Search results for: real-time spatial big data

Authors: Changfeng Fu

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Sustainable urban development has been widely accepted a common sense in the modern urban planning and design. However, the measurement and assessment of urban sustainability, especially the quantitative assessment have been always an issue obsessing planning and design professionals. This paper will present an on-going research on the principles and technologies to develop a quantitative urban sustainability assessment principles and techniques which aim to integrate indicators, geospatial and geo-reference data, and assessment techniques together into a mechanism. It is based on the principles and techniques of geospatial analysis with GIS and statistical analysis methods. The decision-making technologies and methods such as AHP and SMART are also adopted to address overall assessment conclusions. The possible interfaces and presentation of data and quantitative assessment results are also described. This research is based on the knowledge, situations and data sources of UK, but it is potentially adaptable to other countries or regions. The implementation potentials of the mechanism are also discussed.

Keywords: urban sustainability assessment, quantitative analysis, sustainability indicator, geospatial data, big data

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Authors: Hamad Almebayedh, Chuxia Lin, Yu wang

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The environmental impact assessment (EIA) must be improved, assessed, and quality checked for human and environmental health and safety. Soil contamination is expanding, and sites and soil remediation activities proceeding around the word which simplifies the answer “quality soil characterization” will lead to “quality EIA” to illuminate the contamination level and extent and reveal the unknown for the way forward to remediate, countifying, containing, minimizing and eliminating the environmental damage. Spatial interpolation methods play a significant role in decision making, planning remediation strategies, environmental management, and risk assessment, as it provides essential elements towards site characterization, which need to be informed into the EIA. The Innovative 3D soil mapping and soil characterization technology presented in this research paper reveal the unknown information and the extent of the contaminated soil in specific and enhance soil characterization information in general which will be reflected in improving the information provided in developing the EIA related to specific sites. The foremost aims of this research paper are to present novel 3D mapping technology to quality and cost-effectively characterize and estimate the distribution of key soil characteristics in contaminated sites and develop Innovative process/procedure “assessment measures” for EIA quality and assessment. The contaminated site and field investigation was conducted by innovative 3D mapping technology to characterize the composition of petroleum hydrocarbons contaminated soils in a decommissioned oilfield waste pit in Kuwait. The results show the depth and extent of the contamination, which has been interred into a developed assessment process and procedure for the EIA quality review checklist to enhance the EIA and drive remediation and risk assessment strategies. We have concluded that to minimize the possible adverse environmental impacts on the investigated site in Kuwait, the soil-capping approach may be sufficient and may represent a cost-effective management option as the environmental risk from the contaminated soils is considered to be relatively low. This research paper adopts a multi-method approach involving reviewing the existing literature related to the research area, case studies, and computer simulation.

Keywords: quality EIA, spatial interpolation, soil characterization, contaminated site

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Authors: A. Ishag Mohamed, A. A. Rabah

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The objective of this research is to develop a generalized correlation for the prediction of thermal conductivity of n-Alkanes and Alkenes. There is a minority of research and lack of correlation for thermal conductivity of liquids in the open literature. The available experimental data are collected covering the groups of n-Alkanes and Alkenes.The data were assumed to correlate to temperature using Filippov correlation. Nonparametric regression of Grace Algorithm was used to develop the generalized correlation model. A spread sheet program based on Microsoft Excel was used to plot and calculate the value of the coefficients. The results obtained were compared with the data that found in Perry's Chemical Engineering Hand Book. The experimental data correlated to the temperature ranged "between" 273.15 to 673.15 K, with R2 = 0.99.The developed correlation reproduced experimental data that which were not included in regression with absolute average percent deviation (AAPD) of less than 7 %. Thus the spread sheet was quite accurate which produces reliable data.

