Search results for: bicycle handle bar

Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

Procedia PDF Downloads 294

Authors: Radul Shishkov, Orlin Davchev

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The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

Procedia PDF Downloads 63

Authors: A. Bayat, R. Bello-Mendoza, D. G. Wareham

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Two major categories of green waste are fruit and vegetable (FV) waste and garden and yard (GY) waste. Although, anaerobic digestions (AD) is able to manage FV waste; there is less confidence in the conditions for AD to handle GY wastes (grass, leaves, trees and bush trimmings); mainly because GY contains lignin and other recalcitrant organics. GY in the dry state (TS ≥ 15 %) can be digested at mesophilic temperatures; however, little methane data has been reported under thermophilic conditions, where conceivably better methane yields could be achieved. In addition, it is suspected that at lower solids concentrations, the methane yield could be increased. As such, the aim of this research is to find the temperature and solids concentration conditions that produce the most methane; under two different temperature regimes (mesophilic, thermophilic) and three solids states (i.e. 'dry', 'semi-dry' and 'wet'). Twenty liters of GY waste was collected from a public park located in the northern district in Tehran. The clippings consisted of freshly cut grass as well as dry branches and leaves. The GY waste was chopped before being fed into a mechanical blender that reduced it to a paste-like consistency. An initial TS concentration of approximately 38 % was achieved. Four hundred mL of anaerobic inoculum (average total solids (TS) concentration of 2.03 ± 0.131 % of which 73.4% were volatile solid (VS), soluble chemical oxygen demand (sCOD) of 4.59 ± 0.3 g/L) was mixed with the GY waste substrate paste (along with distilled water) to achieve a TS content of approximately 20 %. For comparative purposes, approximately 20 liters of FV waste was ground in the same manner as the GY waste. Since FV waste has a much higher natural water content than GY, it was dewatered to obtain a starting TS concentration in the dry solid-state range (TS ≥ 15 %). Three samples were dewatered to an average starting TS concentration of 32.71 %. The inoculum was added (along with distilled water) to dilute the initial FV TS concentrations down to semi-dry conditions (10-15 %) and wet conditions (below 10 %). Twelve 1-L batch bioreactors were loaded simultaneously with either GY or FV waste at TS solid concentrations ranging from 3.85 ± 1.22 % to 20.11 ± 1.23 %. The reactors were sealed and were operated for 30 days while being immersed in water baths to maintain a constant temperature of 37 ± 0.5 °C (mesophilic) or 55 ± 0.5 °C (thermophilic). A maximum methane yield of 115.42 (L methane/ kg VS added) was obtained for the GY thermophilic-wet AD combination. Methane yield was enhanced by 240 % compared to the GY waste mesophilic-dry condition. The results confirm that high temperature regimes and small solids concentrations are conditions that enhance methane yield from GY waste. A similar trend was observed for the anaerobic digestion of FV waste. Furthermore, a maximum value of VS (53 %) and sCOD (84 %) reduction was achieved during the AD of GY waste under the thermophilic-wet condition.

Keywords: anaerobic digestion, thermophilic, mesophilic, total solids concentration

Procedia PDF Downloads 138

Authors: Jaime E. Salazar Lagos

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Chongqing is located in southwest China and is becoming one of the most significant cities in the world. Its urban territories and metropolitan-related areas have one of the largest urban populations in China and are partitioned and shaped by two of the biggest and longest rivers on Earth, the Yangtze and Jialing Rivers, making Chongqing a megalopolis intersected by rivers. Historically, Chongqing City enjoyed fundamental connections with its rivers; however, current urban development of Chongqing City has lost effective integration of the riverbanks within the urban space and structural dynamics of the city. Therefore, there exists a critical lack of physical and urban space conjoined with the rivers, which diminishes the economic, tourist, and environmental development of Chongqing. Using multi-scale satellite-map site verification the study confirmed the hypothesis and urban-waterside disconnect. Collected data demonstrated that the Chongqing urban zone, an area of 5292 square-kilometers and a water front of 203.4 kilometers, has only 23.49 kilometers of extension (just 11.5%) with high-quality physical and spatial urban-waterside connection. Compared with other metropolises around the world, this figure represents a significant lack of spatial development along the rivers, an issue that has not been successfully addressed in the last 10 years of urban development. On a macro scale, the study categorized the different kinds of relationships between the city and its riverbanks. This data was then utilized in the creation of an urban-waterfront relationship map that can be a tool for future city planning decisions and real estate development. On a micro scale, we discovered there are three primary elements that are causing the urban-waterside disconnect: extensive highways along the most dense areas and city center, large private real estate developments that do not provide adequate riverside access, and large industrial complexes that almost completely lack riverside utilization. Finally, as part of the suggested strategies, the study concludes that the most efficient and practical way to improve this situation is to follow the historic master-planning of Chongqing and create connective nodes in critical urban locations along the river, a strategy that has been used for centuries to handle the same urban-waterside relationship. Reviewing and implementing this strategy will allow the city to better connect with the rivers, reducing the various impacts of disconnect and urban transformation.

Keywords: Chongqing City, megalopolis, nodes, riverbanks disconnection, urban

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Authors: Mohamed El Morsy, Gabriela Achtenová

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Condition monitoring is used to increase machinery availability and machinery performance, whilst reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient condition monitoring system provides early warning of faults by predicting them at an early stage. When a localized fault occurs in gears, the vibration signals always exhibit non-stationary behavior. The periodic impulsive feature of the vibration signal appears in the time domain and the corresponding gear mesh frequency (GMF) emerges in the frequency domain. However, one limitation of frequency-domain analysis is its inability to handle non-stationary waveform signals, which are very common when machinery faults occur. Particularly at the early stage of gear failure, the GMF contains very little energy and is often overwhelmed by noise and higher-level macro-structural vibrations. An effective signal processing method would be necessary to remove such corrupting noise and interference. In this paper, a new hybrid method based on optimal Morlet wavelet filter and autocorrelation enhancement is presented. First, to eliminate the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter determined by a Morlet wavelet whose parameters are selected or optimized based on maximum Kurtosis. Then, to further reduce the residual in-band noise and highlight the periodic impulsive feature, an autocorrelation enhancement algorithm is applied to the filtered signal. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers induce a load on the output joint shaft flanges. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. The gearbox used for experimental measurements is of the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive: a five-speed gearbox with final drive gear and front wheel differential. The results obtained from practical experiments prove that the proposed method is very effective for gear fault diagnosis.

