Search results for: fault tree analysis (FTA) method

Authors: Ada Yurman

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Social reactions to deviant groups with political goals follow two central patterns; one that associates personal characteristics with deviant behavior, and the other that claims that society is to be blamed for deviant behavior. The establishment usually tends towards the former notion and thus disclaims any responsibility for the distress of the underprivileged, while it is usually those who oppose government policies who believe that the fault lies with society. The purpose of the present research was to examine social reactions to the Wadi Salib riots that occurred in Haifa in 1959. These riots represented the first ethnic protest within Israeli society with its ideology of the ingathering of the exiles. The central question was whether this ideology contributed to the development of a different reaction when compared to reactions to similar events abroad. This question was examined by means of analyzing articles in the Israeli press of that period. The Israeli press representing the views of the establishment was at pains to point out that the rioters were criminals, their object being to obstruct the development of society. Opposition party leaders claimed that the rioters lived in poor circumstances, which constituted a direct result of government policies. An analysis of press reports on the Wadi Salib riots indicates a correspondence between the reaction to these events and similar events abroad. Nevertheless, the reaction to the Wadi Salib riots did not only express a conflict between different political camps, but also different symbolic universes. Each group exploited the events at Wadi Salib to prove that their ideology was the legitimate one.

Keywords: riots, media, political deviance, symbolic universe

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Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain

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The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.

Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR

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Authors: S. Al-Khalasi, O. Mahgoub, H. Yaakub

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This study evaluated the use of raw or processed Prosopis juliflora (Meskit) pods as a major ingredient in a formulated ration to provide an alternative non-conventional concentrate for livestock feeding in Oman. Dry Meskit pods were reduced to lengths of 0.5- 1.0 cm to ensure thorough mixing into three diets. Meskit pods were subjected to two types of treatments; roasting and soaking. They were roasted at 150оC for 30 minutes using a locally-made roasting device (40 kg barrel container rotated by electric motor and heated by flame gas cooker). Chopped pods were soaked in tap water for 24 hours and dried for 2 days under the sun with frequent turning. The Meskit-pod-based diets (MPBD) were formulated and pelleted from 500 g/kg ground Meskit pods, 240 g/kg wheat bran, 200 g/kg barley grain, 50 g/kg local dried sardines and 10 g/kg of salt. Twenty four 10 months-old intact Omani male lambs with average body weight of 27.3 kg (± 0.5 kg) were used in a feeding trial for 84 days. They were divided (on body weight basis) and allocated to four diet combination groups. These were: Rhodes grass hay (RGH) plus a general ruminant concentrate (GRC); RGH plus raw Meskit pods (RMP) based concentrate; RGH plus roasted Meskit pods (ROMP) based concentrate; RGH plus soaked Meskit pods (SMP) based concentrate Daily feed intakes and bi-weekly body weights were recorded. MPBD had higher contents of crude protein (CP), acid detergent fibre (ADF) and neutral detergent fibre (NDF) than the GRC. Animals fed various types of MPBD did not show signs of ill health. There was a significant effect of feeding ROMP on the performance of Omani sheep compared to RMP and SMP. The ROMP fed animals had similar performance to those fed the GRC in terms of feed intake, body weight gain and feed conversion ratio (FCR).This study indicated that roasted Meskit pods based diet may be used instead of the commercial concentrate for feeding Omani sheep without adverse effects on performance. It offers a cheap alternative source of protein and energy for feeding Omani sheep. Also, it might help in solving the spread impact of Meskit trees, maintain the ecosystem and helping in preserving the local tree species.

Keywords: growth, Meskit, Omani sheep, Prosopis juliflora

Procedia PDF Downloads 455

Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

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The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

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Authors: Apurv Kulkarni, Shreyas Badave, B. Rajiv

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Non-parametric reliability technique is useful for assessment of reliability of systems for which failure rates are not available. This is useful when detection of malfunctioning of any component is the key purpose during ongoing operation of the system. The main purpose of the Heat Exchanger Cycle discussed in this paper is to provide hot water at a constant temperature for longer periods of time. In such a cycle, certain components play a crucial role and this paper presents an effective way to predict the malfunctioning of the components by determination of system reliability. The method discussed in the paper is feasible and this is clarified with the help of various test cases.

