Search results for: operation estimation

Authors: Zied Guidara, Alexander Morgenstern, Aref Younes Maalej

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In this paper, a desiccant solar unit for air conditioning and desalination is presented first. Secondly, a dynamic modelling study of the desiccant wheel is developed. After that, a simulation study and an experimental investigation of the behaviour of desiccant wheel are developed. The experimental investigation is done in the chamber of commerce in Freiburg-Germany. Indeed, the variations of calculated and measured temperatures and specific humidity of dehumidified and rejected air are presented where a good agreement is found when comparing the model predictions with experimental data under the considered range of operating conditions. Finally, the study of the compartments of desalination and water condensation shows that the unit can produce an acceptable quantity of water at the same time of the air conditioning operation.

Keywords: air conditioning, desalination, condensation, design, desiccant wheel

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

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The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

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Authors: Peihao Huang, Chun Zhao

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Thin-film transistors(TFTs) have the advantages of low power consumption, short reaction time, and have high research value in the field of semiconductors, based on this reason, people have focused on gallium oxide-indium oxide thin-film transistors, a relatively common thin-film transistor, elaborated and analyzed his production process, "aqueous solution method", explained the purpose of each step of operation, and finally explored the influence of potassium ions doped in the channel layer on the electrical properties of the device, as well as the effect of oxygen vacancies on its switching ratio and memory, and summarized the conclusions.

Keywords: aqueous solution, oxygen vacancies, switch ratio, thin-film transistor(TFT)

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Authors: Jung-Ho Moon, Myung-Gon Yoon, Tae Kwon Ha

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This paper presents a wireless sensor network protocol for a car parking monitoring system. A wireless sensor network for the purpose is composed of multiple sensor nodes, a sink node, a gateway, and a server. Each of the sensor nodes is equipped with a 3-axis AMR sensor and deployed in the center of a parking space. The sensor node reads its sensor values periodically and transmits the data to the sink node if the current and immediate past sensor values show a difference exceeding a threshold value. The operations of the sink and sensor nodes are described in detail along with flow diagrams. The protocol allows a low-duty cycle operation of the sensor nodes and a flexible adjustment of the threshold value used by the sensor nodes.

Keywords: car parking monitoring, sensor node, wireless sensor network, network protocol

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Authors: Anel Hasić, Naser Prljača

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In the domain of autonomous or piloted flights, the accurate control of quadrotor trajectories is of paramount significance for large numbers of tasks. These adaptable aerial platforms find applications that span from high-precision aerial photography and surveillance to demanding search and rescue missions. Among the fundamental challenges confronting quadrotor operation is the demand for accurate following of desired flight paths. To address this control challenge, among others, two celebrated well-established control strategies have emerged as noteworthy contenders: Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) control. In this work, we focus on the extensive examination of MPC and PID control techniques by using comprehensive simulation studies in MATLAB/Simulink. Intensive simulation results demonstrate the performance of the studied control algorithms.

Keywords: MATLAB, MPC, PID, quadcopter, simulink

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Authors: Fabio Oettl, Sebastian Hoerbrand, Tobias Wittmeir, Johannes Schilp

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By combining the additive manufacturing (AM)- process with digital concepts, like the digital twin (DT) or the downsized and basing concept of the digital part file (DPF), the competitiveness of additive manufacturing is enhanced and new use cases like decentral production are enabled. But in literature, one can´t find any quantitative approach for valuing the usage of a DT or DPF in AM. Out of this fact, such an approach will be developed within this paper in order to further promote or dissuade the usage of these concepts. The focus is set on the production as an early lifecycle phase, which means that the AM-production process gets analyzed regarding the potential advantages of using DPF in AM. These advantages are transferred to a monetary value with this approach. By calculating the costs of the DPF, an overall monetary value is a result. Thereon a tool, based on a simulation environment is constructed, where the algorithms are transformed into a program. The results of applying this tool show that an overall value of 20,81 € for the DPF can be realized for one special use case. For the future application of the DPF there is the recommendation to integrate especially sustainable information because out of this, a higher value of the DPF can be expected.