Keywords: wavelet analysis, pitted gear, autocorrelation, gear fault diagnosis

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Authors: John Acire, Wilfred Lajul, Ogwang Tom

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Using a qualitative research technique, this study investigates the influence of Early Childhood Education (ECE) on learning outcomes in lower primary schools in Gulu City, Uganda. The study, which is based on Vygotsky's sociocultural theory of human learning, fills gaps in the current literature on the influence of ECE on learning outcomes. The aims of the study include analyzing the state of learning outcomes, investigating ECE practices, and determining the influence of these practices on learning outcomes in lower primary schools. The findings highlight the critical significance of ECE in promoting children's overall development. Nursery education helps children improve their handwriting, reading abilities, and general cognitive development. Children who have received nursery education have improved their abilities to handle pencils, form letters, and engage in social interactions, highlighting the significance of fine motor skills and socializing. Despite the good elements, difficulties in implementing ECE practices were found, such as differences in teaching styles, financial limits, and potential weariness due to prolonged school hours. The study suggests focused interventions to improve the effectiveness of ECE practices, ensure their connection with educational goals and maximize their influence on children's development. The study's findings show that respondents agree on the importance of nursery education in supporting holistic development, socialization, language competency, and conceptual comprehension. Challenges in nursery education, such as differences in teaching techniques and insufficient resources, highlight the need for comprehensive measures to address these challenges. Furthermore, parental engagement in home learning activities was revealed as an important factor affecting early education outcomes. Children who were engaged at home performed better in lower primary, emphasizing the value of a supportive family environment. Finally, the report suggests measures to enhance parental participation, changes in teaching methods through retraining, and age-appropriate enrolment. Future studies might concentrate on the involvement of parents, ECE policy practice, and the influence of ECE teachers on lower primary school learning results. These ideas are intended to help create a more favorable learning environment by encouraging holistic development and preparing children for success in succeeding academic levels.

Keywords: early childhood education, learning outcomes in lower primary schools, early childhood education practices, how ECE practices influence learning outcomes in lower primary schools

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Nivedhitha Venkatakrishnan

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Flooding in urban areas in India has become a usual ritual phenomenon and a nightmare to most cities, which is a consequence of man-made disruption resulting in disaster. The City planning in India falls short of withstanding hydro generated disasters. This has become a barrier and challenge in the process of development put forth by urbanization, high population density, expanding informal settlements, environment degradation from uncollected and untreated waste that flows into natural drains and water bodies, this has disrupted the natural mechanism of hazard protection such as drainage channels, wetlands and floodplains. The magnitude and the impact of the mishap was high because of the failure of development policies, strategies, plans that the city had adopted. In the current scenario, cities are becoming the home for future, with economic diversification bringing in more investment into cities especially in domains of Urban infrastructure, planning and design. The uncertainty of the Urban futures in these low elevated coastal zones faces an unprecedented risk and threat. The study on focuses on three major pillars of resilience such as Recover, Resist and Restore. This process of getting ready to handle the situation bridges the gap between disaster response management and risk reduction requires a shift in paradigm. The study involved a qualitative research and a system design approach (framework). The initial stages involved mapping out of the urban water morphology with respect to the spatial growth gave an insight of the water bodies that have gone missing over the years during the process of urbanization. The major finding of the study was missing links between traditional water harvesting network was a major reason resulting in a manmade disaster. The research conceptualized the ideology of a sponge city framework which would guide the growth through institutional frameworks at different levels. The next stage was on understanding the implementation process at various stage to ensure the shift in paradigm. Demonstration of the concepts at a neighborhood level where, how, what are the functions and benefits of each component. Quantifying the design decision with rainwater harvest, surface runoff and how much water is collected and how it could be collected, stored and reused. The study came with further recommendation for Water Mitigation Spaces that will revive the traditional harvesting network.

Keywords: flooding, man made disaster, resilient city, traditional harvesting network, waterbodies

Procedia PDF Downloads 140

Authors: Martonovich Noa, Maman David, Alfandari Liad, Behrbalk Eyal.

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Introduction: The human body is designed for upright standing and walking, with the lower extremities and axial skeleton supporting weight-bearing. Constant weight-bearing on joints not meant for this action can lead to various pathologies, as seen in wheelchair users. Handstand practitioners use their wrists as weight-bearing joints during activities, but little is known about wrist injuries in this population. This study aims to investigate the epidemiology of wrist pain among handstand practitioners, as no such data currently exist. Methods: The study is a cross-sectional online survey conducted among athletes who regularly practice handstands. Participants were asked to complete a three-part questionnaire regarding their workout regimen, training habits, and history of wrist pain. The inclusion criteria were athletes over 18 years old who practice handstands more than twice a month for at least 4 months. All data were collected using Google Forms, organized and anonymized using Microsoft Excel, and analyzed using IBM SPSS 26.0. Descriptive statistics were calculated, and potential risk factors were tested using asymptotic t-tests and Fisher's tests. Differences were considered significant when p < 0.05. Results: This study surveyed 402 athletes who regularly practice handstands to investigate the prevalence of chronic wrist pain and potential risk factors. The participants had a mean age of 31.3 years, with most being male and having an average of 5 years of training experience. 56% of participants reported chronic wrist pain, and 14.4% reported a history of distal radial fracture. Yoga was the most practiced form, followed by Capoeira. No significant differences were found in demographic data between participants with and without chronic wrist pain, and no significant associations were found between chronic wrist pain prevalence and warm-up routines or protective aids. Conclusion: The lower half of the body is meant to handle weight-bearing and impact, while transferring the load to upper extremities can lead to various pathologies. Athletes who perform handstands are particularly prone to chronic wrist pain, which affects over half of them. Warm-up sessions and protective instruments like wrist braces do not seem to prevent chronic wrist pain, and there are no significant differences in age or training volume between athletes with and without the condition. Further research is needed to understand the causes of chronic wrist pain in athletes, given the growing popularity of sports and activities that can cause this type of injury.