Keywords: heat exchanger cycle, k-statistics, PID controller, system reliability

Procedia PDF Downloads 367

Authors: S. A. M. Yatim, Z. B. Ibrahim, K. I. Othman, M. Suleiman

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The method of solving second order stiff ordinary differential equation (ODEs) that is based on backward differentiation formula (BDF) is considered in this paper. We derived the method by increasing the order of the existing method using an improved strategy in choosing the step size. Numerical results are presented to compare the efficiency of the proposed method to the MATLAB’s suite of ODEs solvers namely ode15s and ode23s. The method was found to be efficient to solve second order ordinary differential equation.

Keywords: backward differentiation formulae, block backward differentiation formulae, stiff ordinary differential equation, variable step size

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Authors: Sogol Zarafshan

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The present study aimed to identify important factors affecting the effectiveness of quality control circles in a hospital, as well as rank them using a combination of fuzzy VIKOR and Grey Relational Analysis (GRA). The study population consisted of five academic members and five experts in the field of nursing working in a hospital, who were selected using a purposive sampling method. Also, a sample of 107 nurses was selected through a simple random sampling method using their employee codes and the random-number table. The required data were collected using a researcher-made questionnaire which consisted of 12 factors. The validity of this questionnaire was confirmed through giving the opinions of experts and academic members who participated in the present study, as well as performing confirmatory factor analysis. Its reliability also was verified (α=0.796). The collected data were analyzed using SPSS 22.0 and LISREL 8.8, as well as VIKOR–GRA and IPA methods. The results of ranking the factors affecting the effectiveness of quality control circles showed that the highest and lowest ranks were related to ‘Managers’ and supervisors’ support’ and ‘Group leadership’. Also, the highest hospital performance was for factors such as ‘Clear goals and objectives’ and ‘Group cohesiveness and homogeneity’, and the lowest for ‘Reward system’ and ‘Feedback system’, respectively. The results showed that although ‘Training the members’, ‘Using the right tools’ and ‘Reward system’ were factors that were of great importance, the organization’s performance for these factors was poor. Therefore, these factors should be paid more attention by the studied hospital managers and should be improved as soon as possible.

Keywords: Quality control circles, Fuzzy VIKOR, Grey Relational Analysis, Importance–Performance Analysis

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Authors: Dereje Moges Azbite

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Laboratory analysis of igneous rocks is performed with the help of the main oxide plots. The lithology of the two wells was identified using the main oxides obtained using the XRF method. Twenty-four (24) cutting samples with different degrees of alteration were analyzed to determine and identify the rock types by plotting these well samples on special diagrams and correlating with the regional rocks. The results for the analysis of the main oxides and trace elements of 24 samples are presented. Alteration analysis in the two well samples was conducted for 21 samples from two wells for identifying clay minerals. Bulk sample analysis indicated quartz, illite & micas, calcite, cristobalite, smectite, pyrite, epidote, alunite, chlorite, wairakite, diaspore and kaolin minerals present in both wells. Hydrothermal clay minerals such as illite, chlorite, smectite and kaoline minerals were identified in both wells by X-ray diffraction.

Keywords: auto geothermal field, igneous rocks, major oxides, tracer elements, XRF, XRD, alteration minerals

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Authors: Abbes Lounis, Kahina Louadj, Mohamed Aidene

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This paper presents an optimal control problem applied to a robot; the problem is to determine a command which makes it possible to reach a final state from a given initial state in record time. The approach followed to solve this optimization problem with constraints on the control starts by presenting the equations of motion of the dynamic system then by applying Pontryagin's maximum principle (PMP) to determine the optimal control, and Picard's successive approximation method combined with the shooting method to solve the resulting differential system.

