Search results for: motion data acquisition

Authors: Natalia Moreira, Trevor Wood-Harper

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The acceptance of sustainable products by the final consumer is still one of the challenges of the industry, which constantly seeks alternative approaches to successfully be accepted in the global market. A large set of methods and approaches have been discussed and analysed throughout the literature. Considering the current need for sustainable development and the current pace of consumption, the need for a combined solution towards the development of new products became clear, forcing researchers in product development to propose alternatives to the previous standard product development models. This paper presents, through a systemic analysis of the literature on product development, eco-design and consumer involvement, a set of alternatives regarding consumer involvement towards the development of sustainable products and how these approaches could help improve the sustainable industry’s establishment in the general market. The initial findings of the research show that the understanding of the benefits of sustainable behaviour lead to a more conscious acquisition and eventually to the implementation of sustainable change in the consumer. Thus this paper is the initial approach towards the development of new sustainable products using the fashion industry as an example of practical implementation and acceptance by the consumers. By comparing the existing literature and critically analysing it this paper concluded that the consumer involvement is strategic to improve the general understanding of sustainability and its features. The use of consumers and communities has been studied since the early 90s in order to exemplify uses and to guarantee a fast comprehension. The analysis done also includes the importance of this approach for the increase of innovation and ground breaking developments, thus requiring further research and practical implementation in order to better understand the implications and limitations of this methodology.

Keywords: consumer involvement, products development, sustainability, eco-design

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Authors: Richard L. Summers

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The advanced computational analysis of biological systems is becoming increasingly dependent upon an understanding of the information-theoretic structure of the materials, energy and interactive processes that comprise those systems. The stability and survival of these living systems are fundamentally contingent upon their ability to acquire and process the meaning of information concerning the physical state of its biological continuum (biocontinuum). The drive for adaptive system reconciliation of a divergence from steady-state within this biocontinuum can be described by an information metric-based formulation of the process for actionable knowledge acquisition that incorporates the axiomatic inference of Kullback-Leibler information minimization driven by survival replicator dynamics. If the mathematical expression of this process is the Lagrangian integrand for any change within the biocontinuum then it can also be considered as an action functional for the living system. In the direct method of Lyapunov, such a summarizing mathematical formulation of global system behavior based on the driving forces of energy currents and constraints within the system can serve as a platform for the analysis of stability. As the system evolves in time in response to biocontinuum perturbations, the summarizing function then conveys information about its overall stability. This stability information portends survival and therefore has absolute existential meaning for the living system. The first derivative of the Lyapunov energy information function will have a negative trajectory toward a system's steady state if the driving force is dissipating. By contrast, system instability leading to system dissolution will have a positive trajectory. The direction and magnitude of the vector for the trajectory then serves as a quantifiable signature of the meaning associated with the living system’s stability information, homeostasis and survival potential.

Keywords: meaning, information, Lyapunov, living systems

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Authors: Wanlapha Phraibueng, Patrick Sentis, Geraldine Riviere-Giordano

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Corporate Social Responsibility (CSR) initiatives have been widely discussed especially in investor-oriented firms. In contrast, cooperatives pay less attention to CSR because their activities have integrated the responsibility and the solidity of social, economic and environment. On the other hand, by adopting ownership theory and agency theory – cooperatives ignore CSR investment due to unclarified decision control in the governance and the limitation to acquire the capital financed. The unique governance and financial structures in cooperatives lead to the conflict among the stakeholders and long-term investment which have an impact on firm financial performance. As an illustration of cooperatives dilemmas, we address the question of Whether or not cooperatives in term of governance and financial structures are the constraints on implementing CSR policies. We find that the governance and financial structures in large cooperatives are the influence factors which predispose cooperatives to invest on CSR. In contrast, in the startup or small cooperatives, its governance and financial structures are the constraints on implementing CSR policies. We propose the alternative financial structure based on the trade-off between debt and equity which aims to relax the restrictions in cooperatives’ governance and allow cooperatives to acquire the capital financed either from its members or non-members. We suggest that engaging equity as a financial structure induces cooperatives to invest on CSR policies. Alternative financial structure eliminates not only cooperative ownership control problem but also the constraints in capital acquisition. By implementing CSR activities consistent with the alternative financial choice, cooperatives can increase firm’s value and reduce the conflict among their stakeholders.