Keywords: additive manufacturing, digital concept costs, digital part file, digital twin, monetary value estimation

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Authors: Eleonora Di Mario

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This paper describes the application of ground improvement to replace a typical piled foundation scheme in a power plant in Singapore. Several buildings within the plant were founded on vibro-compacted sand, including a turbine unit which had extremely stringent requirements on the allowable settlement. The achieved savings in terms of cost and schedule are presented. The monitoring data collected during the operation of the turbine are compared to the design predictions to validate the design approach, and the quality of the ground improvement works. In addition, the calculated carbon footprint of the ground improvement works are compared to the piled solution, showing that the vibro-compaction has a significantly lower carbon footprint.

Keywords: ground improvement, vibro-compaction, case study, sustainability, carbon footprint

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Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

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Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

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Authors: Riznaldi Akbar

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In this study, we compared the performance of the Artificial Neural Network (ANN) model with back-propagation algorithm in correctly predicting in-sample and out-of-sample external debt crisis in Indonesia. We found that exchange rate, foreign reserves, and exports are the major determinants to experiencing external debt crisis. The ANN in-sample performance provides relatively superior results. The ANN model is able to classify correctly crisis of 89.12 per cent with reasonably low false alarms of 7.01 per cent. In out-of-sample, the prediction performance fairly deteriorates compared to their in-sample performances. It could be explained as the ANN model tends to over-fit the data in the in-sample, but it could not fit the out-of-sample very well. The 10-fold cross-validation has been used to improve the out-of-sample prediction accuracy. The results also offer policy implications. The out-of-sample performance could be very sensitive to the size of the samples, as it could yield a higher total misclassification error and lower prediction accuracy. The ANN model could be used to identify past crisis episodes with some accuracy, but predicting crisis outside the estimation sample is much more challenging because of the presence of uncertainty.

Keywords: debt crisis, external debt, artificial neural network, ANN

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Authors: Muttamas Wongwanich, John R. Bryson, Catherine E. Harris

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Science parks are an essential component of localized innovation ecosystems. Science Parks have played a critical role in enhancing local innovation ecosystems in developed market economies. Attempts have been made to replicate best practice in other national contexts. To our best knowledge, the study about the development of Science Parks has not been undertaken on the economic impact on the developing countries. Further research is required to understand the adoption of Science Park policies in developing and emerging economies. This study explores the implementation of Science Park policy and its impacts on economic growth and development in Thailand, focusing on the relationship between universities and businesses. The Thailand context is essential. Thailand’s economy is dominated by agriculture and tourism. The Science Park policy is trying to develop an agriculturally orientated innovative ecosystem. Thailand established four Science Parks based on a policy that highlighted the importance of cooperation between government, HEIs, and businesses. These Science Parks are intended to increase small and medium enterprises’ (SMEs) innovativeness, employment, and regional economic growth by promoting collaboration and knowledge transfer between HEIs and the private sector. This study explores one regional Science Park in Thailand with an emphasis on understanding the implementation and operation of a triple helix innovation policy. The analysis explores the establishment of the Science Park and its impacts on firms and the regional economy through interviews with Science Parks directors, firms, academics, universities, and government officials. The analysis will inform Science Park policy development in Thailand to support the national objective to develop an innovation ecosystem based on the integration of technology with innovation policy, supporting technology-based SMEs in the creation of local jobs. The finding shows that the implementation of the Science Park policy in Thailand requires support and promotion from the government. The regional development plan must be related to the regional industry development strategy, considering the strengths and weaknesses of local entrepreneurs. The long time in granting a patent is the major obstacle in achieving the government’s aim in encouraging local economic activity. The regional Science Parks in Thailand are at the early stage of the operation plan. Thus, the impact on the regional economy cannot be measured and need further investigation in a more extended period. However, local businesses realize the vital of research and development (R&D). There have been more requests for funding support in doing R&D. Furthermore, there is the creation of linkages between businesses, HEIs, and government authorities as expected.