Keywords: robotics, Pontryagin's Maximum Principle, PMP, Picard's method, shooting method, non-linear differential systems

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Authors: Yan Ping Chen, Hau Yin Chung

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The Ideal Profile Method (IPM) is a newly developed descriptive sensory analysis conducted by consumers without previous training. To perform this test, both the perceived and the ideal intensities from the judgements of consumers on products’ attributes, as well as their hedonic ratings were collected for formulating an ideal product (the most liked one). In addition, Ideal Profile Analysis (IPA) was conducted to check the consistency of the ideal data at both the panel and consumer levels. In this test, 12 commercial plain sufus bought from Hong Kong local market were tested by 113 consumers according to the IPM, and rated on 22 attributes. Principal component analysis was used to profile the perceived and the ideal spaces of tested products. The consistency of ideal data was then checked by IPA. The result showed that most consumers shared a common ideal. It was observed that the sensory product space and the ideal product space were structurally similar. Their first dimensions all opposed products with intense fermented related aroma to products with less fermented related aroma. And the predicted ideal profile (the estimated liking score around 7.0 in a 9.0-point scale) got higher hedonic score than the tested products (the average liking score around 6.0 in a 9.0-point scale). For the majority of consumers (95.2%), the stated ideal product considered as a potential ideal through checking the R2 coefficient value. Among all the tested products, sample-6 was the most popular one with consumer liking percentage around 30%. This product with less fermented and moldy flavour but easier to melt in mouth texture possessed close sensory profile according to the ideal product. This experiment validated that data from untrained consumers could be guided as useful information. Appreciated sensory characteristics could be served as reference in the optimization of the commercial plain sufu.

Keywords: ideal profile method, product development, sensory evaluation, sufu (fermented soybean curd)

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Authors: Apedzan Emmanuel Kighir

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This research investigates dividends smoothing among non-financial companies trading on the Nigerian Stock Exchange in an era of unclaimed dividends from 2004 to 2013. There has been a raging controversy among Regulatory Authorities, Company Executives, Registrars of Companies, Shareholders and the general public regarding the increasing incidence of unclaimed dividends in Nigeria. The objective of this study is to find out if corporate earnings management through dividends smoothing is implicated in unclaimed dividends among Nigerian non-financial firms. The research used panel data and employed Generalized Method of Moment as method of analysis. The research finds evidence of dividends-smoothing in this era of unclaimed dividends in Nigeria. The research concludes that dividends-smoothing is a trigger and red flag for unclaimed dividends, an output of earnings management. If earnings management and hence unclaimed dividends in Nigeria is allowed to continue, it will lead to great consequences to the investors and corporate policy of government. It is believed that the research will assist investors and government in making informed decisions regarding dividends policy in Nigeria.

Keywords: dividends smoothing, non financial companies, Nigerian stock exchange, unclaimed dividends, corporate earnings management

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Authors: Kirill Trapezon, Alexandr Trapezon

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A problem is formulated for the natural oscillations of a circular plate of linearly variable thickness on the basis of the symmetry method. The equations of natural frequencies and forms for a plate are obtained, providing that it is rigidly fixed along the inner contour. The first three eigenfrequencies are calculated, and the eigenmodes of the oscillations of the acoustic element are constructed. An algorithm for applying the symmetry method and the factorization method for solving problems in the theory of oscillations for plates of variable thickness is shown. The effectiveness of the approach is demonstrated on the basis of comparison of known results and those obtained in the article. It is shown that the results are more accurate and reliable.

Keywords: vibrations, plate, method of symmetries, differential equation, factorization, approximation

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Authors: Fathi Alwafie

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In this paper we present the simulation of the propagation characteristics of the picocellular propagation channel environment. The first aim has been to find a correct description of the environment for received wave. The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A modified 3D ray tracing image method tool has been utilized for the coverage prediction. A detailed analysis of the dependence of the indoor wave on the wide-band characteristics of the channel: Root Mean Square (RMS) delay spread characteristics and mean excess delay, is also investigated.