Keywords: handstand, handbalance, wrist pain, hand and wrist surgery, yoga, calisthenics, circus, capoeira, movement.

Procedia PDF Downloads 91

Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations

Procedia PDF Downloads 187

Authors: Mohamed Elmogbail

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The present study aimed at investigating difficulties those Translators encounter in understanding idiomatic expressions between Arabic and English languages. To achieve this goal, the researcher raised the three questions are:(1) What are the major difficulties that translators encounter in translating idiomatic expressions? (2) What factors cause such difficulties that translators encountered in translating idiomatic expressions? (3) What are the possible techniques that should be followed to overcome these difficulties? To answer these questions, the researcher designed questionnaire Table (2) and mentioned tables related to Test Show the second question in the study is about the factors that stand behind the challenges. Translators encounter while translating idiomatic expressions. The translators asked Provided the following factors:1- Because of lack of exposure to the source culture, they do not know the connotations of the cultural words that are related to the environment, food, folklore 2- Misusing dictionaries made the participants unable to find a proper target language idiomatic expression. 3-Lack of using idiomatic expressions in daily life. Table (3): (Questionnaire) Results to the table (3) Questions Of the study are About suggestions that can be inferred to handle these challenges. The questioned translators provided the following solutions:1- translators must be exposed to source language culture, including religion, habits, and traditions.2- translators should also be exposed to source language idiomatic expressions by introducing English culture in textbooks and through participating in extensive English culture courses.3- translators should be familiar with the differences between source and target language cultures.4- translators should avoid literal translation that results in most cases in wrong or poor translation.5- Schools, universities, and institutions should introduce translators to English culture.6- translators should participate in cultural workshops at universities.7- translators should try to use idiomatic expressions in everyday situations.8- translators should read more idiomatic expressions books. And researcher also designed a translation test consisted of 40 excerpts given to a random sample of 100 Translators in Khartoum capital of Sudan to translate them. After Collected data for the study, the researcher proceeded to a more detailed analysis, the methodology used in the analysis of idiomatic expressions Is empirical and descriptive. This study is qualitative by nature, but the quantitative method used the analysis of the data. Some figure and statistics are used, such as (statistical package for the social sciences). The researcher calculated the percentage proportion of each translation expressions. And compared them to each other. The finding of the study showed that most translations are inadequate as the translators faced difficulties while communication, these difficulties were mostly due to their unfamiliarity with idiomatic expressions producing improper equivalence in the communication, and not being able to use translation techniques as required, and resorted to literal translation, furthermore, the study recommended that more comprehensive studies to executed on translating idiomatic expressions to enrich the translation field.

Keywords: translation, translators, idioms., expressions

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Authors: Dina Dahood Dabash

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Refugee camps are habitually defined as receptive sites, transient spaces of exile and nondescript depoliticized places of exception. However, such arguments form partial sides of reality, especially in countries that are geopolitically challenged and rely immensely on international aid. In Jordan, the dynamics brought with the floating population of refugees (Palestinian amongst others) have resulted in spatial after-effects that cannot be easily overlooked. For instance, Palestine refugee camps have turned by time into socioeconomic centers of gravity and cores of spatial evolution. Yet, such a position is not instantaneous. Amongst various reasons, it can be related, according to this paper, to a distinctive institutional climate that has been co-produced by the refugees, host community and the state. This paper aims to investigate the evolution of urban and spatial regulations in Jordan between 1948 and 1995, more specifically, state regulations, community regulations and refugee-self-regulation that all dynamically interacted that period. The paper aims to unpack the relations between refugee camps and their environs to further explore the agency of such floating populations in establishing rooted networks that extended the time and place boundaries. The paper’s argument stems from the fact that the spatial configuration of urban systems is not only an outcome of a historical evolutionary process but is also a result of interactions between the actors. The research operationalizes Marka camp in Jordan as a case study. Marka Camp is one of the six "emergency" camps erected in 1968 to shelter 15,000 Palestine refugees and displaced persons who left the West Bank and Gaza Strip. Nowadays, camp shelters more than 50,000 refugees in the same area of land. The camp is located in Russeifa, a city in Zarqa Governorate in Jordan. Together with Amman and Zarqa, Russeifa is part of a larger metropolitan area that acts as a home to more than half of Jordan’s businesses. The paper aspires to further understand the post-conflict strategies which were historically applied in Jordan and can be employed to handle more recent geopolitical challenges such as the Syrian refugee crisis. Methodological framework: The paper traces the evolution of the refugee-camp regulating norms in Jordan, parallel with the horizontal and vertical evolution of the Marka camp and its surroundings. Consequently, the main methods employed are historical and mental tracing, Interviews, in addition to using available Aerial and archival photos of the Marka camp and its surrounding.

Keywords: forced migration, Palestine refugee camps, spatial agency, urban regulations

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Authors: Ishara Madusanka, So Morikawa

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Natural disasters, particularly floods, pose severe challenges globally, affecting both developed and developing countries. In many regions, especially Asia, riverine floods are prevalent and devastating. Integrated flood management incorporates structural and non-structural measures, with preventive relocation emerging as a cost-effective and proactive strategy for areas repeatedly impacted by severe flooding. However, preventive relocation is often hindered by economic, psychological, social, and institutional barriers. This study investigates the factors influencing resistance to preventive relocation and evaluates the role of flood risk information in shaping relocation decisions through risk perception. A conceptual model was developed, incorporating variables such as Flood Risk Information (FRI), Place Attachment (PA), Good Living Conditions (GLC), and Adaptation to Flooding (ATF), with Flood Risk Perception (FRP) serving as a mediating variable. The research was conducted in Welipitiya in the Polwatta river basin, Matara district, Sri Lanka, a region experiencing recurrent flood damage. For this study, an experimental design involving a structured questionnaire survey was utilized, with 185 households participating. The treatment group received flood risk information, including flood risk maps and historical data, while the control group did not. Data were collected in 2023 and analyzed using independent sample t-tests and Partial Least Squares Structural Equation Modeling (PLS-SEM). PLS-SEM was chosen for its ability to model latent variables, handle complex relationships, and suitability for exploratory research. Multi-group Analysis (MGA) assessed variations across different flood risk areas. Findings indicate that flood risk information had a limited impact on flood risk perception and relocation decisions, though its effect was significant in specific high-risk areas. Place attachment was a significant factor influencing relocation decisions across the sample. One potential reason for the limited impact of flood risk information on relocation decisions could be the lack of specificity in the information provided. The results suggest that while flood risk information alone may not significantly influence relocation decisions, it is crucial in specific contexts. Future studies and practitioners should focus on providing more detailed risk information and addressing psychological factors like place attachments to enhance preventive relocation efforts.

