Search results for: project progress prediction

Authors: Kiri Trier, Theresa Treffers

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In the course of continuous volatility like production stops due to the COVID-19 pandemic, video-on-demand player monopolizing the film industry, filmmakers are stuck in traditional, linear content development processes. The industry has to become more agile in order to react quickly and easily to changes. Since content development in agile project management is scientifically–empirically not at all recorded, and a lack beyond the software development in terms of agile methods consists, we examined if the agile manifesto values and principles from the software development can be adapted to the film industry to enable agility and digitalization of content development in the industry. We conducted an online questionnaire with 184 German filmmakers (producers, authors, directors, actors, film financiers) for a first cross-sectional assessment for adaptability of the agile manifesto from the software development to the film industry, factor analysis was used to validate the construct. Our results show that it is crucial to digitalize traditional content development to agile content development end-to-end, with tools, lean processes, new collaboration structures, and holacracy to prepare for any volatility. Overall, we examined the first construct for an agile manifesto for the film industry with four values related to nine own principles. Our findings help to get a better understanding of the agile manifesto beyond the software development as a guideline for implementing agility in the film industry.

Keywords: agile manifesto, agile project management, agility, film industry

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Authors: Yan Ding, Fei Yan, Ji Liang, Hong Jiang, Xiaoguang Yang, Xu Qian

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The health status of GonjiKolela District, Amhara Region, Ethiopia is below its national average, and a sub-project of China UK Global Health Support Programme (GHSP) is expected to increase the uptake of a suite of reproductive, maternal, newborn and child health (RMNCH) interventions there. To explore what is on the ground and what could be helpful for the uptake of RMNCH services in GonjiKolela, a qualitative study was performed as part of the baseline assessment before the implementation of the project. Nine key informants from GonjiKolela were interviewed with self-designed interview guides and they were from the district Health Office, health centers, health posts, women health development army (community volunteer groups), mothers of newborns, and also a gynecologist from the maternal and child health center which is the referral center for pregnant women for this project. The interview were transcribed into words and sorted with qualitative analysis software MAXqda. Content analysis was mainly used to analyze the data. The district health office, the health centers and the health posts all had focal persons taking care of the management and provision of RMNCH services, and RMNCH related indicators were recorded and reported at each level routinely. In addition, district government and administration at community/administrative village level kept a close eye on the reduction of maternal, neonatal and child mortality. Women Health Development Amy at household level supported health workers at community/administrative village level (called health extension workers) in tracing, recording and reporting pregnant women, newborn and under-five children,organizing events for health education, demonstrating and leading health promotion activities, and stimulating the utilization of RMNCH.

Keywords: Reproductive Maternal Newborn and Child Health, Health Care Utilization, Qualitative Study, Ethiopia

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Authors: Esra Zengin, Sinan Akkar

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Reliable and accurate prediction of nonlinear structural response requires specification of appropriate earthquake ground motions to be used in nonlinear time history analysis. The current research has mainly focused on selection and manipulation of real earthquake records that can be seen as the most critical step in the performance based seismic design and assessment of the structures. Utilizing amplitude scaled ground motions that matches with the target spectra is commonly used technique for the estimation of nonlinear structural response. Representative ground motion ensembles are selected to match target spectrum such as scenario-based spectrum derived from ground motion prediction equations, Uniform Hazard Spectrum (UHS), Conditional Mean Spectrum (CMS) or Conditional Spectrum (CS). Different sets of criteria exist among those developed methodologies to select and scale ground motions with the objective of obtaining robust estimation of the structural performance. This study presents ground motion selection and scaling procedure that considers the spectral variability at target demand with the level of ground motion dispersion. The proposed methodology provides a set of ground motions whose response spectra match target median and corresponding variance within a specified period interval. The efficient and simple algorithm is used to assemble the ground motion sets. The scaling stage is based on the minimization of the error between scaled median and the target spectra where the dispersion of the earthquake shaking is preserved along the period interval. The impact of the spectral variability on nonlinear response distribution is investigated at the level of inelastic single degree of freedom systems. In order to see the effect of different selection and scaling methodologies on fragility curve estimations, results are compared with those obtained by CMS-based scaling methodology. The variability in fragility curves due to the consideration of dispersion in ground motion selection process is also examined.

Keywords: ground motion selection, scaling, uncertainty, fragility curve

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Fátima Farinha, Miguel J. Oliveira, Gina Matias, Armando Inverno, Jânio Monteiro, Cristiano Cabrita

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In the last decades, the construction of swimming pools for recreational activities has grown exponentially in southern Europe. Swimming pools are used both for private use in villas and for collective use in hotels or condominiums. However, they have a high environmental impact, mainly in terms of water and energy consumption, being used for a short period of time, depending significantly on favorable atmospheric conditions. Contrary to what would be expected, not enough research has been conducted to reduce the negative impact of this equipment. In this context, this work proposes and analyses technological measures to reduce the environmental impacts of swimming pools, such as thermal insulation of the tank, water balance in order to detect leaks and optimize the backwash process, integration of renewable energy generation, and a smart control system that meets the requirements of the user. The work was developed within the scope of the Ecopool+++ project, which aims to create innovative heated pools with reduced thermal losses and integration of SMART energy plus water management systems. The project is in the final phase of its development, with very encouraging results.

