Search results for: expert testimony

Authors: Agnetha Schuchardt, Jennifer Hartmann, Laura Schulte, Roman Peperhove, Lars Gerhold

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If critical infrastructures fail, even for a short period of time, it can have significant negative consequences for the affected population. This is especially true for the food sector that is strongly interlinked with other sectors like the power supply. A blackout could lead to several cities being without food supply for numerous days, simply because cash register systems do no longer work properly. Following the public opinion, securing the food supply in emergencies is considered a task of the state, however, in the German context, the key players are private enterprises and private households. Both are not aware of their responsibility and both cannot be forced to take any preventive measures prior to an emergency. This problem became evident to officials and politicians so that the law covering food security was revised in order to include private stakeholders into mitigation processes. The paper will present a scientific review of governmental and regulatory literature. The focus is the inclusion of the food industry through a law reform and the challenges that still exist. Together with legal experts, an analysis of regulations will be presented that explains the development of the law reform concerning food security and emergency storage in Germany. The main findings are that the existing public food emergency storage is out-dated, insufficient and too expensive. The state is required to protect food as a critical infrastructure but does not have the capacities to live up to this role. Through a law reform in 2017, new structures should to established. The innovation was to include the private sector into the civil defense concept since it has the required knowledge and experience. But the food industry is still reluctant. Preventive measures do not serve economic purposes – on the contrary, they cost money. The paper will discuss respective examples like equipping supermarkets with emergency power supply or self-sufficient cash register systems and why the state is not willing to cover the costs of these measures, but neither is the economy. The biggest problem with the new law is that private enterprises can only be forced to support food security if the state of emergency has occurred already and not one minute earlier. The paper will cover two main results: the literature review and an expert workshop that will be conducted in summer 2018 with stakeholders from different parts of the food supply chain as well as officials of the public food emergency concept. The results from this participative process will be presented and recommendations will be offered that show how the private economy could be better included into a modern food emergency concept (e. g. tax reductions for stockpiling).

Keywords: critical infrastructure, disaster control, emergency food storage, food security, private economy, resilience

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Authors: Vandenbroucke Karel, Georges Annabel, Schuurman Dimitri

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In the past years, bundling of transport flows, whether or not implemented in an intermodal process, has popped up as a promising concept in the logistics sector. Bundling of transport flows is a process where two or more shippers decide to synergize their shipped goods over a common transport lane. Promoted by the European Commission, several programs have been set up and have shown their benefits. Bundling promises both shippers and logistics service providers economic, societal and ecological benefits. By bundling transport flows and thus reducing truck (or other carrier) capacity, the problems of driver shortage, increased fuel prices, mileage charges and restricted hours of service on the road are solved. In theory, the advantages of bundled transport exceed the drawbacks, however, in practice adoption among shippers remains low. In fact, bundling is mentioned as a disruptive process in the rather traditional logistics sector. In this context, a Belgian company asked iMinds Living Labs to set up a Living Lab research project with the goal to investigate how the uptake of bundling transport flows can be accelerated and to check whether an online data sharing platform can overcome the adoption barriers. The Living Lab research was conducted in 2016 and combined quantitative and qualitative end-user and market research. Concretely, extensive desk research was conducted and combined with insights from expert interviews with four consultants active in the Belgian logistics sector and in-depth interviews with logistics professionals working for shippers (N=10) and LSP’s (N=3). In the article, we present findings which show that there are several factors slowing down the uptake of bundling transport flows. Shippers are hesitant to change how they currently work and they are hesitant to work together with other shippers. Moreover, several practical challenges impede shippers to work together. We also present some opportunities that can accelerate the adoption of bundling of transport flows. First, it seems that there is not enough support coming from governmental and commercial organizations. Secondly, there is the chicken and the egg problem: too few interested parties will lead to no or very few matching lanes. Shippers are therefore reluctant to partake in these projects because the benefits have not yet been proven. Thirdly, the incentive is not big enough for shippers. Road transport organized by the shipper individually is still seen as the easiest and cheapest solution. A solution for the abovementioned challenges might be found in the online data sharing platform of the Belgian company. The added value of this platform is showing shippers possible matching lanes, without the shippers having to invest time in negotiating and networking with other shippers and running the risk of not finding a match. The interviewed shippers and experts indicated that the online data sharing platform is a very promising concept which could accelerate the uptake of bundling of transport flows.

Keywords: adoption barriers, bundling of transport, shippers, transport optimization

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Authors: Senait Belay Adugna, Mirutse Giday, Tsegahun Manyazewal

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Background: The emergence and resurgence of zoonotic diseases have continued to be a major threat to global health and the economy. Developing countries are particularly vulnerable due to agricultural expansions and the domestication of animals by humans. Scientifically sound clinical trials are important to find better ways to prevent, diagnose, and treat zoonotic diseases, while there is a lack of evidence to inform the clinical trials’ capacity and practice in countries highly affected by the diseases. This study aimed to investigate researchers’ perceptions and experiences in conducting clinical trials on zoonotic diseases in Ethiopia. Methods: This study employed a descriptive, qualitative study design. It included major academic and research institutions in Ethiopia that had active engagements in veterinary and public health research. It included the National Veterinary Institute, the National Animal Health Diagnostic and Investigation Center, the College of Veterinary Medicine at Addis Ababa University, the Ethiopian Public Health Institute, the Armauer Hansen Research Institute, and the College of Health Sciences at Addis Ababa University. In-depth interviews were conducted with 14 senior researcher investigators in the institutions who hold a proven exhibit primarily leading research activities or research units. Data were collected from October 2019 to April 2020. Data analysis was undertaken using open code 4.03 for qualitative data analysis. Results: Five major themes, with 18 sub-themes, emerged from the in-depth interview in connection. These were: challenges in the prevention, control, and treatment of zoonotic diseases; One Health approach to mitigate zoonotic diseases; personal and institutional experiences in conducting clinical trials on zoonotic diseases; barriers in conducting clinical trials towards zoonotic diseases; and strategies that promote conducting clinical trials on zoonotic diseases. Conducting clinical trials on zoonotic diseases in Ethiopia is hampered by a lack of clearly articulated ethics and regulatory frameworks, trial experts, financial resources, and good governance. Conclusions: In Ethiopia, conducting clinical trials on zoonotic diseases deserves due attention. Strengthening institutional and human resources capacity is a precondition to harnessing effective implementation of clinical trials on zoonotic diseases in the country. In Ethiopia, where skilled human resource is scarce, the One Health approach has the potential to form multidisciplinary teams to systematically improve clinical trials capacity and outcomes in the country.