Keywords: N-Alkanes, N-Alkenes, nonparametric, regression

Procedia PDF Downloads 657

Authors: Ateeth Shetty, K. S. Jayappa, Ratheesh Ramakrishnan, A. S. Rajawat

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Suspended Sediment Concentration (SSC) was estimated for the period of four months (November, 2013 to February 2014) using Oceansat-2 (Ocean Colour Monitor) satellite images to understand the coastal dynamics and regional sediment transport, especially distribution and budgeting in coastal waters. The coastal zone undergoes continuous changes due to natural processes and anthropogenic activities. The importance of the coastal zone, with respect to safety, ecology, economy and recreation, demands a management strategy in which each of these aspects is taken into account. Monitoring and understanding the sediment dynamics and suspended sediment transport is an important issue for coastal engineering related activities. A study of the transport mechanism of suspended sediments in the near shore environment is essential not only to safeguard marine installations or navigational channels, but also for the coastal structure design, environmental protection and disaster reduction. Such studies also help in assessment of pollutants and other biological activities in the region. An accurate description of the sediment transport, caused by waves and tidal or wave-induced currents, is of great importance in predicting coastal morphological changes. Satellite-derived SSC data have been found to be useful for Indian coasts because of their high spatial (360 m), spectral and temporal resolutions. The present paper outlines the applications of state‐of‐the‐art operational Indian Remote Sensing satellite, Oceansat-2 to study the dynamics of sediment transport.

Keywords: suspended sediment concentration, ocean colour monitor, sediment transport, case – II waters

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Authors: Rachida Houssa, Hassan Rhinane, Fadoumo Ali Malouw, Amina Oulmaalem

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Since the early 70s, the Moroccan Atlantic sea was subjected to the pressure of the bottom trawling, one of the most destructive techniques seabed that cause havoc on fishing catch, nonselective, and responsible for more than half of all releases of fish around the world. The present paper aims to map and assess the impact of the activity of the bottom trawling of the Moroccan Atlantic coast. For this purpose, a dataset of thirty years, between 1962 and 1999, from foreign fishing vessels using bottom trawling, has been used and integrated in a GIS. To estimate the extent and the importance of the geographical distribution of the trawling effort, the Moroccan Atlantic area was divided into a grid of cells of 25 km2 (5x5 km). This grid was joined to the effort trawling data, creating a new entity with a table containing spatial overlay grid with the polygon of swept surfaces. This mapping model allowed to quantify the used fishing effort versus time and to generate the trace indicative of trawling efforts on the seabed. Indeed, for a given year, a grid cell may have a swept area equal to 0 (never been touched by the trawl) or 25 km2 (the trawled area is similar to the cell size) or may be 100 km2 indicating that for this year, the scanned surface is four times the cell area. The results show that the total cumulative sum of trawled area is approximately 28,738,326 km2, scattered throughout the Atlantic coast. 95% of the overall trawling effort is located in the southern zone, between 29°N and 20°30'N. Nearly 5% of the trawling effort is located in the northern coastal region, north of 33°N. The center area between 33°N and 29°N is the least swept by Russian commercial vessels because in this region the majority of the area is rocky, and non trawlable.

Keywords: GIS, Moroccan Atlantic Ocean, seabed, trawling

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Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: big data, social networks, sentiment analysis, twitter

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Authors: Ladislav Kristoufek, Helen Susannah Moat, Tobias Preis

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Data on the number of people who have committed suicide tends to be reported with a substantial time lag of around two years. We examine whether online activity measured by Google searches can help us improve estimates of the number of suicide occurrences in England before official figures are released. Specifically, we analyse how data on the number of Google searches for the terms “depression” and “suicide” relate to the number of suicides between 2004 and 2013. We find that estimates drawing on Google data are significantly better than estimates using previous suicide data alone. We show that a greater number of searches for the term “depression” is related to fewer suicides, whereas a greater number of searches for the term “suicide” is related to more suicides. Data on suicide related search behaviour can be used to improve current estimates of the number of suicide occurrences.

