Search results for: parallel data mining

Authors: Gerardo Sanjuan Sanjuan, Ángel Enrique Chavéz Castellanos

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The knowledge of the rheological behavior of partially solidified metal alloy is an important issue when modeling and simulation of die filling in semisolid processes. Many experiments for like steady state, the step change in shear rate tests, shear stress ramps have been carried out leading that semi-solid alloys exhibit shear thinning, thixotropic behavior and yield stress. More advanced investigation gives evidence some viscoelastic features can be observed. The viscoelastic properties of materials are determinate by transient or dynamic methods; unfortunately, sparse information exists about oscillation experiments. The aim of this present work is to use small amplitude oscillatory tests for knowledge properties such as G´ and G´´. These properties allow providing information about materials structure. For this purpose, we investigated tin-lead alloy (Sn-15%Pb) which exhibits a similar microstructure to aluminum alloys and is the classic alloy for semisolid thixotropic studies. The experiments were performed with parallel plates rheometer AR-G2. Initially, the liquid alloy is cooled down to the semisolid range, a specific temperature to guarantee a constant fraction solid. Oscillation was performed within the linear viscoelastic regime with a strain sweep. So, the loss modulus G´´, the storage modulus G´ and the loss angle (δ) was monitored. In addition a frequency sweep at a strain below the critical strain for characterized its structure. This provides more information about the interactions among solid particles on a liquid matrix. After testing, the sample was removed then cooled, sectioned and examined metallographically. These experiments demonstrate that the viscoelasticity is sensitive to the solid fraction, and is strongly influenced by the shape and size of particles solid.

Keywords: rheology, semisolid alloys, thixotropic, viscoelasticity

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Authors: Soudeh Tabashi, Soudabeh Fazeli Dehkordy, Masood Movahedi, Nasrin Behniafard

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Introduction: Food allergy has increased in three last decades. Since wheat is one of the major constituents of daily meal in many regions throughout the world, wheat allergy is one of the most important allergies ranking among the 8 most common types of food allergies. Our information about epidemiology and etiology of food allergies are limited. Therefore, in this study we sought to evaluate the symptoms and laboratory findings in children with wheat allergy. Materials and methods: There were 23 patients aged up to 18 with the diagnosis of IgE mediated wheat allergy that were included enrolled in this study. Using a questionnaire .we collected their information and organized them into 4 groups categories of: demographic data identification, signs and symptoms, comorbidities, and laboratory data. Then patients were followed up for 6 month and their lab data were compared together. Results: Most of the patients (82%) presented the symptoms of wheat allergy in the first year of their life. The skin and the respiratory system were the most commonly involved organs with an incidence of 86% and 78% respectively. Most of the patients with wheat allergy were also sensitive to the other type of foods and their sensitivity to egg were most common type (47%). in 57% of patients, IgE levels were decreased during the 6 month follow-up period. Conclusion: We do not have enough information about data on epidemiology and response to therapy of wheat allergy and to best of our knowledge no study has addressed this issue in Iran so far. This study is the first source of information about IgE mediated wheat allergy in Iran and It can provide an opening for future studies about wheat allergy and its treatments.

Keywords: wheat allergy, food allergy, IgE, food allergy

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Authors: J. H. Boonzaaier, A. C. Brent

