Search results for: optimization/inverse mapping

Authors: Parastoo Kazemiyan

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Over the past 80 years, in compliance with the advent of modernity in Iran and Turkey, the presence of women in economic and social arenas has creates serious challenges in the capacity of urban spaces to respond to their presence and transport because urban spaces up until then were based on masculine criteria and therefore, women could use such spaces in the company of their fathers or husbands. However, as modernity expanded by Reza Shah and Ataturk, women found the opportunity to work and be present in urban spaces alongside men and their presence in economic and social domains resulted in their presence in these spaces in the early and late hours of the day. Therefore, the city had to be transformed in structural, social, and environmental terms to accommodate women's activities and presence in various urban arenas, which was a huge step in transition from a masculine man-based culture to an all-inclusive human-based culture in these two countries. However, the optimization of urban space was subject to political changes in the two countries, leading to significant differences in designing urban spaces in Tehran and Istanbul. What shows the importance and novelty of the present study lie in the differences in urban planning and optimization in the two capital cities, which gave rise to different outcomes in desirability and quality of living in these two capital cities. Due to the importance of the topic, one of the most significant factors in desirability and acceptability of urban space for women was examined using a descriptive-analytic method based on qualitative methodology in Tehran and Istanbul. The results showed that the infrastructural factors in Istanbul, including safety of access, variety, and number of public transport modes, transparency, and supervision over public spaces have provided women with a safer and more constant presence compared to Tehran. It seems that challenges involved in providing access to urban spaces in Tehran in terms of infrastructure and function have made Tehran unable to respond to the most basic needs of its female citizens.

Keywords: gender differences, urban space security, access to transportation systems, women's challenges

Procedia PDF Downloads 125

Authors: Fariza Yunus, Jasmee Jaafar, Zamalia Mahmud, Nurul Nisa’ Khairul Azmi, Nursalleh K. Chang, Nursalleh K. Chang

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Variation of air temperature from one place to another is cause by air temperature controls. In general, the most important control of air temperature is elevation. Another significant independent variable in estimating air temperature is the location of meteorological stations. Distances to coastline and land use type are also contributed to significant variations in the air temperature. On the other hand, in homogeneous terrain direct interpolation of discrete points of air temperature work well to estimate air temperature values in un-sampled area. In this process the estimation is solely based on discrete points of air temperature. However, this study presents that air temperature controls also play significant roles in estimating air temperature over homogenous terrain of Peninsular Malaysia. An Inverse Distance Weighting (IDW) interpolation technique was adopted to generate continuous data of air temperature. This study compared two different datasets, observed mean monthly data of T, and estimation error of T–T’, where T’ estimated value from a multiple regression model. The multiple regression model considered eight independent variables of elevation, latitude, longitude, coastline, and four land use types of water bodies, forest, agriculture and build up areas, to represent the role of air temperature controls. Cross validation analysis was conducted to review accuracy of the estimation values. Final results show, estimation values of T–T’ produced lower errors for mean monthly mean air temperature over homogeneous terrain in Peninsular Malaysia.

Keywords: air temperature control, interpolation analysis, peninsular Malaysia, regression model, air temperature

Procedia PDF Downloads 374

Authors: Ziaullah, Shah Wahab Ali

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Micro-grid equipped with heterogeneous energy resources present the idea of small scale distributed energy management (DEM). DEM helps in minimizing the transmission and operation costs, power management and peak load demands. Micro-grids are collections of small, independent controllable power-generating units and renewable energy resources. Micro-grids also motivate to enable active customer participation by giving accessibility of real-time information and control to the customer. The capability of fast restoration against faulty situation, integration of renewable energy resources and Information and Communication Technologies (ICT) make micro-grid as an ideal system for distributed power systems. Micro-grids can have a bank of energy storage devices. The energy management system of micro-grid can perform real-time energy forecasting of renewable resources, energy storage elements and controllable loads in making proper short-term scheduling to minimize total operating costs. We present a review of existing micro-grids optimization objectives/goals, constraints, solution approaches and tools used in micro-grids for energy management. Cost-benefit analysis of micro-grid reveals that cooperation among different micro-grids can play a vital role in the reduction of import energy cost and system stability. Cooperative micro-grids energy trading is an approach to electrical distribution energy resources that allows local energy demands more control over the optimization of power resources and uses. Cooperation among different micro-grids brings the interconnectivity and power trading issues. According to the literature, it shows that open area of research is available for cooperative micro-grids energy trading. In this paper, we proposed and formulated the efficient energy management/trading module for interconnected micro-grids. It is believed that this research will open new directions in future for energy trading in cooperative micro-grids/interconnected micro-grids.

