Search results for: shared frailty survival models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8687

Search results for: shared frailty survival models

8117 Predicting Options Prices Using Machine Learning

Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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8116 Immunologically Non-Treated Vascular Xenografts in Long-Term Survival Animals

Authors: W. G. Kim, J. M. Chang, W. S. Kim

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Immunologically non-treated and acellularized porcine xenografts were implanted as an arterial graft in goats and comparatively analyzed for the explanted grafts with gross observation, as well as light microscopy and immunohistochemistry, following the predetermined periods. For immunologically non-treated xenografts, bilateral porcine carotid arteries were harvested, and after short-term freezing at -70°C, were implanted into goats. The preparation of acellularized xenograft vessels has been performed with Nacl-SDS solution and stored at the freezer until use. The goats were randomly assigned for three periods of observation (3, 6, and 12 months after implantation), four animals were observed at each of these times. Periodic ultrasonographic examinations were performed during observation period. Following the predetermined periods, the explanted grafts were analyzed. Among 12 animals, one goat died prematurely, and a total of 22 grafts were evaluated. Gross observations revealed non-thrombotic patent smooth lumens. Microscopic examinations of the explanted grafts showed satisfactory cellular reconstruction up to the 12-month observation period. The proportions of CD3 positive T lymphocytes among inflammatory cells infiltrations were very low. In conclusion, these findings, as a whole, suggest that porcine vessel xenografts can be clinically acceptably implanted in the goats as a form of small-diameter vascular graft, regardless of the acellularized xenograft or immunologically non-treated xenograft.

Keywords: xenograft, arterial graft, long-term survival animals, immunology

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8115 The Martingale Options Price Valuation for European Puts Using Stochastic Differential Equation Models

Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

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8114 The Hyperbolic Smoothing Approach for Automatic Calibration of Rainfall-Runoff Models

Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

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This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

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8113 Efficacy of Solanum anguivi Lam Fruits (African Bitter Berry) in Lowering Glucose Levels in Diabetes Mellitus and Increasing Survival

Authors: Aisha Musaazi Sebunya Nakitto, Anika E. Wagner, Yusuf B. Byaruhanga, John H. Muyonga

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The prevalence and burden of diabetes are rapidly increasing globally, stemming from changes in lifestyle and dietary habits. Although several drugs are available to treat type 2 diabetes mellitus (T2DM), many are accompanied by several side effects and are often costly. Solanum anguivi Lam. fruits (SALF) are bitter berries that commonly grow in the wild and are traditionally cultivated by many globally as a remedy for T2DM. This effect is likely attributable to the presence of bioactive compounds such as phenolics, flavonoids, saponins, alkaloids, and vitamin C in SALF. In this study, we investigated the morphological characteristics of different SALF accessions and the effect of ripeness stages and thermal treatments on the bioactive compounds contents (BCC) and antioxidant activity (AA) of SALF accessions. Using the fruit fly Drosophila melanogaster (D. melanogaster) model, we explored the potential impact of dietary SALF in preventing and treating T2DM phenotypes. Morphological characterization was conducted based on descriptors of Solanum species. The BCC and AA of SALF at different ripeness stages (unripe, yellow, orange, and red) and after thermal treatments were determined using spectrophotometry, HPLC, and gravimetry. Male and female fruit flies were fed a high-sugar diet (HSD) to induce a T2DM-like phenotype, while control flies were fed on SY10 medium for up to 24 days. Experimental flies were exposed to HSD supplemented with 5 or 10 mg/ml SALF. The therapeutic and prevention effect of SALF in T2DM-like phenotype was investigated on weight, climbing activity, glucose and triglyceride contents, survival, and gene expression of PPARγ co-activator 1α fly homolog Srl and Drosophila insulin-like peptides. Methods in fly studies included Gustatory assay, Climbing assay, Glucose GOD-PAP assay, Triglyceride GPO-PAP assay, Roti-Quant®, and Real Time-PCR analysis. The ripeness stage significantly influenced SALF BCC and AA, and this was dependent on the accession. The unripe stage had the highest AA and total phenolics and flavonoids; the orange stage was rich in saponins, while the red stage had the highest alkaloid contents. Boiling and steaming increased the total phenolics and AA up to 4-fold and 3-fold, respectively. Drying at low temperatures resulted in higher phenolics and AA than the control. In the therapeutic model, the HSD-fed female flies exhibited elevated glucose levels, which exhibited a dose-dependent reduction upon exposure to a SALF-supplemented diet. Female flies fed on a SALF+ HSD exhibited a significant increase in survival compared to HSD-fed and control diet-fed flies. SALF supplementation did not alter the weights, fitness, and triglyceride levels of female flies in comparison with HSD-only-fed flies. The mRNA levels of Srl decreased in HSD-fed flies compared to the control-fed, with no effect observed in females exposed to HSD+SALF. Similarly, in the preventative model, the SALF diet resulted in higher survival of supplemented flies compared to controls. Consumption of boiled unripe SALF may result in the highest health benefits due to the high phenolic contents and antioxidant activity observed. Dietary intake of SALF significantly lowered glucose levels and increased survival of the D. melanogaster model. Additional studies in higher organisms are needed to explore the preventative and therapeutic potential of SALF in T2DM.