Keywords: swimming pools, sustainability, thermal losses, water management system

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Authors: Serag El Hegazi

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The development of an assessment methodological framework for local and institutional sustainability is a key factor for future development plans and visions. This paper develops an approach to local and institutional sustainability assessment (ALISA). The ALISA methodology is a methodological framework that assists in the clarification, formulation, preparation, selection, and ranking of key indicators to facilitate the assessment of the level of sustainability at the local and institutional levels in North African and Middle Eastern cities. According to the literature review, this paper formulates a methodological framework, ALISA, which is a combination of the UNCSD (2001) Theme Indicators Framework and the issue-based Framework illustrated by McLaren (1996). The methodological framework has been implemented to formulate, select, and prioritise key indicators that most directly reflect the issues of a case study at the local community and institutional level. Yet, in the meantime, there is a lack of clear indicators and frameworks that can be developed to apply successfully at the local and institutional levels in the MENA Region, particularly in the cities of Benghazi and Amman. This is an essential issue for sustainability development estimation. Therefore, a conceptual framework was developed to be tested as a methodology to collect and classify data. The Approach to Local and Institutional Sustainability Assessment (ALISA) is a methodological framework that was developed to apply to certain cities in the MENA region. The main goal is to develop the ALISA framework to formulate, choose, and prioritize sustainability key indicators, which then can assist in guiding an assessment progress to improve decisions and policymakers towards the development of sustainable cities at the local and institutional level in the city of Benghazi. The conceptual, methodological framework, which supports this research with joint documentary and analysed data in two case studies, including focus-group discussions, semi-structured interviews, and questionnaires, reflects the approach required to develop a combined framework that assists the development of sustainability indicators. To achieve this progress and reach the aim of this paper, which is developing a practical approach for sustainability indicators framework that could be used as a tool to develop local and institutional sustainability indicators, appropriate stages must be applied to propose a set of local and institutional sustainability indicators as follows: Step one: issues clarifications, Step two: objectives formation/analysing of issues and boundaries, Step three: indicators preparation, First list of proposed indictors, Step four: indicator selection, Step five: indicator rating/ranking.

Keywords: sustainability indicators, approach to local and institutional level, ALISA, policymakers

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Authors: N. Šarlija, S. Pfeifer, M. Jeger, A. Bilandžić

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Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.

Keywords: growth measurement constructs, logistic regression, prediction of growth potential, small and medium-sized enterprises

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Authors: P. G. Kaviya, B. Muthupandian, R. Ganesan

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On-chip routers typically have buffers are used input or output ports for temporarily storing packets. The buffers are consuming some router area and power. The multiple queues in parallel as in VC router. While running a traffic trace, not all input ports have incoming packets needed to be transferred. Therefore large numbers of queues are empty and others are busy in the network. So the time consumption should be high for the high traffic. Therefore using a RoShaQ, minimize the buffer area and time The RoShaQ architecture was send the input packets are travel through the shared queues at low traffic. At high load traffic the input packets are bypasses the shared queues. So the power and area consumption was reduced. A parallel cross bar architecture is proposed in this project in order to reduce the power consumption. Also a new adaptive weighted routing algorithm for 8-port router architecture is proposed in order to decrease the delay of the network on chip router. The proposed system is simulated using Modelsim and synthesized using Xilinx Project Navigator.

Keywords: buffer, RoShaQ architecture, shared queue, VC router, weighted routing algorithm

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Authors: E. A. Krasikov

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As the service life of an operating nuclear power plant (NPP) increases, the potential misunderstanding of the degradation of aging components must receive more attention. Integrity assurance analysis contributes to the effective maintenance of adequate plant safety margins. In essence, the reactor pressure vessel (RPV) is the key structural component determining the NPP lifetime. Environmentally induced cracking in the stainless steel corrosion-preventing cladding of RPV’s has been recognized to be one of the technical problems in the maintenance and development of light-water reactors. Extensive cracking leading to failure of the cladding was found after 13000 net hours of operation in JPDR (Japan Power Demonstration Reactor). Some of the cracks have reached the base metal and further penetrated into the RPV in the form of localized corrosion. Failures of reactor internal components in both boiling water reactors and pressurized water reactors have increased after the accumulation of relatively high neutron fluences (5´1020 cm–2, E>0,5MeV). Therefore, in the case of cladding failure, the problem arises of hydrogen (as a corrosion product) embrittlement of irradiated RPV steel because of exposure to the coolant. At present when notable progress in plasma physics has been obtained practical energy utilization from fusion reactors (FR) is determined by the state of material science problems. The last includes not only the routine problems of nuclear engineering but also a number of entirely new problems connected with extreme conditions of materials operation – irradiation environment, hydrogenation, thermocycling, etc. Limiting data suggest that the combined effect of these factors is more severe than any one of them alone. To clarify the possible influence of the in-service synergistic phenomena on the FR structural materials properties we have studied hydrogen-irradiated steel interaction including alternating hydrogenation and heat treatment (annealing). Available information indicates that the life of the first wall could be expanded by means of periodic in-place annealing. The effects of neutron fluence and irradiation temperature on steel/hydrogen interactions (adsorption, desorption, diffusion, mechanical properties at different loading velocities, post-irradiation annealing) were studied. Experiments clearly reveal that the higher the neutron fluence and the lower the irradiation temperature, the more hydrogen-radiation defects occur, with corresponding effects on the steel mechanical properties. Hydrogen accumulation analyses and thermal desorption investigations were performed to prove the evidence of hydrogen trapping at irradiation defects. Extremely high susceptibility to hydrogen embrittlement was observed with specimens which had been irradiated at relatively low temperature. However, the susceptibility decreases with increasing irradiation temperature. To evaluate methods for the RPV’s residual lifetime evaluation and prediction, more work should be done on the irradiated metal–hydrogen interaction in order to monitor more reliably the status of irradiated materials.

