Search results for: fuzzy aggregation operator

Authors: Rudolf Hrach, Stanislav Novak, Vera Hrachova

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Composite and nanocomposite films represent the class of promising materials and are often objects of the study due to their mechanical, electrical and other properties. The most interesting ones are probably the composite metal/dielectric structures consisting of a metal component embedded in an oxide or polymer matrix. Behaviour of composite films varies with the amount of the metal component inside what is called filling factor. The structures contain individual metal particles or nanoparticles completely insulated by the dielectric matrix for small filling factors and the films have more or less dielectric properties. The conductivity of the films increases with increasing filling factor and finally a transition into metallic state occurs. The behaviour of composite films near a percolation threshold, where the change of charge transport mechanism from a thermally-activated tunnelling between individual metal objects to an ohmic conductivity is observed, is especially important. Physical properties of composite films are given not only by the concentration of metal component but also by the spatial and size distributions of metal objects which are influenced by a technology used. In our contribution, a study of composite structures with the help of methods of computational physics was performed. The study consists of two parts: -Generation of simulated composite and nanocomposite films. The techniques based on hard-sphere or soft-sphere models as well as on atomic modelling are used here. Characterizations of prepared composite structures by image analysis of their sections or projections follow then. However, the analysis of various morphological methods must be performed as the standard algorithms based on the theory of mathematical morphology lose their sensitivity when applied to composite films. -The charge transport in the composites was studied by the kinetic Monte Carlo method as there is a close connection between structural and electric properties of composite and nanocomposite films. It was found that near the percolation threshold the paths of tunnel current forms so-called fuzzy clusters. The main aim of the present study was to establish the correlation between morphological properties of composites/nanocomposites and structures of conducting paths in them in the dependence on the technology of composite films.

Keywords: composite films, computer modelling, image analysis, nanocomposite films

Procedia PDF Downloads 369

Authors: Roshanak Afrakhteh, Abdolrasoul Salman Mahini, Mahdi Motagh, Hamidreza Kamyab

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Urban Heat Islands (UHIs) are distinctive urban areas characterized by densely populated central cores surrounded by less densely populated peripheral lands. These areas experience elevated temperatures, primarily due to impermeable surfaces and specific land use patterns. The consequences of these temperature variations are far-reaching, impacting the environment and society negatively, leading to increased energy consumption, air pollution, and public health concerns. This paper emphasizes the need for simplified approaches to comprehend UHI temperature dynamics and explains how urban development patterns contribute to land surface temperature variation. To illustrate this relationship, the study focuses on the Guilan Plain, utilizing techniques like principal component analysis and generalized additive models. The research centered on mapping land use and land surface temperature in the low-lying area of Guilan province. Satellite data from Landsat sensors for three different time periods (2002, 2012, and 2021) were employed. Using eCognition software, a spatial unit known as a "city block" was utilized through object-based analysis. The study also applied the normalized difference vegetation index (NDVI) method to estimate land surface radiance. Predictive variables for urban land surface temperature within residential city blocks were identified categorized as intrinsic (related to the block's structure) and neighboring (related to adjacent blocks) variables. Principal Component Analysis (PCA) was used to select significant variables, and a Generalized Additive Model (GAM) approach, implemented using R's mgcv package, modeled the relationship between urban land surface temperature and predictor variables.Notable findings included variations in urban temperature across different years attributed to environmental and climatic factors. Block size, shared boundary, mother polygon area, and perimeter-to-area ratio were identified as main variables for the generalized additive regression model. This model showed non-linear relationships, with block size, shared boundary, and mother polygon area positively correlated with temperature, while the perimeter-to-area ratio displayed a negative trend. The discussion highlights the challenges of predicting urban surface temperature and the significance of block size in determining urban temperature patterns. It also underscores the importance of spatial configuration and unit structure in shaping urban temperature patterns. In conclusion, this study contributes to the growing body of research on the connection between land use patterns and urban surface temperature. Block size, along with block dispersion and aggregation, emerged as key factors influencing urban surface temperature in residential areas. The proposed methodology enhances our understanding of parameter significance in shaping urban temperature patterns across various regions, particularly in Iran.

Keywords: urban heat island, land surface temperature, LST modeling, GAM, Gilan province

Procedia PDF Downloads 49

Authors: Torsten Hermanns, You Wang, Stefan Janssen, Markus Niessen, Christoph Schoeler, Ulrich Thombansen, Wolfgang Schulz

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In long pulse laser drilling of metals, it can be demonstrated that the ablation shape approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from ultra short pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in long pulse drilling of metals is identified, a model for the description of the asymptotic hole shape numerically implemented, tested and clearly confirmed by comparison with experimental data. The model assumes a robust process in that way that the characteristics of the melt flow inside the arising melt film does not change qualitatively by changing the laser or processing parameters. Only robust processes are technically controllable and thus of industrial interest. The condition for a robust process is identified by a threshold for the mass flow density of the assist gas at the hole entrance which has to be exceeded. Within a robust process regime the melt flow characteristics can be captured by only one model parameter, namely the intensity threshold. In analogy to USP ablation (where it is already known for a long time that the resulting hole shape results from a threshold for the absorbed laser fluency) it is demonstrated that in the case of robust long pulse ablation the asymptotic shape forms in that way that along the whole contour the absorbed heat flux density is equal to the intensity threshold. The intensity threshold depends on the special material and radiation properties and has to be calibrated be one reference experiment. The model is implemented in a numerical simulation which is called AsymptoticDrill and requires such a few amount of resources that it can run on common desktop PCs, laptops or even smart devices. Resulting hole shapes can be calculated within seconds what depicts a clear advantage over other simulations presented in literature in the context of industrial every day usage. Against this background the software additionally is equipped with a user-friendly GUI which allows an intuitive usage. Individual parameters can be adjusted using sliders while the simulation result appears immediately in an adjacent window. A platform independent development allow a flexible usage: the operator can use the tool to adjust the process in a very convenient manner on a tablet during the developer can execute the tool in his office in order to design new processes. Furthermore, at the best knowledge of the authors AsymptoticDrill is the first simulation which allows the import of measured real beam distributions and thus calculates the asymptotic hole shape on the basis of the real state of the specific manufacturing system. In this paper the emphasis is placed on the investigation of the effect of multiple reflections on the asymptotic hole shape which gain in importance when drilling holes with large aspect ratios.