Keywords: Ethiopia, clinical triak, zoonoses, disease

Procedia PDF Downloads 93

Authors: Glenn Koonce

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There is a need to address the improvement of university educational leadership preparation programs through the processes of accreditation and continuous improvement. The program faculty in a university in the eastern part of the United States has incorporated an employer satisfaction focus group to address their national accreditation standard so that employers are satisfied with completers' preparation for the position of principal or assistant principal. Using the Council for the Accreditation of Educator Preparation (CAEP) required proficiencies, the following research questions are investigated: 1) what proficiencies do completers perform the strongest? 2) what proficiencies need to be strengthened? 3) what other strengths beyond the required proficiencies do completers demonstrate? 4) what other areas of responsibility beyond the required proficiencies do completers demonstrate? and 5) how can the program improve in preparing candidates for their positions? This study focuses on employers of one public school district that has a large number of educational leadership completers employed as principals and assistant principals. Central office directors who evaluate principals and principals who evaluate assistant principals are focus group participants. Construction of the focus group questions is a result of recommendations from an accreditation regulatory specialist, reviewed by an expert panel, and piloted by an experienced focus group leader. The focus group session was audio recorded, transcribed, and analyzed using the NVivo Version 14 software. After constructing folders in NVivo, the focus group transcript was loaded and skimmed by diagnosing significant statements and assessing core ideas for developing primary themes. These themes were aligned to address the research questions. From the transcript, codes were assigned to the themes and NVivo provided a coding hierarchy chart or graphical illustration for framing the coding. A final report of the coding process was designed using the primary themes and pertinent codes that were supported in excerpts from the transcript. The outcome of this study is to identify themes that can provide evidence that the educational leadership program is meeting its mission to improve PreK-12 student achievement through well-prepared completers who have achieved the position of principal or assistant principal. The considerations will be used to derive a composite profile of employers' satisfaction with program completers with the capacity to serve, influence, and thrive as educational leaders. Analysis of the idealized themes will result in identifying issues that may challenge university educational leadership programs to improve. Results, conclusions, and recommendations are used for continuous improvement, which is another national accreditation standard required for the program.

Keywords: educational leadership preparation, CAEP accreditation, principal & assistant principal evaluations, continuous improvement

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Authors: Da-Hye Jang, Woo-Jeong Cho

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Marine leisure tourism contributes greatly to the national economy in which the sea is located nearby and many countries are using marine tourism to create value added. The interest and investment of government and local governments on marine leisure tourism growing as a major trend of marine tourism is steadily increasing. But indiscriminate investment in marine leisure tourism such as duplicated business wastes limited resources. In other words, government and local governments need to select and concentrate on the goal they pursue by drawing priority on maritime leisure tourism policies. The purpose of this study is to analyze development strategies on supplier for marine leisure tourism and thus provide a comprehensive and rational framework for developing marine leisure tourism. In order to achieve the purpose, this study is to analyze priorities for each evaluation criterion of marine leisure tourism development policies using Analytic Hierarchy Process. In this study, a questionnaire was used as the survey tool and was developed based on the previous studies, government report, regional report, related thesis and literature for marine leisure tourism. The questionnaire was constructed by verifying the validity of contents from the expert group related to marine leisure tourism after conducting the first and second preliminary surveys. The AHP survey was conducted to experts (university professors, researchers, field specialists and related public officials) from April 6, 2018 to April 30, 2018 by visiting in person or e-mail. This study distributed 123 questionnaires and 68 valid questionnaires were used for data analysis. As a result, 4 factors with 12 detail strategies were analyzed using Excel. Extracted factors of development strategies of marine leisure tourism are consist of 4 factors such as infrastructure, popularization, law & system improvement and advancement. In conclusion, the results of the pairwise comparison of the four major factor on the first class were infrastructure, popularization, law & system improvement and advancement in order. Second, marine water front space maintenance had higher priority than marina facilities expansion and the establishment of marine leisure education center. Third, marine leisure safety·culture improvement had higher priority than strengthening experience·education program and the upkeep and open promotion event. Fourth, specialization·cluster of marine leisure tourism had higher priority than business support system of marine leisure tourism. Fifth, the revision of water-related leisure activities safety act had higher priority than an enactment of marine tourism promotion act and the foster of marina service industry. Finally, marine water front space maintenance was the most important development plan to boost marine leisure tourism.

Keywords: marine leisure tourism, marine leisure, marine tourism, analytic hierarchy process

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Authors: Sina Moradi, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Patrick Hayde, Rose Amal

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Chloramine is commonly used as a disinfectant in drinking water distribution systems (DWDSs), particularly in Australia and the USA. Maintaining a chloramine residual throughout the DWDS is important in ensuring microbiologically safe water is supplied at the customer’s tap. In order to simulate how chloramine behaves when it moves through the distribution system, a water quality network model (WQNM) can be applied. In this work, the WQNM was based on mono-chloramine decomposition reactions, which enabled prediction of mono-chloramine residual at different locations through a DWDS in Australia, using the Bentley commercial hydraulic package (Water GEMS). The accuracy of WQNM predictions is influenced by a number of water quality parameters. Optimization of these parameters in order to obtain the closest results in comparison with actual measured data in a real DWDS would result in both cost reduction as well as reduction in consumption of valuable resources such as energy and materials. In this work, the optimum operating conditions of water quality parameters (i.e. temperature, pH, and initial mono-chloramine concentration) to maximize the accuracy of mono-chloramine residual predictions for two water supply scenarios in an entire network were determined using response surface methodology (RSM). To obtain feasible and economical water quality parameters for highest model predictability, Design Expert 8.0 software (Stat-Ease, Inc.) was applied to conduct the optimization of three independent water quality parameters. High and low levels of the water quality parameters were considered, inevitably, as explicit constraints, in order to avoid extrapolation. The independent variables were pH, temperature and initial mono-chloramine concentration. The lower and upper limits of each variable for two water supply scenarios were defined and the experimental levels for each variable were selected based on the actual conditions in studied DWDS. It was found that at pH of 7.75, temperature of 34.16 ºC, and initial mono-chloramine concentration of 3.89 (mg/L) during peak water supply patterns, root mean square error (RMSE) of WQNM for the whole network would be minimized to 0.189, and the optimum conditions for averaged water supply occurred at pH of 7.71, temperature of 18.12 ºC, and initial mono-chloramine concentration of 4.60 (mg/L). The proposed methodology to predict mono-chloramine residual can have a great potential for water treatment plant operators in accurately estimating the mono-chloramine residual through a water distribution network. Additional studies from other water distribution systems are warranted to confirm the applicability of the proposed methodology for other water samples.

Keywords: chloramine decay, modelling, response surface methodology, water quality parameters

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: E. Tuğba Topçu, Ebru E. Kazan, Erhan Büken

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Emergency nurses are the first health care professional to generally observe the patients, communicate patients’ family or relatives, touch the properties of patients and contact to laboratory sample of patients. Also, they are the encounter incidents related crime, people who engage in violence or suspicious injuries frequently. So, documentation of patients’ condition came to the hospital and conservation of evidence are important in the inquiry of forensic medicine. The aim of the study was to determine the knowledge level of healthcare professional working at the emergency services regarding their approaches to common forensic cases. The study was comprised of 404 healthcare professional working (nurse, emergency medicine technician, health officer) at the emergency services of 6 state hospitals, 6 training and 6 research hospitals and 3 university hospitals in Ankara. Data was collected using questionnaire form which was developed by researches in the direction of literature. Questionnaire form is comprised of two sections. The first section includes 17 questions related demographic information about health care professional and 4 questions related Turkish laws. The second section includes 43 questions to the determination of knowledge level of health care professional’s working in the emergency department, about approaches to frequently encountered forensic cases. For the data evaluation of the study; Mann Whitney U test, Bonferroni correction Kruskal Wallis H test and Chi Square tests have been used. According to study, it’s said that there is no forensic medicine expert in the foundation by 73.4% of health care professionals. Two third (66%) of participants’ in emergency department reported daily average 7 or above forensic cases applied to the emergency department and 52.1% of participants did not evaluate incidents came to the emergency department as a forensic case. Most of the participants informed 'duty of preservation of evidence' is health care professionals duty related forensic cases. In result, we determinated that knowledge level of health care professional working in the emergency department, about approaches to frequently encountered forensic cases, is not the expected level. Because we found that most of them haven't received education about forensic nursing.Postgraduates participants, educated health professional about forensic nursing, staff who applied to sources about forensic nursing and staff who evaluated emergency department cases as forensic cases have significantly higher level of knowledge. Moreover, it’s found that forensic cases diagnosis score is the highest in health officer and university graduated. Health care professional’s deficiency in knowledge about forensic cases can cause defects in operation of the forensic process because of mistakes in collecting and conserving of evidence. It is obvious that training about the approach to forensic nursing should be arranged.

