Search results for: pragmatic function

Authors: Samir Khene

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Present and future industrial uses of high critical temperature superconductors require high critical temperatures TC and strong current densities JC. These two aims constitute the two motivations of the scientific research in this domain. The most significant feature of any superconductor, from the viewpoint of uses, is the maximum electrical transport current density that this superconductor is capable of withstanding without loss of energy. In this work, vortices pinning in conventional and high-TC superconductors will be studied. Our experiments on vortices pinning in single crystals and nanoparticles of YBa2Cu3O7- and La1.85 Sr0.15CuO will be presented. It will be given special attention to the study of the YBa2Cu3O7- nanoparticles doped by ferromagnetic nanoparticles of Y3Fe5O12. The ferromagnetism and superconductivity coexistence in this compound will be demonstrated, and the influence of these ferromagnetic nanoparticles on the variations of the critical current density JC in YBa2Cu3O7- nanoparticles as a function of applied field H and temperature T will be studied.

Keywords: ferromagnetism, superconductivity, coexistence, magnetic material

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Authors: Christoph Ramsauer, Jaydeep Karandikar, Tony Schmitz, Friedrich Bleicher

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Machining stability is an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the Vienna University of Technology, Vienna, Austria. The recorded data from a milling test cut is used to classify the cut as stable or unstable based on the frequency analysis. The test cut result is fed to a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculates the probability of stability as a function of axial depth of cut and spindle speed and recommends the parameters for the next test cut. The iterative process between two transatlantic locations repeats until convergence to a stable optimal process parameter set is achieved.

Keywords: machining stability, machine learning, sensor, optimization

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Stojan Kravanja, Andrej Ivanič, Tomaž Žula

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This contribution focuses on structural optimization in civil engineering using mixed integer non-linear programming (MINLP). MINLP is characterized as a versatile method that can handle both continuous and discrete optimization variables simultaneously. Continuous variables are used to optimize parameters such as dimensions, stresses, masses, or costs, while discrete variables represent binary decisions to determine the presence or absence of structural elements within a structure while also calculating discrete materials and standard sections. The optimization process is divided into three main steps. First, a mechanical superstructure with a variety of different topology-, material- and dimensional alternatives. Next, a MINLP model is formulated to encapsulate the optimization problem. Finally, an optimal solution is searched in the direction of the defined objective function while respecting the structural constraints. The economic or mass objective function of the material and labor costs of a structure is subjected to the constraints known from structural analysis. These constraints include equations for the calculation of internal forces and deflections, as well as equations for the dimensioning of structural components (in accordance with the Eurocode standards). Given the complex, non-convex and highly non-linear nature of optimization problems in civil engineering, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm is applied. This algorithm alternately solves subproblems of non-linear programming (NLP) and main problems of mixed-integer linear programming (MILP), in this way gradually refines the solution space up to the optimal solution. The NLP corresponds to the continuous optimization of parameters (with fixed topology, discrete materials and standard dimensions, all determined in the previous MILP), while the MILP involves a global approximation to the superstructure of alternatives, where a new topology, materials, standard dimensions are determined. The optimization of a convex problem is stopped when the MILP solution becomes better than the best NLP solution. Otherwise, it is terminated when the NLP solution can no longer be improved. While the OA/ER algorithm, like all other algorithms, does not guarantee global optimality due to the presence of non-convex functions, various modifications, including convexity tests, are implemented in OA/ER to mitigate these difficulties. The effectiveness of the proposed MINLP approach is demonstrated by its application to various structural optimization tasks, such as mass optimization of steel buildings, cost optimization of timber halls, composite floor systems, etc. Special optimization models have been developed for the optimization of these structures. The MINLP optimizations, facilitated by the user-friendly software package MIPSYN, provide insights into a mass or cost-optimal solutions, optimal structural topologies, optimal material and standard cross-section choices, confirming MINLP as a valuable method for the optimization of structures in civil engineering.

