Search results for: outputs

Authors: Hamed Jafargholi

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Global warming presents an immense environmental risk, causing detrimental impacts on ecological systems and putting coastal areas at risk. Implementing efficient measures to minimize greenhouse gas emissions and the use of fossil fuels is essential to reducing global warming. Vapor compression heat pumps provide a practical method for harnessing energy from waste heat sources and reducing energy consumption. However, traditional working fluids used in these heat pumps generally contain a significant global warming potential (GWP), which might cause severe greenhouse effects if they are released. The goal of the emphasis on low-GWP (below 150) refrigerants is to further the vapor compression heat pumps. A classification system for vapor compression heat pumps is offered, with different boundaries based on the needed heat temperature and advancements in heat pump technology. A heat pump could be classified as a low temperature heat pump (LTHP), medium temperature heat pump (MTHP), high temperature heat pump (HTHP), or ultra-high temperature heat pump (UHTHP). The HTHP/UHTHP border is 160 °C, the MTHP/HTHP and LTHP/MTHP limits are 100 and 60 °C, respectively. The refrigerant is one of the most important parts of a vapor compression heat pump system. Presently, the main ways to choose a refrigerant are based on ozone depletion potential (ODP) and GWP, with GWP being the lowest possible value and ODP being zero. Pure low-GWP refrigerants, such as natural refrigerants (R718 and R744), hydrocarbons (R290, R600), hydrofluorocarbons (R152a and R161), hydrofluoroolefins (R1234yf, R1234ze(E)), and hydrochlorofluoroolefin (R1233zd(E)), were selected as candidates for vapor compression heat pump systems based on these selection principles. The performance, characteristics, and potential uses of these low-GWP refrigerants in heat pump systems are investigated in this paper. As vapor compression heat pumps with pure low-GWP refrigerants become more common, more and more low-grade heat can be recovered. This means that energy consumption would decrease. The research outputs showed that the refrigerants R718 for UHTHP application, R1233zd(E) for HTHP application, R600, R152a, R161, R1234ze(E) for MTHP, and R744, R290, and R1234yf for LTHP application are appropriate. The selection of an appropriate refrigerant should, in fact, take into consideration two different environmental and thermodynamic points of view. It might be argued that, depending on the situation, a trade-off between these two groups should constantly be considered. The environmental approach is now far stronger than it was previously, according to the European Union regulations. This will promote sustainable energy consumption and social development in addition to assisting in the reduction of greenhouse gas emissions and the management of global warming.

Keywords: vapor compression, global warming potential, heat pumps, greenhouse

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Authors: Spencer Rutherford, Shadi Saleh

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War and conflict negatively impact all facets of a health system; services cease to function, resources become depleted, and any semblance of governance is lost. Following cessation of conflict, the rebuilding process includes a wide array of international and local actors. During this period, stakeholders must contend with various trade-offs, including balancing sustainable outcomes with immediate health needs, introducing health reform measures while also increasing local capacity, and reconciling external assistance with local legitimacy. Compounding these factors are additional challenges, including coordination amongst stakeholders, the re-occurrence of conflict, and ulterior motives from donors and governments, to name a few. Therefore, the present paper evaluated health system development in three post-conflict countries over a 12-year timeline. Specifically, health policies, health inputs (such infrastructure and human resources), and measures of governance, from the post-conflict periods of Afghanistan, Cambodia, and Mozambique, were assessed against health outputs and other measures. All post-conflict countries experienced similar challenges when rebuilding the health sector, including; division and competition between donors, NGOs, and local institutions; urban and rural health inequalities; and the re-occurrence of conflict. However, countries also employed unique and effective mechanisms for reconstructing their health systems, including; government engagement of the NGO and private sector; integration of competing factions into the same workforce; and collaborative planning for health policy. Based on these findings, best-practice development strategies were determined and compiled into a 12-year framework. Briefly, during the initial stage of the post-conflict period, primary stakeholders should work quickly to draft a national health strategy in collaboration with the government, and focus on managing and coordinating NGOs through performance-based partnership agreements. With this scaffolding in place, the development community can then prioritize the reconstruction of primary health care centers, increasing and retaining health workers, and horizontal integration of immunization services. The final stages should then concentrate on transferring ownership of the health system national institutions, implementing sustainable financing mechanisms, and phasing-out NGO services. Overall, these findings contribute post-conflict health system development by evaluating the process holistically and along a timeline and can be of further use by healthcare managers, policy-makers, and other health professionals.

Keywords: Afghanistan, Cambodia, health system development, health system reconstruction, Mozambique, post-conflict, state-building

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Authors: Devika Nair, Sean Bellairs, Ken Evans

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Flow and erosion modeling provides an avenue for simulating the fine suspended sediment in surface water systems like streams and creeks. Fine suspended sediment is highly mobile, and many contaminants that may have been released by any sort of catchment disturbance attach themselves to these sediments. Therefore, a knowledge of fine suspended sediment transport is important in assessing contaminant transport. The CAESAR-Lisflood Landform Evolution Model, which includes a hydrologic model (TOPMODEL) and a hydraulic model (Lisflood), is being used to assess the sediment movement in tropical streams on account of a disturbance in the catchment of the creek and to determine the dynamics of sediment quantity in the creek through the years by simulating the model for future years. The accuracy of future simulations depends on the calibration and validation of the model to the past and present events. Calibration and validation of the model involve finding a combination of parameters of the model, which, when applied and simulated, gives model outputs similar to those observed for the real site scenario for corresponding input data. Calibrating the sediment output of the CAESAR-Lisflood model at the catchment level and using it for studying the equilibrium conditions of the landform is an area yet to be explored. Therefore, the aim of the study was to calibrate the CAESAR-Lisflood model and then validate it so that it could be run for future simulations to study how the landform evolves over time. To achieve this, the model was run for a rainfall event with a set of parameters, plus discharge and sediment data for the input point of the catchment, to analyze how similar the model output would behave when compared with the discharge and sediment data for the output point of the catchment. The model parameters were then adjusted until the model closely approximated the real site values of the catchment. It was then validated by running the model for a different set of events and checking that the model gave similar results to the real site values. The outcomes demonstrated that while the model can be calibrated to a greater extent for hydrology (discharge output) throughout the year, the sediment output calibration may be slightly improved by having the ability to change parameters to take into account the seasonal vegetation growth during the start and end of the wet season. This study is important to assess hydrology and sediment movement in seasonal biomes. The understanding of sediment-associated metal dispersion processes in rivers can be used in a practical way to help river basin managers more effectively control and remediate catchments affected by present and historical metal mining.