Keywords: emergency nurses, forensic case, forensic nursing, level of knowledge

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Authors: Matthias Stange

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Building Information Modelling (BIM) is one of the most promising methods in the building design process and plays an important role in the digitalization of the Architectural, Engineering, and Construction (AEC) Industry. The application of BIM is seen as the key enabler for increasing productivity in the construction industry. The model-based collaboration using the BIM method is intended to significantly reduce cost increases, schedule delays, and quality problems in the planning and construction of buildings. Numerous qualitative studies based on expert interviews support this theory and report perceived benefits from the use of BIM in terms of achieving project objectives related to cost, schedule, and quality. However, there is a large research gap in analysing quantitative data collected from real construction projects regarding the actual benefits of applying BIM based on representative sample size and different application regions as well as different project typologies. In particular, the influence of the project-related BIM maturity level is completely unexplored. This research project examines primary data from 105 construction projects worldwide using quantitative research methods. Projects from the areas of residential, commercial, and industrial construction as well as infrastructure and hydraulic engineering were examined in application regions North America, Australia, Europe, Asia, MENA region, and South America. First, a descriptive data analysis of 6 independent project variables (BIM maturity level, application region, project category, project type, project size, and BIM level) were carried out using statistical methods. With the help of statisticaldata analyses, the influence of the project-related BIM maturity level on 6 dependent project variables (deviation in planning time, deviation in construction time, number of planning collisions, frequency of rework, number of RFIand number of changes) was investigated. The study revealed that most of the benefits of using BIM perceived through numerous qualitative studies have not been confirmed. The results of the examined sample show that the application of BIM did not have an improving influence on the dependent project variables, especially regarding the quality of the planning itself and the adherence to the schedule targets. The quantitative research suggests the conclusion that the BIM planning method in its current application has not (yet) become a recognizable increase in productivity within the planning and construction process. The empirical findings indicate that this is due to the overall low level of BIM maturity in the projects of the examined sample. As a quintessence, the author suggests that the further implementation of BIM should primarily focus on an application-oriented and consistent development of the project-related BIM maturity level instead of implementing BIM for its own sake. Apparently, there are still significant difficulties in the interweaving of people, processes, and technology.

Keywords: AEC-process, building information modeling, BIM maturity level, project results, productivity of the construction industry

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Authors: Sachil Kumar, Anoop K.Verma, Uma Shankar Singh

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It’s extremely important to study postmortem interval in different causes of death since it assists in a great way in making an opinion on the exact cause of death following such incident often times. With diligent knowledge of the interval one could really say as an expert that the cause of death is not feigned hence there is a great need in evaluating such death to have been at the CRIME SCENE before performing an autopsy on such body. The approach described here is based on analyzing the degradation or proteolysis of a cardiac protein in cases of deaths due to burn as a marker of time since death. Cardiac tissue samples were collected from (n=6) medico-legal autopsies, (Department of Forensic Medicine and Toxicology), King George’s Medical University, Lucknow India, after informed consent from the relatives and studied post-mortem degradation by incubation of the cardiac tissue at room temperature (20±2 OC) for different time periods (~7.30, 18.20, 30.30, 41.20, 41.40, 54.30, 65.20, and 88.40 Hours). The cases included were the subjects of burn without any prior history of disease who died in the hospital and their exact time of death was known. The analysis involved extraction of the protein, separation by denaturing gel electrophoresis (SDS-PAGE) and visualization by Western blot using cTnT specific monoclonal antibodies. The area of the bands within a lane was quantified by scanning and digitizing the image using Gel Doc. As time postmortem progresses the intact cTnT band degrades to fragments that are easily detected by the monoclonal antibodies. A decreasing trend in the level of cTnT (% of intact) was found as the PM hours increased. A significant difference was observed between <15 h and other PM hours (p<0.01). Significant difference in cTnT level (% of intact) was also observed between 16-25 h and 56-65 h & >75 h (p<0.01). Western blot data clearly showed the intact protein at 42 kDa, three major (28 kDa, 30kDa, 10kDa) fragments, three additional minor fragments (12 kDa, 14kDa, and 15 kDa) and formation of low molecular weight fragments. Overall, both PMI and cardiac tissue of burned corpse had a statistically significant effect where the greatest amount of protein breakdown was observed within the first 41.40 Hrs and after it intact protein slowly disappears. If the percent intact cTnT is calculated from the total area integrated within a Western blot lane, then the percent intact cTnT shows a pseudo-first order relationship when plotted against the time postmortem. A strong significant positive correlation was found between cTnT and PM hours (r=0.87, p=0.0001). The regression analysis showed a good variability explained (R2=0.768) The post-mortem Troponin-T fragmentation observed in this study reveals a sequential, time-dependent process with the potential for use as a predictor of PMI in cases of burning.

Keywords: burn, degradation, postmortem interval, troponin-T

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

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

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

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Authors: Fatemeh Sadeghi, Peyman Sheikhzadeh

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Introduction: Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm was recently developed to suppress excessive noise by applying a relative difference penalty. The aim of this study was to investigate the effect of various strengths of noise penalization factor in the BSREM algorithm under different acquisition duration and lesion sizes in order to determine an optimum penalty factor by considering both quantitative and qualitative image evaluation parameters in clinical uses. Materials and Methods: The NEMA IQ phantom and 15 clinical whole-body patients with prostate cancer were evaluated. Phantom and patients were injected withGallium-68 Prostate-Specific Membrane Antigen(68 Ga-PSMA)and scanned on a non-time-of-flight Discovery IQ Positron Emission Tomography/Computed Tomography(PET/CT) scanner with BGO crystals. The data were reconstructed using BSREM with a β-value of 100-500 at an interval of 100. These reconstructions were compared to OSEM as a widely used reconstruction algorithm. Following the standard NEMA measurement procedure, background variability (BV), recovery coefficient (RC), contrast recovery (CR) and residual lung error (LE) from phantom data and signal-to-noise ratio (SNR), signal-to-background ratio (SBR) and tumor SUV from clinical data were measured. Qualitative features of clinical images visually were ranked by one nuclear medicine expert. Results: The β-value acts as a noise suppression factor, so BSREM showed a decreasing image noise with an increasing β-value. BSREM, with a β-value of 400 at a decreased acquisition duration (2 min/ bp), made an approximately equal noise level with OSEM at an increased acquisition duration (5 min/ bp). For the β-value of 400 at 2 min/bp duration, SNR increased by 43.7%, and LE decreased by 62%, compared with OSEM at a 5 min/bp duration. In both phantom and clinical data, an increase in the β-value is translated into a decrease in SUV. The lowest level of SUV and noise were reached with the highest β-value (β=500), resulting in the highest SNR and lowest SBR due to the greater noise reduction than SUV reduction at the highest β-value. In compression of BSREM with different β-values, the relative difference in the quantitative parameters was generally larger for smaller lesions. As the β-value decreased from 500 to 100, the increase in CR was 160.2% for the smallest sphere (10mm) and 12.6% for the largest sphere (37mm), and the trend was similar for SNR (-58.4% and -20.5%, respectively). BSREM visually was ranked more than OSEM in all Qualitative features. Conclusions: The BSREM algorithm using more iteration numbers leads to more quantitative accuracy without excessive noise, which translates into higher overall image quality and lesion detectability. This improvement can be used to shorter acquisition time.

