Search results for: governance model

Authors: J. V. Gonzalez Fernandez, T. Mozume, S. Gozu, A. Lastras Martinez, L. F. Lastras Martinez, J. Ortega Gallegos, R. E. Balderas Navarro

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We report on a theoretical-experimental study of photoreflectance anisotropy (PRA) spectroscopy of coupled double quantum wells. By probing the in-plane interfacial optical anisotropies, we demonstrate that PRA spectroscopy has the capacity to detect and distinguish layers with quantum dimensions. In order to account for the experimental PRA spectra, we have used a theoretical model at k=0 based on a linear electro-optic effect through a piezoelectric shear strain.

Keywords: coupled double quantum well (CDQW), linear electro-optic (LEO) effect, photoreflectance anisotropy (PRA), piezoelectric shear strain

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Authors: Thomas Gerstner, Bastian von Harrach, Daniel Roth

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The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions. Our main tool is the one-step survival idea of Glasserman and Staum. Although this technique yields to new terms per observation, while differentiating, the algorithm is still efficient. As an application, we use the results for a two-dimensional calibration of a Coco-Bond, which we model with different types of discretely monitored barrier options.

Keywords: Monte Carlo, discretely monitored barrier options, pathwise sensitivities, Coco-Bond

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Authors: Noureddine Litim

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This work is to theoretical and numerical studying the real analysis of the seismic response of the soil with an Elasto-plastic behavior. To perform this analysis, we used different core drilling performed at the tunnel T4 in El Horace section of the highway east-west. The two-dimensional model (2d) was established by the code of finite element plaxis to estimate the displacement amplification and accelerations caused by the seismic wave in the different core drilling and compared with the factor of acceleration given by the RPA (2003) in the area studying. Estimate the displacement amplification and accelerations caused by the seismic wave.

Keywords: seismic response, deposition of soil, plaxis, elasto-plastic

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Authors: Mehmet Savsar

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Reliability and availability of power stations are extremely important in order to achieve a required level of power generation. In particular, in the hot desert climate of Kuwait, reliable power generation is extremely important because of cooling requirements at temperatures exceeding 50-centigrade degrees. In this paper, a particular power plant, named Sabiya Power Plant, which has 8 steam turbines and 13 gas turbine stations, has been studied in detail; extensive data are collected; and availability of station units are determined. Furthermore, a simulation model is developed and used to analyze the effects of different maintenance policies on availability of these stations. The results show that significant improvements can be achieved in power plant availabilities if appropriate maintenance policies are implemented.

Keywords: power plants, steam turbines, gas turbines, maintenance, availability, simulation

Procedia PDF Downloads 618

Authors: Hanik Park, Kyungsook Jeon, Suchul Shin, Youngchul Park

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The air vent head prevents the inflow of seawater into the cargo holds when it is used for the ballast tank on heavy weather. In this study, the flow characteristics and the grid size were created by the application of Computational Fluid Dynamics by taking into the consideration of comparison of test results. Then, the accuracy of the analysis was verified by comparing with experimental results. Based on this analysis, accurate turbulence model and grid size can be selected. Thus, the design characteristic of air vent head for bulk carrier contributes the reliability based on the research results.

Keywords: bulk carrier, FEM, SST, vent

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Authors: Noha Nagy, Hoda Mokhtar, Mohamed El Sherkawi

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The popularity of workflow delegation models and the increasing number of workflow provenance-aware systems motivate the need for finding more strict delegation models. Such models combine different approaches for enhanced security and respecting workflow privacy. Although modern enterprises seek conformance to workflow constraints to ensure correctness of their work, these constraints pose a threat to security, because these constraints can be good seeds for attacking privacy even in secure models. This paper introduces a comprehensive Workflow Delegation Model (WFDM) that utilizes provenance and workflow constraints to prevent malicious delegate from attacking workflow privacy as well as extending the delegation functionalities. In addition, we argue the need for exploiting workflow constraints to improve workflow security models.