Keywords: flood risk communication, flood risk perception, place attachment, preventive relocation, structural equation modeling

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Authors: Mohamad Chour

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Nowadays, a record number of households are headed by single fathers in most of the European societies. Our research aims to explore how French single fathers experience the domestic sphere, a traditionally feminized field while accomplishing their role of fathers. We adopt a gender role and a parenting role construction theoretical perspectives. Indeed, the interior domestic sphere has been traditionally considered as related to the role of the mother. Moreover, according to the masculine domination theory of Bourdieu, men avoid caregiving and domestic practices that are economically and culturally undervalued. Hence, mothers are considered as more likely to handle the expressive dimension of duties whereas fathers’ role is represented as instrumental, functional and independent. Long interviews have been conducted with twenty French single fathers in order to investigate how the absence of the mother affects the practices of fatherhood. We combined the long interviews with projective techniques method in order to better understand their conception of the family and their family values. Seeking a qualitative diversity, our respondents are from various ages (between 30 and 60); they are coming from different regions in France; living in rural, semi-rural and urban areas. Based on the analysis of 427 pages of data, we identify three main categories of single fathers depending on their strategies to copy and/or delegate the role of the mother. 1) Nurturing fathers completely assume the role of the absent mother as well as her functions. Their discourse is characterized by abnegation and sacrifices reflecting a nurturing role. 2) Juggling fathers are those who take charge of a part of the household duties and delegate the other part to the market or to 'feminine resources' for lacking skills or time. 3) Resistant fathers are the very few respondents who refuse to assume any activities related to the domestic sphere that they perceive as feminine. For lacking competences and even for ideological reasons, they have tendency to delegate all the tasks that were assumed by their ex-spouses. Generally, the majority of fathers seem to experience the domestic sphere differently, and their domestic involvement has been underestimated and even misunderstood. Household duties such as cooking and housekeeping in addition to the nurturing role are experienced by many of the respondents as constructing elements of their fatherhood. Our respondents do not seem to accomplish house holding duties in a functional way. The domestic sphere is managed by those fathers with a strong dimension of abnegation. Thus, our research contributes to illustrating the evolution of gender roles and shows how being simultaneously 'a father and a mother' seems to be an emerging social norm in a French and European cultural context.

Keywords: fathering, gender roles, gender studies, identity construction, single fathers

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Authors: Takamitsu Kodama, Eiji Kawamoto

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Introduction: Ultrasound in emergency room has advantages of safer, faster, repeatable and noninvasive. Especially focused Point-Of-Care Ultrasound (POCUS) is used daily for prompt and accurate diagnoses, for quickly identifying critical and life-threatening conditions. That is why ultrasound has demonstrated its usefulness in emergency medicine. The true value of ultrasound has been once again recognized in recent years. It is thought that all resident physicians working at emergency room should perform an ultrasound scan to interpret signs and symptoms of deteriorating patients in the emergency room. However, a practical education on ultrasound is still in development. To resolve this issue, we established a new educational program using high-fidelity simulators and evaluated the efficacy of this course. Methods: Educational program includes didactic lectures and skill stations in half-day course. Instructor gives a lecture on POCUS such as Rapid Ultrasound in Shock (RUSH) and/or Focused Assessment Transthoracic Echo (FATE) protocol at the beginning of the course. Then, attendees are provided for training of scanning with cooperation of normal simulated patients. In the end, attendees learn how to apply focused POCUS skills at clinical situation using high-fidelity simulators such as SonoSim® (SonoSim, Inc) and SimMan® 3G (Laerdal Medical). Evaluation was conducted through surveillance questionnaires to 19 attendees after two pilot courses. The questionnaires were focused on understanding course concept and satisfaction. Results: All attendees answered the questionnaires. With respect to the degree of understanding, 12 attendees (number of valid responses: 13) scored four or more points out of five points. High-fidelity simulators, especially SonoSim® was highly appreciated to enhance learning how to handle ultrasound at an actual practice site by 11 attendees (number of valid responses: 12). All attendees encouraged colleagues to take this course because the high level of satisfaction was achieved. Discussion: Newly introduced educational course using high-fidelity simulators realizes the circle of learning to deepen the understanding on focused POCUS by gradual stages. SonoSim® can faithfully reproduce scan images with pathologic findings of ultrasound and provide experimental learning for a growth number of beginners such as resident physicians. In addition, valuable education can be provided if it is used combined with SimMan® 3G. Conclusions: Newly introduced educational course using high-fidelity simulators is supposed to be effective and helps in providing better education compared with conventional courses for emergency physicians.