Keywords: BSREM reconstruction, PET/CT imaging, noise penalization, quantification accuracy

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Authors: Sarah J. C. Slabbert

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The uptake of research as part of the diffusion or adoption of innovation by practitioners, whether individuals or organisations, has been a popular topic in agricultural development studies for many decades. In the classical, linear model of innovation theory, the innovation originates from an expert source such as a state-supported research organisation or academic institution. The changing context of agriculture led to the development of the agricultural innovation systems model, which recognizes innovation as a complex interaction between individuals and organisations, which include private industry and collective action organisations. In terms of this model, an innovation can be developed and adopted without any input or intervention from a state or parastatal research organisation. This evolution in the diffusion of agricultural innovation has put forward new challenges for state or parastatal research organisations, which have to demonstrate the impact of their research to the legislature or a regulatory authority: Unless the organisation and the research it produces cross the knowledge paths of the intended audience, there will be no awareness, no uptake and certainly no impact. It is therefore critical for such a research organisation to base its communication strategy on a thorough understanding of the knowledge needs, information sources and knowledge networks of the intended target audience. In 2016, the South African Water Research Commission (WRC) commissioned a study to investigate the knowledge needs, information sources and knowledge networks of Water User Associations and commercial irrigators with the aim of improving uptake of its research on efficient water use in irrigation. The first phase of the study comprised face-to-face interviews with the CEOs and Board Chairs of four Water User Associations along the Orange River in South Africa, and 36 commercial irrigation farmers from the same four irrigation schemes. Intermediaries who act as knowledge conduits to the Water User Associations and the irrigators were identified and 20 of them were subsequently interviewed telephonically. The study found that irrigators interact regularly with grower organisations such as SATI (South African Table Grape Industry) and SAPPA (South African Pecan Nut Association) and that they perceive these organisations as credible, trustworthy and reliable, within their limitations. State and parastatal research institutions, on the other hand, are associated with a range of negative attributes. As a result, the awareness of, and interest in, the WRC and its research on water use efficiency in irrigated agriculture are low. The findings suggest that a communication strategy that involves collaboration with these grower organisations would empower the WRC to participate much more efficiently and with greater impact in agricultural innovation networks. The paper will elaborate on the findings and discuss partnering frameworks and opportunities to manage perceptions and uptake.

Keywords: agricultural innovation systems, communication strategy, diffusion of innovation, irrigated agriculture, knowledge paths, research organisations, target audiences, water use efficiency

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Authors: Micael Sousa

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Board games (BGs) are thriving as new designs emerge from the hobby community to greater audiences all around the world. Although digital games are gathering most of the attention in game studies and serious games research fields, the post-digital movement helps to explain why in the world dominated by digital technologies, the analog experiences are still unique and irreplaceable to users, allowing innovation in new hybrid environments. The BG’s new designs are part of these post-digital and hybrid movements because they result from the use of powerful digital tools that enable the production and knowledge sharing about the BGs and their face-to-face unique social experiences. These new BGs, defined as modern by many authors, are providing innovative designs and unique game mechanics that are still not yet fully explored by the main serious games (SG) approaches. Even the most established frameworks settled to address SG, as fun games implemented to achieve predefined goals need more development, especially when considering modern BGs. Despite the many anecdotic perceptions, researchers are only now starting to rediscover BGs and demonstrating their potentials. They are proving that BGs are easy to adapt and to grasp by non-expert players in experimental approaches, with the possibility of easy-going adaptation to players’ profiles and serious objectives even during gameplay. Although there are many design thinking (DT) models and practices, their relations with SG frameworks are also underdeveloped, mostly because this is a new research field, lacking theoretical development and the systematization of the experimental practices. Using BG as case studies promise to help develop these frameworks. Departing from the Design, Experience, and Play (DPE) framework and considering the Common Design Think Tools (CDST), this paper proposes a new experimental framework for the adaptation and development of modern BG design for DT: the Design, Experience, and Play for Think (DPET) experimental framework. This is done through the systematization of the DPE and CDST approaches applied in two case studies, where two different sequences of adapted BG were employed to establish a DT collaborative process. These two sessions occurred with different participants and in different contexts, also using different sequences of games for the same DT approach. The first session took place at the Faculty of Economics at the University of Coimbra in a training session of serious games for project development. The second session took place in the Casa do Impacto through The Great Village Design Jam light. Both sessions had the same duration and were designed to progressively achieve DT goals, using BGs as SGs in a collaborative process. The results from the sessions show that a sequence of BGs, when properly adapted to address the DPET framework, can generate a viable and innovative process of collaborative DT that is productive, fun, and engaging. The DPET proposed framework intents to help establish how new SG solutions could be defined for new goals through flexible DT. Applications in other areas of research and development can also benefit from these findings.

Keywords: board games, design thinking, methodology, serious games

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Authors: Anne-Margré C. Vink

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Background: Food-related allergies and intolerances are frequently occurring in dogs. Diagnosis and monitoring according to ‘Golden Standard’ of elimination efficiency are time-consuming, expensive, and requires expert clinical setting. In order to facilitate rapid and robust, quantitative testing of intolerance, and determining the individual offending foods, a serological test is implicated. Method: As we developed Medisynx IgG Human Screening Test ELISA before and the dog’s immune system is most similar to humans, we were able to develop Medisynx IgG Dog Screening Test ELISA as well. In this study, 47 dogs suffering from Canine Atopic Dermatitis (CAD) and several secondary induced reactions were included to participate in serological Medisynx IgG Dog Screening Test ELISA (within < 0,02 % SD). Results were expressed as titers relative to the standard OD readings to diagnose alimentary induced diseases and monitoring the efficacy of an individual eliminating diet in dogs. Split sample analysis was performed by independently sending 2 times 3 ml serum under two unique codes. Results: The veterinarian monitored these dogs to check dog’ results at least at 3, 7, 21, 49, 70 days and after period of 6 and 12 months on an individual negative diet and a positive challenge (retrospectively) at 6 months. Data of each dog were recorded in a screening form and reported that a complete recovery of all clinical manifestations was observed at or less than 70 days (between 50 and 70 days) in the majority of dogs(44 out of 47 dogs =93.6%). Conclusion: Challenge results showed a significant result of 100% in specificity as well as 100% positive predicted value. On the other hand, sensitivity was 95,7% and negative predictive value was 95,7%. In conclusion, an individual diet based on IgG ELISA in dogs provides a significant improvement of atopic dermatitis and pruritus including all other non-specific defined allergic skin reactions as erythema, itching, biting and gnawing at toes, as well as to several secondary manifestations like chronic diarrhoea, chronic constipation, otitis media, obesity, laziness or inactive behaviour, pain and muscular stiffness causing a movement disorders, excessive lacrimation, hyper behaviour, nervous behaviour and not possible to stay alone at home, anxiety, biting and aggressive behaviour and disobedience behaviour. Furthermore, we conclude that a relatively more severe systemic candidiasis, as shown by relatively higher titer (class 3 and 4 IgG reactions to Candida albicans), influence the duration of recovery from clinical manifestations in affected dogs. These findings are consistent with our preliminary human clinical studies.