Keywords: distributed energy management, information and communication technologies, microgrid, energy management

Procedia PDF Downloads 375

Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Kiatkulchai Jitt-Aer, Graham Wall, Dylan Jones

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As a result of the Indian Ocean tsunami in 2004, logistics applied to disaster relief operations has received great attention in the humanitarian sector. As learned from such disaster, preparing and responding to the aspect of delivering essential items from distribution centres to affected locations are of the importance for relief operations as the nature of disasters is uncertain especially in suffering figures, which are normally proportional to quantity of supplies. Thus, this study proposes a spatial decision support system (SDSS) for humanitarian logistics by integrating Geographical Information Systems (GIS) and the capacitated vehicle routing problem (CVRP). The GIS is utilised for acquiring demands simulated from the tsunami flooding model of the affected area in the first stage, and visualising the simulation solutions in the last stage. While CVRP in this study encompasses designing the relief routes of a set of homogeneous vehicles from a relief centre to a set of geographically distributed evacuation points in which their demands are estimated by using both simulation and randomisation techniques. The CVRP is modeled as a multi-objective optimization problem where both total travelling distance and total transport resources used are minimized, while demand-cost efficiency of each route is maximized in order to determine route priority. As the model is a NP-hard combinatorial optimization problem, the Clarke and Wright Saving heuristics is proposed to solve the problem for the near-optimal solutions. The real-case instances in the coastal area of Phuket, Thailand are studied to perform the SDSS that allows a decision maker to visually analyse the simulation scenarios through different decision factors.

Keywords: demand simulation, humanitarian logistics, geographical information systems, relief operations, capacitated vehicle routing problem

Procedia PDF Downloads 248

Authors: D. Mehdizadeh, M. Rahimian, M. Eskandari-Ghadi

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This article is concerned with the determination of the static interaction of a vertically loaded rigid circular disc embedded at the interface of a horizontal layer sandwiched in between two different transversely isotropic half-spaces called as tri-material full-space. The axes of symmetry of different regions are assumed to be normal to the horizontal interfaces and parallel to the movement direction. With the use of a potential function method, and by implementing Hankel integral transforms in the radial direction, the government partial differential equation for the solely scalar potential function is transformed to an ordinary 4th order differential equation, and the mixed boundary conditions are transformed into a pair of integral equations called dual integral equations, which can be reduced to a Fredholm integral equation of the second kind, which is solved analytically. Then, the displacements and stresses are given in the form of improper line integrals, which is due to inverse Hankel integral transforms. It is shown that the present solutions are in exact agreement with the existing solutions for a homogeneous full-space with transversely isotropic material. To confirm the accuracy of the numerical evaluation of the integrals involved, the numerical results are compared with the solutions exists for the homogeneous full-space. Then, some different cases with different degrees of material anisotropy are compared to portray the effect of degree of anisotropy.

Keywords: transversely isotropic, rigid disc, elasticity, dual integral equations, tri-material full-space

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Authors: Misra Ayse Adsiz, Selim Selvi

