Search results for: adaptive multiple transforms
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5788

Search results for: adaptive multiple transforms

3928 A Study of the Depression Status of Asian American Adolescents

Authors: Selina Lin, Justin M Fan, Vincent Zhang, Cindy Chen, Daniel Lam, Jason Yan, Ning Zhang

Abstract:

Depression is one of the most common mental disorders in the United States, and past studies have shown a concerning increase in the rates of depression in youth populations over time. Furthermore, depression is an especially important issue for Asian Americans because of the anti-Asian violence taking place during the COVID-19 pandemic. While Asian American adolescents are reluctant to seek help for mental health issues, past research has found a prevalence of depressive symptoms in them that have yet to be fully investigated. There have been studies conducted to understand and observe the impacts of multifarious factors influencing the mental well-being of Asian American adolescents; however, they have been generally limited to qualitative investigation, and very few have attempted to quantitatively evaluate the relationship between depression levels and a comprehensive list of factors for those levels at the same time. To better quantify these relationships, this project investigated the prevalence of depression in Asian American teenagers mainly from the Greater Philadelphia Region, aged 12 to 19, and, with an anonymous survey, asked participants 48 multiple-choice questions pertaining to demographic information, daily behaviors, school life, family life, depression levels (quantified by the PHQ-9 assessment), school and family support against depression. Each multiple-choice question was assigned as a factor and variable for statistical and dominance analysis to determine the most influential factors on depression levels of Asian American adolescents. The results were validated via Bootstrap analysis and t-tests. While certain influential factors identified in this survey are consistent with the literature, such as parent-child relationship and peer pressure, several dominant factors were relatively overlooked in the past. These factors include the parents’ relationship with each other, the satisfaction with body image, sex identity, support from the family and support from the school. More than 25% of participants desired more support from their families and schools in handling depression issues. This study implied that it is beneficial for Asian American parents and adolescents to take programs on parents’ relationships with each other, parent-child communication, mental health, and sexual identity. A culturally inclusive school environment and more accessible mental health services would be helpful for Asian American adolescents to combat depression. This survey-based study paved the way for further investigation of effective approaches for helping Asian American adolescents against depression.

Keywords: Asian American adolescents, depression, dominance analysis, t-test, bootstrap analysis

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3927 Optimal Management of Forest Stands under Wind Risk in Czech Republic

Authors: Zohreh Mohammadi, Jan Kaspar, Peter Lohmander, Robert Marusak, Harald Vacik, Ljusk Ola Eriksson

Abstract:

Storms are important damaging agents in European forest ecosystems. In the latest decades, significant economic losses in European forestry occurred due to storms. This study investigates the problem of optimal harvest planning when forest stands risk to be felled by storms. One of the most applicable mathematical methods which are being used to optimize forest management is stochastic dynamic programming (SDP). This method belongs to the adaptive optimization class. Sequential decisions, such as harvest decisions, can be optimized based on sequential information about events that cannot be perfectly predicted, such as the future storms and the future states of wind protection from other forest stands. In this paper, stochastic dynamic programming is used to maximize the expected present value of the profits from an area consisting of several forest stands. The region of analysis is the Czech Republic. The harvest decisions, in a particular time period, should be simultaneously taken in all neighbor stands. The reason is that different stands protect each other from possible winds. The optimal harvest age of a particular stand is a function of wind speed and different wind protection effects. The optimal harvest age often decreases with wind speed, but it cannot be determined for one stand at a time. When we consider a particular stand, this stand also protects other stands. Furthermore, the particular stand is protected by neighbor stands. In some forest stands, it may even be rational to increase the harvest age under the influence of stronger winds, in order to protect more valuable stands in the neighborhood. It is important to integrate wind risk in forestry decision-making.

Keywords: Czech republic, forest stands, stochastic dynamic programming, wind risk

Procedia PDF Downloads 141
3926 Multichannel Object Detection with Event Camera

Authors: Rafael Iliasov, Alessandro Golkar

Abstract:

Object detection based on event vision has been a dynamically growing field in computer vision for the last 16 years. In this work, we create multiple channels from a single event camera and propose an event fusion method (EFM) to enhance object detection in event-based vision systems. Each channel uses a different accumulation buffer to collect events from the event camera. We implement YOLOv7 for object detection, followed by a fusion algorithm. Our multichannel approach outperforms single-channel-based object detection by 0.7% in mean Average Precision (mAP) for detection overlapping ground truth with IOU = 0.5.

Keywords: event camera, object detection with multimodal inputs, multichannel fusion, computer vision

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3925 Decision Support System for Solving Multi-Objective Routing Problem

Authors: Ismail El Gayar, Ossama Ismail, Yousri El Gamal

Abstract:

This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.