Keywords: hydrogen, radiation, stability, structural steel

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Talip Turkmen

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From the moment the first beats, the first step into the world mankind finds him in a struggle to survive. Most important case to win this fight is power. Power is one of the most common concepts which we encounter in our life. Mainly power is ability to reach desired results on someone else or ability to penetrate into the behavior of others. Throughout history merging technology and changing political trade-offs caused the change of concept of power. Receiving a state of multipolar new world order in the 21st century and increasing impacts of media have narrowed the limits of military power. With increasing globalization and peaceful diplomacy this gap, left by military power, has filled by soft power which has ability to persuade and attract. As concepts of power soft power also has not compromised yet. For that reason it is important to specify, sources of soft power, soft power strategies and limits of soft power. The purpose of this study was to analyze concept of soft power and importance of soft power in foreign relations. This project focuses on power, hard power and soft power relations, sources of soft power and strategies to gain soft power. Datas in this project was acquired from other studies on soft power and foreign relations. This paper was prepared in terms of concept and research techniques. As a result of data gained in this study the one of important topics in international relations is balance between soft power.

Keywords: soft power, foreign policy, national power, hard power

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Authors: Feyza Daloglu

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This paper scrutinizes the Ottoman years of Wasif Jawharriyeh’s memoir, The Storyteller of Jerusalem, within the framework of citadinite, employed by the Open Jerusalem Project. Open Jerusalem Project uses the term citadinite to describe “the dynamic identity relationship city dwellers have with each other and their urban environment.” While Jerusalem and Jerusalemite identity have usually been analyzed within religious, national, or colonial frameworks, citadinite offers a fresh perspective by turning its lens to the urban identity of its citizens in the 19th and 20th centuries to overcome the shortcomings of usual frameworks. Wasif Jawharriyeh is a proud Jerusalemite and a Greek Orthodox Arab, who spent his childhood and teenage years under the Ottoman Empire. His memoir reveals a great deal of urbanity and a strong sense of Jerusalemite identity which appears to be favored over other forms of identities - Arab, Christian - in the late empire years. Through citadinite, this paper aims to discuss aspects of Jerusalemite identity and key points of urban life in the late Ottoman holy city with the guidance of a very lively and social Ottoman citizen and at that time a young musician, Wasif Jawharriyeh.

Keywords: arab memoir, cityscape, jerusalem identity, ottoman city, urban life

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Nahlah Abbas, Saleh A. Wasimi, Nadhir Al-Ansari

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The Greater Zab and Lesser Zab are the major tributaries of Tigris River contributing the largest flow volumes into the river. The impacts of climate change on water resources in these basins have not been well addressed. To gain a better understanding of the effects of climate change on water resources of the study area in near future (2049-2069) as well as in distant future (2080-2099), Soil and Water Assessment Tool (SWAT) was applied. The model was first calibrated for the period from 1979 to 2004 to test its suitability in describing the hydrological processes in the basins. The SWAT model showed a good performance in simulating streamflow. The calibrated model was then used to evaluate the impacts of climate change on water resources. Six general circulation models (GCMs) from phase five of the Coupled Model Intercomparison Project (CMIP5) under three Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5, and RCP 8.5 for periods of 2049-2069 and 2080-2099 were used to project the climate change impacts on these basins. The results demonstrated a significant decline in water resources availability in the future.

Keywords: Tigris River, climate change, water resources, SWAT

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Authors: Xinrong Li, Jiawei Dai

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Food production, food safety, and the food supply chain are causing a great challenge to human health and the environment. Different kinds of food have different environmental costs. Therefore, a healthy diet can alleviate this problem to a certain extent. In this project, an online questionnaire was conducted to understand the purchase behaviour of consumers and their attitudes towards basic food information. However, the data shows that the public's current consumption habits and ideology do not meet the long-term development of sustainable social needs. In order to solve the environmental problems caused by the unbalanced diet of the public and the social problems of unequal food distribution, the purpose of this paper is to explore how to use the emerging media of VR to visualize food supply chain information so as to attract users' attention to the environmental cost of food. In this project, the food supply chain of imported and local cheese was compared side-by-side in the virtual reality environment, including the origin, transportation, sales, and other processes, which can effectively help users understand the difference between the two processes and environmental costs. Besides, the experimental data demonstrated that the participant would like to choose low environmental cost food after experiencing the whole process.