Keywords: cooperatives, corporate social responsibility, financial, governance

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Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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Authors: Mohammadreza Ashouri, Majid Bayatian

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Analysis of fire data is a way for the implementation of any plan to improve the level of safety in cities. Such an analysis is able to reveal signs of changes in a given period and can be used as a measure of safety. The information of about 66,341 fires (from 2002 to 2012) released by Tehran Safety Services and Fire-Fighting Organization and data on the population and the number of households provided by Tehran Municipality and the Statistical Yearbook of Iran were extracted. Using the data, the fire changes, the rate of injuries, and mortality rate were determined and analyzed. The rate of injuries and mortality rate of fires per one million population of Tehran were 59.58% and 86.12%, respectively. During the study period, the number of fires and fire stations increased by 104.38% and 102.63%, respectively. Most fires (9.21%) happened in the 4th District of Tehran. The results showed that the recorded fire data have not been systematically planned for fire prevention since one of the ways to reduce injuries caused by fires is to develop a systematic plan for necessary actions in emergency situations. To determine a reliable source for fire prevention, the stages, definitions of working processes and the cause and effect chains should be considered. Therefore, a comprehensive statistical system should be developed for reported and recorded fire data.

Keywords: fire statistics, fire analysis, accident prevention, Tehran

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Authors: Nam Don Kim, Jungho Moon, Tae Yun Chung

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This paper proposes an Internet of Things (IoT) based virtualization platform for providing smart tourism services. The virtualization platform provides a consistent access interface to various types of data by naming IoT devices and legacy information systems as pathnames in a virtual file system. In the other words, the IoT virtualization platform functions as a middleware which uses the metadata for underlying collected data. The proposed platform makes it easy to provide customized tourism information by using tourist locations collected by IoT devices and additionally enables to create new interactive smart tourism services focused on the tourist locations. The proposed platform is very efficient so that the provided tourism services are isolated from changes in raw data and the services can be modified or expanded without changing the underlying data structure.

Keywords: internet of things (IoT), IoT platform, serviceplatform, virtual file system (VSF)

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Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

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3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Najib Belhadj Messaoud, Slim Souissi

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The non-linear dynamic behavior of a single stage spur gear reducer is studied in this paper in transient regime. Driving and driver rotors are, respectively, powered by a motor torque Cm and loaded by a resistive torque Cr. They are supported by two identical Active Magnetic Bearings (AMBs). Gear excitation is induced by the motor torque and load variation in addition to the fluctuation of meshing stiff-ness due to the variation of input rotational speed. Three models of AMBs were used with four, six and eight magnets. They are operated by P.D controller and powered by control and bias currents. The dynamic parameters of the AMBs are modeled by stiffness and damping matrices computed by the derivation of the electromagnetic forces. The equations of motion are solved iteratively using Newmark time integration method. In the first part of the study, the model is powered by an electric motor and by a four strokes four cylinders diesel engine in the second part. The numerical results of the dynamic responses of the system come to confirm the significant effect of the transient regime on the dynamic behavior of a gear set, particularly in the case of engine acyclism condition. Results also confirm the influence of the magnet number by AMBs on the dynamic behavior of the system. Indeed, vibrations were more important in the case of gear reducer supported by AMBs with four magnets.

Keywords: motor, stiffness, gear, acyclism, fluctuation, torque

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Authors: Boukhadia Karima

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The fluid mechanics is the study of fluid motion laws and their interaction with solid bodies, this project leads to illustrate this interaction with depth studies and approved by experiments on the wind tunnel TE44, ensuring the efficiency, accuracy and reliability of these tests on a NACA0015 profile. A symmetric NACA0015 was placed in a subsonic wind tunnel, and measurements were made of the pressure on the upper and lower surface of the wing and of the velocity across the vortex trailing downstream from the tip of the wing. The aim of this work is to investigate experimentally the scattered pressure profile in a free airflow and the aerodynamic forces acting on this profile. The addition of around-lateral edge to the wing tip was found to eliminate the secondary vortex near the wing tip, but had little effect on the downstream characteristics of the trailing vortex. The increase in wing lift near the tip because of the presence of the trailing vortex was evident in the surface pressure, but was not captured by circulation-box measurements. The circumferential velocity within the vortex was found to reach free-stream values and produce core rotational speeds. Near the wing, the trailing vortex is asymmetric and contains definite zones where the stream wise velocity both exceeds and falls behind the free-stream value. When referenced to the free stream velocity, the maximum vertical velocity of the vortex is directly dependent on α and is independent of Re. A numerical study was conducted through a CFD code called FLUENT 6.0, and the results are compared with experimental.