Keywords: antioxidant activity, bioactive compounds, bitter berries, Drosophila melanogaster, Solanum anguivi, type 2 diabetes mellitus, survival

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8112 Migration, Food Security, Rapid Urbanization and Population Rise in Nigeria: A Wake-Up Call to Policy-Makers

Authors: A. E. Obayelu, S. O. Olubiyo

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Food is different from other commodities because everybody needs food for survival. This has led to a shift in focus to food security in the global policy arena. However, there is paucity of studies on the interactions between food security, migration, urbanization and population rise. This paper therefore look at the linkages between migration and food security in the context of rapid urbanization and population rise of Nigeria. The study obtained data and information from both secondary sources and primary method through the voice of some selected Nigerians through telephone interview. The findings revealed that, the primary factor for the rapid urbanization in Nigeria is migration; most foods are still produced by peasant farmers who are scattered all over the rural areas and not multinational companies who produce on large scale. The country is still characterized with inadequate infrastructural facilities and services to cater for growing population. There are no protective policies enforced by the Nigeria government. In most cases, the migrants are left entirely on mercy of what they can find to due for survival. The most common coping mechanisms by migrants from rural to urban areas are changing food intake in terms of quantity, quality, diversity and frequency and prioritizing children. Policies that address urban food security need to consider the complex relationship between rapid population rise and migration and appropriate transformations that will be able to manage urbanization. With increasing rate of urbanization, the focus of food security should no longer be that of rural only

Keywords: agricultural commercialization, agricultural transformation, food security, urban, urbanization

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8111 Developing Location-allocation Models in the Three Echelon Supply Chain

Authors: Mehdi Seifbarghy, Zahra Mansouri

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In this paper a few location-allocation models are developed in a multi-echelon supply chain including suppliers, manufacturers, distributors and retailers. The objectives are maximizing demand coverage, minimizing the total distance of distributors from suppliers, minimizing some facility establishment costs and minimizing the environmental effects. Since nature of the given models is multi-objective, we suggest a number of goal-based solution techniques such L-P metric, goal programming, multi-choice goal programming and goal attainment in order to solve the problems.

Keywords: location, multi-echelon supply chain, covering, goal programming

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8110 A Machine Learning Model for Dynamic Prediction of Chronic Kidney Disease Risk Using Laboratory Data, Non-Laboratory Data, and Metabolic Indices

Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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8109 Intensive Use of Software in Teaching and Learning Calculus

Authors: Nodelman V.

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Despite serious difficulties in the assimilation of the conceptual system of Calculus, software in the educational process is used only occasionally, and even then, mainly for illustration purposes. The following are a few reasons: The non-trivial nature of the studied material, Lack of skills in working with software, Fear of losing time working with software, The variety of the software itself, the corresponding interface, syntax, and the methods of working with the software, The need to find suitable models, and familiarize yourself with working with them, Incomplete compatibility of the found models with the content and teaching methods of the studied material. This paper proposes an active use of the developed non-commercial software VusuMatica, which allows removing these restrictions through Broad support for the studied mathematical material (and not only Calculus). As a result - no need to select the right software, Emphasizing the unity of mathematics, its intrasubject and interdisciplinary relations, User-friendly interface, Absence of special syntax in defining mathematical objects, Ease of building models of the studied material and manipulating them, Unlimited flexibility of models thanks to the ability to redefine objects, which allows exploring objects characteristics, and considering examples and counterexamples of the concepts under study. The construction of models is based on an original approach to the analysis of the structure of the studied concepts. Thanks to the ease of construction, students are able not only to use ready-made models but also to create them on their own and explore the material studied with their help. The presentation includes examples of using VusuMatica in studying the concepts of limit and continuity of a function, its derivative, and integral.

Keywords: counterexamples, limitations and requirements, software, teaching and learning calculus, user-friendly interface and syntax

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8108 Federated Knowledge Distillation with Collaborative Model Compression for Privacy-Preserving Distributed Learning

Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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8107 Nasopharyngeal Cancer in Children and Adolescents: Experience of Emir Abdelkader Cancer Center of Oran Algeria

Authors: Taleb L., Benarbia M., Brahmi M., Belmiloud H., Boukerche A.