Keywords: virtual reality, information design, food supply chain, environmental cost

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Authors: Jesús Ulloa

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The creation, rise, and consolidation of far right-wing, ultranationalist, and eurosceptic parties in Europe after the Second World War pose a real threat towards the disintegration of the European Union. Starting more than thirty years ago with Jean-Marie Le Pen's FN and Margaret Thatcher's policies, to Marine Le Pen's current FN and anti-immigration proposals along with Nigel Farage's UKIP and their intentions to leave the European Union, the progress of right-wing parties should be noted, taking into account that they may have very important differences within their postures but that they also reach common ground in certain areas. The actual disintegration of the EU would represent an enormous failure of the new liberal world order. Through this essay, the roots of this political parties will be analyzed and the conclusion of whether the disintegration may become a reality or if the principles of cooperation and unity will prevail will be answered.

Keywords: eurosceptic, ultarnationalist, right-wing, European Union

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Authors: Lisa Fox, Jill Aylott

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There is a global need to identify ways to engage doctors in non-clinical matters such as medical leadership, service improvement and health system transformation. Using the core principles of Realistic Evaluation (RE), this study examined what works, for doctors of different grades, specialities and experience in an acute NHS Hospital Trust in the UK. Realistic Evaluation is an alternative to more traditional cause and effect evaluation models and seeks to understand the interdependencies of Context, Mechanism and Outcome proposing that Context (C) + Mechanism (M) = Outcome (O). In this study, the context, mechanism and outcome were examined from within individual medical leaders to determine what enables levels of medical engagement in a specific improvement project to reduce hospital inpatient mortality. Five qualitative case studies were undertaken with consultants who had regularly completed mortality reviews over a six month period. The case studies involved semi-structured interviews to test the theory behind the drivers for medical engagement. The interviews were analysed using a theory-driven thematic analysis to identify CMO configurations to explain what works, for whom and in what circumstances. The findings showed that consultants with a longer length of service became more engaged if there were opportunities to be involved in the beginning of an improvement project, with more opportunities to affect the design. Those that are new to a consultant role were more engaged if they felt able to apply any learning directly into their own settings or if they could use it as an opportunity to understand more about the organisation they are working in. This study concludes that RE is a useful methodology for better understanding the complexities of motivation and consultant engagement in a trust wide service improvement project. The study showed that there should be differentiated and bespoke training programmes to maximise each individual doctor’s propensity for medical engagement. The RE identified that there are different ways to ensure that doctors have the right skills to feel confident in service improvement projects.

Keywords: realistic evaluation, medical leadership, medical engagement, patient safety, service improvement

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Authors: Kinga Wieczorek, Elzbieta Kukier, Remigiusz Pomykala, Beata Lachtara, Renata Szewczyk, Krzysztof Kwiatek, Jacek Osek

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The MICRORISK project (Research cooperation in assessment of microbiological hazard and risk in the food chain) was funded by the European Commission under the FP7 PEOPLE 2012 IRSES call within the International Research Staff Exchange Scheme of Marie Curie Action and realized during years from 2014 to 2015. The main aim of the project was to establish a cooperation between the European Union (EU) and the third State in the area important from the public health point of view. The following organizations have been engaged in the activity: National Veterinary Research Institute (NVRI) in Pulawy, Poland (coordinator), French Agency for Food, Environmental and Occupational Health & Safety (ANSES) in Maisons Alfort, France, National Scientific Center Institute of Experimental and Clinical Veterinary Medicine (NSC IECVM), Kharkov and State Scientific and Research Institute of Laboratory Diagnostics and Veterinary and Sanitary Expertise (SSRILDVSE) Kijev Ukraine. The results of the project showed that Ukraine used microbiological criteria in accordance with Commission Regulation (EC) No 2073/2005 of 15 November 2005 on microbiological criteria for foodstuffs. Compliance concerns both the criteria applicable at the stage of food safety (retail trade), as well as evaluation criteria and process hygiene in food production. In this case, the Ukrainian legislation also provides application of the criteria that do not have counterparts in the food law of the European Union, and are based on the provisions of Ukrainian law. Partial coherence of the Ukrainian and EU legal requirements in terms of microbiological criteria for food and feed concerns microbiological parameters such as total plate count, coliforms, coagulase-positive Staphylococcus spp., including S. aureus. Analysis of laboratory methods used for microbiological hazards control in food production chain has shown that most methods used in the EU are well-known by Ukrainian partners, and many of them are routinely applied as the only standards in the laboratory practice or simultaneously used with Ukrainian methods. The area without any legislation, where the EU regulation and analytical methods should be implemented is the area of Shiga toxin producing E. coli, including E. coli O157 and staphylococcal enterotoxin detection. During the project, the analysis of the existing Ukrainian and EU data concerning the prevalence of the most important food-borne pathogens on different stages of food production chain was performed. Particularly, prevalence of Salmonella spp., Campylobacter spp., L. monocytogenes as well as clostridia was examined. The analysis showed that poultry meat still appears to be the most important food-borne source of Campylobacter and Salmonella in the UE. On the other hand, L. monocytogenes were seldom detected above the legal safety limit (100 cfu/g) among the EU countries. Moreover, the analysis revealed the lack of comprehensive data regarding the prevalence of the most important food-borne pathogens in Ukraine. The results of the MICRORISK project are networking activities among researches originations participating in the tasks will help with a better recognition of each other regarding very important, from the public health point of view areas such as microbiological hazards in the food production chain and finally will help to improve food quality and safety for consumers.

