Search results for: distributed disaster reduction

Authors: Şehri Çınar, Aydın Akın

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This study was conducted Razakı grape variety (Vitis vinifera L.) and its vine which was aged 19 was grown on 5 BB rootstock in a vegetation period of 2014 in Afyon province in Turkey. In this research, it was investigated whether the applications of Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), Shoot Tip Reduction (STR), 1/3 CTR + STR, Boric Acid (BA), 1/3 CTR + BA, STR + BA, 1/3 CTR + STR + BA on yield and yield components of Razakı grape variety. The results were obtained as the highest fresh grape yield (7.74 kg/vine) with C application, as the highest cluster weight (244.62 g) with STR application, as the highest 100 berry weight (504.08 g) with C application, as the highest maturity index (36.89) with BA application, as the highest must yield (695.00 ml) with BA and (695.00 ml) with 1/3 CTR + STR + BA applications, as the highest intensity of L* color (46.93) with STR and (46.10) with 1/3 CTR + STR + BA applications, as the highest intensity of a* color (-5.37) with 1/3 CTR + STR and (-5.01) with STR, as the highest intensity of b* color (12.59) with STR application. The shoot tip reduction to increase cluster weight and boric acid application to increase maturity index of Razakı grape variety can be recommended.

Keywords: razakı, 1/3 cluster tip reduction, shoot tip reduction, boric acid, yield and yield components

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Authors: A. Kourou, A. Ioakeimidou, S. Hadjiefthymiades, V. Abramea

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During the last decades, the task of engaging governments, communities and citizens to reduce risk and vulnerability of the populations has made variable progress. Experience has demonstrated that lack of awareness, education and preparedness may result in significant material and other losses both on the onset of the disaster. Schools play a vital role in the community and are important elements of values and culture of the society. A proper school education not only teaches children, but also is a key factor in the promotion of a safety culture into the wider community. In Greece School Earthquake Safety Initiative has been undertaken by Earthquake Planning and Protection Ogranization with specific actions (seminars, lectures, guidelines, educational material, campaigns, national or EU projects, drills etc.). The objective of this initiative is to develop disaster-resilient school communities through awareness, self-help, cooperation and education. School preparedness requires the participation of Principals, teachers, students, parents, and competent authorities. Preparation and earthquake readiness involves: a) learning what should be done before, during, and after earthquake; b) doing or preparing to do these things now, before the next earthquake; and c) developing teachers’ and students’ skills to cope efficiently in case of an earthquake. In the above given framework this paper presents the results of a survey aimed to identify the level of education and preparedness of school community in Greece. More specifically, the survey questionnaire investigates issues regarding earthquake protection actions, appropriate attitudes and behaviors during an earthquake and existence of contingency plans at elementary and secondary schools. The questionnaires were administered to Principals and teachers from different regions of the country that attend the EPPO national training project 'Earthquake Safety at Schools'. A closed-form questionnaire was developed for the survey, which contained questions regarding the following: a) knowledge of self protective actions b) existence of emergency planning at home and c) existence of emergency planning at school (hazard mitigation actions, evacuation plan, and performance of drills). Survey results revealed that a high percentage of teachers have taken the appropriate preparedness measures concerning non-structural hazards at schools, emergency school plan and simulation drills every year. In order to improve the action-planning for ongoing school disaster risk reduction, the implementation of earthquake drills, the involvement of students with disabilities and the evaluation of school emergency plans, EPPO participates in E-PreS project. The main objective of this project is to create smart tools which define, simulate and evaluate all hazards emergency steps customized to the unique district and school. The project comes up with a holistic methodology using real-time evaluation involving different categories of actors, districts, steps and metrics. The project is supported by EU Civil Protection Financial Instrument with a duration of two years. Coordinator is the Kapodistrian University of Athens and partners are from four countries; Greece, Italy, Romania and Bulgaria.

Keywords: drills, earthquake, emergency plans, E-PreS project

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Authors: Aofan Liu, Qianqian Tan, Burra Venkata Durga Kumar

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Data security is of the utmost importance in the healthcare area, as sensitive patient information is constantly sent around and analyzed by many different parties. The use of federated learning, which enables data to be evaluated locally on devices rather than being transferred to a central server, has emerged as a potential solution for protecting the privacy of user information. To protect against data breaches and unauthorized access, federated learning alone might not be adequate. In this context, the application of blockchain technology could provide the system extra protection. This study proposes a distributed federated learning system that is built on blockchain technology in order to enhance security in healthcare. This makes it possible for a wide variety of healthcare providers to work together on data analysis without raising concerns about the confidentiality of the data. The technical aspects of the system, including as the design and implementation of distributed learning algorithms, consensus mechanisms, and smart contracts, are also investigated as part of this process. The technique that was offered is a workable alternative that addresses concerns about the safety of healthcare while also fostering collaborative research and the interchange of data.