Keywords: asymptotic hole shape, intensity threshold, long pulse laser drilling, robust process

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Authors: Pompilia Buzatu, Hazim Qiblawey, Albert Odai, Jana Jamaleddin, Mustafa Nasser, Simon J. Judd

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Membrane bioreactor (MBR) technology is challenged by the tendency for the membrane permeability to decrease due to ‘clogging’. Clogging includes ‘sludging’, the filling of the membrane channels with sludge solids, and ‘ragging’, the aggregation of short filaments to form long rag-like particles. Both sludging and ragging demand manual intervention to clear out the solids, which is time-consuming, labour-intensive and potentially damaging to the membranes. These factors impact on costs more significantly than membrane surface fouling which, unlike clogging, is largely mitigated by the chemical clean. However, practical evaluation of MBR clogging has thus far been limited. This paper presents the results of recent work attempting to quantify sludging and clogging based on simple bench-scale tests. Results from a novel ragging simulation trial indicated that rags can be formed within 24-36 hours from dispersed < 5 mm-long filaments at concentrations of 5-10 mg/L under gently agitated conditions. Rag formation occurred for both a cotton wool standard and samples taken from an operating municipal MBR, with between 15% and 75% of the added fibrous material forming a single rag. The extent of rag formation depended both on the material type or origin – lint from laundering operations forming zero rags – and the filament length. Sludging rates were quantified using a bespoke parallel-channel test cell representing the membrane channels of an immersed flat sheet MBR. Sludge samples were provided from two local MBRs, one treating municipal and the other industrial effluent. Bulk sludge properties measured comprised mixed liquor suspended solids (MLSS) concentration, capillary suction time (CST), particle size, soluble COD (sCOD) and rheology (apparent viscosity μₐ vs shear rate γ). The fouling and sludging propensity of the sludge was determined using the test cell, ‘fouling’ being quantified as the pressure incline rate against flux via the flux step test (for which clogging was absent) and sludging by photographing the channel and processing the image to determine the ratio of the clogged to unclogged regions. A substantial difference in rheological and fouling behaviour was evident between the two sludge sources, the industrial sludge having a higher viscosity but less shear-thinning than the municipal. Fouling, as manifested by the pressure increase Δp/Δt, as a function of flux from classic flux-step experiments (where no clogging was evident), was more rapid for the industrial sludge. Across all samples of both sludge origins the expected trend of increased fouling propensity with increased CST and sCOD was demonstrated, whereas no correlation was observed between clogging rate and these parameters. The relative contribution of fouling and clogging was appraised by adjusting the clogging propensity via increasing the MLSS both with and without a commensurate increase in the COD. Results indicated that whereas for the municipal sludge the fouling propensity was affected by the increased sCOD, there was no associated increased in the sludging propensity (or cake formation). The clogging rate actually decreased on increasing the MLSS. Against this, for the industrial sludge the clogging rate dramatically increased with solids concentration despite a decrease in the soluble COD. From this was surmised that sludging did not relate to fouling.

Keywords: clogging, membrane bioreactors, ragging, sludge

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Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva

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The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.

Keywords: analog ensemble, electricity market, PV forecast, solar energy

Procedia PDF Downloads 128

Authors: Prem Kumar, Anuj Tyagi, Harsh Panwar, Vaneet Inder Kaur

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Though aquaculture started as an occupation for poor and weak farmers for livelihood, it has now acquired the shape of one of the biggest industry to grow live protein in the form of aquatic organisms. Industrialization of the aquaculture sector has led to intensification resulting in stress on aquatic organisms and frequent disease outbreaks leading to huge economic impacts. Indiscriminate use of antibiotics as growth promoter and prophylactic agent in aquaculture has resulted in rapid emergence and spread of antibiotic resistance in bacterial pathogens. Over the past few years, use of probiotics (as an alternative of antibiotics) in aquaculture has gained attention due to their immunostimulant and growth promoting properties. It has now well known that after administration, a probiotic bacterium has to compete and establish itself against native microbiota to show its eventual beneficial properties. Due to their non-fish origin, commercial probiotics sometimes may display poor probiotic functionalities and antagonistic effects. Thus, isolation and characterization of probiotic bacteria from same fish host is very much necessary. In this study, attempts were made to isolate potent probiotic lactic acid bacteria (LAB) from intestinal microflora of rohu fish. Twenty-five experimental rohu fishes (mean weight 400 ± 20gm, mean standard length 20 ± 3cm) were used in the study to collect fish gut after dissection in a sterile condition. A total of 150 tentative LAB isolates from selective agar media (de Man-Rogosa-Sharpe (MRS)) were screened for their antimicrobial activity against Aeromonas hydrophila and Microccocus leuteus. A total of 17 isolates, identified as Lactobacillus plantarum and Lactococcus lactis, identified by biochemical tests and PCR amplification and sequencing of 16S rRNA gene fragment, displayed promising antimicrobial activity against both the pathogens. Two isolates from each species (FLB1, FLB2 from L. plantarum; and FLC1, FLC2 from L. lactis) were subjected to downstream probiotic potential characterization. These isolates were compared in vitro for their hemolytic activity, acid and bile tolerance for growth kinetics, auto-aggregation, cell-surface hydrophobicity against xylene, and chloroform, tolerance to phenol, cell adhesion, and safety parameters (by intraperitoneal and intramuscular injections). None of the tested isolates showed any hemolytic activity indicating their potential safety. Moreover, these isolates were tolerant to 0.3% bile (75-82% survival), phenol stress (96-99% survival) with 100% viability at pH 3 over a period of 3 h. Antibiotic sensitivity test revealed that all the tested LAB isolates were resistant to vancomycin, gentamicin, streptomycin, and erythromycin and sensitive to Erythromycin, Chloramphenicol, Ampicillin, Trimethoprim, and Nitrofurantoin. Tetracycline resistance was found in L. plantarum (FLB1 and FLB2 isolates), whereas L. lactis were susceptible to it. Intramuscular and intraperitoneal challenges to fingerlings of rohu fish (5 ± 1gm weight) with FLB1 showed no pathogenicity and occurrence of disease symptoms in fishes over an observation period of 7 days. The results revealed FLB1 as a potential probiotic candidate for aquaculture application among other isolates.

Keywords: aquaculture, Lactobacillus plantarum, Lactococcus lactis, probiotics

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Authors: S. J. Addinell, A. F. Grabsch, P. D. Fawell, B. Evans

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The Deep Exploration Technologies Cooperative Research Centre (DET CRC) is researching and developing a new coiled tubing based greenfields mineral exploration drilling system utilising down-hole water-powered percussive drill tooling. This new drilling system is aimed at significantly reducing the costs associated with identifying mineral resource deposits beneath deep, barren cover. This system has shown superior rates of penetration in water-rich, hard rock formations at depths exceeding 500 metres. With fluid flow rates of up to 120 litres per minute at 200 bar operating pressure to energise the bottom hole tooling, excessive quantities of high quality drilling fluid (water) would be required for a prolonged drilling campaign. As a result, drilling fluid recovery and recycling has been identified as a necessary option to minimise costs and logistical effort. While the majority of the cuttings report as coarse particles, a significant fines fraction will typically also be present. To maximise tool life longevity, the percussive bottom hole assembly requires high quality fluid with minimal solids loading and any recycled fluid needs to have a solids cut point below 40 microns and a concentration less than 400 ppm before it can be used to reenergise the system. This paper presents experimental results obtained from the research program during laboratory and field testing of the prototype drilling system. A study of the morphological aspects of the cuttings generated during the percussive drilling process shows a strong power law relationship for particle size distributions. This data is critical in optimising solids control strategies and cuttings dewatering techniques. Optimisation of deployable solids control equipment is discussed and how the required centrate clarity was achieved in the presence of pyrite-rich metasediment cuttings. Key results were the successful pre-aggregation of fines through the selection and use of high molecular weight anionic polyacrylamide flocculants and the techniques developed for optimal dosing prior to scroll decanter centrifugation, thus keeping sub 40 micron solids loading within prescribed limits. Experiments on maximising fines capture in the presence of thixotropic drilling fluid additives (e.g. Xanthan gum and other biopolymers) are also discussed. As no core is produced during the drilling process, it is intended that the particle laden returned drilling fluid is used for top-of-hole geochemical and mineralogical assessment. A discussion is therefore presented on the biasing and latency of cuttings representivity by dewatering techniques, as well as the resulting detrimental effects on depth fidelity and accuracy. Data pertaining to the sample biasing with respect to geochemical signatures due to particle size distributions is presented and shows that, depending on the solids control and dewatering techniques used, it can have unwanted influence on top-of-hole analysis. Strategies are proposed to overcome these effects, improving sample quality. Successful solids control and cuttings dewatering for water-powered percussive drilling is presented, contributing towards the successful advancement of coiled tubing based greenfields mineral exploration.