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Introduction and purpose of the study: Cavum cancer in children and adolescents is rare and represents 8% of all nasopharyngeal cancers treated in our department. Our objective is to study its epidemiological, clinical, therapeutic, and evolutionary particularities. Material and methods: Retrospective study of 39 patients under 20 years old, treated for undifferentiated non-metastatic carcinoma of the nasopharynx at the Emir Abdelkader Cancer Center between 2014 and 2020. Results and statistical analysis: Median age was 14 years [7-19 years], with a sex ratio of 2.9. The median time to diagnosis was 5.6 months [1 to 14 months], the circumstances of the discovery of which were dominated by lymph node syndrome in 43.6% of cases (n=17) followed by a rhinological syndrome in 30.8% of cases (n=13). The tumor stage was T1 for two patients (5.1%), T2 for 8 (20.5%), T3 for 9 (23.1%), T4 for 20 (51.3%), N0 for 2 (5 .1%) N1 for 4 (10.3%), N2 for 28 (71.8%) and N3 for 5 (12.8%). All patients received induction chemotherapy followed by concomitant radiotherapy with cisplatin. The dose of irradiation delivered to the cavum and adenopathies was 66 Gy with fractionation of 2 Gy per session in 69.2% of cases (n=27) and 1.8 Gy in 30.8% of cases (n=12). With a median follow-up of 51 months (15 to 97 months), the locoregional, metastatic, specific, and overall relapse-free survival rates at five years were 91.1%, 73.5%, 66.1%, and 68.4, respectively. Conclusion: Chemotherapy and radiotherapy treatment of cavum cancer in children and adolescents has allowed excellent locoregional control despite the advanced stage of the disease. However, the frequency of metastatic relapses could justify the possible use of systemic maintenance treatment.

Keywords: cancer, nasopharynx, radiotherapy, chemotherapy, survival

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8106 Effect of Different Feed Composition on the Growth Performance in Early Weaned Piglets

Authors: Obuzor Eze Obuzor, Ekpoke Okurube Sliver

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The study was carried out at Debee farms at Ahoada West Local Government area, Rivers State, Nigeria. To evaluate the impact of two different cost-effective available feed composition on growth performance of weaned piglets. Thirty weaned uncontrolled cross bred (Large white x pietrain) piglets of average initial weight of 3.04 Kg weaned at 30days were assigned to three dietary treatments, comprising three replicates of 10 weaned piglets each, piglets were kept at 7 °C in different pens with dimensions of 4.50 × 4.50 m. The design of the experiment was completely randomized design, data from the study were subjected to one-way analysis of variance (ANOVA) and significant means were separated using Duncan's Multiple Range Test using Statistical Analysis System (SAS) software for windows (2 0 0 3), statistical significance was assessed at P < 0.05 (95% confidence interval) while survival rate was calculated using simple percentage. A standard diet was prepared to meet the nutrient requirements of weaned piglets at (20.8% crude protein). The three diets were fed to the animals in concrete feeding trough, control diet (C) had soybean meal while first treatment had spent grain (T1) and the second treatment had wheat offal (T2) respectively. The experiment was partitioned into four weeks periods (days 1-7, 8-14, 15-21 and 22-28). Feed and water were given unrestrictedly throughout the period of the experiment. The feed intake and weights of the pigs were recorded on weekly basis. Feed conversion ratio and daily weight gain were calculated and the study lasted for four weeks. There was no significant (P>0.05) effect of diet on survival rate, final body weight, average daily weight gain, daily feed intake and feed conversion ratio. The overall performance showed that treatment one (T1) had survival rate (93%), improved daily weight gain (36.21 g), average daily feed intake (120.14 g) and had the best feed conversion ratio (0.29) similar high mean value with the control while treatment two (T2) had lowest and negative response to all parameters. It could be concluded that feed formulated with spent grain is cheaper than control (soybean meal) and also improved the growth performance of weaned piglets.

Keywords: piglets, weaning, feed conversions ratio, daily weight gain

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8105 Nanoparticles on Biological Biomarquers Models: Paramecium Tetraurelia and Helix aspersa

Authors: H. Djebar, L. Khene, M. Boucenna, M. R. Djebar, M. N. Khebbeb, M. Djekoun

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Currently in toxicology, use of alternative models permits to understand the mechanisms of toxicity at different levels of cells. Objectives of our research concern the determination of NPs ZnO, TiO2, AlO2, and FeO2 effect on ciliate protist freshwater Paramecium sp and Helix aspersa. The result obtained show that NPs increased antioxidative enzyme activity like catalase, glutathione –S-transferase and level GSH. Also, cells treated with high concentrations of NPs showed a high level of MDA. In conclusion, observations from growth and enzymatic parameters suggest on one hand that treatment with NPs provokes an oxidative stress and on the other that snale and paramecium are excellent alternatives models for ecotoxicological studies.

Keywords: NPs, GST, catalase, GSH, MDA, toxicity, snale and paramecium

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8104 Evaluation of Radio Protective Potential of Indian Bamboo Leaves