Keywords: CFD code, NACA Profile, detachment, angle of incidence, wind tunnel

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Authors: Ivan Balachin, Geanette Polanco, Jiang Xingliang, Hu Qin

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The problem of global warming raised up interest towards renewable energy sources. To reduce cost of wind energy is a challenge. Before building of wind park conditions such as: average wind speed, direction, time for each wind, probability of icing, must be considered in the design phase. Operation values used on the setting of control systems also will depend on mentioned variables. Here it is proposed a procedure to be include in the evaluation of the performance of a wind turbine, based on the amplitude of wind changes, the number of changes and their duration. A generic study case based on actual data is presented. Data analysing techniques were applied to model the power required for yaw system based on amplitude and data amount of wind changes. A theoretical model between time, amplitude of wind changes and angular speed of nacelle rotation was identified.

Keywords: field data processing, regression determination, wind turbine performance, wind turbine placing, yaw system losses

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Authors: Masoud Charkhabi

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We examine trade theory with this motivation. The full set of World Trade Organization data are organized into country-year pairs, each treated as a different entity. Topological Data Analysis reveals that among the 16 region and 240 region-year pairs there exists in fact a distinguishable group of region-period pairs. The generally accepted periods of shifts from dissimilar-dissimilar to similar-similar trade in goods among regions are examined from this new perspective. The period breaks are treated as cumulative and are flexible. This type of all-subsets analysis is motivated from computer science and is made possible with Lossy Compression and Graph Theory. The results question many patterns in similar-similar to dissimilar-dissimilar trade. They also show indications of economic shifts that only later become evident in other economic metrics.

Keywords: econometrics, globalization, network science, topological data, analysis, trade theory, visualization, world trade

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Authors: Candy Chieh Lee

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Objective: The purpose of this study is to investigate the relationship between visual perception and social function in patients with schizophrenia. The specific aims are: 1) To explore performances in visual perception and social function in patients with schizophrenia 2) to examine the correlation between visual perceptual skills and social function in patients with schizophrenia The long-term goal is to be able to provide the most adequate intervention program for promoting patients’ visual perceptual skills and social function, as well as compensatory techniques. Background: Perceptual deficits in schizophrenia have been well documented in the visual system. Clinically, a considerable portion (up to 60%) of schizophrenia patients report distorted visual experiences such as visual perception of motion, color, size, and facial expression. Visual perception is required for the successful performance of most activities of daily living, such as dressing, making a cup of tea, driving a car and reading. On the other hand, patients with schizophrenia usually exhibit psychotic symptoms such as auditory hallucination and delusions which tend to alter their perception of reality and affect their quality of interpersonal relationship and limit their participation in various social situations. Social function plays an important role in the prognosis of patients with schizophrenia; lower social functioning skills can lead to poorer prognosis. Investigations on the relationship between social functioning and perceptual ability in patients with schizophrenia are relatively new but important as the results could provide information for effective intervention on visual perception and social functioning in patients with schizophrenia. Methods: We recruited 50 participants with schizophrenia in the mental health hospital (Taipei City Hospital, Songde branch, Taipei, Taiwan) acute ward. Participants who have signed consent forms, diagnosis of schizophrenia and having no organic vision deficits were included. Participants were administered the test of visual-perceptual skills (non-motor), third edition (TVPS-3) and the personal and social performance scale (PSP) for assessing visual perceptual skill and social function. The assessments will take about 70-90 minutes to complete. Data Analysis: The IBM SPSS 21.0 will be used to perform the statistical analysis. First, descriptive statistics will be performed to describe the characteristics and performance of the participants. Lastly, Pearson correlation will be computed to examine the correlation between PSP and TVPS-3 scores. Results: Significant differences were found between the means of participants’ TVPS-3 raw scores of each subtest with the age equivalent raw score provided by the TVPS-3 manual. Significant correlations were found between all 7 subtests of TVPS-3 and PSP total score. Conclusions: The results showed that patients with schizophrenia do exhibit visual perceptual deficits and is correlated social functions. Understanding these facts of patients with schizophrenia can assist health care professionals in designing and implementing adequate rehabilitative treatment according to patients’ needs.