Keywords: cooperation, European Union, food chain safety, food law, microbiological risk, Microrisk, Poland, Ukraine

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Authors: Margarida Porfírio Tomás, Paula Pereira, José Manuel Palma Oliveira

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The decline in employment rates across sectors like industry and construction is exacerbated by an aging workforce. This has far-reaching implications for the economy, including skills gaps, labour shortages, productivity challenges due to physical limitations, and workplace safety concerns. To sustain the workforce and pension systems, technology plays a pivotal role. Robots provide valuable support to human workers, and effective human-robot interaction is essential. FORTIS, a Horizon project, aims to address these challenges by creating a comprehensive Human-Robot Interaction (HRI) solution. This solution focuses on multi-modal communication and multi-aspect interaction, with a primary goal of maintaining a human-centric approach. By meeting the needs of both human workers and robots, FORTIS aims to facilitate efficient and safe collaboration. The project encompasses three key activities: 1) A Human-Centric Approach involving data collection, annotation, understanding human behavioural cognition, and contextual human-robot information exchange. 2) A Robotic-Centric Focus addressing the unique requirements of robots during the perception and evaluation of human behaviour. 3) Ensuring Human-Robot Trustworthiness through measures such as human-robot digital twins, safety protocols, and resource allocation. Factor Social, a project partner, will analyse psycho-physiological signals that influence human factors, particularly in hazardous working conditions. The analysis will be conducted using a combination of case studies, structured interviews, questionnaires, and a comprehensive literature review. However, the adoption of novel technologies, particularly those involving human-robot interaction, often faces hurdles related to acceptance. To address this challenge, FORTIS will draw upon insights from Social Sciences and Humanities (SSH), including risk perception and technology acceptance models. Throughout its lifecycle, FORTIS will uphold a human-centric approach, leveraging SSH methodologies to inform the design and development of solutions. This project received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No 101135707 (FORTIS).

Keywords: skills gaps, productivity challenges, workplace safety, human-robot interaction, human-centric approach, social sciences and humanities, risk perception

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Authors: Yirui Wang

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In the past few decades, patient safety has been the focus of much attention in the global medical and health field. As medical standards continue to improve and develop, the demand for patient safety is also growing. As one of the important dimensions in assessing patient safety, the Patient Perception Patient Safety Assessment Tool provides unique and valuable information from the patient's own perspective and plays an important role in promoting patient safety. This article aims to summarize and analyze the assessment content, assessment methods and applications of currently commonly used patient-perceived patient safety assessment tools at home and abroad, with a view to providing a reference for medical staff to select appropriate patient-perceived patient safety assessment tools.

Keywords: patients, patient safety, perception, assessment tools, review

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Authors: Joshua Midha

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This paper provides an evaluation of an intervention designed to promote a risk-realistic environment for women in the workplace and regulate their risk-related decision-making. In past research, women -specifically women of color- are highly risk-averse, and this may prove to be an innate obstacle in gender progress in corporations. By helping women see the risks and the benefits and increasing potential benefits, we can increase the chances of success in the workplace. Our intervention was a success and significantly increased comfort, trust, and frequency in the use of decision-making skills in the workplace. In this paper, we explore the intervention, the methods, the results, and the implications.

Keywords: behavioral economics, decision support, risk, gender equality

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Authors: Rosy Makeresemese Qhosola

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South Africa has maintained the effort to uphold its guiding principles in terms of its constitution. The constitution upholds principles such as equity, social justice, peace, freedom and hope, to mention but a few. So, such principles are made to form the basis for any legislation and policies that are in place to guide all fields/departments of government. Education is one of those departments or fields and is expected to abide by such principles as outlined in their policies. Therefore, as expected education policies and legislation outline their intentions to ensure the development of students’ clear critical thinking capacity as well as their creative capacities by creating learning contexts and opportunities that accommodate the effective teaching and learning strategies, that are learner centered and are compatible with the prescripts of a democratic constitution of the country. The paper aims at exploring and analyzing the progress of conventional accounting in terms of its adherence to the effective use of principles of good teaching, as per policy expectations in South Africa. The progress is traced by comparing conventional accounting to Critical Accounting Research (CAR), where the history of accounting as intended in the curriculum of SA and CAR are highlighted. Critical Accounting Research framework is used as a lens and mode of teaching in this paper, since it can create a space for the learning of accounting that is optimal marked by the use of more learner-centred methods of teaching. The Curriculum of South Africa also emphasises the use of more learner-centred methods of teaching that encourage an active and critical approach to learning, rather than rote and uncritical learning of given truths. The study seeks to maintain that conventional accounting is in contrast with principles of good teaching as per South African policy expectations. The paper further maintains that, the possible move beyond it and the adherence to the effective use of good teaching, could be when CAR forms the basis of teaching. Data is generated through Participatory Action Research where the meetings, dialogues and discussions with the focused groups are conducted, which consists of lecturers, students, subject heads, coordinators and NGO’s as well as departmental officials. The results are analysed through Critical Discourse Analysis since it allows for the use of text by participants. The study concludes that any teacher who aspires to achieve in the teaching and learning of accounting should first meet the minimum requirements as stated in the NQF level 4, which forms the basic principles of good teaching and are in line with Critical Accounting Research.

