Search results for: secure data sharing

Authors: Juan A. Arzate, Funda C. Ertem, M. Nicolas Cruz-Bournazou, Peter Neubauer, Stefan Junne

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— One of the biggest challenges the world faces today is global warming that is caused by greenhouse gases (GHGs) coming from the combustion of fossil fuels for energy generation. In order to mitigate climate change, the European Union has committed to reducing GHG emissions to 80–95% below the level of the 1990s by the year 2050. Renewable technologies are vital to diminish energy-related GHG emissions. Since water and biomass are limited resources, the largest contributions to renewable energy (RE) systems will have to come from wind and solar power. Nevertheless, high proportions of fluctuating RE will present a number of challenges, especially regarding the need to balance the variable energy demand with the weather dependent fluctuation of energy supply. Therefore, biogas plants in this content would play an important role, since they are easily adaptable. Feedstock availability varies locally or seasonally; however there is a lack of knowledge in how biogas plants should be operated in a stable manner by local feedstock. This problem may be prevented through suitable control strategies. Such strategies require the development of convenient mathematical models, which fairly describe the main processes. Modelling allows us to predict the system behavior of biogas plants when different feedstocks are used with different loading rates. Life cycle assessment (LCA) is a technique for analyzing several sides from evolution of a product till its disposal in an environmental point of view. It is highly recommend to use as a decision making tool. In order to achieve suitable strategies, the combination of a flexible energy generation provided by biogas plants, a secure production process and the maximization of the environmental benefits can be obtained by the combination of process modelling and LCA approaches. For this reason, this study focuses on the biogas plant which flexibly generates required energy from the co-digestion of maize, grass and cattle manure, while emitting the lowest amount of GHG´s. To achieve this goal AMOCO model was combined with LCA. The program was structured in Matlab to simulate any biogas process based on the AMOCO model and combined with the equations necessary to obtain climate change, acidification and eutrophication potentials of the whole production system based on ReCiPe midpoint v.1.06 methodology. Developed simulation was optimized based on real data from operating biogas plants and existing literature research. The results prove that AMOCO model can successfully imitate the system behavior of biogas plants and the necessary time required for the process to adapt in order to generate demanded energy from available feedstock. Combination with LCA approach provided opportunity to keep the resulting emissions from operation at the lowest possible level. This would allow for a prediction of the process, when the feedstock utilization supports the establishment of closed material circles within a smart bio-production grid – under the constraint of minimal drawbacks for the environment and maximal sustainability.

Keywords: AMOCO model, GHG emissions, life cycle assessment, modelling

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Authors: Noor Abdelhamid, Donovan Nelson, Cara Prosser

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The architectural design process could be mapped out as a dialogue between designer and user that is constructed across multiple phases with the overarching goal of aligning design outcomes with user needs. Traditionally, this dialogue is bounded within a preliminary phase of determining factors that will direct the design intent, and a completion phase, of handing off the project to the client. Pre- and post-occupancy evaluations (P/POE’s) could provide an alternative process by extending this dialogue on both ends of the design process. The purpose of this research is to study the influence of systematic pre-occupancy data collection in achieving design goals by conducting post-occupancy evaluations of two case studies. In the context of this study, systematic pre-occupancy data collection is defined as the preliminary documentation of the existing conditions that helps portray stakeholders’ needs. When implemented, pre-occupancy occurs during the early phases of the architectural design process, utilizing the information to shape the design intent. Investigative POE’s are performed on two case studies with distinct early design approaches to understand how the current space is impacting user needs, establish design outcomes, and inform future strategies. The first case study underwent systematic pre-occupancy data collection and synthesis, while the other represents the traditional, uncoordinated practice of informally collecting data during an early design phase. POE’s target the dynamics between the building and its occupants by studying how spaces are serving the needs of the users. Data collection for this study consists of user surveys, audiovisual materials, and observations during regular site visits. Mixed methods of qualitative and quantitative analyses are synthesized to identify patterns in the data. The paper concludes by positioning value on both sides of the architectural design process: the integration of systematic pre-occupancy methods in the early phases and the reinforcement of a continued dialogue between building and design team after building completion.