Keywords: MINLP, mixed-integer non-linear programming, optimization, structures

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Authors: Hae-Yeoun Lee

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Quantification of cardiac function is performed by calculating blood volume and ejection fraction in routine clinical practice. However, these works have been performed by manual contouring,which requires computational costs and varies on the observer. In this paper, an automatic left ventricle segmentation algorithm on cardiac magnetic resonance images (MRI) is presented. Using knowledge on cardiac MRI, a K-mean clustering technique is applied to segment blood region on a coil-sensitivity corrected image. Then, a graph searching technique is used to correct segmentation errors from coil distortion and noises. Finally, blood volume and ejection fraction are calculated. Using cardiac MRI from 15 subjects, the presented algorithm is tested and compared with manual contouring by experts to show outstanding performance.

Keywords: cardiac MRI, graph searching, left ventricle segmentation, K-means clustering

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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Authors: Heejin Song

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Employing a critical action research approach that rejects essentialist onto-epistemological orientations to research in English language teaching (ELT) and interrogates the hegemonic relations in the knowledge construction and reconstruction processes, this study illuminates how an action research-informed pedagogical practice can transform the English for academic purposes (EAP) teaching to be more culturally and linguistically inclusive and critically oriented for English language learners’ advancement in academic literacies skills. More specifically, this paper aims to showcase the action research-informed pedagogical innovations that emphasize multilingual learners’ multiliteracies engagement and experiential education-oriented learning to facilitate the development of learners’ academic literacies, intercultural communicative competence, and inclusive global citizenship in the context of Canadian university EAP classrooms. The pedagogical innovations through action research embarked in response to growing discussions surrounding pedagogical possibilities of plurilingualism in ELT and synchronous online teaching. The paper is based on two iterations of action research over the pandemic years between 2020 and 2022. The data includes student work samples, focus group interviews, anonymous surveys, teacher feedback and comments on student work and teaching reflections. The first iteration of the action research focused on the affordances of multimodal expressions in individual learners’ academic endeavors for their literacy skills development through individual online activities such as ‘my language autobiography,’ ‘multimodal expression corner’ and public speeches. While these activities help English language learners enhance their knowledge and skills of English-spoken discourses, these tasks did not necessarily require learners’ team-based collaborative endeavors to complete the assigned tasks. Identifying this area for improvement in the instructional design, the second action research cycle/iteration emphasized collaborative performativity through newly added performance/action-based innovative learning tasks, including ‘situational role-playing’, ‘my cooking show & interview’, and group debates in order to provide learners increased opportunities to communicate with peers who joined the class virtually from different parts of the world and enhance learners’ intercultural competence through various strategic and pragmatic communicative skills to collaboratively achieve their shared goals (i.e., successful completion of the given group tasks). The paper exemplifies instances wherein learners’ unique and diverse linguistic and cultural strengths were amplified, and critical literacies were further developed through learners’ performance-oriented multiliteracies engagement. The study suggests that the action research-informed teaching practice that advocates for collaborative multiliteracies engagement serves to facilitate learners’ activation of their existing linguistic and cultural knowledge and contributes to the development of learners’ academic literacy skills. Importantly, the study illuminates that such action research-informed pedagogical initiatives create an inclusive space for learners to build a strong sense of connectedness as global citizens with increased intercultural awareness in their community of language and cultural practices, and further allow learners to actively participate in the construction of ‘collaborative relations of power’ with their peers.

Keywords: action research, EAP, higher education, multiliteracies

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Authors: Yoshino Murakami, Takeshi Hashimoto, Steve Cole