Keywords: erosion modelling, fine suspended sediments, hydrology, surface water systems

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Wenjun Hou, Marek Perkowski

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The Traveling Salesman problem is famous in computing and graph theory. In short, it asks for the Hamiltonian cycle of the least total weight in a given graph with N nodes. All variations on this problem, such as those with K-bounded-degree nodes, are classified as NP-complete in classical computing. Although several papers propose theoretical high-level designs of quantum algorithms for the Traveling Salesman Problem, no quantum circuit implementation of these algorithms has been created up to our best knowledge. In contrast to previous papers, the goal of this paper is not to optimize some abstract complexity measures based on the number of oracle iterations, but to be able to evaluate the real circuit and time costs of the quantum computer. Using the emerging quantum programming language Q# developed by Microsoft, which runs quantum circuits in a quantum computer simulation, an implementation of the bounded-degree problem and its respective quantum circuit were created. To apply Grover’s algorithm to this problem, a quantum oracle was designed, evaluating the cost of a particular set of edges in the graph as well as its validity as a Hamiltonian cycle. Repeating the Grover algorithm with an oracle that finds successively lower cost each time allows to transform the decision problem to an optimization problem, finding the minimum cost of Hamiltonian cycles. N log₂ K qubits are put into an equiprobablistic superposition by applying the Hadamard gate on each qubit. Within these N log₂ K qubits, the method uses an encoding in which every node is mapped to a set of its encoded edges. The oracle consists of several blocks of circuits: a custom-written edge weight adder, node index calculator, uniqueness checker, and comparator, which were all created using only quantum Toffoli gates, including its special forms, which are Feynman and Pauli X. The oracle begins by using the edge encodings specified by the qubits to calculate each node that this path visits and adding up the edge weights along the way. Next, the oracle uses the calculated nodes from the previous step and check that all the nodes are unique. Finally, the oracle checks that the calculated cost is less than the previously-calculated cost. By performing the oracle an optimal number of times, a correct answer can be generated with very high probability. The oracle of the Grover Algorithm is modified using the recalculated minimum cost value, and this procedure is repeated until the cost cannot be further reduced. This algorithm and circuit design have been verified, using several datasets, to generate correct outputs.

Keywords: quantum computing, quantum circuit optimization, quantum algorithms, hybrid quantum algorithms, quantum programming, Grover’s algorithm, traveling salesman problem, bounded-degree TSP, minimal cost, Q# language

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Authors: S. R. Dehghani, Y. S. Muzychka, G. F. Naterer

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The ice accretion of salt water on cold substrates creates brine-spongy ice. This type of ice is a mixture of pure ice and liquid brine. A real case of creation of this type of ice is superstructure icing which occurs on marine vessels and offshore structures in cold and harsh conditions. Transient heat transfer through this medium causes phase changes between brine pockets and pure ice. Salt rejection during the process of transient heat conduction increases the salinity of brine pockets to reach a local equilibrium state. In this process the only effect of passing heat through the medium is not changing the sensible heat of the ice and brine pockets; latent heat plays an important role and affects the mechanism of heat transfer. In this study, a new analytical model for evaluating heat transfer through brine-spongy ice is suggested. This model considers heat transfer and partial solidification and melting together. Properties of brine-spongy ice are obtained using properties of liquid brine and pure ice. A numerical solution using Method of Lines discretizes the medium to reach a set of ordinary differential equations. Boundary conditions are chosen using one of the applicable cases of this type of ice; one side is considered as a thermally isolated surface, and the other side is assumed to be suddenly affected by a constant temperature boundary. All cases are evaluated in temperatures between -20 C and the freezing point of brine-spongy ice. Solutions are conducted using different salinities from 5 to 60 ppt. Time steps and space intervals are chosen properly to maintain the most stable and fast solution. Variation of temperature, volume fraction of brine and brine salinity versus time are the most important outputs of this study. Results show that transient heat conduction through brine-spongy ice can create a various range of salinity of brine pockets from the initial salinity to that of 180 ppt. The rate of variation of temperature is found to be slower for high salinity cases. The maximum rate of heat transfer occurs at the start of the simulation. This rate decreases as time passes. Brine pockets are smaller at portions closer to the colder side than that of the warmer side. A the start of the solution, the numerical solution tends to increase instabilities. This is because of sharp variation of temperature at the start of the process. Changing the intervals improves the unstable situation. The analytical model using a numerical scheme is capable of predicting thermal behavior of brine spongy ice. This model and numerical solutions are important for modeling the process of freezing of salt water and ice accretion on cold structures.

Keywords: method of lines, brine-spongy ice, heat conduction, salt water

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

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Authors: Aditi Madan, Jayant Kumar Routray

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Purpose: Over the years flood related risks have compounded due to increasing vulnerability caused by rapid urbanisation and growing population. This increase is an indication of the need for enhancing the preparedness of institutions to respond to floods. The study describes disaster management structure and its linkages with institutions involved in managing disasters. It addresses issues and challenges associated with readiness of disaster management institutions to respond to floods. It suggests policy options for enhancing the current state of readiness of institutions to respond by considering factors like institutional, manpower, financial, technical, leadership & networking, training and awareness programs, monitoring and evaluation. Methodology: The study is based on qualitative data with statements and outputs from primary and secondary sources to understand the institutional framework for disaster management in India. Primary data included field visits, interviews with officials from institutions managing disasters and the affected community to identify the challenges faced in engaging national, state, district and local level institutions in managing disasters. For focus group discussions, meetings were held with district project officers and coordinators, local officials, community based organisation, civil defence volunteers and community heads. These discussions were held to identify the challenges associated with preparedness to respond of institutions to floods. Findings: Results show that disasters are handled by district authority and the role of local institutions is limited to a reactive role during disaster. Data also indicates that although the existing institutional setup is well coordinated at the district level but needs improvement at the local level. Wide variations exist in awareness and perception among the officials engaged in managing disasters. Additionally, their roles and responsibilities need to be clearly defined with adequate budget and dedicated permanent staff for managing disasters. Institutions need to utilise the existing manpower through proper delegation of work. Originality: The study suggests that disaster risk reduction needs to focus more towards inclusivity of the local urban bodies. Wide variations exist in awareness and perception among the officials engaged in managing disasters. In order to ensure community participation, it is important to address their social and economic problems since such issues can overshadow attempts made for reducing risks. Thus, this paper suggests development of direct linkages among institutions and community for enhancing preparedness to respond to floods.