Keywords: propagation, ray tracing, network, mobile computing

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Authors: Ortiz M. Rocío, Rocha G. Karina, Domenech A. Gloria

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There are several tools to assess the nutritional status of the population. A main instrument commonly used to build those tools is the food composition tables (FCT). Despite the importance of FCT, there are many error sources and variability factors that can be presented on building those tables and can lead to an under or over estimation of ingest of nutrients of a population. This work identified different food composition tables used as an instrument to estimate the nutrient ingest in Ecuador.The collection of data for choosing FCT was made through key informants –self completed questionnaires-, supplemented with institutional web research. A questionnaire with general variables (origin, year of edition, etc) and methodological variables (method of elaboration, information of the table, etc) was passed to the identified FCT. Those variables were defined based on an extensive literature review. A descriptive analysis of content was performed. Ten printed tables and three databases were reported which were all indistinctly treated as food composition tables. We managed to get information from 69% of the references. Several informants referred to printed documents that were not accessible. In addition, searching the internet was not successful. Of the 9 final tables, n=8 are from Latin America, and, n= 5 of these were constructed by indirect method (collection of already published data) having as a main source of information a database from the United States department of agriculture USDA. One FCT was constructed by using direct method (bromatological analysis) and has its origin in Ecuador. The 100% of the tables made a clear distinction of the food and its method of cooking, 88% of FCT expressed values of nutrients per 100g of edible portion, 77% gave precise additional information about the use of the table, and 55% presented all the macro and micro nutrients on a detailed way. The more complete FCT were: INCAP (Central America), Composition of foods (Mexico). The more referred table was: Ecuadorian food composition table of 1965 (70%). The indirect method was used for most tables within this study. However, this method has the disadvantage that it generates less reliable food composition tables because foods show variations in composition. Therefore, a database cannot accurately predict the composition of any isolated sample of a food product.In conclusion, analyzing the pros and cons, and, despite being a FCT elaborated by using an indirect method, it is considered appropriate to work with the FCT of INCAP Central America, given the proximity to our country and a food items list that is very similar to ours. Also, it is imperative to have as a reference the table of composition for Ecuadorian food, which, although is not updated, was constructed using the direct method with Ecuadorian foods. Hence, both tables will be used to elaborate a questionnaire with the purpose of assessing the food consumption of the Ecuadorian population. In case of having disparate values, we will proceed by taking just the INCAP values because this is an updated table.

Keywords: Ecuadorian food composition tables, FCT elaborated by direct method, ingest of nutrients of Ecuadorians, Latin America food composition tables

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Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

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This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

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Authors: Maysam Shahsavari, Seyed Jamalaldin Haddadi

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There are several methods to localize a mobile robot such as relative, absolute and probabilistic. In this paper, particle filter due to its simple implementation and the fact that it does not need to know to the starting position will be used. This method estimates the position of the mobile robot using a probabilistic distribution, relying on a known map of the environment instead of predicting it. Afterwards, it updates this estimation by reading input sensors and control commands. To receive information from the surrounding world, distance to obstacles, for example, a Kinect is used which is much cheaper than a laser range finder. Finally, after explaining the Adaptive Particle Filter method and its implementation in detail, we will compare this method with the dead reckoning method and show that this method is much more suitable for situations in which we have a map of the environment.

Keywords: particle filter, localization, methods, odometry, kinect

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Authors: Mohammad Mojtahedpoor

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In this paper, it has been studied the method of optimal design of the supersonic nozzle. It could make viscous axisymmetric nozzles that the quality of their outlet flow is quite desired. In this method, it is optimized the divergent nozzle, at first. The initial divergent nozzle contour is designed through the method of characteristics and adding a suitable boundary layer to the inviscid contour. After that, it is made a proper grid and then simulated flow by the numerical solution and AUSM+ method by using the operation boundary condition. At the end, solution outputs are investigated and optimized. The numerical method has been validated with experimental results. Also, in order to evaluate the effectiveness of the present method, the nozzles compared with the previous studies. The comparisons show that the nozzles obtained through this method are sufficiently better in some conditions, such as the flow uniformity, size of the boundary layer, and obtained an axial length of the nozzle. Designing the convergent nozzle part affects by flow uniformity through changing its axial length and input diameter. The results show that increasing the length of the convergent part improves the output flow uniformity.

