an absorption peak at 378 nm by applying a 300-rpm magnetic rate. In this report, Ga decreased the harmful effect on the human body.

Keywords: nanocapsules, technolgy, biology, nano

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23311 Deriving Generic Transformation Matrices for Multi-Axis Milling Machine

Authors: Alan C. Lin, Tzu-Kuan Lin, Tsong Der Lin

Abstract:

This paper proposes a new method to find the equations of transformation matrix for the rotation angles of the two rotational axes and the coordinates of the three linear axes of an orthogonal multi-axis milling machine. This approach provides intuitive physical meanings for rotation angles of multi-axis machines, which can be used to evaluate the accuracy of the conversion from CL data to NC data.

Keywords: CAM, multi-axis milling machining, transformation matrix, rotation angles

Procedia PDF Downloads 482
23310 A Stepwise Approach to Automate the Search for Optimal Parameters in Seasonal ARIMA Models

Authors: Manisha Mukherjee, Diptarka Saha

Abstract:

Reliable forecasts of univariate time series data are often necessary for several contexts. ARIMA models are quite popular among practitioners in this regard. Hence, choosing correct parameter values for ARIMA is a challenging yet imperative task. Thus, a stepwise algorithm is introduced to provide automatic and robust estimates for parameters (p; d; q)(P; D; Q) used in seasonal ARIMA models. This process is focused on improvising the overall quality of the estimates, and it alleviates the problems induced due to the unidimensional nature of the methods that are currently used such as auto.arima. The fast and automated search of parameter space also ensures reliable estimates of the parameters that possess several desirable qualities, consequently, resulting in higher test accuracy especially in the cases of noisy data. After vigorous testing on real as well as simulated data, the algorithm doesn’t only perform better than current state-of-the-art methods, it also completely obviates the need for human intervention due to its automated nature.

Keywords: time series, ARIMA, auto.arima, ARIMA parameters, forecast, R function

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23309 Effect of Temperature and Deformation Mode on Texture Evolution of AA6061

Authors: M. Ghosh, A. Miroux, L. A. I. Kestens

Abstract:

At molecular or micrometre scale, practically all materials are neither homogeneous nor isotropic. The concept of texture is used to identify the structural features that cause the properties of a material to be anisotropic. For metallic materials, the anisotropy of the mechanical behaviour originates from the crystallographic nature of plastic deformation, and is therefore controlled by the crystallographic texture. Anisotropy in mechanical properties often constitutes a disadvantage in the application of materials, as it is often illustrated by the earing phenomena during drawing. However, advantages may also be attained when considering other properties (e.g. optimization of magnetic behaviour to a specific direction) by controlling texture through thermo-mechanical processing). Nevertheless, in order to have better control over the final properties it is essential to relate texture with materials processing route and subsequently optimise their performance. However, up to date, few studies have been reported about the evolution of texture in 6061 aluminium alloy during warm processing (from room temperature to 250ºC). In present investigation, recrystallized 6061 aluminium alloy samples were subjected to tensile and plane strain compression (PSC) at room and warm temperatures. The gradual change of texture following both deformation modes were measured and discussed. Tensile tests demonstrate the mechanism at low strain while PSC does the same at high strain and eventually simulate the condition of rolling. Cube dominated texture of the initial rolled and recrystallized AA6061 sheets were replaced by domination of S and R components after PSC at room temperature, warm temperature (250ºC) though did not reflect any noticeable deviation from room temperature observation. It was also noticed that temperature has no significant effect on the evolution of grain morphology during PSC. The band contrast map revealed that after 30% deformation the substructure inside the grain is mainly made of series of parallel bands. A tendency for decrease of Cube and increase of Goss was noticed after tensile deformation compared to as-received material. Like PSC, texture does not change after deformation at warm temperature though. n-fibre was noticed for all the three textures from Goss to Cube.

Keywords: AA 6061, deformation, temperature, tensile, PSC, texture

Procedia PDF Downloads 485
23308 Building Biodiversity Conservation Plans Robust to Human Land Use Uncertainty

Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

Abstract:

Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

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23307 Decision-Making Strategies on Smart Dairy Farms: A Review

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

Abstract:

Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

Procedia PDF Downloads 189