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The autonomic nervous system (ANS), particularly the sympathetic (SNS) and parasympathetic (PNS) branches, plays a vital role in modulating immune function and physiological homeostasis. In recent years, the Conserved Transcriptional Response to Adversity (CTRA) has emerged as a key marker of the body's response to chronic stress. This gene expression profile is characterized by SNS-mediated upregulation of pro-inflammatory genes (such as IL1B and TNF) and downregulation of antiviral response genes (e.g., IFI and MX families). CTRA has been observed in individuals exposed to prolonged stressors like loneliness, social isolation, and bereavement. Some research suggests that PNS activity, as indicated by heart rate variability (HRV), may help counteract the CTRA. However, previous PNS-CTRA studies have focused on Western populations, raising questions about the generalizability of these findings across different cultural and ethnic backgrounds. This study aimed to examine the relationship between HRV and CTRA gene expression in young, healthy adults in Japan. We hypothesized that HRV would be inversely related to CTRA gene expression, similar to patterns observed in previous Western studies. A total of 49 participants aged 20 to 39 were recruited, and after data exclusions, 26 participants' HRV and CTRA data were analyzed. HRV was measured using an electrocardiogram (ECG), and two time-domain indices were utilized: the root mean square of successive differences (RMSSD) and the standard deviation of NN intervals (SDNN). Blood samples were collected for gene expression analysis, focusing on a standard set of 47 CTRA indicator gene transcripts. it findings revealed a significant inverse relationship between HRV and CTRA gene expression, with higher HRV correlating with reduced pro-inflammatory gene activity and increased antiviral response. These results are consistent with findings from Western populations and demonstrate that the relationship between ANS function and immune response generalizes to an East Asian population. The study highlights the importance of HRV as a biomarker for psychophysiological health, reflecting the body's ability to buffer stress and maintain immune balance. These findings have implications for understanding how physiological systems interact across different cultures and ethnicities. Given the influence of chronic stress in promoting inflammation and disease risk, interventions aimed at improving HRV, such as mindfulness-based practices or physical exercise, could provide significant health benefits. Future research should focus on larger sample sizes and experimental interventions to better understand the causal pathways linking HRV to CTRA gene expression, and determine whether improving HRV may help mitigate the harmful effects of stress on health by reducing inflammation.

Keywords: autonomic nervous activity, neuroendocrine system, inflammation, Japan

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Authors: Sergio J. Calleja, Adria Roca, José D. Santotoribio

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Pancreatic endocrine diseases include pathologies like insulin resistance (IR), prediabetes, and type 2 diabetes mellitus (DM2). Some of them are highly prevalent in the U.S.—40% of U.S. adults have IR, 38% of U.S. adults have prediabetes, and 12% of U.S. adults have DM2—, as reported by the National Center for Biotechnology Information (NCBI). Building upon this imperative, the objective of the present study was to develop a non-invasive test for the assessment of the patient’s pancreatic endocrine function and to evaluate its accuracy in detecting various pancreatic endocrine diseases, such as IR, prediabetes, and DM2. This approach to a routine blood and urine test is based around serum and urine biomarkers. It is made by the combination of several independent public algorithms, such as the Adult Treatment Panel III (ATP-III), triglycerides and glucose (TyG) index, homeostasis model assessment-insulin resistance (HOMA-IR), HOMA-2, and the quantitative insulin-sensitivity check index (QUICKI). Additionally, it incorporates essential measurements such as the creatinine clearance, estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (ACR), and urinalysis, which are helpful to achieve a full image of the patient’s pancreatic endocrine disease. To evaluate the estimated accuracy of this test, an iterative process was performed by a machine learning (ML) algorithm, with a training set of 9,391 patients. The sensitivity achieved was 97.98% and the specificity was 99.13%. Consequently, the area under the receiver operating characteristic (AUROC) curve, the positive predictive value (PPV), and the negative predictive value (NPV) were 92.48%, 99.12%, and 98.00%, respectively. The algorithm was validated with a randomized controlled trial (RCT) with a target sample size (n) of 314 patients. However, 50 patients were initially excluded from the study, because they had ongoing clinically diagnosed pathologies, symptoms or signs, so the n dropped to 264 patients. Then, 110 patients were excluded because they didn’t show up at the clinical facility for any of the follow-up visits—this is a critical point to improve for the upcoming RCT, since the cost of each patient is very high and for this RCT almost a third of the patients already tested were lost—, so the new n consisted of 154 patients. After that, 2 patients were excluded, because some of their laboratory parameters and/or clinical information were wrong or incorrect. Thus, a final n of 152 patients was achieved. In this validation set, the results obtained were: 100.00% sensitivity, 100.00% specificity, 100.00% AUROC, 100.00% PPV, and 100.00% NPV. These results suggest that this approach to a routine blood and urine test holds promise in providing timely and accurate diagnoses of pancreatic endocrine diseases, particularly among individuals aged 40 and above. Given the current epidemiological state of these type of diseases, these findings underscore the significance of early detection. Furthermore, they advocate for further exploration, prompting the intention to conduct a clinical trial involving 26,000 participants (from March 2025 to December 2026).