Keywords: allergy, canine atopic dermatitis, CAD, food allergens, IgG-ELISA, food-incompatibility

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Authors: Mareike Dornhoefer, Madjid Fathi

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Water supply and water quality are key problems of mankind at the moment and - due to increasing population - in the future. Management disciplines like water, environment and quality management therefore need to closely interact, to establish a high level of water quality and to guarantee water supply in all parts of the world. Groundwater remediation is one aspect in this process. From a knowledge management perspective it is only possible to solve complex ecological or environmental problems if different factors, expert knowledge of various stakeholders and formal regulations regarding water, waste or chemical management are interconnected in form of a knowledge base. In general knowledge management focuses the processes of gathering and representing existing and new knowledge in a way, which allows for inference or deduction of knowledge for e.g. a situation where a problem solution or decision support are required. A knowledge base is no sole data repository, but a key element in a knowledge based system, thus providing or allowing for inference mechanisms to deduct further knowledge from existing facts. In consequence this knowledge provides decision support. The given paper introduces an environmental knowledge system in water management. The proposed environmental knowledge system is part of a research concept called Green Knowledge Management. It applies semantic technologies or concepts such as ontology or linked open data to interconnect different data and information sources about environmental aspects, in this case, water quality, as well as background material enriching an established knowledge base. Examples for the aforementioned ecological or environmental factors threatening water quality are among others industrial pollution (e.g. leakage of chemicals), environmental changes (e.g. rise in temperature) or floods, where all kinds of waste are merged and transferred into natural water environments. Water quality is usually determined with the help of measuring different indicators (e.g. chemical or biological), which are gathered with the help of laboratory testing, continuous monitoring equipment or other measuring processes. During all of these processes data are gathered and stored in different databases. Meanwhile the knowledge base needs to be established through interconnecting data of these different data sources and enriching its semantics. Experts may add their knowledge or experiences of previous incidents or influencing factors. In consequence querying or inference mechanisms are applied for the deduction of coherence between indicators, predictive developments or environmental threats. Relevant processes or steps of action may be modeled in form of a rule based approach. Overall the environmental knowledge system supports the interconnection of information and adding semantics to create environmental knowledge about water environment, supply chain as well as quality. The proposed concept itself is a holistic approach, which links to associated disciplines like environmental and quality management. Quality indicators and quality management steps need to be considered e.g. for the process and inference layers of the environmental knowledge system, thus integrating the aforementioned management disciplines in one water management application.

Keywords: water quality, environmental knowledge system, green knowledge management, semantic technologies, quality management

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Authors: Polina Trusova

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The majority of young enterprises is founded and run by teams and develops new, innovative products or services. While problems within the team are considered to be an important reason for the failure of young enterprises, effective teamwork on innovation may be a key success factor. It may require special teamwork design or members’ creativity not needed during work routine. However, little is known about how young enterprises develop innovative solutions in teams, what makes their teamwork special and what influences its effectivity. Extending this knowledge is essential for understanding the success and failure factors for young enterprises. Previous research focused on working on innovation or professional teams in general. Rare studies combining these issues usually concentrate on homogenous groups like IT expert teams in innovation projects of big, well-established firms. The transferability of those studies’ findings to the entrepreneurial context is doubtful because of several reasons why teamwork should differ significantly between big, well-established firms and young enterprises. First, teamwork is conducted by team members, e.g., employees. The personality of employees in young enterprises, in contrast to that of employees in established firms, has been shown to be more similar to the personality of entrepreneurs. As entrepreneurs were found to be more open to experience and show less risk aversion, it may have a positive impact on their teamwork. Persons open to novelty are more likely to develop or accept a creative solution, which is especially important for teamwork on innovation. Secondly, young enterprises are often characterized by a flat hierarchy, so in general, teamwork should be more participative there. It encourages each member (and not only the founder) to produce and discuss innovative ideas, increasing their variety and enabling the team to select the best idea from the larger idea pool. Thirdly, teams in young enterprises are often multidisciplinary. It has some advantages but also increases the risk of internal conflicts making teamwork less effective. Despite the key role of teamwork on innovation and presented barriers for transferring existing evidence to the context of young enterprises, only a few researchers have addressed this issue. In order to close the existing research gap, to explore and understand how innovations are developed in teams of young enterprises and which factors influencing teamwork may be especially relevant for such teams, a qualitative study has been developed. The study consisting of 20 half-structured interviews with (co-)founders of young innovative enterprises in the UK and USA started in September 2017. The interview guide comprises but is not limited to teamwork dimensions discussed in literature like members’ skill or authority differentiation. Data will be evaluated following the rules of qualitative content analysis. First results indicate some factors which may be relevant especially for teamwork in young innovative enterprises. They will enrich the scientific discussion and provide the evidence needed to test a possible causality between identified factors and teamwork effectivity in future research on young innovative enterprises. Results and their discussion can be presented at the conference.

Keywords: innovation, qualitative study, teamwork, young enterprises

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Authors: Nkechi V. Osuji

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The use of blockchain to address the issue of climate change is increasingly a discourse among countries, industries, and stakeholders. For a long time, the European Union (EU) has been combating the issue of climate action in industries through sustainability programs. One of such programs is the EU monitoring reporting and verification (MRV) program of the EU ETS. However, the system has some key challenges and areas for improvement, which makes it inefficient. The main objective of the research is to look at how blockchain can be used to improve the inefficiency of the EU ETS program for the Danish energy industry with a focus on its monitoring and reporting framework. Applying empirical data from 13 semi-structured expert interviews, three case studies, and literature reviews, three outcomes are presented in the study. The first is on the current conditions and challenges of monitoring and reporting CO₂ emission trading. The second is putting into consideration if blockchain is the right fit to solve these challenges and how. The third stage looks at the factors that might affect the implementation of such a system and provides recommendations to mitigate these challenges. The first stage of the findings reveals that the monitoring and reporting of CO₂ emissions is a mandatory requirement by law for all energy operators under the EU ETS program. However, most energy operators are non-compliant with the program in reality, which creates a gap and causes challenges in the monitoring and reporting of CO₂ emission trading. Other challenges the study found out are the lack of transparency, lack of standardization in CO₂ accounting, and the issue of double-counting in the current system. The second stage of the research was guided by three case studies and requirement engineering (RE) to explore these identified challenges and if blockchain is the right fit to address them. This stage of the research addressed the main research question: how can blockchain be used for monitoring and reporting CO₂ emission trading in the energy industry. Through analysis of the study data, the researcher developed a conceptual private permissioned Hyperledger blockchain and elucidated on how it can address the identified challenges. Particularly, the smart contract of blockchain was highlighted as a key feature. This is because of its ability to automate, be immutable, and digitally enforce negotiations without a middleman. These characteristics are unique in solving the issue of compliance, transparency, standardization, and double counting identified. The third stage of the research presents technological constraints and a high level of stakeholder collaboration as major factors that might affect the implementation of the proposed system. The proposed conceptual model requires high-level integration with other technologies such as the Internet of Things (IoT) and machine learning. Therefore, the study encourages future research in these areas. This is because blockchain is continually evolving its technology capabilities. As such, it remains a topic of interest in research and development for addressing climate change. Such a study is a good contribution to creating sustainable practices to solve the global climate issue.