Keywords: critical accounting research, critical discourse analysis, participatory action research, principles of good teaching

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Authors: Daniela Istrati, Alina Morosan, Maria Stanca, Bogdan Purcareanu, Adrian Fudulu, Laura Olariu, Alice Buteica, Ion Mindrila, Rodica Cristescu, Dan Eduard Mihaiescu

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Our present work is related to the synthesis, characterization and applications of new nanocomposite materials based on silica mesoporous nanocompozites systems. The nanocomposite support was obtained by using a specific step–by–step multilayer structure buildup synthetic route, characterized by XRD (X-Ray Difraction), TEM (Transmission Electron Microscopy), FT-IR (Fourier Transform-Infra Red Spectrometry), BET (Brunauer–Emmett–Teller method) and loaded with Salvia officinalis plant extract obtained by a hydro-alcoholic extraction route. The sustained release of the target compounds was studied by a modified LC method, proving low release profiles, as expected for the high specific surface area support. The obtained results were further correlated with the in vitro / in vivo behavior of the nanocomposite material and recommending the silica mesoporous nanocomposites as good candidates for biomedical applications. Acknowledgements: This study has been funded by the Research Project PN-III-P2-2.1-PTE-2016-0160, 49-PTE / 2016 (PROZECHIMED) and Project Number PN-III-P4-ID-PCE-2016-0884 / 2017.

Keywords: biomedical, mesoporous, nanocomposites, natural products, sustained release

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Authors: C. S. Subhashini, H. L. Premaratne

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Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

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Authors: June Keeling, Christina Athanasiades, Vaiva Hendrixson, Delyth Wyndham

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Recognition and education in violence, abuse, and neglect for medical and healthcare practitioners (REVAMP) is a trans-European project aiming to introduce a training programme that has been specifically developed by partners across seven European countries to meet the needs of medical and healthcare practitioners. Amalgamating the knowledge and experience of clinicians, researchers, and educators from interdisciplinary and multi-professional backgrounds, REVAMP has tackled the under-resourced and underdeveloped area of domestic violence and abuse. The team designed an online training programme to support medical and healthcare practitioners to recognise and respond appropriately to survivors of domestic violence and abuse at their point of contact with a health provider. The REVAMP partner countries include Europe: France, Lithuania, Germany, Greece, Iceland, Norway, and the UK. The training is delivered through a series of interactive online modules, adapting evidence-based pedagogical approaches to learning. Capturing and addressing the complexities of the project impacted the methodological decisions and approaches to evaluation. The challenge was to find an evaluation methodology that captured valid data across all partner languages to demonstrate the extent of the change in knowledge and understanding. Co-development by all team members was a lengthy iterative process, challenged by a lack of consistency in terminology. A mixed methods approach enabled both qualitative and quantitative data to be collected, at the start, during, and at the conclusion of the training for the purposes of evaluation. The module content and evaluation instrument were accessible in each partner country's language. Collecting both types of data provided a high-level snapshot of attainment via the quantitative dataset and an in-depth understanding of the impact of the training from the qualitative dataset. The analysis was mixed methods, with integration at multiple interfaces. The primary focus of the analysis was to support the overall project evaluation for the funding agency. A key project outcome was identifying that the trans-European approach posed several challenges. Firstly, the project partners did not share a first language or a legal or professional approach to domestic abuse and neglect. This was negotiated through complex, systematic, and iterative interaction between team members so that consensus could be achieved. Secondly, the context of the data collection in several different cultural, educational, and healthcare systems across Europe challenged the development of a robust evaluation. The participants in the pilot evaluation shared that the training was contemporary, well-designed, and of great relevance to inform practice. Initial results from the evaluation indicated that the participants were drawn from more than eight partner countries due to the online nature of the training. The primary results indicated a high level of engagement with the content and achievement through the online assessment. The main finding was that the participants perceived the impact of domestic abuse and neglect in very different ways in their individual professional contexts. Most significantly, the participants recognised the need for the training and the gap that existed previously. It is notable that a mixed-methods evaluation of a trans-European project is unusual at this scale.