Keywords: architecture, design process, pre-occupancy data, post-occupancy evaluation

Procedia PDF Downloads 157

Authors: Shu-Hui Jan, Hui-Ping Tserng, Shih-Ping Ho

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Construction project control attempts to obtain real-time as-built schedule information and to eliminate project delays by effectively enhancing dynamic schedule control and management. Suitable platforms for enhancing an as-built schedule visually during the construction phase are necessary and important for general contractors. As the application of building information modeling (BIM) becomes more common, schedule management integrated with the BIM approach becomes essential to enhance visual construction management implementation for the general contractor during the construction phase. To enhance visualization of the updated as-built schedule for the general contractor, this study presents a novel system called the Construction BIM-assisted Schedule Management (ConBIM-SM) system for general contractors in Taiwan. The primary purpose of this study is to develop a web ConBIM-SM system for the general contractor to enhance visual as-built schedule information sharing and efficiency in tracking construction as-built schedule. Finally, the ConBIM-SM system is applied to a case study of a commerce building project in Taiwan to verify its efficacy and demonstrate its effectiveness during the construction phase. The advantages of the ConBIM-SM system lie in improved project control and management efficiency for general contractors, and in providing BIM-assisted as-built schedule tracking and management, to access the most current as-built schedule information through a web browser. The case study results show that the ConBIM-SM system is an effective visual as-built schedule management platform integrated with the BIM approach for general contractors in a construction project.

Keywords: building information modeling (BIM), construction schedule management, as-built schedule management, BIM schedule updating mechanism

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Authors: Niloofar Ashktorab, Negar Ashktorab

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Oil exports fund nearly half of Iran’s government expenditures, since many years other countries have been imposed different sanctions against Iran. Sanctions that primarily target Iran’s key energy sector have harmed Iran’s economy. The strategic effects of sanctions might be reduction as Iran adjusts to them economically. In this study, we evaluate the impact of oil price and sanctions against Iran on food commodity prices by using panel data method. Here, we find that the food commodity prices, the oil price and real exchange rate are stationary. The results show positive effect of oil price changes, real exchange rate and sanctions on food commodity prices.

Keywords: oil price, food basket, sanctions, panel data, Iran

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Authors: Laila Khaled Almawaldi, Hiew Khai Hang, Sugumaran A. l. Nallusamy

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Legacy systems are crucial for organizations, but their intricacy and lack of documentation pose challenges for maintenance and enhancement. Redocumentation of legacy systems is vital for automatically or semi-automatically creating documentation for software lacking sufficient records. It aims to enhance system understandability, maintainability, and knowledge transfer. However, existing redocumentation methods need improvement in data processing performance and document generation efficiency. This stems from the necessity to efficiently handle the extensive and complex code of legacy systems. This paper proposes a method for semi-automatic legacy system re-documentation using semantic parallel processing and ontology. Leveraging parallel processing and ontology addresses current challenges by distributing the workload and creating documentation with logically interconnected data. The paper outlines challenges in legacy system redocumentation and suggests a method of redocumentation using parallel processing and ontology for improved efficiency and effectiveness.

Keywords: legacy systems, redocumentation, big data analysis, parallel processing

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Authors: Joanna Skopinska-Wisniewska, Anna Bajek, Marta Ziegler-Borowska, Alina Sionkowska

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Hydrogels are a class of materials widely used in medicine for many years. Proteins, such as collagen, due to the presence of a large number of functional groups are easily wettable by polar solvents and can create hydrogels. The supramolecular network capable to swelling is created by cross-linking of the biopolymers using various reagents. Many cross-linking agents has been tested for last years, however, researchers still are looking for a new, more secure reactants. Squaric acid, 3,4-dihydroxy 3-cyclobutene 1,2- dione, is a very strong acid, which possess flat and rigid structure. Due to the presence of two carboxyl groups the squaric acid willingly reacts with amino groups of collagen. The main purpose of this study was to investigate the influence of addition of squaric acid on the chemical, physical and biological properties of collagen materials. The collagen type I was extracted from rat tail tendons and 1% solution in 0.1M acetic acid was prepared. The samples were cross-linked by the addition of 5%, 10% and 20% of squaric acid. The mixtures of all reagents were incubated 30 min on magnetic stirrer and then dialyzed against deionized water. The FTIR spectra show that the collagen structure is not changed by cross-linking by squaric acid. Although the mechanical properties of the collagen material deteriorate, the temperature of thermal denaturation of collagen increases after cross-linking, what indicates that the protein network was created. The lyophilized collagen gels exhibit porous structure and the pore size decreases with the higher addition of squaric acid. Also the swelling ability is lower after the cross-linking. The in vitro study demonstrates that the materials are attractive for 3T3 cells. The addition of squaric acid causes formation of cross-ling bonds in the collagen materials and the transparent, stiff hydrogels are obtained. The changes of physicochemical properties of the material are typical for cross-linking process, except mechanical properties – it requires further experiments. However, the results let us to conclude that squaric acid is a suitable cross-linker for protein materials for medicine and tissue engineering.