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In today's world, technology is competing with time. In order to catch up with the world's companies and adapt quickly to the changes, it is necessary to speed up the processes and keep pace with the rate of change of the technology. The missile system design processes, which are handled with classical methods, keep behind in this race. Because customer requirements are not clear, and demands are changing again and again in the design process. Therefore, in the system design process, a methodology suitable for the missile system design dynamics has been investigated and the processes used for catching up the era are examined. When commonly used design processes are analyzed, it is seen that any one of them is dynamic enough for today’s conditions. So a hybrid design process is established. After a detailed review of the existing processes, it is decided to focus on the Scrum Framework and Agile Philosophy. Scrum is a process framework. It is focused on to develop software and handling change management with rapid methods. In addition, agile philosophy is intended to respond quickly to changes. In this study, it is aimed to integrate Scrum framework and agile philosophy, which are the most appropriate ways for rapid production and change adaptation, into the missile system design process. With this approach, it is aimed that the design team, involved in the system design processes, is in communication with the customer and provide an iterative approach in change management. These methods, which are currently being used in the software industry, have been integrated with the product design process. A team is created for system design process. The roles of Scrum Team are realized with including the customer. A scrum team consists of the product owner, development team and scrum master. Scrum events, which are short, purposeful and time-limited, are organized to serve for coordination rather than long meetings. Instead of the classic system design methods used in product development studies, a missile design is made with this blended method. With the help of this design approach, it is become easier to anticipate changing customer demands, produce quick solutions to demands and combat uncertainties in the product development process. With the feedback of the customer who included in the process, it is worked towards marketing optimization, design and financial optimization.

Keywords: agile, design, missile, scrum

Procedia PDF Downloads 168

Authors: Assabo Mohamed, Bile Mohamed, Ali Farah, Isman Souleiman, Olga Alos Ramos, Marie Cadet

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The life of a nuclear power plant is regularly punctuated by short or long period outages to carry out maintenance operations and/or nuclear fuel reloading. During these stops periods, it is essential to conserve all the secondary circuit equipment to avoid corrosion priming. This kind of circuit is one of the main components of a nuclear reactor. Indeed, the conservation materials on shutdown of a nuclear unit improve circuit performance and reduce the maintenance cost considerably. This study is a part of the optimization of the dry preservation of equipment from the water station of the nuclear reactor. The main objective is to provide tools to guide Electricity Production Nuclear Centre (EPNC) in order to achieve the criteria required by the chemical specifications of conservation materials. A theoretical model of drying exchangers of water station is developed by the software Engineering Equation Solver (EES). It used to size requirements and air quality needed for dry conservation of equipment. This model is based on heat transfer and mass transfer governing the drying operation. A parametric study is conducted to know the influence of aerothermal factor taking part in the drying operation. The results show that the success of dry conservation of equipment of the secondary circuit of nuclear reactor depends strongly on the draining, the quality of drying air and the flow of air injecting in the secondary circuit. Finally, theoretical case study performed on EES highlights the importance of mastering the entire system to balance the air system to provide each exchanger optimum flow depending on its characteristics. From these results, recommendations to nuclear power plants can be formulated to optimize drying practices and achieve good performance in the conservation of material from the water at the stop position.

Keywords: dry conservation, optimization, sizing, water station

Procedia PDF Downloads 262

Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

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Authors: Ammar Juma Abdlmutalib, Osman Abdullatif

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Upper Jurrasic Arab-D Reservoir is considered as the largest oil reservoir in Saudi Arabia. The equivalent outcrop is exposed near Riyadh. The study investigates the relationships between lithofacies properties changes and geomechanical properties of Arab-D Reservoir in the outcrop scale. The methods used included integrated field observations and laboratory measurements. Schmidt Hammer Rebound Hardness, Point Load Index tests were carried out to estimate the strength of the samples, ultrasonic wave velocity test also was applied to measure P-wave, S-wave, and dynamic Poisson's ratio. Thin sections have been analyzed and described. The results show that there is a variation in geomechanical properties between the Arab-D member and Upper Jubaila Formation at outcrop scale, the change in texture or grain size has no or little effect on these properties. This is because of the clear effect of diagenesis which changes the strength of the samples. The result also shows the negative or inverse correlation between porosity and geomechanical properties. As for the strength, dolomitic mudstone and wackestone within Upper Jubaila Formation has higher Schmidt hammer values, wavy rippled sandy grainstone which is rich in quarts has the greater point load index values. While laminated mudstone and breccias, facies has lower strength. This emphasizes the role of mineral content in the geomechanical properties of Arab-D reservoir lithofacies.