Keywords: nowcasting, search data, Google Trends, official statistics

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Authors: Qianqian He, Naian Liu, Xiaodong Xie, Linhe Zhang, Yang Zhang, Weidong Yan

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In the wild, the vegetation layer with exceptionally complex fuel composition and heterogeneous spatial distribution strongly affects the rate of fire spread (ROS) and fire intensity. Clarifying the influence of fuel bed structure on fire spread behavior is of great significance to wildland fire management and prediction. The packing ratio is one of the key physical parameters describing the property of the fuel bed. There is a threshold value of the packing ratio for ROS, but little is known about the controlling mechanism. In this study, to address this deficiency, a series of fire spread experiments were performed across a discrete fuel bed composed of some regularly arranged laser-cut cardboards, with constant wind speed and different packing ratios (0.0125-0.0375). The experiment aims to explore the relative importance of the internal and surface heat transfer with packing ratio. The dependence of the measured ROS on the packing ratio was almost consistent with the previous researches. The data of the radiative and total heat fluxes show that the internal heat transfer and surface heat transfer are both enhanced with increasing packing ratio (referred to as ‘Stage 1’). The trend agrees well with the variation of the flame length. The results extracted from the video show that the flame length markedly increases with increasing packing ratio in Stage 1. Combustion intensity is suggested to be increased, which, in turn, enhances the heat radiation. The heat flux data shows that the surface heat transfer appears to be more important than the internal heat transfer (fuel preheating inside the fuel bed) in Stage 1. On the contrary, the internal heat transfer dominates the fuel preheating mechanism when the packing ratio further increases (referred to as ‘Stage 2’) because the surface heat flux keeps almost stable with the packing ratio in Stage 2. As for the heat convection, the flow velocity was measured using Pitot tubes both inside and on the upper surface of the fuel bed during the fire spread. Based on the gas velocity distribution ahead of the flame front, it is found that the airflow inside the fuel bed is restricted in Stage 2, which can reduce the internal heat convection in theory. However, the analysis indicates not the influence of inside flow on convection and combustion, but the decreased internal radiation of per unit fuel is responsible for the decrease of ROS.

Keywords: discrete fuel bed, fire spread, packing ratio, wildfire

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Authors: Maja Ruzic-Baf, Mirjana Radetic-Paic

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The use of computers by children has many positive aspects, including the development of memory, learning methods, problem-solving skills and the feeling of one’s own competence and self-confidence. Playing on line video games can encourage hanging out with peers having similar interests as well as communication; it develops coordination, spatial relations and presentation. On the other hand, the Internet enables quick access to different information and the exchange of experiences. How kids use computers and what the negative effects of this can be depends on various factors. ICT has improved and become easy to get for everyone. In the past 12 years so many video games has been made even to that level that some of them are free to play. Young people, even some adults, had simply start to forget about the real outside world because in that other, digital world, they have found something that makes them feal more worthy as a man. This article present the use of ICT, forms of behavior and addictions to on line video games. The use of computers by children has many positive aspects, including the development of memory, learning methods, problem-solving skills and the feeling of one’s own competence and self-confidence. Playing on line video games can encourage hanging out with peers having similar interests as well as communication; it develops coordination, spatial relations and presentation. On the other hand, the Internet enables quick access to different information and the exchange of experiences. How kids use computers and what the negative effects of this can be depends on various factors. ICT has improved and become easy to get for everyone. In the past 12 years so many video games has been made even to that level that some of them are free to play. Young people, even some adults, had simply start to forget about the real outside world because in that other, digital world, they have found something that makes them feal more worthy as a man. This article present the use of ICT, forms of behavior and addictions to on line video games.

