Search results for: public transportation network

Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir

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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

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Authors: M. Kamel, A. Hoayek, M. Batton-Hubert

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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.

Keywords: logs, anomaly detection, ML, scoring, NLP

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Authors: Teja Sai Puligadda

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Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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Authors: A. Olusegun Egunjobi, Samson Sunday Adekunte

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This study investigated the teachers’ and learners’ ICT-readiness assessment for agricultural science instruction in secondary schools in Ogun State, Nigeria. However, the sample population of 6 and 120 agricultural science teachers and learners were randomly selected respectively from 3 public and 3 private senior secondary schools in Ado-Odo/Ota Local Government Area of Ogun State, Nigeria. Descriptive survey design of ex post-facto type was adopted for the study. Two structured questionnaires tagged Teachers’ and Learners’ Questionnaires on ICT-Readiness for Agricultural Science Instruction TQICTRASI and LQICTRASI respectively were used for data collection. The two questionnaires were subjected to Cronbach alpha coefficient with the results 0.86 and 0.82 respectively. Five research hypotheses were tested at 0.05 level of significance. Findings revealed that teachers in private senior secondary school (SSS) were more ready and prepared than their counterparts in public SSS with the result t-value = 4.25 greater than t-critical = 2.77, df = 4 at p<0.05. Also, learners in private SSS were more prepared and ready for the utilisation of ICT-facilities for agricultural science instruction with the result t-value = 3.51 greater than t-critical = 1.98, df = 118 at p<0.05. However, male and female learners in both private and public SSS were equally prepared and ready for the ICT-facilities utilisation for agricultural science instruction, thus, there were no significant differences in their ICT-readiness. Therefore, the study proffered that, both male and female teachers and learners should be more ICT-compliant and always ready to upgrade their skills and knowledge in ICT-facilities, utilisation for agricultural science instruction and even for other school subjects particularly in Ogun State and in generally in Nigeria.

Keywords: ICT-readiness, teachers’ and learners’ assessment, private and public senior secondary schools, agricultural science instruction

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Authors: Anu Paul, Varghese Paul

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The focal aspire of e-Government (eGovt) is to offer citizen-centered service delivery. Accordingly, the citizenry consumes services from multiple government agencies through national portal. Thus, eGovt is an enterprise with the primary business motive of transparent, efficient and effective public services to its citizenry and its logical structure is the eGovernment Enterprise Architecture (eGEA). Since eGovt is IT oriented multifaceted service-centric system, EA doesn’t do much on an automated enterprise other than the business artifacts. Service-Oriented Architecture (SOA) manifestation led some governments to pertain this in their eGovts, but it limits the source of business artifacts. The concurrent use of EA and SOA in eGovt executes interoperability and integration and leads to Service-Oriented e-Government Enterprise (SOeGE). Consequently, agile eGovt system becomes a reality. As an IT perspective eGovt comprises of centralized public service artifacts with the existing application logics belong to various departments at central, state and local level. The eGovt is renovating to SOeGE by apply the Service-Orientation (SO) principles in the entire system. This paper explores IT perspective of SOeGE in India which encompasses the public service models and illustrated with a case study the Passport service of India.

Keywords: enterprise architecture, service-oriented e-Government enterprise, service interface layer, service model

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Authors: Atousa Khodadadyan, Ali Rostami

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The objective of off-site construction manufacturing is to utilise the workforce and machinery in a controlled environment without external interference for higher productivity and quality. The usage of prefabricated components can save up to 14% of the total energy consumption in comparison with the equivalent number of cast-in-place ones. Despite the benefits of prefabrication construction, its current project practices encompass technical and managerial issues. Building design, precast components’ production, logistics, and prefabrication installation processes are still mostly discontinued and fragmented. Furthermore, collaboration among prefabrication manufacturers, transportation parties, and on-site assemblers rely on real-time information such as the status of precast components, delivery progress, and the location of components. From the technical point of view, in this industry, geometric variability is still prevalent, which can be caused during the transportation or production of components. These issues indicate that there are still many aspects of prefabricated construction that can be developed using disruptive technologies. Practical real-time risk analysis can be used to address these issues as well as the management of safety, quality, and construction environment issues. On the other hand, the lack of research about risk assessment and the absence of standards and tools hinder risk management modeling in prefabricated construction. It is essential to note that no risk management standard has been established explicitly for prefabricated construction projects, and most software packages do not provide tailor-made functions for this type of projects.