Keywords: geomechanical properties, Arab-D reservoir, lithofacies changes, Poisson's ratio, diageneis

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Authors: Changju Lee, Seungmo Ku, Sondo Kim, Woojin Chang

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How to detecting financial bubble? Addressing this simple question has been the focus of a vast amount of empirical research spanning almost half a century. However, financial bubble is hard to observe and varying over the time; there needs to be more research on this area. In this paper, we used abnormal difference between common stocks price and those preferred stocks price to explain financial bubble. First, we proposed the ‘W-index’ which indicates spread between common stocks and those preferred stocks in stock market. Second, to prove that this ‘W-index’ is valid for measuring financial bubble, we showed that there is an inverse relationship between this ‘W-index’ and S&P500 rate of return. Specifically, our hypothesis is that when ‘W-index’ is comparably higher than other periods, financial bubbles are added up in stock market and vice versa; according to our hypothesis, if investors made long term investments when ‘W-index’ is high, they would have negative rate of return; however, if investors made long term investments when ‘W-index’ is low, they would have positive rate of return. By comparing correlation values and adjusted R-squared values of between W-index and S&P500 return, VIX index and S&P500 return, and TED index and S&P500 return, we showed only W-index has significant relationship between S&P500 rate of return. In addition, we figured out how long investors should hold their investment position regard the effect of financial bubble. Using this W-index, investors could measure financial bubble in the market and invest with low risk.

Keywords: financial bubble detection, future return, forecasting, pairs trading, preferred stocks

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Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

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This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

Procedia PDF Downloads 147

Authors: Priscila Vitorino, Jeeziane Rezende, Edison Pereira, Adrielly Silva, Weimar Barroso

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Body composition insight during physical activity is relevant to follow up sports income since it can be important and actuate in velocity, resistance, potency, and has an effect on force and agility. The purpose of this study was to identify anthropometric profile, evaluate and correlate body mass index and bioimpedance behavior during the days of Caminhada Ecológica de Goiás - Brasil. A longitudinal study was performed with 25 male participants, with an average age of 45.6±9.1 years. All patients were actives. Body composition was evaluated by body mass index (BMI) measurement and bioimpedance procedures. Both were collected 20 days before walking beginning (A0) and in the four days along the same (A1, A2, A3 e A4). Data were collected in the end of each walking day at athletes accommodations. Final distance during walking route was 308 km in five days, with an average of 62km/day and 7,6 km/hour, and an average temperature of 30°C. Data are represented with mean and standard deviation. ANOVA (Bonferroni pos test) was used to compare frequent measurements between the days. Pearson's correlation test was used to correlate BMI with lean mass, fat mass, and water. BMI decreased from A0 to A1, A2 and A3 (p < 0,01) and increased on A4 (p < 0,01). No changes were observed concerning fat percentage (p=0,60), lean mass (p=0,10) and body water composition (p=0,09). A positive and moderate correlation between BMI and fat percentage was observed; an inverse and moderate correlation between BMI, lean mass and body water composition occurred. Total body mass increased during high intensity and long term walking distance. However, the values of body fat, lean mass and water were maintained.

Keywords: aerobic exercise, body composition, metabolism, sports

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

Procedia PDF Downloads 342

Authors: M. K. Benhaoua, A. E. H. Benyamina, T. Djeradi, P. Boulet

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In this paper, we propose adaptive routing that considers the routing of communications in order to optimize the overall performance. The routing technique uses a newly proposed Algorithm to route communications between the tasks. The routing we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed routing approach provides significant performance improvements when compared to those using static routing.