Keywords: data privacy, distributed system, federated learning, machine learning

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Authors: Vega Erdiana Dwi Fransiska, Abyan Rai Fauzan Machmudin

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Particularly, space configuration zoning is the very first juncture of a complete space configuration and region planning. Zoning is aimed to define discrete knowledge based on a local wisdom. Ancient predecessor scientifically study the sign of natural disaster towards ethnography approach by operating this knowledge. There are three main functions of space zoning, which are control function, guidance function, and additional function. The control function refers to an instrument for development control and as one of the essentials in controlling land use. Hence, the guidance function indicates as guidance for proposing operational planning and technical development or land usage. Any additional function is useful as a supplementary for region or province planning details. This phase likewise accredits to define boundary in an open space based on geographical appearance. Informant who is categorized as an elder lives in earthquake prone area, to be precise the area is the surrounding of Mount Krakatau. The collected data is one of method for analyzed with thematic model. Later on, it will be verified. In space zoning, long-range distance sensor is applied to determine visualization of the area, which will be zoned before the step of survey to validate the data. The data, which is obtained from long-range distance sensor and site survey, will be overlaid using GIS Platform. Comparing the knowledge based on a local wisdom that is well known by elderly in that area, some of it is relevant to the research, while the others are not. Based on the site survey, the interpretation of a long-range distance sensor, and determining space zoning by considering various aspects resulted in the pattern map of space zoning. This map can be integrated with disaster mitigation affected by volcano eruption.

Keywords: elderly, GIS platform, local wisdom, space zoning

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Authors: Ishraq M. Anjum

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Distributed Bragg reflectors are used in vertical-cavity surface-emitting lasers (VCSELs) in order to achieve very high reflectivity. Use of metamaterial in place of distributed Bragg reflector can reduce the device size significantly. A silicon-based metamaterial near perfect reflector is designed to be used in place of distributed Bragg reflectors in VCSELs. Mie resonance in dielectric microparticles is exploited in order to design the metamaterial. A reflectivity of 98.31% is achieved using finite-difference time-domain method. An 808nm double intra-cavity contacted VCSEL structure with 1.5 λ cavity is proposed using this metamaterial near perfect reflector. The active region is designed to be composed of seven GaAs/AlGaAs quantum wells. Upon numerical investigation of the designed VCSEL structure, the threshold current is found to be 2.96 mA at an aperture of 40 square micrometers and the maximum output power is found to be 71 mW at a current of 141 mA. Miniaturization of conventional VCSELs is possible using this design.

Keywords: GaAs, LASER, metamaterial, VCSEL, vertical cavity surface emitting laser

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Authors: Bernard Doherty, Andrew Jelfs, Aveek Dasgupta, Patrick Holden

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Many companies have moved to agile and hybrid agile methodologies where portions of the Software Design Life-cycle (SDLC) and Software Test Life-cycle (STLC) can be time boxed in order to enhance delivery speed, quality and to increase flexibility to changes in software requirements. Despite widespread proliferation of agile practices, implementation often fails due to lack of adequate project management support, decreased motivation or fear of increased interaction. Consequently, few organizations effectively adopt agile processes with tailoring often required to integrate agile methodology in large scale environments. This paper provides an overview of the challenges in implementing an innovative large-scale tailored realization of the agile methodology termed the Agile Factory Model (AFM), with the aim of comparing and contrasting issues of specific importance to organizations undertaking large scale agile development. The conclusions demonstrate that agile practices can be effectively translated to a globally distributed development environment.

Keywords: agile, agile factory model, globally distributed development, large-scale agile

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Authors: K. L. Pan, M. B. Chang