Keywords: project risk management, risk analysis, risk modelling, prefabricated construction projects

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Authors: Enola Lamy, Jean Paul Mereaux, Jean Claude Lopez

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In the face of new regulations related to waste management, it has become essential to understand the organizational process that accompanies this change. Through an experiment on the sorting of food waste in the community of Grand Reims, this research explores the acceptability, behavior, and tools needed to manage the change. Our position within a private company, SUEZ, a key player in the waste management sector, has allowed us to set up a driven team with concerned public organizations. The research was conducted through a theoretical study combined with semi-structured interviews. This qualitative method allowed us to conduct exchanges with users to assess the motivations and obstacles linked to the sorting of bio-waste. The results revealed the action levers necessary for the project's sustainability. Making the sorting gestures accessible and simplified makes it possible to target all populations. Playful communication adapted to each type of persona allows the user and stakeholders to be placed at the heart of the strategy. These recommendations are spotlighted thanks to the combination of theoretical and operational contributions, with the aim of facilitating the new public management and inducing the notion of performance while providing an example of added value.

Keywords: bio-waste, CSR approach, stakeholders, users, perception

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Authors: Gheyzer Villegas, Edgardo Cedeño, Veruska Mata, Edmundo Chauran

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One of the most significant changes that occurred in global commerce was the emergence of cryptocurrencies and blockchain technology. There is still much debate about the adoption of the economic model based on crypto assets, and myriad international projects and initiatives are being carried out to try and explore the potential that this new field offers. The Hive blockchain is a prime example of this, featuring two use cases: of how trade based on its native currencies can give successful results in the exchange of goods and services and in the financing of social impact projects. Its decentralized management model and visionary administration of its development fund have become a key part of its success.

Keywords: Hive, business, network, blockchain

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Authors: Chee Kwan Foong, Foong Mei Kei

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This study aimed to investigate the influence of self-stigma, perceived public stigma, assertiveness and gender role beliefs on attitudes toward seeking professional psychological help. Two hundred and fifty young adults from universities in Brunei were recruited through convenience sampling to complete a survey. Individuals facing higher stigmatisation (both self-stigma and public-stigma) had less positive attitude towards seeking professional psychological help. Individuals who were more assertive had more positive attitude towards seeking professional psychological help. For males, individuals with more traditional gender role belief showed less positive attitude towards seeking professional psychological help. For female, there was no relationship between gender role beliefs and attitude towards seeking professional psychological help. Results confirmed there was a significant mediating effect between public stigma and attitude toward seeking professional psychological help. This study could guide the mental-health professionals in promoting more positive help-seeking attitude and raise the awareness about mental challenges which could assist in reducing stigmatization, and therefore, gain a deeper understanding.

Keywords: assertiveness, attitude towards seeking professional psychological help, gender role beliefs, stigmatization