Keywords: cuttings, dewatering, flocculation, percussive drilling, solids control

Procedia PDF Downloads 222

Authors: Liuhui Zhu, Peng Zeng

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With the rapid development in China, the urbanization has entered the transformation and promotion stage, and its direction of development has shifted to overall regional synergy. China has a large number of towns and villages, with comparative small scale and scattered distribution, which always support and provide resources to cities leading to urban-rural opposition, so it is difficult to achieve common development in a single town or village. In this context, the regional development should focus more on towns and villages to form a synergetic system, joining the regional association with cities. Thus, the paper raises the question about how to effectively organize towns and villages system to regulate the resource allocation and improve the comprehensive value of the regional area. To answer the question, it is necessary to find a suitable research unit and analysis of its present situation of towns and villages system for optimal development. By combing relevant researches and theoretical models, the county is the most basic administrative unit in China, which can directly guide and regulate the development of towns and villages, so the paper takes county as the research unit. Following the theoretical concept of ‘three structures and one network’, the paper concludes the research framework to analyse the present situation of towns and villages system, including scale structure, functional structure, spatial structure, and organization network. The analytical methods refer to the fractal theory and gravity model, using statistics and spatial data. The scale structure analyzes rank-size dimensions and uses the principal component method to calculate the comprehensive scale of towns and villages. The functional structure analyzes the functional types and industrial development of towns and villages. The spatial structure analyzes the aggregation dimension, network dimension, and correlation dimension of spatial elements to represent the overall spatial relationships. In terms of organization network, from the perspective of entity and ono-entity, the paper analyzes the transportation network and gravitational network. Based on the present situation analysis, the optimization strategies are proposed in order to achieve a synergetic relationship between towns and villages in the county area. The paper uses Suning county in the Beijing-Tianjin-Hebei region as a case study to apply the research framework and methods and then proposes the optimization orientations. The analysis results indicate that: (1) The Suning county is lack of medium-scale towns to transfer effect from towns to villages. (2) The distribution of gravitational centers is uneven, and the effect of gravity is limited only for nearby towns and villages. The gravitational network is not complete, leading to economic activities scattered and isolated. (3) The overall development of towns and villages system is immature, staying at ‘single heart and multi-core’ stage, and some specific optimization strategies are proposed. This study provides a regional view for the development of towns and villages and concludes the research framework and methods of towns and villages system for forming an effective synergetic relationship between them, contributing to organize resources and stimulate endogenous motivation, and form counter magnets to join the urban-rural integration.

Keywords: towns and villages system, organization structure, county area, fractal theory, gravity model

Procedia PDF Downloads 114

Authors: Christoph Opperer

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The rapid urbanization of modern societies and the need for sustainable urban development demand innovative solutions that meet both individual and collective needs while addressing environmental concerns. To address these challenges, this paper presents a study that explores the potential of spatial and energetic/ecological optimization to enhance the performance of urban settlements, focusing on both architectural and urban scales. The study focuses on the application of biological principles and self-organization processes in urban planning and design, aiming to achieve a balance between ecological performance, architectural quality, and individual living conditions. The research adopts a case study approach, focusing on a 10-hectare brownfield site in the south of Vienna. The site is surrounded by a small-scale built environment as an appropriate starting point for the research and design process. However, the selected urban form is not a prerequisite for the proposed design methodology, as the findings can be applied to various urban forms and densities. The methodology used in this research involves dividing the overall building mass and program into individual small housing units. A computational model has been developed to optimize the distribution of these units, considering factors such as solar exposure/radiation, views, privacy, proximity to sources of disturbance (such as noise), and minimal internal circulation areas. The model also ensures that existing vegetation and buildings on the site are preserved and incorporated into the optimization and design process. The model allows for simultaneous optimization at two scales, architectural and urban design, which have traditionally been addressed sequentially. This holistic design approach leads to individual and collective benefits, resulting in urban environments that foster a balance between ecology and architectural quality. The results of the optimization process demonstrate a seemingly random distribution of housing units that, in fact, is a densified hybrid between traditional garden settlements and allotment settlements. This urban typology is selected due to its compatibility with the surrounding urban context, although the presented methodology can be extended to other forms of urban development and density levels. The benefits of this approach are threefold. First, it allows for the determination of ideal housing distribution that optimizes solar radiation for each building density level, essentially extending the concept of sustainable building to the urban scale. Second, the method enhances living quality by considering the orientation and positioning of individual functions within each housing unit, achieving optimal views and privacy. Third, the algorithm's flexibility and robustness facilitate the efficient implementation of urban development with various stakeholders, architects, and construction companies without compromising its performance. The core of the research is the application of global and local optimization strategies to create efficient design solutions. By considering both, the performance of individual units and the collective performance of the urban aggregation, we ensure an optimal balance between private and communal benefits. By promoting a holistic understanding of urban ecology and integrating advanced optimization strategies, our methodology offers a sustainable and efficient solution to the challenges of modern urbanization.

Keywords: sustainable development, self-organization, ecological performance, solar radiation and exposure, daylight, visibility, accessibility, spatial distribution, local and global optimization

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Authors: Marian Mihalik, Kornel Csach, Martin Kovalik, Matúš Mihalik, Martina Kubovčíková, Maria Zentková, Martin Vavra, Vladimír Girman, Jaroslav Briančin, Marija Perovic, Marija Boškovic, Magdalena Fitta, Robert Pelka