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South Africa, a water scarce country, experiences the phenomenon that its life supporting natural water resources is seriously threatened by the users that are totally dependent on it. South Africa is globally applauded to have of the best and most progressive water laws and policies. There are however growing concerns regarding natural water resource quality deterioration and a critical void in the management of natural resources and compliance to policies due to increasing institutional uncertainties and failures. These are in accordance with concerns of many South African researchers and practitioners that call for a change in paradigm from talk to practice and a more constructive, practical approach to governance challenges in the management of water resources. A qualitative theory-building case study through longitudinal action research was conducted from 2014 to 2017. The research assessed whether a strategic positioned institutional agent can be parlayed to facilitate and execute WRM on catchment level by engaging multiple stakeholders in a polycentric setting. Through a critical realist approach a distinction was made between ex ante self-deterministic human behaviour in the realist realm, and ex post governance-management in the constructivist realm. A congruence analysis, including Toulmin’s method of argumentation analysis, was utilised. The study evaluated the unique case of a self-steering local water management institution, the Impala Water Users Association (WUA) in the Pongola River catchment in the northern part of the KwaZulu-Natal Province of South Africa. Exploiting prevailing water resource threats, it expanded its ancillary functions from 20,000 to 300,000 ha. Embarking on WRM activities, it addressed natural water system quality assessments, social awareness, knowledge support, and threats, such as: soil erosion, waste and effluent into water systems, coal mining, and water security dimensions; through structured engagement with 21 different catchment stakeholders. By implementing a proposed polycentric governance-management model on a catchment scale, the WUA achieved to fill the void. It developed a foundation and capacity to protect the resilience of the natural environment that is critical for freshwater resources to ensure long-term water security of the Pongola River basin. Further work is recommended on appropriate statutory delegations, mechanisms of sustainable funding, sufficient penetration of knowledge to local levels to catalyse behaviour change, incentivised support from professionals, back-to-back expansion of WUAs to alleviate scale and cost burdens, and the creation of catchment data monitoring and compilation centres.

Keywords: institutional agent, water governance, polycentric water resource management, water resource management

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Authors: Sizar Abed Mohammed, Zahraa Ghazi Sadeeq

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The use of the classic method, least squares (OLS) to estimate the linear regression parameters, when they are available assumptions, and capabilities that have good characteristics, such as impartiality, minimum variance, consistency, and so on. The development of alternative statistical techniques to estimate the parameters, when the data are contaminated with outliers. These are powerful methods (or resistance). In this paper, three of robust methods are studied, which are: Maximum likelihood type estimate M-estimator, Modified Maximum likelihood type estimate MM-estimator and Least Trimmed Squares LTS-estimator, and their results are compared with OLS method. These methods applied to real data taken from Duhok company for manufacturing furniture, the obtained results compared by using the criteria: Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Sum of Absolute Error (MSAE). Important conclusions that this study came up with are: a number of typical values detected by using four methods in the furniture line and very close to the data. This refers to the fact that close to the normal distribution of standard errors, but typical values in the doors line data, using OLS less than that detected by the powerful ways. This means that the standard errors of the distribution are far from normal departure. Another important conclusion is that the estimated values of the parameters by using the lifeline is very far from the estimated values using powerful methods for line doors, gave LTS- destined better results using standard MSE, and gave the M- estimator better results using standard MAPE. Moreover, we noticed that using standard MSAE, and MM- estimator is better. The programs S-plus (version 8.0, professional 2007), Minitab (version 13.2) and SPSS (version 17) are used to analyze the data.

Keywords: Robest, LTS, M estimate, MSE

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Authors: Ayan Giri, Lukaranjan Phukan, Shantanu Karmakar

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Structure and tectonics play a vital role in ore genesis and deposition. The existence of a swelling structure below the current level of a mine leads to the discovery of ores below some permeant developments of the mine. The discovery and the extraction of the ore body are very critical to sustain the business requirement of the mine. The challenge was to extract the ore without hampering the global stability of the mine. In order to do so, different mining options were considered and analysed by numerical modelling in FLAC3d software. The constitutive model prepared for this simulation is the improved unified constitutive model, which can better and more accurately predict the stress-strain relationships in a continuum model. The IUCM employs the Hoek-Brown criterion to determine the instantaneous Mohr-Coulomb parameters cohesion (c) and friction (ɸ) at each level of confining stress. The extra swelled part can be dimensioned as north-south strike width 50m, east-west strike width 50m. On the north side, already a stope (P1) is excavated of the dimension of 25m NS width. The different options considered were (a) Open stoping of extraction of southern part (P0) of 50m to the full extent, (b) Extraction of the southern part of 25m, then filling of both the primaries and extraction of secondary (S0) 25m in between. (c) Extraction of the southern part (P0) completely, preceded by backfill and modify the design of the secondary (S0) for the overall stability of the permanent excavation above the stoping.