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Nitrogen oxides (NOₓ) is regarded as one of the most important air pollutants. It not only causes adverse environmental effects but also harms human lungs and respiratory system. As a post-combustion treatment, selective catalytic reduction (SCR) possess the highest NO removal efficiency ( ≥ 85%), which is considered as the most effective technique for removing NO from gas streams. However, injection of reducing agent such as NH₃ is requested, and it is costly and may cause secondary pollution. Reduction of NO with carbon monoxide (CO) as reducing agent has been previously investigated. In this process, the key step involves the NO adsorption and dissociation. Also, the high performance mainly relies on the amounts of oxygen vacancy on catalyst surface and redox ability of catalyst, because oxygen vacancy can activate the N-O bond to promote its dissociation. Additionally, perfect redox ability can promote the adsorption of NO and oxidation of CO. Typically, noble metals such as iridium (Ir), platinum (Pt), and palladium (Pd) are used as catalyst for the reduction of NO with CO; however, high cost has limited their applications. Recently, transition metal oxides have been investigated for the reduction of NO with CO, especially CuₓOy, CoₓOy, Fe₂O₃, and MnOₓ are considered as effective catalysts. However, deactivation is inevitable as oxygen (O₂) exists in the gas streams because active sites (oxygen vacancies) of catalyst are occupied by O₂. In this study, Cu-Ce-Fe-Co is prepared and supported on activated carbon by impregnation method to form 10% wt. Cu-Ce-Fe-Co/activated carbon catalyst. Generally, addition of activated carbon on catalyst can bring several advantages: (1) NO can be effectively adsorbed by interaction between catalyst and activated carbon, resulting in the improvement of NO removal, (2) direct NO decomposition may be achieved over carbon associated with catalyst, and (3) reduction of NO could be enhanced by a reducing agent over carbon-supported catalyst. Therefore, 10% wt. Cu-Ce-Fe-Co/activated carbon may have better performance for reduction of NO with CO. Experimental results indicate that NO conversion achieved with 10% wt. Cu-Ce-Fe-Co/activated carbon reaches 83% at 150°C with 300 ppm NO and 10,000 ppm CO. As temperature is further increased to 200°C, 100% NO conversion could be achieved, implying that 10% wt. Cu-Ce-Fe-Co/activated carbon prepared has good activity for the reduction of NO with CO. In order to investigate the effect of O₂ on reduction of NO with CO, 1-5% O₂ are introduced into the system. The results indicate that NO conversions still maintain at ≥ 90% with 1-5% O₂ conditions at 200°C. It is worth noting that effect of O₂ on reduction of NO with CO could be significantly improved as carbon is used as support. It is inferred that carbon support can react with O₂ to produce CO₂ as O₂ exists in the gas streams. Overall, 10% wt. Cu-Ce-Fe-Co/activated carbon is demonstrated with good potential for reduction of NO with CO, and possible mechanisms will be elucidated in this paper.

Keywords: nitrogen oxides (NOₓ), carbon monoxide (CO), reduction of NO with CO, carbon material, catalysis

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Authors: A. Kourou, A. Ioakeimidou, A. Gakou

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Greece due to its location in the Eastern Mediterranean region is characterized by a high degree of seismicity and occurrence of severe earthquakes. It is generally accepted that preventive planning is vital in mitigating impacts, protecting those who are the most vulnerable namely children and increasing the degree of resilience of local communities. Worldwide, States have highlighted the need to ensure the safety of early childhood environments in case of disaster. A great number of children are enrolled in daycare facilities, so building and improving the preparedness of pre-primary schools to prevent injuries and fatalities in case of an earthquake becomes an important policy issue. It is more than evident that preparedness in early preschool level will be increased through awareness and education of the people who work to pre-primary classes and provide early childhood care. The aim of the present study is to assess the level of awareness and preparedness of the Greek pre-primary schools staff concerning earthquake protection issues, as well as their risk mitigation behaviors and earthquake management in case of a strong event. In this framework, specific questionnaire was developed and filled by the abovementioned target group at 30 different municipalities of Greece (2014-2016). Also in the framework of this study it is presented the Pre-Primary Schools’ Earthquake Safety Initiative that has been undertaken by Earthquake Planning and Protection Organization (EPPO) the last years. This initiative aims to develop disaster-resilient day care centers through awareness, self-help, cooperation and education. Recognizing the necessity of integration of the disaster safety concept at pre-primary environments, EPPO published practical guidelines that focused on earthquake planning of these workspaces. Furthermore, dozens of seminars are implemented in municipality or prefecture-level every year by EPPO, in order the early childhood schools’ staff to be appropriately educated and adequately trained to face the earthquake risk. Great progress has been made towards building awareness and increasing preschool preparedness in Greece but significant gaps still remain. Anyway, it is extremely important that the implementation of effective programs and practices and the broad collaboration of all involved parties have been recognized as essential in order to develop a comprehensive disaster management system at preschool environment.

Keywords: awareness, earthquake, education, emergency plans, preparedness, pre-primary schools

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Authors: Muhammad Anwar, Ameen Ullah, Intakhab Alam Qadri

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This study presents a technique utilizing the Iterative Rational Krylov Algorithm (IRKA) to reduce the order of large-scale descriptor systems. Descriptor systems, which incorporate differential and algebraic components, pose unique challenges in Model Order Reduction (MOR). The proposed method partitions the descriptor system into polynomial and strictly proper parts to minimize approximation errors, applying IRKA exclusively to the strictly adequate component. This approach circumvents the unbounded errors that arise when IRKA is directly applied to the entire system. A comparative analysis demonstrates the high accuracy of the reduced model and a significant reduction in computational burden. The reduced model enables more efficient simulations and streamlined controller designs. The study highlights IRKA-based MOR’s effectiveness in optimizing complex systems’ performance across various engineering applications. The proposed methodology offers a promising solution for reducing the complexity of large-scale descriptor systems while maintaining their essential characteristics and facilitating their analysis, simulation, and control design.