Keywords: preparedness, response, disaster, flood, community, institution

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: Jaroslav Kraus

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Spatial information about demographic processes are a standard part of outputs in the Czech Republic. That was also the case of Population and Housing Census which was held on 2011. This is a starting point for a follow up study devoted to two basic types of households: single person households and households of one completed family. Single person households and one family households create more than 80 percent of all households, but the share and spatial structure is in long-term changing. The increase of single households is results of long-term fertility decrease and divorce increase, but also possibility of separate living. There are regions in the Czech Republic with traditional demographic behavior, and regions like capital Prague and some others with changing pattern. Population census is based - according to international standards - on the concept of currently living population. Three types of geospatial approaches will be used for analysis: (i) firstly measures of geographic distribution, (ii) secondly mapping clusters to identify the locations of statistically significant hot spots, cold spots, spatial outliers, and similar features and (iii) finally analyzing pattern approach as a starting point for more in-depth analyses (geospatial regression) in the future will be also applied. For analysis of this type of data, number of households by types should be distinct objects. All events in a meaningful delimited study region (e.g. municipalities) will be included in an analysis. Commonly produced measures of central tendency and spread will include: identification of the location of the center of the point set (by NUTS3 level); identification of the median center and standard distance, weighted standard distance and standard deviational ellipses will be also used. Identifying that clustering exists in census households datasets does not provide a detailed picture of the nature and pattern of clustering but will be helpful to apply simple hot-spot (and cold spot) identification techniques to such datasets. Once the spatial structure of households will be determined, any particular measure of autocorrelation can be constructed by defining a way of measuring the difference between location attribute values. The most widely used measure is Moran’s I that will be applied to municipal units where numerical ratio is calculated. Local statistics arise naturally out of any of the methods for measuring spatial autocorrelation and will be applied to development of localized variants of almost any standard summary statistic. Local Moran’s I will give an indication of household data homogeneity and diversity on a municipal level.

Keywords: census, geo-demography, households, the Czech Republic

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Authors: Sidharth Talan, Sanjay Kumar Sharma, Eoin Joseph Wallace, Nikita Agrawal

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Underground mining is at the core of rapidly evolving metals and minerals sector due to the increasing mineral consumption globally. Even though the surface mines are still more abundant on earth, the scales of industry are slowly tipping towards underground mining due to rising depth and complexities of orebodies. Thus, the efficient and productive functioning of underground operations depends significantly on the synchronized performance of key elements such as operating site, mining equipment, manpower and mine services. Production drilling is the process of conducting long hole drilling for the purpose of charging and blasting these holes for the production of ore in underground metal mines. Thus, production drilling is the crucial segment in the underground metal mining value chain. This paper presents the process mapping tool to evaluate the production drilling process in the underground metal mining operation by dividing the given process into three segments namely Input, Process and Output. The three segments are further segregated into factors and sub-factors. As per the study, the major input factors crucial for the efficient functioning of production drilling process are power, drilling water, geotechnical support of the drilling site, skilled drilling operators, services installation crew, oils and drill accessories for drilling machine, survey markings at drill site, proper housekeeping, regular maintenance of drill machine, suitable transportation for reaching the drilling site and finally proper ventilation. The major outputs for the production drilling process are ore, waste as a result of dilution, timely reporting and investigation of unsafe practices, optimized process time and finally well fragmented blasted material within specifications set by the mining company. The paper also exhibits the drilling loss matrix, which is utilized to appraise the loss in planned production meters per day in a mine on account of availability loss in the machine due to breakdowns, underutilization of the machine and productivity loss in the machine measured in drilling meters per unit of percussion hour with respect to its planned productivity for the day. The given three losses would be essential to detect the bottlenecks in the process map of production drilling operation so as to instigate the action plan to suppress or prevent the causes leading to the operational performance deficiency. The given tool is beneficial to mine management to focus on the critical factors negatively impacting the production drilling operation and design necessary operational and maintenance strategies to mitigate them. 

Keywords: process map, drilling loss matrix, SIPOC, productivity, percussion rate

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Authors: William Creighton, Jan Smitheram

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Queer discourse has been tied to a middle-class, urban-centric, white approach to the discussion of queerness. In doing so, the multilayeredness of queer existence has been washed away in favour of palatable queer occupation. This paper uses design to explore a queer anti-urbanist approach to facilitate a more egalitarian architectural occupancy. Scott Herring’s work on queer anti-urbanism is key to this approach. Herring redeploys anti-urbanism from its historical understanding of open hostility, rejection and desire to destroy the city towards a mode of queer critique that counters normative ideals of homonormative metronormative gay lifestyles. He questions how queer identity has been closed down into a more diminutive frame where those who do not fit within this frame are subjected to persecution or silenced through their absence. We extend these ideas through design to ask how a queer anti-urbanist approach facilitates a more egalitarian architectural occupancy. Following a “design as research” methodology, the design outputs allow a vehicle to ask how we might live, otherwise, in architectural space. A design as research methodologically is a process of questioning, designing and reflecting – in a non-linear, iterative approach – establishes itself through three projects, each increasing in scale and complexity. Each of the three scales tackled a different body relationship. The project began exploring the relations between body to body, body to known others, and body to unknown others. Moving through increasing scales was not to privilege the objective, the public and the large scale; instead, ‘intra-scaling’ acts as a tool to re-think how scale reproduces normative ideas of the identity of space. There was a queering of scale. Through this approach, the results were an installation that brings two people together to co-author space where the installation distorts the sensory experience and forces a more intimate and interconnected experience challenging our socialized proxemics: knees might touch. To queer the home, the installation was used as a drawing device, a tool to study and challenge spatial perception, drawing convention, and as a way to process practical information about the site and existing house – the device became a tool to embrace the spontaneous. The final design proposal operates as a multi-scalar boundary-crossing through “private” and “public” to support kinship through communal labour, queer relationality and mooring. The resulting design works to set adrift bodies in a sea of sensations through a mix of pleasure programmes. To conclude, through three design proposals, this design research creates a relationship between queer anti-urbanism and design. It asserts that queering the design process and outcome allows a more inclusive way to consider place, space and belonging. The projects lend to a queer relationality and interdependence by making spaces that support the unsettled, out-of-place, but is it queer enough?