Keywords: bus scheduling problem, decision support system, genetic algorithm, shortest path

Procedia PDF Downloads 407
3924 Undifferentiated Embryonal Sarcoma of Liver: A Rare Case Report

Authors: Thieu-Thi Tra My

Abstract:

Undifferentiated embryonal sarcoma of the liver (UESL), a rare malignant mesenchymal tumor, is commonly seen in children. The symptoms and imaging were not specific, so it could be mimicked with other tumors or liver abscesses. The tumor often appears as a large heterogeneous echoic solid mass with small cystic areas while showing a cyst-like appearance on CT and MRI. The histopathological manifestation of the UESL consisted of stellate-shaped and spindle cells scattered on a myxoid background with high mitotic count. Cells with multiple or bizarre nuclear were also observed. Here, we aimed to describe a 9-year-old male diagnosed with UESL focused on imaging and histopathological characteristics.

Keywords: undifferentiated embryonal sarcoma of liver, UESL, liver sarcoma, liver tumor, children

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3923 Fast Robust Switching Control Scheme for PWR-Type Nuclear Power Plants

Authors: Piyush V. Surjagade, Jiamei Deng, Paul Doney, S. R. Shimjith, A. John Arul

Abstract:

In sophisticated and complex systems such as nuclear power plants, maintaining the system's stability in the presence of uncertainties and disturbances and obtaining a fast dynamic response are the most challenging problems. Thus, to ensure the satisfactory and safe operation of nuclear power plants, this work proposes a new fast, robust optimal switching control strategy for pressurized water reactor-type nuclear power plants. The proposed control strategy guarantees a substantial degree of robustness, fast dynamic response over the entire operational envelope, and optimal performance during the nominal operation of the plant. To improve the robustness, obtain a fast dynamic response, and make the system optimal, a bank of controllers is designed. Various controllers, like a baseline proportional-integral-derivative controller, an optimal linear quadratic Gaussian controller, and a robust adaptive L1 controller, are designed to perform distinct tasks in a specific situation. At any instant of time, the most suitable controller from the bank of controllers is selected using the switching logic unit that designates the controller by monitoring the health of the nuclear power plant or transients. The proposed switching control strategy optimizes the overall performance and increases operational safety and efficiency. Simulation studies have been performed considering various uncertainties and disturbances that demonstrate the applicability and effectiveness of the proposed switching control strategy over some conventional control techniques.

Keywords: switching control, robust control, optimal control, nuclear power control

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3922 Spatial Analysis of Flood Vulnerability in Highly Urbanized Area: A Case Study in Taipei City

Authors: Liang Weichien

Abstract:

Without adequate information and mitigation plan for natural disaster, the risk to urban populated areas will increase in the future as populations grow, especially in Taiwan. Taiwan is recognized as the world's high-risk areas, where an average of 5.7 times of floods occur per year should seek to strengthen coherence and consensus in how cities can plan for flood and climate change. Therefore, this study aims at understanding the vulnerability to flooding in Taipei city, Taiwan, by creating indicators and calculating the vulnerability of each study units. The indicators were grouped into sensitivity and adaptive capacity based on the definition of vulnerability of Intergovernmental Panel on Climate Change. The indicators were weighted by using Principal Component Analysis. However, current researches were based on the assumption that the composition and influence of the indicators were the same in different areas. This disregarded spatial correlation that might result in inaccurate explanation on local vulnerability. The study used Geographically Weighted Principal Component Analysis by adding geographic weighting matrix as weighting to get the different main flood impact characteristic in different areas. Cross Validation Method and Akaike Information Criterion were used to decide bandwidth and Gaussian Pattern as the bandwidth weight scheme. The ultimate outcome can be used for the reduction of damage potential by integrating the outputs into local mitigation plan and urban planning.

Keywords: flood vulnerability, geographically weighted principal components analysis, GWPCA, highly urbanized area, spatial correlation

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3921 Parallel 2-Opt Local Search on GPU

Authors: Wen-Bao Qiao, Jean-Charles Créput

Abstract:

To accelerate the solution for large scale traveling salesman problems (TSP), a parallel 2-opt local search algorithm with simple implementation based on Graphics Processing Unit (GPU) is presented and tested in this paper. The parallel scheme is based on technique of data decomposition by dynamically assigning multiple K processors on the integral tour to treat K edges’ 2-opt local optimization simultaneously on independent sub-tours, where K can be user-defined or have a function relationship with input size N. We implement this algorithm with doubly linked list on GPU. The implementation only requires O(N) memory. We compare this parallel 2-opt local optimization against sequential exhaustive 2-opt search along integral tour on TSP instances from TSPLIB with more than 10000 cities.