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Current nanomaterials for use in biomedicine are based mainly on iron oxides and on present knowledge on magnetic nanostructures. Manganites can represent another material which can be used optionally. Manganites and their unique electronic properties have been extensively studied in the last decades not only due to fundamental interest but to possible applications of colossal magnetoresistance, magnetocaloric effect, and ferroelectric properties. It was found that the oxygen-reduction reaction on perovskite oxide is intimately connected with metal ion e.g., orbital occupation. The effect of oxygen deviation from the stoichiometric composition on crystal structure was studied very carefully by many authors on LaMnO₃. Depending on oxygen content, the crystal structure changes from orthorhombic one to rhombohedric for oxygen content 3.1. In the case of hole-doped manganites, the change from the orthorhombic crystal structure, which is typical for La1-xCaxMnO3 based manganites, to the rhombohedric crystal structure (La1-xMxMnO₃ where M = K, Ag, and Sr based materials) results in an enormous increase of the Curie temperature. In our paper, we study the effect of oxygen content on crystal structure, thermal, and magnetic properties (including magnetocaloric effect) of La1-xAgxMnO₃nano particle system. The content of oxygen in samples was tuned by heat treatment in different thermal regimes and in various environment (air, oxygen, argon). Water nanosuspensions based on La0.80Ag0.15MnO₃ magnetic particles with the Curie temperature of about 43oC were prepared by two different approaches. First, by using a laboratory circulation mill for milling of powder in the presence of sodium dodecyl sulphate (SDS) and subsequent centrifugation. Second nanosuspension was prepared using an agate bowl, etching in citric acid and HNO3, ultrasound homogeniser, centrifugation, and dextran 40 kDA or 15 kDA as surfactant. Electrostatic stabilisation obtained by the first approach did not offer long term kinetic and aggregation colloidal stability and was unable to compensate for attractive forces between particles under a magnetic field. By the second approach, we prepared suspension oversaturated by dextran 40 kDA for steric stabilisation, with evidence of the presence of superparamagnetic behaviour. Low concentration of nanoparticles and not ideal coverage of nanoparticles impacting the stability of ferrofluids was the disadvantage of this approach. Strong steric stabilisation was observable at alcaic conditions under pH = ~10. Application of dextran 15 kDA leads to relatively stable ferrofluid with pH around physiological conditions, but desegregation of powder by HNO₃ was not effective enough, and the average size of fragments was to large of about 150 nm, and we did not see any signature of superparamagnetic behaviour. The prepared ferrofluids were characterised by scanning and transition microscope method, thermogravimetry, magnetization, and AC susceptibility measurements. Specific Absorption Rate measurements were undertaken on powder as well on ferrofluids in order to estimate the potential application of La₀.₈₀Ag₀.₁₅MnO₃ magnetic particles based ferrofluid for hyperthermia. Our complex study contains an investigation of biocompatibility and potential biohazard of this material.

Keywords: manganites, magnetic nanoparticles, oxygen content, magnetic phase transition, magnetocaloric effect, ferrofluid, hyperthermia

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Authors: Seungsik Yu, Minho Kang

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As the threat of terrorism to nuclear facilities is increasing globally after the attacks of September 11, we are striving to recognize the physical protection system and strengthen the emergency response system. Since 2015, Korea has implemented physical protection security exercise for nuclear facilities. The exercise should be carried out with full cooperation between the operator and response forces. Performance testing of the physical protection system should include appropriate exercises, for example, force-on-force exercises, to determine if the response forces can provide an effective and timely response to prevent sabotage. Significant deficiencies and actions taken should be reported as stipulated by the competent authority. The IAEA(International Atomic Energy Agency) is also preparing force-on-force exercise program documents to support exercise of member states. Currently, ROK(Republic of Korea) is implementing exercise on the force-on-force exercise evaluation system which is developed by itself for the nuclear power plant, and it is necessary to establish the exercise procedure considering the use of the force-on-force exercise evaluation system. The purpose of this study is to establish the work procedures of the three major organizations related to the force-on-force exercise of nuclear power plants in ROK, which conduct exercise using force-on-force exercise evaluation system. The three major organizations are composed of licensee, KINAC (Korea Institute of Nuclear Nonproliferation and Control), and the NSSC(Nuclear Safety and Security Commission). Major activities are as follows. First, the licensee establishes and conducts an exercise plan, and when recommendations are derived from the result of the exercise, it prepares and carries out a force-on-force result report including a plan for implementation of the recommendations. Other detailed tasks include consultation with surrounding units for adversary, interviews with exercise participants, support for document evaluation, and self-training to improve the familiarity of the MILES (Multiple Integrated Laser Engagement System). Second, KINAC establishes a force-on-force exercise plan review report and reviews the force-on-force exercise plan report established by licensee. KINAC evaluate force-on-force exercise using exercise evaluation system and prepare training evaluation report. Other detailed tasks include MILES training, adversary consultation, management of exercise evaluation systems, and analysis of exercise evaluation results. Finally, the NSSC decides whether or not to approve the force-on-force exercise and makes a correction request to the nuclear facility based on the exercise results. The most important part of ROK's force-on-force exercise system is the analysis through the exercise evaluation system implemented by KINAC after the exercise. The analytical method proceeds in the order of collecting data from the exercise evaluation system and analyzing the collected data. The exercise application process of the exercise evaluation system introduced in ROK in 2016 will be concretely set up, and a system will be established to provide objective and consistent conclusions between exercise sessions. Based on the conclusions drawn up, the ultimate goal is to complement the physical protection system of licensee so that the system makes licensee respond effectively and timely against sabotage or unauthorized removal of nuclear materials.

Keywords: Force-on-Force exercise, nuclear power plant, physical protection, sabotage, unauthorized removal

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Authors: A. Odoom, A. Salama, H. Ibrahim

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Hydrogen is a clean source of energy for power production and transportation. The main source of hydrogen in this research is biodiesel. Glycerol also called glycerine is a by-product of biodiesel production by transesterification of vegetable oils and methanol. This is a reliable and environmentally-friendly source of hydrogen production than fossil fuels. A typical composition of crude glycerol comprises of glycerol, water, organic and inorganic salts, soap, methanol and small amounts of glycerides. Crude glycerol has limited industrial application due to its low purity thus, the usage of crude glycerol can significantly enhance the sustainability and production of biodiesel. Reforming techniques is an approach for hydrogen production mainly Steam Reforming (SR), Autothermal Reforming (ATR) and Partial Oxidation Reforming (POR). SR produces high hydrogen conversions and yield but is highly endothermic whereas POR is exothermic. On the downside, PO yields lower hydrogen as well as large amount of side reactions. ATR which is a fusion of partial oxidation reforming and steam reforming is thermally neutral because net reactor heat duty is zero. It has relatively high hydrogen yield, selectivity as well as limits coke formation. The complex chemical processes that take place during the production phases makes it relatively difficult to construct a reliable and robust numerical model. Numerical model is a tool to mimic reality and provide insight into the influence of the parameters. In this work, we introduce a finite volume numerical study for an 'in-house' lab-scale experiment of ATR. Previous numerical studies on this process have considered either using Comsol or nodal finite difference analysis. Since Comsol is a commercial package which is not readily available everywhere and lab-scale experiment can be considered well mixed in the radial direction. One spatial dimension suffices to capture the essential feature of ATR, in this work, we consider developing our own numerical approach using MATLAB. A continuum fixed bed reactor is modelled using MATLAB with both pseudo homogeneous and heterogeneous models. The drawback of nodal finite difference formulation is that it is not locally conservative which means that materials and momenta can be generated inside the domain as an artifact of the discretization. Control volume, on the other hand, is locally conservative and suites very well problems where materials are generated and consumed inside the domain. In this work, species mass balance, Darcy’s equation and energy equations are solved using operator splitting technique. Therefore, diffusion-like terms are discretized implicitly while advection-like terms are discretized explicitly. An upwind scheme is adapted for the advection term to ensure accuracy and positivity. Comparisons with the experimental data show very good agreements which build confidence in our modeling approach. The models obtained were validated and optimized for better results.