Authors: Mansi Patel, Priti Mehta

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Background: Ionizing radiations have detrimental effects on humans, and the growing technological encroachment has increased human exposure to it enormously. So, the safety issues have emphasized researchers to develop radioprotector from natural resources having minimal toxicity. A substance having anti-inflammatory, antioxidant, and immunomodulatory activity can be a potential candidate for radioprotection. One such plant with immense potential i.e. Bamboo was selected for the present study. Purpose: The study aims to evaluate the potential of Indian bamboo leaves for protection against the clastogenic effect of gamma radiation. Methods: The protective effect of bamboo leaf extract against gamma radiation-induced genetic damage in human peripheral blood lymphocytes (HPBLs) was evaluated in vitro using Cytokinesis blocked micronuclei assay (CBMN). The blood samples were pretreated with varying concentration of extract 30 min before the radiation exposure (4Gy & 6Gy). The reduction in the frequency of micronuclei was observed for the irradiated and control groups. The effect of various concentration of bamboo leaf extract (400,600,800 mg/kg) on the development of radiation induced sickness and altered mortality in mice exposed to 8 Gy of whole-body gamma radiation was studied. The developed symptoms were clinically scored by multiple endpoints for 30 days. Results: Treatment of HPBLs with varying concentration of extract before exposure to a different dose of γ- radiation resulted in significant (P < 0.0001) decline of radiation induced micronuclei. It showed dose dependent and concentration driven activity. The maximum protection ~ 70% was achieved at nine µg/ml concentration. Extract treated whole body irradiated mice showed 50%, 83.3% and 100% survival for 400, 600, and 800mg/kg with 1.05, 0.43 and 0 clinical score respectively when compared to Irradiated mice having 6.03 clinical score and 0% survival. Conclusion: Our findings indicate bamboo leaf extract reduced the radiation induced cytogenetic damage. It has also increased the survival ratio and reduced the radiation induced sickness and mortality when exposed to a lethal dose of gamma radiation.

Keywords: bamboo leaf extract, Cytokinesis blocked micronuclei (CBMN) assay, ionizing radiation, radio protector

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8103 Maintenance of Non-Crop Plants Reduces Insect Pest Population in Tropical Chili Pepper Agroecosystems

Authors: Madelaine Venzon, Dany S. S. L. Amaral, André L. Perez, Natália S. Diaz, Juliana A. Martinez Chiguachi, Maira C. M. Fonseca, James D. Harwood, Angelo Pallini

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Integrating strategies of sustainable crop production and promoting the provisioning of ecological services on farms and within rural landscapes is a challenge for today’s agriculture. Habitat management, through increasing vegetational diversity, enhances heterogeneity in agroecosystems and has the potential to improve the recruitment of natural enemies of pests, which promotes biological control services. In tropical agroecosystems, however, there is a paucity of information pertaining to the resources provided by associated plants and their interactions with natural enemies. The maintenance of non-crop plants integrated into and/or surrounding crop fields provides the farmer with a low-investment option to enhance biological control. We carried out field experiments in chili pepper agroecosystems with small stakeholders located in the Zona da Mata, State of Minas Gerais, Brazil, from 2011 to 2015 where we assessed: (a) whether non-crop plants within and around chili pepper fields affect the diversity and abundance of aphidophagous species; (b) whether there are direct interactions between non-crop plants and aphidophagous arthropods; and (c) the importance of non-crop plant resources for survival of Coccinellidae and Chrysopidae species. Aphidophagous arthropods were dominated by Coccinellidae, Neuroptera, Syrphidae, Anthocoridae and Araneae. These natural enemies were readily observed preying on aphids, feeding on flowers or extrafloral nectaries and using plant structures for oviposition and/or protection. Aphid populations were lower on chili pepper fields associated with non-crop plants that on chili pepper monocultures. Survival of larvae and adults of different species of Coccinellidae and Chrysopidae on non-crop resources varied according to the plant species. This research provides evidence that non-crop plants in chili pepper agroecosystems can affect aphid abundance and their natural enemy abundance and survival. It is also highlighting the need for further research to fully characterize the structure and function of plant resources in these and other tropical agroecosystems. Financial support: CNPq, FAPEMIG and CAPES (Brazil).

Keywords: Conservation biological control, aphididae, Coccinellidae, Chrysopidae, plant diversification

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8102 The Effect of Nursing Teamwork Training on Nursing Teamwork Effectiveness

Authors: Manar Ahmed Elbadawy

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Background: Empirical evidence suggested that improving nursing teamwork (NTW) may be the key to reducing medical error. The functioning nursing teams require open communication, mutual respect, and shared mental models to activate quality patient care. The complexity and the high demands for specialized nursing knowledge and skill also require nursing staff to consult with one another and work in teams regularly. The current study aimed to evaluate the effect of the nursing teamwork training program on nursing teamwork effectiveness. Design: A quasi-experimental (one group pretest-posttest) design was utilized. Three medical intensive care units at a teaching hospital affiliated to Cairo University Hospital, Egypt. Subjects: A convenient sample of 48 nursing staff worked at the selected units. The Nursing Teamwork Observational Checklist was used. Results: Total (NTW) mean scores exhibited quite elevation post-program implementation compared to preprogram and showed little decrease 3 months later ( = 2.52, SD = ± 0.27, mean % =51.98, = 2.72, SD = ± 0.20, mean %=72.45, = 2.67, SD = ± 0.11, mean %= 67.48 respectively). Conclusion: Implementation of (NTW) training program had a positive effect on increasing (NTW) effectiveness. Regular and frequent short-term teamwork training is important to be introduced as well as sustainable monitoring is required to ensure nursing attitudes, knowledge and skills’ change about teamwork effectiveness.