Keywords: parallel 2-opt, double links, large scale TSP, GPU

Procedia PDF Downloads 618
3920 Quality Business Ethics: A Case Study

Authors: Fotis Vouzas

Abstract:

This paper is an attempt to investigate the Business Ethics link to Quality Management. Business Ethics as a management practice is well rooted in many organizations, but its contribution to quality management implementation programs and practices is not well documented. The ISO 9000 and the Business Excellence frameworks and Awards seem to provide a basis for the implementation of a TQM philosophy contributing to efficiency, enhanced performance and sustainability. The author examines a series of Corporate Ethics initiatives and investigates the relationship to Total Quality Management in an MNC operating in Greece. The data gathering was carried out through extensive and in-depth interviews with several multiple informants, i.e., the plant manager, the production manager, and the personnel manager, using a semi-structured questionnaire with open-ended questions.

Keywords: total quality management, business ethics, Greece, ISO 9000

Procedia PDF Downloads 74
3919 Grid Computing for Multi-Objective Optimization Problems

Authors: Aouaouche Elmaouhab, Hassina Beggar

Abstract:

Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

Procedia PDF Downloads 478
3918 Development of Taiwanese Sign Language Receptive Skills Test for Deaf Children

Authors: Hsiu Tan Liu, Chun Jung Liu

Abstract:

It has multiple purposes to develop a sign language receptive skills test. For example, this test can be used to be an important tool for education and to understand the sign language ability of deaf children. There is no available test for these purposes in Taiwan. Through the discussion of experts and the references of standardized Taiwanese Sign Language Receptive Test for adults and adolescents, the frame of Taiwanese Sign Language Receptive Skills Test (TSL-RST) for deaf children was developed, and the items were further designed. After multiple times of pre-trials, discussions and corrections, TSL-RST is finally developed which can be conducted and scored online. There were 33 deaf children who agreed to be tested from all three deaf schools in Taiwan. Through item analysis, the items were picked out that have good discrimination index and fair difficulty index. Moreover, psychometric indexes of reliability and validity were established. Then, derived the regression formula was derived which can predict the sign language receptive skills of deaf children. The main results of this study are as follows. (1). TSL-RST includes three sub-test of vocabulary comprehension, syntax comprehension and paragraph comprehension. There are 21, 20, and 9 items in vocabulary comprehension, syntax comprehension, and paragraph comprehension, respectively. (2). TSL-RST can be conducted individually online. The sign language ability of deaf students can be calculated fast and objectively, so that they can get the feedback and results immediately. This can also contribute to both teaching and research. The most subjects can complete the test within 25 minutes. While the test procedure, they can answer the test questions without relying on their reading ability or memory capacity. (3). The sub-test of the vocabulary comprehension is the easiest one, syntax comprehension is harder than vocabulary comprehension and the paragraph comprehension is the hardest. Each of the three sub-test and the whole test are good in item discrimination index. (4). The psychometric indices are good, including the internal consistency reliability (Cronbach’s α coefficient), test-retest reliability, split-half reliability, and content validity. The sign language ability are significantly related to non-verbal IQ, the teachers’ rating to the students’ sign language ability and students’ self-rating to their own sign language ability. The results showed that the higher grade students have better performance than the lower grade students, and students with deaf parent perform better than those with hearing parent. These results made TLS-RST have great discriminant validity. (5). The predictors of sign language ability of primary deaf students are age and years of starting to learn sign language. The results of this study suggested that TSL-RST can effectively assess deaf student’s sign language ability. This study also proposed a model to develop a sign language tests.

Keywords: comprehension test, elementary school, sign language, Taiwan sign language

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3917 New Result for Optical OFDM in Code Division Multiple Access Systems Using Direct Detection

Authors: Cherifi Abdelhamid

Abstract:

In optical communication systems, OFDM has received increased attention as a means to overcome various limitations of optical transmission systems such as modal dispersion, relative intensity noise, chromatic dispersion, polarization mode dispersion and self-phase modulation. The multipath dispersion limits the maximum transmission data rates. In this paper we investigate OFDM system where multipath induced intersymbol interference (ISI) is reduced and we increase the number of users by combining OFDM system with OCDMA system using direct detection Incorporate OOC (orthogonal optical code) for minimize a bit error rate.

Keywords: OFDM, OCDMA, OOC (orthogonal optical code), (ISI), prim codes (Pc)

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3916 Access and Utilization of Family Planning Services among Women in a Rural Community of Enugu state Nigeria, using a Descriptive Cross-sectional Design

Authors: Chidiebere Joy Nwankwo, Benjamin S. C. Uzochukwu, Florence T. Sibeudu

Abstract:

Background: Family planning is one of the most cost-effective ways to prevent maternal, infant, and child mortality. It can decrease maternal mortality by reducing the number of unintended pregnancies, the number of abortions, and the proportion of births at high risk. It has been seen to improve the health and economic well-being of families and communities and ensures women’s planned childbearing in order to achieve education and career goals which could raise family income thereby reducing poverty. The choice and use of a particular family planning method and their sources vary globally. Rural Communities often face significant challenges in accessing and utilizing family planning services. Aim: This study set out to assess Access and Utilization of Family Planning Services among Women of Reproductive Age in a Rural Community of Enugu state, Nigeria. Rural communities were chosen for this study because past demographic surveys have shown that women in urban areas are more likely to accept and practice family planning compared to those in rural areas. Method: A Descriptive Cross-sectional Research design was employed to achieve the aim and objectives of the study. Data collected from 177 consenting participants using interviewer-administered questionnaires was analysed using Descriptive statistics to summarize the Socio-demographic characteristics of the participants and Access and Utilization of Family Planning Services among the participants including Reasons for using different Family Planning Methods and Barriers encountered in Access and Utilization of these services. A Cross-tabulation between Socio-demographic Characteristics of respondents and the use of Family Planning services was carried out. Result: The findings of this study revealed that majority of the participants (72.9%) have not utilized any family planning service. Out of those (27.1%) that have used any family planning service, majority of them are still currently using a form of family planning service and have access to them in health facilities, patent medicine vendors and others based on multiple responses. Male condoms were the most utilized modern family planning service. Based on multiple responses, inaccessibility, personal beliefs and partner’s objection were the most identified barriers encountered in accessing family planning services. Conclusion: Access and uptake of family planning services in rural communities is lower than the national average. Increasing access to family planning is an urgent priority for rural areas Interventions that will scale up Access and Utilization of family planning services in rural communities should be intensified.

Keywords: access, family planning, rural community, utilization

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3915 The Effect of Emotion Self-Confidence and Perceived Social Support on Hong Kong Higher-Education Students' Suicide-Related Emotional Experiences

Authors: K. C. Ching

Abstract:

There is growing public concern over the increasing prevalence of student suicide in Hong Kong. Some identify the problem with insufficient social support, while some attribute it to the vast fluctuations in emotional experience and the hindrances to emotion-regulation, both typical of adolescence and emerging adulthood. This study is thus designed to explore the respective effect of perceived social support and emotion self-confidence, on positive emotions and negative emotions. Fifty-seven Hong Kong higher-education students (17 males, 40 females) aged between 18 and 25 (M = 21.78) responded to an online questionnaire consisted of self-reported measures of perceived social support, emotional self-confidence, positive emotions, and negative emotions. Hierarchical regression analysis revealed that emotional self-confidence positively associated with positive emotions and negatively with negative emotions, while perceived social support positively associated with positive emotions but was not related to negative emotions. Perceived social support and emotional self-confidence both predicted positive emotions, but did not interact to predict any emotional outcome. It is concluded that students’ positive and negative emotional experiences are closely related to their emotion-regulation process. But for social support, its effect is merely protective, meaning that although perceived social support generally promotes positive emotions, it alone does not suffice to alleviate students’ negative emotions. These conclusions carry profound implications to suicide prevention practices, including that most existing suicide prevention campaigns should advance from merely fostering mutual support to directly promoting adaptive coping of emotional negativity.

Keywords: emerging adulthood, emotional self-confidence, hong kong, perceived social support, suicide prevention

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3914 Development and Validation of a Semi-Quantitative Food Frequency Questionnaire for Use in Urban and Rural Communities of Rwanda

Authors: Phenias Nsabimana, Jérôme W. Some, Hilda Vasanthakaalam, Stefaan De Henauw, Souheila Abbeddou

Abstract:

Tools for the dietary assessment in adults are limited in low- and middle-income settings. The objective of this study was to develop and validate a semi-quantitative food frequency questionnaire (FFQ) against the multiple pass-24 h recall tool for use in urban and rural Rwanda. A total of 212 adults (154 females and 58 males), 18-49 aged, including 105 urban and 107 rural residents, from the four regions of Rwanda, were recruited in the present study. A multiple-pass 24- H recall technique was used to collect dietary data in both urban and rural areas in four different rounds, on different days (one weekday and one weekend day), separated by a period of three months, from November 2020 to October 2021. The details of all the foods and beverages consumed over the 24h period of the day prior to the interview day were collected during face-to-face interviews. A list of foods, beverages, and commonly consumed recipes was developed by the study researchers and ten research assistants from the different regions of Rwanda. Non-standard recipes were collected when the information was available. A single semi-quantitative FFQ was also developed in the same group discussion prior to the beginning of the data collection. The FFQ was collected at the beginning and the end of the data collection period. Data were collected digitally. The amount of energy and macro-nutrients contributed by each food, recipe, and beverage will be computed based on nutrient composition reported in food composition tables and weight consumed. Median energy and nutrient contents of different food intakes from FFQ and 24-hour recalls and median differences (24-hour recall –FFQ) will be calculated. Kappa, Spearman, Wilcoxon, and Bland-Altman plot statistics will be conducted to evaluate the correlation between estimated nutrient and energy intake found by the two methods. Differences will be tested for their significance and all analyses will be done with STATA 11. Data collection was completed in November 2021. Data cleaning is ongoing and the data analysis is expected to be completed by July 2022. A developed and validated semi-quantitative FFQ will be available for use in dietary assessment. The developed FFQ will help researchers to collect reliable data that will support policy makers to plan for proper dietary change intervention in Rwanda.