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Authors: Mirko Klaric

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In different countries, sub-municipal units have different organizational and political positions. In some countries, the role of sub-municipal units is important; in others, it is marginal. That depends on the organization of the local government system in different countries, and the political role of local self-government units, their size, public authorities, and the possibility for managing various local public tasks. This paper attempts to analyze the sub-municipal government as an organizational form of local governance participation of citizens in the local community with a comparative perspective. Secondly, it presents elements that generally format sub-municipal government as a tool for strengthening of democratization processes in local government units. Those elements are crucial for the understanding of the dynamic in relation to local government vs. sub-municipal government. Special focus is put on the sub-municipal government in South-Eastern European countries, which have a common history and institutional framework, with this main question: how can sub-municipal government contribute to strengthening democratic processes in these countries. In centralized countries, the sub-municipal government usually has a reduced role, which relates to managing public tasks connected with local community needs. The purpose of this comparative research methodology is used for analyzing the present organization and role of sub-municipal government in local government systems in Croatia and other significant countries in Europe, with a special focus on the states in South-Eastern Europe and Croatia. Comparative analyses attempt to show that local government systems with bigger local government units have more significant sub-municipal government. On the other hand, local government systems with small local government units don’t have a strong sub-municipal government. Finally, this paper aims to present ideas on how the sub-municipal government can improve decentralization and contribute to better development of the local community and the whole of society.

Keywords: public administration, local government, sub-municipal government, decentralization

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Authors: Busra Mutlu Ipek, Merve Mutlu, Ahmet Mutlu

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Novel coronavirus COVID-19, which has recently influenced the world, poses a great threat to humanity. In order to overcome this challenging situation, scientists are working on developing effective vaccine against coronavirus. Many experts and researchers have also produced articles and done studies on this highly important subject. In this direction, this special topic was chosen for article to make a contribution to this area. The purpose of this article is to perform RNA sequence analysis of selected virus forms in the Coronaviridae family and predict/classify SARS-CoV-2 (COVID-19) from other selected complete genomes in coronaviridae family using proposed Artificial Neural Network(ANN) algorithm.

Keywords: Coronaviridae family, COVID-19, RNA sequencing, ANN, neural network

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

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Authors: Samai'la Abdullahi

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A graph is a pair of two set and so that a graph is a pictorial representation of a system using two basic element nodes and edges. A node is represented by a circle (either hallo shade) and edge is represented by a line segment connecting two nodes together. In this paper, we present a circuit network in the concept of graph theory application and also circuit models of graph are represented in logical connection method were we formulate matrix method of adjacency and incidence of matrix and application of truth table.

Keywords: euler circuit and path, graph representation of circuit networks, representation of graph models, representation of circuit network using logical truth table

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Authors: Erin Lawlor

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In 2008 Time magazine named terrorist rehabilitation as one of the best ideas of the year. The term deradicalisation has become synonymous with rehabilitation within security discourse. The allure for a “quick fix” when managing terrorist populations (particularly within prisons) has led to a focus on prescriptive programmes where there is a distinct lack of exploration into the drivers for a person to disengage or deradicalise from violence. It has been argued that to tackle a snowballing issue that interventions have moved too quickly for both theory development and methodological structure. This overly quick acceptance of a term that lacks rigorous testing, measuring, and monitoring means that there is distinct lack of evidence base for deradicalisation being a genuine process/phenomenon, leading to academics retrospectively attempting to design frameworks and interventions around a concept that is not truly understood. The UK Home Office has openly acknowledged the lack of empirical data on this subject. This lack of evidence has a direct impact on policy and intervention development. Extremism and deradicalisation are issues that affect public health outcomes on a global scale, to the point that terrorism has now been added to the list of causes of trauma, both in the direct form of being victim of an attack but also the indirect context of witnesses, children and ordinary citizens who live in daily fear. This study critiques current deradicalisation discourses to establish whether public health approaches offer opportunities for development. The research begins by exploring the theoretical constructs of both what deradicalisation, and public health issues are. Questioning: What does deradicalisation involve? Is there an evidential base on which deradicalisation theory has established itself? What theory are public health interventions devised from? What does success look like in both fields? From establishing this base, current deradicalisation practices will then be explored through examples of work already being carried out. Critiques can be broken into discussion points of: Language, the difficulties with conducting empirical studies and the issues around outcome measurements that deradicalisation interventions face. This study argues that a public health approach towards deradicalisation offers the opportunity to attempt to bring clarity to the definitions of radicalisation, identify what could be modified through intervention and offer insights into the evaluation of interventions. As opposed to simply focusing on an element of deradicalisation and analysing that in isolation, a public health approach allows for what the literature has pointed out is missing, a comprehensive analysis of current interventions and information on creating efficacy monitoring systems. Interventions, policies, guidance, and practices in both the UK and Australia will be compared and contrasted, due to the joint nature of this research between Sheffield Hallam University and La Trobe, Melbourne.