Keywords: collagen, squaric acid, cross-linking, hydrogel

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Authors: Meline Mesropyan

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At the beginning of the 20th century, Japan served as a transit point for Armenian refugees fleeing the 1915 Genocide. However, research on Armenian refugees in Japan is sparse, and the Armenian Diaspora has never taken root in Japan. Consequently, Japan has not been considered a relevant research site for studying Armenian refugees. The primary objective of this study is to shed light on the number of Armenian refugees who passed through Japan between 1915 and 1930. Quantitative analyses will be conducted based on newly uncovered Japanese archival documents. Subsequently, the Japanese data will be compared to American immigration data to estimate the potential number of refugees in Japan during that period. This under-researched area is relevant to both the Armenian Diaspora and refugee studies in Japan. By clarifying the number of refugees, this study aims to enhance understanding of Japan's treatment of refugees and the extent of humanitarian efforts conducted by organizations and individuals in Japan, contributing to the broader field of historical refugee studies.

Keywords: Armenian genocide, Armenian refugees, Japanese statistics, number of refugees

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Authors: Gon Park

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Seoul in South Korea established the 2030 Seoul City Master Plan that contains green-link projects to connect critical green areas within the city. However, the plan does not have detailed analyses for green infrastructure to incorporate land-cover information to many structural classes. This study maps green infrastructure networks of Seoul for complementing their green plans with identifying and raking green areas. Hubs and links of main elements of green infrastructure have been identified from incorporating cadastral data of 967,502 parcels to 135 of land use maps using geographic information system. Network analyses were used to rank hubs and links of a green infrastructure map with applying a force-directed algorithm, weighted values, and binary relationships that has metrics of density, distance, and centrality. The results indicate that network analyses using cadastral parcel data can be used as the framework to identify and rank hubs, links, and networks for the green infrastructure planning under a variable scenarios of green areas in cities.

Keywords: cadastral data, green Infrastructure, network analysis, parcel data

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: A. Almaneea, N. Kapur, J. L. Summers, H. M. Thompson

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Meeting the growth in demand for digital services such as social media, telecommunications, and business and cloud services requires large scale data centres, which has led to an increase in their end use energy demand. Generally, over 30% of data centre power is consumed by the necessary cooling overhead. Thus energy can be reduced by improving the cooling efficiency. Air and liquid can both be used as cooling media for the data centre. Traditional data centre cooling systems use air, however liquid is recognised as a promising method that can handle the more densely packed data centres. Liquid cooling can be classified into three methods; rack heat exchanger, on-chip heat exchanger and full immersion of the microelectronics. This study quantifies the improvements of heat transfer specifically for the case of immersed microelectronics by varying the CPU and heat sink location. Immersion of the server is achieved by filling the gap between the microelectronics and a water jacket with a dielectric liquid which convects the heat from the CPU to the water jacket on the opposite side. Heat transfer is governed by two physical mechanisms, which is natural convection for the fixed enclosure filled with dielectric liquid and forced convection for the water that is pumped through the water jacket. The model in this study is validated with published numerical and experimental work and shows good agreement with previous work. The results show that the heat transfer performance and Nusselt number (Nu) is improved by 89% by placing the CPU and heat sink on the bottom of the microelectronics enclosure.

Keywords: CPU location, data centre cooling, heat sink in enclosures, immersed microelectronics, turbulent natural convection in enclosures

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Authors: J. Fajardo, J. Guerra, E. Gonzales

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This paper will outline a study of Brazil's industrial base of defense (IDB), through a bibliographic research method, combined with an analysis of macroeconomic data from several available public data platforms. This paper begins with a brief study about Brazilian national industry, including analyzes of productivity, income, outcome and jobs. Next, the research presents a study on the defense industry in Brazil, presenting the main national companies that operate in the aeronautical, army and naval branches. After knowing the main points of the Brazilian defense industry, data on the productivity of the defense industry of the main countries and competing companies of the Brazilian industry were analyzed, in order to summarize big cases in Brazil with a comparative analysis. Concerned the methodology, were used bibliographic research and the exploration of historical data series, in order to analyze information, to get trends and to make comparisons along the time. The research is finished with the main trends for the development of the Brazilian defense industry, comparing the current situation with the point of view of several countries.