Keywords: addiction to video games, behaviour, ICT, young people

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Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

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Authors: Sidi M. A. Ghaly, Mohammad O. Khan, Mohammed Shalaby, Khaled A. Al-Snaie

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Electrical capacitance tomography (ECT) is a valuable, non-invasive technique used to monitor multiphase flow processes, especially within industrial pipelines. This study focuses on the design, testing, and performance comparison of ECT sensors configured with 8, 12, and 16 electrodes, aiming to evaluate their effectiveness in imaging accuracy, resolution, and sensitivity. Each sensor configuration was designed to capture the spatial permittivity distribution within a pipeline cross-section, enabling visualization of phase distribution and flow characteristics such as oil and water interactions. The sensor designs were implemented and tested in closed pipes to assess their response to varying flow regimes. Capacitance data collected from each electrode configuration were reconstructed into cross-sectional images, enabling a comparison of image resolution, noise levels, and computational demands. Results indicate that the 16-electrode configuration yields higher image resolution and sensitivity to phase boundaries compared to the 8- and 12-electrode setups, making it more suitable for complex flow visualization. However, the 8 and 12-electrode sensors demonstrated advantages in processing speed and lower computational requirements. This comparative analysis provides critical insights into optimizing ECT sensor design based on specific industrial requirements, from high-resolution imaging to real-time monitoring needs.

Keywords: capacitance tomography, modeling, simulation, electrode, permittivity, fluid dynamics, imaging sensitivity measurement

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Authors: Rahma Saleh Hussein Al Balushi

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Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS department. This paper will describe in detail the current GIS data submission process and the journey for developing it. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, and updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) for excavation permits and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting and data alterations has also contributed to reducing the missing attributes and enhance data quality index of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the years 2017 and year 2022. Overall, concluding that by governance, asset information & GIS department can control the GIS data process; collect, properly record, and manage asset data and information within the OETC network. This control extends to other applications and systems integrated with/related to GIS systems.

Keywords: asset management ISO55001, standard procedures process, governance, CMMS

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Authors: Sajid Abas, Jon Pyo Hong, Jung-Ryun Le, Seungryong Cho

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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: computed tomography, computed laminography, compressive sending, low-dose

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Authors: Joseph Fitoussi, Mohammadali Shirinbayan, Abbas Tcharkhtchi

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Due to material flow during processing, short fiber reinforced composites structures obtained by injection or compression molding generally present strong spatial microstructure variation. On the other hand, quasi-static, dynamic, and fatigue behavior of these materials are highly dependent on microstructure parameters such as fiber orientation distribution. Indeed, because of complex damage mechanisms, SFRC structures design is a key challenge for safety and reliability. In this paper, we propose a micromechanical model allowing prediction of damage behavior of real structures as a function of microstructure spatial distribution. To this aim, a statistical damage criterion including strain rate and fatigue effect at the local scale is introduced into a Mori and Tanaka model. A critical local damage state is identified, allowing fatigue life prediction. Moreover, the multi-scale model is coupled with an experimental intrinsic link between damage under monotonic loading and fatigue life in order to build an abacus giving Tsai-Wu failure criterion parameters as a function of microstructure and targeted fatigue life. On the other hand, the micromechanical damage model gives access to the evolution of the anisotropic stiffness tensor of SFRC submitted to complex thermomechanical loading, including quasi-static, dynamic, and cyclic loading with temperature and amplitude variations. Then, the latter is used to fill out microstructure dependent material cards in finite element analysis for design optimization in the case of complex loading history. The proposed methodology is illustrated in the case of a real automotive component made of sheet molding compound (PSA 3008 tailgate). The obtained results emphasize how the proposed micromechanical methodology opens a new path for the automotive industry to lighten vehicle bodies and thereby save energy and reduce gas emission.

Keywords: short fiber reinforced composite, structural design, damage, micromechanical modelling, fatigue, strain rate effect

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Authors: Tri Wijayanti Septiarini, Agus Maman Abadi, Muhammad Rifki Taufik

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The exchange rate of IDR/USD can be the indicator to analysis Indonesian economy. The exchange rate as a important factor because it has big effect in Indonesian economy overall. So, it needs the analysis data of exchange rate. There is decomposition data of exchange rate of IDR/USD to be frequency and time. It can help the government to monitor the Indonesian economy. This method is very effective to identify the case, have high accurate result and have simple structure. In this paper, data of exchange rate that used is weekly data from December 17, 2010 until November 11, 2014.