Keywords: queer, queer anti-urbanism, design as research, design

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Authors: D. Kakulia, L. Shoshiashvili, G. Sapharishvili

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The results of the study are related to the direction of plastic mine detection research using electromagnetic induction, the development of appropriate equipment, and the evaluation of expected results. Electromagnetic induction sensing is effectively used in the detection of metal objects in the soil and in the discrimination of unexploded ordnances. Metal objects interact well with a low-frequency alternating magnetic field. Their electromagnetic response can be detected at the low-frequency range even when they are placed in the ground. Detection of plastic things such as plastic mines by electromagnetic induction is associated with difficulties. The interaction of non-conducting bodies or low-conductive objects with a low-frequency alternating magnetic field is very weak. At the high-frequency range where already wave processes take place, the interaction increases. Interactions with other distant objects also increase. A complex interference picture is formed, and extraction of useful information also meets difficulties. Sensing by electromagnetic induction at the intermediate MHz frequency range is the subject of research. The concept of detecting plastic mines in this range can be based on the study of the electromagnetic response of non-conductive cavity in a low-conductivity environment or the detection of small metal components in plastic mines, taking into account constructive features. The detector node based on the amplitude and phase detector 'Analog Devices ad8302' has been developed for experimental studies. The node has two inputs. At one of the inputs, the node receives a sinusoidal signal from the generator, to which a transmitting coil is also connected. The receiver coil is attached to the second input of the node. The additional circuit provides an option to amplify the signal output from the receiver coil by 20 dB. The node has two outputs. The voltages obtained at the output reflect the ratio of the amplitudes and the phase difference of the input harmonic signals. Experimental measurements were performed in different positions of the transmitter and receiver coils at the frequency range 1-20 MHz. Arbitrary/Function Generator Tektronix AFG3052C and the eight-channel high-resolution oscilloscope PICOSCOPE 4824 were used in the experiments. Experimental measurements were also performed with a low-conductive test object. The results of the measurements and comparative analysis show the capabilities of the simple detector node and the prospects for its further development in this direction. The results of the experimental measurements are compared and analyzed with the results of appropriate computer modeling based on the method of auxiliary sources (MAS). The experimental measurements are driven using the MATLAB environment. Acknowledgment -This work was supported by Shota Rustaveli National Science Foundation (SRNSF) (Grant number: NFR 17_523).

Keywords: EM induction sensing, detector, plastic mines, remote sensing

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Authors: Xuan (Iris) Li, Jenny Zhengye Hou, Greg Hearn

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Food waste is a global issue, with an estimated 30% to 50% of food created never being consumed. Therefore, it is vital to reduce food waste and convert wasted food into recyclable outputs. TikTok provides a simple way of creating and duetting videos in just a few steps by using templates with the same sound/vision/caption effects to produce personalized content – this is called a duet, which is revealing to study the impact of TikTok on wasting more food or saving food. The research focuses on examining food-related content on TikTok, with particular attention paid to two distinct themes, food waste pranks and food-saving practices, to understand the potential impacts of these themes on adolescents and their attitudes toward sustainable food consumption practices. Specifically, the analysis explores how TikTok content related to food waste and/or food saving may contribute to the normalization and promotion of either positive or negative food behaviours among young viewers. The research employed content analysis and semi-structured interviews to understand what factors contribute to the difference in popularity between food pranks and food-saving videos and insights from the former can be applied to the latter to increase their communication effectiveness. The first category of food content on TikTok under examination pertains to food waste, including videos featuring pranks and mukbang. These forms of content have the potential to normalize or even encourage food waste behaviours among adolescents, exacerbating the already significant food waste problem. The second category of TikTok food content under examination relates to food saving, for example, videos teaching viewers how to maximize the use of food to reduce waste. This type of content can potentially empower adolescents to act against food waste and foster positive and sustainable food practices in their communities. The initial findings of the study suggest that TikTok content related to pranks appears to be more popular among viewers than content focused on teaching people how to save food. Additionally, these types of videos are gaining fans at a faster rate than content promoting more sustainable food practices. However, we argue there is a great potential for social media platforms like TikTok to play an educative role in promoting positive behaviour change among young people by sharing engaging content suitable to target audiences. This research serves as the first to investigate the potential utility of TikTok in food waste reduction and underscores the important role social media platforms can play in promoting sustainable food practices. The findings will help governments, organizations, and communities promote tailored and effective interventions to reduce food waste and help achieve the United Nations’ sustainable development goal of halving food waste by 2030.

Keywords: food waste reduction, behaviour, social media, TikTok, adolescents

Procedia PDF Downloads 67

Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

Procedia PDF Downloads 129

Authors: Ali Ashtiani, Hamid Shirazi

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This paper reviews the status of existing practice and research related to measuring pavement cracking and using crack density as a pavement surface evaluation protocol. Crack density for pavement evaluation is currently not widely used within the airport community and its use by the highway community is limited. However, surface cracking is a distress that is closely monitored by airport staff and significantly influences the development of maintenance, rehabilitation and reconstruction plans for airport pavements. Therefore crack density has the potential to become an important indicator of pavement condition if the type, severity and extent of surface cracking can be accurately measured. A pavement distress survey is an essential component of any pavement assessment. Manual crack surveying has been widely used for decades to measure pavement performance. However, the accuracy and precision of manual surveys can vary depending upon the surveyor and performing surveys may disrupt normal operations. Given the variability of manual surveys, this method has shown inconsistencies in distress classification and measurement. This can potentially impact the planning for pavement maintenance, rehabilitation and reconstruction and the associated funding strategies. A substantial effort has been devoted for the past 20 years to reduce the human intervention and the error associated with it by moving toward automated distress collection methods. The automated methods refer to the systems that identify, classify and quantify pavement distresses through processes that require no or very minimal human intervention. This principally involves the use of a digital recognition software to analyze and characterize pavement distresses. The lack of established protocols for measurement and classification of pavement cracks captured using digital images is a challenge to developing a reliable automated system for distress assessment. Variations in types and severity of distresses, different pavement surface textures and colors and presence of pavement joints and edges all complicate automated image processing and crack measurement and classification. This paper summarizes the commercially available systems and technologies for automated pavement distress evaluation. A comprehensive automated pavement distress survey involves collection, interpretation, and processing of the surface images to identify the type, quantity and severity of the surface distresses. The outputs can be used to quantitatively calculate the crack density. The systems for automated distress survey using digital images reviewed in this paper can assist the airport industry in the development of a pavement evaluation protocol based on crack density. Analysis of automated distress survey data can lead to a crack density index. This index can be used as a means of assessing pavement condition and to predict pavement performance. This can be used by airport owners to determine the type of pavement maintenance and rehabilitation in a more consistent way.