Keywords: occupational therapy, social function, schizophrenia, visual perception

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Authors: Muhammad Awais Shafique, Eiji Hato, Hideki Yaginuma

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Recently GPS data is used in a lot of studies to automatically reconstruct travel patterns for trip survey. The aim is to minimize the use of questionnaire surveys and travel diaries so as to reduce their negative effects. In this paper data acquired from GPS and accelerometer embedded in smart phones is utilized to predict the mode of transportation used by the phone carrier. For prediction, Support Vector Machine (SVM) and Adaptive boosting (AdaBoost) are employed. Moreover a unique method to improve the prediction results from these algorithms is also proposed. Results suggest that the prediction accuracy of AdaBoost after improvement is relatively better than the rest.

Keywords: accelerometer, AdaBoost, GPS, mode prediction, support vector machine

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Authors: Eric Kumar, Erica Cochran, Zhiang Zhang, Wei Liang, Ronak Mody

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The objective of this article was to create a modelling framework that exposes the marginal costs of shifting workloads across geographically distributed data-centers. Geographical distribution of internet services helps to optimize their performance for localized end users with lowered communications times and increased availability. However, due to the geographical and temporal effects, the physical embodiments of a service's data center infrastructure can vary greatly. In this work, we first identify that the sources of variances in the physical infrastructure primarily stem from local weather conditions, specific user traffic profiles, energy sources, and the types of IT hardware available at the time of deployment. Second, we create a traffic simulator that indicates the IT load at each data-center in the set as an approximator for user traffic profiles. Third, we implement a framework that quantifies the global level energy demands using building energy models and the traffic profiles. The results of the model provide a time series of energy demands that can be used for further life cycle analysis of internet services.

Keywords: data-centers, energy, life cycle, network simulation

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Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

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This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

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Authors: Shiori Ishida, Hiromi Okuno, Hisato Igarashi, Akemi Yamazaki, Hiroko Takahashi

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The purpose of this study was to clarify the differences and similarities regarding the social support of fathers and mothers towards considering increased assistance for the paternity of children with developmental disabilities. Written questionnaires were completed by fathers (n=85) and mothers (n=101) of children using rehabilitation facilities between infancy and 5 years of age. The survey contained multiple-choice questions on four categories: information support (6 items), emotional support (7 items), evaluation support (3 items), and daily living support (3 items). Regarding information support, fathers answered ‘spouse’ as the provider in over 50% of cases for all 6 items, which was significantly different compared with mothers (all p < 0.001). For emotional support, fathers were significantly more likely to get support from the workplace (p < 0.001) and from spouse (p < 0.001). The ‘evaluation support’ did not have significant differences for fathers in all the items, but the most frequent support providers were ‘spouses’. ‘Daily living support’ was significantly different from fathers in the workplace (p < 0.000) in terms of make allowances for work and duties. Thus, it appeared that fathers had fewer social support sources as compared with mothers and limited non-spouse support. The understanding of developmental disabilities, acquisition of methods of rehabilitation, and sources of support might have been inadequately addressed among fathers, which could be a hindrance to the involvement of fathers in the rearing of children with developmental disabilities. On the other hand, we also observed that some fathers were involved in the care of developmentally troubled children while providing mental support for their spouse, cooperating with housework, and adjusting their work life. However, the results on the external and social backgrounds of fathers indicated a necessity for greater empowerment and peer support to improve the paternal care of children with developmental disabilities in the family survey.

Keywords: children with developmental disabilities, family support, father, social support

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Authors: Ahmed M. F. El Shiwi

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Background: Low back pain affects about 60% to 90% of the working-age population in modern industrial society. Myofascial pain syndrome is a condition characterized by muscles shortening with increased tone and associated with trigger points that aggravated with the activity of daily living. Purpose: To examine the effects of magnetic field therapy in patients with lower back myofascial pain syndrome. Methods: Thirty patients were assigned randomly into two groups. Subjects in the experimental group (n=15) with main age of 36.73 (2.52) received traditional physical therapy program (Infrared radiation, ultrasonic, stretching and strengthening exercises for back muscles) as well as magnetic field, and control group (n=15) with main age of 37.27 (2.52) received traditional physical therapy only. The following parameters including pain severity, functional disability and lumbar range of motion (flexion, extension, right side bending, and left side bending) were measured before and after four weeks of treatment. Results: The results showed significant improvement in all parameters in the experimental group compared with those in the control group. Interpretation/Conclusion: By the present date, it is possible to conclude that a magnetic field is effective as a method of treatment for lower back myofascial pain syndrome patients with the parameters used in the present study.