Keywords: economics of defence, industry, trends, market

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Authors: M. Lghoul, N. El Goumi, M. Guernouche

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In order to predict the structural and tectonic framework of the Bahira basin and to have a 3D geological modeling of the basin, an integrated multidisciplinary work has been conducted using gravity, magnetic and geological data. The objective of the current study is delineating the subsurfacefeatures, faults, and geological limits, using airborne magnetic and gravity data analysis of the Bahira basin. To achieve our goal, we have applied different enhanced techniques on magnetic and gravity data: power spectral analysis techniques, reduction to pole (RTP), upward continuation, analytical signal, tilt derivative, total horizontal derivative, 3D Euler deconvolutionand source parameter imagining. The major lineaments/faults trend are: NE–SW, NW-SE, ENE–WSW, and WNW–ESE. The 3D Euler deconvolution analysis highlighted a number of fault trend, mainly in the ENE-WSW, WNW-ESE directions. The depth tothe top of the basement sources in the study area ranges between 200 m, in the southern and northern part of the Bahira basin, to 5000 m located in the Eastern part of the basin.

Keywords: magnetic, gravity, structural trend, depth to basement

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Authors: U. S. Putro, L. Mayangsari, M. Siallagan, N. P. Tjahyani

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National Collective Management Institute (LKMN) in Indonesia stated that legal music products were about 77.552.008 unit while illegal music products were about 22.0688.225 unit in 1996 and this number keeps getting worse every year. Consequently, Indonesia named as one of the countries with high piracy levels in 2005. This study models people decision toward unlawful behavior, music content piracy in particular, using agent-based modeling and simulation (ABMS). The classification of actors in the model constructed in this study are legal consumer, illegal consumer, and neutral consumer. The decision toward piracy among the actors is a manifestation of the social norm which attributes are social pressure, peer pressure, social approval, and perceived prevalence of piracy. The influencing attributes fluctuate depending on the majority of surrounding behavior called social network. There are two main interventions undertaken in the model, campaign and peer influence, which leads to scenarios in the simulation: positively-framed descriptive norm message, negatively-framed descriptive norm message, positively-framed injunctive norm with benefits message, and negatively-framed injunctive norm with costs message. Using NetLogo, the model is simulated in 30 runs with 10.000 iteration for each run. The initial number of agent was set 100 proportion of 95:5 for illegal consumption. The assumption of proportion is based on the data stated that 95% sales of music industry are pirated. The finding of this study is that negatively-framed descriptive norm message has a worse reversed effect toward music piracy. The study discovers that selecting the context-based campaign is the key process to reduce the level of intention toward music piracy as unlawful behavior by increasing the compliance awareness. The context of Indonesia reveals that that majority of people has actively engaged in music piracy as unlawful behavior, so that people think that this illegal act is common behavior. Therefore, providing the information about how widespread and big this problem is could make people do the illegal consumption behavior instead. The positively-framed descriptive norm message scenario works best to reduce music piracy numbers as it focuses on supporting positive behavior and subject to the right perception on this phenomenon. Music piracy is not merely economical, but rather social phenomenon due to the underlying motivation of the actors which has shifted toward community sharing. The indication of misconception of value co-creation in the context of music piracy in Indonesia is also discussed. This study contributes theoretically that understanding how social norm configures the behavior of decision-making process is essential to breakdown the phenomenon of unlawful behavior in music industry. In practice, this study proposes that reward-based and context-based strategy is the most relevant strategy for stakeholders in music industry. Furthermore, this study provides an opportunity that findings may generalize well beyond music piracy context. As an emerging body of work that systematically constructs the backstage of law and social affect decision-making process, it is interesting to see how the model is implemented in other decision-behavior related situation.

Keywords: music piracy, social norm, behavioral decision-making, agent-based model, value co-creation

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Authors: Manoj Kumar Mahapatra, Arvind Kumar

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Batch adsorption experiments were carried out for the removal of phenol from its aqueous solution using water hyancith activated carbon (WHAC) as an adsorbent. The sorption kinetics were analysed using pseudo-first order kinetics and pseudo-second order model, and it was observed that the sorption data tend to fit very well in pseudo-second order model for the entire sorption time. The experimental data were analyzed by the Langmuir and Freundlich isotherm models. Equilibrium data fitted well to the Freundlich model with a maximum biosorption capacity of 31.45 mg/g estimated using Langmuir model. The adsorption intensity 3.7975 represents a favorable adsorption condition.