Keywords: multi-processor systems-on-chip (mpsocs), network-on-chip (noc), heterogeneous architectures, adaptive routin

Procedia PDF Downloads 375

Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

Procedia PDF Downloads 190

Authors: C. C. Egwuonwu, N. A. A. Okereke, K. O. Chilakpu, S. O. Ohanyere

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In this study, initial soil strength indices (qu) and stress-strain characteristics, namely failure strain (ϵf), area under the stress-strain curve up to failure (Is) and stress-strain modulus between no load and failure (Es) were investigated as potential indicators for characterizing the erosion resistance of two compacted soils, namely sandy clay loam (SCL) and clay loam (CL) in some selected sites in Enugu State, Nigeria. The unconfined compressive strength (used in obtaining strength indices) and stress-strain measurements were obtained as a function of moisture content in percentage (mc %) and dry density (γd). Test were conducted over a range of 8% to 30% moisture content and 1.0 g/cm3 to 2.0 g/cm3 dry density at applied loads of 20, 40, 80, 160 and 320 kPa. Based on the results, it was found out that initial soil strength alone was not a good indicator of erosion resistance. For instance, in the comparison of exponents of mc% and γd for jet index or erosion resistance index (Ji) and the strength measurements, qu and Es agree in signs for mc%, but are opposite in signs for γd. Therefore, there is an inconsistency in exponents making it difficult to develop a relationship between the strength parameters and Ji for this data set. In contrast, the exponents of mc% and γd for Ji and ϵf and Is are opposite in signs, there is potential for an inverse relationship. The measured stress-strain characteristics, however, appeared to have potential in providing useful information on erosion resistance. The models developed for the prediction of the extent or the susceptibility of soils to erosion and subjected to sensitivity test on some selected sites achieved over 90% efficiency in their functions.

Keywords: characterization of erodibility, selected sites in Enugu state, soil strength, stress-strain indices

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Authors: Gyumin Hwang, Jihong Lee

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This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1 m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: chirp spread spectrum, indoor localization, pattern-matching, time of arrival, multi-path, mahalanobis distance, reception rate, simultaneous localization and mapping, laser range finder

Procedia PDF Downloads 244

Authors: Noura El-Ahmady El-Naggar

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Among the antitumour drugs, bacterial enzyme L-asparaginase has been employed as the most effective chemotherapeutic agent in pediatric oncotherapy especially for acute lymphoblastic leukemia. Glutaminase free L-asparaginase producing actinomycetes were isolated from soil samples collected from Egypt. Among them, a potential culture, strain NEAE-119, was selected and identified on the basis of morphological, cultural, physiological and biochemical properties, together with 16S rDNA sequence as Streptomyces olivaceus NEAE-119 and sequencing product(1509 bp) was deposited in the GenBank database under accession number KJ200342. The optimization of different process parameters for L-asparaginase production by Streptomyces olivaceus NEAE-119 using Plackett–Burman experimental design and response surface methodology was carried out. Fifteen nutritional variables (temperature, pH, incubation time, inoculum size, inoculum age, agitation speed, dextrose, starch, L-asparagine, KNO3, yeast extract, K2HPO4, MgSO4.7H2O, NaCl and FeSO4. 7H2O) were screened using Plackett–Burman experimental design. The most positive significant independent variables affecting enzyme production (temperature, inoculum age and agitation speed) were further optimized by the central composite face-centered design -response surface methodology. As a result, a medium of the following formula is the optimum for producing an extracellular L-asparaginase in the culture filtrate of Streptomyces olivaceus NEAE-119: Dextrose 3g, starch 20g, L-asparagine 10g, KNO3 1g, K2HPO4 1g, MgSO4.7H2O 0.1g, NaCl 0.1g, pH 7, temperature 37°C, agitation speed 200 rpm/min, inoculum size 4%, v/v, inoculum age 72 h and fermentation period 5 days.

Keywords: Streptomyces olivaceus NEAE-119, glutaminase free L-asparaginase, production, Plackett-Burman design, central composite face-centered design, 16S rRNA, scanning electron microscope

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Authors: D. Madhushanka, Y. Liu, H. C. Fernando

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Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

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Authors: Seon-Ho Yoon, Jin-Young Choi, Dong-Jun Won