Keywords: the exchange rate, fuzzy mamdani, discrete wavelet transforms, fuzzy wavelet

Procedia PDF Downloads 578

Authors: Durhane Wong-Rieger, Kawaldip Sehmi, Nicola Bedlington, Nicole Boice, Tamás Bereczky

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Patient-generated health data should be seen as the expression of the experience of patients, including the outcomes reflecting the impact a treatment or service had on their physical health and wellness. We discuss how the healthcare system can reach a place where digital is a determinant of health - where data is generated by patients and is respected and which acknowledges their contribution to science. We explore the biggest barriers facing this. The International Experience Exchange with Patient Organisation’s Position Paper is based on a global patient survey conducted in Q3 2021 that received 304 responses. Results were discussed and validated by the 15 patient experts and supplemented with literature research. Results are a subset of this. Our research showed patient communities want to influence how their data is generated, shared, and used. Our study concludes that a reasonable framework is needed to protect the integrity of patient data and minimise abuse, and build trust. Results also demonstrated a need for patient communities to have more influence and control over how health data is generated, shared, and used. The results clearly highlight that the community feels there is a lack of clear policies on sharing data.

Keywords: digital health, equitable access, humanise healthcare, patient data

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Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

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Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

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Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: Martin Kleynhans, Margot Soler, Gavin Quibell

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Malawi is one of the world’s poorest nations and consequently, the design of flood risk management infrastructure comes with a different set of challenges. There is a lack of good quality hydromet data, both in spatial terms and in the quality thereof and the challenge in the design of flood risk management infrastructure is compounded by the fact that maintenance is almost completely non-existent and that solutions have to be simple to be effective. Solutions should not require any further resources to remain functional after completion, and they should be resilient. They also have to be cost effective. The Lower Shire Valley of Malawi suffers from frequent flood events. Various flood risk management interventions have been designed across the valley during the course of the Shire River Basin Management Project – Phase I, and due to the data poor environment, indigenous knowledge was relied upon to a great extent for hydrological and hydraulic model calibration and verification. However, indigenous knowledge comes with the caveat that it is ‘fuzzy’ and that it can be manipulated for political reasons. The experience in the Lower Shire valley suggests that indigenous knowledge is unlikely to invent a problem where none exists, but that flood depths and extents may be exaggerated to secure prioritization of the intervention. Indigenous knowledge relies on the memory of a community and cannot foresee events that exceed past experience, that could occur differently to those that have occurred in the past, or where flood management interventions change the flow regime. This complicates communication of planned interventions to local inhabitants. Indigenous knowledge is, for the most part, intuitive, but flooding can sometimes be counter intuitive, and the rural poor may have a lower trust of technology. Due to a near complete lack of maintenance of infrastructure, infrastructure has to be designed with no moving parts and no requirement for energy inputs. This precludes pumps, valves, flap gates and sophisticated warning systems. Designs of dykes during this project included ‘flood warning spillways’, that double up as pedestrian and animal crossing points, which provide warning of impending dangerous water levels behind dykes to residents before water levels that could cause a possible dyke failure are reached. Locally available materials and erosion protection using vegetation were used wherever possible to keep costs down.

Keywords: design of dykes in low-income countries, flood warning spillways, indigenous knowledge, Malawi

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Authors: S. S. Nafee, A. M. Al-Ramady, S. A. Shaheen

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Evaluated nuclear decay data for the 217Po nuclide ispresented in the present work. These data include recommended values for the half-life T1/2, α-, β--, and γ-ray emission energies and probabilities. Decay data from 221Rn α and 217Bi β—decays are presented. Q(α) has been updated based on the recent published work of the Atomic Mass Evaluation AME2012. In addition, the logft values were calculated using the Logft program from the ENSDF evaluation package. Moreover, the total internal conversion electrons has been calculated using Bricc program. Meanwhile, recommendation values or the multi-polarities have been assigned based on recently measurement yield a better intensity balance at the 254 keV and 264 keV gamma transitions.

