Search results for: Adaptive beam forming

Authors: Roland S. Nattermann, Reiner Anderl

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Existing proceeding-models for the development of mechatronic systems provide a largely parallel action in the detailed development. This parallel approach is to take place also largely independent of one another in the various disciplines involved. An approach for a new proceeding-model provides a further development of existing models to use for the development of Adaptronic Systems. This approach is based on an intermediate integration and an abstract modeling of the adaptronic system. Based on this system-model a simulation of the global system behavior, due to external and internal factors or Forces is developed. For the intermediate integration a special data management system is used. According to the presented approach this data management system has a number of functions that are not part of the "normal" PDM functionality. Therefore a concept for a new data management system for the development of Adaptive system is presented in this paper. This concept divides the functions into six layers. In the first layer a system model is created, which divides the adaptronic system based on its components and the various technical disciplines. Moreover, the parameters and properties of the system are modeled and linked together with the requirements and the system model. The modeled parameters and properties result in a network which is analyzed in the second layer. From this analysis necessary adjustments to individual components for specific manipulation of the system behavior can be determined. The third layer contains an automatic abstract simulation of the system behavior. This simulation is a precursor for network analysis and serves as a filter. By the network analysis and simulation changes to system components are examined and necessary adjustments to other components are calculated. The other layers of the concept treat the automatic calculation of system reliability, the "normal" PDM-functionality and the integration of discipline-specific data into the system model. A prototypical implementation of an appropriate data management with the addition of an automatic system development is being implemented using the data management system ENOVIA SmarTeam V5 and the simulation system MATLAB.

Keywords: Adaptronic, Data-Management, LOEWE-CentreAdRIA

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Authors: Elena B. Cherepetskaya, Alexander A. Karabutov, Natalia B. Podymova, Ivan Sas

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Nonlinear evolution of broadband ultrasonic pulses passed through the rock specimens is studied using the apparatus “GEOSCAN-02M”. Ultrasonic pulses are excited by the pulses of Qswitched Nd:YAG laser with the time duration of 10 ns and with the energy of 260 mJ. This energy can be reduced to 20 mJ by some light filters. The laser beam radius did not exceed 5 mm. As a result of the absorption of the laser pulse in the special material – the optoacoustic generator–the pulses of longitudinal ultrasonic waves are excited with the time duration of 100 ns and with the maximum pressure amplitude of 10 MPa. The immersion technique is used to measure the parameters of these ultrasonic pulses passed through a specimen, the immersion liquid is distilled water. The reference pulse passed through the cell with water has the compression and the rarefaction phases. The amplitude of the rarefaction phase is five times lower than that of the compression phase. The spectral range of the reference pulse reaches 10 MHz. The cubic-shaped specimens of the Karelian gabbro are studied with the rib length 3 cm. The ultimate strength of the specimens by the uniaxial compression is (300±10) MPa. As the reference pulse passes through the area of the specimen without cracks the compression phase decreases and the rarefaction one increases due to diffraction and scattering of ultrasound, so the ratio of these phases becomes 2.3:1. After preloading some horizontal cracks appear in the specimens. Their location is found by one-sided scanning of the specimen using the backward mode detection of the ultrasonic pulses reflected from the structure defects. Using the computer processing of these signals the images are obtained of the cross-sections of the specimens with cracks. By the increase of the reference pulse amplitude from 0.1 MPa to 5 MPa the nonlinear transformation of the ultrasonic pulse passed through the specimen with horizontal cracks results in the decrease by 2.5 times of the amplitude of the rarefaction phase and in the increase of its duration by 2.1 times. By the increase of the reference pulse amplitude from 5 MPa to 10 MPa the time splitting of the phases is observed for the bipolar pulse passed through the specimen. The compression and rarefaction phases propagate with different velocities. These features of the powerful broadband ultrasonic pulses passed through the rock specimens can be described by the hysteresis model of Preisach- Mayergoyz and can be used for the location of cracks in the optically opaque materials.

Keywords: Cracks, geological materials, nonlinear evolution of ultrasonic pulses, rock.