Keywords: adsorption, isotherm, kinetics, phenol

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Authors: Vedant Janapaty

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Estuaries are wetlands where fresh water from streams mixes with salt water from the sea. Also known as “kidneys of our planet”- they are extremely productive environments that filter pollutants, absorb floods from sea level rise, and shelter a unique ecosystem. However, eutrophication and loss of native species are ailing our wetlands. There is a lack of uniform data collection and sparse research on correlations between satellite data and in situ measurements. Remote sensing (RS) has shown great promise in environmental monitoring. This project attempts to use satellite data and correlate metrics with in situ observations collected at five estuaries. Images for satellite data were processed to calculate 7 bands (SIs) using Python. Average SI values were calculated per month for 23 years. Publicly available data from 6 sites at ELK was used to obtain 10 parameters (OPs). Average OP values were calculated per month for 23 years. Linear correlations between the 7 SIs and 10 OPs were made and found to be inadequate (correlation = 1 to 64%). Fourier transform analysis on 7 SIs was performed. Dominant frequencies and amplitudes were extracted for 7 SIs, and a machine learning(ML) model was trained, validated, and tested for 10 OPs. Better correlations were observed between SIs and OPs, with certain time delays (0, 3, 4, 6 month delay), and ML was again performed. The OPs saw improved R² values in the range of 0.2 to 0.93. This approach can be used to get periodic analyses of overall wetland health with satellite indices. It proves that remote sensing can be used to develop correlations with critical parameters that measure eutrophication in situ data and can be used by practitioners to easily monitor wetland health.

Keywords: estuary, remote sensing, machine learning, Fourier transform

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Authors: Mahdi Akbari, Ali Torabi Haghighi

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Hamun Lakes, located in the Helmand Basin, consisting of four water bodies, were the greatest (>8500 km2) freshwater bodies in Iran plateau but have almost entirely desiccated over the last 20 years. The desiccation of the lakes caused dust storm in the region which has huge economic and health consequences on the inhabitants. The flow of the Hirmand (or Helmand) River, the most important feeding river, has decreased from 4 to 1.9 km3 downstream due to anthropogenic activities. In this basin, water is mainly consumed for farming. Due to the lack of in-situ data in the basin, this research utilizes remote-sensing data to show how croplands and consequently consumed water in the agricultural sector have changed. Based on Landsat NDVI, we suggest using a threshold of around 0.35-0.4 to detect croplands in the basin. Croplands of this basin has doubled since 1990, especially in the downstream of the Kajaki Dam (the biggest dam of the basin). Using PML V2 Actual Evapotranspiration (AET) data and considering irrigation efficiency (≈0.3), we estimate that the consumed water (CW) for farming. We found that CW has increased from 2.5 to over 7.5 km3 from 2002 to 2017 in this basin. Also, the annual average Potential Evapotranspiration (PET) of the basin has had a negative trend in the recent years, although the AET over croplands has an increasing trend. In this research, using remote sensing data, we covered lack of data in the studied area and highlighted anthropogenic activities in the upstream which led to the lakes desiccation in the downstream.

Keywords: Afghanistan-Iran transboundary Basin, Iran-Afghanistan water treaty, water use, lake desiccation

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Authors: Julia Wimmers Klick

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Interprofessional Education (IPE) is widely recognized as a valuable approach in healthcare education, despite the challenges it presents. This study explores IP surface anatomy lab sessions, with a focus on fostering trust and collaboration among healthcare students. The research is conducted within the context of rural healthcare settings in British Columbia (BC), where a medical school and a physical therapy (PT) program operate under the Faculty of Medicine at the University of British Columbia (UBC). While IPE sessions addressing soft skills have been implemented, the integration of hard skills, such as Anatomy, remains limited. To address this gap, a pilot feasibility study was conducted with a positive outcome, a follow-up study involved these IPE sessions aimed at exploring the influence of bonding and trust between medical and PT students. Data were collected through focus groups comprising participating students and faculty members, and a structured SWOC (Strengths, Weaknesses, Opportunities, and Challenges) analysis was conducted. The IPE sessions, 3 in total, consisted of a 2.5-hour lab on surface anatomy, where PT students took on the teaching role, and medical students were newly exposed to surface anatomy. The focus of the study was on the relationship-building process and trust development between the two student groups, rather than assessing the acquisition of surface anatomy skills. Results indicated that the surface anatomy lab served as a suitable tool for the application and learning of soft skills. Faculty members observed positive outcomes, including productive interaction between students, reversed hierarchy with PT students teaching medical students, practicing active listening skills, and using a mutual language of anatomy. Notably, there was no grade assessment or external pressure to perform. The students also reported an overall positive experience; however, the specific impact on the development of soft skill competencies could not be definitively determined. Participants expressed a sense of feeling respected, welcomed, and included, all of which contributed to feeling safe. Within the small group environment, students experienced becoming a part of a community of healthcare providers that bonded over a shared interest in health professions education. They enjoyed sharing diverse experiences related to learning across their varied contexts, without fear of judgment and reprisal that were often intimidating in single professional contexts. During a joint Christmas party for both cohorts, faculty members observed students mingling, laughing, and forming bonds. This emphasized the importance of early bonding and trust development among healthcare colleagues, particularly in rural settings. In conclusion, the findings emphasize the potential of IPE sessions to enhance trust and collaboration among healthcare students, with implications for their future professional lives in rural settings. Early bonding and trust development are crucial in rural settings, where healthcare professionals often rely on each other. Future research should continue to explore the impact of content-concentrated IPE on the development of soft skill competencies.