Keywords: nozzle, supersonic, optimization, characteristic method, CFD

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Authors: Riaan Kleyn

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Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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Authors: Assiya Madenovna Borsynbayeva, Kairat Altynbekovich Turgenbayev, Nikolay Petrovich Ivanov

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In this article presents the results of rapid diagnostics of tuberculosis in comparison with classical bacteriological method. The proposed method of rapid diagnosis of tuberculosis than bacteriological method allows shortening the time of diagnosis to 7 days, to visualize the growth of mycobacteria in the semi-liquid medium and differentiate the type of mycobacterium. Fast definition of Mycobacterium tuberculosis and its derivatives in the culture medium is a new and promising direction in the diagnosis of tuberculosis.

Keywords: animal diagnosis of tuberculosis, bacteriological diagnostics, antigen, specific antibodies, immunological reaction

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Authors: M. Y. Malik, Farzana Khan

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In this article, we discuss the behavior of viscous fluid near stagnation point over a stretching cylinder with variable thermal conductivity. The effects of slip conditions are also encountered. Thermal conductivity is considered as a linear function of temperature. By using homotopy analysis method and Fehlberg method we compare the graphical results for both momentum and energy equations. The effect of different parameters on velocity and temperature fields are shown graphically.

Keywords: slip conditions, stretching cylinder, heat generation/absorption, stagnation point flow, variable thermal conductivity

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Suchi Barua, Narottam Das, Sven Nordholm, Mohammad Razaghi

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This paper presents nonlinear pulse propagation characteristics for different input optical pulse shapes with various input pulse energy levels in semiconductor optical amplifiers. For simulation of nonlinear pulse propagation, finite-difference beam propagation method is used to solve the nonlinear Schrödinger equation. In this equation, gain spectrum dynamics, gain saturation are taken into account which depends on carrier depletion, carrier heating, spectral-hole burning, group velocity dispersion, self-phase modulation and two photon absorption. From this analysis, we obtained the output waveforms and spectra for different input pulse shapes as well as for different input energies. It shows clearly that the peak position of the output waveforms are shifted toward the leading edge which due to the gain saturation of the SOA for higher input pulse energies. We also analyzed and compared the normalized difference of full-width at half maximum for different input pulse shapes in the SOA.

Keywords: finite-difference beam propagation method, pulse shape, pulse propagation, semiconductor optical amplifier

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Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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Authors: Alsaidi M. Altaher, Mohd Tahir Ismail

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Wavelet thresholding has been a power tool in curve estimation and data analysis. In the presence of outliers this non parametric estimator can not suppress the outliers involved. This study proposes a new two-stage combined method based on the use of the median filter as primary step before applying wavelet thresholding. After suppressing the outliers in a signal through the median filter, the classical wavelet thresholding is then applied for removing the remaining noise. We use automatic boundary corrections; using a low order polynomial model or local polynomial model as a more realistic rule to correct the bias at the boundary region; instead of using the classical assumptions such periodic or symmetric. A simulation experiment has been conducted to evaluate the numerical performance of the proposed method. Results show strong evidences that the proposed method is extremely effective in terms of correcting the boundary bias and eliminating outlier’s sensitivity.

Keywords: boundary correction, median filter, simulation, wavelet thresholding

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Authors: S. Madhu, V. V. Subba Rao

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In the implementation of carbon nanotube reinforced polymer matrix composites in structural applications, deflection and stress analysis are important considerations. In the present study, a multi scale analysis of deflection and stress analysis of carbon nanotube (CNT) reinforced polymer composite plates is presented. A micromechanics model based on the Mori-Tanaka method is developed by introducing straight CNTs aligned in one direction. The effect of volume fraction and diameter of CNTs on plate deflection and the stresses are investigated using Classical Laminate Plate Theory (CLPT). The study is primarily conducted with the intention of observing the suitability of CNT reinforced polymer composite plates under static loading for structural applications.

