Search results for: cloud computing framework

Authors: Anat Keller

Abstract:

Given that macro-prudential supervision is a relatively new policy area and its empirical and analytical research are still in their infancy, its theoretical foundations are also lagging behind. This paper contributes to the developing discussion on effective legal and institutional macroprudential supervision frameworks. In the first part of the paper, it is argued that effectiveness as a key benchmark poses some challenges in the context of macroprudential supervision such as the difficulty in proving causality between supervisory actions and the achievement of the supervisor’s mission. The paper suggests that effectiveness in the macroprudential context should, therefore, be assessed at the supervisory decision-making process (to be differentiated from the supervisory outcomes). The second part of the essay examines whether insights from behavioural economics can point to biases in the macroprudential decision-making process. These biases include, inter alia, preference bias, groupthink bias and inaction bias. It is argued that these biases are exacerbated in the multilateral setting of the macroprudential supervision framework in the EU. The paper then examines how legal and institutional frameworks should be designed to acknowledge and perhaps contain these identified biases. The paper suggests that the effectiveness of macroprudential policy will largely depend on the existence of clear and robust transparency and accountability arrangements. Accountability arrangements can be used as a vehicle for identifying and addressing potential biases in the macro-prudential framework, in particular, inaction bias. Inclusiveness of the public in the supervisory process in the form of transparency and awareness of the logic behind policy decisions may assist in minimising their potential unpopularity thus promoting their effectiveness. Furthermore, a governance structure which facilitates coordination of the macroprudential supervisor with other policymakers and incorporates outside perspectives and opinions could ‘break-down’ groupthink bias as well as inaction bias.

Keywords: behavioural economics and biases, effectiveness of macroprudential supervision, legal and institutional macroprudential frameworks, macroprudential decision-making process

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Authors: Samuel Ahamefula Mba

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Fluid turbulence is a complex and nonlinear phenomenon that occurs in various natural and industrial processes. Understanding turbulence remains a challenging task due to its intricate nature. One approach to gain insights into turbulence is through the study of entropy, which quantifies the disorder or randomness of a system. This research presents a numerical investigation of entropy signatures in fluid turbulence. The work is to develop a numerical framework to describe and analyse fluid turbulence in terms of entropy. This decomposes the turbulent flow field into different scales, ranging from large energy-containing eddies to small dissipative structures, thus establishing a correlation between entropy and other turbulence statistics. This entropy-based framework provides a powerful tool for understanding the underlying mechanisms driving turbulence and its impact on various phenomena. This work necessitates the derivation of the Poisson equation for pressure transformation of Navier-Stokes equation and using Chebyshev-Finite Difference techniques to effectively resolve it. To carry out the mathematical analysis, consider bounded domains with smooth solutions and non-periodic boundary conditions. To address this, a hybrid computational approach combining direct numerical simulation (DNS) and Large Eddy Simulation with Wall Models (LES-WM) is utilized to perform extensive simulations of turbulent flows. The potential impact ranges from industrial process optimization and improved prediction of weather patterns.

Keywords: turbulence, Navier-Stokes equation, Poisson pressure equation, numerical investigation, Chebyshev-finite difference, hybrid computational approach, large Eddy simulation with wall models, direct numerical simulation

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Authors: Meseret Gebeyehu Yehuala

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Women represent the majority of urban farmers engaged in vegetable and fruit production in Bahir Dar, Ethiopia. We examine urban agriculture in Bahir Dar city in the context of disruptions caused by the civil war and COVID-19. The Sustainable Livelihoods Framework serves as a conceptual frame to explore the vulnerability context, the structural and institutional challenges faced by women, and how this impacts their livelihoods. A total of 25 urban women farmers and 6 key informants were involved in the study through explorative and structured interviews conducted in 2021. Observations and informal conversations during repeated visits provided deeper insights. In addition, key informants employed in civil service institutions and experts were interviewed. Data were analysed by applying qualitative content analysis by using Atlas tia software. Women report that they experience a lack of access to land, insecurity of tenure, irregular technical support and input provision by agricultural extension services, and lack of access to credit and formal marketplaces. The COVID-19 pandemic restrictions aggravated this situation by delaying agricultural extension offices’ provision of necessary inputs and disrupting food handling and storage leading to the loss of perishable products. Bombing in relation to the civil war has destroyed harvests and left women in fear of returning to their fields. Women stated that vegetable and fruit production could contribute to their incomes, household food supplies, and more diversified diets. However, the city municipal office has, so far, not committed to supporting urban agriculture as a livelihood strategy.