Keywords: airport pavement management, crack density, pavement evaluation, pavement management

Procedia PDF Downloads 179

Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

Procedia PDF Downloads 123

Authors: K. Mellou, G. Anastopoulos, T. Zakinthinos, C. Botsi, A. Terzidis

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‘PHILOS – Emergency health response to refugee crisis’ is a programme of the Greek Ministry of Health, implemented by the Hellenic Center for Disease Control and Prevention (HCDCP). The programme is funded by the Asylum, Migration and Integration Fund (AMIF) of EU’s DG Migration and Home Affairs. With the EU Member States accepting, the last period, accelerating migration flows, Greece inevitably occupies a prominent position in the migratory map due to this geographical location. The main objectives of the programme are a) reinforcement of the capacity of the public health system and enhancement of the epidemiological surveillance in order to cover refugees/migrant population, b) provision of on-site primary health care and psychological support services, and c) strengthening of national health care system task-force. The basic methods for achieving the aforementioned goals are: a) implementation of syndromic surveillance system at camps and enhancement of public health response with the use of mobile medical units (Sub-action A), b) enhancement of health care services inside the camps via increasing human resources and implementing standard operating procedures (Sub-action B), and c) reinforcement of the national health care system (primary healthcare units, hospitals, and emergency care spots) of affected regions with personnel (Sub-action C). As a result, 58 health professionals were recruited under sub-action 2 and 10 mobile unit teams (one or two at each health region) were formed. The main actions taken so far by the mobile units are the evaluation, of syndromic surveillance, of living conditions at camps and medical services. Also, vaccination coverage of children population was assessed, and more than 600 catch-up vaccinations were performed by the end of June 2017. Mobile units supported transportation of refugees/migrants from camps to medical services reducing the load of the National Center for Emergency Care (more than 350 transportations performed). The total number of health professionals (MD, nurses, etc.) placed at camps was 104. Common practices were implemented in the recording and collection of psychological and medical history forms at the camps. Protocols regarding maternity care, gender based violence and handling of violent incidents were produced and distributed at personnel working at camps. Finally, 290 health care professionals were placed at primary healthcare units, public hospitals and the National Center for Emergency Care at affected regions. The program has, also, supported training activities inside the camps and resulted to better coordination of offered services on site.

Keywords: migrants, refugees, public health, syndromic surveillance, national health care system, primary care, emergency health response

Procedia PDF Downloads 190

Authors: Krishmali N. Ekanayake, Brendan J. Holland, Colin J. Barrow, Rick Wood

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Globally, more than one-third of all food produced is lost or wasted, equating to 1.3 billion tonnes per year. Around 31.2 million tonnes of food waste are generated across the production, supply, and consumption chain in Australia. Generally, the food waste management processes adopt environmental-friendly and more sustainable approaches such as composting, anerobic digestion and energy implemented technologies. However, unavoidable, and non-recyclable food waste ends up as landfilling and incineration that involve many undesirable impacts and challenges on the environment. A biorefinery approach contributes to a waste-minimising circular economy by converting food and other organic biomass waste into valuable outputs, including feeds, nutrition, fertilisers, and biomaterials. As a solution, Green Eco Technologies has developed a food waste treatment process using WasteMaster system. The system uses charged oxygen and moderate temperatures to convert food waste, without bacteria, additives, or water, into a virtually odour-free, much reduced quantity of reusable residual material. In the context of a biorefinery, the WasteMaster dries and mills food waste into a form suitable for storage or downstream extraction/separation/concentration to create products. The focus of the study is to determine the nutritional composition of WasteMaster processed residue to potential develop aquafeed ingredients. The global aquafeed industry is projected to reach a high value market in future, which has shown high demand for the aquafeed products. Therefore, food waste can be utilized for aquaculture feed development by reducing landfill. This framework will lessen the requirement of raw crops cultivation for aquafeed development and reduce the aquaculture footprint. In the present study, the nutritional elements of processed residue are consistent with the input food waste type, which has shown that the WasteMaster is not affecting the expected nutritional distribution. The macronutrient retention values of protein, lipid, and nitrogen free extract (NFE) are detected >85%, >80%, and >95% respectively. The sensitive food components including omega 3 and omega 6 fatty acids, amino acids, and phenolic compounds have been found intact in each residue material. Preliminary analysis suggests a price comparability with current aquafeed ingredient cost making the economic feasibility. The results suggest high potentiality of aquafeed development as 5 to 10% of the ingredients to replace/partially substitute other less sustainable ingredients across biorefinery setting. Our aim is to improve the sustainability of aquaculture and reduce the environmental impacts of food waste.