Keywords: effectiveness, nursing, teamwork, training

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8101 Exposure to Bullying and General Psychopathology: A Prospective, Longitudinal Study

Authors: Jolien Rijlaarsdam, Charlotte A. M. Cecil, J. Marieke Buil, Pol A. C. Van Lier, Edward D. Barker

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Although there is mounting evidence that the experience of being bullied associates with both internalizing and externalizing symptoms, it is not known yet whether the identified associations are specific to these symptoms or shared between them. The primary focus of this study is to assess the prospective associations of bullying exposure with both general and specific (i.e., internalizing, externalizing) factors of psychopathology. This study included data from 6,210 children participating in the Avon Longitudinal Study of Parents and Children (ALSPAC). Child bullying was measured by self-report at ages 8 and 10 years. Child psychopathology symptoms were assessed by parent-interview, using the Development and Well-being Assessment (DAWBA) at ages 7 and 13 years. Bullying exposure is significantly associated with the general psychopathology factor in early adolescence. In particular, chronically victimized youth exposed to multiple forms of bullying (i.e., both overt and relational) showed the highest levels of general psychopathology. Bullying exposure is also associated with both internalizing and externalizing factors from the correlated-factors model. However, the effect estimates for these factors decreased considerably in size and dropped to insignificant for the internalizing factor after extracting the shared variance that belongs to the general factor of psychopathology. In an integrative longitudinal model, higher levels of general psychopathology at age seven are associated with bullying exposure at age eight, which, in turn, is associated with general psychopathology at age 13 through its two-year continuity. Findings suggest that exposure to bullying is a risk factor for a more general vulnerability to psychopathology through mutually influencing relationships.

Keywords: bullying exposure, externalizing, general psychopathology, internalizing, longitudinal

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8100 A Large Language Model-Driven Method for Automated Building Energy Model Generation

Authors: Yake Zhang, Peng Xu

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The development of building energy models (BEM) required for architectural design and analysis is a time-consuming and complex process, demanding a deep understanding and proficient use of simulation software. To streamline the generation of complex building energy models, this study proposes an automated method for generating building energy models using a large language model and the BEM library aimed at improving the efficiency of model generation. This method leverages a large language model to parse user-specified requirements for target building models, extracting key features such as building location, window-to-wall ratio, and thermal performance of the building envelope. The BEM library is utilized to retrieve energy models that match the target building’s characteristics, serving as reference information for the large language model to enhance the accuracy and relevance of the generated model, allowing for the creation of a building energy model that adapts to the user’s modeling requirements. This study enables the automatic creation of building energy models based on natural language inputs, reducing the professional expertise required for model development while significantly decreasing the time and complexity of manual configuration. In summary, this study provides an efficient and intelligent solution for building energy analysis and simulation, demonstrating the potential of a large language model in the field of building simulation and performance modeling.

Keywords: artificial intelligence, building energy modelling, building simulation, large language model

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8099 Key Factors for Stakeholder Engagement and Sustainable Development

Authors: Jo Rhodes, Bruce Bergstrom, Peter Lok, Vincent Cheng

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The aim of this study is to determine key factors and processes for multinationals (MNCs) to develop an effective stakeholder engagement and sustainable development framework. A qualitative multiple-case approach was used. A triangulation method was adopted (interviews, archival documents and observations) to collect data on three global firms (MNCs). 9 senior executives were interviewed for this study (3 from each firm). An initial literature review was conducted to explore possible practices and factors (the deductive approach) to sustainable development. Interview data were analysed using Nvivo to obtain appropriate nodes and themes for the framework. A comparison of findings from interview data and themes, factors developed from the literature review and cross cases comparison were used to develop the final conceptual framework (the inductive approach). The results suggested that stakeholder engagement is a key mediator between ‘stakeholder network’ (internal and external factors) and outcomes (corporate social responsibility, social capital, shared value and sustainable development). Key internal factors such as human capital/talent, technology, culture, leadership and processes such as collaboration, knowledge sharing and co-creation of value with stakeholders were identified. These internal factors and processes must be integrated and aligned with external factors such as social, political, cultural, environment and NGOs to achieve effective stakeholder engagement.

Keywords: stakeholder, engagement, sustainable development, shared value, corporate social responsibility

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8098 A Novel Algorithm for Parsing IFC Models

Authors: Raninder Kaur Dhillon, Mayur Jethwa, Hardeep Singh Rai

Abstract:

Information technology has made a pivotal progress across disparate disciplines, one of which is AEC (Architecture, Engineering and Construction) industry. CAD is a form of computer-aided building modulation that architects, engineers and contractors use to create and view two- and three-dimensional models. The AEC industry also uses building information modeling (BIM), a newer computerized modeling system that can create four-dimensional models; this software can greatly increase productivity in the AEC industry. BIM models generate open source IFC (Industry Foundation Classes) files which aim for interoperability for exchanging information throughout the project lifecycle among various disciplines. The methods developed in previous studies require either an IFC schema or MVD and software applications, such as an IFC model server or a Building Information Modeling (BIM) authoring tool, to extract a partial or complete IFC instance model. This paper proposes an efficient algorithm for extracting a partial and total model from an Industry Foundation Classes (IFC) instance model without an IFC schema or a complete IFC model view definition (MVD).