Keywords: urban agriculture, institutional challenges, Bahir Dar, sustainable livelihood framework

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Authors: Delna Shroff

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Merchant shipping is an occupation with a high rate of fatal injuries caused by organizational accidents and maritime disasters. In most accident investigations, the leader’s actions are under scrutiny and point out the necessity to investigate the leader’s decisions in critical conditions. While several leadership studies have been carried out in the past, there is a tendency for most research to focus on holders of formal positions. The unit of analysis in most studies has been the ‘individual.’ A need is, therefore, felt to adopt a practice-based perspective of leadership, understand how leadership emerges to affect maritime safety. This paper explores the phenomenon of distributed leadership among seafarers more holistically. It further examines the role of one form of distributed leadership, that is, planfully aligned leadership in the emergency response of the team. A mixed design will be applied. In the first phase, the data gathered by way of semi-structured interviews will be used to explore the seafarer’s implicit understanding of leadership. The data will be used to develop a conceptual framework of distributed leadership, specific to the maritime context. This framework will be used to develop a simulation. Experimental design will be used to examine the relationship between planfully aligned leadership and emergency response of the team members during navigation. Findings show that planfully aligned leadership significantly and positively predicts the emergency response of team members. Planfully aligned leadership leads to a better emergency response of the team members as compared to authoritarian leadership. In the third qualitative phase, additional data will be gathered through semi-structured interviews to further validate the findings to gain a more complete understanding of distributed leadership and its relation to emergency response. Above are the predictive results; the study expects to be a cornerstone of safety leadership research and has important implications for leadership development and training within the maritime industry.

Keywords: authoritarian leadership, distributed leadership, emergency response , planfully aligned leadership

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Authors: Andrew Kipp

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Student absenteeism is harmful to both the school and the absentee student. One approach to improving student absenteeism is targeting contextual factors within the students’ learning environment. However, contemporary literature has not taken an ecological agency approach to understanding student absenteeism. Ecological agency is a theoretical framework that magnifies the interplay between the environment and the actions of people within the environment. To elaborate, the person’s personal history and aspirations and the environmental conditions provide potential outlets or restrictions to their intended action. The framework provides the unique perspective of understanding absentee students’ decision-making through the affordances and constraints found in their learning environment. To that effect, the study was guided by the question, “Why do absentee students decide to engage in absenteeism in a suburban Kansas school?” A case study methodology was used to answer the research question. Four suburban, Kansas high school absentee students in the 2020-2021 school year were selected for the study. The fall 2020 semester was in a remote learning setting, and the spring 2021 semester was in an in-person learning setting. The study captured their decision-making with respect to school attendance throughsemi-structured interviews, prolonged observations, drawings, and concept maps. The data was analyzed through thematic analysis. The findings revealed that peer socialization opportunities, methods of instruction, shifts in cultural beliefs due to COVID-19, manifestations of anxiety and lack of space to escape their anxiety, social media bullying, and the inability to receive academic tutoring motivated the participants’ daily decision to either attend or miss school. The findings provided a basis to improve several institutional and classroom practices. These practices included more student-led instruction and less teacher-led instruction in both in-person and remote learning environments, promoting socialization through classroom collaboration and clubs based on emerging student interests, reducing instances of bullying through prosocial education, safe spaces for students to escape the classroom to manage their anxiety, and more opportunities for one-on-one tutoring to improve grades. The study provides an example of using the ecological agency approach to better understand the personal and environmental factors that lead to absenteeism. The study also informs educational policies and classroom practices to better promote student attendance. Further research should investigate other school contexts using the ecological agency theoretical framework to better understand the influence of the school environment on student absenteeism.

Keywords: student absenteeism, ecological agency, classroom practices, educational policy, student decision-making

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Authors: Jian-Jun Shu

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The statistical properties of CRMs are explored by estimating similar-word set occurrence distribution. It is observed that CRMs tend to have a fat-tail distribution for similar-word set occurrence. Thus, the fat-tail test with two fatness coefficients is proposed to distinguish CRMs from non-CRMs, especially from exons. For the first fatness coefficient, the separation accuracy between CRMs and exons is increased as compared with the existing content-based CRM prediction method – fluffy-tail test. For the second fatness coefficient, the computing time is reduced as compared with fluffy-tail test, making it very suitable for long sequences and large data-base analysis in the post-genome time. Moreover, these indexes may be used to predict the CRMs which have not yet been observed experimentally. This can serve as a valuable filtering process for experiment.