Keywords: algorithm, diabetes, laboratory medicine, non-invasive

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Authors: Dnaya Soukaina

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It’s over six decades that Reverse logistics had appeared as a research area, and it is emerging again and again in the scientific fields. As reverse logistics presents real potential for value recovery and environmental impacts decrease, it’s still necessary to extend this concept more in the industrial and commercial field especially in developing countries. The process of reverse logistics is a progression of steps beginning with the customer and finishing with the organization or even the customer, however the issue is that this cycle must be adjustable to the organization concerned, in addition of legislative, operational, financial and social obstacles. Literature had demonstrated that there are many other uncertainties while the implementation of this process that vary in function of the sector concerned and the kind of activity. Besides, even if literature is developing this topic over the last years, reseraches about uncertainties quantification in reverse logistics process still being few. the paper has the objective to fill this gap, and carry out a study to identify sustainable strategies that can be adapted to different industrial or commercial sectors to facilitate the implementation of reverse logistics.

Keywords: reverse logistics, implementation, unceratinties quantification, mathematical model

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Authors: Thu Le Thi Bao

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Industrial parks have both active roles in promoting economic development and source of appearance of boarding houses and slums in the adjacent area, lacking infrastructure, causing many social evils. The context of the recent pandemic and climate change on a global scale pose issues that need to be resolved for sustainable development. Ho Chi Minh City aims to develop housing for migrant workers to stabilize human resources and, at the same time, solve problems of social evils caused by poor living conditions. The paper focuses on the content of renovating existing industrial parks and worker accommodation in Ho Chi Minh City to propose appropriate models, contributing to the goal of urban embellishment and solutions for industrial parks to adapt to abnormal impact conditions such as pandemics, climate change, crises.

Keywords: industrial park, social housing, accommodation, distribution center

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Authors: Tiee-Jian Wu, Chih-Yuan Hsu

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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

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Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

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Authors: Samira Mohabbatdar, Abbas Ahmadi, Mohsen S. Sajadieh

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This paper deals with a two-level supply chain consisted of one manufacturer and one retailer for single-type product. The demand function of the customers depends on price. We consider an integrated production inventory system where the manufacturer processes raw materials in order to deliver finished product with imperfect quality to the retailer. Then retailer inspects the products and after that delivers perfect products to customers. The proposed model is based on the joint total profit of both the manufacturer and the retailer, and it determines the optimal ordering lot-size, number of shipment and selling price of the retailer. A numerical example is provided to analyse and illustrate the behaviour and application of the model. Finally, sensitivity analysis of the key parameters are presented to test feasibility of the model.

Keywords: supply chain, pricing policy, defective quality, joint economic lot sizing

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Authors: Amir Azaron

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In this research, a stochastic programming approach is developed for designing supply chains with uncertain parameters. Demands and selling prices of products at markets are considered as the uncertain parameters. The proposed mathematical model will be multi-period two-stage stochastic programming, which takes into account the selection of retailer sites, suppliers, production levels, inventory levels, transportation modes to be used for shipping goods, and shipping quantities among the entities of the supply chain network. The objective function is to maximize the chain’s net present value. In order to maximize the chain’s NPV, the sum of first-stage investment costs on retailers, and the expected second-stage processing, inventory-holding and transportation costs should be kept as low as possible over multiple periods. The effects of supply uncertainty where suppliers are unreliable will also be investigated on the efficiency of the supply chain.