Keywords: workflow delegation models, secure workflow, workflow privacy, workflow provenance

Procedia PDF Downloads 332

Authors: Pablo Reyes, Vanessa Riveros Fiallo, Cesar Acevedo, Camila Castellanos, Catalina Moncaleano, Maria F. Parra, Laura Colmenares

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Social emotions are physiological, cognitive and behavioral phenomenon that intervene in the mechanisms of adaptation of individuals and their context. These are mediated by interpersonal relationship and language. Such emotions are subdivided into moral and comparison. The present research emphasizes two comparative emotions: Envy and Schadenfreude. Envy arises when a person lack of quality, possessions or achievements and these are superior in someone else. The Schadenfreude (SC) expresses the pleasure that someone experienced by the misfortune of the other. The relationship between both emotions has been questioned before. Hence there are reports showing that envy increases and modulates SC response. Other documents suggest that envy causes SC response. However, the methodological approach of the topic has been made through self-reports, as well as the hypothetical scenarios. Given this problematic, the neuroscience social framework provides an alternative and demonstrates that social emotions have neurophysiological correlates that can be measured. This is relevant when studying social emotions that are reprehensible like envy or SC are. When tested, the individuals tend to report low ratings due to social desirability. In this study, it was drawn up a proposal in research's protocol and the progress on its own piloting. The aim is to evaluate the effect of feeling envy and Schadenfreude has on the decision-making process, as well as the cooperative behavior in an economic game. To such a degree, it was proposed an experimental model that will provoke to feel envious by performing games against an unknown opponent. The game consists of asking general knowledge questions. The difficulty level in questions and the strangers' facial response have been manipulated in order to generate an ecological comparison framework and be able to arise both envy and SC emotions. During the game, an electromyography registry will be made for two facial muscles that have been associated with the expressiveness of envy and SC emotions. One of the innovations of the current proposal is the measurement of the effect that emotions have on a specific behavior. To that extent, it was evaluated the effect of each condition on the dictators' economic game. The main intention is to evaluate if a social emotion can modulate actions that have been associated with social norms, in the literacy. The result of the evaluation of a pilot model (without electromyography record and self-report) have shown an association between envy and SC, in a way that as the individuals report a greater sense of envy, the greater the chance to experience SC. The results of the economic game show a slight tendency towards profit maximization decisions. It is expected that at the time of using real cash this behavior will be strengthened and also to correlate with the responses of electromyography.

Keywords: envy, schadenfreude, electromyography, economic games

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Authors: Vojtěch Svěrák

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Climate change ethics have recently shifted away from individualistic paradigms towards concepts of shared or collective responsibility. Despite this evolving trend, a noticeable gap remains: a lack of research exclusively addressing the moral responsibility of specific unorganized social groups. The primary objective of the article is to fill this gap. The article employs the structuralist methodological approach proposed by some feminist philosophers, utilizing structural analysis to explain the existence of social groups. The argument is made for the integration of this framework with the so-called forward-looking Social Connection Model (SCM) of responsibility, which ascribes responsibilities to individuals based on their participation in social structures. The article offers an extension of this model to justify the responsibility of unorganized social groups. The major finding of the study is that although members of unorganized groups are loosely connected, collectively they instantiate specific external social structures, share social positioning, and the notion of responsibility could be based on that. Specifically, if the structure produces harm or perpetuates injustices, and the group both benefits from and possesses the capacity to significantly influence the structure, a greater degree of responsibility should be attributed to the group as a whole. This thesis is applied and justified within the context of climate change, based on the asymmetrical positioning of different social groups. Climate change creates a triple inequality: in contribution, vulnerability, and mitigation. The study posits that different degrees of group responsibility could be drawn from these inequalities. Two social groups serve as a case study for the article: first, the Pakistan lower class, consisting of people living below the national poverty line, with a low greenhouse gas emissions rate, severe climate change-related vulnerability due to the lack of adaptation measures, and with very limited options to participate in the mitigation of climate change. Second, the so-called polluter elite, defined by members' investments in polluting companies and high-carbon lifestyles, thus with an interest in the continuation of structures leading to climate change. The first identified group cannot be held responsible for climate change, but their group interest lies in structural change and should be collectively maintained. On the other hand, the responsibility of the second identified group is significant and can be fulfilled by a justified demand for some political changes. The proposed approach of group responsibility is suggested to help navigate climate justice discourse and environmental policies, thus helping with the sustainability transition.