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This paper presents hierarchical operation strategies which are minimizing operation error between day ahead operation plan and real time operation. Operating power systems between centralized and decentralized approaches can be represented as hierarchical control scheme, featured as primary control, secondary control and tertiary control. Primary control is known as local control, featuring fast response. Secondary control is referred to as microgrid Energy Management System (EMS). Tertiary control is responsible of coordinating the operations of multi-microgrids. In this paper, we formulated 3 stage microgrid operation strategies which are similar to hierarchical control scheme. First stage is to set a day ahead scheduled output power of Battery Energy Storage System (BESS) which is only controllable source in microgrid and it is optimized to minimize cost of exchanged power with main grid using Particle Swarm Optimization (PSO) method. Second stage is to control the active and reactive power of BESS to be operated in day ahead scheduled plan in case that State of Charge (SOC) error occurs between real time and scheduled plan. The third is rescheduling the system when the predicted error is over the limited value. The first stage can be compared with the secondary control in that it adjusts the active power. The second stage is comparable to the primary control in that it controls the error in local manner. The third stage is compared with the secondary control in that it manages power balancing. The proposed strategies will be applied to one of the buildings in Electronics and Telecommunication Research Institute (ETRI). The building microgrid is composed of Photovoltaic (PV) generation, BESS and load and it will be interconnected with the main grid. Main purpose of that is minimizing operation cost and to be operated in scheduled plan. Simulation results support validation of proposed strategies.

Keywords: Battery Energy Storage System (BESS), Energy Management System (EMS), Microgrid (MG), Particle Swarm Optimization (PSO)

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Authors: S. Bayona, J. Nunez, D. Paez, C. Diaz

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The application of Lean manufacturing tools continues to be an effective solution for increasing productivity, reducing costs and eliminating waste in the manufacture of goods and services. This article analyzes the production process of a hot asphalt manufacturing company from an administrative and technical perspective. Three main phases were analyzed, the first phase was related to the determination of the risk priority number of the main operations in asphalt mix production process by an FMEA (Failure Mode Effects Analysis), in the second phase the Value Stream Mapping (VSM) of the production line was performed and in the third phase a SWOT (Strengths, Weaknesses Opportunities, Threats) matrix was constructed. Among the most valued failure modes were the lack training of workers in occupational safety and health issues, the lack of signaling and classification of granulated material, and the overweight of vehicles loaded. The analysis of the results in the three phases agree on the importance of training operational workers, improve communication with external actors in order to minimize delays in material orders and strengthen control suppliers.

Keywords: asphalt, lean manufacturing, productivity, process

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Authors: D. Henninger, A. Zopey, T. Ihde, C. Mehring

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The dynamic performance of a 4-way solenoid operated hydraulic spool valve has been analyzed by means of a one-dimensional modeling approach capturing flow, magnetic and fluid forces, valve inertia forces, fluid compressibility, and damping. Increased model accuracy was achieved by analyzing the detailed three-dimensional electromagnetic behavior of the solenoids and flow behavior through the spool valve body for a set of relevant operating conditions, thereby allowing the accurate mapping of flow and magnetic forces on the moving valve body, in lieu of representing the respective forces by lower-order models or by means of simplistic textbook correlations. The resulting high-fidelity one-dimensional model provided the basis for specific and timely design modification eliminating experimentally observed valve oscillations.

Keywords: dynamic performance model, high-fidelity model, 1D-3D decoupled analysis, solenoid-operated hydraulic servo valve, CFD and electromagnetic FEA

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Authors: Hedi Dghim, Ahmed El-Naggar, Istvan Erlich

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Power electronic converters are being introduced in low voltage (LV) grids at an increasingly rapid rate due to the growing adoption of power electronic-based home appliances in residential grid. Photovoltaic (PV) systems are considered one of the potential installed renewable energy sources in distribution power systems. This trend has led to high distortion in the supply voltage which consequently produces harmonic currents in the network and causes an inherent voltage unbalance. In order to investigate the effect of harmonic distortions, a case study of a typical LV grid configuration with high penetration of 3-phase and 1-phase rooftop mounted PV from southern Germany was first considered. Electromagnetic transient (EMT) simulations were then carried out under the MATLAB/Simulink environment which contain detailed models for power electronic-based loads, ohmic-based loads as well as 1- and 3-phase PV. Note that, the switching patterns of the power electronic circuits were considered in this study. Measurements were eventually performed to analyze the distortion levels when PV operating under different solar irradiance. The characteristics of the load-side harmonic impedances were analyzed, and their harmonic contributions were evaluated for different distortion levels. The effect of the high penetration of PV on the harmonic distortion of both positive and negative sequences was also investigated. The simulation results are presented based on case studies. The current distortion levels are in agreement with relevant standards, otherwise the Total Harmonic Distortion (THD) increases under low PV power generation due to its inverse relation with the fundamental current.