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Authors: Sylvain Chardon, Timotéo Payre, Hugo Grardel, Yann Quentel, Mathieu Thomachot, Gérald Aigouy, Frank Claeyssen

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With the increasing digitalization of society, access to data has become vital and strategic for individuals and nations. In this context, the number of satellite constellation projects is growing drastically worldwide and is a next-generation challenge of the New Space industry. So far, existing satellite constellations have been using radio frequencies (RF) for satellite-to-ground communications, inter-satellite communications, and feeder link communication. However, RF has several limitations, such as limited bandwidth and low protection level. To address these limitations, space optical communication will be the new trend, addressing both very high-speed and secured encrypted communication. Fast Steering Mirrors (FSM) are key components used in optical communication as well as space imagery and for a large field of functions such as Point Ahead Mechanisms (PAM), Raster Scanning, Beam Steering Mirrors (BSM), Fine Pointing Mechanisms (FPM) and Line of Sight stabilization (LOS). The main challenges of space FSM development for optical communication are to propose both a technology and a supply chain relevant for high quantities New Space approach, which requires secured connectivity for high-speed internet, Earth planet observation and monitoring, and mobility applications. CTEC proposes a mini-FSM technology offering a stroke of +/-6 mrad and a resonant frequency of 1700 Hz, with a mass of 50 g. This FSM mechanism is a good candidate for giant constellations and all applications on board NanoSats and CubeSats, featuring a very high level of miniaturization and optimized for New Space high quantities cost efficiency. The use of piezo actuators offers a high resonance frequency for optimal control, with almost zero power consumption in step and stay pointing, and with very high-reliability figures > 0,995 demonstrated over years of recurrent manufacturing for Optronics applications at CTEC.

Keywords: Fast steering mirror, feeder link, line of sight stabilization, optical communication, pointing ahead mechanism, raster scan.

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Authors: Lee Bih Ni, Zulfhikar Rabe, Nurul Asyikin Hassan

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The Ministry of Education Malaysia dynamically and drastically made the subject of History mandatory to be in force in 2013. This is in recognition of the nation's heritage and treasures in maintaining true facts and information for future generations of the State. History reveals the civilization of a nation and the fact of national cultural heritage. Civilization needs to be preserved as a legacy of sovereign heritage. Today's generation is the catalyst for future heirs who will support the principle and direction of the country. In line with the National Education Philosophy that aims to shape the potential development of individuals holistically and uniquely in order to produce a balanced and harmonious student in terms of intellectual, spiritual, emotional and physical. Hence, understanding the importance of studying the history subject as a pillar of identity and the history of nationhood is to be a priority in the pursuit of knowledge and empowering the spirit of statehood that is nurtured through continuous learning at school. Judging from the aspect of teacher leadership role in integrating history in a combined way based on Teacher Education Philosophy. It empowers the teaching profession towards the teacher to support noble character. It also supports progressive and scientific views. Teachers are willing to uphold the State's aspirations and celebrate the country's cultural heritage. They guarantee individual development and maintain a united, democratic, progressive and disciplined society. Teacher's role as a change and leadership agent in education begins in the classroom through formal or informal educational processes. This situation is expanded in schools, communities and countries. The focus of this paper is on the role of teacher leadership influencing the effectiveness of teaching and learning history in the classroom environment. Leadership guides to teachers' perceptions on the role of teacher leadership, teaching leadership, and the teacher leadership role and effective teacher leadership role. Discussions give emphasis on aspects of factors affecting the classroom environment, forming the classroom agenda, effective classroom implementation methods, suitable climate for historical learning and teacher challenges in implicating the effectiveness of teaching and learning processes.

Keywords: Teacher leadership, leadership lessons, effective classroom, effective teacher.

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Authors: Lei Zhao, Yi Song, Tim Dunne, Jiaxiang (Jason) Ren, Wenhan Yue, Lei Yang, Li Wen, Yu Liu

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Fasting dissolving magnesium (DM) alloy technology has contributed significantly to the “Shale Revolution” in oil and gas industry. This application requires DM downhole tools dissolving initially at a slow rate, rapidly accelerating to a high rate after certain period of operation time (typically 8 h to 2 days), a contradicting requirement that can hardly be addressed by traditional Mg alloying or processing itself. Premature disintegration has been broadly reported in downhole DM tool from field trials. To address this issue, “temporary” thin polymers of various formulations are currently coated onto DM surface to delay its initial dissolving. Due to conveying parts, harsh downhole condition, and high dissolving rate of the base material, the current delay coatings relying on pure polymers are found to perform well only at low temperature (typical < 100 ℃) and parts without sharp edges or corners, as severe geometries prevent high quality thin film coatings from forming effectively. In this study, a coating technology combining Plasma Electrolytic Oxide (PEO) coatings with advanced thin film deposition has been developed, which can delay DM complex parts (with sharp corners) in corrosive fluid at 150 ℃ for over 2 days. Synergistic effects between porous hard PEO coating and chemical inert elastic-polymer sealing leads to its delaying dissolution improvement, and strong chemical/physical bonding between these two layers has been found to play essential role. Microstructure of this advanced coating and compatibility between PEO and various polymer selections has been thoroughly investigated and a model is also proposed to explain its delaying performance. This study could not only benefit oil and gas industry to unplug their High Temperature High Pressure (HTHP) unconventional resources inaccessible before, but also potentially provides a technical route for other industries (e.g., bio-medical, automobile, aerospace) where primer anti-corrosive protection on light Mg alloy is highly demanded.