Keywords: statistical approach, transcription factor binding sites, cis-regulatory modules, DNA sequences

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Authors: Peter Tabatt, Christian Siemers

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Using FPGA devices to improve the behavior of time-critical parts of embedded systems is a proven concept for years. With reconfigurable FPGA devices, the logical blocks can be partitioned and grouped into static and dynamic parts. The dynamic parts can be reloaded 'on demand' at runtime. This work uses cellular automata, which are constructed through compilation from (partially restricted) ANSI-C sources, to determine the suitability of various metrics for optimal partitioning. Significant metrics, in this case, are for example the area on the FPGA device for the partition, the pass count for loop constructs and communication characteristics to other partitions. With successful partitioning, it is possible to use smaller FPGA devices for the same requirements as with not reconfigurable FPGA devices or – vice versa – to use the same FPGAs for larger programs.

Keywords: reconfigurable FPGA, cellular automata, partitioning, metrics, parallel computing

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Authors: Melanie Kerschner

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Language is our main means of social interaction. News journalism, especially opinion discourse, holds a powerful position in this context. Editorials can be regarded as encounters of different, partially contradictory relationships between discourse participants constructed through the editorial voice. Their primary goal is to shape public opinion by commenting on events already addressed by other journalistic genres in the given newspaper. In doing so, the author tries to establish a consensus over the negotiated matter (i.e. the news event) with the reader. At the same time, he/she claims authority over the “correct” description and evaluation of an event. Yet, how can the relationship and the interaction between the discourse participants, i.e. the journalist, the reader and the news actors represented in the editorial, be best visualized and studied from a cross-cultural perspective? The present research project attempts to give insights into the role of (media) culture in British, Italian and German editorials. For this purpose the presenter will propose a basic framework: the so called “pyramid of discourse participants”, comprising the author, the reader, two types of news actors and the semantic macro-structure (as meta-level of analysis). Based on this framework, the following questions will be addressed: • Which strategies does the author employ to persuade the reader and to prompt him to give his opinion (in the comment section)? • In which ways (and with which linguistic tools) is editorial opinion expressed? • Does the author use adjectives, adverbials and modal verbs to evaluate news actors, their actions and the current state of affairs or does he/she prefer nominal labels? • Which influence do language choice and the related media culture have on the representation of news events in editorials? • In how far does the social context of a given media culture influence the amount of criticism and the way it is mediated so that it is still culturally-acceptable? The following culture-contrastive study shall examine 45 editorials (i.e. 15 per media culture) from six national quality papers that are similar in distribution, importance and the kind of envisaged readership to make valuable conclusions about culturally-motivated similarities and differences in the coverage and assessment of news events. The thematic orientation of the editorials will be the NSA scandal and the reactions of various countries, as this topic was and still is relevant to each of the three media cultures. Starting out from the “pyramid of discourse participants” as underlying framework, eight different criteria will be assigned to the individual discourse participants in the micro-analysis of the editorials. For the purpose of illustration, a single criterion, referring to the salience of authorial opinion, will be selected to demonstrate how the pyramid of discourse participants can be applied as a basis for empirical analysis. Extracts from the corpus shall furthermore enhance the understanding.

Keywords: Micro-analysis of editorials, culture-contrastive research, media culture, interaction between discourse participants, evaluation

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Authors: Lucas Bublitz, Michael Herdrich

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By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

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Authors: Anjali Kanagali, Astha Sinha

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Climate change is the greatest threat being faced by mankind in the 21st century. It no longer is merely an environmental, scientific or economic issue but is a humanitarian issue as well. Paris Agreement put great pressure on the businesses to reduce carbon emissions and mitigate the impact of climate change. However, the already increased climate variability and extreme weather are aggravating emergency humanitarian needs. According to the Intergovernmental Panel on Climate Change (IPCC), if efficient policy changes are not made in time to combat the climate change issues, the situation will deteriorate with an estimated global temperature rise of 4 degrees. The existing international network of Humanitarian system is not adequately structured to handle the projected natural disasters and climate change crisis. The 2030 Agenda which embraces the 17 Sustainable Development Goals (SGDs) discussed the relationship between the climate change and humanitarian assistance. The Humanitarian law aims to protect, amongst other things, ‘internally displaced persons’ which includes people displaced due to natural hazard related disasters engulfing the hazards of climate change. ‘Legal protection’ of displaced people to protect their rights is becoming a pressing need in such times. In this paper, attempts will be made to analyze the causes of the displacement, identify areas where the effect of the climate change is most likely to occur and to examine the character of forced displacement triggering population movement. We shall discuss the pressure on the Humanitarian system and assistance due to climate change issues and the need for vesting powers to the local communities or local government players to deal with the climate changes. We shall also discuss the possibility of setting up a new framework where non-state actors could be set up for climate change impact and its governance.