Keywords: carbon nanotube, micromechanics, composite plate, multi-scale analysis, classical laminate plate theory

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Authors: Iryna Biskub

Abstract:

The interdisciplinary approach to modern linguistic studies is exemplified by the merge of various research methods, which sometimes causes complications related to the verification of the research results. This methodological confusion can be resolved by means of creating new techniques of linguistic analysis combining several scientific paradigms. Modern linguistics has developed really productive and efficient methods for the investigation of cognitive and communicative phenomena of which language is the central issue. In the field of discourse studies, one of the best examples of research methods is the method of Critical Discourse Analysis (CDA). CDA can be viewed both as a method of investigation, as well as a critical multidisciplinary perspective. In CDA the position of the scholar is crucial from the point of view exemplifying his or her social and political convictions. The generally accepted approach to obtaining scientifically reliable results is to use a special well-defined scientific method for researching special types of language phenomena: cognitive methods applied to the exploration of cognitive aspects of language, whereas communicative methods are thought to be relevant only for the investigation of communicative nature of language. In the recent decades discourse as a sociocultural phenomenon has been the focus of careful linguistic research. The very concept of discourse represents an integral unity of cognitive and communicative aspects of human verbal activity. Since a human being is never able to discriminate between cognitive and communicative planes of discourse communication, it doesn’t make much sense to apply cognitive and communicative methods of research taken in isolation. It is possible to modify the classical CDA procedure by means of mapping human cognitive procedures onto the strategic communicative planning of discourse communication. The analysis of the electronic petition 'Block Donald J Trump from UK entry. The signatories believe Donald J Trump should be banned from UK entry' (584, 459 signatures) and the parliamentary debates on it has demonstrated the ability to map cognitive and communicative levels in the following way: the strategy of discourse modeling (communicative level) overlaps with the extraction of semantic macrostructures (cognitive level); the strategy of discourse management overlaps with the analysis of local meanings in discourse communication; the strategy of cognitive monitoring of the discourse overlaps with the formation of attitudes and ideologies at the cognitive level. Thus, the experimental data have shown that it is possible to develop a new complex methodology of discourse analysis, where cognition would meet communication, both metaphorically and literally. The same approach may appear to be productive for the creation of computational models of human-computer interaction, where the automatic generation of a particular type of a discourse could be based on the rules of strategic planning involving cognitive models of CDA.

Keywords: cognition, communication, discourse, strategy

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Authors: Hongyu Ye, Hong Zhang, Minjie Sun, Hongfang Xu

Abstract:

In the context of China's promotion of smart construction and building industrialization, there is a need for evaluation standards for the development of building industrialization based on assembly-type construction. However, the evaluation of smart construction remains a challenge in the industry's development process. This paper addresses this issue by proposing a calculation and evaluation method for the smartization rate of concrete structure building construction. The study focuses on examining the factors of smart equipment application and their impact on costs throughout the process of smart construction design, production, transfer, and construction. Based on this analysis, the paper presents an evaluation method for the smartization rate based on components. Furthermore, it introduces calculation methods for assessing the smartization rate of buildings. The paper also suggests a rapid calculation method for determining the smartization rate using Building Information Modeling (BIM) and information expression technology. The proposed research provides a foundation for the swift calculation of the smartization rate based on BIM and information technology. Ultimately, it aims to promote the development of smart construction and the construction of high-quality buildings in China.