Keywords: model order reduction, descriptor systems, iterative rational Krylov algorithm, interpolatory model reduction, computational efficiency, projection methods, H₂-optimal model reduction

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Authors: Abigail M. Csik, Gabriel A. Radvansky

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As people read through event-based narratives, they construct an event model that captures information about the characters, goals, location, time, and causality. For many reasons, memory for such narratives is represented at different levels, namely, the surface form, textbase, and event model levels. Rereading has been shown to decrease surface form memory, while, at the same time, increasing textbase and event model memories. More generally, distributed practice has consistently shown memory benefits over massed practice for different types of materials, including texts. However, little research has investigated distributed practice of narratives at different inter-study intervals and these effects on these three levels of memory. Recent work in our lab has indicated that there may be dramatic changes in patterns of forgetting around one week, which may affect the three levels of memory. The present experiment aimed to determine the effects of rereading on the three levels of memory as a factor of whether the texts were reread before versus after one week. Participants (N = 42) read a set of stories, re-read them either before or after one week (with an inter-study interval of three days, seven days, or fourteen days), and then took a recognition test, from which the three levels of representation were derived. Signal detection results from this study reveal that differential patterns at the three levels as a factor of whether the narratives were re-read prior to one week or after one week. In particular, an ANOVA revealed that surface form memory was lower (p = .08) while textbase (p = .02) and event model memory (p = .04) were greater if narratives were re-read 14 days later compared to memory when narratives were re-read 3 days later. These results have implications for what type of memory benefits from distributed practice at various inter-study intervals.

Keywords: memory, event cognition, distributed practice, consolidation

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Authors: Jiahui Song

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There have been decades of research into the action potential block in nerves. To our best knowledge electrical voltages can reversibly block the conduction of action potentials across whole animal nerves. Blocking biological electrical signaling pathways can have a variety of applications in muscular and sensory incapacitation and clinical research, including urethral pressure reduction and relieving chronic pain relief from a peripheral nerve injury. The cessation ability has been used in muscle activation and fatigue reduction. Ultrashort, high-intensity electric pulses modulate the membrane conductivity to block nerve conduction through the electroporation process. Nanopore formation on the membrane surface would increase the local membrane conductivity and effectively "short-out" the trans-membrane potential of a nerve that inhibits action potential propagation. This block would be similar in concept to stopping the propagation of an air-pressure wave down a "leaky" pipe. This research focuses on a distributed electrical model with an additional time-dependent membrane conductance to calculate the poration induced by the ultrashort, high-intensity electric pulses. The changes in membrane conductivity are used to predict changes in action potential transmission. A "strength-duration (SD)" curve is generated for action potential blockage and would be used as a design guide for benchmarking safety thresholds or setting the pulse voltage and/or durations necessary for neuro-muscular incapacitation.

Keywords: action potential, ultrashort, high-intensity, nerve, strength-duration

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Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: M. A. Hasnat, M. Amirul Islam, M. A. Rashed, Jamil. Safwan, M. Mahabubul Alam

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Symmetric (Cu–Pt|Nafion|Pt–Cu) and asymmetric(Pt|Nafion|Pt–Cu) assemblies were fabricated to study the nitrate reduction processes at the cathode. The electrocatalytic nitrate reduction reactions were performed in these assemblies in order to investigate the prerequisite for the enhanced catalytic activity, electrochemical cell durability as well as preferable product selectivity resulting from the reduction of nitrate at the cathode. It has been observed for the symmetric assembly that Cu particles were oxidized on the anode surface under an applied potential and the resulting copper ions migrated to the cathode surface through the Nafion membrane, which deposited as copper oxide on the cathode surface. The formation of this copper oxide covering layer on the Pt–Cu cathode surface is attributed as the reason for the deactivation of the cathode that governed the reduced nitrate reduction along with increasing nitrite selectivity. These problems were addressed and resolved with the asymmetric design of the electrocatalytic reactor, where enhanced hydrogen evolution activates the surface by eroding the CuO over layer as well as speeding up the slow rate determining hydrogenation reactions.

Keywords: membrane, nitrate, electrocatalysis, voltammetry, electrolysis

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Authors: Mehrnaz Mostafavi

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The current research aims to explore a method for creating nano-ring structures through chemical reduction. By employing a direct reduction process at a controlled, slow pace, and concurrently introducing specific reduction agents, the goal is to fabricate these unique nano-ring formations. The deliberate slow reduction of nanoparticles within this process helps prevent spatial hindrances caused by the reduction agents. The timing of the reduction of metal atoms, facilitated by these agents, emerges as a crucial factor influencing the creation of nano-ring structures. In investigation involves a chemical approach utilizing bovine serum albumin and human serum albumin as organic reducing agents to produce gold nano-rings. The controlled reduction of metal atoms at a slow pace and under specific pH conditions plays a pivotal role in the successful fabrication of these nanostructures. Optical spectroscopic analyses revealed distinctive plasmonic behavior in both visible and infrared spectra, owing to the collective movement of electrons along the inner and outer walls of the gold nano-rings. Importantly, these ring-shaped nanoparticles exhibit customizable plasmon resonances in the near-infrared spectrum, a characteristic absent in solid particles of similar sizes. This unique attribute makes the generated samples valuable for applications in Nanomedicine and Nanobiotechnology, leveraging the distinct optical properties of these nanostructures.