Keywords: humanitarian assistance to climate change, humanitarian crisis, internally displaced person, legal framework for climate migrants, non-state actors

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Authors: Divij Gupta

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Pendular systems have a range of both mathematical and engineering applications, ranging from modelling the behaviour of a continuous mass-density rope to utilisation as Tuned Mass Dampers (TMD). Thus, it is of interest to study the differential equations governing the motion of such systems. Here we attempt to generalise these equations of motion for the plane compound pendulum with a finite number of N point masses. A Lagrangian approach is taken, and we attempt to find the generalised form for the Euler-Lagrange equations of motion for the i-th bob of the N -bob pendulum. The co-ordinates are parameterized as angular quantities to reduce the number of degrees of freedom from 2N to N to simplify the form of the equations. We analyse the form of these equations up to N = 4 to determine the general form of the equation. We also develop a MATLAB program to compute a solution to the system for a given input value of N and a given set of initial conditions.

Keywords: classical mechanics, differential equation, lagrangian analysis, pendulum

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Authors: Diane Ghanem, Whitney Kagabo, Rebecca Engels, Uma Srikumaran, Babar Shafiq

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Hospitalist co-management of orthopaedic surgery patients is a growing trend across the country. It was created as a collaborative effort to provide overarching care to patients with the goal of improving their postoperative care and decreasing in-hospital medical complications. The aim of this project is to provide a guide for implementing and optimizing a hospitalist co-management service in orthopaedic surgery. Key leaders from the hospitalist team, orthopaedic team and quality, safety and service team were identified. Multiple meetings were convened to discuss the comanagement service and determine the necessary building blocks behind an efficient and well-designed co-management framework. After meticulous deliberation, a consensus was reached on the final service agreement and a written guide was drafted. Fundamental features of the service include the identification of service stakeholders and leaders, frequent consensus meetings, a well-defined framework, with goals, program metrics and unified commands, and a regular satisfaction assessment to update and improve the program. Identified pearls for co-managing orthopaedic surgery patients are standardization, timing, adequate patient selection, and two-way feedback between hospitalists and orthopaedic surgeons to optimize the protocols. Developing a service agreement is a constant work in progress, with meetings, discussions, revisions, and multiple piloting attempts before implementation. It is a partnership created to provide hospitals with a streamlined admission process where at-risk patients are identified early, and patient care is optimized regardless of the number or nature of medical comorbidities. A wellestablished hospitalist co-management service can increase patient care quality and safety, as well as health care value.

Keywords: co-management, hospitalist co-management, implementation, orthopaedic surgery, quality improvement

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Authors: T. Salami, O. S. Idowu, N. J. Bello

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Climatic variability is an essential issue when dealing with the issue of climate change. Variability of some climate parameter helps to determine how variable the climatic condition of a region will behave. The most important of these climatic variables which help to determine the climatic condition in an area are both the Temperature and Precipitation. This research deals with Longterm climatic variability in Nigeria. Variables examined in this analysis include near-surface temperature, near surface minimum temperature, maximum temperature, relative humidity, vapour pressure, precipitation, wet-day frequency and cloud cover using data ranging between 1901-2010. Analyses were carried out and the following methods were used: - Regression and EOF analysis. Results show that the annual average, minimum and maximum near-surface temperature all gradually increases from 1901 to 2010. And they are in the same case in a wet season and dry season. Minimum near-surface temperature, with its linear trends are significant for annual, wet season and dry season means. However, the diurnal temperature range decreases in the recent 100 years imply that the minimum near-surface temperature has increased more than the maximum. Both precipitation and wet day frequency decline from the analysis, demonstrating that Nigeria has become dryer than before by the way of rainfall. Temperature and precipitation variability has become very high during these periods especially in the Northern areas. Areas which had excessive rainfall were confronted with flooding and other related issues while area that had less precipitation were all confronted with drought. More practical issues will be presented.

Keywords: climate, variability, flooding, excessive rainfall

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Authors: Yoganathan Karthik, Guhanathan Poravi

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Colorizing near-infrared (NIR) images poses unique challenges due to the absence of color information and the nuances in light absorption. In this paper, we present an approach to NIR image colorization utilizing a synthetic dataset generated from visible light images. Our method addresses two major challenges encountered in NIR image colorization: accurately colorizing objects with color variations and avoiding over/under saturation in dimly lit scenes. To tackle these challenges, we propose a Generative Adversarial Network (GAN)-based framework that learns to map NIR images to their corresponding colorized versions. The synthetic dataset ensures diverse color representations, enabling the model to effectively handle objects with varying hues and shades. Furthermore, the GAN architecture facilitates the generation of realistic colorizations while preserving the integrity of dimly lit scenes, thus mitigating issues related to over/under saturation. Experimental results on benchmark NIR image datasets demonstrate the efficacy of our approach in producing high-quality colorizations with improved color accuracy and naturalness. Quantitative evaluations and comparative studies validate the superiority of our method over existing techniques, showcasing its robustness and generalization capability across diverse NIR image scenarios. Our research not only contributes to advancing NIR image colorization but also underscores the importance of synthetic datasets and GANs in addressing domain-specific challenges in image processing tasks. The proposed framework holds promise for various applications in remote sensing, medical imaging, and surveillance where accurate color representation of NIR imagery is crucial for analysis and interpretation.