Keywords: interprofessional education, rural healthcare settings, trust, surface anatomy

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Authors: Luís Marques, João Rocha, Andreia Fernandes, Maria Moura, Cláudia Caseiro, Filipa Figueiredo, João Nunes

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The implementation of circularity strategies other than recycling, such as reducing the amount of raw material, as well as reusing or sharing existing products, remains marginal. The European Commission announced that the transition towards a more circular economy could lead to the net creation of about 700,000 jobs in Europe by 2030, through additional labour demand from recycling plants, repair services and other circular activities. Efforts to create new circular business models in accordance with completely circular processes, as opposed to linear ones, have increased considerably in recent years. In order to create a societal Circular Economy transition model, it is necessary to include innovative solutions, where startups play a key role. Early-stage startups based on new business models according to circular processes often face difficulties in creating enough impact. The StartUp Zero Program designs a model and approach to increase the flow of startups in the Circular Economy field, focusing on a systemic decision analysis and multi-generational approach, considering Multi-Criteria Decision Analysis to support a decision-making tool, which is also supported by the use of a combination of an Analytical Hierarchy Process and Multi-Attribute Value Theory methods. We define principles, criteria and indicators for evaluating startup prerogatives, quantifying the evaluation process in a unique result. Additionally, this entrepreneurship program spanning 16 months involved more than 2400 young people, from ages 14 to 23, in more than 200 interaction activities.

Keywords: circular economy, entrepreneurship, startups;, multi-criteria decision analysis

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Subesh Panta

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The land is a one of the major boosting factors of production for the agricultural country like Nepal where access to land has been a major source of livelihood of tenants and small farmers. But there is an absence of secure land tenure arrangement which drastically affect the overall production of farmers leading towards food insecurity. Sharecropping is practiced in Nepal especially in tarai region from early period, but there is the gap in the academic study whether the sharecropping has benefitted tenant farmers and make them food sufficient or not. This study attempts to find out the food sufficiency among the tenant households. The research was carried in the three VDCs of Parsa district -Paterwa (Sugauli), Jitpur and Nirchuta. A total of 111 households were determined as the sample size from each of the three VDCs was randomly visited for interview in the study. The size of land rent-in was found to be very small and fragmented. At the same time, the land tenure security was not found to be secured among the tenants. Due to lack of land tenure security, on one hand tenants and small farmers were not found to be motivated to investment in agriculture as they need to share fifty percent of their production with the land owners, and on other hand land owners were also not interested in investing as they have other alternative sources of livelihood rather than agriculture. In conclusion, the study highpoint that the crop production and food sufficiency level of the tenants’ farmers of the Parsa district are decreasing. Many tenants’ farmers are seeking alternative opportunities for livelihood rather than sharecropping due to insecure land tenure, feudalistic practice, lack of storage for agriculture production, lack of proper agro-market. The situation is such that, if no action is taken timely, there may be a situation that we will have to depend on imports for all the food requirements. Thus, the study discloses that the sharecropping could act as catalyst for ensuring food sufficiency for all, if proper land tenure police are promoted to tenants/small farmers with legal titles to their land or promoted with sustainable agriculture methods.