Keywords: Dissolvable magnesium, coating, plasma electrolytic oxide, sealer.

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Authors: Qing Liu, Jean-Fabien Capsal, Claude Richard

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In this current contribution, authors are dedicated to investigate influence of the crystal lamellae orientation on electromechanical behaviors of relaxor ferroelectric Poly (vinylidene fluoride –trifluoroethylene -chlorotrifluoroethylene) (P(VDF-TrFE-CTFE)) films by control of polymer microstructure, aiming to picture the full map of structure-property relationship. In order to define their crystal orientation films, terpolymer films were fabricated by solution-casting, stretching and hot-pressing process. Differential scanning calorimetry, impedance analyzer, and tensile strength techniques were employed to characterize crystallographic parameters, dielectric permittivity, and elastic Young’s modulus respectively. In addition, large electrical induced out-of-plane electrostrictive strain was obtained by cantilever beam mode. Consequently, as-casted pristine films exhibited surprisingly high electrostrictive strain 0.1774% due to considerably small value of elastic Young’s modulus although relatively low dielectric permittivity. Such reasons contributed to large mechanical elastic energy density. Instead, due to 2 folds increase of elastic Young’s modulus and less than 50% augmentation of dielectric constant, fullycrystallized film showed weak electrostrictive behavior and mechanical energy density as well. And subjected to mechanical stretching process, Film C exhibited stronger dielectric constant and out-performed electrostrictive strain over Film B because edge-on crystal lamellae orientation induced by uniaxially mechanical stretch. Hot-press films were compared in term of cooling rate. Rather large electrostrictive strain of 0.2788% for hot-pressed Film D in quenching process was observed although its dielectric permittivity equivalent to that of pristine as-casted Film A, showing highest mechanical elastic energy density value of 359.5 J/m3. In hot-press cooling process, dielectric permittivity of Film E saw values at 48.8 concomitant with ca.100% increase of Young’s modulus. Films with intermediate mechanical energy density were obtained.

Keywords: Crystal orientation, electrostrictive strain, mechanical energy density, permittivity, relaxor ferroelectric.

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: Lithium-Ion batteries, genetic algorithm optimization, battery aging test, and parameter identification.

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Authors: Reiko Yamamoto

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This paper reports on a joint research project in which a researcher in applied linguistics and elementary school teachers in Japan explored new ways to realize emotional synchrony in a classroom in childhood education. The primary purpose of this project was to develop a cross-curriculum of the first language (L1) and second language (L2) based on the concept of plurilingualism. This concept is common in Europe, and can-do statements are used in forming the standard of linguistic proficiency in any language; these are attributed to the action-oriented approach in the Common European Framework of Reference for Languages (CEFR). CEFR has a basic tenet of language education: improving communicative competence. Can-do statements are classified into five categories based on the tenet: reading, writing, listening, speaking/ interaction, and speaking/ speech. The first approach of this research was to specify the linguistic proficiency of the children, who are still developing their L1. Elementary school teachers brainstormed and specified the linguistic proficiency of the children as the competency needed to synchronize with others – teachers or peers – physically and mentally. The teachers formed original can-do statements in language proficiency on the basis of the idea that emotional synchrony leads to understanding others in communication. The research objectives are to determine the effect of language education based on the newly developed curriculum and can-do statements. The participants of the experiment were 72 third-graders in Uji Elementary School, Japan. For the experiment, 17 items were developed from the can-do statements formed by the teachers and divided into the same five categories as those of CEFR. A can-do checklist consisting of the items was created. The experiment consisted of three steps: first, the students evaluated themselves using the can-do checklist at the beginning of the school year. Second, one year of instruction was given to the students in Japanese and English classes (six periods a week). Third, the students evaluated themselves using the same can-do checklist at the end of the school year. The results of statistical analysis showed an enhancement of linguistic proficiency of the students. The average results of the post-check exceeded that of the pre-check in 12 out of the 17 items. Moreover, significant differences were shown in four items, three of which belonged to the same category: speaking/ interaction. It is concluded that children can get to understand others’ minds through physical and emotional synchrony. In particular, emotional synchrony is what teachers should aim at in childhood education.