Keywords: computer vision, near-infrared images, automatic image colorization, generative adversarial networks, synthetic data

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Authors: Belkacem Benadda, Adil Benabdellah, Boutheyna Souna

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The Internet of Things (IoT) is an unprecedented creation. Electronics objects are now able to interact, share, respond and adapt to their environment on a much larger basis. Actual spread of these modern means of connectivity and solutions with high data volume exchange are affecting our ways of life. Accommodation is becoming an intelligent living space, not only suited to the people circumstances and desires, but also to systems constraints to make daily life simpler, cheaper, increase possibilities and achieve a higher level of services and luxury. In this paper we are as Internet access, teleworking, consumption monitoring, information search, etc.). This paper addresses the design and integration of a smart home, it also purposes an IoT solution that allows smart power consumption based on measurements from power-grid and deep learning analysis.

Keywords: array sensors, IoT, power grid, FPGA, embedded

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Authors: Andreas Kapardis, Maria Krambia-Kapardis, Sofia Michaelides-Mateou

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Corruption and economic crime is a serious problem affecting the sustainability of businesses in the 21st century. Nowadays, many corruption or fraud cases come to light thanks to whistleblowers. This article will first discuss the concept of whistleblowing as well as some relevant legislation enacted around the world. Secondly, it will discuss the findings of a survey of whistleblowers or could-have-been whistleblowers. Finally, suggestions for the development of a comprehensive whistleblowing framework will be considered. Whistleblowing can be described as expressing a concern about a wrongdoing within an organization, such as a corporation, an association, an institution or a union. Such concern must be in the public interest and in good faith and should relate to the cover up of matters that could potentially result in a miscarriage of justice, a crime, criminal offence and threats to health and safety. Whistleblowing has proven to be an effective anti-corruption mechanism and a powerful tool that helps deterring fraud, violations, and malpractices within organizations, corporations and the public sector. Research in the field of whistleblowing has concentrated on the reasons for whistleblowing and financial bounties; the effectiveness of whistleblowing; whistleblowing being a prosocial behavior with a psychological perspective and consequences; as a tool in protecting shareholders, saving lives and billions of dollars of public funds. Whilst, no other study of whistleblowing has been carried out on whistleblowers or intended whistleblowers. The study reported in the current paper analyses the findings of 74 whistleblowers or intended whistleblowers, the reasons behind their decision to blow the whistle, or not to proceed to blow the whistle and any regrets they may have had. In addition a profile of a whistleblower is developed concerning their age, gender, marital and family status and position in an organization. Lessons learned from the intended whistleblowers and in response to the questions if they would be willing to blow the whistle again show that enacting legislation to protect the whistleblower is not enough. Similarly, rewarding the whistleblower does not appear to provide the whistleblower with an incentive since the majority noted that “work ethics is more important than financial rewards”. We recommend the development of a comprehensive and holistic framework for the protection of the whistleblower and to ensure that remedial actions are immediately taken once a whistleblower comes forward. The suggested framework comprises (a) hard legislation in ensuring the whistleblowers follow certain principles when blowing the whistle and, in return, are protected for a period of 5 years from being fired, dismissed, bullied, harassed; (b) soft legislation in establishing an agency to firstly ensure psychological and legal advice is provided to the whistleblowers and secondly any required remedial action is immediately taken to avert the undesirable events reported by a whistleblower from occurring and, finally; (c) mechanisms to ensure the coordination of actions taken.

Keywords: whistleblowing, business ethics, legislation, business

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Authors: Noriki Amano

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The final goal of this study is to create another way in which people enjoy music through the performance of 'Wearable Music'. Concretely speaking, we generate colorful costumes in real- time from music and to realize their dressing by projecting them to a person. For this purpose, we propose three methods in this study. First, a method of giving color to music in a three-dimensionally way. Second, a method of generating images of costumes from music. Third, a method of wearing the images of music. In particular, this study stands out from other related work in that we generate images of unique costumes from music and realize to wear them. In this study, we use the technique of generative arts to generate images of unique costumes and project the images to the fog generated around a person from 3-way using projectors. From this study, we can get how to enjoy music as 'wearable'. Furthermore, we are also able to have the prospect of unconventional entertainment based on the fusion between music and costumes.