Keywords: harmonic distortion analysis, power quality, PV systems, residential distribution system

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Authors: Salma Kaouthar Letaief

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This article investigates the experience of diaspora in the writings of Algerian diasporic writers, namely: Leila Sebbar’s Silence on the Shores (2000), Keltoum Staali’ December’s Mimosa (2012). The study discusses the collective trauma of violence in Algeria and overseas. The experience of displacement of the characters to an alien territory compel their journey with issues related to nostalgia, identity crisis, alienation, racism, and in-betweeness. The focus in this research is, thus, on Algerian immigrants’ experience in the host country and their psychological conflicts. The theories Multiculturalism and Psychoanalysis are used to analyse the novels in this paper. While Multiculturalism examines how characters negotiate and navigate their identities in multicultural settings, Psychoanalysis enables the analysis of how characters in diasporic novels grapple with issues of identity, belonging, and self-discovery. Hence, interweaving multiculturalism and psychoanalysis provides an interdisciplinary framework that addresses both the socio-cultural and psychological aspects of the diasporic experience. Accordingly, this paper is an attempt to examine the diasporic experience and cultural dialectics.

Keywords: diaspora, algerian diasporic writers, trauma, algeria, displacement, identity crisis, cultural dialects

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Authors: A. S. Gorobtsov, A. S. Polyanina, A. E. Andreev

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The movement of points feet of the anthropomorphous robot in space occurs along some stable trajectory of a known form. A large number of modifications to the methods of control of biped robots indicate the fundamental complexity of the problem of stability of the program trajectory and, consequently, the stability of the control for the deviation for this trajectory. Existing gait generators use piecewise interpolation of program trajectories. This leads to jumps in the acceleration at the boundaries of sites. Another interpolation can be realized using differential equations with fractional derivatives. In work, the approach to synthesis of generators of program trajectories is considered. The resulting system of nonlinear differential equations describes a smooth trajectory of movement having rectilinear sites. The method is based on the theory of an asymptotic stability of invariant sets. The stability of such systems in the area of localization of oscillatory processes is investigated. The boundary of the area is a bounded closed surface. In the corresponding subspaces of the oscillatory circuits, the resulting stable limit cycles are curves having rectilinear sites. The solution of the problem is carried out by means of synthesis of a set of the continuous smooth controls with feedback. The necessary geometry of closed trajectories of movement is obtained due to the introduction of high-order nonlinearities in the control of stabilization systems. The offered method was used for the generation of trajectories of movement of point’s feet of the anthropomorphous robot. The synthesis of the robot's program movement was carried out by means of the inverse method.