Keywords: nuclear decay data evaluation, mass evaluation, total converison coefficients, atomic mass evaluation

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Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

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Authors: I. Nyoman Mahayasa Adiputra

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Data in the field of health can be useful for the purposes of data analysis, one example of health data is disease data. Disease data is usually in a geographical plot in accordance with the area. Where the data was collected, in the city of Denpasar, Bali. Disease data report is still published in tabular form, disease information has not been mapped in GIS form. In this research, disease information in Denpasar city will be digitized in the form of a geographic information system with the smallest administrative area in the form of district. Denpasar City consists of 4 districts of North Denpasar, East Denpasar, West Denpasar and South Denpasar. In this research, we use Google fusion table technology for map digitization process, where this technology can facilitate from the administrator and from the recipient information. From the administrator side of the input disease, data can be done easily and quickly. From the receiving end of the information, the resulting GIS application can be published in a website-based application so that it can be accessed anywhere and anytime. In general, the results obtained in this study, divided into two, namely: (1) Geolocation of Denpasar and all of Denpasar districts, the process of digitizing the map of Denpasar city produces a polygon geolocation of each - district of Denpasar city. These results can be utilized in subsequent GIS studies if you want to use the same administrative area. (2) Dengue fever mapping in 2014 and 2015. Disease data used in this study is dengue fever case data taken in 2014 and 2015. Data taken from the profile report Denpasar Health Department 2015 and 2016. This mapping can be useful for the analysis of the spread of dengue hemorrhagic fever in the city of Denpasar.

Keywords: geographic information system, Google fusion table technology, delivery of disease data information, Denpasar city

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Authors: Mitzi S. Brammer

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Given that the cultural make-up of programs of study in institutions of higher learning is becoming increasingly diverse, much has been written about cultural diversity from a university-level perspective. However, there are little data in the way of specific programs and how they address inclusive practices when teaching and working with marginalized populations. This research study aimed to discover baseline knowledge and attitudes of health sciences faculty, instructional staff, and students related to inclusive teaching/learning and interactions. Quantitative data were collected via an anonymous online survey (one designed for students and another designed for faculty/instructional staff) using a web-based program called Qualtrics. Quantitative data were analyzed amongst the faculty/instructional staff and students, respectively, using descriptive and comparative statistics (t-tests). Additionally, some participants voluntarily engaged in a focus group discussion in which qualitative data were collected around these same variables. Collecting qualitative data to triangulate the quantitative data added trustworthiness to the overall data. The research team analyzed collected data and compared identified categories and trends, comparing those data between faculty/staff and students, and reported results as well as implications for future study and professional practice.

Keywords: inclusion, higher education, pedagogy, equity, diversity

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Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

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Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

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Authors: Kalidas Sarma

Abstract:

Fraud is a social problem changing with social change and it has a regional and global impact. Introduction of private domain in higher education along with public institutions has led to commercialization of higher education which encourages unprecedented mushrooming of private institutions resulting in fraudulent activities in higher educational institutions in Assam, India. Presently, fraud has been noticed in in-service promotion, fake entry qualification by teachers in different levels of work-place by using fake master degrees, master of philosophy and doctor of philosophy degree certificates. The aim and objective of the study are to identify grey areas in maintenance of quality in higher educational institutions in Assam and also to draw the contour for planning and implementation. This study is based on both primary and secondary data collected through questionnaire and seeking information through Right to Information Act 2005. In Assam, there are 301 undergraduate and graduate colleges distributed in 27 (Twenty seven) administrative districts with 11000 (Eleven thousand) college teachers. Total 421 (Four hundred twenty one) college teachers from the 14 respondent colleges have been taken for analysis. Data collected has been analyzed by using 'Hypertext Pre-processor' (PhP) application with My Sequel Structure Query Language (MySQL) and Google Map Application Programming Interface (APIs). Graph has been generated by using open source tool Chart.js. Spatial distribution maps have been generated with the help of geo-references of the colleges. The result shows: (i) the violation of University Grants Commission's (UGCs) Regulation for the awards of M. Phil/Ph.D. clearly exhibits. (ii) There is a gap between apex regulatory bodies of higher education at national and as well as state level to check fraud. (iii) Mala fide 'No Objection Certificate' (NOC) issued by the Government of Assam have played pivotal role in the occurrence of fraudulent practices in higher educational institutions of Assam. (iv) Violation of verdict of the Hon'ble Supreme Court of India regarding territorial jurisdiction of Universities for the awards of Ph.D. and M. Phil degrees in distance mode/study centre is also a responsible factor for the spread of these academic frauds in Assam and other states. The challenges and mitigation of these issues have been discussed.