Keywords: Elementary school education, emotional synchrony, language proficiency, sympathy with others.

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent’s attributes. Also, the influence of social networks in the developing of agents interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: Artificial stock markets, agent based simulation, bounded rationality, behavioral finance, artificial neural network, interaction, scale-free networks.

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Authors: Fiona Wahr, Sitalakshmi Venkatraman

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Industry employers require new graduates to bring with them a range of knowledge, skills and abilities which mean these new employees can immediately make valuable work contributions. These will be a combination of discipline and professional knowledge, skills and abilities which give graduates the technical capabilities to solve practical problems whilst interacting with a range of stakeholders. Underpinning the development of these disciplines and professional knowledge, skills and abilities, are “enabling” knowledge, skills and abilities which assist students to engage in learning. These are academic and learning skills which are essential to common starting points for both the learning process of students entering the course as well as forming the foundation for the fully developed graduate knowledge, skills and abilities. This paper reports on a project created to introduce and strengthen these enabling skills into the first semester of a Bachelor of Information Technology degree in an Australian polytechnic. The project uses an action research approach in the context of ongoing continuous improvement for the course to enhance the overall learning experience, learning sequencing, graduate outcomes, and most importantly, in the first semester, student engagement and retention. The focus of this is implementing the new curriculum in first semester subjects of the course with the aim of developing the “enabling” learning skills, such as literacy, research and numeracy based knowledge, skills and abilities (KSAs). The approach used for the introduction and embedding of these KSAs, (as both enablers of learning and to underpin graduate attribute development), is presented. Building on previous publications which reported different aspects of this longitudinal study, this paper recaps on the rationale for the curriculum redevelopment and then presents the quantitative findings of entering students’ reading literacy and numeracy knowledge and skills degree as well as their perceived research ability. The paper presents the methodology and findings for this stage of the research. Overall, the cohort exhibits mixed KSA levels in these areas, with a relatively low aggregated score. In addition, the paper describes the considerations for adjusting the design and delivery of the new subjects with a targeted learning experience, in response to the feedback gained through continuous monitoring. Such a strategy is aimed at accommodating the changing learning needs of the students and serves to support them towards achieving the enabling learning goals starting from day one of their higher education studies.

Keywords: Enabling skills, student retention, embedded learning support, continuous improvement.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: Deep learning, long-short-term memory, energy, renewable energy load forecasting.

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Authors: R. Kenova, K. Anguelov, R. Nikolova

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The human factor plays a major role in boosting the competitive capacity of logistic enterprises. This is of particular importance when it comes to logistic companies. On the one hand they should be strictly compliant with legislation; on the other hand, they should be competitive in terms of pricing and of delivery timelines. Moreover, their policies should allow them to be as flexible as possible. All these circumstances are reason for very serious challenges for the qualification, motivation and experience of the human resources, working in logistic companies or in logistic departments of trade and industrial enterprises. The geographic place of Bulgaria puts it in position of a country with some specific competitive advantages in the goods transport from Europe to Asia and back. Along with it, there is a number of logistic companies, that operate in this sphere in Bulgaria. In the current paper, the authors aim to establish the condition of the administrative capacity and human resources in the logistic companies and logistic departments of trade and industrial companies in Bulgaria in order to propose some guidelines for improving of their effectiveness. Due to independent empirical research, conducted in Bulgarian logistic, trade and industrial enterprises, the authors investigate both the impact degree and the interdependence of various factors that characterize the administrative capacity. The study is conducted with a prepared questionnaire, in format of direct interview with the respondents. The volume of the poll is 50 respondents, representatives of: general managers of industrial or trade enterprises; logistic managers of industrial or trade enterprises; general managers of forwarding companies – either with own or with hired transport; experts from Bulgarian association of logistics; logistic lobbyist and scientists of the relevant area. The data are gathered for 3 months, then arranged by a specialized software program and analyzed by preset criteria. Based on the results of this methodological toolbox, it can be claimed that there is a correlation between the individual criteria. Also, a commitment between the administrative capacity and other factors that determine the competitiveness of the studied companies is established. In this paper, the authors present results of the empirical research that concerns the number and the workload in the logistic departments of the enterprises. Also, what is commented is the experience, related to logistic processes management and human resources competence. Moreover, the overload level of the logistic specialists is analyzed as one of the main threats for making mistakes and losing clients. The paper stands behind the thesis that there is indispensability of forming an effective and efficient administrative capacity, based on the number, qualification, experience and motivation of the staff in the logistic companies. The paper ends with recommendations about the qualification and experience of the specialists in logistic departments; providing effective and efficient administrative capacity in the logistic departments; interdependence of the human factor and the other factors that influence the enterprise competitiveness.