Keywords: entertainment computing, costumes, music, generative programming

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Authors: Yusuf Garba Baba

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The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.

Keywords: risk management, risk identification, risk analysis, analytic hierarchical process

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

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Authors: Abdul Khalique Baloch, Ali Okatan

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The quality analysis of food and vegetable from image is hot topic now a day, where researchers make them better then pervious findings through different technique and methods. In this research we have review the literature, and find gape from them, and suggest better proposed approach, design the algorithm, developed a software to measure the quality from images, where accuracy of image show better results, and compare the results with Perouse work done so for. The Application we uses an open-source dataset and python language with tensor flow lite framework. In this research we focus to sort food and vegetable from image, in the images, the application can sorts and make them grading after process the images, it could create less errors them human base sorting errors by manual grading. Digital pictures datasets were created. The collected images arranged by classes. The classification accuracy of the system was about 94%. As fruits and vegetables play main role in day-to-day life, the quality of fruits and vegetables is necessary in evaluating agricultural produce, the customer always buy good quality fruits and vegetables. This document is about quality detection of fruit and vegetables using images. Most of customers suffering due to unhealthy foods and vegetables by suppliers, so there is no proper quality measurement level followed by hotel managements. it have developed software to measure the quality of the fruits and vegetables by using images, it will tell you how is your fruits and vegetables are fresh or rotten. Some algorithms reviewed in this thesis including digital images, ResNet, VGG16, CNN and Transfer Learning grading feature extraction. This application used an open source dataset of images and language used python, and designs a framework of system.

Keywords: deep learning, computer vision, image processing, rotten fruit detection, fruits quality criteria, vegetables quality criteria

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Authors: Nuria Vargas, Frances Rodriguez

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Neotropical medium cities have opportunities to develop in a good manner. Xalapa City (Veracruz capital, Mexico) and its metropolitan region, near to the Gulf of Mexico, has already <1 million inhabitants, a medium city size, but it’s growing rapidly as several cities in Latin America. Inside a landscape where it had been a forest cloud and coffee land, emerges the city with an irregular topography. The rapid grow of the urbanization and the loss of vegetation has result in a change on the climate parameters. Frequently warms spells, floods and landslides had been impacted last 2 decades, also a higher incidence of dengue and diarrhea is mentioned in the region. Therefore, the analysis of hydrometeorological events is crucial to understand the role they play in its problem. The urbanization and others radiative forces has created a modulation that can explain the decadal climate changes on the Xalapa region. The Atlantic Multidecadal Oscillation directly influences the temperature and precipitation of the region, even more than climate change does. The total effect of these drivers can create a significant context that origin more risk. However, the most policies frequently consider only the climate change as a principal factor, but other drivers are important to consider and evaluate for the implementation of actions that improve our ambient and cities, in a context of climate change. Medium-sized cities could create better conditions for future citizens, preventing with urban planning that considers possible risks associated with weather and climate.

Keywords: natural variability, urbanization, atlantic multidecadal oscillation, land use changes

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Authors: Bekim Berisha, Sebastian Hirsiger, Pavel Hora

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Advanced material models involving several sets of model parameters require a big experimental effort. As models are getting more and more complex like e.g. the so called “Homogeneous Anisotropic Hardening - HAH” model for description of the yielding behavior in the 2D/3D stress space, the number and complexity of the required experiments are also increasing continuously. In the context of sheet metal forming, these requirements are even more pronounced, because of the anisotropic behavior or sheet materials. In addition, some of the experiments are very difficult to perform e.g. the plane stress biaxial compression test. Accordingly, tensile tests in at least three directions, biaxial tests and tension-compression or shear-reverse shear experiments are performed to determine the parameters of the macroscopic models. Therefore, determination of the macroscopic model parameters based on virtual experiments is a very promising strategy to overcome these difficulties. For this purpose, in the framework of multiscale material modeling, a dislocation density based crystal plasticity model in combination with a FFT-based spectral solver is applied to perform virtual experiments. Modeling of the plastic behavior of metals based on crystal plasticity theory is a well-established methodology. However, in general, the computation time is very high and therefore, the computations are restricted to simplified microstructures as well as simple polycrystal models. In this study, a dislocation density based crystal plasticity model – including an implementation of the backstress – is used in a spectral solver framework to generate virtual experiments for three deep drawing materials, DC05-steel, AA6111-T4 and AA4045 aluminum alloys. For this purpose, uniaxial as well as multiaxial loading cases, including various pre-strain histories, has been computed and validated with real experiments. These investigations showed that crystal plasticity modeling in the framework of Representative Volume Elements (RVEs) can be used to replace most of the expensive real experiments. Further, model parameters of advanced macroscopic models like the HAH model can be determined from virtual experiments, even for multiaxial deformation histories. It was also found that crystal plasticity modeling can be used to model anisotropic hardening more accurately by considering the backstress, similar to well-established macroscopic kinematic hardening models. It can be concluded that an efficient coupling of crystal plasticity models and the spectral solver leads to a significant reduction of the amount of real experiments needed to calibrate macroscopic models. This advantage leads also to a significant reduction of computational effort needed for the optimization of metal forming process. Further, due to the time efficient spectral solver used in the computation of the RVE models, detailed modeling of the microstructure are possible.