Keywords: domestic violence, e-learning, health professionals, trans-European

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Authors: Matar Celine, Gaucel Sebastien, Gontard Nathalie, Guilbert Stephane, Guillard Valerie

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To increase the very short shelf life of fresh fruits and vegetable, Modified Atmosphere Packaging (MAP) allows an optimal atmosphere composition to be maintained around the product and thus prevent its decay. This technology relies on the modification of internal packaging atmosphere due to equilibrium between production/consumption of gases by the respiring product and gas permeation through the packaging material. While, to the best of our knowledge, benefit of MAP for fresh fruits and vegetable has been widely demonstrated in the literature, its effect on shelf life increase has never been quantified and formalized in a clear and simple manner leading difficult to anticipate its economic and environmental benefit, notably through the decrease of food losses. Mathematical modelling of mass transfers in the food/packaging system is the basis for a better design and dimensioning of the food packaging system. But up to now, existing models did not permit to estimate food quality nor shelf life gain reached by using MAP. However, shelf life prediction is an indispensable prerequisite for quantifying the effect of MAP on food losses reduction. The objective of this work is to propose an innovative approach to predict shelf life of MAP food product and then to link it to a reduction of food losses and wastes. In this purpose, a ‘Virtual MAP modeling tool’ was developed by coupling a new predictive deterioration model (based on visual surface prediction of deterioration encompassing colour, texture and spoilage development) with models of the literature for respiration and permeation. A major input of this modelling tool is the maximal percentage of deterioration (MAD) which was assessed from dedicated consumers’ studies. Strawberries of the variety Charlotte were selected as the model food for its high perishability, high respiration rate; 50-100 ml CO₂/h/kg produced at 20°C, allowing it to be a good representative of challenging post-harvest storage. A value of 13% was determined as a limit of acceptability for the consumers, permitting to define products’ shelf life. The ‘Virtual MAP modeling tool’ was validated in isothermal conditions (5, 10 and 20°C) and in dynamic temperature conditions mimicking commercial post-harvest storage of strawberries. RMSE values were systematically lower than 3% for respectively, O₂, CO₂ and deterioration profiles as a function of time confirming the goodness of model fitting. For the investigated temperature profile, a shelf life gain of 0.33 days was obtained in MAP compared to the conventional storage situation (no MAP condition). Shelf life gain of more than 1 day could be obtained for optimized post-harvest conditions as numerically investigated. Such shelf life gain permitted to anticipate a significant reduction of food losses at the distribution and consumer steps. This food losses' reduction as a function of shelf life gain has been quantified using a dedicated mathematical equation that has been developed for this purpose.

Keywords: food losses and wastes, modified atmosphere packaging, mathematical modeling, shelf life prediction

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Authors: Saurabh B. Ganorkar, Atul A. Shirkhedkar

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The need for investigations protecting against toxic impurities though seems to be a primary requirement; the impurities which may prove non - toxic can be explored for their therapeutic potential if any to assist advanced drug discovery. The essential role of pharmaceutical analysis can thus be extended effectively to achieve it. The present study successfully achieved these objectives with characterization of major degradation products as impurities for Zileuton which has been used for to treat asthma since years. The forced degradation studies were performed to identify the potential degradation products using Ultra-fine Liquid-chromatography. Liquid-chromatography-Mass spectrometry (Time of Flight) and Proton Nuclear Magnetic Resonance Studies were utilized effectively to characterize the drug along with five major oxidative and hydrolytic degradation products (DP’s). The mass fragments were identified for Zileuton and path for the degradation was investigated. The characterized DP’s were subjected to In-Silico studies as XP Molecular Docking to compare the gain or loss in binding affinity with 5-Lipooxygenase enzyme. One of the impurity of was found to have the binding affinity more than the drug itself indicating for its potential to be more bioactive as better Antiasthmatic. The close structural resemblance has the ability to potentiate or reduce bioactivity and or toxicity. The chances of being active biologically at other sites cannot be denied and the same is achieved to some extent by predictions for probability of being active with Prediction of Activity Spectrum for Substances (PASS) The impurities found to be bio-active as Antineoplastic, Antiallergic, and inhibitors of Complement Factor D. The toxicological abilities as Ames-Mutagenicity, Carcinogenicity, Developmental Toxicity and Skin Irritancy were evaluated using Toxicity Prediction by Komputer Assisted Technology (TOPKAT). Two of the impurities were found to be non-toxic as compared to original drug Zileuton. As the drugs are purposed and repurposed effectively the impurities can also be; as they can have more binding affinity; less toxicity and better ability to be bio-active at other biological targets.