Keywords: Administrative capacity, human resources, logistic competitiveness, staff qualification.

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Authors: Mikhail V. Khachaturyan

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The article analyzes problems of improving the management systems of the ownership risks in the conditions of the transformation of the Russian economy. Among the main sources of threats business owners should highlight is the inefficiency of the implementation of business models and interaction with hired managers. In this context, it is particularly important to analyze the relationship of business models and ownership risks. The analysis of this problem appears to be relevant for a number of reasons: Firstly, the increased risk appetite of the owner directly affects the business model and the composition of his holdings; secondly, owners with significant stakes in the company are factors in the formation of particular types of risks for owners, for which relations have a significant influence on a firm's competitiveness and ultimately determines its survival; and thirdly, inefficient system of management ownership of risk is one of the main causes of mass bankruptcies, which significantly affects the stable operation of the economy as a whole. The separation of the processes of possession, disposal and use in modern organizations is the cause of not only problems in the process of interaction between the owner and managers in managing the organization as a whole, but also the asymmetric information about the kinds and forms of the main risks. Managers tend to avoid risky projects, inhibit the diversification of the organization's assets, while owners can insist on the development of such projects, with the aim not only of creating new values for themselves and consumers, but also increasing the value of the company as a result of increasing capital. In terms of separating ownership and management, evaluation of projects by the ratio of risk-yield requires preservation of the influence of the owner on the process of development and making management decisions. It is obvious that without a clearly structured system of participation of the owner in managing the risks of their business, further development is hopeless. In modern conditions of forming a risk management system, owners are compelled to compromise between the desire to increase the organization's ability to produce new value, and, consequently, increase its cost due to the implementation of risky projects and the need to tolerate the cost of lost opportunities of risk diversification. Improving the effectiveness of the management of ownership risks may also contribute to the revitalization of creditors on implementation claims to inefficient owners, which ultimately will contribute to the efficiency models of ownership control to exclude variants of insolvency. It is obvious that in modern conditions, the success of the model of the ownership of risk management and audit is largely determined by the ability and willingness of the owner to find a compromise between potential opportunities for expanding the firm's ability to create new value through risk and maintaining the current level of new value creation and an acceptable level of risk through the use of models of diversification.

Keywords: Risk management, ownership risks, economic transformation, Russian economy, management systems.

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Authors: A. M. Alaskari, S. E. Oraby

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The quality of a machined surface is becoming more and more important to justify the increasing demands of sophisticated component performance, longevity, and reliability. Usually, any machining operation leaves its own characteristic evidence on the machined surface in the form of finely spaced micro irregularities (surface roughness) left by the associated indeterministic characteristics of the different elements of the system: tool-machineworkpart- cutting parameters. However, one of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Time-dependent modeling is beneficial when modern machining systems, such as adaptive control techniques are considered, where the state of the machined surface and the health of the cutting edge are monitored, assessed and controlled online using realtime information provided by the variability encountered in the measured force signals. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge-s random deformation.