Keywords: control, limits cycle, robot, stability

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Authors: Adam J. Bowen

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Abstract— Should robots have rights or legal protections. Often debates concerning whether robots and AI should be afforded rights focus on conditions of personhood and the possibility of future advanced forms of AI satisfying particular intrinsic cognitive and moral attributes of rights-holding persons. Such discussions raise compelling questions about machine consciousness, autonomy, and value alignment with human interests. Although these are important theoretical concerns, especially from a future design perspective, they provide limited guidance for addressing the moral and legal standing of current and near-term AI that operate well below the cognitive and moral agency of human persons. Robots and AI are already being pressed into service in a wide range of roles, especially in healthcare and biomedical contexts. The design and large-scale implementation of robots in the context of core societal institutions like healthcare systems continues to rapidly develop. For example, we bring them into our homes, hospitals, and other care facilities to assist in care for the sick, disabled, elderly, children, or otherwise vulnerable persons. We enlist surgical robotic systems in precision tasks, albeit still human-in-the-loop technology controlled by surgeons. We also entrust them with social roles involving companionship and even assisting in intimate caregiving tasks (e.g., bathing, feeding, turning, medicine administration, monitoring, transporting). There have been advances to enable severely disabled persons to use robots to feed themselves or pilot robot avatars to work in service industries. As the applications for near-term AI increase and the roles of robots in restructuring our biomedical practices expand, we face pressing questions about the normative implications of human-robot interactions and collaborations in our collective worldmaking, as well as the moral and legal status of robots. This paper argues that robots operating in public and private spaces be afforded some protections as either moral patients or legal agents to establish prohibitions on robot abuse, misuse, and mistreatment. We already implement robots and embed them in our practices and institutions, which generates a host of human-to-machine and machine-to-machine relationships. As we interact with machines, whether in service contexts, medical assistance, or home health companions, these robots are first encountered in relationship to us and our respective roles in the encounter (e.g., surgeon, physical or occupational therapist, recipient of care, patient’s family, healthcare professional, stakeholder). This proposal aims to outline a framework for establishing limiting factors and determining the extent of moral or legal protections for robots. In doing so, it advocates for a relational approach that emphasizes the priority of mapping the complex contextually sensitive roles played and the relations in which humans and robots stand to guide policy determinations by relevant institutions and authorities. The relational approach must also be technically informed by the intended uses of the biomedical technologies in question, Design History Files, extensive risk assessments and hazard analyses, as well as use case social impact assessments.

Keywords: biomedical robots, robot ethics, robot laws, human-robot interaction

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Authors: A. Hol

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21^st century brought waves of business and industry eTransformations. The impact of change is also being seen in education. To identify the extent of this, scenario analysis methodology was utilised with the aim to assess business transformations across industry sectors ranging from craftsmanship, medicine, finance and manufacture to innovations and adoptions of new technologies and business models. Firstly, scenarios were drafted based on the current eTransformation models and its dimensions. Following this, eTransformation framework was utilised with the aim to derive the key eTransformation parameters, the essential characteristics that have enabled eTransformations across the sectors. Following this, identified key parameters were mapped to the transforming domain-education. The mapping assisted in deriving a cognitive eTransformation framework for education sector. The framework highlights the importance of context and the notion that education today needs not only to deliver content to students but it also needs to be able to meet the dynamically changing demands of specific student and industry groups. Furthermore, it pinpoints that for such processes to be supported, specific technology is required, so that instant, on demand and periodic feedback as well as flexible, dynamically expanding study content can be sought and received via multiple education mediums.

Keywords: education sector, business transformation, eTransformation model, cognitive model, cognitive systems, eTransformation

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Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: Hussaini Bala

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There are different opinions in the literature on the relationship between Audit Committee characteristics and earnings management. The mix of opinions makes the direction of their relationship ambiguous. This study investigated the relationship between Audit Committee characteristics and earnings management of listed food and beverages Firms in Nigeria. The study covered the period of six years from 2007 to 2012. Data for the study were extracted from the Firms’ annual reports and accounts. After running the OLS regression, a robustness test was conducted for the validity of statistical inferences. The dependent variable was generated using two steps regression in order to determine the discretionary accrual of the sample Firms. Multiple regression was employed to run the data of the study using Random Model. The results from the analysis revealed a significant association between audit committee characteristics and earnings management of the Firms. While audit committee size and committees’ financial expertise showed an inverse relationship with earnings management, committee’s independence, and frequency of meetings are positively and significantly related to earnings management. In line with the findings, the study recommended among others that listed food and beverages Firms in Nigeria should strictly comply with the provision of Companies and Allied Matters Act (CAMA) and SEC Code of Corporate Governance on the issues regarding Audit Committees. Regulators such as SEC should increase the minimum number of Audit Committee members with financial expertise and also have a statutory position on the maximum number of Audit Committees meetings, which should not be greater than four meetings in a year as SEC code of corporate governance is silent on this.

Keywords: audit committee, earnings management, listed Food and beverages size, leverage, Nigeria

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