Keywords: biorefinery, ffood waste residue, input, wasteMaster

Procedia PDF Downloads 52

Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

Procedia PDF Downloads 19

Authors: Fatemeh Faramarzi, Hosein Mahjoob

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Building dams on rivers for utilization of water resources causes problems in hydrodynamic equilibrium and results in leaving all or part of the sediments carried by water in dam reservoir. This phenomenon has also significant impacts on water and sediment flow regime and in the long term can cause morphological changes in the environment surrounding the river, reducing the useful life of the reservoir which threatens sustainable development through inefficient management of water resources. In the past, empirical methods were used to predict the sedimentation amount in dam reservoirs and to estimate its efficient lifetime. But recently the mathematical and computational models are widely used in sedimentation studies in dam reservoirs as a suitable tool. These models usually solve the equations using finite element method. This study compares the results from tow software packages, GSTARS4 & HEC-6, in the prediction of the sedimentation amount in Dez dam, southern Iran. The model provides a one-dimensional, steady-state simulation of sediment deposition and erosion by solving the equations of momentum, flow and sediment continuity and sediment transport. GSTARS4 (Generalized Sediment Transport Model for Alluvial River Simulation) which is based on a one-dimensional mathematical model that simulates bed changes in both longitudinal and transverse directions by using flow tubes in a quasi-two-dimensional scheme to calibrate a period of 47 years and forecast the next 47 years of sedimentation in Dez Dam, Southern Iran. This dam is among the highest dams all over the world (with its 203 m height), and irrigates more than 125000 square hectares of downstream lands and plays a major role in flood control in the region. The input data including geometry, hydraulic and sedimentary data, starts from 1955 to 2003 on a daily basis. To predict future river discharge, in this research, the time series data were assumed to be repeated after 47 years. Finally, the obtained result was very satisfactory in the delta region so that the output from GSTARS4 was almost identical to the hydrographic profile in 2003. In the Dez dam due to the long (65 km) and a large tank, the vertical currents are dominant causing the calculations by the above-mentioned method to be inaccurate. To solve this problem, we used the empirical reduction method to calculate the sedimentation in the downstream area which led to very good answers. Thus, we demonstrated that by combining these two methods a very suitable model for sedimentation in Dez dam for the study period can be obtained. The present study demonstrated successfully that the outputs of both methods are the same.

Keywords: Dez Dam, prediction, sedimentation, water resources, computational models, finite element method, GSTARS4, HEC-6

Procedia PDF Downloads 303

Authors: M. K. Sheikh, Y. M. Laghari., P. K. Lashari., N. T. Narejo

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The Indus River is one of the longest important rivers of the world in Asia that flows southward through Pakistan, merges into the Arabian Sea near the port city of Karachi in Sindh Province, and forms the Indus Delta. Fish are an important resource for humans worldwide, especially as food. In fish, healthy nutriments are present which are not found in any other meat source because it have a huge quantity of omega- 3 fatty acids, which are very essential for the human body. Ichthyologic surveys were conducted to explore the diversity of freshwater fishes, distribution, abundance and current status of the fishes at different spatial scale of the downstream, Indus River. Total eight stations were selected namely Railo Miyan (RM), Karokho (Kk), Khanpur (Kp), Mullakatiyar (Mk), Wasi Malook Shah (WMS), Branch Morie (BM), Sujawal (Sj) and Jangseer (JS). The study was carried in the period of January 2016 to December 2019 to identify River and biodiversity threats and to suggest recommendations for conservation. The data were analysed by different population diversity index. Altogether, 124 species were recorded belonging to 12 Orders and 43 Families from the downstream of Indus River. Among 124 species, 29% belong to high commercial value and 35% were trash fishes. 31% of fishes were identified as marine/estuarine origin (migratory) and 05% were exotic fish species. Perciformes is the most predominated order, contributing to 41% of families. Among 43 families, the family Cyprinidae was the richest family from all localities of downstream, represented by 24% of fish species demonstrating a significant dominance in the number of species. A significant difference was observed for species abundance in between all sites, the maximum abundance species were found at first location RM having 115 species and minimum observed at the last station JS 56 genera. In the recorded Ichthyofauna, seven groups were found according to the International Union for Conservation of Nature status (IUCN), where a high species ratio was collected, in Least Concern (LC) having 94 species, 11 were found as not evaluated (NE), whereas 8 was identified as near threatened (NT), 1 was recorded as critically endangered (CR), 11 were collected as data deficient (DD), and while 8 was observed as vulnerable (VU) and 3 endangered (EN) species. Different diversity index has been used extensively in environmental studies to estimate the species richness and abundance of ecosystems outputs of their wellness; a positive environment (biodiversity rich) with species at RM had an environmental wellness and biodiversity levels of 4.566% while a negative control environment (biodiversity poor) on last station JS had an environmental wellness and biodiversity levels of 3.931%. The status of fish biodiversity and river has been found under serious threat. Due to the lower diversity of fishes, it became not only venerable for fish but also risky for fishermen. Necessary steps are recommended to protect the biodiversity by conducting further conservative research in this area.

Keywords: ichthyofaunal biodiversity, threatened species, diversity index, Indus River downstream

Procedia PDF Downloads 163

Authors: Rojan Dahal

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One Health refers to a collaborative effort between multiple disciplines - locally, nationally, and globally - to attain optimal health. Although there were unprecedented intersectoral alliances between the animal and human health sectors during the avian influenza outbreak, there are different views and perceptions concerning institutionalizing One Health in South Asia. It is likely a structural barrier between the relevant professionals working in different entities or ministries when it comes to collaborating on One Health actions regarding zoonotic diseases. Politicians and the public will likely need to invest large amounts of money, demonstrate political will, and understand how One Health works to overcome these barriers. One Health might be hard to invest in South Asian countries, where the benefits are based primarily on models and projections and where numerous issues related to development and health need urgent attention. The other potential barrier to enabling the One Health concept in responding to zoonotic diseases is a failure to represent One Health in zoonotic disease control and prevention measures in the national health policy, which is a critical component of institutionalizing the One Health concept. One Health cannot be institutionalized without acknowledging the linkages between animal, human, and environmental sectors in dealing with zoonotic diseases. Efforts have been made in the past to prepare a preparedness plan for One Health implementation, but little has been done to establish a policy environment to institutionalize One Health. It is often assumed that health policy refers specifically to medical care issues and health care services. When drafting, reviewing, and redrafting the policy, it is important to engage a wide range of stakeholders. One Health institutionalization may also be hindered by the interplay between One Health professionals and bureaucratic inertia in defining the priorities of diseases due to competing interests on limited budgets. There is a possibility that policymakers do not recognize the importance of veterinary professionals in preventing human diseases originating in animals. Compared to veterinary medicine, the human health sector has produced most of the investment and research outputs related to zoonotic diseases. The public health profession may consider itself superior to the veterinary profession. Zoonotic diseases might not be recognized as threats to human health, impeding integrated policies. The effort of One Health institutionalization remained only among the donor agencies and multi-sectoral organizations. There is a need for strong political will and state capacity to overcome the existing institutional, financial, and professional barriers for its effective implementation. There is a need to assess the structural challenges, policy challenges, and the attitude of the professional working in the multiple disciplines related to One Health. Limited research has been conducted to identify the reasons behind the barriers to institutionalizing the One Health concept in South Asia. Institutionalizing One Health in responding to zoonotic diseases breaks down silos and integrates animals, humans, and the environment.