Keywords: radicalisation, deradicalisation, violent extremism, public health

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Roberto Machado

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We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, analyzing 2,996 studies and synthesizing 41 of them to explore the evolution of data science and its integration into geography. By employing optimization algorithms, we accelerated the review process, significantly enhancing the efficiency and precision of literature selection. Our findings indicate that data science has developed over five decades, facing challenges such as the diversified integration of data and the need for advanced statistical and computational skills. In geography, the integration of data science underscores the importance of interdisciplinary collaboration and methodological innovation. Techniques like large-scale spatial data analysis and predictive algorithms show promise in natural disaster management and transportation route optimization, enabling faster and more effective responses. These advancements highlight the transformative potential of data science in geography, providing tools and methodologies to address complex spatial problems. The relevance of this study lies in the use of optimization algorithms in systematic reviews and the demonstrated need for deeper integration of data science into geography. Key contributions include identifying specific challenges in combining diverse spatial data and the necessity for advanced computational skills. Examples of connections between these two fields encompass significant improvements in natural disaster management and transportation efficiency, promoting more effective and sustainable environmental solutions with a positive societal impact.

Keywords: data science, geography, systematic review, optimization algorithms, supervised learning

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Authors: Harshan Baskar, Anirudh S. Chakravarthy, Prateek Garg, Divyam Goel, Abhijith S. Raj, Kshitij Kumar, Lakshya, Ravichandra Parvatham, V. Sushant, Bijay Kumar Rout

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In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a new benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a new network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve SSIM of 0.8962 and PSNR of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task, particularly for autonomous navigation applications, and we hope that our work will open up new frontiers in research. Our dataset and code will be made publicly available upon acceptance of our paper.

Keywords: dehazing, image enhancement, nighttime, computer vision

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Authors: Hannah Rosenqvist, Fanny Guay

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Critical infrastructure protection has been an important topic for several years. Programmes such as the European Programme for Critical Infrastructure Protection (EPCIP), Critical Infrastructure Warning Information Network (CIWIN) and the European Reference Network for Critical Infrastructure Protection (ENR-CIP) have been the pillars to the work done since 2006. However, measuring critical infrastructure resilience has not been an easy task. This has to do with the fact that the concept of resilience has several definitions and is applied in different domains such as engineering and social sciences. Since June 2015, the EU project IMPROVER has been focusing on developing a methodology for implementing a combination of societal, organizational and technological resilience concepts, in the hope to increase critical infrastructure resilience. For this paper, we performed research on how to include societal resilience as a form of measurement of the context of critical infrastructure resilience. Because one of the main purposes of critical infrastructure (CI) is to deliver services to the society, we believe that societal resilience is an important factor that should be considered when assessing the overall CI resilience. We found that existing methods for CI resilience assessment focus mainly on technical aspects and therefore that is was necessary to develop a resilience model that take social factors into account. The model developed within the project IMPROVER aims to include the community’s expectations of infrastructure operators as well as information sharing with the public and planning processes. By considering such aspects, the IMPROVER framework not only helps operators to increase the resilience of their infrastructures on the technical or organizational side, but aims to strengthen community resilience as a whole. This will further be achieved by taking interdependencies between critical infrastructures into consideration. The knowledge gained during this project will enrich current European policies and practices for improved disaster risk management. The framework for societal resilience analysis is based on three dimensions for societal resilience; coping capacity, adaptive capacity and transformative capacity which are capacities that have been recognized throughout a widespread literature review in the field. A set of indicators have been defined that describe a community’s maturity within these resilience dimensions. Further, the indicators are categorized into six community assets that need to be accessible and utilized in such a way that they allow responding to changes and unforeseen circumstances. We conclude that the societal resilience model developed within the project IMPROVER can give a good indication of the level of societal resilience to critical infrastructure operators.