Keywords: building industrialization, high quality building, smart construction, smartization rate, component

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Authors: Abubakar Maikudi

Abstract:

Contrastive analysis is the method of analyzing the structure of any two languages with a view to determining the possible differential aspects of their systems irrespective of their genetic affinity or level of development. Contrastive analysis of two languages becomes useful when it is adequately describing the sound structure and grammatical structure of two languages, with comparative statements giving emphasis to the compatible items in the two systems. This research work uses comparative analysis theory to analyze adjective and adjectival phrases in Hausa and Yorùbá languages. The Hausa language belongs to the Chadic family of the Afro-Asiatic phylum, while the Yorùbá language belongs to the Benue-Congo family of the Niger-Congo phylum. The findings of the research clearly demonstrated that there are significant similarities in the adjectival phrase constructions of the two languages, i.e., nominal (Head) and post-nominal (Post-Head) use of the adjective, predicative function of an adjective, use of the reduplicative adjective, use of the comparative and superlative adjective, etc. However, there are dissimilarities in the adjectival phrase of the two languages in gender/number agreement and pre-nominal (Post-Head) use of adjectives.

Keywords: genetic affinity, contrastive analysis, phylum, pre-head, post-head

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Authors: Gilang Maulana Majid

Abstract:

If a government program remains scientifically uncontested for a long time, it is likely that its effects will be far from expected as there is no concrete evaluation of the steps being taken. This article identifies how such a theory aptly describes the case of the 'tourism ambassador' program in Indonesia. Being set out as one of the tourism promotional means of many regional governments in Indonesia, this program is heavily criticized for being ineffective despite a large number of budgets being spent on an annual basis. Taking the program as a case study, this article applies content analysis, SWOT analysis, and TOPSIS as data analysis methods, with a total of 56 tourism ambassadors invited to become coders, respondents, and/or interviewees in this research. The study reveals the SWOT of the program, recognizes four strategies that can be taken to optimize the program's effects and prioritizes a strategy based on the preferences of the involved tourism ambassadors using TOPSIS. It is found that incorporation of technology such as the creation of an online platform is, among others, the most expected approach to be taken to solve the problems concerning tourism ambassador program. However, based on the costs and benefits of each strategy presented in the current study, each alternative appears to have trade-offs between one and another.

Keywords: Indonesia, optimization strategies, 'Tourism Ambassador' program, SWOT-TOPSIS

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Authors: Manuela Villani, Anila Xhahysa, Christopher Brooks, Marco Pagani

Abstract:

The geological structure of Western Balkans is strongly affected by the collision between Adria microplate and the southwestern Euroasia margin, resulting in a considerably active seismic region. The Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project (BSHAP) (2007-2011, 2012-2015) by NATO supported the preparation of new seismic hazard maps of the Western Balkan, but when inspecting the seismic hazard models produced later by these countries on a national scale, significant differences in design PGA values are observed in the border, for instance, North Albania-Montenegro, South Albania- Greece, etc. Considering the fact that the catalogues were unified and seismic sources were defined within BSHAP framework, obviously, the differences arise from the Ground Motion Prediction Equations selection, which are generally the component with highest impact on the seismic hazard assessment. At the time of the project, a modest database was present, namely 672 three-component records, whereas nowadays, this strong motion database has increased considerably up to 20,939 records with Mw ranging in the interval 3.7-7 and epicentral distance distribution from 0.47km to 490km. Statistical analysis of the strong motion database showed the lack of recordings in the moderate-to-large magnitude and short distance ranges; therefore, there is need to re-evaluate the Ground Motion Prediction Equation in light of the recently updated database and the new generations of GMMs. In some cases, it was observed that some events were more extensively documented in one database than the other, like the 1979 Montenegro earthquake, with a considerably larger number of records in the BSHAP Analogue SM database when compared to ESM23. Therefore, the strong motion flat-file provided from the Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project was merged with the ESM23 database for the polygon studied in this project. After performing the preliminary residual analysis, the candidate GMPE-s were identified. This process was done using the GMPE performance metrics available within the SMT in the OpenQuake Platform. The Likelihood Model and Euclidean Distance Based Ranking (EDR) were used. Finally, for this study, a GMPE logic tree was selected and following the selection of candidate GMPEs, model weights were assigned using the average sample log-likelihood approach of Scherbaum.

Keywords: residual analysis, GMPE, western balkan, strong motion, openquake

Procedia PDF Downloads 57