Keywords: magnetic field, lower back pain, myofascial pain syndrome, biological systems engineering

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Authors: Mehdi Khaki, Ehsan Forootan, Joseph Awange, Michael Kuhn

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Terrestrial water storage, as a source of freshwater, plays an important role in human lives. Hydrological models offer important tools for simulating and predicting water storages at global and regional scales. However, their comparisons with 'reality' are imperfect mainly due to a high level of uncertainty in input data and limitations in accounting for all complex water cycle processes, uncertainties of (unknown) empirical model parameters, as well as the absence of high resolution (both spatially and temporally) data. Data assimilation can mitigate this drawback by incorporating new sets of observations into models. In this effort, we use multi-mission satellite-derived remotely sensed observations to improve the performance of World-Wide Water Resources Assessment system (W3RA) hydrological model for estimating terrestrial water storages. For this purpose, we assimilate total water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) and surface soil moisture data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) into W3RA. This is done to (i) improve model estimations of water stored in ground and soil moisture, and (ii) assess the impacts of each satellite of data (from GRACE and AMSR-E) and their combination on the final terrestrial water storage estimations. These data are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) filtering technique over Mississippi Basin (the United States) and Murray-Darling Basin (Australia) between 2002 and 2013. In order to evaluate the results, independent ground-based groundwater and soil moisture measurements within each basin are used.

Keywords: data assimilation, GRACE, AMSR-E, hydrological model, EnSRF

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Authors: Siu-Siu Guo, Qingxuan Shi

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In this paper, single-degree-of-freedom (SDOF) systems to white noise and colored noise excitations are investigated. By expressing colored noise excitation as a second-order filtered white noise process and introducing colored noise as an additional state variable, the equation of motion for SDOF system under colored noise is then transferred artificially to multi-degree-of-freedom (MDOF) system under white noise excitations. As a consequence, corresponding Fokker-Planck-Kolmogorov (FPK) equation governing the joint probabilistic density function (PDF) of state variables increases to 4-dimension (4-D). Solution procedure and computer programme become much more sophisticated. The exponential-polynomial closure (EPC) method, widely applied for cases of SDOF systems under white noise excitations, is developed and improved for cases of systems under colored noise excitations and for solving the complex 4-D FPK equation. On the other hand, Monte Carlo simulation (MCS) method is performed to test the approximate EPC solutions. Two examples associated with Gaussian and non-Gaussian colored noise excitations are considered. Corresponding band-limited power spectral densities (PSDs) for colored noise excitations are separately given. Numerical studies show that the developed EPC method provides relatively accurate estimates of the stationary probabilistic solutions. Moreover, statistical parameter of mean-up crossing rate (MCR) is taken into account, which is important for reliability and failure analysis.

Keywords: filtered noise, narrow-banded noise, nonlinear dynamic, random vibration

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Authors: Abdool Qaiyum Mohabuth

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Transferrable skills are learnt abilities which are mainly acquired when experiencing work. University students have the opportunities to develop the knowledge and aptitude at work when they undertake WBL placement during their studies. There is a range of transferrable skills which students may acquire at their placement settings. Several studies have tried to identify a core set of transferrable skills which students can acquire at their placement settings. However, the different lists proposed have often been criticised for being exhaustive and duplicative. In addition, assessing the achievement of students on practice learning based on the transferrable skills is regarded as being complex and tedious due to the variability of placement settings. No attempt has been made in investigating whether these skills are assessable at practice settings. This study seeks to define a set of generic transferrable skills that can be assessed during WBL practice. Quantitative technique was used involving the design of two questionnaires. One was administered to University of Mauritius students who have undertaken WBL practice and the other was slightly modified, destined to mentors who have supervised and assessed students at placement settings. To obtain a good representation of the student’s population, the sample considered was stratified over four Faculties. As for the mentors, probability sampling was considered. Findings revealed that transferrable skills may be subject to formal assessment at practice settings. Hypothesis tested indicate that there was no significant difference between students and mentors as regards to the application of transferrable skills for formal assessment. A list of core transferrable skills that are assessable at any practice settings has been defined after taking into account their degree of being generic, extent of acquisition at work settings and their consideration for formal assessment. Both students and mentors assert that these transferrable skills are accessible at work settings and require commitment and energy to be acquired successfully.