Keywords: developing country, emerging economy, regional development, science park, Thailand, triple helix

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Authors: Natsuki Kishizawa, Keiko Nakano, Hussam Organji, Amer Shaiban, Mohammad Albeirutty

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One of the most important tasks in operating desalination plants using a reverse osmosis (RO) method is preventing RO membrane fouling caused by foulants found in seawater. Optimal design of the pre-treatment process of RO process for plants enables the reduction of foulants. Therefore, a quantitative evaluation of the fouling risk in pre-treated water, which is fed to RO, is required for optimal design. Some measurement methods for water quality such as silt density index (SDI) and total organic carbon (TOC) have been conservatively applied for evaluations. However, these methods have not been effective in some situations for evaluating the fouling risk of RO feed water. Furthermore, stable management of plants will be possible by alerts and appropriate control of the pre-treatment process by using the method if it can be applied to the inline monitoring system for the fouling risk of RO feed water. The purpose of this study is to develop a method to evaluate the fouling risk of RO feed water. We applied a quartz crystal microbalance (QCM) to measure the amount of foulants found in seawater using a sensor whose surface is coated with polyamide thin film, which is the main material of a RO membrane. The increase of the weight of the sensor after a certain length of time in which the sample water passes indicates the fouling risk of the sample directly. We classified the values as “FP: Fouling Potential”. The characteristics of the method are to measure the very small amount of substances in seawater in a short time: < 2h, and from a small volume of the sample water: < 50mL. Using some RO cell filtration units, a higher correlation between the pressure increase given by RO fouling and the FP from the method than SDI and TOC was confirmed in the laboratory-scale test. Then, to establish the correlation in the actual bench-scale RO membrane module, and to confirm the feasibility of the monitoring system as a control tool for the pre-treatment process, we have started a long-term test at an experimental desalination site by the Red Sea in Jeddah, Kingdom of Saudi Arabia. Implementing inline equipment for the method made it possible to measure FP intermittently (4 times per day) and automatically. Moreover, for two 3-month long operations, the RO operation pressure among feed water samples of different qualities was compared. The pressure increase through a RO membrane module was observed at a high FP RO unit in which feed water was treated by a cartridge filter only. On the other hand, the pressure increase was not observed at a low FP RO unit in which feed water was treated by an ultra-filter during the operation. Therefore, the correlation in an actual scale RO membrane was established in two runs of two types of feed water. The result suggested that the FP method enables the evaluation of the fouling risk of RO feed water.

Keywords: fouling, monitoring, QCM, water quality

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Sudhir Kumar Tiwari

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The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

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Authors: Michal Kozubík, Svetlana Síthová

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Aim: Aim of this study is to introduce the method of instrumental enrichment to people who works in the helping professions, and show further possibilities of its realization with children from socially disadvantaged backgrounds into society. Methods: We focused on Feuerstein’s Instrumental Enrichment method, its theoretical grounds and practical implementation. We carried out questionnaires and directly observed children from the disadvantaged background in Partizánske district. Results: We outlined the issues of children from disadvantaged social environment and their opportunity of social integration using the method. The findings showed the utility of Feuerstein method. Conclusions: We conclude that Feuerstein methods are very suitable for children from socially disadvantaged background and importance of social workers and special educator co-operation.