Keywords: food frequency questionnaire, reproducibility, 24-H recall questionnaire, validation

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3913 Optimization Modeling of the Hybrid Antenna Array for the DoA Estimation

Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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3912 The Behavior of The Zeros of Bargmann Analytic Functions for Multiple-Mode Systems

Authors: Muna Tabuni

Abstract:

The paper contains an investigation of the behavior of the Zeros of Bargmann functions for one and two-mode systems. A brief introduction to Harmonic oscillator formalism for one and two-mode is given. The Bargmann analytic representation for one and two-mode has been studied. The zeros of Bargmann analytic function for one-mode are considered. The Q Husimi functions are introduced. The Bargmann functions and the Husimi functions have the same zeros. The Bargmann functions f(z) have exactly q zeros. The evolution time of the zeros are discussed. The zeros of Bargmann analytic functions for two-mode are introduced. Various examples have been given.

Keywords: Bargmann functions, two-mode, zeros, harmonic oscillator

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3911 Techno-Economic Analysis (TEA) of Circular Economy Approach in the Valorisation of Pig Meat Processing Wastes

Authors: Ribeiro A., Vilarinho C., Luisa A., Carvalho J

Abstract:

The pig meat industry generates large volumes of by- and co-products like blood, bones, skin, trimmings, organs, viscera, and skulls, among others, during slaughtering and meat processing and must be treated and disposed of ecologically. The yield of these by-products has been reported to account for about 10% to 15% of the value of the live animal in developed countries, although animal by-products account for about two-thirds of the animal after slaughter. It was selected for further valorization of the principal wastes produced throughout the value chain of pig meat production: Pig Manure, Pig Bones, Fats, Skins, Pig Hair, Wastewater, Wastewater sludges, and other animal subproducts type III. According to the potential valorization options, these wastes will be converted into Biomethane, Fertilizers (phosphorus and digestate), Hydroxyapatite, and protein hydrolysates (Keratin and Collagen). This work includes comprehensive technical and economic analyses (TEA) for each valorization route or applied technology. Metrics such as Net Present Value (NPV), Internal Rate of Return (IRR), and payback periods were used to evaluate economic feasibility. From this analysis, it can be concluded that, for Biogas Production, the scenarios using pig manure, wastewater sludges and mixed grass and leguminous wastes presented a remarkably high economic feasibility. Scenarios showed high economic feasibility with a positive payback period, NPV, and IRR. The optimal scenario combining pig manure with mixed grass and leguminous wastes had a payback period of 1.2 years and produced 427,6269 m³ of biomethane annually. Regarding the Chemical Extraction of Phosphorous and Nitrogen, results proved that the process is economically unviable due to negative cash flows despite high recovery rates. The TEA of Hydrolysis and Extraction of Keratin Hydrolysates indicate that a unit processing and valorizing 10 tons of pig hair per year for the production of keratin hydrolysate has an NPV of 907,940 €, an IRR of 13.07%, and a Payback period of 5.41 years. All of these indicators suggest a highly potential project to explore in the future. On the opposite, the results of Hydrolysis and Extraction of Collagen Hydrolysates showed a process economically unviable with negative cash flows in all scenarios due to the high-fat content in raw materials. In fact, the results from the valorization of 10 tons of pig skin had a negative cash flow of 453 743,88 €. TEA results of Extraction and purification of Hydroxyapatite from Pig Bones with Pyrolysis indicate that unit processing and valorizing 10 tons of pig bones per year for the production of hydroxyapatite has an NPV of 1 274 819,00 €, an IRR of 65.43%, and a Payback period of 1,5 years over a timeline of 10 years with a discount rate of 10%. These valorization routes, circular economy and bio-refinery approach offer significant contributions to sustainable bio-based operations within the agri-food industry. This approach transforms waste into valuable resources, enhancing both environmental and economic outcomes and contributing to a more sustainable and circular bioeconomy.

Keywords: techno-economic analysis (TEA), pig meat processing wastes, circular economy, bio-refinery

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3910 Association Rules Mining and NOSQL Oriented Document in Big Data

Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

Abstract:

Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

Procedia PDF Downloads 157
3909 AER Model: An Integrated Artificial Society Modeling Method for Cloud Manufacturing Service Economic System

Authors: Deyu Zhou, Xiao Xue, Lizhen Cui

Abstract:

With the increasing collaboration among various services and the growing complexity of user demands, there are more and more factors affecting the stable development of the cloud manufacturing service economic system (CMSE). This poses new challenges to the evolution analysis of the CMSE. Many researchers have modeled and analyzed the evolution process of CMSE from the perspectives of individual learning and internal factors influencing the system, but without considering other important characteristics of the system's individuals (such as heterogeneity, bounded rationality, etc.) and the impact of external environmental factors. Therefore, this paper proposes an integrated artificial social model for the cloud manufacturing service economic system, which considers both the characteristics of the system's individuals and the internal and external influencing factors of the system. The model consists of three parts: the Agent model, environment model, and rules model (Agent-Environment-Rules, AER): (1) the Agent model considers important features of the individuals, such as heterogeneity and bounded rationality, based on the adaptive behavior mechanisms of perception, action, and decision-making; (2) the environment model describes the activity space of the individuals (real or virtual environment); (3) the rules model, as the driving force of system evolution, describes the mechanism of the entire system's operation and evolution. Finally, this paper verifies the effectiveness of the AER model through computational and experimental results.

Keywords: cloud manufacturing service economic system (CMSE), AER model, artificial social modeling, integrated framework, computing experiment, agent-based modeling, social networks

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3908 Design of Robust and Intelligent Controller for Active Removal of Space Debris

Authors: Shabadini Sampath, Jinglang Feng

Abstract:

With huge kinetic energy, space debris poses a major threat to astronauts’ space activities and spacecraft in orbit if a collision happens. The active removal of space debris is required in order to avoid frequent collisions that would occur. In addition, the amount of space debris will increase uncontrollably, posing a threat to the safety of the entire space system. But the safe and reliable removal of large-scale space debris has been a huge challenge to date. While capturing and deorbiting space debris, the space manipulator has to achieve high control precision. However, due to uncertainties and unknown disturbances, there is difficulty in coordinating the control of the space manipulator. To address this challenge, this paper focuses on developing a robust and intelligent control algorithm that controls joint movement and restricts it on the sliding manifold by reducing uncertainties. A neural network adaptive sliding mode controller (NNASMC) is applied with the objective of finding the control law such that the joint motions of the space manipulator follow the given trajectory. A computed torque control (CTC) is an effective motion control strategy that is used in this paper for computing space manipulator arm torque to generate the required motion. Based on the Lyapunov stability theorem, the proposed intelligent controller NNASMC and CTC guarantees the robustness and global asymptotic stability of the closed-loop control system. Finally, the controllers used in the paper are modeled and simulated using MATLAB Simulink. The results are presented to prove the effectiveness of the proposed controller approach.

Keywords: GNC, active removal of space debris, AI controllers, MatLabSimulink

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3907 Generator Subgraphs of the Wheel

Authors: Neil M. Mame

Abstract:

We consider only finite graphs without loops nor multiple edges. Let G be a graph with E(G) = {e1, e2, …., em}. The edge space of G, denoted by ε(G), is a vector space over the field Z2. The elements of ε(G) are all the subsets of E(G). Vector addition is defined as X+Y = X Δ Y, the symmetric difference of sets X and Y, for X, Y ∈ ε(G). Scalar multiplication is defined as 1.X =X and 0.X = Ø for X ∈ ε(G). The set S ⊆ ε(G) is called a generating set if every element ε(G) is a linear combination of the elements of S. For a non-empty set X ∈ ε(G), the smallest subgraph with edge set X is called edge-induced subgraph of G, denoted by G[X]. The set EH(G) = { A ∈ ε(G) : G[A] ≅ H } denotes the uniform set of H with respect to G and εH(G) denotes the subspace of ε(G) generated by EH(G). If εH(G) is generating set, then we call H a generator subgraph of G. This paper gives the characterization for the generator subgraphs of the wheel that contain cycles and gives the necessary conditions for the acyclic generator subgraphs of the wheel.

Keywords: edge space, edge-induced subgraph, generator subgraph, wheel

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3906 Interpretable Deep Learning Models for Medical Condition Identification

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

Abstract:

Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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3905 The Vulnerability of Climate Change to Farmers, Fishermen and Herdsmen in Nigeria

Authors: Nasiru Medugu Idris

Abstract:

This research is aimed at assessing the vulnerability of climate change to rural communities (farmers, herdsmen and fishermen) in Nigeria with the view to study the underlying causes and degree of vulnerability to climate change and examine the conflict between farmers and herdsmen as a result of climate change. This research employed the use of quantitative and qualitative means of data gathering techniques as well as physical observations. Six states (Kebbi, Adamawa, Nasarawa, Osun, Ebonyi, and Akwa Ibom) have been selected on the ground that they are key food production areas in the country and are therefore essential to continual food security in the country. So also, they also double as fishing communities in order to aid the comprehensive study of all the effects on climate on farmers and fishermen alike. Community focus group discussions were carried out in the various states for an interactive session and also to have firsthand information on their level of awareness on climate change. Climate data from the Nigerian Meteorological Agency over the past decade were collected for the purpose of analyzing trends in climate. The study observed that the level of vulnerability of rural dwellers most especially farmers, herdsmen and fishermen to climate change is very high due to their socioeconomic, ethnic and historical perspective of their trend. The study, therefore, recommends that urgent step needs to be put in place to help control natural hazards and man-made disasters and serious measures are also needed in order to minimize severe societal, economic and political crises; some of which may either escalate to violent conflicts or could be avoided by efforts of conflict resolution and prevention by the initiation of a process of de-escalation. So this study has recommended the best-fit adaptive and mitigation measures to climate change vulnerability in rural communities of Nigeria.