Keywords: supply chain management, stochastic programming, multiobjective programming, inventory control

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Authors: Ali Kurşun, Emre Kara, Erhan Çetin, Şafak Aksoy, Ahmet Kesimli

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In this study, thermal elastic stress distribution occurred on long hollow cylinders made of functionally graded material (FGM) was analytically defined under thermal, mechanical and thermo mechanical loads. In closed form solutions for elastic stresses and displacements are obtained analytically by using the infinitesimal deformation theory of elasticity. It was assumed that elasticity modulus, thermal expansion coefficient and density of cylinder materials could change in terms of an exponential function as for that Poisson’s ratio was constant. A gradient parameter n is chosen between - 1 and 1. When n equals to zero, the disc becomes isotropic. Circumferential, radial and longitudinal stresses in the FGMs cylinders are depicted in the figures. As a result, the gradient parameters have great effects on the stress systems of FGMs cylinders.

Keywords: functionally graded materials, thermoelasticity, thermomechanical load, hollow cylinder.

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Authors: Hsien Hao Teng

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This study uses numerical simulation to analyze the aerodynamic characteristics of the 53-degree Lambda wing with a sweep angle and mainly discusses the numerical simulation results and physical characteristics of the wall y+. Use the commercial software Fluent to execute Mach number 0.15; when the angle of attack attitude is between 0 degrees and 27 degrees, the physical characteristics of the overall aerodynamic force are analyzed, especially when the fluid separation and vortex structure changes are discussed under the condition of high angle of attack, it will affect The instability of pitching moment. In the numerical calculation, the use of wall y+ and turbulence model will affect the prediction of vortex generation and the difference in structure. The analysis results are compared with experimental data to discuss the trend of the aerodynamic characteristics of the Lambda wing.

Keywords: lambda wing, wall function, turbulence model, computational fluid dynamics

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Authors: Grzegorz Zinkiewicz

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The paper explores affective potential implicit in Bergman’s movies. This is done by the use of affect theory and the concept of affect in terms of paradigmatic and syntagmatic relations, from both diachronic and synchronic perspective. Since its inception in the early 2000s, affect theory has been applied to a number of academic fields. In Film Studies, it offers new avenues for discovering deeper, hidden layers of a given film. The aim is to show that the form and content of the films by Ingmar Bergman are determined by their inner affects that function independently of the viewer and, to an extent, are autonomous entities that can be analysed in separation from the auteur and actual characters. The paper discovers layers in Ingmar Bergman films and focuses on aspects that are often marginalised or studied from other viewpoints such as the connection between the content and visual side. As a result, a revaluation of Bergman films is possible that is more consistent with his original interpretations and comments included in his lectures, interviews and autobiography.

Keywords: affect theory, experimental cinema, Ingmar Bergman, viewer response

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Authors: Sukhleen Bindra Narang, Dalveer Kaur, Kunal Pubby

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Dielectric ceramic samples in the BaO-Re2O3-TiO2 ternary system were synthesized with structural formula Ba2-xRe4+2x/3Ti8O24 where Re= rare earth metal and Re= Sm and La where x varies from 0.0 to 0.6 with step size 0.1. Polycrystalline samples were prepared by the conventional solid state reaction technique. The dielectric, electrical and impedance analysis of all the samples in the frequency range 1KHz- 1MHz at room temperature (25°C) have been done to get the understanding of electrical conduction and dielectric relaxation and their correlation. Dielectric response of the samples at lower frequencies shows dielectric dispersion while at higher frequencies it shows dielectric relaxation. The ac conductivity is well fitted by the Jonscher law (σac = σdc+Aωn). The spectroscopic data in the impedance plane confirms the existence of grain contribution to the relaxation. All the properties are found out to be function of frequency as well as the amount of substitution.

Keywords: dielectric ceramics, dielectric constant, loss tangent, AC conductivity, impedance spectroscopy

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Authors: Wang Ye, Wei Wei

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Residential block construction of big cities in China began in the 1950s, and four models had far-reaching influence on modern residential block in its development process, including unit compound and residential district in 1950s to 1980s, and gated community and open community in 1990s to now. Based on analysis of the four models’ fabric, the article takes residential blocks in Hangzhou west area as an example and carries on the studies from urban structure level and block special level, mainly including urban road network, land use, community function, road organization, public space and building fabric. At last, the article puts forward semi-open sub-community strategy to improve the current fabric.