Keywords: collective responsibility, climate justice, climate change ethics, group responsibility, social ontology, structural analysis

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Authors: Ercan Yilmaz, Ali Murat Sünbül

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The aim of the study is to investigate teachers’ self-efficacy with regards to their emotional intelligence. The relational model was used in the study. The participant of the study included 194 teachers from secondary schools in Konya, Turkey. In order to assess teachers’ emotional intelligence, “Trait Emotional Intelligence Questionnaire-short Form was implemented. For teachers’ self-efficacy, “Teachers’ Sense of Self-Efficacy Scale” was used. As a result of the study, a significant relationship is available between teachers’ sense of self-efficacy and their emotional intelligence. Teachers’ emotional intelligence enucleates approximate eighteen percent of the variable in dimension named teachers’ self-efficacy for the students’ involvement. About nineteen percent of the variable in dimension “self-efficacy for teaching strategies is represented through emotional intelligence. Teachers’ emotional intelligence demonstrates about seventeen percent of variable aimed at classroom management.

Keywords: teachers, self-efficacy, emotional intelligence, education

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Authors: Pradyumna Mohanty

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The paper aims to explore whether accounting information of Indian companies in the Steel sector are value relevant or not. Ohlson’s model which usually takes into consideration book value per share (BV) and earnings per share (EARN) has been used and the same has been expanded to include two more variables such as cash flow from operations (CFO) and return on equity (ROE). The data were collected from CMIE-Prowess data base in respect of BSE-listed steel companies and the time frame spans from 2010 to 2014. OLS regression has been used to test the value relevance of these accounting numbers. Results indicate that both CFO and BV are having significant influence on the stock price in two out of five years of study. But, BV is emerging as the most significant and highly value relevant of all the four variables during the entire period of study.

Keywords: value relevance, accounting information, book value per share, earnings per share

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Authors: Csaba Tóth, Éva Lakatos, László Pethő, Seoyoung Cho

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The temperature effect on asphalt pavement structure is a crucial factor at the design stage. In this paper, by applying the German guidelines for temperature along the asphalt depth is estimated. The aim is to consider temperature profiles in different seasons in numerical modelling. The model is built with an elastic and isotropic solid element with 19 subdivisions of asphalt layers to reflect the temperature variation. Comparison with the simple three-layer pavement system (asphalt layers, base, and subgrade layers) will be followed to see the difference in result without temperature variation along with the depth. Finally, the fatigue life calculation was checked to prove the validity of the methodology of considering the temperature in the numerical modelling.

Keywords: temperature profile, flexible pavement modeling, finite element method, temperature modeling

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Authors: Bakur Gulua

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In this work, we consider some boundary value problems for the plate. The plate is the elastic material with voids. The state of plate equilibrium is described by the system of differential equations that is derived from three-dimensional equations of equilibrium of an elastic material with voids (Cowin-Nunziato model) by Vekua's reduction method. Its general solution is represented by means of analytic functions of a complex variable and solutions of Helmholtz equations. The problem is solved analytically by the method of the theory of functions of a complex variable.