Keywords: blockchain, carbon emission trading, European Union emission trading system, monitoring and reporting

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

Procedia PDF Downloads 253

Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: Dalia Hanna, Alexander Ferworn

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This research provides detailed proposed training modules for the public safety teams and, specifically, SAR teams responsible for search and rescue operations related to finding lost persons with dementia. Finding a lost person alive is the goal of this training. Time matters if a lost person is to be found alive. Finding lost people living with dementia is quite challenging, as they are unaware they are lost and will not seek help. Even a small contribution to SAR operations could contribute to saving a life. SAR operations will always require expert professional and human volunteers. However, we can reduce their time, save lives, and reduce costs by providing practical training that is based on real-life scenarios. The content for the proposed training is based on the research work done by the researcher in this area. This research has demonstrated that, based on utilizing drones, the algorithmic approach could support a successful search outcome. Understanding the behavior of the lost person, learning where they may be found, predicting their survivability, and automating the search are all contributions of this work, founded in theory and demonstrated in practice. In crisis management, human behavior constitutes a vital aspect in responding to the crisis; the speed and efficiency of the response often get affected by the difficulty of the context of the operation. Therefore, training in this area plays a significant role in preparing the crisis manager to manage the emotional aspects that lead to decision-making in these critical situations. Since it is crucial to gain high-level strategic choices and the ability to apply crisis management procedures, simulation exercises become central in training crisis managers to gain the needed skills to respond critically to these events. The training will enhance the responders’ ability to make decisions and anticipate possible consequences of their actions through flexible and revolutionary reasoning in responding to the crisis efficiently and quickly. As adult learners, search and rescue teams will be approaching training and learning by taking responsibility of the learning process, appreciate flexible learning and as contributors to the teaching and learning happening during that training. These are all characteristics of adult learning theories. The learner self-reflects, gathers information, collaborates with others and is self-directed. One of the learning strategies associated with adult learning is effective elaboration. It helps learners to remember information in the long term and use it in situations where it might be appropriate. It is also a strategy that can be taught easily and used with learners of different ages. Designers must design reflective activities to improve the student’s intrapersonal awareness.

Keywords: training, OER, dementia, drones, search and rescue, adult learning, UDL, instructional design

Procedia PDF Downloads 108

Authors: Aisha Ijaz

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The paper focuses on the impact of Muslim religiosity on convenience food purchases and involvement experienced in a non-Muslim culture. There is a scarcity of research on the purchasing patterns of Muslim diaspora communities residing in risk societies, particularly in contexts where there is an increasing inclination toward industrialized food items alongside a renewed interest in the concept of natural foods. The United Kingdom serves as an appropriate setting for this study due to the increasing Muslim population in the country, paralleled by the expanding Halal Food Market. A multi-dimensional framework is proposed, testing for five forms of involvement, specifically Purchase Decision Involvement, Product Involvement, Behavioural Involvement, Intrinsic Risk and Extrinsic Risk. Quantitative cross-sectional consumer data were collected through a face-to-face survey contact method with 141 Muslims during the summer of 2020 in Liverpool located in the Northwest of England. proportion formula was utilitsed, and the population of interest was stratified by gender and age before recruitment took place through local mosques and community centers. Six input variables were used (intrinsic religiosity and involvement dimensions), dividing the sample into 4 clusters using the Two-Step Cluster Analysis procedure in SPSS. Nuanced variances were observed in the type of involvement experienced by religiosity group, which influences behaviour when purchasing convenience food. Four distinct market segments were identified: highly religious ego-involving (39.7%), less religious active (26.2%), highly religious unaware (16.3%), less religious concerned (17.7%). These segments differ significantly with respects to their involvement, behavioural variables (place of purchase and information sources used), socio-cultural (acculturation and social class), and individual characteristics. Choosing the appropriate convenience food is centrally related to the value system of highly religious ego-involving first-generation Muslims, which explains their preference for shopping at ethnic food stores. Less religious active consumers are older and highly alert in information processing to make the optimal food choice, relying heavily on product label sources. Highly religious unaware Muslims are less dietary acculturated to the UK diet and tend to rely on digital and expert advice sources. The less-religious concerned segment, who are typified by younger age and third generation, are engaged with the purchase process because they are worried about making unsuitable food choices. Research implications are outlined and potential avenues for further explorations are identified.

Keywords: consumer behaviour, consumption, convenience food, religion, muslims, UK

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Authors: Alena Radina

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On the global stage, national image is shaped by historical memory of wars and alliances, government ideology and particularly media stereotypes which represent countries in positive or negative ways. News magazine covers are a key site for national representation. The object of analysis in this paper is the portrayals of the US, Germany, China, and Russia in the front pages and cover stories of “Time”, “Der Spiegel”, “Beijing Review”, and “Expert”. Political comedy helps people learn about current affairs even if politics is not their area of interest, and thus satire indirectly sets the public agenda. Coupled with satirical messages, cover images and the linguistic messages embedded in the covers become persuasive visual and verbal factors, known to drive about 80% of magazine sales. Preliminary analysis identified satirical elements in magazine covers, which are known to influence and frame understandings and attract younger audiences. Multimodal and transnational comparative framing analyses lay the groundwork to investigate why journalists, editors and designers deploy certain frames rather than others. This research investigates to what degree frames used in covers correlate with frames within the cover stories and what these framings can tell us about media professionals’ representations of their own and other nations. The study sample includes 32 covers consisting of two covers representing each of the four chosen countries from the four magazines. The sampling framework considers two time periods to compare countries’ representation with two different presidents, and between men and women when present. The countries selected for analysis represent each category of the international news flows model: the core nations are the US and Germany; China is a semi-peripheral country; and Russia is peripheral. Examining textual and visual design elements on the covers and images in the cover stories reveals not only what editors believe visually attracts the reader’s attention to the magazine but also how the magazines frame and construct national images and national leaders. The cover is the most powerful editorial and design page in a magazine because images incorporate less intrusive framing tools. Thus, covers require less cognitive effort of audiences who may therefore be more likely to accept the visual frame without question. Analysis of design and linguistic elements in magazine covers helps to understand how media outlets shape their audience’s perceptions and how magazines frame global issues. While previous multimodal research of covers has focused mostly on lifestyle magazines or newspapers, this paper examines the power of current affairs magazines’ covers to shape audience perception of national image.

Keywords: framing analysis, magazine covers, multimodality, national image, satire

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Authors: Mohammadreza Bakhtiari, Mehrdad Maghsoudi, Hamidreza Bakhtiari

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The widespread adoption of laptops has become essential to modern lifestyles, supporting work, education, and entertainment. Social media platforms have emerged as key spaces where users share real-time feedback on laptop performance, providing a valuable source of data for understanding consumer preferences. This study leverages aspect-based sentiment analysis (ABSA) on 1.5 million tweets to examine how users from developed and developing countries perceive and prioritize 16 key laptop features. The analysis reveals that consumers in developing countries express higher satisfaction overall, emphasizing affordability, durability, and reliability. Conversely, users in developed countries demonstrate more critical attitudes, especially toward performance-related aspects such as cooling systems, battery life, and chargers. The study employs a mixed-methods approach, combining ABSA using the PyABSA framework with expert insights gathered through a Delphi panel of ten industry professionals. Data preprocessing included cleaning, filtering, and aspect extraction from tweets. Universal issues such as battery efficiency and fan performance were identified, reflecting shared challenges across markets. However, priorities diverge between regions, while users in developed countries demand high-performance models with advanced features, those in developing countries seek products that offer strong value for money and long-term durability. The findings suggest that laptop manufacturers should adopt a market-specific strategy by developing differentiated product lines. For developed markets, the focus should be on cutting-edge technologies, enhanced cooling solutions, and comprehensive warranty services. In developing markets, emphasis should be placed on affordability, versatile port options, and robust designs. Additionally, the study highlights the importance of universal charging solutions and continuous sentiment monitoring to adapt to evolving consumer needs. This research offers practical insights for manufacturers seeking to optimize product development and marketing strategies for global markets, ensuring enhanced user satisfaction and long-term competitiveness. Future studies could explore multi-source data integration and conduct longitudinal analyses to capture changing trends over time.