Keywords: Hangzhou west area, residential block model, residential block fabric, semi-open sub-community strategy

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Authors: Badr M. Alshammari, T. Guesmi

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This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones

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Authors: Anthony Barker, Roland Jiang

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Dupuytren’s contractures are a debilitating condition affecting the palmar fascia of the hand reducing its function. This case series looks at the minimally-invasive technique of Xiaflex injections and the outcome in a public health setting. 15 patients undertook collagenase injection (Xiaflex, C. histolyticum) injection over the period from September 2015 to May 2017 at Fairfield Hospital, NSW. Their reported outcome post injection and in follow-up was recorded as well as their satisfaction and likelihood to request the procedure in the future. Other treatment modalities include percutaneous needle aponeurotomy, limited palmar fasciotomy, and palmar fasciectomy. A literature review of cost-effectiveness was performed to compare Xiaflex suitability for waitlist reduction in a public setting given average waiting times in the public setting extend past 365 days.

Keywords: Dupuytrens Disease, xiaflex, collagenase, plastic surgery

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Authors: V. V. Singh

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We have studied the reliability measures of a system, which consists of two subsystems i.e. subsystem-1 and subsystem-2 in series configuration under different types of failure. The subsystem-1 has three identical units in parallel configuration and operating under 2-out-of-3: G policy and connected to subsystem-2 in series configuration. Each subsystem has different types of failure and repair rates. An important cause for failure of system is unsuitability of the environmental conditions, like overheating, weather conditions, heavy rainfall, storm etc. The environmental failure is taken into account in the proposed repairable system. Supplementary variable technique is used to study of system and some traditional measures such as; availability, reliability, MTTF and profit function are obtained for different values of parameters. In the proposed model, some particular cases of failure rates are explicitly studied.

Keywords: environmental failure, human failure, availability, MTTF, reliability, profit analysis, Gumbel-Hougaard family copula

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Authors: Harihara Prakash Ramanathan, Daksha Mishra, Ankita Dhaduk

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Relevance: This qualitative study will educate the clinician in putting into practice the advanced method of movement science in restoring the function. Purpose: The purpose of this study is to compare the effectiveness of Active Release Technique and myofascial release technique on range of motion, neck function and pain in patients with upper trapezius spasm. Methods/Analysis: The study was approved by the institutional Human Research and Ethics committee. This study included sixty patients of age group between 20 to 55 years with upper trapezius spasm. Patients were randomly divided into two groups receiving Active Release Technique (Group A) and Myofascial Release Technique (Group B). The patients were treated for 1 week and three outcome measures ROM, pain and functional level were measured using Goniometer, Visual analog scale(VAS), Neck disability Index Questionnaire(NDI) respectively. Paired Sample 't' test was used to compare the differences of pre and post intervention values of Cervical Range of motion, Neck disability Index, Visual analog scale of Group A and Group B. Independent't' test was used to compare the differences between two groups in terms of improvement in cervical range of motion, decrease in visual analogue scale(VAS), decrease in Neck disability index score. Results: Both the groups showed statistically significant improvements in cervical ROM, reduction in pain and in NDI scores. However, mean change in Cervical flexion, cervical extension, right side flexion, left side flexion, right side rotation, left side rotation, pain, neck disability level showed statistically significant improvement (P < 0. 05)) in the patients who received Active Release Technique as compared to Myofascial release technique. Discussion and conclusions: In present study, the average improvement immediately post intervention is significantly greater as compared to before treatment but there is even more improvement after seven sessions as compared to single session. Hence, this proves that several sessions of Manual techniques are necessary to produce clinically relevant results. Active release technique help to reduce the pain threshold by removing adhesion and promote normal tissue extensibility. The act of tensioning and compressing the affected tissue both with digital contact and through the active movement performed by the patient can be a plausible mechanism for tissue healing in this study. This study concluded that both Active Release Technique (ART) and Myofascial release technique (MFR) are equally effective in managing upper trapezius muscle spasm, but more improvement can be achieved by Active Release Technique (ART). Impact and Implications: Active Release Technique can be adopted as mainstay of treatment approach in treating trapezius spasm for faster relief and improving the functional status.