Keywords: extraction, IUCM, FLAC 3D, stoping, tectonics

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Authors: Soha A. Bahanshal, Byung G. Kim

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Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: Farzaneh Khorram

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This paper endeavors to construct a block model to assess grinding energy consumption (CCE) and pinpoint blocks with the highest potential for energy usage during the grinding process within a specified region. Leveraging geostatistical techniques, particularly joint estimation, or simulation, based on geometallurgical data from various mineral processing stages, our objective is to forecast CCE across the study area. The dataset encompasses variables obtained from 2754 drill samples and a block model comprising 4680 blocks. The initial analysis encompassed exploratory data examination, variography, multivariate analysis, and the delineation of geological and structural units. Subsequent analysis involved the assessment of contacts between these units and the estimation of CCE via cokriging, considering its correlation with SPI. The selection of blocks exhibiting maximum CCE holds paramount importance for cost estimation, production planning, and risk mitigation. The study conducted exploratory data analysis on lithology, rock type, and failure variables, revealing seamless boundaries between geometallurgical units. Simulation methods, such as Plurigaussian and Turning band, demonstrated more realistic outcomes compared to cokriging, owing to the inherent characteristics of geometallurgical data and the limitations of kriging methods.

Keywords: geometallurgy, multivariate analysis, plurigaussian, turning band method, cokriging

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Authors: Alan C. Lin, Tzu-Kuan Lin, Tsong Der Lin

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This paper proposes a new method to find the equations of transformation matrix for the rotation angles of the two rotational axes and the coordinates of the three linear axes of an orthogonal multi-axis milling machine. This approach provides intuitive physical meanings for rotation angles of multi-axis machines, which can be used to evaluate the accuracy of the conversion from CL data to NC data.

Keywords: CAM, multi-axis milling machining, transformation matrix, rotation angles

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Authors: Manisha Mukherjee, Diptarka Saha

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Reliable forecasts of univariate time series data are often necessary for several contexts. ARIMA models are quite popular among practitioners in this regard. Hence, choosing correct parameter values for ARIMA is a challenging yet imperative task. Thus, a stepwise algorithm is introduced to provide automatic and robust estimates for parameters (p; d; q)(P; D; Q) used in seasonal ARIMA models. This process is focused on improvising the overall quality of the estimates, and it alleviates the problems induced due to the unidimensional nature of the methods that are currently used such as auto.arima. The fast and automated search of parameter space also ensures reliable estimates of the parameters that possess several desirable qualities, consequently, resulting in higher test accuracy especially in the cases of noisy data. After vigorous testing on real as well as simulated data, the algorithm doesn’t only perform better than current state-of-the-art methods, it also completely obviates the need for human intervention due to its automated nature.

Keywords: time series, ARIMA, auto.arima, ARIMA parameters, forecast, R function

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Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

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Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

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Authors: Raghavi Janaswamy, Saraswathi K. Vasudev

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Music is ubiquitous in human lives. Ever since the fetus hears the sound inside the mother’s womb and later upon birth, the baby experiences alluring sounds, the curiosity of learning emanates and evokes exploration. Music is an education than mere entertainment. The intricate balance between music, education, and entertainment has well been recognized by the scientific community and is being explored as a viable tool to understand and improve human cognition. There are seven basic swaras (notes) Sa, Ri, Ga, Ma, Pa, Da, and Ni in the Carnatic music system that are analogous to C, D, E, F, G, A, and B of the western system. The Carnatic music builds on the conscious use of microtones, gamakams (oscillation), and rendering styles that evolved over centuries and established its stance. The complex but erudite raga system has been designed with elaborate experiments on srutis (musical sounds) and human perception abilities. In parallel, ‘rasa’- the emotions evoked by certain srutis and hence the ragas been solidified along with the power of language in combination with the musical sounds. The Carnatic music branches out as Kalpita sangeetam (pre-composed music) and Manodharma sangeetam (improvised music). This article explores the Manodharma sangeetam and its subdivisions such as raga alapana, swara kalpana, neraval, and ragam-tanam-pallavi (RTP). The intrinsic mathematical strategies in it’s practice methods toward improvising the music have been explored in detail with concert examples. The techniques on swara weaving for swara kalpana rendering and methods on the alapana development are also discussed at length with an emphasis on the impact on the human cognitive abilities. The articulation of the outlined conscious practice methods not only helps to leave a long-lasting melodic impression on the listeners but also onsets cognitive developments.