Keywords: the elastic material with voids, boundary value problems, Vekua's reduction method, a complex variable

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Authors: E. Selçuk, Z. Karaçor, P. Yardımcı

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Trade liberalization and its effects on the economies of developing countries have been investigated by many different studies, and some of them have focused on its impact on the current account balance. Turkey, as being one of the countries, which has liberalized its foreign trade in the 1980s, also needs to be studied in terms of the impact of liberalization on current account deficits. Therefore, the aim of this study is to find out whether trade liberalization has affected Turkey’s trade and current account balances. In order to determine this, yearly data of Turkey from 1980 to 2013 is used. As liberalization dummy, the year 1989, which was set for Turkey, is selected. Structural break test and model estimation results show that trade liberalization has a negative impact on trade balance but do not have a significant impact on the current account balance.

Keywords: budget deficit, liberalization, Turkish economy, current account

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Authors: Beverley Gallimore

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The Individuals with Disabilities Education Act of 2004 (IDEA) has helped to improve outcomes for students with special education needs. Through IDEA, students with Special Education Needs (SEN) have opportunities for more equitable education within the General Education classroom. However, students with disabilities lack access to instructions that can help them to maximize their fullest learning potential. Recently, educational stakeholders have emphasized Integrated Co-teaching as a tool to increase engagement and learning outcomes for students with disabilities in general education classrooms. As a result of this new approach, general and special education teachers are working collaboratively to teach students with disabilities. However, co-teaching models are not properly designed and structured to effectively benefit students with disabilities. Teachers must be oriented correctly in the co-teaching models if it is to be beneficial for students.

Keywords: CO-teaching, differentiation, equitable, collaborative

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Authors: Haoming Ma, Guo Yu, Peiru Zhou

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Background: Previous studies show that dysglycemia, mostly hyperglycemia, hypoglycemia and glycemic variability(GV), are associated with excess mortality in critically ill patients, especially those without diabetes. Glycemic variability is an increasingly important measure of glucose control in the intensive care unit (ICU) due to this association. However, there is limited data pertaining to the relationship between different clinical factors and glycemic variability and clinical outcomes categorized by their DM status. This retrospective study of 958 intensive care unit(ICU) patients was conducted to investigate the relationship between GV and outcome in critically ill patients and further to determine the significant factors that contribute to the glycemic variability. Aim: We hypothesize that the factors contributing to mortality and the glycemic variability are different from critically ill patients with or without diabetes. And the primary aim of this study was to determine which dysglycemia (hyperglycemia\hypoglycemia\glycemic variability) is independently associated with an increase in mortality among critically ill patients in different groups (DM/Non-DM). Secondary objectives were to further investigate any factors affecting the glycemic variability in two groups. Method: A total of 958 diabetic and non-diabetic patients with severe diseases in the ICU were selected for this retrospective analysis. The glycemic variability was defined as the coefficient of variation (CV) of blood glucose. The main outcome was death during hospitalization. The secondary outcome was GV. The logistic regression model was used to identify factors associated with mortality. The relationships between GV and other variables were investigated using linear regression analysis. Results: Information on age, APACHE II score, GV, gender, in-ICU treatment and nutrition was available for 958 subjects. Predictors remaining in the final logistic regression model for mortality were significantly different in DM/Non-DM groups. Glycemic variability was associated with an increase in mortality in both DM(odds ratio 1.05; 95%CI:1.03-1.08,p＜0.001) or Non-DM group(odds ratio 1.07; 95%CI:1.03-1.11,p=0.002). For critically ill patients without diabetes, factors associated with glycemic variability included APACHE II score(regression coefficient, 95%CI:0.29,0.22-0.36,p＜0.001), Mean BG(0.73,0.46-1.01,p＜0.001), total parenteral nutrition(2.87,1.57-4.17,p＜0.001), serum albumin(-0.18,-0.271 to -0.082,p＜0.001), insulin treatment(2.18,0.81-3.55,p=0.002) and duration of ventilation(0.006,0.002-1.010,p=0.003).However, for diabetes patients, APACHE II score(0.203,0.096-0.310,p＜0.001), mean BG(0.503,0.138-0.869,p=0.007) and duration of diabetes(0.167,0.033-0.301,p=0.015) remained as independent risk factors of GV. Conclusion: We found that the relation between dysglycemia and mortality is different in the diabetes and non-diabetes groups. And we confirm that GV was associated with excess mortality in DM or Non-DM patients. Furthermore, APACHE II score, Mean BG, total parenteral nutrition, serum albumin, insulin treatment and duration of ventilation were significantly associated with an increase in GV in Non-DM patients. While APACHE II score, mean BG and duration of diabetes (years) remained as independent risk factors of increased GV in DM patients. These findings provide important context for further prospective trials investigating the effect of different clinical factors in critically ill patients with or without diabetes.