Keywords: nano-ring structure, nano-particles, reductant agents, plasmon resonace

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Authors: S. Jursová, P. Pustějovská, S. Brožová, J. Bilík

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The paper deals with possibilities of interpretation of iron ore reducibility tests. It presents a mathematical model developed at Centre ENET, VŠB–Technical University of Ostrava, Czech Republic for an evaluation of metallurgical material of blast furnace feedstock such as iron ore, sinter or pellets. According to the data from the test, the model predicts its usage in blast furnace technology and its effects on production parameters of shaft aggregate. At the beginning, the paper sums up the general concept and experience in mathematical modelling of iron ore reduction. It presents basic equation for the calculation and the main parts of the developed model. In the experimental part, there is an example of usage of the mathematical model. The paper describes the usage of data for some predictive calculation. There are presented material, method of carried test of iron ore reducibility. Then there are graphically interpreted effects of used material on carbon consumption, rate of direct reduction and the whole reduction process.

Keywords: blast furnace technology, iron ore reduction, mathematical model, prediction of iron ore reduction

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Authors: Ogunwole Cecilia Oluwakemi, Timothy Ayomitunde Aderemi

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Provision of sufficient food and elimination of abject poverty have usually been the conventional benefits of agriculture in any society. Meanwhile, despite the fact that Nigeria is an agrarian society, food insecurity and poverty have become the issues of concern among both scholars and policymakers in the recent times. Against this backdrop, this study examined the nexus among agriculture, food security, and poverty reduction in Nigeria from 1990 to 2019 within the framework of the Cointegration and Granger Causality approach. Data was collected from the Central Bank of Nigeria Statistical Bulletin and the World Development Indicators, respectively. The following are the major results that emanated from the study. A long run equilibrium relationship exists among agricultural value added, food production index, and GDP per capita in Nigeria. Similarly, there is a unidirectional causality which flows from food production index to poverty reduction in Nigeria. In the same vein, one way causality flows from poverty reduction to agricultural value added in Nigeria. Consequently, this study makes the following recommendation for the policymakers in Nigeria, and other African countries by extension, that agricultural value added and food production are the important variables that cannot be undermined when poverty reduction occupies the central focus of the policymakers. Therefore, any time these policymakers want to reduce poverty, policies that drive agricultural value added and food production should be embarked upon. Therefore, this study will contribute to the literature by establishing the type of linkage that exists between agriculture, food security, and poverty reduction in Nigeria.

Keywords: agriculture, value added, food production, GDP per capita, Nigeria

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Authors: Behrooz Balaei, Suzanne Wilkinson, Regan Potangaroa, Larry Abel, Philip McFarlane

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Water supply system failure has serious direct and indirect effects on people wellbeing. Post-disaster water system serviceability depends on a variety of factors from technical characteristics to social, economic, and organizational attributes of communities. This paper tests the organizational factors affecting water supply resilience to outline how these factors contributed to previous disasters. To do so, a framework is briefly introduced in this study to provide a clear guide to identify the significant relevant organizational factors. Then the factors affecting water serviceability following a disaster are outlines. Next, these factors are measured in the case of Tropical Cyclone Pam, which hit Vanuatu in March 2015. Reviewing the existing literature has also been carried out to obtain a comprehensive understanding of the background A site visit and a series of interviews have also been undertaken following the cyclone to collect site-specific data and information. In the end, the organizational factors were ranked to enable decision makers to identify significance of each factor compared to the others.

Keywords: water supply, resilience, organizational capacity, Vanuatu, Tropical Cyclone Pam

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Authors: N. Nivedita, S. Durbha

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Critical Infrastructure (CI) consists of services and technological networks such as healthcare, transport, water supply, electricity supply, information technology etc. These systems are necessary for the well-being and to maintain effective functioning of society. Critical Infrastructures can be represented as nodes in a network where they are connected through a set of links depicting the logical relationship among them; these nodes are interdependent on each other and interact with each at other at various levels, such that the state of each infrastructure influences or is correlated to the state of another. Disruption in the service of one infrastructure nodes of the network during a disaster would lead to cascading and escalating disruptions across other infrastructures nodes in the network. The operation of Healthcare Infrastructure is one such Critical Infrastructure that depends upon a complex interdependent network of other Critical Infrastructure, and during disasters it is very vital for the Healthcare Infrastructure to be protected, accessible and prepared for a mass casualty. To reduce the consequences of a disaster on the Critical Infrastructure and to ensure a resilient Critical Health Infrastructure network, knowledge, understanding, modeling, and analyzing the inter-dependencies between the infrastructures is required. The paper would present inter-dependencies related to Healthcare Critical Infrastructure based on Hierarchical Coloured Petri Nets modeling approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The model properties are being analyzed for the various state changes which occur when there is a disruption or damage to any of the Critical Infrastructure. The failure probabilities for the failure risk of interconnected systems are calculated by deriving a reachability graph, which is later mapped to a Markov chain. By analytically solving and analyzing the Markov chain, the overall vulnerability of the Healthcare CI HCPN model is demonstrated. The entire model would be integrated with Geographic information-based decision support system to visualize the dynamic behavior of the interdependency of the Healthcare and related CI network in a geographically based environment.