Keywords: autothermal reforming, crude glycerol, hydrogen, numerical model

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Authors: Sandra Cecilia Bautista-Rodríguez, Vladimir Melgarejo

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Climate change, loss of ecosystems, increasing poverty, increasing marginalization of rural communities and declining food security are global issues that require urgent attention. In this regard, a great deal of research has focused on how agroecosystems respond to these challenges as they provide ecosystem services (ES) that lead to higher levels of resilience, adaptation, productivity and self-sufficiency. Hence, the valuing of ecosystem services plays an important role in the decision-making process for the design and management of agroecosystems. This paper aims to define the link between ecosystem service valuation methods and ES value dimensions in agroecosystems from ecological economics and agroecology. The method used to identify valuation methodologies was a literature review in the fields of Agroecology and Ecological Economics, based on a strategy of information search and classification. The conceptual framework of the work is based on the multidimensionality of value, considering the social, ecological, political, technological and economic dimensions. Likewise, the valuation process requires consideration of the ecosystem function associated with ES, such as regulation, habitat, production and information functions. In this way, valuation methods for ES in agroecosystems can integrate more than one value dimension and at least one ecosystem function. The results allow correlating the ecosystem functions with the ecosystem services valued, and the specific tools or models used, the dimensions and valuation methods. The main methodologies identified are multi-criteria valuation (1), deliberative - consultative valuation (2), valuation based on system dynamics modeling (3), valuation through energy or biophysical balances (4), valuation through fuzzy logic modeling (5), valuation based on agent-based modeling (6). Amongst the main conclusions, it is highlighted that the system dynamics modeling approach has a high potential for development in valuation processes, due to its ability to integrate other methods, especially multi-criteria valuation and energy and biophysical balances, to describe through causal cycles the interrelationships between ecosystem services, the dimensions of value in agroecosystems, thus showing the relationships between the value of ecosystem services and the welfare of communities. As for methodological challenges, it is relevant to achieve the integration of tools and models provided by different methods, to incorporate the characteristics of a complex system such as the agroecosystem, which allows reducing the limitations in the processes of valuation of ES.

Keywords: ecological economics, agroecosystems, ecosystem services, valuation of ecosystem services

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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: Guenther Schuh, Michael Riesener, Frederic Diels

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Nowadays, manufacturing companies are faced with the challenge of meeting heterogeneous customer requirements in short product life cycles with a variety of product functions. So far, some of the functional requirements remain unknown until late stages of the product development. A way to handle these uncertainties is the highly iterative product development (HIP) approach. By structuring the development project as a highly iterative process, this method provides customer oriented and marketable products. There are first approaches for combined, hybrid models comprising deterministic-normative methods like the Stage-Gate process and empirical-adaptive development methods like SCRUM on a project management level. However, almost unconsidered is the question, which development scopes can preferably be realized with either empirical-adaptive or deterministic-normative approaches. In this context, a development scope constitutes a self-contained section of the overall development objective. Therefore, this paper focuses on a methodology that deals with the uncertainty of requirements within the early development stages and the corresponding selection of the most appropriate development approach. For this purpose, internal influencing factors like a company’s technology ability, the prototype manufacturability and the potential solution space as well as external factors like the market accuracy, relevance and volatility will be analyzed and combined into an Agile-Indicator. The Agile-Indicator is derived in three steps. First of all, it is necessary to rate each internal and external factor in terms of the importance for the overall development task. Secondly, each requirement has to be evaluated for every single internal and external factor appropriate to their suitability for empirical-adaptive development. Finally, the total sums of internal and external side are composed in the Agile-Indicator. Thus, the Agile-Indicator constitutes a company-specific and application-related criterion, on which the allocation of empirical-adaptive and deterministic-normative development scopes can be made. In a last step, this indicator will be used for a specific clustering of development scopes by application of the fuzzy c-means (FCM) clustering algorithm. The FCM-method determines sub-clusters within functional clusters based on the empirical-adaptive environmental impact of the Agile-Indicator. By means of the methodology presented in this paper, it is possible to classify requirements, which are uncertainly carried out by the market, into empirical-adaptive or deterministic-normative development scopes.

Keywords: agile, highly iterative development, agile-indicator, product development

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Authors: Karan Sharma, Ajay Kumar

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Epileptic seizure is a type of disease due to which electrical charge in the brain flows abruptly resulting in abnormal activity by the subject. One percent of total world population gets epileptic seizure attacks.Due to abrupt flow of charge, EEG (Electroencephalogram) waveforms change. On the display appear a lot of spikes and sharp waves in the EEG signals. Detection of epileptic seizure by using conventional methods is time-consuming. Many methods have been evolved that detect it automatically. The initial part of this paper provides the review of techniques used to detect epileptic seizure automatically. The automatic detection is based on the feature extraction and classification patterns. For better accuracy decomposition of the signal is required before feature extraction. A number of parameters are calculated by the researchers using different techniques e.g. approximate entropy, sample entropy, Fuzzy approximate entropy, intrinsic mode function, cross-correlation etc. to discriminate between a normal signal & an epileptic seizure signal.The main objective of this review paper is to present the variations in the EEG signals at both stages (i) Interictal (recording between the epileptic seizure attacks). (ii) Ictal (recording during the epileptic seizure), using most appropriate methods of analysis to provide better healthcare diagnosis. This research paper then investigates the effects of a noninvasive healing therapy on the subjects by studying the EEG signals using latest signal processing techniques. The study has been conducted with Reiki as a healing technique, beneficial for restoring balance in cases of body mind alterations associated with an epileptic seizure. Reiki is practiced around the world and is recommended for different health services as a treatment approach. Reiki is an energy medicine, specifically a biofield therapy developed in Japan in the early 20th century. It is a system involving the laying on of hands, to stimulate the body’s natural energetic system. Earlier studies have shown an apparent connection between Reiki and the autonomous nervous system. The Reiki sessions are applied by an experienced therapist. EEG signals are measured at baseline, during session and post intervention to bring about effective epileptic seizure control or its elimination altogether.