Keywords: Assam, fraud, higher education, mitigation

Procedia PDF Downloads 174

Authors: Rahma Al Balushi

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Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS dept. This paper will describe in detail the GIS data submission process and the journey to develop the current process. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting, and data alterations salso aided to reduce the missing attributes of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the year 2017 and the year 2021. Overall, concluding that by governance, asset information & GIS department can control GIS data process; collect, properly record, and manage asset data and information within OETC network. This control extends to other applications and systems integrated with/related to GIS systems.

Keywords: asset management ISO55001, standard procedures process, governance, geodatabase, NOC, CMMS

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Authors: Pallavi Malhotra

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This paper examines the importance of ethics in cloud computing. In the modern society, cloud computing is offering individuals and businesses an unlimited space for storing and processing data or information. Most of the data and information stored in the cloud by various users such as banks, doctors, architects, engineers, lawyers, consulting firms, and financial institutions among others require a high level of confidentiality and safeguard. Cloud computing offers centralized storage and processing of data, and this has immensely contributed to the growth of businesses and improved sharing of information over the internet. However, the accessibility and management of data and servers by a third party raise concerns regarding the privacy of clients’ information and the possible manipulations of the data by third parties. This document suggests the approaches various stakeholders should take to address various ethical issues involving cloud-computing services. Ethical education and training is key to all stakeholders involved in the handling of data and information stored or being processed in the cloud.

Keywords: IT ethics, cloud computing technology, cloud privacy and security, ethical education

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Authors: Tingting Liu, Yufeng Wu, Xi Tian, Yu Gong, Tieyong Zuo

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The household solid waste generated by household in Beijing is increasing quickly due to rapid population growth and lifestyle changes. However, there are no rigorous data on the generation and collection of the recyclable household solid wastes. The Beijing city government needs this information to make appropriate policies and plans for waste management. To address this information need, we undertook the first comprehensive study of recyclable household solid waste for Beijing. We carried out a survey of 500 families across sixteen districts in Beijing. We also analyzed the quantities, spatial distribution and categories of collected waste handled by curbside recyclers and permanent recycling centers for 340 of the 9797 city-defined residential areas of Beijing. From our results, we estimate that the total quantity of recyclable household solid waste was 1.8 million tonnes generated by Beijing household in 2013 and 71.6% of that was collected. The main generation categories were waste paper (24.4%), waste glass bottle (23.7%) and waste furniture (14.3%). The recycling rate was varied among different kinds of municipal solid waste. Also based on our study, we estimate there were 22.8 thousand curbside recyclers and 5.7 thousand permanent recycling centers in Beijing. The problems of household solid waste collecting system were inadequacies of authorized collection centers, skewed ratios of curbside recyclers and authorized permanent recycling centers, weak recycling awareness of residents and lack of recycling resources statistics and appraisal system. According to the existing problems, we put forward the suggestions to improve household solid waste management.

Keywords: Municipal waste; Recyclable waste; Waste categories; Waste collection

Procedia PDF Downloads 299