Keywords: agriculture, food sufficiency, land, tenant farmes

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Authors: Eli Buchbinder

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Introduction. Language is the basis to our experience as human being. We use language in describing our experiences and construct meaning and narratives from experiences. Metaphors are a valuable linguistic tool commonly use. Metaphors link two domains that are ordinarily not related. Metaphors achieve simultaneously multi-level integration: abstract and concrete, rational and imaginative, familiar and the unfamiliar, conscious and preconscious/unconscious. As such, metaphors epistemological and ontological tool that are important in social work in every field and domain. Goals and Methods The presentation’s aim is to validate the value of metaphors through the first psychiatric breakdown is a traumatic for families. The presentation is based on two pooled qualitative studies. The first study focused on 12 spouses: 7 women and 5 men, between the ages of 22 and 57, regarding their experiences and meanings of the first psychiatric hospitalization of their partners diagnosed with affective disorders. The second study focused on 10 parents, between the ages of 47 and 62, regarding their experiences and meanings following their child's first psychotic breakdown during young adulthood. Results Two types of major metaphors evolved from the interviews in farming the trauma of the first mental breakdown. The first mode - orientation (spatial) metaphors, reflect symbolic expression of the loss of a secure base, represented in the physical environment, e.g., describing hospitalization as "falling into an abyss." The second mode- ontological metaphors, reflect how parents and spouses present their traumatic experiences of hospitalization in terms of discrete, powerful and coherent entities, e.g., describing the first hospitalization as "swimming against the tide." The two metaphors modes reflect the embodiment of the unpredictability, being mired in distress, shock, intense pain and the experience the collapse of continuity on the life course and cuts off the experience of control. Conclusions Metaphors are important and powerful guide in assessing individuals and families’ phenomenological reality. As such, metaphors are useful for understanding and orientated therapeutic intervening, in the studies above, with the first psychiatric hospitalization experienced, as well as in others social workers’ interventions.

Keywords: first mental breakdown, metaphors, family perspective, qualitative research

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Authors: Hasan Vural

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Turkey is a favorable country to produce a great variety of agricultural products because of her different geographic and climatic conditions which have been used to divide the country into four main and seven sub regions. This classification into seven regions traditionally has been used in order to data collection and publication especially related with agricultural production. Afterwards, nine agricultural regions were considered. Recently, the governmental body which is responsible of data collection and dissemination (Turkish Institute of Statistics-TIS) has used 12 classes which include 11 sub regions and Istanbul province. This study aims to evaluate these classification efforts based on the acreage of ten main crops in a ten years time period (1996-2005). The panel data grouped in 11 subregions has been evaluated by cluster and multivariate statistical methods. It was concluded that from the agricultural production point of view, it will be rather meaningful to consider three main and eight sub-agricultural regions throughout the country.

Keywords: agricultural region, factorial analysis, cluster analysis,

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Authors: Rohtash

Abstract:

Academically, the concept of Justice in the literature is vast, and theories are voluminous and definitions are numerous but it is very difficult to define. Through the ages, justice has been evolving and developing reasoning that how individuals and communities do the right thing that is just and fair to all in that society. Justice is a relative and dynamic concept, not absolute one. It is different in different societies based on their morality and ethics. The idea of justice cannot arise from a single morality but interaction of competing moralities and contending perspectives. Justice is the conditional and circumstantial term. Therefore, justice takes different meanings in different contexts. Justice is the application of the Laws. It is a values-based concept in order to protect the rights and liberties of the people. It is a socially created concept that has no physical reality. It exists in society on the basis of the spirit of sharing by the communities and members of society. The conception of justice in society or among communities and individuals is based on their social coordination. It can be effective only when people’s judgments are based on collective reasoning. Their behavior is shaped by social values, norms and laws. People must accept, share and respect the set of principles for delivering justice. Thus justice can be a reasonable solution to conflicts and to coordinate behavior in society. The subject matter of distributive justice is the Public Good and societal resources that should be evenly distributed among the different sections of society on the principles developed and established by the State through legislation, public policy and Executive orders. The Socioeconomic transformation of the society is adopted by the constitution within the limit of its morality and gives a new dimension to transformative justice. Therefore, both Procedural and Transformative justice is part of Distributive justice. Distributive justice is purely an economic phenomenon. It concerns the allocation of resources among the communities and individuals. The subject matter of distributive justice is the distribution of rights, responsibilities, burdens and benefits in society on the basis of the capacity and capability of individuals.

Keywords: distributive justice, constitutionalism, institutionalism, constitutional morality

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Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim

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Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

Keywords: building system, time series, diagnosis, outliers, delay, data gap

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Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: Omojokun Gabriel Aju