Keywords: EEG signal, Reiki, time consuming, epileptic seizure

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Authors: Huseyin Sinan Gunesli

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Process Safety Management is a disciplined framework for managing the integrity of systems and processes that handle hazardous substances. It relies on good design principles, well-implemented automation systems, and operating and maintenance practices. Alarm Management Systems play a critically important role in the safe and efficient operation of modern industrial plants. In that respect, Alarm Management is one of the critical factors feeding the safe operations of the plants in the manner of applying effective process safety principles. Trans Anatolian Natural Gas Pipeline (TANAP) is part of the Southern Gas Corridor, which extends from the Caspian Sea to Italy. TANAP transports Natural Gas from the Shah Deniz gas field of Azerbaijan, and possibly from other neighboring countries, to Turkey and through Trans Adriatic Pipeline (TAP) Pipeline to Europe. TANAP plays a crucial role in maintaining Energy Security for the region and Europe. In that respect, the application of Process Safety principles is vital to deliver safe, reliable and efficient Natural Gas delivery to Shippers both in the region and Europe. Effective Alarm Management is one of those Process Safety principles which feeds safe operations of the TANAP pipeline. Alarm Philosophy was designed and implemented in TANAP Pipeline according to the relevant standards. However, it is essential to manage the alarms received in the control room effectively to maintain safe operations. In that respect, TANAP has commenced Alarm Management & Rationalization program as of February 2022 after transferring to Plateau Regime, reaching the design parameters. While Alarm Rationalization started, there were more than circa 2300 alarms received per hour from one of the compressor stations. After applying alarm management principles such as reviewing and removal of bad actors, standing, stale, chattering, fleeting alarms, comprehensive review and revision of alarm set points through a change management principle, conducting alarm audits/design verification and etc., it has been achieved to reduce down to circa 40 alarms per hour. After the successful implementation of alarm management principles as specified above, the number of alarms has been reduced to industry standards. That significantly improved operator vigilance to focus on mainly important and critical alarms to avoid any excursion beyond safe operating limits leading to any potential process safety events. Following the ‟What Gets Measured, Gets Managed” principle, TANAP has identified key Performance Indicators (KPIs) to manage Process Safety principles effectively, where Alarm Management has formed one of the key parameters of those KPIs. However, review and analysis of the alarms were performed manually. Without utilizing Alarm Management Software, achieving full compliance with international standards is almost infeasible. In that respect, TANAP has started using one of the industry-wide known Alarm Management Applications to maintain full review and analysis of alarms and define actions as required. That actually significantly empowered TANAP’s process safety principles in terms of Alarm Management.

Keywords: process safety principles, energy security, natural gas pipeline operations, alarm rationalization, alarm management, alarm management application

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Authors: Andreas Kerstan, Darren Robey, Wesam Alvan, David Troiani

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Over the last 3.5 years, Quantum Cascade Lasers (QCL) technology has become increasingly important in infrared (IR) microscopy. The advantages over fourier transform infrared (FTIR) are that large areas of a few square centimeters can be measured in minutes and that the light intensive QCL makes it possible to obtain spectra with excellent S/N, even with just one scan. A firmly established solution of the laser direct infrared imaging (LDIR) 8700 is the analysis of microplastics. The presence of microplastics in the environment, drinking water, and food chains is gaining significant public interest. To study their presence, rapid and reliable characterization of microplastic particles is essential. Significant technical hurdles in microplastic analysis stem from the sheer number of particles to be analyzed in each sample. Total particle counts of several thousand are common in environmental samples, while well-treated bottled drinking water may contain relatively few. While visual microscopy has been used extensively, it is prone to operator error and bias and is limited to particles larger than 300 µm. As a result, vibrational spectroscopic techniques such as Raman and FTIR microscopy have become more popular, however, they are time-consuming. There is a demand for rapid and highly automated techniques to measure particle count size and provide high-quality polymer identification. Analysis directly on the filter that often forms the last stage in sample preparation is highly desirable as, by removing a sample preparation step it can both improve laboratory efficiency and decrease opportunities for error. Recent advances in infrared micro-spectroscopy combining a QCL with scanning optics have created a new paradigm, LDIR. It offers improved speed of analysis as well as high levels of automation. Its mode of operation, however, requires an IR reflective background, and this has, to date, limited the ability to perform direct “on-filter” analysis. This study explores the potential to combine the filter with an infrared reflective surface filter. By combining an IR reflective material or coating on a filter membrane with advanced image analysis and detection algorithms, it is demonstrated that such filters can indeed be used in this way. Vibrational spectroscopic techniques play a vital role in the investigation and understanding of microplastics in the environment and food chain. While vibrational spectroscopy is widely deployed, improvements and novel innovations in these techniques that can increase the speed of analysis and ease of use can provide pathways to higher testing rates and, hence, improved understanding of the impacts of microplastics in the environment. Due to its capability to measure large areas in minutes, its speed, degree of automation and excellent S/N, the LDIR could also implemented for various other samples like food adulteration, coatings, laminates, fabrics, textiles and tissues. This presentation will highlight a few of them and focus on the benefits of the LDIR vs classical techniques.

Keywords: QCL, automation, microplastics, tissues, infrared, speed

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Authors: Imen Soltani, Takoua Soltani, Taoufik Aguili

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Metamaterials crossover classic physical boundaries and gives rise to new phenomena and applications in the domain of beam steering and shaping. Where electromagnetic near and far field manipulations were achieved in an accurate manner. In this sense, 3D imaging is one of the beneficiaries and in particular Denis Gabor’s invention: holography. But, the major difficulty here is the lack of a suitable recording medium. So some enhancements were essential, where the 2D version of bulk metamaterials have been introduced the so-called metasurface. This new class of interfaces simplifies the problem of recording medium with the capability of tuning the phase, amplitude, and polarization at a given frequency. In order to achieve an intelligible wavefront control, the electromagnetic properties of the metasurface should be optimized by means of solving Maxwell’s equations. In this context, integral methods are emerging as an important method to study electromagnetic from microwave to optical frequencies. The method of moment presents an accurate solution to reduce the problem of dimensions by writing its boundary conditions in the form of integral equations. But solving this kind of equations tends to be more complicated and time-consuming as the structural complexity increases. Here, the use of equivalent circuit’s method exhibits the most scalable experience to develop an integral method formulation. In fact, for allaying the resolution of Maxwell’s equations, the method of Generalised Equivalent Circuit was proposed to convey the resolution from the domain of integral equations to the domain of equivalent circuits. In point of fact, this technique consists in creating an electric image of the studied structure using discontinuity plan paradigm and taken into account its environment. So that, the electromagnetic state of the discontinuity plan is described by generalised test functions which are modelled by virtual sources not storing energy. The environmental effects are included by the use of an impedance or admittance operator. Here, we propose a tunable metasurface composed of graphene-based elements which combine the advantages of reflectarrays concept and graphene as a pillar constituent element at Terahertz frequencies. The metasurface’s building block consists of a thin gold film, a dielectric spacer SiO₂ and graphene patch antenna. Our electromagnetic analysis is based on the method of moment combined with generalised equivalent circuit (MoM-GEC). We begin by restricting our attention to study the effects of varying graphene’s chemical potential on the unit cell input impedance. So, it was found that the variation of complex conductivity of graphene allows controlling the phase and amplitude of the reflection coefficient at each element of the array. From the results obtained here, we were able to determine that the phase modulation is realized by adjusting graphene’s complex conductivity. This modulation is a viable solution compared to tunning the phase by varying the antenna length because it offers a full 2π reflection phase control.