Keywords: anisotropic hardening, crystal plasticity, micro structure, spectral solver

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Authors: Raul G. Angeles, Rowena R. De Guzman

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The future workforce for health in a globalized context highlights better health human resource planning. Health sciences students are challenged to develop skills needed for global migration. Advancing health sciences education is crucial in preparing them to overcome border challenges. The purpose of this mixed-method, two-part study was to determine the extent by which the current instructional planning and implementation (IPI) framework is reframed with teaching approaches that foster students' 21st-century skills development and to examine participants’ over-all insights on learner-centered teaching and learning (LCTL) particularly in health sciences classrooms. Participants were groups of teachers and students drawn from a national sample through the Philippine higher education institutions (HEIs). To the participants, the use of technology, practices driven by students’ interests and enriching learning experiences through project-based learning are the approaches that must be incorporated with great extent in IPI to encourage student engagement, active learning and collaboration. Participants were asked to detail their insights of learner-centered teaching and learning and using thematic content analysis parallel insights between the groups of participants lead to three emerging themes: opportunities, challenges and prospects. More contemporary understanding of LTCL in today’s health sciences classrooms were demonstrated by the participants. Armed with true understanding, educational leaders can provide interventions appropriate to the students’ level of need, teachers’ preparation and school’s readiness in terms of resources. Health sciences classrooms are innovated to meet the needs of the current and future students.

Keywords: globalization, health workforce, role of education, student-centered teaching and learning, technology in education

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Authors: Sawarni Hasibuan, Juliza Hidayati

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Competitiveness and sustainability issues not only put pressure on big companies, but also small and medium enterprises (SMEs). SMEs Batik Bogor is one of the local culture-based creative industries in Bogor city which is also dealing with the issue of sustainability. The purpose of this research is to develop framework of sustainability at SMEs Batik Indonesia case of SMEs Batik Bogor by integrating innovation of cleaner production in its supply chain. The approach used is desk study, field survey, in-depth interviews, and benchmarking best practices of SMEs sustainability. In-depth interviews involve stakeholders to identify the needs and standards of sustainability of SMEs Batik. Data analysis was done by benchmarking method, Multi Dimension Scaling (MDS) method, and Strength, Weakness, Opportunity, Threat (SWOT) analysis. The results recommend the framework of sustainability for SMEs Batik in Indonesia. The sustainability status of SMEs Batik Bogor is classified as Moderate Sustainable. Factors that support the sustainability of SMEs Batik Bogor such is a strong commitment of top management in adopting cleaner production innovation and creativity approach. Successful cleaner production innovations are implemented primarily in the substitution of dye materials from toxic to non-toxic, reducing the intensity of non-renewable energy use, as well as the reuse and recycle of solid waste. “Mosaic Batik” is one of the innovations of solid waste utilization of batik waste produced by company R&D center that gives benefit to three pillars of sustainability, that is financial benefit, environmental benefit, and social benefit. The sustainability of SMEs Batik Bogor cannot be separated from the support of Bogor City Government which proactively facilitates the promotion of sustainable innovation produced by SMEs Batik Bogor.

Keywords: cleaner production innovation, creativity, SMEs Batik, sustainability supply chain

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Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

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High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

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Authors: Xinwen Zhu, Xingguang Li, Sun Yi

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Crack is one of the most common damages in buildings, bridges, roads and so on, which may pose safety hazards. However, cracks frequently happen in structures of various materials. Traditional methods of manual detection and measurement, which are known as subjective, time-consuming, and labor-intensive, are gradually unable to meet the needs of modern development. In addition, crack detection and measurement need be safe considering space limitations and danger. Intelligent crack detection has become necessary research. In this paper, an efficient method for crack detection and quantification using a 3D sensor, LiDAR, and depth camera is proposed. This method works even in a dark environment, which is usual in real-world applications. The LiDAR rapidly spins to scan the surrounding environment and discover cracks through lasers thousands of times per second, providing a rich, 3D point cloud in real-time. The LiDAR provides quite accurate depth information. The precision of the distance of each point can be determined within around  ±3 cm accuracy, and not only it is good for getting a precise distance, but it also allows us to see far of over 100m going with the top range models. But the accuracy is still large for some high precision structures of material. To make the depth of crack is much more accurate, the depth camera is in need. The cracks are scanned by the depth camera at the same time. Finally, all data from LiDAR and Depth cameras are analyzed, and the size of the cracks can be quantified successfully. The comparison shows that the minimum and mean absolute percentage error between measured and calculated width are about 2.22% and 6.27%, respectively. The experiments and results are presented in this paper.