Keywords: Carnatic, Manodharmam, music cognition, Alapana

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Authors: Yooseo Pang, Jongwoong Choi, Yong Cho, Yongchae Jeong

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Climate crisis, such as environmental problems related to energy supply, is getting emerged issues, so the use of renewable energy is essentially required to solve these problems, which are mainly managed by the Paris Agreement, the international treaty on climate change. The government of the Republic of Korea announced that the key long-term goal for a low-carbon strategy is “Carbon neutrality by 2050”. It is focused on the role of the internet data centers (IDC) in which large amounts of data, such as artificial intelligence (AI) and big data as an impact of the 4th industrial revolution, are managed. The demand for the cooling system market for IDC was about 9 billion US dollars in 2020, and 15.6% growth a year is expected in Korea. It is important to control the temperature in IDC with an efficient air conditioning system, so hydrothermal energy is one of the best options for saving energy in the cooling system. In order to save energy and optimize the operating conditions, it has been considered to apply ‘the dam deep water air conditioning system. Deep water at a specific level from the dam can supply constant water temperature year-round. It will be tested & analyzed the amount of energy saving with a pilot plant that has 100RT cooling capacity. Also, a target of this project is 1.2 PUE (Power Usage Effectiveness) which is the key parameter to check the efficiency of the cooling system.

Keywords: hydrothermal energy, HVAC, internet data center, free-cooling

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Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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Authors: Atefeh Omidkhah, Mohammadreza Bemanian

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The issue of way-finding earmarks a wide range of literature in architecture and despite the 50 year background of way-finding studies, it still lacks a comprehensive theory for indoor settings. Way-finding has a notable role in emergency evacuation as well. People in the panic situation of a fire emergency need to find the safe egress route correctly and in as minimum time as possible. In this regard the parameters of an appropriate way-finding are mentioned in the evacuation related researches albeit scattered. This study reviews the fire safety related literature to extract a way-finding related framework for architectural purposes of the design of a safe evacuation route. In this regard a research trend review in addition with applied methodological approaches review is conducted. Then by analyzing eight original researches related to way-finding parameters in fire evacuation, main parameters that affect way-finding in emergency situation of a fire incident are extracted and a framework was developed based on them. Results show that the issues related to exit route and emergency evacuation can be chased in task oriented studies of way-finding. This research trend aims to access a high-level framework and in the best condition a theory that has an explanatory capability to define differences in way-finding in indoor/outdoor settings, complex/simple buildings and different building types or transitional spaces. The methodological advances demonstrate the evacuation way-finding researches in line with three approaches that the latter one is the most up-to-date and precise method to research this subject: real actors and hypothetical stimuli as in evacuation experiments, hypothetical actors and stimuli as in agent-based simulations and real actors and semi-real stimuli as in virtual reality environment by adding multi-sensory simulation. Findings on data-mining of 8 sample of original researches in way-finding in evacuation indicate that emergency way-finding design of a building should consider two level of space cognition problems in the time of emergency and performance consequences of them in the built environment. So four major classes of problems in way-finding which are visual information deficiency, confusing layout configuration, improper navigating signage and demographic issues had been defined and discussed as the main parameters that should be provided with solutions in design and interior of a building. In the design phase of complex buildings, which face more reported problem in way-finding, it is important to consider the interior components regarding to the building type of occupancy and behavior of its occupants and determine components that tend to become landmarks and set the architectural features of egress route in line with the directions that they navigate people. Research on topological cognition of environmental and its effect on way-finding task in emergency evacuation is proposed for future.