Keywords: point-of-care ultrasound, high-fidelity simulators, education, circle of learning

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Authors: Ibitoye Olabode Clement

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The huge amount of grants for infrastructures development in Tertiary Institutions in Nigeria calls for transparency and accountability in the procurement process. However, questions have been raised concerning the judicious and appropriate use of the funds, and it was doubtful if the institutions complied with due process. This paper examined the causes of non-compliance with the Public Procurement Act (2007) in the procurement of Goods, Works, and Services through either direct or indirect processes of procurement, mostly in Tertiary Institutions of State government subvention institutions in Nigeria. Nigeria has over 120 public universities, polytechnics, and colleges of Education. This paper will take samples of some selected Institutions in southwest Nigeria. The institutions comprise 5 Universities, 5 Polytechnics, and 5 Colleges of Education / Health and Technology. The opinions of the institutions’ Procurement Officers on the tremendous investment through grants and interventions for infrastructure development in Tertiary Education Institutions (TEI) in Nigeria call for transparency and accountability in the procurement process. However, there are a lot of questions have been raised as to the judicious use of the funds, and it was doubtful if the institutions complied with due process. This study examined the causes of non-compliance with the Public Procurement Act (2007) in the procurement of Goods, Works, and Services in most State Government Public Institutions in Southwest Nigeria. Over, 120 public institutions comprising 5 Universities, 5 Polytechnics, and 5 Colleges of Education / Health and Technology were used for the study. The opinions of the institutions’ Procurement Officers on the causes of non-compliance with the Act in their procurement process were sought using a structured questionnaire. The results revealed that non-independent of Procurement Officers, non-compliance with the Act by some at the managerial level, claiming inadequate knowledge of the Act, non-employment of qualified and experienced Procurement officers, insufficient publicity of the Act, and non-existence of corporate governance led to poor management of procurement record and non-provision of incentive, Inability to separate the duties of Internal Auditors and Procurement Officers, Inability to translate procurement entity at large which makes nearly all at departmental level believe they procurement officers. Conclusively, on taking the Procurement Officers through interviewing having it that: the right educational and professional qualifications, understanding of the Act, sufficient cognate working experience, recruiting most professionals needed if not all, and occupying management position will enhance compliance. Hence, in addition, adopting an external empowered department from the Bureau should raise for monitoring the compliance mostly in State Government Tertiary Education Institution. Also, an organizational culture with a corporate governance structure that supports the engagement of the right and qualified personnel to handle procurement, encourages them to perform at their best and rewards excellent service by giving incentives, and operates within an administrative environment devoid of corruption.

Keywords: non compliance of procurement act, tertiary education institution, university, polytechnic and college of education/ health science and technology, Nigeria

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Loris Franchi, Daniele Calvi, Sabrina Corpino

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This paper presents a design methodology in which stakeholders are assisted with the exploration of a so-called negotiation space, aiming to the maximization of both group social welfare and single stakeholder’s perceived utility. The outcome results in less design iterations needed for design convergence while obtaining a higher solution effectiveness. During the early stage of a space project, not only the knowledge about the system but also the decision outcomes often are unknown. The scenario is exacerbated by the fact that decisions taken in this stage imply delayed costs associated with them. Hence, it is necessary to have a clear definition of the problem under analysis, especially in the initial definition. This can be obtained thanks to a robust generation and exploration of design alternatives. This process must consider that design usually involves various individuals, who take decisions affecting one another. An effective coordination among these decision-makers is critical. Finding mutual agreement solution will reduce the iterations involved in the design process. To handle this scenario, the paper proposes a design methodology which, aims to speed-up the process of pushing the mission’s concept maturity level. This push up is obtained thanks to a guided negotiation space exploration, which involves autonomously exploration and optimization of trade opportunities among stakeholders via Artificial Intelligence algorithms. The negotiation space is generated via a multidisciplinary collaborative optimization method, infused by game theory and multi-attribute utility theory. In particular, game theory is able to model the negotiation process to reach the equilibria among stakeholder needs. Because of the huge dimension of the negotiation space, a collaborative optimization framework with evolutionary algorithm has been integrated in order to guide the game process to efficiently and rapidly searching for the Pareto equilibria among stakeholders. At last, the concept of utility constituted the mechanism to bridge the language barrier between experts of different backgrounds and differing needs, using the elicited and modeled needs to evaluate a multitude of alternatives. To highlight the benefits of the proposed methodology, the paper presents the design of a CubeSat mission for the observation of lunar radiation environment. The derived solution results able to balance all stakeholders needs and guaranteeing the effectiveness of the selection mission concept thanks to its robustness in valuable changeability. The benefits provided by the proposed design methodology are highlighted, and further development proposed.

Keywords: concurrent engineering, artificial intelligence, negotiation in engineering design, multidisciplinary optimization

Procedia PDF Downloads 136

Authors: Apurva Patil, Ashay Aswale, Akshay Kulkarni, Shubham Bharadiya

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The potential benefit of gravity compensation of linkages in mechanisms using springs to reduce actuator requirements is well recognized, but practical applications have been elusive. Although existing methods provide exact spring balance, they require additional masses or auxiliary links, or all the springs used originate from the ground, which makes the resulting device bulky and space-inefficient. This paper uses a method of static balancing of mechanisms with conservative loads such as gravity and spring loads using non-zero-free-length springs with child–parent connections and no auxiliary links. Application of this method to the developed arm of a humanoid robot is presented here. Spring balancing is particularly important in this case because the serial chain of linkages has to work against gravity.This work involves approximate spring balancing of the open-loop chain of linkages using minimization of potential energy variance. It uses the approach of flattening the potential energy distribution over the workspace and fuses it with numerical optimization. The results show the considerable reduction in actuator torque requirement with practical spring design and arrangement. Reduced actuator torque facilitates the use of lower end actuators which are generally smaller in weight and volume thereby lowering the space requirements and the total weight of the arm. This is particularly important for humanoid robots where the parent actuator has to handle the weight of the subsequent actuators as well. Actuators with lower actuation requirements are more energy efficient, thereby reduce the energy consumption of the mechanism. Lower end actuators are lower in cost and facilitate the development of low-cost devices. Although the method provides only an approximate balancing, it is versatile, flexible in choosing appropriate control variables that are relevant to the design problem and easy to implement. The true potential of this technique lies in the fact that it uses a very simple optimization to find the spring constant, free-length of the spring and the optimal attachment points subject to the optimization constraints. Also, it uses physically realizable non-zero-free-length springs directly, thereby reducing the complexity involved in simulating zero-free-length springs from non-zero-free-length springs. This method allows springs to be attached to the preceding parent link, which makes the implementation of spring balancing practical. Because auxiliary linkages can be avoided, the resultant arm of the humanoid robot is compact. The cost benefits and reduced complexity can be significant advantages in the development of this arm of the humanoid robot.