Keywords: LiDAR, depth camera, real-time, detection and measurement

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Authors: Alex Knighton, Roba Khundkar, Michael Dunn

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Neo-colonialism is defined as the use of economic, political, cultural, or other pressures to control or influence other countries, especially former dependencies, and concerns have been raised about its presence in surgical missions. Surgical missions aim to rectify the huge disparity in surgical access worldwide, but their ethics must be carefully considered. This is especially in light of colonial history which affects international relations and global health today, to ensure that colonial attitudes are not influencing efforts to promote equity. This review examines the history of colonial global health, demonstrating that global health initiatives have consistently been used to benefit those providing them, and then asks whether elements of colonialism are still pervasive in surgical missions today. Data was collected from the literature using specified search terms and snowball searching, as well as from international expert web-based conferences on global surgery ethics. A thematic analysis was then conducted on this data, resulting in the identification of six themes which are identifiable in both past and present global health initiatives. These six themes are power, lack of understanding or respect, feelings of superiority, exploitation, enabling of dependency, and acceptance of poorer standards of care. An ethical analysis follows, concluding that the concerns of power and neo-colonialism in global surgery would be addressed by adopting a framework of procedural justice that promotes a refined governance process in which stakeholders are able to propose and reject decisions that affect them. The paper argues that adopting this model would address concerns of the power disparity in the field directly, as well as promoting an ethical framework to enable the other concerns of power disparity and neo-colonialism identified in the present analysis to be addressed.

Keywords: medical ethics, global surgery, global health, neocolonialism, surgical missions

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Authors: Modesta E. Ezema, Chikwendu V. Alabekee, Victoria N. Ishiwu, Ifeyinwa NwosuArize, Chinedu I. Nwoye

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The advent of wireless networking in computing technology cannot be overemphasized, it opened up easy accessibility to information resources, networking made easier and brought internet accessibility to our doorsteps, but despite all these, some mishap came in with it that is causing mayhem in today ‘s overall information security. The cyber criminals will always compromise the integrity of a message that is not encrypted or that is encrypted with a weak algorithm.In other to correct the mayhem, this study focuses on cryptosystem and cryptography. This ensures end to end crypt messaging. The study of various cryptographic algorithms, as well as the techniques and applications of the cryptography for efficiency, were all considered in the work., present and future applications of cryptography were dealt with as well as Quantum Cryptography was exposed as the current and the future area in the development of cryptography. An empirical study was conducted to collect data from network users.

Keywords: algorithm, cryptography, cryptosystem, network

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Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

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Authors: Saheed Ahmad Rufai

Abstract:

The growing nature of insurgencies in their various forms in the Muslim world is now of great concern to both the leadership and the citizenry. The high sense of insecurity occasioned by the unpleasant experience has in fact attained an alarming rate in the estimation of both Muslims and non-Muslims alike. Consequently, the situation began to attract contributions from scholars and researchers in security-related fields of humanities and social sciences. However, there is little evidence of contribution to the discourse and the scholarship involved by scholars in the field of education. The purpose of this proposed study is to contribute an education dimension to the growing scholarship on the subject. The study which is situated in the broad scholarship of curriculum making and grounded in both the philosophical and sociological foundations of the curriculum, employs a combination of curriculum criticism and creative synthesis, as methods, in reconstructing Muslim schools’ educational blueprint. The significance of the proposed study lies in its potential to contribute a useful addition to the scholarship of curriculum construction in the context of the Muslim world. The significance also lies in its potential to offer an ameliorative proposal over unnecessary insurgency or militancy thereby paving the way for the enthronement of a regime characterized by peaceful, harmonious and tranquil co-existence among people of diverse orientations and ideological persuasions in the Muslim world. The study is restricted to only the first two stages of curriculum making namely the formulation of philosophy which concerns the articulation of objectives, aims, purposes, goals, and principles, as well as the second stage which covers the translation of such principles to an anti-insurgency secondary school curriculum for the Muslim world.

Keywords: education for conflict resolution, anti-insurgency curriculum principles, peace education, anti-terrorist curriculum framework, curriculum for Muslim secondary schools

Procedia PDF Downloads 224