Keywords: Dynamic force signals, surface roughness (finish), tool wear and deformation, tool wear modes (nose, flank)

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

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In the recent past Learning Classifier Systems have been successfully used for data mining. Learning Classifier System (LCS) is basically a machine learning technique which combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. All LCSs models more or less, comprise four main components; a finite population of condition–action rules, called classifiers; the performance component, which governs the interaction with the environment; the credit assignment component, which distributes the reward received from the environment to the classifiers accountable for the rewards obtained; the discovery component, which is responsible for discovering better rules and improving existing ones through a genetic algorithm. The concatenate of the production rules in the LCS form the genotype, and therefore the GA should operate on a population of classifier systems. This approach is known as the 'Pittsburgh' Classifier Systems. Other LCS that perform their GA at the rule level within a population are known as 'Mitchigan' Classifier Systems. The most predominant representation of the discovered knowledge is the standard production rules (PRs) in the form of IF P THEN D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski and Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: IF P THEN D UNLESS C, where Censor C is an exception to the rule. Such rules are employed in situations, in which conditional statement IF P THEN D holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the IF P THEN D part of CPR expresses important information, while the UNLESS C part acts only as a switch and changes the polarity of D to ~D. In this paper Pittsburgh style LCSs approach is used for automated discovery of CPRs. An appropriate encoding scheme is suggested to represent a chromosome consisting of fixed size set of CPRs. Suitable genetic operators are designed for the set of CPRs and individual CPRs and also appropriate fitness function is proposed that incorporates basic constraints on CPR. Experimental results are presented to demonstrate the performance of the proposed learning classifier system.

Keywords: Censored Production Rule, Data Mining, GeneticAlgorithm, Learning Classifier System, Machine Learning, PittsburgApproach, , Reinforcement learning.

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Authors: C. Amer, M. Sahin

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The design of an optimised horizontal axis 5-meter-long wind turbine rotor blade in according with IEC 61400-2 standard is a research and development project in order to fulfil the requirements of high efficiency of torque from wind production and to optimise the structural components to the lightest and strongest way possible. For this purpose, a research study is presented here by focusing on the structural characteristics of a composite wind turbine blade via finite element modelling and analysis tools. In this work, first, the required data regarding the general geometrical parts are gathered. Then, the airfoil geometries are created at various sections along the span of the blade by using CATIA software to obtain the two surfaces, namely; the suction and the pressure side of the blade in which there is a hat shaped fibre reinforced plastic spar beam, so-called chassis starting at 0.5m from the root of the blade and extends up to 4 m and filled with a foam core. The root part connecting the blade to the main rotor differential metallic hub having twelve hollow threaded studs is then modelled. The materials are assigned as two different types of glass fabrics, polymeric foam core material and the steel-balsa wood combination for the root connection parts. The glass fabrics are applied using hand wet lay-up lamination with epoxy resin as METYX L600E10C-0, is the unidirectional continuous fibres and METYX XL800E10F having a tri-axial architecture with fibres in the 0,+45,-45 degree orientations in a ratio of 2:1:1. Divinycell H45 is used as the polymeric foam. The finite element modelling of the blade is performed via MSC PATRAN software with various meshes created on each structural part considering shell type for all surface geometries, and lumped mass were added to simulate extra adhesive locations. For the static analysis, the boundary conditions are assigned as fixed at the root through aforementioned bolts, where for dynamic analysis both fixed-free and free-free boundary conditions are made. By also taking the mesh independency into account, MSC NASTRAN is used as a solver for both analyses. The static analysis aims the tip deflection of the blade under its own weight and the dynamic analysis comprises normal mode dynamic analysis performed in order to obtain the natural frequencies and corresponding mode shapes focusing the first five in and out-of-plane bending and the torsional modes of the blade. The analyses results of this study are then used as a benchmark prior to modal testing, where the experiments over the produced wind turbine rotor blade has approved the analytical calculations.

Keywords: Dynamic analysis, Fiber Reinforced Composites, Horizontal axis wind turbine blade, Hand-wet layup, Modal Testing.

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Authors: S. Aziz, B. Alexander, C. Gengnagel, S. Weinzierl

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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the Building Information Modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: Acoustical design, additive manufacturing, computational design, multimodal optimization.

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Authors: Karishma Kashyap, Subha D. Parida