Keywords: actuator torque, child-parent connections, spring balancing, the arm of a humanoid robot

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Feng-Ming Fan, Xiu-Hui Wen

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Shortage of water resources is a crucial problem to be solved in Taiwan. However, lack of effective and mandatory regulation on water recovery and recycling leads to no effective water resource controls currently. Although existing legislation sets standards regarding water recovery, implementation and enforcement of legislation are facing challenges. In order to break through the dilemma, this study aims to find enforcement tools, improve inspection skills, develop an inspection system, to achieve sustainable development of precious water resources. The Taiwan Environmental Impact Assessment Act (EIA Act) was announced on 1994. The aim of EIA Act is to protect the environment by preventing and mitigating the adverse impact of development activity on the environment. During the EIA process, we can set standards that require enterprises to reach a certain percentage of water recycling based on different case characteristics, to promote sewage source reduction and water saving benefits. Next, we have to inspect how the enterprises handle their waste water and perform water recovery based on environmental assessment commitments, for the purpose of reviewing and measuring the implementation efficiency of water recycling and reuse, an eco-friendly measure. We invited leading experts in related fields to provide lecture on water recycling, strengthen law enforcement officials’ inspection knowledge, and write inspection reference manual to be used as basis of enforcement. Then we finalized the manual by reaching mutual agreement between the experts and relevant agencies. We then inspected 65 high-tech companies whose daily water consumption is over 1,000 tons individually, located at 3 science parks, set up by Ministry of Science and Technology. Great achievement on water recycling was achieved at an amount of 400 million tons per year, equivalent to 2.5 months water usage for general public in Taiwan. The amount is equal to 710 billion bottles of 600 ml cola, 170 thousand international standard swimming pools of 2,500 tons, irrigation water applied to 40 thousand hectares of rice fields, or 1.7 Taipei Feitsui Reservoir of reservoir storage. This study demonstrated promoting effects of environmental impact assessment commitments on water recycling, and therefore water resource sustainable development. It also confirms the value of EIA Act for environmental protection. Economic development should go hand in hand with environmental protection, and it’s a mainstream. It clearly shows the EIA regulation can minimize harmful effects caused by development activity to the environment, as well as pursuit water resources sustainable development.

Keywords: the environmental impact assessment act, water recycling environmental assessment commitment, water resource sustainable development, water recycling, water reuse

Procedia PDF Downloads 247

Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

Procedia PDF Downloads 76

Authors: Peter Burggräf, Matthias Dannapfel, Hanno Voet, Patrick-Benjamin Bök, Jérôme Uelpenich, Julian Hoppe

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The increasing digitalization of value chains can help companies to handle rising complexity in their processes and thereby reduce the steadily increasing planning and control effort in order to raise performance limits. Due to technological advances, companies face the challenge of smart value chains for the purpose of improvements in productivity, handling the increasing time and cost pressure and the need of individualized production. Therefore, companies need to ensure quick and flexible decisions to create self-optimizing processes and, consequently, to make their production more efficient. Lean production, as the most commonly used paradigm for complexity reduction, reaches its limits when it comes to variant flexible production and constantly changing market and environmental conditions. To lift performance limits, which are inbuilt in current value chains, new methods and tools must be applied. Digitalization provides the potential to derive these new methods and tools. However, companies lack the experience to harmonize different digital technologies. There is no practicable framework, which instructs the transformation of current value chains into digital pervasive value chains. Current research shows that a connection between lean production and digitalization exists. This link is based on factors such as people, technology and organization. In this paper, the introduced method for the determination of digitally pervasive value chains takes the factors people, technology and organization into account and extends existing approaches by a new dimension. It is the first systematic approach for the digital transformation of lean production and consists of four steps: The first step of ‘target definition’ describes the target situation and defines the depth of the analysis with regards to the inspection area and the level of detail. The second step of ‘analysis of the value chain’ verifies the lean-ability of processes and lies in a special focus on the integration capacity of digital technologies in order to raise the limits of lean production. Furthermore, the ‘digital evaluation process’ ensures the usefulness of digital adaptions regarding their practicability and their integrability into the existing production system. Finally, the method defines actions to be performed based on the evaluation process and in accordance with the target situation. As a result, the validation and optimization of the proposed method in a German company from the electronics industry shows that the digital transformation of current value chains based on lean production achieves a raise of their inbuilt performance limits.

Keywords: digitalization, digital transformation, Industrie 4.0, lean production, value chain

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Authors: John Dimopoulos

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This proposal attempts a refabrication of Heidegger’s classic thing-being and object-being analysis in order to provide better ontological tools for understanding contemporary culture, technology, and society. In his work, Heidegger sought to understand and comment on the problem of technology in an era of rampant innovation and increased perils for society and the planet. Today we seem to be at another crossroads in this course, coming after postmodernity, during which dreams and dangers of modernity augmented with critical speculations of the post-war era take shape. The new era which we are now living in, referred to as hypermodernity by researchers in various fields such as architecture and cultural theory, is defined by the horizontal implementation of digital technologies, cybernetic networks, and mixed reality. Technology today is rapidly approaching a turning point, namely the point of no return for humanity’s supervision over its creations. The techno-scientific civilization of the 21st century creates a series of problems, progressively more difficult and complex to solve and impossible to ignore, climate change, data safety, cyber depression, and digital stress being some of the most prevalent. Humans often have no other option than to address technology-induced problems with even more technology, as in the case of neuron networks, machine learning, and AI, thus widening the gap between creating technological artifacts and understanding their broad impact and possible future development. As all technical disciplines and particularly design, become enmeshed in a matrix of digital hyper-objects, a conceptual toolbox that allows us to handle the new reality becomes more and more necessary. Weaponized design, prevalent in many fields, such as social and traditional media, urban planning, industrial design, advertising, and the internet in general, hints towards an increase in conflicts. These conflicts between tech companies, stakeholders, and users with implications in politics, work, education, and production as apparent in the cases of Amazon workers’ strikes, Donald Trump’s 2016 campaign, Facebook and Microsoft data scandals, and more are often non-transparent to the wide public’s eye, thus consolidating new elites and technocratic classes and making the public scene less and less democratic. The new category proposed, weapon-being, is outlined in respect to the basic function of reducing complexity, subtracting materials, actants, and parameters, not strictly in favor of a humanistic re-orientation but in a more inclusive ontology of objects and subjects. Utilizing insights of Object-Oriented Ontology (OOO) and its schematization of technological objects, an outline for a radical ontology of technology is approached.