Keywords: Feuerstein, inclusion, education, socially disadvantaged background

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Authors: Qian Zhang, Dongkai Shen, Yan Shi

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A new mechanical ventilator with automatic secretion clearance function can improve the secretion clearance safely and efficiently. However, in recent modeling studies on various mechanical ventilators, it was considered that human had one lung, and the coupling effect of double lungs was never illustrated. In this paper, to expound the coupling effect of double lungs, a mathematical model of a ventilation system of a bi-level positive airway pressure (BiPAP) controlled ventilator with secretion clearance was set up. Moreover, an experimental study about the mechanical ventilation system of double lungs on BiPAP ventilator was conducted to verify the mathematical model. Finally, the coupling effect of double lungs of the mathematical ventilation was studied by simulation and orthogonal experimental design. This paper adds to previous studies and can be referred to optimization methods in medical researches.

Keywords: double lungs, coupling effect, secretion clearance, orthogonal experimental design

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Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani

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In this study, the absorbed dose of human organs after injection of ¹⁷⁷Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, ¹⁷⁷Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.

Keywords: ¹⁷⁷Lu, breast cancer, compartmental modeling, dosimetry

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Authors: Mustapha El Mataouy, Abellatif Aaliti, Mouhamed Khaddor

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Erbium actived silica-hafnia planar waveguides have been prepared by sol-gel route. The films were deposited on vitreous silica substrates using dip-coating technique. The parameters of preparation have been chosen to optimize the waveguides for operation in the near infrared (NIR) region, and to increase the luminescence efficiency of the metastable 4I13/2 state of Erbium ions. The waveguides properties were determined by m-lines spectroscopy, loss measurements. Waveguide Raman and luminescence spectroscopy were used to obtain information about the structure of the prepared films and about the dynamical process related to the emission in the C telecom band (1530nm-1565nm) of the Erbium ions. The results are discussed with the aim of comparing the structural and optical properties of Erbium activated silica-hafnia planar waveguides with different molar ratio of Si / Hf.

Keywords: erbium, optical amplifiers, silica-hafnia, sol-gel, waveguide

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Authors: Adrian Millea

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In hierarchical reinforcement learning, one of the main issues encountered is the discovery of subgoal states or options (which are policies reaching subgoal states) by partitioning the environment in a meaningful way. This partitioning usually requires an expensive global clustering operation or eigendecomposition of the Laplacian of the states graph. We propose a local solution to this issue, much more efficient than algorithms using global information, which successfully discovers subgoal states by computing a simple function, which we call heterogeneity for each state as a function of its neighbors. Moreover, we construct a value function using the difference in heterogeneity from one step to the next, as reward, such that we are able to explore the state space much more efficiently than say epsilon-greedy. The same principle can then be applied to higher level of the hierarchy, where now states are subgoals discovered at the level below.

Keywords: exploration, hierarchical reinforcement learning, locality, options, value functions

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Authors: Tomas Menard

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The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters.

Keywords: dynamical system, control law design, sampled output, observer design

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Authors: Majid Khalili, Hamed Tayebi

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This paper considers a stochastic flexible job-shop scheduling (SFJSS) problem in the presence of production disruptions, and reactive scheduling is implemented in order to find the optimal solution under uncertainty. In this problem, there are two main disruptions including machine failure which influences operation time, and modification or cancellation of the order delivery date during production. In order to decrease the negative effects of these difficulties, two derived strategies from reactive scheduling are used; the first one is relevant to being able to allocate multiple machine to each job, and the other one is related to being able to select the best alternative process from other job while some disruptions would be created in the processes of a job. For this purpose, a Mixed Integer Linear Programming model is proposed.

Keywords: flexible job-shop scheduling, reactive scheduling, stochastic environment, mixed integer linear programming

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Authors: Magdi M. E. Zumrawi, Mohamed Awad

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Determination of Resilient Modulus (M_R) is quite important for characterizing materials in pavement design and evaluation. The main focus of this study is to develop a correlation that predict the resilient modulus of subgrade soils from simple and easy measured soil index properties. To achieve this objective, three subgrade soils representing typical Khartoum soils were selected and tested in the laboratory for measuring resilient modulus. Other basic laboratory tests were conducted on the soils to determine their physical properties. Several soil samples were prepared and compacted at different moisture contents and dry densities and then tested using resilient modulus testing machine. Based on experimental results, linear relationship of M_R with the consistency factor ‘F_c’ which is a combination of dry density, void ratio and consistency index had been developed. The results revealed that very good linear relationship found between the M_R and the consistency factor with a coefficient of linearity (R²) more than 0.9. The consistency factor could be used for the prediction of the M_R of compacted subgrade soils with precise and reliable results.