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Rapid population growth and urbanization is creating pressure throughout the world. This has a dramatic effect on a lot of elements which include water, food, transportation, energy, infrastructure etc. as few of the key services. Built environment sector is growing concurrently to meet the needs of urbanization. Due to such large scale development of buildings, there is a need for them to be monitored and managed efficiently. Along with appropriate management, climate adaptation is highly crucial as well because buildings are one of the major sources of greenhouse gas emission in their operation phase. Buildings to be adaptive need to provide a triple bottom approach to sustainability i.e., being socially, environmentally and economically sustainable. Hence, in order to deliver these sustainability outcomes, there is a growing understanding and thrive towards switching to green buildings or renovating new ones as per green standards wherever possible. Academic institutions in particular have been following this trend globally. This is highly significant as universities usually have high occupancy rates because they manage a large building portfolio. Also, as universities accommodate the future generation of architects, policy makers etc., they have the potential of setting themselves as a best industry practice model for research and innovation for the rest to follow. Hence their climate adaptation, sustainable growth and performance management becomes highly crucial in order to provide the best services to users. With the objective of evaluating appropriate management mechanisms within academic institutions, a feasibility study was carried out in a recent 5-Star Green Star rated university building (housing the School of Construction) in Victoria (south-eastern state of Australia). The key aim was to understand the behavioral and social aspect of the building users, management and the impact of their relationship on overall building sustainability. A survey was used to understand the building occupant’s response and reactions in terms of their work environment and management. A report was generated based on the survey results complemented with utility and performance data which were then used to evaluate the management structure of the university. Followed by the report, interviews were scheduled with the facility and asset managers in order to understand the approach they use to manage the different buildings in their university campuses (old, new, refurbished), respective building and parameters incorporated in maintaining the Green Star performance. The results aimed at closing the communication and feedback loop within the respective institutions and assist the facility managers to deliver appropriate stakeholder engagement. For the wider design community, analysis of the data highlights the applicability and significance of prioritizing key stakeholders, integrating desired engagement policies within an institution’s management structures and frameworks and their effect on building performance

Keywords: Building Optimization, Green Building, Post Occupancy Evaluation, Stakeholder Engagement.

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Authors: Sotirios Raptis

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Health and Social care (HSc) services planning and scheduling are facing unprecedented challenges, due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven approaches can help to improve policies, plan and design services provision schedules using algorithms that assist healthcare managers to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as Classification and Regression Trees (CART), Random Forests (RF), and Logistic Regression (LGR). The significance tests Chi-Squared and Student’s test are used on data over a 39 years span for which data exist for services delivered in Scotland. The demands are associated using probabilities and are parts of statistical hypotheses. These hypotheses, as their NULL part, assume that the target demand is statistically dependent on other services’ demands. This linking is checked using the data. In addition, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus, groups of services. Statistical tests confirmed ML coupling and made the prediction statistically meaningful and proved that a target service can be matched reliably to other services while ML showed that such marked relationships can also be linear ones. Zero padding was used for missing years records and illustrated better such relationships both for limited years and for the entire span offering long-term data visualizations while limited years periods explained how well patients numbers can be related in short periods of time or that they can change over time as opposed to behaviours across more years. The prediction performance of the associations were measured using metrics such as Receiver Operating Characteristic (ROC), Area Under Curve (AUC) and Accuracy (ACC) as well as the statistical tests Chi-Squared and Student. Co-plots and comparison tables for the RF, CART, and LGR methods as well as the p-value from tests and Information Exchange (IE/MIE) measures are provided showing the relative performance of ML methods and of the statistical tests as well as the behaviour using different learning ratios. The impact of k-neighbours classification (k-NN), Cross-Correlation (CC) and C-Means (CM) first groupings was also studied over limited years and for the entire span. It was found that CART was generally behind RF and LGR but in some interesting cases, LGR reached an AUC = 0 falling below CART, while the ACC was as high as 0.912 showing that ML methods can be confused by zero-padding or by data’s irregularities or by the outliers. On average, 3 linear predictors were sufficient, LGR was found competing well RF and CART followed with the same performance at higher learning ratios. Services were packed only when a significance level (p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, low birth weights, alcoholism, drug abuse, and emergency admissions. The work found  that different HSc services can be well packed as plans of limited duration, across various services sectors, learning configurations, as confirmed by using statistical hypotheses.

Keywords: Class, cohorts, data frames, grouping, prediction, probabilities, services.

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Authors: Elizabeth J. Currie, Fernando Ortega Perez