Keywords: BIM, CAD, IFC, MVD

Procedia PDF Downloads 300
8097 Forecasting Performance Comparison of Autoregressive Fractional Integrated Moving Average and Jordan Recurrent Neural Network Models on the Turbidity of Stream Flows

Authors: Daniel Fulus Fom, Gau Patrick Damulak

Abstract:

In this study, the Autoregressive Fractional Integrated Moving Average (ARFIMA) and Jordan Recurrent Neural Network (JRNN) models were employed to model the forecasting performance of the daily turbidity flow of White Clay Creek (WCC). The two methods were applied to the log difference series of the daily turbidity flow series of WCC. The measurements of error employed to investigate the forecasting performance of the ARFIMA and JRNN models are the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The outcome of the investigation revealed that the forecasting performance of the JRNN technique is better than the forecasting performance of the ARFIMA technique in the mean square error sense. The results of the ARFIMA and JRNN models were obtained by the simulation of the models using MATLAB version 8.03. The significance of using the log difference series rather than the difference series is that the log difference series stabilizes the turbidity flow series than the difference series on the ARFIMA and JRNN.

Keywords: auto regressive, mean absolute error, neural network, root square mean error

Procedia PDF Downloads 268
8096 Preliminary Conceptions of 3D Prototyping Model to Experimental Investigation in Hypersonic Shock Tunnels

Authors: Thiago Victor Cordeiro Marcos, Joao Felipe de Araujo Martos, Ronaldo de Lima Cardoso, David Romanelli Pinto, Paulo Gilberto de Paula Toro, Israel da Silveira Rego, Antonio Carlos de Oliveira

Abstract:

Currently, the use of 3D rapid prototyping, also known as 3D printing, has been investigated by some universities around the world as an innovative technique, fast, flexible and cheap for a direct plastic models manufacturing that are lighter and with complex geometries to be tested for hypersonic shock tunnel. Initially, the purpose is integrated prototyped parts with metal models that actually are manufactured through of the conventional machining and hereafter replace them with completely prototyped models. The mechanical design models to be tested in hypersonic shock tunnel are based on conventional manufacturing processes, therefore are limited forms and standard geometries. The use of 3D rapid prototyping offers a range of options that enables geometries innovation and ways to be used for the design new models. The conception and project of a prototyped model for hypersonic shock tunnel should be rethought and adapted when comparing the conventional manufacturing processes, in order to fully exploit the creativity and flexibility that are allowed by the 3D prototyping process. The objective of this paper is to compare the conception and project of a 3D rapid prototyping model and a conventional machining model, while showing the advantages and disadvantages of each process and the benefits that 3D prototyping can bring to the manufacture of models to be tested in hypersonic shock tunnel.

Keywords: 3D printing, 3D prototyping, experimental research, hypersonic shock tunnel

Procedia PDF Downloads 469
8095 Evolutionary Advantages of Loneliness with an Agent-Based Model

Authors: David Gottlieb, Jason Yoder

Abstract:

The feeling of loneliness is not uncommon in modern society, and yet, there is a fundamental lack of understanding in its origins and purpose in nature. One interpretation of loneliness is that it is a subjective experience that punishes a lack of social behavior, and thus its emergence in human evolution is seemingly tied to the survival of early human tribes. Still, a common counterintuitive response to loneliness is a state of hypervigilance, resulting in social withdrawal, which may appear maladaptive to modern society. So far, no computational model of loneliness’ effect during evolution yet exists; however, agent-based models (ABM) can be used to investigate social behavior, and applying evolution to agents’ behaviors can demonstrate selective advantages for particular behaviors. We propose an ABM where each agent contains four social behaviors, and one goal-seeking behavior, letting evolution select the best behavioral patterns for resource allocation. In our paper, we use an algorithm similar to the boid model to guide the behavior of agents, but expand the set of rules that govern their behavior. While we use cohesion, separation, and alignment for simple social movement, our expanded model adds goal-oriented behavior, which is inspired by particle swarm optimization, such that agents move relative to their personal best position. Since agents are given the ability to form connections by interacting with each other, our final behavior guides agent movement toward its social connections. Finally, we introduce a mechanism to represent a state of loneliness, which engages when an agent's perceived social involvement does not meet its expected social involvement. This enables us to investigate a minimal model of loneliness, and using evolution we attempt to elucidate its value in human survival. Agents are placed in an environment in which they must acquire resources, as their fitness is based on the total resource collected. With these rules in place, we are able to run evolution under various conditions, including resource-rich environments, and when disease is present. Our simulations indicate that there is strong selection pressure for social behavior under circumstances where there is a clear discrepancy between initial resource locations, and against social behavior when disease is present, mirroring hypervigilance. This not only provides an explanation for the emergence of loneliness, but also reflects the diversity of response to loneliness in the real world. In addition, there is evidence of a richness of social behavior when loneliness was present. By introducing just two resource locations, we observed a divergence in social motivation after agents became lonely, where one agent learned to move to the other, who was in a better resource position. The results and ongoing work from this project show that it is possible to glean insight into the evolutionary advantages of even simple mechanisms of loneliness. The model we developed has produced unexpected results and has led to more questions, such as the impact loneliness would have at a larger scale, or the effect of creating a set of rules governing interaction beyond adjacency.

