Search results for: JMeter master and slave using cloud Services

Authors: Rachel Tambyah, Katarzyna Olcoń, Julaine Allan, Pete Destry, Thomas Astell-Burt

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The rising social and financial burden of mental illness indicates an urgent need to explore interventions that can be used as well as or instead of traditional treatments. Although there is growing evidence of the positive mental health outcomes of spending time in nature, the implementation of nature-based interventions (NBIs) within mental health services remains minimal. Based on interviews with mental health clinicians in Australia, this study demonstrated that clinicians supported the use of NBIs and would promote them to their clients.

Keywords: nature, nature-based interventions, mental health, mental health services, mental health clinicians

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Authors: Rania Khadim, Mohammed Erritali, Abdelhakim Maaden

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Nowadays Wireless Sensor Networks have attracted worldwide research and industrial interest, because they can be applied in various areas. Geographic routing protocols are very suitable to those networks because they use location information when they need to route packets. Obviously, location information is maintained by Location-Based Services provided by network nodes in a distributed way. In this paper we choose to evaluate the performance of two hierarchical rendezvous location based-services, GLS (Grid Location Service) and HLS (Hierarchical Location Service) coupled to the GPSR routing protocol (Greedy Perimeter Stateless Routing) for Wireless Sensor Network. The simulations were performed using NS2 simulator to evaluate the performance and power of the two services in term of location overhead, the request travel time (RTT) and the query Success ratio (QSR). This work presents also a new scalability performance study of both GLS and HLS, specifically, what happens if the number of nodes N increases. The study will focus on three qualitative metrics: The location maintenance cost, the location query cost and the storage cost.

Keywords: location based-services, routing protocols, scalability, wireless sensor networks

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Authors: Yakubu Nkom Bityong, A. I. Kabido, K. Venkateswarlu

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The influence of branding and consultancy services on sports development and marketing mix has been a matter of interest among coaches athletes and sports managers in Nigeria. Marketers use sports as a promotional vehicle towards attracting customers to their products and services. The use of images, names, and photographs of sports personalities to advertise beverages, cars, and a whole range of other products and services as it is clearly noticed all over the television, radio and print media has generated a lot of argument among consumers who have vested interest and are more drawn to their favorite teams and sports personalities than they are to many company products This paper examines the influence of branding and consultancy services on sports Performance of coaches, athletes and sports managers in Nigeria. From a population of 7,441 made up of coaches, athletes and sports managers, 372 respondents were sampled for the study. A self developed and standardized questionnaire was the instrument used for data collection. One-tailed t-test was used to test the hypothesis. Results revealed that branding and consultancy services influence the performances of coaches, athletes and sports managers in Nigeria. It was concluded that the establishment of the National Institute of Sports (NIS) in Lagos with affiliated sports training programmes in Nigerian Universities is responsible for boosting the performance of sports personalities in Nigeria. It was recommended that National Policy on Sports should be reviewed in order to inculcate new methods and strategies towards enhancing sports development initiatives in the country while stakeholders should intensify regular training and retraining programmes for coaches, athletes and sports managers to update their knowledge and skills.

Keywords: branding, consultancy, sports performance, sports development

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Authors: Natalia Khvorostianov, Nelly Elias

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The present study seeks to analyze representation of social work in immigrant media, focusing on the case of online newspapers established by immigrants from the Former Soviet Union (FSU) in Israel. This immigrant population is particularly interesting because social work did not exist as a profession practiced in the USSR and hence most FSU immigrants arrive in Israel without a basic knowledge of the essence of social work, the services it provides and the logic behind its treatment methods. The sample of 37 items was built through a Google search of the Russian online newspapers and portals originated in Israel by using keywords such as “social worker,” “social work services” and the like. All items were analyzed by using qualitative content analysis. Principal analytical categories used for the analysis were: Assessment of social work services (negative, positive, neutral); social workers’ professionalism and effectiveness; goals and motives underlying their activity; cross-cultural contact with immigrants and methods used in working with immigrants. On this basis, four dominant images used to portray Israeli social work services and social workers were identified: Lack of professionalism, cultural gaps between FSU immigrants and Israeli social workers, repressive character of social work services and social workers’ involvement in corruption and crime.