Keywords: community resilience, critical infrastructure protection, critical infrastructure resilience, societal resilience

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Authors: S. P. Hewagama

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Different kinds of distressing events happen in the world causing a wide range of reactions and feelings. Psychological first aid (PFA) is humane supportive response for suffering. All health workers especially PHMs who play a major role as first responders in a disaster should be able to provide basic PFA effectively. Aim of this study was to assess the knowledge, attitudes and associated factors on the provision of PFA among PHMs during disasters. A descriptive cross-sectional study was carried out among 307 Public Health Midwives in Colombo RDHS area. In the study population, 86.6% (n=266) of the respondents were aware of the term “Psychological first aid” while 13.4% (n=41) were not aware. The total knowledge score was good in majority 85.4%(n=262) of the respondents while only 14.3%(n=45) had a poor knowledge on PFA. There was the statistically significant difference in relation to the level of education with the total knowledge score. Comprehensive desirable attitudes towards PFA was low (30.61%, n=94). According to the study, only a less than a quarter (21.82%, (n = 67)) of the study population had received training on PFA. More than half (56%, n=172) of the respondents had experience in responding to disasters. Conclusions and Recommendations: The overall knowledge and attitudes were found to be satisfactory. However, it is important to improve the knowledge level of the PHMs by providing training and workshops on PFA.

Keywords: disaster, humane supportive assistance, psychological first aid, public health midwives

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Authors: Kareem Adedokun

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Official secrecy is one of the colonial vestiges which upholds non – disclosure of essential information for public consumption. Information, though an indispensable tool in tax administration, is not to be divulged by any person in an official duty of the revenue agency. As a matter o fact, the Federal Inland Revenue Service (Establishment) Act, 2007 emphasizes secrecy and confidentiality in dealing with tax payer’s document, information, returns and assessment in a manner reminiscent of protecting tax payer’s privacy in all situations. It is so serious that any violation attracts criminal sanction. However, Nigeria, being a democratic and egalitarian state recently enacted Freedom of Information Act which heralded in openness in governance and takes away the confidentialities associated with official secrets Laws. Official secrecy no doubts contradicts the philosophy of freedom of information but maintaining a proper balance between protected rights of tax payers and public interest which revenue agency upholds is an uphill task. Adopting the Doctrinal method, therefore, the author of this paper probes into the real nature of the relationship between taxpayers and Revenue Agencies. It also interfaces official secrecy with the doctrine of Freedom of Information and consequently queries the retention of non – disclosure clause under Federal Inland Revenue Service (Establishment) Act (FIRSEA) 2007. The paper finds among others that non – disclosure provision in tax statutes particularly as provided for in FIRSEA is not absolute; so also is the constitutional rights and freedom of information and unless the non – disclosure clause finds justification under any recognized exemption provided under the Freedom of Information Act, its retention is antithesis to democratic ethos and beliefs as it may hinder public interest and public order.

Keywords: confidentiality, information, official secrecy, tax administration

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Authors: Ronald Mraz, Gary C. Kessler, Ethan Gold, John G. Cline

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The International Ice Patrol (IIP) continually monitors iceberg activity in the North Atlantic by direct observation using ships, aircraft, and satellite imagery. Daily reports detailing navigational boundaries of icebergs have significantly reduced the risk of iceberg contact. What is currently lacking is formatting this data for automatic transmission and display of iceberg navigational boundaries in commercial navigation equipment. This paper describes the methodology and implementation of a system to format iceberg limit information for dissemination through existing radio network communications. This information will then automatically display on commercial navigation equipment. Additionally, this information is reformatted for Google Earth rendering of iceberg track line limits. Having iceberg limit information automatically available in standard navigation equipment will help support full autonomous operation of sailing vessels.