Keywords: critical infrastructure interdependency, hierarchical coloured petrinet, healthcare critical infrastructure, Petri Nets, Markov chain

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Authors: Samina Khalid, Shamila Nasreen

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Dimensionality reduction as a preprocessing step to machine learning is effective in removing irrelevant and redundant data, increasing learning accuracy, and improving result comprehensibility. However, the recent increase of dimensionality of data poses a severe challenge to many existing feature selection and feature extraction methods with respect to efficiency and effectiveness. In the field of machine learning and pattern recognition, dimensionality reduction is important area, where many approaches have been proposed. In this paper, some widely used feature selection and feature extraction techniques have analyzed with the purpose of how effectively these techniques can be used to achieve high performance of learning algorithms that ultimately improves predictive accuracy of classifier. An endeavor to analyze dimensionality reduction techniques briefly with the purpose to investigate strengths and weaknesses of some widely used dimensionality reduction methods is presented.

Keywords: age related macular degeneration, feature selection feature subset selection feature extraction/transformation, FSA’s, relief, correlation based method, PCA, ICA

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Authors: Thomas P. Roper, Brad Forbes, Jurij Karlovšek

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Shear displacement along bedding defects is a well-recognised behaviour when tunnelling and mining in stratified rock. This deformation can affect the durability and integrity of installed rock bolts. In-situ monitoring of rock bolt deformation under bedding shear cannot be accurately derived from traditional strain gauge bolts as sensors are too large and spaced too far apart to accurately assess concentrated displacement along discrete defects. A possible solution to this is the use of fiber optic technologies developed for precision monitoring. Distributed Optic Sensor (DOS) embedded rock bolts were installed in a tunnel project with the aim of measuring the bolt deformation profile under significant shear displacements. This technology successfully measured the 3D strain distribution along the bolts when subjected to bedding shear and resolved the axial and lateral strain constituents in order to determine the deformational geometry of the bolts. The results are compared well with the current visual method for monitoring shear displacement using borescope holes, considering this method as suitable.

Keywords: distributed optical strain sensing, rock bolt, bedding shear, sandstone tunnel

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Seyeon Lee, Suyeon Lee, Julia Rogers

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This research investigates and records post-flood and typhoon conditions of low income housing in the Thua Thien Hue Province, Vietnam; area prone to extreme flooding in Central Vietnam. The cost of rebuilding houses after flood and typhoon has been always a burden for low income households. These costs often lead to the elimination of essential construction practices for disaster resistance. Despite relief efforts from international non-profit organizations and Vietnam government, the impacts of flood and typhoon damages to residential construction has been reoccurring to the same neighborhood annually. Notwithstanding its importance, this topic has not been systematically investigated. The study is limited to assistance provided to low income households documenting existing conditions of low income homes impacted by post flood and typhoon conditions in the Thua Thien Hue Province. The research identifies leading causes of the building failure from the natural disasters. Relief efforts and progress made since the last typhoon is documented. The quality of construction and repairs are assessed based on Home Builders Guide to Coastal Construction by Federal Emergency Management Agency. Focus group discussions and individual interviews with local residents from four different communities were conducted to get incites on repair effort by the non-profit organizations and Vietnam government, and their needs post flood and typhoon. The findings from the field study informed that many of the local people are now aware of the importance of improving housing conditions as one of the key coping strategies to withstand flood and typhoon events as it makes housing and community more resilient to future events. While there has been a remarkable improvement of housing and infrastructure with the support from the local government as well as the non-profit organizations, many households in the study areas are found to still live in weak and fragile housing conditions without gaining access to the aid to repair and strengthen the houses. Given that the major immediate recovery action taken by the local people tends to focus on repairing damaged houses, and on this ground, low-income households spend a considerable amount of their income on housing repair, providing proper and applicable construction practices will not only improve the housing condition, but also contribute to reducing poverty in Vietnam.

Keywords: disaster coping mechanism, housing welfare, low-income housing, recovery reduction

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Authors: Lai Ving Kam

Abstract:

Many markets are maturing, consumer buying powers are weakening and customer preferences change rapidly. To survive, many adopt fast paced continuous cost reduction and competitive pricing to remain relevance. Marketers desire to push for more sales to increase revenues have intensified competitions at time cannibalize the product and market. The amazing technologies changes have created both hope and despair to the industries. The pressure to constantly reduce cost, on the one hand, create and market new products in cheaper prices and shorter life cycles, on the other has become a continuous endeavour. The twin trends appear irreconcilable. Can core strategic vision provides and adapts new directions in continuous cost reduction? This study investigates core strategic vision able to meet this need, for firms to survive and stay profitable. Under current uncertainty market, are firms falling back on their core strategic visions to take them out of the unfavourable positions?