Keywords: FSU immigrants, immigrant media, media images, social workers

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Authors: Shivkumar Krishnamurti, Ruchi Agarwal

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The study examines the influence of marital status on consumers of products and services using blogs as a source of information. A pre-designed questionnaire was used to collect the primary data from the respondents (experiences). Data were collected from one hundred and eighty seven respondents residing in and around the Emirates of Sharjah and Dubai of the United Arab Emirates. The collected data was analyzed with the help of statistical tools such as averages, percentages, factor analysis, student’s t-test and structural equation modeling technique. Objectives of the study are to know the reasons how married and unmarried or single consumers of products and services are motivated to use blogs as a source of information, to know whether the consumers of products and services irrespective of their marital status share their views and experiences with other bloggers and to know the respondents’ future intentions towards blogging. The study revealed the following: Majority of the respondents have the motivation to blog because they are willing to receive comments on what they post about services, convenience of blogs to search for information about services and products, by blogging respondents share information on the symptoms of a disease/ disorder that may be experienced by someone, helps to share information about ready to cook mix products and are keen to spend more time blogging in the future.

Keywords: blog, consumer, information, marital status

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Authors: Dipendra Kumar Yadav, Rajani Ghimire, Saroj Yadav

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Background: The concern about adolescent on reproductive health has grown due to unprecedented increasing rates of early pregnancies and sexually transmitted Infections and they do not have adequate awareness and knowledge about it. Access to these services as well as information about them is, therefore, crucial for adolescents to utilize and benefit from sexual and reproductive health services. The objective of the study was to assess the reproductive health knowledge, attitude and health services utilization among adolescents in rural and urban areas of Kaski district. Materials and Methods: A community-based descriptive cross-sectional study was conducted among adolescents (10-19 years of age) in rural and urban areas of Kaski district, Nepal. The period of data collection was October to November, 2014. Altogether 419 participants were taken for the study. Results: The mean age of the respondents was 15.86 and standard deviation was ±2.305. More than half (58.7 %) of the respondents were females and 41.3 % were males. Out of 419, majority (78.8%) of the respondents were known about family planning, among them only 70 % of respondents were aware about family planning methods. Fifty-one percentages of the respondents were aware about the sexually transmitted diseases. Before giving a birth there is need to consult with partner with this fact 68.7 % of the respondents were agree, 23.6 % of them were neutral and very few (7.6%) of them were disagree. Nearly twenty six percentage of the respondents were faced the reproductive health problems within one month. Out of 107 respondents, 57.9 % did not utilize reproductive health services because of different reasons. Conclusions: The overall level of knowledge towards reproductive health among adolescents was found low. However, levels of attitude towards different reproductive health components were found favorable. Only 42.1% of the respondents were utilized reproductive health services among those who was faced the reproductive health problems within one month which was low coverage of reproductive health services utilization.

Keywords: reproductive health knowledge, reproductive health attitudes, adolescent, service utilization

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Authors: Anant Deogaonkar, Archana Nanoty

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The term civil service plays a vital role in functioning of any government. In today’s modern era of globalization civil services essentially contribute for the success of the good governance system. The civil service in India refers to the body of government officials employed in civil occupations that are neither political nor judicial. The Indian Civil Services were created to foster the idea of unity in diversity with the expectation of giving continuity and change in administration independent of the political scenario and turmoil affecting the country. The civil service is an integral part of administration and the structures of administration to determine the way civil service functions. The concept of good governance necessarily precludes the effective human resource management ensuring the root level reach of the good governance. The serious matter of concern is the element of change. The civil service in general has maintained status quo instead of sweeping changes in social and economic scenario. One may disagree for this but it is a fact on the street that the Indian civil service was not able to deliver up to the expectations of the people and was lacking on the service front. The effective management of human resources at civil service needs to be prioritized and will form a key factor in successful delivery of the desired results may be in minimum duration. This paper focuses on the various ways of effective management of human resources in civil services. It also highlights the importance of improvement in human resource management in civil services with the detailed discussion of positives and negatives if any of the human resource management in civil services.