Keywords: design, hypermodernity, object-oriented ontology, weapon-being

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Authors: Ana Breda, Catarina Cruz

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Daily, we face unpredictable events, often attributed to chance, as there is no justification for such an occurrence. Chance, understood as a source of uncertainty, is present in several aspects of human life, such as weather forecasts, dice rolling, and lottery. Surprisingly, humans and some animals can quickly adjust their behavior to handle efficiently doubly stochastic processes (random events with two layers of randomness, like unpredictable weather affecting dice rolling). This adjustment ability suggests that the human brain has built-in mechanisms for perceiving, understanding, and responding to simple probabilities. It also explains why current trends in mathematics education include probability concepts in official curriculum programs, starting from the third year of primary education onwards. In the first years of schooling, children learn to use a certain type of (specific) vocabulary, such as never, always, rarely, perhaps, likely, and unlikely, to help them to perceive and understand the probability of some events. These are keywords of crucial importance for their perception and understanding of probabilities. The development of the probabilistic concepts comes from facts and cause-effect sequences resulting from the subject's actions, as well as the notion of chance and intuitive estimates based on everyday experiences. As part of a junior summer school program, which took place at a Portuguese university, a non-formal learning experiment was carried out with 18 children in the 5th and 6th grades. This experience was designed to be implemented in a dynamic of a serious ice-breaking game, to assess their levels of probabilistic, critical, and creative thinking in understanding impossible, certain, equally probable, likely, and unlikely events, and also to gain insight into how the non-formal learning context influenced their achievements. The criteria used to evaluate probabilistic thinking included the creative ability to conceive events classified in the specified categories, the ability to properly justify the categorization, the ability to critically assess the events classified by other children, and the ability to make predictions based on a given probability. The data analysis employs a qualitative, descriptive, and interpretative-methods approach based on students' written productions, audio recordings, and researchers' field notes. This methodology allowed us to conclude that such an approach is an appropriate and helpful formative assessment tool. The promising results of this initial exploratory study require a future research study with children from these levels of education, from different regions, attending public or private schools, to validate and expand our findings.

Keywords: critical and creative thinking, non-formal mathematics learning, probabilistic thinking, serious game

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Authors: Nor Azian Binti Aziz, Muhammad Afiq Bin Tambichik, Zamri Bin Hashim

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The rapid development of the construction industry has contributed to increased construction waste, with concrete waste being among the most abundant. This waste is generated from ready-mix batching plants after the concrete cube testing process is completed and disposed of in landfills, leading to increased solid waste management costs. This study aims to evaluate the engineering characteristics of foamed concrete with waste mixtures construction and agricultural waste to determine the usability of recycled materials in the construction of non-load-bearing walls. This study involves the collection of construction wastes, such as recycled aggregates (RCA) obtained from the remains of finished concrete cubes, which are then tested in the laboratory. Additionally, agricultural waste, such as rice husk ash, is mixed into foamed concrete interlock blocks to enhance their strength. The optimal density of foamed concrete for this study was determined by mixing mortar and foam-backed agents to achieve the minimum targeted compressive strength required for non-load-bearing walls. The tests conducted in this study involved two phases. In Phase 1, elemental analysis using an X-ray fluorescence spectrometer (XRF) was conducted on the materials used in the production of interlock blocks such as sand, recycled aggregate/recycled concrete aggregate (RCA), and husk ash paddy/rice husk ash (RHA), Phase 2 involved physical and thermal tests, such as compressive strength test, heat conductivity test, and fire resistance test, on foamed concrete mixtures. The results showed that foamed concrete can produce lightweight interlock blocks. X-ray fluorescence spectrometry plays a crucial role in the characterization, quality control, and optimization of foamed concrete mixes containing construction and agriculture waste. The unique composition mixer of foamed concrete and the resulting chemical and physical properties, as well as the nature of replacement (either as cement or fine aggregate replacement), the waste contributes differently to the performance of foamed concrete. Interlocking blocks made from foamed concrete can be advantageous due to their reduced weight, which makes them easier to handle and transport compared to traditional concrete blocks. Additionally, foamed concrete typically offers good thermal and acoustic insulation properties, making it suitable for a variety of building projects. Using foamed concrete to produce lightweight interlock blocks could contribute to more efficient and sustainable construction practices. Additionally, RCA derived from concrete cube waste can serve as a substitute for sand in producing lightweight interlock blocks.

Keywords: construction waste, recycled aggregates (RCA), sustainable concrete, structure material

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Authors: Venkata Madhusudana Rao Kapavarapu