Keywords: knowledge, skills, assessment, placement, mentors

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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Authors: Snehal Mevada, Darshana Bhatt, Aryan Kalthiya, Neel Parmar, Vishal Baraiya, Dhruvit Bhanderi, Tisha Patel

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In multi-storeyed framed buildings, damage occurring from earthquake ground motion generally initiates at locations of structural weaknesses present in the lateral load-resisting frame. In some cases, these weaknesses may be created by discontinuities in stiffness, mass, plan, and torsion. Such discontinuity between storeys is often associated with sudden variations in the vertical geometric irregularities and plan irregularities. Vertical irregularities are structures with a soft storey that can further be broken down into the different types of irregularities as well as their severity for a more refined assessment tool pushover analysis which is one of the methods available for evaluating building against earthquake loads. So, it is very necessary to analyse and understand the seismic performance of the irregular structure in order to reduce the damage which occurs during an earthquake. In this project, a multi-storey (G+4) RCC building with four irregularities (stiffness, mass, plan, torsion) is studied for earthquake loads using the response spectrum method (dynamic analysis) and STADD PRO. All analyses have been done for seismic zone IV and for Medium Soil. In this study effects of different irregularities are analysed based on storey displacement, storey drift, and storey shear.

Keywords: comparison of regular and irregular structure, dynamic analysis, mass irregularity, plan irregularity, response spectrum method, stiffness irregularity, seismic performance, torsional irregularity, STAAD PRO

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Authors: Chuanzhi Chen, Wenjing Yu

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Parabolic cylindrical deployable antenna has the characteristics of wide cutting width, strong directivity, high gain, and easy automatic beam scanning. While, due to its large size, high flexibility, and strong coupling, the deployment process of parabolic cylindrical deployable antenna presents such problems as unsynchronized deployment speed, large local deformation and discontinuous switching of deployment state. A large deployable parabolic cylindrical antenna is taken as the research object, and the problem of unfolding process instability of cylindrical antenna is studied in the paper, which is caused by multiple factors such as multiple closed loops, elastic deformation, motion friction, and gap collision. Firstly, the multi-flexible system dynamics model of large-scale parabolic cylindrical antenna is established to study the influence of friction and elastic deformation on the stability of large multi-closed loop antenna. Secondly, the evaluation method of antenna expansion stability is studied, and the quantitative index of antenna configuration design is proposed to provide a theoretical basis for improving the overall performance of the antenna. Finally, through simulation analysis and experiment, the development dynamics and stability of large-scale parabolic cylindrical antennas are verified by in-depth analysis, and the principles for improving the stability of antenna deployment are summarized.

Keywords: multibody dynamics, expandable parabolic cylindrical antenna, stability, flexible deformation

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Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell

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A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.

Keywords: crime, narrative, video, neighborhood

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Authors: Nasim Eslamirad, Mahdi Rasoulinezhad, Francesco De Luca, Sadok Ben Yahia, Kimmo Sakari Lylykangas, Francesco Pilla

Abstract:

With the ongoing urbanization, cities face increasing environmental challenges impacting human well-being. To tackle these issues, data-driven approaches in urban analysis have gained prominence, leveraging urban data to promote sustainability. Integrating Machine Learning techniques enables researchers to analyze and predict complex environmental phenomena like Urban Heat Island occurrences in urban areas. This paper demonstrates the implementation of data-driven approach and interpretable Machine Learning algorithms with interpretability techniques to conduct comprehensive data analyses for sustainable urban design. The developed framework and algorithms are demonstrated for Tallinn, Estonia to develop sustainable urban strategies to mitigate urban heat waves. Geospatial data, preprocessed and labeled with UHI levels, are used to train various ML models, with Logistic Regression emerging as the best-performing model based on evaluation metrics to derive a mathematical equation representing the area with UHI or without UHI effects, providing insights into UHI occurrences based on buildings and urban features. The derived formula highlights the importance of building volume, height, area, and shape length to create an urban environment with UHI impact. The data-driven approach and derived equation inform mitigation strategies and sustainable urban development in Tallinn and offer valuable guidance for other locations with varying climates.