Keywords: iceberg, iceberg risk, iceberg track lines, AIS messaging, international ice patrol, North American ice service, google earth, autonomous surface vessels

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Authors: Mohammed Sani Abdulai

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Public sector budgeting, all over the world, is underpinned by some universally accepted principles of sound budget management such as budget unity, universality, annuality, and a balanced budget. These traditional principles, though fundamental, had, in recent years, been augmented by the more modern principles of budgeting within fiscal objective, alignment with medium-term strategic plans as well as the observance of such related concepts as transparency, openness and accessibility. In this paper, we have endeavored to shed light, from literature and practice, on the meaning and purposes of such fundamental budgeting principles. We have also assessed the extent to which the Government of Ghana’s budget complies with the four traditional principles of budget unity, universality, annuality, and a balanced budget and the three out of the ten modern principles of budgetary governance of Organisation for Economic Co-operation and Development (OECD). We did so by using a qualitative method of review and analysis of existing documents and the performance assessment reports on Ghana’s Public Financial Management (PFM) measured using such frameworks as the Public Expenditure and Financial Accountability (PEFA), the Open Budget Survey (OBS) and its Index (OBI), the reports and action plans of Open Government Partnership (OGP) and the Global Initiative for Fiscal Transparency (GIFT). Other performance assessment reports that were relied on included, but not limited to, the Joint Evaluation Report of PFM in Ghana, 2001-2010, and the Joint Evaluation of Budget Support to Ghana, 2005-2015. We have, through this paper, brought to the fore the lessons that could be learned on how those budgetary principles undergird the Government of Ghana’s budget formulation, execution, accounting, control, and oversight. These lessons include, but are not limited to, the need for both scholars and practitioners in the PFM space to be aware of the impact of those principles on public sector budgeting.

Keywords: annulaity, balanced budget, budget unity, budgetary principles, OECD’s principles on budgetary governance, open budget index, public expenditure and financial accountability, universality

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Authors: Ningfei Xiao, Simon Twose, Hannah Hopewell

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In urban settings worldwide, artists and researchers have drawn from shamanic healing, providing insightful responses to the environment. This project is a transdisciplinary creative research project where architecture and art practice draw from shamanic healing and provide the potential to expand knowledge of public space and inspire more aesthetic explorations of public spatial visions. The research started from the encounters with the Ewengki/Evenki shaman tribe in settlement areas of northern China in 2019 and extended through the partnerships with Maori artists in Poneke Aotearoa, New Zealand, in 2023. Based on the learnings and collaborations with female indigenous tradition practitioners and the healing that the researcher received from the land, a spatial installation exhibition was developed in this project. Indigenous practices are intricately woven with contemporary technology, merging visuals, soundscapes, and other non-visual aesthetics influenced by the researcher's personal experiences of embodied shamanic healing with brainwave generative technology. This synthesis seeks to ritualize and reimagine future public spaces, encompassing streetscapes and greenscapes from China to Aotearoa, and fostering connections between urbanized human body, mind, spirit, and land. In doing so, the project presents a feminist posthuman inquiry into how individuals perceive materiality within the context of a future city. Grounded in creative research and embodied methodologies, this paper focuses on the conceptual and autoethnographic aspects of visual-non-visual aesthetics and their creative representation. Through the exploration of aesthetics beyond the visual realm within urban and spatial contexts, this project showcases the spatial installation exhibition as an example of shamanic influence and related response to public space through embodied artistry and transdisciplinary creative inquiry.