Keywords: Consistency factor, resilient modulus, subgrade soil, properties

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Authors: Anna Guitart Atienza, Ana Fernández del Río, Madhav Nekkar, Jelena Ljubicic, África Periáñez, Eura Shin, Lauren Bellhouse

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The use of digital devices in healthcare or mobile health (mHealth) has increased in recent years due to the advances in digital technology, making it possible to nudge healthy behaviors through individual interventions. In addition, mHealth is becoming essential in poor-resource settings due to the widespread use of smartphones in areas where access to professional healthcare is limited. In this work, we evaluate mHealth interventions in low-income countries with a focus on causal inference. Counterfactuals estimation and other causal computations are key to determining intervention success and assisting in empirical decision-making. Our main purpose is to personalize treatment recommendations and triage patients at the individual level in order to maximize the entire intervention's impact on the desired outcome. For this study, collected data includes mHealth individual logs from front-line healthcare workers, electronic health records (EHR), and external variables data such as environmental, demographic, and geolocation information.

Keywords: causal inference, mHealth, intervention, personalization

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Authors: Tomasz Robert Kuczerski

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The high complexity of the algorithm of the autonomous tandem detonator system creates an optimization problem due to the parallel operation of several machine states of the system. Many years of experience and classic analyses have led to a partially optimized model. Limitations on the energy resources of this class of autonomous systems make it necessary to search for more effective methods of optimisation. The use of the Quantum Approximate Optimization Algorithm (QAOA) in these studies shows the most promising results. With the help of multiple evaluations of several qubit quantum circuits, proper results of variable parameter optimization were obtained. In addition, it was observed that the increase in the number of assessments does not result in further efficient growth due to the increasing complexity of optimising variables. The tests confirmed the effectiveness of the QAOA optimization method.

Keywords: algorithm analysis, autonomous system, quantum optimization, tandem detonator

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Authors: Riad

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As present world needs more and more energy in a low cost way, it needs to find out the optimal way of power generation. In the sense of low cost, renewable energy is one of the greatest sources of power generation. Water vapour of sea/river/lake can be used for power generation by using the greenhouse effect in a large flat type water chamber floating on the water surface. The water chamber will always be kept half filled. When water evaporates by sunlight, the high pressured gaseous water will be stored in the chamber. By passing through a pipe and by using aerodynamics it can be used for power generation. The water level of the chamber is controlled by some means. As a large amount of water evaporates, an estimation can be highlighted, approximately 3 to 4 thousand gallons of water evaporates from per acre of surface (this amount will be more by greenhouse effect). This large amount of gaseous water can be utilized for power generation by passing through a pipe. This method can be a source of power generation.

Keywords: renewable energy, greenhouse effect, water chamber, water vapour

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Authors: Larry Hawkins, Scott K. Sakakura, Michael J. Salopek