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Communication network is a process of exchanging data between two or more devices via some forms of transmission medium using communication protocols. The data could be in form of text, images, audio, video or numbers which can be grouped into FTP, Email, HTTP, VOIP or Video applications. The effectiveness of such data exchange will be proved if they are accurately delivered within specified time. While some senders will not really mind when the data is actually received by the receiving device, inasmuch as it is acknowledged to have been received by the receiver. The time a data takes to get to a receiver could be very important to another sender, as any delay could cause serious problem or even in some cases rendered the data useless. The validity or invalidity of a data after delay will therefore definitely depend on the type of data (information). It is therefore imperative for the network device (such as router) to be able to differentiate among the packets which are time sensitive and those that are not, when they are passing through the same network. So, here is where the queuing disciplines comes to play, to handle network resources when such network is designed to service widely varying types of traffics and manage the available resources according to the configured policies. Therefore, as part of the resources allocation mechanisms, a router within the network must implement some queuing discipline that governs how packets (data) are buffered while waiting to be transmitted. The implementation of the queuing discipline will regulate how the packets are buffered while waiting to be transmitted. In achieving this, various queuing disciplines are being used to control the transmission of these packets, by determining which of the packets get the highest priority, less priority and which packets are dropped. The queuing discipline will therefore control the packets latency by determining how long a packet can wait to be transmitted or dropped. The common queuing disciplines are first-in-first-out queuing, Priority queuing and Weighted-fair queuing (FIFO, PQ and WFQ). This paper critically evaluates and analyse through the use of Optimized Network Evaluation Tool (OPNET) Modeller, Version 14.5 the effects of three queuing disciplines (FIFO, PQ and WFQ) on the performance of 5 different applications (FTP, HTTP, E-Mail, Voice and Video) within specified parameters using packets sent, packets received and transmission delay as performance metrics. The paper finally suggests some ways in which networks can be designed to provide better transmission performance while using these queuing disciplines.

Keywords: applications, first-in-first-out queuing (FIFO), optimised network evaluation tool (OPNET), packets, priority queuing (PQ), queuing discipline, weighted-fair queuing (WFQ)

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Authors: Prangvalai Buasan, Boonrod Sajjakulnukit, Thongchart Bowonthumrongchai

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The demand for biomass pellets in the industrial sector has significantly increased since 2020. The revised version of Thailand’s power development plan as well as the Alternative Energy Development Plan, aims to promote biomass fuel consumption by around 485 MW by 2030. The replacement of solid fossil fuel with biomass pellets will affect medium-term and long-term national benefits for all industries throughout the supply chain. Therefore, the evaluation of environmental and economic impacts throughout the biomass pellet supply chain needs to be performed to provide better insight into the goods and financial flow of this activity. This study extended the national input-output table for the biomass pellet industry and applied the input-output analysis (IOA) method, a sort of macroeconomic analysis, to interpret the result of transactions between industries in the monetary unit when the revised national power development plan was adopted and enforced. Greenhouse gas emissions from consuming energy and raw material through the supply chain are also evaluated. The total intermediate transactions of all economic sectors, which included the biomass pellets sector (CASE 2), increased by 0.02% when compared with the conservative case (CASE 1). The control total, which is the sum of total intermediate transactions and value-added, the control total of CASE 2 is increased by 0.07% when compared with CASE 1. The pellet production process emitted 432.26 MtCO2e per year. The major sharing of the GHG is from the plantation process of raw biomass.

Keywords: input-output analysis, environmental extended input-output analysis, macroeconomic planning, biomass pellets, renewable energy

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Authors: Peaceman Sopazi, Mabila Mathebula, John Smallwood

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Recent health and safety (H&S) concerns and their resultant impact on railway operations, namely, the severe acute respiratory syndrome (SARS) or collectively known as SARS-CoV-2 (Covid-19) pandemic and the Fourth Industrial Revolution (4IR), which have dominated public discourse, brought into question as to whether, or not, some aspects of how we have so far managed safety oversight as railway regulatory bodies and operators will remain relevant in a changing railway environment. Railway practitioners have generally found themselves between a proverbial rock and a hard place by being confronted by emerging challenges which have brought along great opportunities for sustainability. As witnesses and participants to the progressively introduced railway safety management, and transformation regimes, this paper attempts to share gathered field experience on adaptable regulatory oversight and safety awareness. The discourse is approached from a South African context but also with an informed perspective of what seems to work and what usually does not. The authors share their own multi and transdisciplinary experience coupled with insights they have gained as researchers of global trends in general safety management and specific aspects of railway safety management, for sustainability. In addition to sharing a largely experience-based methodology for survival, suggestions are offered for consideration as a way of keeping the railway safety management discourse alive as practitioners navigate a new path which is shrouded in a cloud of untold uncertainty. The authors further believe that the right timing for the implementation of the proposed suggestions in this paper will produce beneficial outcomes. Finally, the paper will identify areas that are still open for further investigation for and by researchers and practitioners alike.

Keywords: health & safety management, safety awareness, railway safety management, railway systems sustainability

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Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

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The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

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Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

Procedia PDF Downloads 470