Keywords: graphene, method of moment combined with generalised equivalent circuit, reconfigurable metasurface, reflectarray, terahertz domain

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Authors: Davood Vatankhah, Reza Mokhtari Malekabadi, Mohsen Saghaei

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Function of urban transportation systems depends on the existence of the required infrastructures, appropriate placement of different components, and the cooperation of these components with each other. Establishing various neighboring parking spaces in city neighborhood in order to prevent long-term and inappropriate parking of cars in the allies is one of the most effective operations in reducing the crowding and density of the neighborhoods. Every place with a certain application attracts a number of daily travels which happen throughout the city. A large percentage of the people visiting these places go to these travels by their own cars; therefore, they need a space to park their cars. The amount of this need depends on the usage function and travel demand of the place. The study aims at investigating the spatial distribution of the public parking spaces, determining the effective factors in locating, and their combination in GIS environment in Khomeinishahr of Isfahan city. Ultimately, the study intends to create an appropriate pattern for locating parking spaces, determining the request for parking spaces of the traffic areas, choosing the proper places for providing the required public parking spaces, and also proposing new spots in order to promote quality and quantity aspects of the city in terms of enjoying public parking spaces. Regarding the method, the study is based on applied purpose and regarding nature, it is analytic-descriptive. The population of the study includes people of the center of Khomeinishahr which is located on Northwest of Isfahan having about 5000 hectares of geographic area and the population of 241318 people are in the center of Komeinishahr. In order to determine the sample size, Cochran formula was used and according to the population of 26483 people of the studied area, 231 questionnaires were used. Data analysis was carried out by usage of SPSS software and after estimating the required space for parking spaces, initially, the effective criteria in locating the public parking spaces are weighted by the usage of Analytic Hierarchical Process in the Arc GIS software. Then, appropriate places for establishing parking spaces were determined by fuzzy method of Order Weighted Average (OWA). The results indicated that locating of parking spaces in Khomeinishahr have not been carried out appropriately and per capita of the parking spaces is not desirable in relation to the population and request; therefore, in addition to the present parking lots, 1434 parking lots are needed in the area of the study for each day; therefore, there is not a logical proportion between parking request and the number of parking lots in Khomeinishahr.

Keywords: GIS, locating, parking, khomeinishahr

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Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

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Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri

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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.

Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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Authors: Yael Rieder, Yael Gilboa, S. O. Adva, Efrat Halevi, Ronnie Tepper

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Background: Operation of ultrasound equipment is a core skill for many clinical specialties. As part of the training program at -Simultech- a simulation center for Ob\Gyn at the Meir Medical Center, Israel, teaching how to operate ultrasound equipment requires dealing with misunderstandings of spatial and 3D orientation, failure of the operator to hold a transducer correctly, and limited ability to evaluate the data on the screen. We have developed a platform intended to endow physicians and sonographers with clinical and operational skills of obstetric ultrasound. Simultech's simulations are focused on medical knowledge, risk management, technology operations and physician-patient communication. The simulations encompass extreme work conditions. Setup: Between eight and ten of the eight hundred and fifty physicians and sonographers of the Clalit health services from seven hospitals and eight community centers across Israel, participate in individual Ob/Gyn training sessions each week. These include Ob/Gyn specialists, experts, interns, and sonographers. Innovative teaching and training methodologies: The six-hour training program includes: (1) An educational computer program that challenges trainees to deal with medical questions based upon ultrasound pictures and films. (2) Sophisticated hands-on simulators that challenge the trainees to practice correct grip of the transducer, elucidate pathology, and practice daily tasks such as biometric measurements and analysis of sonographic data. (3) Participation in a video-taped simulation which focuses on physician-patient communications. In the simulation, the physician is required to diagnose the clinical condition of a hired actress based on the data she provides and by evaluating the assigned ultrasound films accordingly. Giving ‘bad news’ to the patient may put the physician in a stressful situation that must be properly managed. (4) Feedback at the end of each phase is provided by a designated trainer, not a physician, who is specially qualified by Ob\Gyn senior specialists. (5) A group exercise in which the trainer presents a medico-legal case in order to encourage the participants to use their own experience and knowledge to conduct a productive ‘brainstorming’ session. Medical cases are presented and analyzed by the participants together with the trainer's feedback. Findings: (1) The training methods and content that Simultech provides allows trainees to review their medical and communications skills. (2) Simultech training sessions expose physicians to both basic and new, up-to-date cases, refreshing and expanding the trainee's knowledge. (3) Practicing on advanced simulators enables trainees to understand the sonographic space and to implement the basic principles of ultrasound. (4) Communications simulations were found to be beneficial for trainees who were unaware of their interpersonal skills. The trainer feedback, supported by the recorded simulation, allows the trainee to draw conclusions about his performance. Conclusion: Simultech was found to contribute to physicians at all levels of clinical expertise who deal with ultrasound. A break in daily routine together with attendance at a neutral educational center can vastly improve performance and outlook.

Keywords: medical training, simulations, ultrasound, Simultech

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Authors: Yitian Ren, Liyin Shen, Tao Zhou, Xiao Li

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The past urbanization process in China has brought out series of problems, the Chinese government has then positioned small towns in essential roles for implementing the strategy 'The National New-type Urbanization Plan (2014-2020)'. As the connector and transfer station of cities and countryside, small towns are important force to narrow the gap between urban and rural area, and to achieve the mission of new-type urbanization in China. The sustainable development of small towns plays crucial role because cities are not capable enough to absorb the surplus rural population. Nevertheless, there are various types of barriers hindering the sustainable development of small towns, which led to the limited development of small towns and has presented a bottleneck in Chinese urbanization process. Therefore, this paper makes deep understanding of these barriers, thus effective actions can be taken to address them. And this paper chooses the perspective of Southwest China (refers to Sichuan province, Yunnan province, Guizhou province, Chongqing Municipality City and Tibet Autonomous Region), cause the urbanization rate in Southwest China is far behind the average urbanization level of the nation and the number of small towns accounts for a great proportion in mainland China, also the characteristics of small towns in Southwest China are distinct. This paper investigates the barriers of sustainable development of small towns which located in Southwest China by using the content analysis method, combing with the field work and interviews in sample small towns, then identified and concludes 18 barriers into four dimensions, namely, institutional barriers, economic barriers, social barriers and ecological barriers. Based on the research above, questionnaire survey and data analysis are implemented, thus the key barriers hinder the sustainable development of small towns in Southwest China are identified by using fuzzy set theory, those barriers are, lack of independent financial power, lack of construction land index, financial channels limitation, single industrial structure, topography variety and complexity, which mainly belongs to institutional barriers and economic barriers. In conclusion part, policy suggestions are come up with to improve the politic and institutional environment of small town development, also the market mechanism are supposed to be introduced to the development process of small towns, which can effectively overcome the economic barriers, promote the sustainable development of small towns, accelerate the in-situ urbanization by absorbing peasants in nearby villages, and achieve the mission of new-type urbanization in China from the perspective of people-oriented.