Keywords: core strategy vision, continuous cost reduction, fashionable products industry, competitive pricing

Procedia PDF Downloads 320

Authors: K. Vallianou, T. Alexopoulos, V. Plaka, M. K. Seleventi, V. Skanavis, C. Skanavis

Abstract:

The present research addresses the role of place attachment and emotions in community resiliency and recovery within the context of a disaster. Natural disasters represent a disruption in the normal functioning of a community, leading to a general feeling of disorientation. This study draws on the trauma caused by a natural hazard such as a forest fire. The changes of the sense of togetherness are being assessed. Finally this research determines how the place attachment of the inhabitants was affected during the reorientation process of the community. The case study area is Mati, a small coastal town in eastern Attica, Greece. The fire broke out on July 23^rd, 2018. A quantitative research was conducted through questionnaires via phone interviews, one year after the disaster, to address community resiliency in the long-run. The sample was composed of 159 participants from the rural community of Mati plus 120 coming from Skyros Island that was used as a control group. Inhabitants were prompted to answer items gauging their emotions related to the event, group identification and emotional significance of their community, and place attachment before and a year after the fire took place. Importantly, the community recovery and reorientation were examined within the context of a relative absence of government backing and official support. Emotions related to the event were aggregated into 4 clusters related to: activation/vigilance, distress/disorientation, indignation, and helplessness. The findings revealed a decrease in the level of place attachment in the impacted area of Mati as compared to the control group of Skyros Island. Importantly, initial distress caused by the fire prompted the residents to identify more with their community and to report more positive feelings toward their community. Moreover, a mediation analysis indicated that the positive effect of community cohesion on place attachment one year after the disaster was mediated by the positive feelings toward the community. Finally, place attachment contributes to enhanced optimism and a more positive perspective concerning Mati’s future prospects. Despite an insufficient state support to this affected area, the findings suggest an important role of emotions and place attachment during the process of recovery. Implications concerning the role of emotions and social dynamics in meshing place attachment during the disaster recovery process as well as community resiliency are discussed.

Keywords: community resilience, natural disasters, place attachment, wildfire

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Authors: Muhammad Fanseem E. M., Rama Satya Satish Kumar, Indrajeet Bhausaheb Bhavar, Deepak M.

Abstract:

Keeping the right balance of electricity between the supply and demand sides of the grid is one of the most important objectives of electrical grid operation. Power generation and demand forecasting are the core of power management and generation scheduling. Large, centralized producing units were used in the construction of conventional power systems in the past. A certain level of balance was possible since the generation kept up with the power demand. However, integrating renewable energy sources into power networks has proven to be a difficult challenge due to its intermittent nature. The power imbalance caused by rising demands and peak loads is negatively affecting power quality and dependability. Demand side management and demand response were one of the solutions, keeping generation the same but altering or rescheduling or shedding completely the load or demand. However, shedding the load or rescheduling is not an efficient way. There comes the significance of virtual power plants. The virtual power plant integrates distributed generation, dispatchable load, and distributed energy storage organically by using complementing control approaches and communication technologies. This would eventually increase the utilization rate and financial advantages of distributed energy resources. Most of the writing on virtual power plant models ignored technical limitations, and modeling was done in favor of a financial or commercial viewpoint. Therefore, this paper aims to address the modeling intricacies of VPPs and their technical limitations, shedding light on a holistic understanding of this innovative power management approach.

Keywords: cost optimization, distributed energy resources, dynamic modeling, model quality tests, power system modeling

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Authors: Gen Sakoda, Hideki Takayasu, Misako Takayasu

Abstract:

Waste reduction is a fundamental problem for sustainability. Methods for waste reduction with point-of-sales (POS) data are proposed, utilizing the knowledge of a recent econophysics study on a statistical property of POS data. Concretely, the non-stationary time series analysis method based on the Particle Filter is developed, which considers abnormal fluctuation scaling known as Taylor's law. This method is extended for handling incomplete sales data because of stock-outs by introducing maximum likelihood estimation for censored data. The way for optimal stock determination with pricing the cost of waste reduction is also proposed. This study focuses on the examination of the methods for large sales numbers where Taylor's law is obvious. Numerical analysis using aggregated POS data shows the effectiveness of the methods to reduce food waste maintaining a high profit for large sales numbers. Moreover, the way of pricing the cost of waste reduction reveals that a small profit loss realizes substantial waste reduction, especially in the case that the proportionality constant  of Taylor’s law is small. Specifically, around 1% profit loss realizes half disposal at =0.12, which is the actual  value of processed food items used in this research. The methods provide practical and effective solutions for waste reduction keeping a high profit, especially with large sales numbers.