Keywords: trapezius spasm, myofascial release, active release technique, pain

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Authors: Mounir Belattar

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In this paper the Analysis of voltage waves that propagate along a lossless exponential nonuniform line is presented. For this analysis the parameters of this line are assumed to be varying function of the distance x along the line from the source end. The approach is based on the tow-port networks cascading presentation to derive the ABDC parameters of transmission using Picard-Carson Method which is a powerful method in getting a power series solution for distributed network because it is easy to calculate poles and zeros and solves differential equations such as telegrapher equations by an iterative sequence. So the impedance, admittance voltage and current along the line are expanded as a Taylor series in x/l where l is the total length of the line to obtain at the end, the main transmission line parameters such as voltage response and transmission and reflexion coefficients represented by scattering parameters in frequency domain.

Keywords: ABCD parameters, characteristic impedance exponential nonuniform transmission line, Picard-Carson's method, S parameters, Taylor's series

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: Ferydon Salehifar, Hassan Safarikia, Hossein Boromandfar

Abstract:

Karkheh plant in Iran's Khuzestan province and is located in the city Andimeshk. The plant has a production capacity of 400 MW units with water and three hours. One of the important parameters of each country's power grid stability is the stability of the power grid is affected by the voltage and frequency In plants, the amount of active power frequency control is done so that when the unit is placed in the frequency control their productivity is a function of frequency and output power varies with frequency. Produced by hydroelectric power plants with the water level behind the dam has a direct relationship And to decrease and increase the water level behind the dam in order to reduce the power output increases But these changes have a different interval is due to some mechanical problems such as turbine cavitation and vibration are limited. In this study, the range of the frequency control can be Karkheh manufacturing plants have been identified and their effectiveness has been determined.

Keywords: Karkheh power, frequency control system, active power, efficiency

Procedia PDF Downloads 620

Authors: S. Heydari, H. Sharififard, M. Nabavinia, H. Kiani, M. Parvizi

Abstract:

Rapid industrialization has led to increased disposal of heavy metals into the environment. Activated carbon adsorption has proven to be an effective process for the removal of trace metal contaminants from aqueous media. This paper was investigated chromium adsorption efficiency by commercial activated carbon. The sorption studied as a function of activated carbon particle size, dose of activated carbon and initial pH of solution. Adsorption tests for the effects of these factors were designed with Taguchi approach. According to the Taguchi parameter design methodology, L9 orthogonal array was used. Analysis of experimental results showed that the most influential factor was initial pH of solution. The optimum conditions for chromium adsorption by activated carbons were found to be as follows: Initial feed pH 6, adsorbent particle size 0.412 mm and activated carbon dose 6 g/l. Under these conditions, nearly %100 of chromium ions was adsorbed by activated carbon after 2 hours.

Keywords: chromium, adsorption, Taguchi method, activated carbon

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Authors: Bin Liu

Abstract:

Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

Procedia PDF Downloads 161

Authors: Kul Pun, F. A. Hamad, T. Ahmed, J. O. Ugwu, J. Eyers, G. Lawson, P. A. Russell

Abstract:

Determining droplet size and distribution is essential when determining the separation efficiency of a two/three-phase separator. This paper investigates the effect of liquid flow and oil pad thickness on the droplet size at the lab scale. The findings show that increasing the inlet flow rates of the oil and water results in size reduction of the droplets and increasing the thickness of the oil pad increases the size of the droplets. The data were fitted with a simple Gaussian model, and the parameters of mean, standard deviation, and amplitude were determined. Trends have been obtained for the fitted parameters as a function of the Reynolds number, which suggest a way forward to better predict the starting parameters for population models when simulating separation using CFD packages. The key parameter to predict to fix the position of the Gaussian distribution was found to be the mean droplet size.

Keywords: two-phase separator, average bubble droplet, bubble size distribution, liquid-liquid phase

Procedia PDF Downloads 200