Keywords: consumer behavior, durability, laptop industry, sentiment analysis, social media analytics

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Authors: Taekyun Hur, Yoonyoung Kim, Junkyu Lim

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Previous works on leisure activities had been categorizing activities arbitrarily and subjectively while focusing on a single dimension (e.g. active-passive, individual-group). To overcome these problems, this study proposed a Korean leisure activities’ matrix model that considered multidimensional features of leisure activities, which was comprised of 3 main factors and 6 sub factors: (a) Active (physical, mental), (b) Relational (quantity, quality), (c) Expert (entry barrier, possibility of improving). We developed items for measuring the degree of each dimension for every leisure activity. Using the developed Leisure Activities Dimensions (LAD) questionnaire, we investigated the presented dimensions of a total of 78 leisure activities which had been enjoyed by most Koreans recently (e.g. watching movie, taking a walk, watching media). The study sample consisted of 1348 people (726 men, 658 women) ranging in age from teenagers to elderlies in their seventies. This study gathered 60 data for each leisure activity, a total of 4860 data, which were used for statistical analysis. First, this study compared 3-factor model (Activity, Relation, Expertise) fit with 6-factor model (physical activity, mental activity, relational quantity, relational quality, entry barrier, possibility of improving) fit by using confirmatory factor analysis. Based on several goodness-of-fit indicators, the 6-factor model for leisure activities was a better fit for the data. This result indicates that it is adequate to take account of enough dimensions of leisure activities (6-dimensions in our study) to specifically apprehend each leisure attributes. In addition, the 78 leisure activities were cluster-analyzed with the scores calculated based on the 6-factor model, which resulted in 8 leisure activity groups. Cluster 1 (e.g. group sports, group musical activity) and Cluster 5 (e.g. individual sports) had generally higher scores on all dimensions than others, but Cluster 5 had lower relational quantity than Cluster 1. In contrast, Cluster 3 (e.g. SNS, shopping) and Cluster 6 (e.g. playing a lottery, taking a nap) had low scores on a whole, though Cluster 3 showed medium levels of relational quantity and quality. Cluster 2 (e.g. machine operating, handwork/invention) required high expertise and mental activity, but low physical activity. Cluster 4 indicated high mental activity and relational quantity despite low expertise. Cluster 7 (e.g. tour, joining festival) required not only moderate degrees of physical activity and relation, but low expertise. Lastly, Cluster 8 (e.g. meditation, information searching) had the appearance of high mental activity. Even though clusters of our study had a few similarities with preexisting taxonomy of leisure activities, there was clear distinctiveness between them. Unlike the preexisting taxonomy that had been created subjectively, we assorted 78 leisure activities based on objective figures of 6-dimensions. We also could identify that some leisure activities, which used to belong to the same leisure group, were included in different clusters (e.g. filed ball sports, net sports) because of different features. In other words, the results can provide a different perspective on leisure activities research and be helpful for figuring out what various characteristics leisure participants have.

Keywords: leisure, dimensional model, activity, relationship, expertise

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Authors: Smita Lahkar

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Sattriya, the youngest of the eight principal Classical Indian dance traditions, has undergone too many changes and modifications to arrive at its present stage of performing art form extracting itself from age-old religious confinement. Although some of the other traditions have been revived in the recent past, Sattriya has a living tradition since its inception in the 15th century by Srimanta Sankardeva, the great Vaishnavite saint, poet, playwright, lyricist, painter, singer and dancer of Assam, a primary north-eastern state of India. This living dance tradition from the Sattras, the Vaishnavite monasteries, has been practiced for over five hundred years by celibate male monks, as a powerful medium for propagating the Vaishnava religious faith. Sankardeva realised the potential of the vocalised word integrated with the visual image as a powerful medium of expression and communication. So he used this principal medium for propagating his newly found message of devotion among the people of his time. Earlier, Sattriya was performed by male monks alone in monasteries (Sattras) as a part of daily rituals. The females were not even allowed to learn this art form. But, in present time, Sattriya has come out from the Sattras to proscenium stage, performed mostly by female as well as few male dancers also. The technique of performing movements, costumes, ornaments, music and style of performance too have experienced too many changes and modifications. For example, earlier and even today in Sattra, the ‘Pataka’ hand gesture is depicted in conformity with the original context (religious) of creation of the dance form. But, today stage-performers prefer the instructions of the scripture ‘Srihastamuktavali’ and depict the ‘Pataka’ in a sophisticated manner affecting decontextualisation to a certain extent. This adds aesthetic beauty to the dance form as an art distancing it from its context of being a vehicle for propagating Vaishnava religion. The Sattriya dance today stands at the crossroads of past and future, tradition and modernity, devotion and display, spirituality and secularism. The traditional exponents trained under the tutelage of Sattra maestros and imbibing a devotionally inspired rigour of the religion, try to retain the traditional nuances; while the young artists being trained outside the monasteries are more interested in taking up the discipline purely from the perspective of ‘performing arts’ bereft of the philosophy of religion or its sacred associations. Hence, this paper will be an endeavor to establish the hypothesis that the Sattriya, whose origin was for propagating Vaishnava faith, has now entered the world of performing arts with highly aesthetical components. And as a transformed art form, Sattriya may be expected to carve a niche in world dance arena. This will be done with the help of historical evidences, observations from the recorded past and expert rendezvous.

Keywords: dance, performing art, religion, Sattriya

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Authors: Antonio Martín-Pardo

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With regard to the context in which this paper is inserted, it is noteworthy that the current criminal policy model in which we find immersed, denominated by some doctrine sector as the citizen security model, is characterized by a marked tendency towards the discredit of expert knowledge. This type of technic knowledge has been displaced by the common sense and by the daily experience of the people at the time of legislative drafting, as well as by excessive attention to the short-term political effects of the law. Despite this criminal-political adverse scene, we still find valuable efforts in the side of experts to bring some rationality to the legislative development. This is the case of the proposal for a new cannabis regulation model in Spain carried out by the Cannabis Policy Studies Group (hereinafter referred as ‘GEPCA’). The GEPCA is a multidisciplinary group composed by authors with multiple/different orientations, trajectories and interests, but with a common minimum objective: the conviction that the current situation regarding cannabis is unsustainable and, that a rational legislative solution must be given to the growing social pressure for the regulation of their consumption and production. This paper details the main lines through which this technical proposal is developed with the purpose of its dissemination and discussion in the Congress. The basic methodology of the proposal is inductive-expository. In that way, firstly, we will offer a brief, but solid contextualization of the situation of cannabis in Spain. This contextualization will touch on issues such as the national regulatory situation and its relationship with the international context; the criminal, judicial and penitentiary impact of the offer and consumption of cannabis, or the therapeutic use of the substance, among others. In second place, we will get down to the business properly by detailing the minutia of the three main cannabis access channels that are proposed. Namely: the regulated market, the associations of cannabis users and personal self-cultivation. In each of these options, especially in the first two, special attention will be paid to both, the production and processing of the substance and the necessary administrative control of the activity. Finally, in a third block, some notes will be given on a series of subjects that surround the different access options just mentioned above and that give fullness and coherence to the proposal outlined. Among those related issues we find some such as consumption and tenure of the substance; the issue of advertising and promotion of cannabis; consumption in areas of special risk (work or driving v. g.); the tax regime; the need to articulate evaluation instruments for the entire process; etc. The main conclusion drawn from the analysis of the proposal is the unsustainability of the current repressive system, clearly unsuccessful, and the need to develop new access routes to cannabis that guarantee both public health and the rights of people who have freely chosen to consume it.