Keywords: food waste reduction, particle filter, point-of-sales, sustainable development goals, Taylor's law, time series analysis

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Authors: Fatima Ammari, Meriem Chenouf

Abstract:

Synthesis of gold nanoparticles (AuNPs) has attracted much attention since the pioneering discovery of the high catalytic activity of supported gold nanoparticles in the reaction of CO oxidation at low temperature. In this research field, we used montmorillonite pre-acidified under gentle conditions for AuNPs stabilization; using different loading percentage 1, 2 and 5%. The gold nanoparticles were obtained using chemical reduction method using NaBH4 as reductant agent. The obtained gold nanoparticles stabilized in acid-activated montmorillonite were used as catalysts for reduction of 4-nitrophenol to aminophenol with sodium borohydride at room temperature The UV-Vis results confirm directly the gold nanaoparticles formation. The XRD N2 adsorption and MET results showed the formation of gold nanoparticles in the pores of preacidified montmorillonite with an average size of 5.7nm. The reduction reaction of 4-nitrophenol into 4-aminophenol with NaBH4 catalyzed by Au°-montmorillonite catalyst exhibits remarkably a high activity; the reaction was completed within 4.5min.

Keywords: gold, acid-activated montmorillonite, nanoparticles, 4-nitrophenol

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Authors: Fuqiang Wang, Jun Liu, Liyan Cai

Abstract:

This paper investigates the coordination of the conflicting two-stage low carbon supply chain consisting of upstream and downstream manufacturers. The conflict means that the upstream manufacturer takes action for carbon emissions reduction under carbon trading mechanism while the downstream manufacturer’s production cost rises. It assumes for the Stackelberg game that the upstream manufacturer plays as a leader and the downstream manufacturer does as a follower. Four kinds of the situation of decentralized decision making, centralized decision-making, the production cost sharing contract and the carbon emissions reduction revenue sharing contract under decentralized decision making are considered. The backward induction approach is adopted to solve the game. The results show that the more intense the conflict is, the lower the efficiency of carbon emissions reduction and the higher the retail price is. The optimal investment of the decentralized supply chain under the two contracts is unchanged and still lower than that of the centralized supply chain. Both the production cost sharing contract and the carbon emissions reduction revenue sharing contract cannot coordinate the supply chain, because that the sharing cost or carbon emissions reduction sharing revenue will transfer through the wholesale price mechanism. As a result, it requires more complicated contract forms to coordinate such a supply chain.

Keywords: cap-and-trade mechanism, carbon emissions reduction, conflict, supply chain coordination

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Authors: Margaret S. Wright

Abstract:

Background/Significance: During many recent public health emergencies/disasters, public health nursing data has been missing or delayed, potentially impacting the decision-making and response. Data used as evidence for decision-making in response, planning, and mitigation has been erratic and slow, decreasing the ability to respond. Methodology: Applying best practices in data management and data use in public health settings, and guided by the concepts outlined in ‘Disaster Standards of Care’ models leads to the development of recommendations for a model of best practices in data management and use in public health disasters/emergencies by public health nurses. As the ‘patient’ in public health disasters/emergencies is the community (local, regional or national), guidelines for patient documentation are incorporated in the recommendations. Findings: Using model public health nurses could better plan how to prepare for, respond to, and mitigate disasters in their communities, and better participate in decision-making in all three phases bringing public health nursing data to the discussion as part of the evidence base for decision-making.

Keywords: data management, decision making, disaster planning documentation, public health nursing

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Authors: Ming-Hwi Yao, Su-Szu Yang

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Typhoons are one of the major types of disasters that affect Taiwan each year and that cause severe damage to agriculture. Indeed, the damage exacted during a typical typhoon season can be up to $1 billion, and is responsible for nearly 75% of yearly agricultural losses. However, there is no consensus on how to reduce the damage caused by the strong winds and heavy precipitation engendered by typhoons. One suggestion is the use of windbreak nets, which are a low-cost and easy-to-use disaster mitigation strategy for crop production. In the present study, we conducted an evaluation to determine the optimal conditions of a windbreak net by using a computational fluid dynamics (CFD) model. This model may be used as a reference for crop protection. The results showed that CFD simulation validated windbreak nets of different mesh sizes and heights in the experimental area; thus, CFD is an efficient tool for evaluating the effectiveness of windbreak nets. Specifically, the effective wind protection length and height were found to be 6 and 1.3 times the length and height of the windbreak net, respectively. During a real typhoon, maximum wind gusts of 18 m s-1 can be reduced to 4 m s-1 by using a windbreak net that has a 70% blocking rate. In short, windbreak nets are significantly effective in protecting typhoon-affected areas.

Keywords: computational fluid dynamics, disaster, typhoon, windbreak net

Procedia PDF Downloads 191