Keywords: one health, institutionalization, South Asia, institutionalizations

Procedia PDF Downloads 80

Authors: E. Omanya, E. Mueni, G. Makau, M. Kariuki

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HIV infection is the strongest risk factor for a person to develop TB. Isoniazid preventive therapy (IPT) for People Living with HIV (PLWHIV) not only reduces the individual patients’ risk of developing active TB but mitigates cross infection. In Kenya, IPT for six months was recommended through the National TB, Leprosy and Lung Disease Program to treat latent TB. In spite of this recommendation by the national government, uptake of IPT among PLHIV remained low in Kenya by the end of 2015. The USAID/Kenya and East Africa Afya Jijini project, which supports 42 TBHIV health facilities in Nairobi County, began addressing low uptake of IPT through Quality Improvement (QI) teams set up at the facility level. Quality is characterized by WHO as one of the four main connectors between health systems building blocks and health systems outputs. Afya Jijini implements the Kenya Quality Model for Health, which involves QI teams being formed at the county, sub-county and facility levels. The teams review facility performance to identify gaps in service delivery and use QI tools to monitor and improve performance. Afya Jijini supported the formation of these teams in 42 facilities and built the teams’ capacity to review data and use QI principles to identify and address performance gaps. When the QI teams began working on improving IPT uptake among PLHIV, uptake was at 31.8%. The teams first conducted a root cause analysis using cause and effect diagrams, which help the teams to brainstorm on and to identify barriers to IPT uptake among PLHIV at the facility level. This is a participatory process where program staff provides technical support to the QI teams in problem identification and problem-solving. The gaps identified were inadequate knowledge and skills on the use of IPT among health care workers, lack of awareness of IPT by patients, inadequate monitoring and evaluation tools, and poor quantification and forecasting of IPT commodities. In response, Afya Jijini trained over 300 health care workers on the administration of IPT, supported patient education, supported quantification and forecasting of IPT commodities, and provided IPT data collection tools to help facilities monitor their performance. The facility QI teams conducted monthly meetings to monitor progress on implementation of IPT and took corrective action when necessary. IPT uptake improved from 31.8% to 61.2% during the second year of the Afya Jijini project and improved to 80.1% during the third year of the project’s support. Use of QI teams and root cause analysis to identify and address service delivery gaps, in addition to targeted program interventions and continual performance reviews, can be successful in increasing TB related service delivery uptake at health facilities.

Keywords: isoniazid, quality, health care workers, people leaving with HIV

Procedia PDF Downloads 89

Authors: Belinda du Plooy, Ruth Albertyn, Christel Troskie-De Bruin, Ella Belcher

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In the academy, scholarliness or intellectual craftsmanship is considered the highest level of achievement, culminating in being consistently successfully published in impactful, peer-reviewed journals and books. Scholarliness implies rigorous methods, systematic exposition, in-depth analysis and evaluation, and the highest level of critical engagement and reflexivity. However, being a scholar does not happen automatically when one becomes an academic or completes graduate studies. A graduate qualification is an indication of one’s level of research competence but does not necessarily prepare one for the type of scholarly writing for publication required after a postgraduate qualification has been conferred. Scholarly writing for publication requires a high-level skillset and a specific mindset, which must be intentionally developed. The rite of passage to become a scholar is an iterative process with liminal spaces, thresholds, transitions, and transformations. The journey from researcher to published author is often fraught with rejection, insecurity, and disappointment and requires resilience and tenacity from those who eventually triumph. It cannot be achieved without support, guidance, and mentorship. In this article, the authors use collective auto-ethnography (CAE) to describe the phases and types of liminality encountered during the liminal journey toward scholarship. The authors speak as long-time facilitators of Writing for Academic Publication (WfAP) capacity development events (training workshops and writing retreats) presented at South African universities. Their WfAP facilitation practice is structured around experiential learning principles that allow them to act as critical reading partners and reflective witnesses for the writer-participants of their WfAP events. They identify three essential facilitation features for the effective holding of a generative, liminal, and transformational writing space for novice academic writers in order to enable their safe passage through the various liminal spaces they encounter during their scholarly development journey. These features are that facilitators should be agents of disruption and liminality while also guiding writers through these liminal spaces; that there should be a sense of mutual trust and respect, shared responsibility and accountability in order for writers to produce publication-worthy scholarly work; and that this can only be accomplished with the continued application of high levels of sensitivity and discernment by WfAP facilitators. These are key features for successful WfAP scholarship training events, where focused, individual input triggers personal and professional transformational experiences, which in turn translate into high-quality scholarly outputs.

Keywords: academic writing, liminality, scholarship, scholarliness, threshold experience, writing for publication

Procedia PDF Downloads 36

Authors: Moira Cordiner

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As a result of an Australian university approving a policy to improve the quality of assessment practices, as an academic developer (AD) with expertise in criterion-referenced assessment commenced in 2008. The four-year appointment was to support 40 'champions' in their Schools. This presentation is based on the experiences of a group of Chemistry academics who worked with the AD to develop and implement an honours dissertation rubric. Honours is a research year following a three-year undergraduate year. If the standard of the student's work is high enough (mainly the dissertation) then the student can commence a PhD. What became clear during the process was that much more was at stake than just the successful development and trial of the rubric, including academics' reputations, university rankings and research outputs. Working with the champion-Head of School(HOS) and the honours coordinator, the AD helped them adapt an honours rubric that she had helped create and trial successfully for another Science discipline. A year of many meetings and complex power plays between the two academics finally resulted in a version that was critiqued by the Chemistry teaching and learning committee. Accompanying the rubric was an explanation of grading rules plus a list of supervisor expectations to explain to students how the rubric was used for grading. Further refinements were made until all staff were satisfied. It was trialled successfully in 2011, then small changes made. It was adapted and implemented for Medicine honours with her help in 2012. Despite coming to consensus about statements of quality in the rubric, a few academics found it challenging matching these to the dissertations and allocating a grade. They had had no time to undertake training to do this, or make overt their implicit criteria and standards, which some admitted they were using - 'I know what a first class is'. Other factors affecting grading included: the small School where all supervisors knew each other and the students, meant that friendships and collegiality were at stake if low grades were given; no external examiners were appointed-all were internal with the potential for bias; supervisors’ reputations were at stake if their students did not receive a good grade; the School's reputation was also at risk if insufficient honours students qualified for PhD entry; and research output was jeopardised without enough honours students to work on supervisors’ projects. A further complication during the study was a restructure of the university and retrenchments, with pressure to increase research output as world rankings assumed greater importance to senior management. In conclusion, much more was at stake than developing a usable rubric. The HOS had to be seen to champion the 'new' assessment practice while balancing institutional demands for increased research output and ensuring as many honours dissertations as possible met high standards, so that eventually the percentage of PhD completions and research output rose. It is therefore in the institution's best interest for this cycle to be maintained as it affects rankings and reputations. In this context, are rubrics redundant?