Keywords: adaptation, farmers, fishermen, herdsmen

Procedia PDF Downloads 186
3904 Synthesis of Bimetallic Fe/Cu Nanoparticles with Different Copper Loading Ratios

Authors: May Thant Zin, Josephine Borja, Hirofumi Hinode, Winarto Kurniawan

Abstract:

Nanotechnology has multiple and enormous advantages for all application. Therefore, this research is carried out to synthesize and characterize bimetallic iron with copper nano-particles. After synthesizing nano zero valent iron by reduction of ferric chloride by sodium borohydride under nitrogen purging environment, bimetallic iron with copper nanoparticles are synthesized by varying different loads of copper chloride. Due to different standard potential (E0) values of copper and iron, copper is coupled with iron at (Cu to Fe ratio of 1:5, 1:6.7, 1:10, 1:20). It is found that the resulted bimetallic Fe/Cu nanoparticles are composing phases of iron and copper. According to the diffraction patterns indicating the state of chemical combination of the bimetallic nanoparticles, the particles are well-combined and crystalline sizes are less than 1000 Ao (or 100 nm). Specifically, particle sizes of synthesized bimetallic Fe/Cu nanoparticles are ranging from 44.583 nm to 85.149 nm.

Keywords:

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3903 An Interesting Case of Management of Life Threatening Calcium Disequilibrium in a Patient with Parathyroid Tumor

Authors: Rajish Shil, Mohammad Ali Houri, Mohammad Milad Ismail, Fatimah Al Kaabi

Abstract:

The clinical presentation of Primary hyperparathyroidism can vary from simple asymptomatic hypercalcemia to severe life-threatening hypercalcemic crisis with multi-organ dysfunction, which can be due to parathyroid adenoma or sometimes with malignant cancer. This cascade of clinical presentation can lead to a diagnostic and therapeutic challenge for treating the disease. We are presenting a case of severe hypercalcemic crisis due to parathyroid adenoma with an emphasis on early management, diagnosis, and interventions to prevent any lifelong complications and any permanent organ dysfunction. A 30 years old female with a history of primary Infertility, admitted to Al Ain Hospital critical care unit with Acute Severe Necrotizing Pancreatitis. She initially had a 1-month history of abdominal pain on and off, for which she was treated conservatively with no much improvement, and later on, she developed life-threatening severe pancreatitis, which required her to be admitted to the critical care unit. She was transferred from a private healthcare facility, where she was found to have a very high level of calcium up to 15mmol/L. She received systemic Zoledronic Acid, which lowered her calcium level transiently and later was increased again. She went on to develop multiple end-organ damages along with multiple electrolytes disturbances. She was found to have high levels of Parathyroid hormone, which was correlated with a parathyroid mass on the neck via radiological imaging. After a long course of medical treatment to lower the calcium to a near-normal level, parathyroidectomy was done, which showed parathyroid adenoma on histology. She developed hungry bone syndrome after the surgery and pancreatic pseudocyst after resolving of pancreatitis. She required aggressive treatment with Intravenous calcium for her hypocalcemia as she received zoledronic acid at the beginning of the disease. Later on, she was discharged on long term calcium and other electrolytes supplements. In patients presenting with hypercalcemia, it is prudent to investigate and start treatment early to prevent complications and end-organ damage from hypercalcemia and also to treat the primary cause of the hypercalcemia, with conscious follow up to prevent hypocalcemic complications after treatment. It is important to follow up patients with parathyroid adenomas for a long period in order to detect any recurrence of the tumor or to make sure if the primary tumor is either benign or malignant.

Keywords: hypercalcemia, pancreatitis, hypocalcemia, hyperparathyroidism

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3902 The Effect of Artificial Intelligence on Banking Development and Progress

Authors: Mina Malak Hanna Saad

Abstract:

New strategies for supplying banking services to the customer have been brought, which include online banking. Banks have begun to recall electronic banking (e-banking) as a manner to replace some conventional department features by means of the usage of the internet as a brand-new distribution channel. A few clients have at least one account at multiple banks and get admission to those debts through online banking. To test their present-day internet worth, customers need to log into each of their debts, get particular statistics, and paint closer to consolidation. Not only is it time-ingesting; however, but it is also a repeatable activity with a certain frequency. To solve this problem, the idea of account aggregation was delivered as a solution. Account consolidation in e-banking as a form of digital banking appears to build stronger dating with clients. An account linking service is usually known as a service that permits customers to manipulate their bank accounts held at exceptional institutions through a common online banking platform that places a high priority on safety and statistics protection. The object affords an outline of the account aggregation approach in e-banking as a distinct carrier in the area of e-banking. The advanced facts generation is becoming a vital thing in the improvement of financial services enterprise, specifically the banking enterprise. It has brought different ways of delivering banking to the purchaser, which includes net Banking. Banks began to study electronic banking (e-banking) as a means to update some of their traditional branch functions and the use of the net as a distribution channel. Some clients have at least multiple accounts throughout banks and get the right of entry to that money owed through the usage of e-banking offerings. To examine the contemporary internet's well-worth position, customers have to log in to each of their money owed, get the information and work on consolidation. This no longer takes sufficient time; however, it is a repetitive interest at a specified frequency. To address this point, an account aggregation idea is brought as an answer. E-banking account aggregation, as one of the e-banking kinds, appeared to construct a more potent dating with clients. Account Aggregation carrier usually refers to a service that allows clients to control their bank bills maintained in one-of-a-kind institutions via a common Internet banking working platform, with an excessive subject to protection and privateness. This paper offers an overview of an e-banking account aggregation technique as a new provider in the e-banking field.

Keywords: compatibility, complexity, mobile banking, observation, risk banking technology, Internet banks, modernization of banks, banks, account aggregation, security, enterprise developmente-banking, enterprise development

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3901 Knowledge and Eating Behavior of Teenage Pregnancy

Authors: Udomporn Yingpaisuk, Premwadee Karuhadej

Abstract:

The purposed of this research was to study the eating habit of teenage pregnancy and its relationship to the knowledge of nutrition during pregnancy. The 100 samples were derived from simple random sampling technique of the teenage pregnancy in Bangkae District. The questionnaire was used to collect data with the reliability of 0.8. The data were analyzed by SPSS for Windows with multiple regression technique. Percentage, mean and the relationship of knowledge of eating and eating behavior were obtained. The research results revealed that their knowledge in nutrition was at the average of 4.07 and their eating habit that they mentioned most was to refrain from alcohol and caffeine at 82% and the knowledge in nutrition influenced their eating habits at 54% with the statistically significant level of 0.001.

Keywords: teenage pregnancy, knowledge of eating, eating behavior, alcohol, caffeine

Procedia PDF Downloads 354
3900 An Efficient Automated Radiation Measuring System for Plasma Monopole Antenna

Authors: Gurkirandeep Kaur, Rana Pratap Yadav

Abstract:

This experimental study is aimed to examine the radiation characteristics of different plasma structures of a surface wave-driven plasma antenna by an automated measuring system. In this study, a 30 cm long plasma column of argon gas with a diameter of 3 cm is excited by surface wave discharge mechanism operating at 13.56 MHz with RF power level up to 100 Watts and gas pressure between 0.01 to 0.05 mb. The study reveals that a single structured plasma monopole can be modified into an array of plasma antenna elements by forming multiple striations or plasma blobs inside the discharge tube by altering the values of plasma properties such as working pressure, operating frequency, input RF power, discharge tube dimensions, i.e., length, radius, and thickness. It is also reported that plasma length, electron density, and conductivity are functions of operating plasma parameters and controlled by changing working pressure and input power. To investigate the antenna radiation efficiency for the far-field region, an automation-based radiation measuring system has been fabricated and presented in detail. This developed automated system involves a combined setup of controller, dc servo motors, vector network analyzer, and computing device to evaluate the radiation intensity, directivity, gain and efficiency of plasma antenna. In this system, the controller is connected to multiple motors for moving aluminum shafts in both elevation and azimuthal plane whereas radiation from plasma monopole antenna is measured by a Vector Network Analyser (VNA) which is further wired up with the computing device to display radiations in polar plot forms. Here, the radiation characteristics of both continuous and array plasma monopole antenna have been studied for various working plasma parameters. The experimental results clearly indicate that the plasma antenna is as efficient as a metallic antenna. The radiation from plasma monopole antenna is significantly influenced by plasma properties which provides a wider range in radiation pattern where desired radiation parameters like beam-width, the direction of radiation, radiation intensity, antenna efficiency, etc. can be achieved in a single monopole. Due to its wide range of selectivity in radiation pattern; this can meet the demands of wider bandwidth to get high data speed in communication systems. Moreover, this developed system provides an efficient and cost-effective solution for measuring the radiation pattern in far-field zone for any kind of antenna system.

Keywords: antenna radiation characteristics, dynamically reconfigurable, plasma antenna, plasma column, plasma striations, surface wave

Procedia PDF Downloads 113
3899 Stock Movement Prediction Using Price Factor and Deep Learning

Authors: Hy Dang, Bo Mei

Abstract:

The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

Procedia PDF Downloads 144