Keywords: UFLC, LC-MS-TOF, NMR, Zileuton, impurities, toxicity, bio-activity

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Authors: Ime R. Udotong, Justina I. R. Udotong, Ofonime U. M. John

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Brass terminal, one of the several crude oil and petroleum products storage/handling facilities in the Niger Delta was built in the 1980s. Activities at this site, over the years, released crude oil into this 3 m-deep, 1500 m-long canal lying adjacent to the terminal with oil floating on it and its sediment heavily polluted. To ensure effective clean-up, three major activities were planned: Site characterization, bioremediation pilot plant construction and testing and full-scale bioremediation of contaminated sediment/bank soil by land farming. The canal was delineated into 12 lots and each characterized, with reference to the floating oily phase, contaminated sediment and canal bank soil. As a result of site characterization, a pilot plant for on-site bioremediation was designed and a treatment basin constructed for carrying out pilot bioremediation test. Following a designed sampling protocol, samples from this pilot plant were collected for analysis at two laboratories as a quality assurance/quality control check. Results showed that Brass Canal upstream is contaminated with dark, thick and viscous oily film with characteristic hydrocarbon smell while downstream, thin oily film interspersed with water were observed. Sediments were observed to be dark with mixture of brownish sandy soil with TPH ranging from 17,800 mg/kg in Lot 1 to 88,500 mg/kg in Lot 12 samples. Brass Canal bank soil was observed to be sandy from ground surface to 3m, below ground surface (bgs) it was silty-sandy and brownish while subsurface soil (4-10m bgs) was sandy-clayey and whitish/grayish with typical hydrocarbon smell. Preliminary results obtained so far have been very promising but were proprietary. This project is considered, to the best of technical literature knowledge, the first large-scale on-site bioremediation project in the Niger Delta region, Nigeria.

Keywords: bioremediation, contaminated sediment, land farming, oily sludge, oil terminal

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Authors: Peter Pomlenyi, Orsolya Semperger, Gergely Hegedus

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The purpose of the project is to develop a complex composite component with visible class ‘A’ surface. It is going to integrate more functions, including continuous fiber reinforcement, foam core, injection molded ribs, and metal inserts. Therefore we are going to produce recyclable structural composite part from thermoplastic polymer in serial production with short cycle time for automotive applications. Our design of the process line is determined by the principles of Industry 4.0. Accordingly, our goal is to map in details the properties of the final product including the mechanical properties in order to replace metal elements used in automotive industry, with special regard to the effect of each manufacturing process step on the afore mentioned properties. Period of the project is 3 years, which lasts from the 1st of December 2016 to the 30th November 2019. There are four consortium members in the R&D project evopro systems engineering Ltd., Department of Polymer Engineering of the Budapest University of Technology and Economics, Research Centre for Natural Sciences of Hungarian Academy of Sciences and eCon Engineering Ltd. One of the most important result that we can obtain short cycle time (up to 2-3 min) with in-situ polymerization method, which is an innovation in the field of thermoplastic composite production. Because of the mentioned method, our fully automated production line is able to manufacture complex thermoplastic composite parts and satisfies the short cycle time required by the automotive industry. In addition to the innovative technology, we are able to design, analyze complex composite parts with finite element method, and validate our results. We are continuously collecting all the information, knowledge and experience to improve our technology and obtain even more accurate results with respect to the quality and complexity of the composite parts, the cycle time of the production, and the design and analyzing method of the composite parts.

Keywords: T-RTM technology, composite, automotive, class A surface

Procedia PDF Downloads 139

Authors: Agnieszka Zalejska-Jonsson

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The Swedish Green Building Council (SGBC) was established in 2009. Since then, over 1000 buildings have been certified, of which approximately 600 are newly produced and 340 are residential buildings. During that time, approximately 2000 apartment buildings have been built in Sweden. This means that over a five- year period 17% of residential buildings have been certified according to the environmental building scheme. The certification of the building is not a guarantee of environmental progress but it gives us an indication of the extent of the progress. The overarching aim of this study is to investigate the factors behind the relatively slow evolution of the green residential housing market in Sweden. The intention is to examine stated willingness to pay (WTP) for green and low energy apartments, and to explore which factors have a significant effect on stated WTP among apartment owners. A green building was defined as a building certified according to the environmental scheme and a low energy building as a building designed and constructed with high energy efficiency goals. Data for this study were collected through a survey conducted among occupants of comparable apartment buildings: two green and one conventional. The total number of received responses was 429: green A (N=160), response rate 42%; green B (N=138) response rate 35%, and conventional (N=131) response rate 43%. The study applied a quasi-experimental method. Survey responses regarding factors affecting purchase of apartment, stated WTP and environmental literacy have been analysed using descriptive statistics, the Mann–Whitney (rank sum) test and logistic models. Comments received from respondents have been used for further interpretation of results. Results indicate that environmental education has a significant effect on stated WTP. Occupants who declared higher WTP showed a higher level of environmental literacy and indicated that energy efficiency was one of the important factors that affected their decision to buy an apartment. Generally, the respondents were more likely to pay more for low energy buildings than for green buildings. This is to a great extent a consequence of rational customer behaviour and difficulty in apprehending the meaning of green building certification. The analysis shows that people living in green buildings indicate higher WTP for both green and low energy buildings, the difference being statistically significant. It is concluded that growth in the green housing market in Sweden might be achieved if policymakers and developers engage in active education in the environmental labelling system. The demand for green buildings is more likely to increase when the difference between green and conventional buildings is easily understood and information is not only delivered by the estate agent, but is part of an environmental education programme.

Keywords: consumer, environmental education, housing market, stated WTP, Sweden

Procedia PDF Downloads 241