Keywords: architectural design, egress route, way-finding, fire safety, evacuation

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

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Authors: Runlin Liu, Shilong Li

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China is a mountainous country, with two-thirds of its territory covered by plateaus, hills, and mountains, and nearly half of the cities and towns are distributed in mountainous areas. Compared with the environmental constraints in the development path of cities and towns in the plains, there are heterogeneities in aspects such as spatial characteristics, growth mode, and ecological protection and so on for mountain village and townlets, and the development path of mountain village and townlets has a bidirectional relationship between mountain space and economic growth. Based on classical growth theory, this article explores the two-dimensional coupling relation between space and economy in mountain village and townlets under background of rural rejuvenation. GIS technology is adopted in the study to analyze spatial trends and patterns, economical spatial differentiation characteristics of village and townlets. This powerful tool can also help differentiate and analyze limiting factors and assessment systems in the economic growth of village and townlets under spatial dimension of mountainous space. To make the research more specific, this article selects mountain village and townlets in Southwest China as the object of study; this provides good cases for analyzing parallel coupling mechanism of the duality structure system between economic growth and spatial expansion and discussing the path selection of spatial economic growth of mountain village and towns with multiple constraints. The research results can provide quantitative references for the spatial and economic development paths of mountain villages and towns, which is helpful in realizing efficient and high-quality development mode with equal emphasis on spatial and economic benefits for these type of towns.

Keywords: coupling mechanism, geographic information technology, mountainous town, synergetic development, spatial economy

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Authors: D. Benatiallah, A. Benatiallah, K. Bouchouicha, A. Harouz

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The development and operation of renewable energy known an important development in the world with significant growth potential. Estimate the solar radiation on terrestrial geographic locality is of extreme importance, firstly to choose the appropriate site where to place solar systems (solar power plants for electricity generation, for example) and also for the design and performance analysis of any system using solar energy. In addition, solar radiation measurements are limited to a few areas only in Algeria. Thus, we use theoretical approaches to assess the solar radiation on a given location. The Adrar region is one of the most favorable sites for solar energy use with a medium flow that exceeds 7 kWh / m2 / d and saddle of over 3500 hours per year. Our goal in this work focuses on the creation of a data bank for the given data in the energy field of the Adrar region for the period of the year and the month then the integration of these data into a geographic Information System (GIS) to estimate the solar flux on a location on the map.

Keywords: Adrar, flow, GIS, deposit potential

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Authors: Gaya Bin Noon, Thoko Hanjahanja-Phiri, Laura Xavier Fadrique, Plinio Pelegrini Morita, Hélène Vaillancourt, Jennifer Teague, Tania Donovska

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Active Assisted Living (AAL) refers to systems designed to improve the quality of life, aid in independence, and create healthier lifestyles for care recipients. As the population ages, there is a pressing need for non-intrusive, continuous, adaptable, and reliable health monitoring tools to support aging in place. AAL has great potential to support these efforts with the wide variety of solutions currently available, but insufficient efforts have been made to address concerns arising from the integration of AAL into care. The purpose of this research was to (1) explore the integration of AAL technologies and data into the clinical pathway, and (2) map data access and governance for AAL technology in order to develop standards for use by policy-makers, technology manufacturers, and developers of smart communities for seniors. This was done through four successive research phases: (1) literature search to explore existing work in this area and identify lessons learned; (2) modeling of the continuum of care; (3) adapting a framework for data governance into the AAL context; and (4) interviews with stakeholders to explore the applicability of previous work. Opportunities for standards found in these research phases included a need for greater consistency in language and technology requirements, better role definition regarding who can access and who is responsible for taking action based on the gathered data, and understanding of the privacy-utility tradeoff inherent in using AAL technologies in care settings.