Keywords: diabetes, glycemic variability, predictors, severe disease

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Authors: N. Targui, H. Kahalerras

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The present work is a numerical simulation of nanofluids flow in a double pipe heat exchanger provided with porous baffles. The hot nanofluid flows in the inner cylinder, whereas the cold nanofluid circulates in the annular gap. The Darcy-Brinkman-Forchheimer model is adopted to describe the flow in the porous regions, and the governing equations with the appropriate boundary conditions are solved by the finite volume method. The results reveal that the addition of metallic nanoparticles enhances the rate of heat transfer in comparison to conventional fluids but this augmentation is accompanied by an increase in pressure drop. The highest heat exchanger performances are obtained when nanoparticles are added only to the cold fluid.

Keywords: double pipe heat exchanger, nanofluids, nanoparticles, porous baffles

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 83

Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: H. R. Kamali, A. Sadegheih, M. A. Vahdat-Zad, H. Khademi-Zare

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In this paper, a single product, multi-echelon, multi-period closed loop supply chain is surveyed, including a variety of costs, time conditions, and capacities, to plan and determine the values and time of the components procurement, production, distribution, recycling and disposal specially for high-tech products that undergo a decreasing production cost and sale price over time. For this purpose, the mathematic model of the problem that is a kind of mixed integer linear programming is presented, and it is finally proved that the problem belongs to the category of NP-hard problems.

Keywords: closed loop supply chain, continuous price decrease, NP-hard, planning

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Authors: Ljubica Milanović Glavan

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Because of the increasing business pressures, companies must be adaptable and flexible in order to withstand them. Inadequate business processes and low level of business process orientation, that in its core accentuates business processes as opposed to business functions and focuses on process performance and customer satisfaction, hider the ability to adapt to changing environment. It has been shown in previous studies that the companies which have reached higher business process maturity level consistently outperform those that have not reached them. The aim of this paper is to provide a basic understanding of business process orientation concept and business process maturity model. Besides that the paper presents the state of business process orientation in Croatia that has been captured with a study conducted in 2013. Based on the results some practical implications and guidelines for managers are given.

Keywords: business process orientation, business process maturity, Croatia, maturity score

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Authors: Kamalpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network.

Keywords: ERA, fuzzy logic, network model, WSN

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

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The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: auto tuning, balanced robot, closed loop identification, subspace identification

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Authors: Riddhi Jangid, Gajendra Pratap Singh

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Petri nets, a mathematical tool, is used for modeling in different areas of computer sciences, biological networks, chemical systems and many other disciplines. A Petri net model of a given system is created by the graphical representation that describes the properties and behavior of the system. While looking for the behavior of any system, 1-safe Petri nets are of particular interest to many in the application part. Boolean Petri nets correspond to those class in 1- safe Petri nets that generate all the binary n-vectors in their reachability analysis. We study the class by changing different parameters like the token counts in the places and how the structure of the tree changes in the reachability analysis. We discuss here an extended class of Boolean Petri nets that generates n-ary trees in their reachability-based analysis.