Keywords: explicit and implicit standards, judging quality, university rankings, research reputations

Procedia PDF Downloads 325

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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Authors: Oliver Bertram, Leonel Akoto Chama

Abstract:

In today's civil transport aircraft, the design of flight control systems is based on the experience gained from previous aircraft configurations with a clear distinction between primary and secondary flight control functions for controlling the aircraft altitude and trajectory. Significant system improvements are now seen particularly in multifunctional moveable concepts where the flight control functions are no longer considered separate but integral. This allows new functions to be implemented in order to improve the overall aircraft performance. However, the classical design process of flight controls is sequential and insufficiently interdisciplinary. In particular, the systems discipline is involved only rudimentarily in the early phase. In many cases, the task of systems design is limited to meeting the requirements of the upstream disciplines, which may lead to integration problems later. For this reason, approaching design with an incremental development is required to reduce the risk of a complete redesign. Although the potential and the path to multifunctional moveable concepts are shown, the complete re-engineering of aircraft concepts with less classic moveable concepts is associated with a considerable risk for the design due to the lack of design methods. This represents an obstacle to major leaps in technology. This gap in state of the art is even further increased if, in the future, unconventional aircraft configurations shall be considered, where no reference data or architectures are available. This means that the use of the above-mentioned experience-based approach used for conventional configurations is limited and not applicable to the next generation of aircraft. In particular, there is a need for methods and tools for a rapid trade-off between new multifunctional flight control systems architectures. To close this gap in the state of the art, an integrated system-driven design process for multifunctional flight control systems of non-classical aircraft configurations will be presented. The overall goal of the design process is to find optimal solutions for single or combined target criteria in a fast process from the very large solution space for the flight control system. In contrast to the state of the art, all disciplines are involved for a holistic design in an integrated rather than a sequential process. To emphasize the systems discipline, this paper focuses on the methodology for designing moveable actuation systems in the context of this integrated design process of multifunctional moveables. The methodology includes different approaches for creating system architectures, component design methods as well as the necessary process outputs to evaluate the systems. An application example of a reference configuration is used to demonstrate the process and validate the results. For this, new unconventional hydraulic and electrical flight control system architectures are calculated which result from the higher requirements for multifunctional moveable concept. In addition to typical key performance indicators such as mass and required power requirements, the results regarding the feasibility and wing integration aspects of the system components are examined and discussed here. This is intended to show how the systems design can influence and drive the wing and overall aircraft design.

Keywords: actuation systems, flight control surfaces, multi-functional movables, wing design process

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Authors: Rodchares Hanrinth, Theerapong Srisil, Peeraya Sriphong, Pawich Paktipat

Abstract:

The trigger tool is the low-cost, low-tech method to detect adverse events through clues called triggers. The Institute for Healthcare Improvement (IHI) has developed the Global Trigger Tool for measuring and preventing adverse events. However, this tool is not specific for detecting adverse drug events. The pharmacy-based trigger tool is needed to detect adverse drug events (ADEs). Group concept mapping is an effective method for conceptualizing various ideas from diverse stakeholders. This technique was used to identify a pharmacy-based trigger to detect adverse drug events (ADEs). The aim of this study was to involve the pharmacists in conceptualizing, developing, and prioritizing a feasible trigger tool to detect adverse drug events in a provincial hospital, the northeastern part of Thailand. The study was conducted during the 6-month period between April 1 and September 30, 2017. Study participants involved 20 pharmacists (17 hospital pharmacists and 3 pharmacy lecturers) engaging in three concept mapping workshops. In this meeting, the concept mapping technique created by Trochim, a highly constructed qualitative group technic for idea generating and sharing, was used to produce and construct participants' views on what triggers were potential to detect ADEs. During the workshops, participants (n = 20) were asked to individually rate the feasibility and potentiality of each trigger and to group them into relevant categories to enable multidimensional scaling and hierarchical cluster analysis. The outputs of analysis included the trigger list, cluster list, point map, point rating map, cluster map, and cluster rating map. The three workshops together resulted in 21 different triggers that were structured in a framework forming 5 clusters: drug allergy, drugs induced diseases, dosage adjustment in renal diseases, potassium concerning, and drug overdose. The first cluster is drug allergy such as the doctor’s orders for dexamethasone injection combined with chlorpheniramine injection. Later, the diagnosis of drug-induced hepatitis in a patient taking anti-tuberculosis drugs is one trigger in the ‘drugs induced diseases’ cluster. Then, for the third cluster, the doctor’s orders for enalapril combined with ibuprofen in a patient with chronic kidney disease is the example of a trigger. The doctor’s orders for digoxin in a patient with hypokalemia is a trigger in a cluster. Finally, the doctor’s orders for naloxone with narcotic overdose was classified as a trigger in a cluster. This study generated triggers that are similar to some of IHI Global trigger tool, especially in the medication module such as drug allergy and drug overdose. However, there are some specific aspects of this tool, including drug-induced diseases, dosage adjustment in renal diseases, and potassium concerning which do not contain in any trigger tools. The pharmacy-based trigger tool is suitable for pharmacists in hospitals to detect potential adverse drug events using clues of triggers.

Keywords: adverse drug events, concept mapping, hospital, pharmacy-based trigger tool

Procedia PDF Downloads 152