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—‘MEDICINE’ is a new project funded under the EC Horizon 2020 Marie-Sklodowska Curie Actions, to determine concepts of health and healing from a culturally specific indigenous context, using a framework of interdisciplinary methods which integrates archaeological-historical, ethnographic and modern health sciences approaches. The study will generate new theoretical and methodological approaches to model how peoples survive and adapt their traditional belief systems in a context of alien cultural impacts. In the immediate wake of the conquest of Peru by invading Spanish armies and ideology, native Andeans responded by forming the Taki Onkoy millenarian movement, which rejected European philosophical and ontological teachings, claiming “you make us sick”. The study explores how people’s experience of their world and their health beliefs within it, is fundamentally shaped by their inherent beliefs about the nature of being and identity in relation to the wider cosmos. Cultural and health belief systems and related rituals or behaviors sustain a people’s sense of identity, wellbeing and integrity. In the event of dislocation and persecution these may change into devolved forms, which eventually inter-relate with ‘modern’ biomedical systems of health in as yet unidentified ways. The development of new conceptual frameworks that model this process will greatly expand our understanding of how people survive and adapt in response to cultural trauma. It will also demonstrate the continuing role, relevance and use of TM in present-day indigenous communities. Studies will first be made of relevant pre-Colombian material culture, and then of early colonial period ethnohistorical texts which document the health beliefs and ritual practices still employed by indigenous Andean societies at the advent of the 17^th century Jesuit campaigns of persecution - ‘Extirpación de las Idolatrías’. Core beliefs drawn from these baseline studies will then be used to construct a questionnaire about current health beliefs and practices to be taken into the study population of indigenous Quechua peoples in the northern Andean region of Ecuador. Their current systems of knowledge and medicine have evolved within complex historical contexts of both the conquest by invading Inca armies in the late 15^th century, followed a generation later by Spain, into new forms. A new model will be developed of contemporary  Andean concepts of health, illness and healing demonstrating  the way these have changed through time. With this, a ‘policy tool’ will be constructed as a bridhging facility into contemporary global scenarios relevant to other Indigenous, First Nations, and migrant peoples to provide a means through which their traditional health beliefs and current needs may be more appropriately understood and met. This paper presents findings from the first analytical phases of the work based upon the study of the literature and the archaeological records. The study offers a novel perspective and methods in the development policies sensitive to indigenous and minority people’s health needs.

Keywords: Andean ethnomedicine, andean health beliefs, health beliefs models, traditional medicine.

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Authors: Vaso K. Kapnopoulou, Piero Caridis

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The fatigue of ship structural details is of major concern in the maritime industry as it can generate fracture issues that may compromise structural integrity. In the present study, a fatigue analysis of the lower hopper knuckle connection of a bulk carrier was conducted using the Finite Element Method by means of ABAQUS/CAE software. The fatigue life was calculated using Miner’s Rule and the long-term distribution of stress range by the use of the two-parameter Weibull distribution. The cumulative damage ratio was estimated using the fatigue damage resulting from the stress range occurring at each load condition. For this purpose, a cargo hold model was first generated, which extends over the length of two holds (the mid-hold and half of each of the adjacent holds) and transversely over the full breadth of the hull girder. Following that, a submodel of the area of interest was extracted in order to calculate the hot spot stress of the connection and to estimate the fatigue life of the structural detail. Two hot spot locations were identified; one at the top layer of the inner bottom plate and one at the top layer of the hopper plate. The IACS Common Structural Rules (CSR) require that specific dynamic load cases for each loading condition are assessed. Following this, the dynamic load case that causes the highest stress range at each loading condition should be used in the fatigue analysis for the calculation of the cumulative fatigue damage ratio. Each load case has a different effect on ship hull response. Of main concern, when assessing the fatigue strength of the lower hopper knuckle connection, was the determination of the maximum, i.e. the critical value of the stress range, which acts in a direction normal to the weld toe line. This acts in the transverse direction, that is, perpendicularly to the ship's centerline axis. The load cases were explored both theoretically and numerically in order to establish the one that causes the highest damage to the location examined. The most severe one was identified to be the load case induced by beam sea condition where the encountered wave comes from the starboard. At the level of the cargo hold model, the model was assumed to be simply supported at its ends. A coarse mesh was generated in order to represent the overall stiffness of the structure. The elements employed were quadrilateral shell elements, each having four integration points. A linear elastic analysis was performed because linear elastic material behavior can be presumed, since only localized yielding is allowed by most design codes. At the submodel level, the displacements of the analysis of the cargo hold model to the outer region nodes of the submodel acted as boundary conditions and applied loading for the submodel. In order to calculate the hot spot stress at the hot spot locations, a very fine mesh zone was generated and used. The fatigue life of the detail was found to be 16.4 years which is lower than the design fatigue life of the structure (25 years), making this location vulnerable to fatigue fracture issues. Moreover, the loading conditions that induce the most damage to the location were found to be the various ballasting conditions.

Keywords: Lower hopper knuckle, high cycle fatigue, finite element method, dynamic load cases.

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