Keywords: agent-based, behavior, evolution, loneliness, social

Procedia PDF Downloads 97
8094 Controlling Images and Survival Strategies for Muslim Women in Pakistan

Authors: Ayesha Murtza

Abstract:

Controlling images develop misinformed behaviors about impoverished Muslim Pakistani women that add to the oppression these Pakistani women endure their whole lives. Meanwhile, patriarchal and stereotypical societies provide an ideological justification for gender, class, and racial oppression, especially for women. Cojoining the concepts of controlling images by Patricia Hill Collins (1990) and binary thinking by Barbara Christian (1987), this paper discusses the ways in which various controlling images of urban and rural women are being presented in Pakistani dramas. These images reinforce an interlocking system of oppression for women in Pakistan. This paper further explores how these controlling images of intersecting components like class, gender, religion, ethnicity, physical appearance, color, and caste normalize hegemonic gendered oppression in society and how men have the same attitude towards women of their family whether they belong to the rural or urban class since they are the product of the same society. It further sheds light on how these matrixes of domination are an inevitable part of Pakistani women’s everyday lives and how these women reinforce survival strategies for coping with all these forms of oppression. By employing the feminist interactional framework, this paper elucidates the role of masculinity, femininity, feminist activism, and traditional knowledge against a monolithic image of Pakistani women. By highlighting these, this paper complicates the role of descriptive and visual images, religion, women’s rights, and the stereotypical role of women in Pakistani dramas.

Keywords: controlling images, oppression, women, Pakistan

Procedia PDF Downloads 85
8093 Mesozooplankton in the Straits of Florida: Patterns in Biomass and Distribution

Authors: Sharein El-Tourky, Sharon Smith, Gary Hitchcock

Abstract:

Effective fisheries management is necessarily dependent on the accuracy of fisheries models, which can be limited if they omit critical elements. One critical element in the formulation of these models is the trophic interactions at the larval stage of fish development. At this stage, fish mortality rates are at their peak and survival is often determined by resource limitation. Thus it is crucial to identify and quantify essential prey resources and determine how they vary in abundance and availability. The main resources larval fish consume are mesozooplankton. In the Straits of Florida, little is known about temporal and spatial variability of the mesozooplankton community despite its importance as a spawning ground for fish such as the Blue Marlin. To investigate mesozooplankton distribution patterns in the Straits of Florida, a transect of 16 stations from Miami to the Bahamas was sampled once a month in 2003 and 2004 at four depths. We found marked temporal and spatial variability in mesozooplankton biomass, diversity, and depth distribution. Mesozooplankton biomass peaked on the western boundary of the SOF and decreased gradually across the straits to a minimum at eastern stations. Midcurrent stations appeared to be a region of enhanced year-round variability, but limited seasonality. Examination of dominant zooplankton groups revealed groups could be parsed into 6 clusters based on abundance. Of these zooplankton groups, copepods were the most abundant zooplankton group, with the 20 most abundant species making up 86% of the copepod community. Copepod diversity was lowest at midcurrent stations and highest in the Eastern SOF. Interestingly, one copepods species, previously identified to compose up to 90% of larval blue marlin and sailfish diets in the SOF, had a mean abundance of less than 7%. However, the unique spatial and vertical distribution patterns of this copepod coincide with peak larval fish spawning periods and larval distribution, suggesting an important relationship requiring further investigation.

Keywords: mesozooplankton biodiversity, larval fish diet, food web, Straits of Florida, vertical distribution, spatiotemporal variability, cross-current comparisons, Gulf Stream

Procedia PDF Downloads 552
8092 Protein Stabilized Foam Structures as Protective Carrier Systems during Microwave Drying of Probiotics

Authors: Jannika Dombrowski, Sabine Ambros, Ulrich Kulozik

Abstract:

Due to the increasing popularity of healthy products, probiotics are still of rising importance in food manufacturing. With the aim to amplify the field of probiotic application to non-chilled products, the cultures have to be preserved by drying. Microwave drying has proved to be a suitable technique to achieve relatively high survival rates, resulting from drying at gentle temperatures, among others. However, diffusion limitation due to compaction of cell suspension during drying can prolong drying times as well as deteriorate product properties (grindability, rehydration performance). Therefore, we aimed to embed probiotics in an aerated matrix of whey proteins (surfactants) and di-/polysaccharides (foam stabilization, probiotic protection) during drying. As a result of the manifold increased inner surface of the cell suspension, drying performance was enhanced significantly as compared to non-foamed suspensions. This work comprises investigations on suitable foam matrices, being stable under vacuum (variation of protein concentration, type and concentration of di-/polysaccharide) as well as development of an applicable microwave drying process in terms of microwave power, chamber pressure and maximum product temperatures. Performed analyses included foam characteristics (overrun, drainage, firmness, bubble sizes), and properties of the dried cultures (survival, activity). In addition, efficiency of the drying process was evaluated.