Keywords: active assisted living, aging in place, internet of things, standards

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Tassili, occupying a large area of Algeria, is characterized by a rich vegetative biodiversity to be preserved and managed both in time and space. The management of a large area (case of Tassili), by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information etc.), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Multispectral imaging sensors have been very useful in the last decade in very interesting applications of remote sensing. They can aid in several domains such as the de¬tection and identification of diverse surface targets, topographical details, and geological features. In this work, we try to extract vegetative areas using fusion techniques between data acquired from sensor on-board the Earth Observing 1 (EO-1) satellite and Landsat ETM+ and TM sensors. We have used images acquired over the Oasis of Djanet in the National Park of Tassili in the south of Algeria. Fusion technqiues were applied on the obtained image to extract the vegetative fraction of the different classes of land use. We compare the obtained results in vegetation end member extraction with vegetation indices calculated from both Hyperion and other multispectral sensors.

Keywords: Landsat ETM+, EO1, data fusion, vegetation, Tassili, Algeria

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Authors: Nyaris Pambudiyatno, Asto Buditjahjanto, Eppy Yundra, Arie Wardhono, Eko Hariadi

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Vocational education is part of the national education system that is prepared to produce graduates who have the skills and knowledge according to the needs and requirements required by the job. Vocational Education is a secondary education that prepares students to work in a particular field. The purpose of this study was to analyze and find out the effect of industrial work practice experience and career information on work readiness through work motivation. This type of research is causal research with a quantitative approach. The population in this study was 359 cadets of Aviation Polytechnic Surabaya. While the number of samples calculates using slovin calculations obtained by 189 cadets of Surabaya Aviation Polytechnic. The type of data used is quantitative data with the primary data source. Data collection techniques are by distributing questionnaires. Analysis of this study is with Lisrel. The findings prove that: (1) Industrial Work Experience experience has a positive and significant effect on work motivation; (2) Industrial Work Experience has a positive and significant impact on work readiness; (3) Career information has a positive and significant effect on job readiness; (4) Career information has a positive and significant impact on job readiness; Dan (5) Work motivation has a positive and significant effect on work readiness.

Keywords: career information, increase work readiness, industrial work experience, work motivation

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Authors: Ranajoy Bhattcharyya

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We estimate international product cycles as shifting product spaces by using 1976 to 2010 UN Comtrade data on all differentiated tradable products in all countries. We use a product space approach to identify the representative product baskets of high-, middle and low-income countries and then use these baskets to identify the patterns of change in comparative advantage of countries over time. We find evidence of a product cycle in two senses: First, high-, middle- and low-income countries differ in comparative advantage, and high-income products migrate to the middle-income basket. A similar pattern is observed for middle- and low-income countries. Our estimation of the lag shows that middle-income countries tend to quickly take up the products of high-income countries, but low-income countries take a longer time absorbing these products. Thus, the gap between low- and middle-income countries is considerably higher than that between middle- and high-income nations.

Keywords: product cycle, comparative advantage, representative product basket, ex-post data

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Authors: Jonathan Turner, Julie Doyle, Laura O’Philbin, Dympna O’Sullivan

Abstract:

People living with dementia should be at the centre of decision-making regarding goals for daily living. These goals include basic activities (dressing, hygiene, and mobility), advanced activities (finances, transportation, and shopping), and meaningful activities that promote well-being (pastimes and intellectual pursuits). However, there is limited involvement of people living with dementia in the design of technology to support their goals. A project is described that is co-designing intelligent computer-based support for, and with, people affected by dementia and their carers. The technology will support self-management, empower participation in shared decision-making with carers and help people living with dementia remain healthy and independent in their homes for longer. It includes information from the patient’s care plan, which documents medications, contacts, and the patient's wishes on end-of-life care. Importantly for this work, the plan can outline activities that should be maintained or worked towards, such as exercise or social contact. The authors discuss how to integrate care goal information from such a care plan with data collected from passive sensors in the patient’s home in order to deliver individualized planning and interventions for persons with dementia. A number of scientific challenges are addressed: First, to co-design with dementia patients and their carers computerized support for shared decision-making about their care while allowing the patient to share the care plan. Second, to develop a new and open monitoring framework with which to configure sensor technologies to collect data about whether goals and actions specified for a person in their care plan are being achieved. This is developed top-down by associating care quality types and metrics elicited from the co-design activities with types of data that can be collected within the home, from passive and active sensors, and from the patient’s feedback collected through a simple co-designed interface. These activities and data will be mapped to appropriate sensors and technological infrastructure with which to collect the data. Third, the application of machine learning models to analyze data collected via the sensing devices in order to investigate whether and to what extent activities outlined via the care plan are being achieved. The models will capture longitudinal data to track disease progression over time; as the disease progresses and captured data show that activities outlined in the care plan are not being achieved, the care plan may recommend alternative activities. Disease progression may also require care changes, and a data-driven approach can capture changes in a condition more quickly and allow care plans to evolve and be updated.