Keywords: marking vector, n-vector, petri nets, reachability

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Authors: Mehmet Savsar

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This paper presents a practical case application of simulation modeling and analysis in a specific industrial setting. Various maintenance related parameters of the equipment in the system under consideration are determined and a simulation model is developed to study system behavior. System performance is determined based on established parameters and operational policies, which included system operation with and without preventive maintenance implementation. The results show that preventive maintenance practice has significant effects on improving system productivity. The simulation procedures outlined in this paper can be used by operation managers to perform production line analysis under different maintenance policies in various industrial settings.

Keywords: simulation, production line, machine failures, maintenance, industrial bakery

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Authors: Rajaa Filali, Mohamed Bouhdadi

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This paper presents an incremental development of the Dynamic Host Configuration Protocol (DHCP) in Event-B. DHCP is widely used communication protocol, which provides a standard mechanism to obtain configuration parameters. The specification is performed in a stepwise manner and verified through a series of refinements. The Event-B formal method uses the Rodin platform to modeling and verifying some properties of the protocol such as safety, liveness and deadlock freedom. To model and verify the protocol, we use the formal technique Event-B which provides an accessible and rigorous development method. This interaction between modelling and proving reduces the complexity and helps to eliminate misunderstandings, inconsistencies, and specification gaps.

Keywords: DHCP protocol, Event-B, refinement, proof obligation, Rodin

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Authors: K. E. Daryani, H. Mohamad

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Uncertainties in the geo-structure analysis and design have a significant impact on the safety of slopes. Traditionally, uncertainties in the geotechnical design are addressed by incorporating a conservative factor of safety in the analytical model. In this paper, a risk-based approach is adopted to assess the influence of the geotechnical variable uncertainties on the stability of infinite slopes in cohesionless soils using the “partial factor of safety on shear strength” approach as stated in Eurocode 7. Analyses conducted using Monte Carlo simulation show that the same partial factor can have very different levels of risk depending on the degree of uncertainty of the mean values of the soil friction angle and void ratio.

Keywords: Safety, Probability of Failure, Reliability, Infinite Slopes, Sand.

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Authors: Mostefa Bendouba, Djebli Abdelkader, Abdelkrim Aid, Mohamed Benguediab

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The damage evolution mechanism is one of the important focuses of fatigue behaviour investigation of composite materials and also is the foundation to predict fatigue life of composite structures for engineering application. This paper is dedicated to a damage investigation under two block loading cycle fatigue conditions submitted to composite material. The loading sequence effect and the influence of the cycle ratio of the first stage on the cumulative fatigue life were studied herein. Two loading sequences, i.e., high-to-low and low-to-high cases are considered in this paper. The proposed damage indicator is connected cycle by cycle to the S-N curve and the experimental results are in agreement with model expectations. Some experimental researches are used to validate this proposition.

Keywords: fatigue, damage acumulation, composite, evolution

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Authors: Marcelo R. G. Duarte, Marcilio Alves

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Pedestrians are the fourth group among road traffic users that most suffer accidents. Their death rate is even higher than the motorcyclists group. This gives motivation for the development of an urban vehicle capable of complying with the United Nations Economic Commission for Europe pedestrian regulations. The conceptual vehicle is capable of transporting two passengers and small parcels for 100 km at a maximum speed of 90 km/h. This paper presents the design of this vehicle using the finite element method specially in connection with frontal crash test and car to pedestrian collision. The simulation is based in a human body FE.

Keywords: electric urban vehicle, finite element method, global human body model, pedestrian safety, road safety

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Authors: Claus N. Holm, Oliver F. Grooss, Robert A. Alphinas

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This research strives to predict the remaining product life cycle of a song on radio after it has been played for one or two months. The best results were achieved using a k-d tree to calculate the most similar songs to the test songs and use a Random Forest model to forecast radio plays. An 82.78% and 83.44% accuracy is achieved for the two time periods, respectively. This explorative research leads to over 4500 test metrics to find the best combination of models and pre-processing techniques. Other algorithms tested are KNN, MLP and CNN. The features only consist of daily radio plays and use no musical features.

Keywords: hit song science, product life cycle, machine learning, radio

Procedia PDF Downloads 155