Keywords: barrier analysis, sustainable development, small town, Southwest China

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Authors: Shengnan Chen, Shuhua Wang

Abstract:

Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

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Authors: James Brown, Stella Kortekaas, Ian Finnie, George Zhang, Christine Devine, Neil Healy

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The use of GIS as an analysis tool for engineering decision making is now best practice in the offshore industry. GIS enables multidisciplinary data integration, analysis and visualisation which allows the presentation of large and intricate datasets in a simple map-interface accessible to all project stakeholders. Presenting integrated geoscience and geotechnical data in GIS enables decision makers to be well-informed. This paper is a successful case study of how GIS spatial analysis techniques were applied to help select the most favourable pipeline route. Routing a pipeline through any natural environment has numerous obstacles, whether they be topographical, geological, engineering or financial. Where the pipeline is subjected to external hydrostatic water pressure and is carrying pressurised hydrocarbons, the requirement to safely route the pipeline through hazardous terrain becomes absolutely paramount. This study illustrates how the application of modern, GIS-based pipeline routing techniques enabled the identification of a single most-favourable pipeline route crossing of a challenging seabed terrain. Conventional approaches to pipeline route determination focus on manual avoidance of primary constraints whilst endeavouring to minimise route length. Such an approach is qualitative, subjective and is liable to bias towards the discipline and expertise that is involved in the routing process. For very short routes traversing benign seabed topography in shallow water this approach may be sufficient, but for deepwater geohazardous sites, the need for an automated, multi-criteria, and quantitative approach is essential. This study combined multiple routing constraints using modern least-cost-routing algorithms deployed in GIS, hitherto unachievable with conventional approaches. The least-cost-routing procedure begins with the assignment of geocost across the study area. Geocost is defined as a numerical penalty score representing hazard posed by each routing constraint (e.g. slope angle, rugosity, vulnerability to debris flows) to the pipeline. All geocosted routing constraints are combined to generate a composite geocost map that is used to compute the least geocost route between two defined terminals. The analyses were applied to select the most favourable pipeline route for a potential gas development in deep water. The study area is geologically complex with a series of incised, potentially active, canyons carved into a steep escarpment, with evidence of extensive debris flows. A similar debris flow in the future could cause significant damage to a poorly-placed pipeline. Protruding inter-canyon spurs offer lower-gradient options for ascending an escarpment but the vulnerability of periodic failure of these spurs is not well understood. Close collaboration between geoscientists, pipeline engineers, geotechnical engineers and of course the gas export pipeline operator guided the analyses and assignment of geocosts. Shorter route length, less severe slope angles, and geohazard avoidance were the primary drivers in identifying the most favourable route.

Keywords: geocost, geohazard, pipeline route determination, pipeline route optimisation, spatial analysis

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Authors: Chung-Ming Lo, Chung-Chien Lee

Abstract:

In many countries, the lifetime prevalence of shoulder pain is up to 70%. In America, the health care system spends 7 billion per year about the healthy issues of shoulder pain. With respect to the origin, up to 70% of shoulder pain is attributed to rotator cuff lesions This study proposed a computer-aided diagnosis (CAD) system to assist radiologists classifying rotator cuff lesions with less operator dependence. Quantitative features were extracted from the shoulder ultrasound images acquired using an ALOKA alpha-6 US scanner (Hitachi-Aloka Medical, Tokyo, Japan) with linear array probe (scan width: 36mm) ranging from 5 to 13 MHz. During examination, the postures of the examined patients are standard sitting position and are followed by the regular routine. After acquisition, the shoulder US images were drawn out from the scanner and stored as 8-bit images with pixel value ranging from 0 to 255. Upon the sonographic appearance, the boundary of each lesion was delineated by a physician to indicate the specific pattern for analysis. The three lesion categories for classification were composed of 20 cases of tendon inflammation, 18 cases of calcific tendonitis, and 18 cases of supraspinatus tear. For each lesion, second-order statistics were quantified in the feature extraction. The second-order statistics were the texture features describing the correlations between adjacent pixels in a lesion. Because echogenicity patterns were expressed via grey-scale. The grey-scale co-occurrence matrixes with four angles of adjacent pixels were used. The texture metrics included the mean and standard deviation of energy, entropy, correlation, inverse different moment, inertia, cluster shade, cluster prominence, and Haralick correlation. Then, the quantitative features were combined in a multinomial logistic regression classifier to generate a prediction model of rotator cuff lesions. Multinomial logistic regression classifier is widely used in the classification of more than two categories such as the three lesion types used in this study. In the classifier, backward elimination was used to select a feature subset which is the most relevant. They were selected from the trained classifier with the lowest error rate. Leave-one-out cross-validation was used to evaluate the performance of the classifier. Each case was left out of the total cases and used to test the trained result by the remaining cases. According to the physician’s assessment, the performance of the proposed CAD system was shown by the accuracy. As a result, the proposed system achieved an accuracy of 86%. A CAD system based on the statistical texture features to interpret echogenicity values in shoulder musculoskeletal ultrasound was established to generate a prediction model for rotator cuff lesions. Clinically, it is difficult to distinguish some kinds of rotator cuff lesions, especially partial-thickness tear of rotator cuff. The shoulder orthopaedic surgeon and musculoskeletal radiologist reported greater diagnostic test accuracy than general radiologist or ultrasonographers based on the available literature. Consequently, the proposed CAD system which was developed according to the experiment of the shoulder orthopaedic surgeon can provide reliable suggestions to general radiologists or ultrasonographers. More quantitative features related to the specific patterns of different lesion types would be investigated in the further study to improve the prediction.

Keywords: shoulder ultrasound, rotator cuff lesions, texture, computer-aided diagnosis

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Authors: Vânia Costa, Nuno De Sá Teixeira, Ana C. Santos, Eduardo Santos

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Financial literacy and numeracy have been regarded as paramount for rational household decision making in the increasing complexity of financial markets. However, financial decisions are often made under sub-optimal circumstances, including cognitive overload. The present study aims to clarify how financial literacy and numeracy, taken as relevant expert knowledge for financial decision-making, modulate possible effects of cognitive load. Participants were required to perform a choice between a sure loss or a gambling pertaining a financial investment, either with or without a competing memory task. Two experiments were conducted varying only the content of the competing task. In the first, the financial choice task was made while maintaining on working memory a list of five random letters. In the second, cognitive load was based upon the retention of six random digits. In both experiments, one of the items in the list had to be recalled given its serial position. Outcomes of the first experiment revealed no significant main effect or interactions involving cognitive load manipulation and numeracy and financial literacy skills, strongly suggesting that retaining a list of random letters did not interfere with the cognitive abilities required for financial decision making. Conversely, and in the second experiment, a significant interaction between the competing mnesic task and level of financial literacy (but not numeracy) was found for the frequency of choice of a gambling option. Overall, and in the control condition, both participants with high financial literacy and high numeracy were more prone to choose the gambling option. However, and when under cognitive load, participants with high financial literacy were as likely as their illiterate counterparts to choose the gambling option. This outcome is interpreted as evidence that financial literacy prevents intuitive risk-aversion reasoning only under highly favourable conditions, as is the case when no other task is competing for cognitive resources. In contrast, participants with higher levels of numeracy were consistently more prone to choose the gambling option in both experimental conditions. These results are discussed in the light of the opposition between classical dual-process theories and fuzzy-trace theories for intuitive decision making, suggesting that while some instances of expertise (as numeracy) are prone to support easily accessible gist representations, other expert skills (as financial literacy) depend upon deliberative processes. It is furthermore suggested that this dissociation between types of expert knowledge might depend on the degree to which they are generalizable across disparate settings. Finally, applied implications of the present study are discussed with a focus on how it informs financial regulators and the importance and limits of promoting financial literacy and general numeracy.

Keywords: decision making, cognitive load, financial literacy, numeracy

Procedia PDF Downloads 153