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The Intermediate Slug Catcher (ISC) facility was built to process nominally 234 MSCFD of export gas from the booster station on a day-to-day basis and to receive liquid slugs up to 1600 m³ (10,000 BBLS) in volume when the incoming 24” gas pipelines are pigged following upsets or production of non-dew-pointed gas from gathering centers. The maximum slug sizes expected are 812 m³ (5100 BBLS) in winter and 542 m³ (3400 BBLS) in summer after operating for a month or more at 100 MMSCFD of wet gas, being 60 MMSCFD of treated gas from the booster station, combined with 40 MMSCFD of untreated gas from gathering center. The water content is approximately 60% but may be higher if the line is not pigged for an extended period, owing to the relative volatility of the condensate compared to water. In addition to its primary function as a slug catcher, the ISC facility will receive pigged liquids from the upstream and downstream segments of the 14” condensate pipeline, returned liquids from the AGRP, pigged through the 8” pipeline, and blown-down fluids from the 14” condensate pipeline prior to maintenance. These fluids will be received in the condensate flash vessel or the condensate separator, depending on the specific operation, for the separation of water and condensate and settlement of solids scraped from the pipelines. Condensate meeting the colour and 200 ppm water specifications will be dispatched to the AGRP through the 14” pipeline, while off-spec material will be returned to BS-171 via the existing 10” condensate pipeline. When they are not in operation, the existing 24” export gas pipeline and the 10” condensate pipeline will be maintained under export gas pressure, ready for operation. The gas manifold area contains the interconnecting piping and valves needed to align the slug catcher with either of the 24” export gas pipelines from the booster station and to direct the gas to the downstream segment of either of these pipelines. The manifold enables the slug catcher to be bypassed if it needs to be maintained or if through-pigging of the gas pipelines is to be performed. All gas, whether bypassing the slug catcher or returning to the gas pipelines from it, passes through black powder filters to reduce the level of particulates in the stream. These items are connected to the closed drain vessel to drain the liquid collected. Condensate from the booster station is transported to AGRP through 14” condensate pipeline. The existing 10” condensate pipeline will be used as a standby and for utility functions such as returning condensate from AGRP to the ISC or booster station or for transporting off-spec fluids from the ISC back to booster station. The manifold contains block valves that allow the two condensate export lines to be segmented at the ISC, thus facilitating bi-directional flow independently in the upstream and downstream segments, which ensures complete pipeline integrity and facility integrity. Pipeline failures will be attended to with the latest technologies by remote techno plug techniques, and repair activities will be carried out as needed. Pipeline integrity will be evaluated with ili pigging to estimate the pipeline conditions.

Keywords: integrity, oil & gas, innovation, new technology

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Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

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Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

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Authors: Lisa Rudolfsson

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Socio-cognitive factors, such as social support and attribution of blame, influence the victim’s psychological adjustment after the abuse. Furthermore, the response from the person that the victim first confides to effect adjustment following the abuse. In Sweden, although police are investigating most of the reported cases of rape, very few rape-cases leads to trial and sentence. For many women who have been raped, contact with the police officer when reporting the crime will, therefore, be the most notable experience of how representatives for the Swedish society regard and handle what has happened. Hence, it seems urgent to gather information about these initial meetings. This study is part of a three-year research project, titled 'Female rape victims: Quality of initial police and medical care contact', funded by the Swedish Crime Victim and Support Authority. The focus of this study was on police officers in Sweden: their thoughts and experiences of meeting with raped women. Forthcoming are interviews with raped women about their experiences of meeting with police. Sixteen police officers participated in three focus groups and one interview. The participants consisted of five men and eleven women. Focus groups and interview were audio recorded and transcribed verbatim. The material was analyzed using thematic analysis. Participants described how violence against women was not a priority in Swedish society or within the Police Authority. They talked about rape cases as a Sisyphean work-task that put high demands on them, while they also lacked training and support. They expressed a wish to offer the woman some kind of restoration, and they talked about their work as potentially making a difference for the woman – even if she did not get juridical justice. However, participants also described that they did not feel validated in their hard work. They talked about working rape cases as causing them a great deal of frustration - directed towards the Police Authority, the juridical system, colleagues, and sometimes towards the woman. Participants also described how meeting with raped women was a work that affected them in a personal manner. Listening to stories about sexual violence made the participants sad, and they described it as a struggle to understand. They described wondering how the woman’s life turned out and how they sometimes questioned if they had done enough. Some of the conclusions concern the lack of prerequisites needed for police officers to be able to offer a good-enough treatment of raped women, as well as the lack of tools needed for police officers to care for themselves. In lack of training, validation, and support, the knowledge of how to offer a good- enough treatment of raped women becomes a task learned by doing. Attempts to offer, if not legal justice, then at least some kind of restoration becomes a personal task, dependent on individual police officers. It seems urgent that we address the risk of police officers’ frustration building up to be detrimental for both the crime victim and the officer her/himself.

Keywords: focus groups, police, raped women, restoration

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Authors: Beatrice Arthur

Abstract:

The rapid development of artificial intelligence (AI) has transformed various industries, enabling faster and more accurate decision-making processes. However, with these advancements come increased risks, including data privacy issues, systemic biases, and challenges related to transparency and accountability. As AI technologies become more integrated into business processes, there is a growing need for comprehensive auditing and assurance frameworks to manage these risks and ensure ethical use. This paper provides a literature review on AI auditing and assurance programs, highlighting the importance of adapting traditional audit methodologies to the complexities of AI-driven systems. Objective: The objective of this review is to explore current AI audit practices and their role in mitigating risks, ensuring accountability, and fostering trust in AI systems. The study aims to provide a structured framework for developing audit programs tailored to AI technologies while also investigating how AI impacts governance, risk management, and regulatory compliance in various sectors. Methodology: This research synthesizes findings from academic publications and industry reports from 2014 to 2024, focusing on the intersection of AI technologies and IT assurance practices. The study employs a qualitative review of existing audit methodologies and frameworks, particularly the COBIT 2019 framework, to understand how audit processes can be aligned with AI governance and compliance standards. The review also considers real-time auditing as an emerging necessity for influencing AI system design during early development stages. Outcomes: Preliminary findings indicate that while AI auditing is still in its infancy, it is rapidly gaining traction as both a risk management strategy and a potential driver of business innovation. Auditors are increasingly being called upon to develop controls that address the ethical and operational risks posed by AI systems. The study highlights the need for continuous monitoring and adaptable audit techniques to handle the dynamic nature of AI technologies. Future Directions: Future research will explore the development of AI-specific audit tools and real-time auditing capabilities that can keep pace with evolving technologies. There is also a need for cross-industry collaboration to establish universal standards for AI auditing, particularly in high-risk sectors like healthcare and finance. Further work will involve engaging with industry practitioners and policymakers to refine the proposed governance and audit frameworks. Funding/Support Acknowledgements: This research is supported by the Information Systems Assurance Management Program at Concordia University of Edmonton.

Keywords: AI auditing, assurance, risk management, governance, COBIT 2019, transparency, accountability, machine learning, compliance

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