Keywords: care goals, decision-making, dementia, self-care, sensors

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Authors: Mohamed H. Khalil

Abstract:

Water is one of the most crucial elements which influence human lives and development. Noteworthy, over the last few years, GIS plays a significant role in optimizing water management systems, especially after exponential developing in this sector. In this context, the Egyptian government initiated an advanced ‘GIS-Web Based System’. This system is efficiently designed to tangibly assist and optimize the complement and integration of data between departments of Call Center, Operation and Maintenance, and laboratory. The core of this system is a unified ‘Data Model’ for all the spatial and tabular data of the corresponding departments. The system is professionally built to provide advanced functionalities such as interactive data collection, dynamic monitoring, multi-user editing capabilities, enhancing data retrieval, integrated work-flow, different access levels, and correlative information record/track. Noteworthy, this cost-effective system contributes significantly not only in the completeness of the base-map (93%), the water network (87%) in high level of details GIS format, enhancement of the performance of the customer service, but also in reducing the operating costs/day-to-day operations (~ 5-10 %). In addition, the proposed system facilitates data exchange between different departments (Call Center, Operation and Maintenance, and laboratory), which allowed a better understanding/analyzing of complex situations. Furthermore, this system reflected tangibly on: (i) dynamic environmental monitor/water quality indicators (ammonia, turbidity, TDS, sulfate, iron, pH, etc.), (ii) improved effectiveness of the different water departments, (iii) efficient deep advanced analysis, (iv) advanced web-reporting tools (daily, weekly, monthly, quarterly, and annually), (v) tangible planning synthesizing spatial and tabular data; and finally, (vi) scalable decision support system. It is worth to highlight that the proposed future plan (second phase) of this system encompasses scalability will extend to include integration with departments of Billing and SCADA. This scalability will comprise advanced functionalities in association with the existing one to allow further sustainable contributions.

Keywords: GIS Web-Based, base-map, water network, decision support system

Procedia PDF Downloads 74

Authors: A. Harrouz, O. Harrouz, A. Benatiallah

Abstract:

This paper is to review the essential definitions, roles, and characteristics of communication of metering system. We discuss measurement, data acquisition, and metrological control of a signal sensor from dynamic metering system. After that, we present control of instruments of metering system of fluid with more detailed discussions to the reference standards.

Keywords: data acquisition, dynamic metering system, reference standards, metrological control

Procedia PDF Downloads 478

Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl

Abstract:

Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Keywords: aerodynamic angles, air data system, flight test, neural network, unmanned aerial vehicle, virtual sensor

Procedia PDF Downloads 207

Authors: Erik Eklund

Abstract:

Mary Kathleen was a purpose-built company town located in northwest Queensland in Australia. It was created to work on a rich uranium deposit discovered in the area in July 1954. The town was complete by 1958, possessing curved streets, modern materials, and a progressive urban planning scheme. Formed in the minds of corporate executives and architects and made manifest in arid zone country between Cloncurry and Mount Isa, Mary Kathleen was a modern marvel in the outback, a town that tamed the wild country of northwest Queensland, or so it seemed. The town was also a product of the Cold War. In the context of a nuclear arms race between the Soviet Union and her allies, and the United States of America (USA) and her Allies, a rapid rush to locate, mine, and process uranium after 1944 led to the creation of uranium towns in Czechoslovakia, Canada, the Soviet Union, USA and Australia of which Mary Kathleen was one such example. Mary Kathleen closed in 1981, and most of the town’s infrastructure was removed. Since then, the town’s ghostly remains have attracted travellers and tourists. Never an officially-sanctioned tourist site, the area has nevertheless become a regular stop for campers and day trippers who have engaged with the site often without formal interpretation. This paper explores the status of this vernacular heritage and asks why it has not gained any official status and what visitors might see in the place despite its uncertain status.

Keywords: uranium mining, planned communities, official heritage, vernacular heritage, Australian history

Procedia PDF Downloads 71

Authors: J. R. Wang, Y. Chiang, W. Y. Li, H. T. Lin, H. C. Chen, C. Shih, S. W. Chen

Abstract:

The dry-storage systems of nuclear power plants (NPPs) in Taiwan have become one of the major safety concerns. There are two steps considered in this study. The first step is the verification of the TRACE by using VSC-17 experimental data. The results of TRACE were similar to the VSC-17 data. It indicates that TRACE has the respectable accuracy in the simulation and analysis of the dry-storage systems. The next step is the application of TRACE in the dry-storage system of Kuosheng NPP (BWR/6). Kuosheng NPP is the second BWR NPP of Taiwan Power Company. In order to solve the storage of the spent fuels, Taiwan Power Company developed the new dry-storage system for Kuosheng NPP. In this step, the dry-storage system model of Kuosheng NPP was established by TRACE. Then, the steady state simulation of this model was performed and the results of TRACE were compared with the Kuosheng NPP data. Finally, this model was used to perform the safety analysis of Kuosheng NPP dry-storage system. Besides, FRAPTRAN was used tocalculate the transient performance of fuel rods.

Keywords: BWR, TRACE, FRAPTRAN, dry-storage

Procedia PDF Downloads 501

Authors: Huie-Wen Lin

Abstract:

This study integrated various teaching factors -based on the idea of a flipped classroom- in a financial management course. The study’s aim was to establish an effective teaching implementation strategy and evaluation mechanism with respect to learning outcomes, which can serve as a reference for the future modification of teaching methods. This study implemented a teaching method in five stages and estimated the learning efficiencies of 22 students (in the teaching scenario and over two semesters). Subsequently, data envelopment analysis (DEA) was used to compare, for each student, between the learning efficiencies before and after participation in the flipped classroom -in the first and second semesters, respectively- to identify the crucial external factors influencing learning efficiency. According to the results, the average overall student learning efficiency increased from 0.901 in the first semester to 0.967 in the second semester, which demonstrate that the flipped classroom approach can improve teaching effectiveness and learning outcomes. The results also revealed a difference in learning efficiency between male and female students.

Keywords: data envelopment analysis, flipped classroom, learning outcome, teaching and learning

Procedia PDF Downloads 139

Authors: J. R. Wang, Y. Chiang, W. S. Hsu, H. C. Chen, S. H. Chen, J. H. Yang, S. W. Chen, C. Shih

Abstract:

In this study, the RASCAL and ALOHA codes are used to establish an analysis methodology for hydrogen fluoride (HF) evaluation. There are three main steps in this study. First, the UF₆ data were collected. Second, one postulated case was analyzed by using the RASCAL and UF₆ data. This postulated case assumes that fire occurring and UF₆ is releasing from a building. Third, the results of RASCAL for HF mass were as the input data of ALOHA. Two postulated cases of HF were analyzed by using ALOHA code and the results of RASCAL. These postulated cases assume fire occurring and HF is releasing with no raining (Case 1) or raining (Case 2) condition. According to the analysis results of ALOHA, the HF concentration of Case 2 is smaller than Case 1. The results can be a reference for the preparing of emergency plans for the release of HF.

Keywords: RASCAL, ALOHA, UF₆, hydrogen fluoride

Procedia PDF Downloads 724