Keywords: aesthetic, embodiment, visual and/or non-visual, spatial installation, shamanic healing, public space

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Authors: Kamyar Fakhr, Roozbeh Salmani

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Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

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Authors: A. Briseno, A, Zorrilla

Abstract:

Firms are increasingly responding to social and environmental claims from society. Practices oriented to attend issues such as poverty, work equality, or renewable energy, are being implemented more frequently by firms to address impacts on sustainability. However, questions remain on how the responses of firms vary across industries and regions between the social and the economic objectives. Using concepts from organizational theory and social network theory, this paper aims to create a theoretical framework that explains the internal and external influences that make a firm establish its objective. The framework explains why firms might have a different objective orientation in terms of its economic and social prioritization.

Keywords: organizational identity, social network theory, firm objective, value maximization, social responsibility

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Authors: Alessandra Rossodivita, Alexei Tikhomirov, Andrey Trufanov, Nikolay Kinash, Olga Berestneva, Svetlana Nikitina, Fabio Casati, Alessandro Visconti, Tommaso Saporito

Abstract:

It is well known that world and national societies are exposed to diverse threats: anthropogenic, technological, and natural. Anthropogenic ones are of greater risks and, thus, attract special interest to researchers within wide spectrum of disciplines in efforts to lower the pertinent risks. Some researchers showed by means of multilayered, complex network models how media promotes the prevention of disease spread. To go further, not only are mass-media sources included in scope the paper suggests but also personificated social bots (socbots) linked according to reflexive theory. The novel scope considers information spread over conscious and unconscious agents while counteracting both natural and man-made threats, i.e., infections and terrorist hazards. Contrary to numerous publications on misinformation disseminated by ‘bad’ bots within social networks, this study focuses on ‘good’ bots, which should be mobilized to counter the former ones. These social bots deployed mixture with real social actors that are engaged in concerted actions at spreading, receiving and analyzing information. All the contemporary complex network platforms (multiplexes, interdependent networks, combined stem networks et al.) are comprised to describe and test socbots activities within competing information sharing tools, namely mass-media hubs, social networks, messengers, and e-mail at all phases of disasters. The scope and concomitant techniques present evidence that embedding such socbots into information sharing process crucially change the network topology of actor interactions. The change might improve or impair robustness of social network environment: it depends on who and how controls the socbots. It is demonstrated that the topological approach elucidates techno-social processes within the field and outline the roadmap to a safer world.

Keywords: complex network platform, counterterrorism, information sharing topology, social bots

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Authors: May Newisar, Richard Kingston, Philip Black

Abstract:

Heritage-led regeneration developments have been considered as one of the cornerstones of the economic and social revival of historic towns and cities in the UK. However, this approach has proved its deficiency within the development of Liverpool World Heritage site. This is due to the conflict between sustaining the tangible and intangible values as well as achieving the aimed economic developments. Accordingly, the development of such areas is influenced by a top-down approach which considers heritage as consumable experience and urban regeneration as the economic development for it. This neglects the heritage sites characteristics and values as well as the design criteria for public open spaces that overlap with the heritage sites. Currently, knowledge regarding the relationship between the physical built environment of the heritage sites including the intangible values and the design development of the public open spaces is limited. Public open spaces have been studied from different perspectives such as increasing walkability, a source of social cohesion, provide a good quality of life as well as understanding users’ perception. While heritage sites have been discussed heavily on how to maintain the physical environment, understanding the courses of threats and how to be protected. In addition to users’ experiences and motivations of visiting such areas. Furthermore, new approaches tried to overcome the gap such as the historic urban landscape approach. This approach is focusing on the entire human environment with all its tangible and intangible qualities. However, this research aims to understand the relationship between the heritage sites and public open spaces and how the overlap of the design and development of both could be used as a quality to enhance the heritage sites and improve users’ experience. A meaning-making approach will be used in order to understand and articulate how the development of Liverpool World Heritage site and its value could influence and shape the design of public open space Pier Head in order to attract a different level of tourists to be used as a tool for economic development. Consequently, this will help in bridging the gap between the planning and conservation areas’ policies through an understanding of how flexible is the system in order to adopt alternative approaches for the design and development strategies for those areas.