Keywords: data-driven approach, machine learning transparent models, interpretable machine learning models, urban heat island effect

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Authors: Ibrahim A. Adeniran, Rui F. Zhu, Man S. Wong

Abstract:

Owing to the insufficiency in the spatial representativeness and continuity of in situ temperature measurements from weather stations (WS), the use of temperature measurement from WS for large-range diurnal analysis in heterogenous landscapes has been limited. This has made the accurate estimation of land surface temperature (LST) from remotely sensed data more crucial. Moreover, the study of dynamic interaction between the atmosphere and the physical surface of the Earth could be enhanced at both annual and diurnal scales by using optimal LST data derived from satellite sensors. The tradeoff between the spatial and temporal resolution of LSTs from satellite’s thermal infrared sensors (TIRS) has, however, been a major challenge, especially when high spatiotemporal LST data are recommended. It is well-known from existing literature that polar satellites have the advantage of high spatial resolution, while geostationary satellites have a high temporal resolution. Hence, this study is aimed at designing a framework for the cross-comparison of LST data from polar and geostationary satellites in a heterogeneous landscape. This could help to understand the relationship between the LST estimates from the two satellites and, consequently, their integration in diurnal LST analysis. Landsat-8 satellite data will be used as the representative of the polar satellite due to the availability of its long-term series, while the Himawari-8 satellite will be used as the data source for the geostationary satellite because of its improved TIRS. For the study area, Hong Kong Special Administrative Region (HK SAR) will be selected; this is due to the heterogeneity in the landscape of the region. LST data will be retrieved from both satellites using the Split window algorithm (SWA), and the resulting data will be validated by comparing satellite-derived LST data with temperature data from automatic WS in HK SAR. The LST data from the satellite data will then be separated based on the land use classification in HK SAR using the Global Land Cover by National Mapping Organization version3 (GLCNMO 2013) data. The relationship between LST data from Landsat-8 and Himawari-8 will then be investigated based on the land-use class and over different seasons of the year in order to account for seasonal variation in their relationship. The resulting relationship will be spatially and statistically analyzed and graphically visualized for detailed interpretation. Findings from this study will reveal the relationship between the two satellite data based on the land use classification within the study area and the seasons of the year. While the information provided by this study will help in the optimal combination of LST data from Polar (Landsat-8) and geostationary (Himawari-8) satellites, it will also serve as a roadmap in the annual and diurnal urban heat (UHI) analysis in Hong Kong SAR.

Keywords: automatic weather station, Himawari-8, Landsat-8, land surface temperature, land use classification, split window algorithm, urban heat island

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Authors: Hassan Abo-Salem, Huang Xiaolin

Abstract:

Background and Purpose: The effectiveness of mirror therapy (MT) has been investigated in acute hemiplegia. The present study examines whether MT, given during chronic stroke, was more effective in promoting motor recovery of the lower extremity and walking speed than standard rehabilitation alone. Methods: The study enrolled 30 patients with chronic stroke. Fifteen patients each were assigned to the treatment group and the control group. All patients received a conventional rehabilitation program for a 4-week period. In addition to this rehabilitation program, patients in the treatment group received mirror therapy for 4 weeks, 5 days a week. Main measures: Passive ankle joint dorsiflexion range of motion, gait speed, Brunnstrom stages of motor recovery, plantarflexor muscle tone by Modified Ashworth Scale. Results: Results: No significant difference was found in the outcome measures among groups before treatment. When compared with standard rehabilitation, mirror therapy improved Ankle ROM, Brunnstrom stages and waking speed (p < 0.05). However, there were no significant differences between two groups on MAS (P > 0.05). Conclusions: Mirror therapy combined with a conventional stroke rehabilitation program enhances lower-extremity motor recovery and walking speed in chronic stroke patients.

Keywords: mirror therapy, stroke, MAS, walking speed

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Authors: Najrullah Khan, Athar Ali Khan

Abstract:

The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Amir Taghizadeh Vahed, Adithya Thaduri

Abstract:

Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

Procedia PDF Downloads 222