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The Marshall Space Flight Center is designing and building a next-generation CO₂ removal system, the Four Bed Carbon Dioxide Scrubber (4BCO₂), which will use the International Space Station (ISS) as a testbed. The current ISS CO2 removal system has faced many challenges in both performance and reliability. Given that CO2 removal is an integral Environmental Control and Life Support System (ECLSS) subsystem, the 4BCO2 Scrubber has been designed to eliminate the shortfalls identified in the current ISS system. One of the key required upgrades was to improve the performance and reliability of the blower that provides the airflow through the CO₂ sorbent beds. A magnetically levitated blower, capable of higher airflow and pressure than the previous system, was developed to meet this need. The design and qualification testing of this next-generation blower are described here. The new blower features a high-efficiency permanent magnet motor, a five-axis, active magnetic bearing system, and a compact controller containing both a variable speed drive and a magnetic bearing controller. The blower uses a centrifugal impeller to pull air from the inlet port and drive it through an annular space around the motor and magnetic bearing components to the exhaust port. Technical challenges of the blower and controller development include survival of the blower system under launch random vibration loads, operation in microgravity, packaging under strict size and weight requirements, and successful operation during 4BCO₂ operational changeovers. An ANSYS structural dynamic model of the controller was used to predict response to the NASA defined random vibration spectrum and drive minor design changes. The simulation results are compared to measurements from qualification testing the controller on a vibration table. Predicted blower performance is compared to flow loop testing measurements. Dynamic response of the system to valve changeovers is presented and discussed using high bandwidth measurements from dynamic pressure probes, magnetic bearing position sensors, and actuator coil currents. The results presented in the paper show that the blower controller will survive launch vibration levels, the blower flow meets the requirements, and the magnetic bearings have adequate load capacity and control bandwidth to maintain the desired rotor position during the valve changeover transients.

Keywords: blower, carbon dioxide removal, environmental control and life support system, magnetic bearing, permanent magnet motor, validation testing, vibration

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Authors: Yasir Khan

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The continued growth in international students coming to China for higher education had a significant positive impact on trade and GDP in China. Student mobility may expend trade with their country of origin, owing to superior knowledge, or preferential access to market opportunities. We test this hypothesis using Chinese trade data from 1999 to 2017. In fully-modify (OLS) and dynamic (OLS) testing estimation, we find that a 1.24 percent increase in student inward mobility is associated with a 1 percent increase in Chinese export trade. On the other hand, we find that a 1.18 percent increase in the student inward mobility to China is associated with a 1 percent increase in import trade. In addition, we find that a 1.13 percent increase in international student inward mobility is associated with a 1 percent increase in the GDP. The outcome suggests that international students have a strong influence on Gross Domestic Product (GDP), exports and imports trade. However, the study holds that the government should attach great attachment and importance to the role of international students in the export and import trade.

Keywords: international student mobility, China, export, import, GDP, FMOLS, DOLS

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Authors: G. N. Tiwari, Shyam

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Photovoltaic thermal (PVT) roof type greenhouse dryer installed above the wind tower of SODHA BERS COMPLEX, Varanasi has been analyzed for all types of weather conditions. The product to be dried has been kept at three different trays. The upper tray receives energy from the PV cover while the bottom tray receives thermal energy from the hot air of the wind tower. The annual energy estimation has been done for the all types of weather condition of composite climate of northern India. It has been found that maximum energy saving is observed for c type of weather condition whereas minimum energy saving is observed for a type of weather condition. The energy saving on overall thermal energy basis and exergy basis are 1206.8 kWh and 360 kWh respectively for c type of weather condition. The energy saving from all types of weather condition are found to be 3175.3 kWh and 957.6 kWh on overall thermal energy and overall exergy basis respectively.

Keywords: exergy, greenhouse, photovoltaic thermal, solar dryer

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Hee-Choul Kwon, Heeyong Kwon

Abstract:

Image rotation is one of main pre-processing steps for image processing or image pattern recognition. It is implemented with a rotation matrix multiplication. It requires a lot of floating point arithmetic operations and trigonometric calculations, so it takes a long time to execute. Therefore, there has been a need for a high speed image rotation algorithm without two major time-consuming operations. However, the rotated image has a drawback, i.e. distortions. We solved the problem using an augmented two-step shear transform. We compare the presented algorithm with the conventional rotation with images of various sizes. Experimental results show that the presented algorithm is superior to the conventional rotation one.

Keywords: high-speed rotation operation, image rotation, transform matrix, image processing, pattern recognition

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Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

Abstract:

In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

Procedia PDF Downloads 356