Keywords: cannabis regulation proposal, cannabis policies studies group, criminal policy, expertise participation

Procedia PDF Downloads 119

Authors: Michael Mederle, Heinz Bernhardt

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The Management of machine fleets or autonomous vehicle control will considerably increase efficiency in future agricultural production. Especially entire process chains, e.g. harvesting complexes with several interacting combine harvesters, grain carts, and removal trucks, provide lots of optimization potential. Organization and pre-planning ensure to get these efficiency reserves accessible. One way to achieve this is to optimize infield path planning. Particularly autonomous machinery requires precise specifications about infield logistics to be navigated effectively and process optimized in the fields individually or in machine complexes. In the past, a lot of theoretical optimization has been done regarding infield logistics, mainly based on field geometry. However, there are reasons why farmers often do not apply the infield strategy suggested by mathematical route planning tools. To make the computational optimization more useful for farmers this study focuses on these influencing factors by expert interviews. As a result practice-oriented navigation not only to the field but also within the field will be possible. The survey study is intended to cover the entire range of German agriculture. Rural mixed farms with simple technology equipment are considered as well as large agricultural cooperatives which farm thousands of hectares using track guidance and various other electronic assistance systems. First results show that farm managers using guidance systems increasingly attune their infield-logistics on direction giving obstacles such as power lines. In consequence, they can avoid inefficient boom flippings while doing plant protection with the sprayer. Livestock farmers rather focus on the application of organic manure with its specific requirements concerning road conditions, landscape terrain or field access points. Cultivation of sugar beets makes great demands on infield patterns because of its particularities such as the row crop system or high logistics demands. Furthermore, several machines working in the same field simultaneously influence each other, regardless whether or not they are of the equal type. Specific infield strategies always are based on interactions of several different influences and decision criteria. Single working steps like tillage, seeding, plant protection or harvest mostly cannot be considered each individually. The entire production process has to be taken into consideration to detect the right infield logistics. One long-term objective of this examination is to integrate the obtained influences on infield strategies as decision criteria into an infield navigation tool. In this way, path planning will become more practical for farmers which is a basic requirement for automatic vehicle control and increasing process efficiency.

Keywords: autonomous vehicle control, infield logistics, path planning, process optimizing

Procedia PDF Downloads 233

Authors: Maria C. Almario, Pam Remer, Jeff Resse, Kathy Moran, Linda Theander Adam

Abstract:

The identification of victims of human trafficking and consequential service provision is characterized by a significant disconnection between the estimated prevalence of this issue and the number of cases identified. This poses as tremendous problem for human rights advocates as it prevents data collection, information sharing, allocation of resources and opportunities for international dialogues. The current paper introduces the Inclusive Human Trafficking Checklist (IHTC) as a measurement methodology with theoretical underpinnings derived from dialectic theory. The presence of human trafficking in a person’s life is conceptualized as a dynamic and dialectic interaction between vulnerability and exploitation. The current papers explores the operationalization of exploitation and vulnerability, evaluates the metric qualities of the instrument, evaluates whether there are differences in assessment based on the participant’s profession, level of knowledge, and training, and assesses if users of the instrument perceive it as useful. A total of 201 participants were asked to rate three vignettes predetermined by experts to qualify as a either human trafficking case or not. The participants were placed in three conditions: business as usual, utilization of the IHTC with and without training. The results revealed a statistically significant level of agreement between the expert’s diagnostic and the application of the IHTC with an improvement of 40% on identification when compared with the business as usual condition While there was an improvement in identification in the group with training, the difference was found to have a small effect size. Participants who utilized the IHTC showed an increased ability to identify elements of identity-based vulnerabilities as well as elements of fraud, which according to the results, are distinctive variables in cases of human trafficking. In terms of the perceived utility, the results revealed higher mean scores for the groups utilizing the IHTC when compared to the business as usual condition. These findings suggest that the IHTC improves appropriate identification of cases and that it is perceived as a useful instrument. The application of the IHTC as a multidisciplinary instrumentation that can be utilized in legal and human services settings is discussed as a pivotal piece of helping victims restore their sense of dignity, and advocate for legal, physical and psychological reparations. It is noteworthy that this study was conducted with a sample in the United States and later re-tested in Colombia. The implications of the instrument for treatment conceptualization and intervention in human trafficking cases are discussed as opportunities for enhancement of victim well-being, restoration engagement and activism. With the idea that what is personal is also political, we believe that the careful observation and data collection in specific cases can inform new areas of human rights activism.

Keywords: exploitation, human trafficking, measurement, vulnerability, screening

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Authors: Ana Flavia Belchior De Andrade

Abstract:

Forensic laboratories all over the world face a great challenge to overcame waiting time and backlog in many different areas. Many aspects contribute to this situation, such as an increase in drug complexity, increment in the number of exams requested and cuts in funding limiting laboratories hiring capacity. Altogether, those facts pose an essential challenge for forensic chemistry laboratories to keep both quality and time of response within an acceptable period. In this paper we will analyze how the backlog affects test results and, in the end, the whole judicial system. In this study data from marijuana samples seized by the Federal District Civil Police in Brazil between the years 2013 and 2017 were tabulated and the results analyzed and discussed. In the last five years, the number of petitioned exams increased from 822 in February 2013 to 1358 in March 2018, representing an increase of 32% in 5 years, a rise of more than 6% per year. Meanwhile, our data shows that the number of performed exams did not grow at the same rate. Product numbers are stationed as using the actual technology scenario and analyses routine the laboratory is running in full capacity. Marijuana detection is the most prevalence exam required, representing almost 70% of all exams. In this study, data from 7,110 (seven thousand one hundred and ten) marijuana samples were analyzed. Regarding waiting time, most of the exams were performed not later than 60 days after receipt (77%). Although some samples waited up to 30 months before being examined (0,65%). When marijuana´s exam is delayed we notice the enlargement of inconclusive results using thin-layer chromatography (TLC). Our data shows that if a marijuana sample is stored for more than 18 months, inconclusive results rise from 2% to 7% and when if storage exceeds 30 months, inconclusive rates increase to 13%. This is probably because Cannabis plants and preparations undergo oxidation under storage resulting in a decrease in the content of Δ9-tetrahydrocannabinol ( Δ9-THC). An inconclusive result triggers other procedures that require at least two more working hours of our analysts (e.g., GC/MS analysis) and the report would be delayed at least one day. Those new procedures increase considerably the running cost of a forensic drug laboratory especially when the backlog is significant as inconclusive results tend to increase with waiting time. Financial aspects are not the only ones to be observed regarding backlog cases; there are also social issues as legal procedures can be delayed and prosecution of serious crimes can be unsuccessful. Delays may slow investigations and endanger public safety by giving criminals more time on the street to re-offend. This situation also implies a considerable cost to society as at some point, if the exam takes a long time to be performed, an inconclusive can turn into a negative result and a criminal can be absolved by flawed expert evidence.

Keywords: backlog, forensic laboratory, quality management, accreditation

Procedia PDF Downloads 122