Keywords: foam structure, microwave drying, polysaccharides, probiotics

Procedia PDF Downloads 262
8091 Neural Machine Translation for Low-Resource African Languages: Benchmarking State-of-the-Art Transformer for Wolof

Authors: Cheikh Bamba Dione, Alla Lo, Elhadji Mamadou Nguer, Siley O. Ba

Abstract:

In this paper, we propose two neural machine translation (NMT) systems (French-to-Wolof and Wolof-to-French) based on sequence-to-sequence with attention and transformer architectures. We trained our models on a parallel French-Wolof corpus of about 83k sentence pairs. Because of the low-resource setting, we experimented with advanced methods for handling data sparsity, including subword segmentation, back translation, and the copied corpus method. We evaluate the models using the BLEU score and find that transformer outperforms the classic seq2seq model in all settings, in addition to being less sensitive to noise. In general, the best scores are achieved when training the models on word-level-based units. For subword-level models, using back translation proves to be slightly beneficial in low-resource (WO) to high-resource (FR) language translation for the transformer (but not for the seq2seq) models. A slight improvement can also be observed when injecting copied monolingual text in the target language. Moreover, combining the copied method data with back translation leads to a substantial improvement of the translation quality.

Keywords: backtranslation, low-resource language, neural machine translation, sequence-to-sequence, transformer, Wolof

Procedia PDF Downloads 147
8090 The Influence of Contact Models on Discrete Element Modeling of the Ballast Layer Subjected to Cyclic Loading

Authors: Peyman Aela, Lu Zong, Guoqing Jing

Abstract:

Recently, there has been growing interest in numerical modeling of ballast railway tracks. A commonly used mechanistic modeling approach for ballast is the discrete element method (DEM). Up to now, the effects of the contact model on ballast particle behavior have not been precisely examined. In this regard, selecting the appropriate contact model is mainly associated with the particle characteristics and the loading condition. Since ballast is cohesionless material, different contact models, including the linear spring, Hertz-Mindlin, and Hysteretic models, could be used to calculate particle-particle or wall-particle contact forces. Moreover, the simulation of a dynamic test is vital to investigate the effect of damping parameters on the ballast deformation. In this study, ballast box tests were simulated by DEM to examine the influence of different contact models on the mechanical behavior of the ballast layer under cyclic loading. This paper shows how the contact model can affect the deformation and damping of a ballast layer subjected to cyclic loading in a ballast box.

Keywords: ballast, contact model, cyclic loading, DEM

Procedia PDF Downloads 197
8089 Suppression of Immunostimulatory Function of Dendritic Cells and Prolongation of Skin Allograft Survival by Dryocrassin

Authors: Hsin-Lien Lin, Ju-Hui Fu

Abstract:

Dendritic cells (DCs) are the major professional antigen-presenting cells for the development of optimal T-cell immunity. DCs can be used as pharmacological targets to screen novel biological modifiers for the treatment of harmful immune responses, such as transplantation rejection. Dryopteris crassirhizoma Nakai (Aspiadaceae) is used for traditional herbal medicine in the region of East Asia. The root of this fern plant has been listed for treating inflammatory diseases. Dryocrassin is the tetrameric phlorophenone component derived from Dryopteris. Here, we tested the immunomodulatory potential of dryocrassin on lipopolysaccharide (LPS)-stimulated activation of mouse bone marrow-derived DCs in vitro and in skin allograft transplantation in vivo. Results demonstrated that dryocrassin reduced the secretion of tumor necrosis factor-α, interleukin-6, and interleukin-12p70 by LPS-stimulated DCs. The expression of LPS-induced major histocompatibility complex class II, CD40, and CD86 on DCs was also blocked by dryocrassin. Moreover, LPS-stimulated DC-elicited allogeneic T-cell proliferation was lessened by dryocrassin. In addition, dryocrassin inhibited LPS-induced activation of IϰB kinase, JNK/p38 mitogen-activated protein kinase, as well as the translocation of NF-ϰB. Treatment with dryocrassin obviously diminished 2,4-dinitro-1-fluorobenzene- induced delayed-type hypersensitivity and prolonged skin allograft survival. Dryocrassin may be one of the potent immunosuppressive agents for transplant rejection through the destruction of DC maturation and function.

Keywords: dryocrassin, dendritic cells, immunosuppression, skin allograft

Procedia PDF Downloads 386
8088 Interpretation of Ultrasonic Backscatter of Linear FM Chirp Pulses from Targets Having Frequency-Dependent Scattering

Authors: Stuart Bradley, Mathew Legg, Lilyan Panton

Abstract:

Ultrasonic remote sensing is a useful tool for assessing the interior structure of complex targets. For these methods, significantly enhanced spatial resolution is obtained if the pulse is coded, for example using a linearly changing frequency during the pulse duration. Such pulses have a time-dependent spectral structure. Interpretation of the backscatter from targets is, therefore, complicated if the scattering is frequency-dependent. While analytic models are well established for steady sinusoidal excitations applied to simple shapes such as spheres, such models do not generally exist for temporally evolving excitations. Therefore, models are developed in the current paper for handling such signals so that the properties of the targets can be quantitatively evaluated while maintaining very high spatial resolution. Laboratory measurements on simple shapes are used to confirm the validity of the models.

Keywords: linear FM chirp, time-dependent acoustic scattering, ultrasonic remote sensing, ultrasonic scattering

Procedia PDF Downloads 317