Keywords: historic urban landscape, environmental psychology, urban governance, identity

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Authors: Carolina Mayen Huerta, Clara Ivanescu, Paloma Marcos

Abstract:

Due to their unique geographic challenges and the imperative to combat climate change, Small Island Developing States (SIDS) are experiencing rapid growth in the renewable energy (RE) sector. However, women's representation in formal employment within this burgeoning field remains significantly lower than their male counterparts. Conventional methodologies often overlook critical geographic data that influence women's job prospects. To address this gap, this paper introduces a Multicriteria Evaluation (MCE) framework designed to identify spatially enabling environments and restrictions affecting women's access to formal employment and business opportunities in the SIDS' RE sector. The proposed MCE framework comprises 24 key factors categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. "Individual factors" encompass personal attributes influencing women's career development, including caregiving responsibilities, exposure to domestic violence, and disparities in education. "Contextual factors" pertain to the legal and policy environment, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment. "Accessibility factors" evaluate women's day-to-day mobility, considering travel patterns, access to public transport, educational facilities, RE job opportunities, healthcare facilities, and financial services. Finally, "Place Characterization factors" enclose attributes of geographical locations or environments. This dimension includes walkability, public transport availability, safety, electricity access, digital inclusion, fragility, conflict, violence, water and sanitation, and climatic factors in specific regions. The analytical framework proposed in this paper incorporates a spatial methodology to visualize regions within countries where conducive environments for women to access RE jobs exist. In areas where these environments are absent, the methodology serves as a decision-making tool to reinforce critical factors, such as transportation, education, and internet access, which currently hinder access to employment opportunities. This approach is designed to equip policymakers and institutions with data-driven insights, enabling them to make evidence-based decisions that consider the geographic dimensions of disparity. These insights, in turn, can help ensure the efficient allocation of resources to achieve gender equity objectives.

Keywords: gender, women, spatial analysis, renewable energy, access

Procedia PDF Downloads 69

Authors: Carolina Mayen Huerta, Clara Ivanescu, Paloma Marcos

Abstract:

Due to their unique geographic challenges and the imperative to combat climate change, Small Island Developing States (SIDS) are experiencing rapid growth in the renewable energy (RE) sector. However, women's representation in formal employment within this burgeoning field remains significantly lower than their male counterparts. Conventional methodologies often overlook critical geographic data that influence women's job prospects. To address this gap, this paper introduces a Multicriteria Evaluation (MCE) framework designed to identify spatially enabling environments and restrictions affecting women's access to formal employment and business opportunities in the SIDS' RE sector. The proposed MCE framework comprises 24 key factors categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. "Individual factors" encompass personal attributes influencing women's career development, including caregiving responsibilities, exposure to domestic violence, and disparities in education. "Contextual factors" pertain to the legal and policy environment, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment. "Accessibility factors" evaluate women's day-to-day mobility, considering travel patterns, access to public transport, educational facilities, RE job opportunities, healthcare facilities, and financial services. Finally, "Place Characterization factors" enclose attributes of geographical locations or environments. This dimension includes walkability, public transport availability, safety, electricity access, digital inclusion, fragility, conflict, violence, water and sanitation, and climatic factors in specific regions. The analytical framework proposed in this paper incorporates a spatial methodology to visualize regions within countries where conducive environments for women to access RE jobs exist. In areas where these environments are absent, the methodology serves as a decision-making tool to reinforce critical factors, such as transportation, education, and internet access, which currently hinder access to employment opportunities. This approach is designed to equip policymakers and institutions with data-driven insights, enabling them to make evidence-based decisions that consider the geographic dimensions of disparity. These insights, in turn, can help ensure the efficient allocation of resources to achieve gender equity objectives.

Keywords: gender, women, spatial analysis, renewable energy, access

Procedia PDF Downloads 83