Keywords: civil services, human resources management, India, governance

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Authors: Mei-Hui Liu

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This paper reports 20 preservice EFL teachers’ learning-to-teach experience when they were engaged in an online project-based practicum implemented on a Cloud Platform. This 10-month study filled in the literature gap by documenting the impact of online project-based instruction on preservice EFL teachers’ professional development. Data analysis showed that the online practicum was regarded as a flexible mechanism offering chances of teaching practices without geographical barriers. Additionally, this project-based practice helped the participants integrate the theories they had learned and further foster them how to create a self-directed online learning environment. Furthermore, these preservice teachers with experiences of technology-enabled practicum showed their motivation to apply technology and online platforms into future instructional practices. Yet, this study uncovered several concerns encountered by these participants during this online field experience. The findings of this study rendered meaning and lessons for teacher educators intending to integrate online practicum into preservice training courses.

Keywords: online teaching practicum, project-based learning, teacher preparation, English language education

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Authors: Thuy Hang Le

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Traditional agroforestry systems are land-use practices still widespread in tropical and subtropical countries, while in Europe have significantly decreased due to land-use intensification, land abandonment, and urbanization. Nevertheless, scientific evidence reveals that traditional agroforestry systems significantly support biodiversity and ecosystem services and may positively contribute to socioeconomic rural regional development. We worked out a review that follows the PRISMA approach and compiled comprehensive information on traditional agroforestry systems in Europe. Based on the differentiation of different land-use systems, also considering the agricultural as well as forestry components, we compiled information regarding current distribution, management (agrodiversity), biodiversity and agrobiodiversity, ecosystem and landscape services, threats, and restoration initiatives. From a total of 3,304 studies that dealt with agroforestry systems in Europe, both “modern” (e.g., buffer strip) and “traditional” (e.g., meadow orchards), we filtered out 158 studies from 35 European countries which represent the basis for in-depth investigation. We found, for example, that the traditional pastoral agroforestry system in the Mediterranean region, the so-called Dehesa, can harbor up to 300 plant species as well as 238 bird species, of which 134 are breeding birds. With regard to carbon storage, the traditional orchard agroforestry system in Germany stocks ranged between 6.5 and 9.8 Mg C ha−1, showing significantly higher values compared to an intensively used grassland with around 3.4 to 6.7 Mg C ha−1. With the remarkably high benefit for biodiversity and ecosystem services provided, the important role and multifunctionality of traditional agroforestry systems in Europe should be acknowledged and promoted.

Keywords: biodiversity, ecosystem services, landscape services, traditional agroforestry systems

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Authors: J. F. Reinoso-Gordo, F. J. Ariza-López, A. Mozas-Calvache, J. L. García-Balboa, S. Eddargani

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The DEMs quality may depend on several factors such as data source, capture method, processing type used to derive them, or the cell size of the DEM. The two most important capture methods to produce regional-sized DEMs are photogrammetry and LiDAR; DEMs covering entire countries have been obtained with these methods. The quality of these DEMs has traditionally been evaluated by the national cartographic agencies through punctual sampling that focused on its vertical component. For this type of evaluation there are standards such as NMAS and ASPRS Positional Accuracy Standards for Digital Geospatial Data. However, it seems more appropriate to carry out this evaluation by means of a method that takes into account the superficial nature of the DEM and, therefore, its sampling is superficial and not punctual. This work is part of the Research Project "Functional Quality of Digital Elevation Models in Engineering" where it is necessary to control the quality of a DEM whose data source is an experimental LiDAR flight with a density of 14 points per square meter to which we call Point Cloud Product (PCpro). In the present work it is described the capture data on the ground and the postprocessing tasks until getting the point cloud that will be used as reference (PCref) to evaluate the PCpro quality. Each PCref consists of a patch 50x50 m size coming from a registration of 4 different scan stations. The area studied was the Spanish region of Navarra that covers an area of 10,391 km2; 30 patches homogeneously distributed were necessary to sample the entire surface. The patches have been captured using a Leica BLK360 terrestrial laser scanner mounted on a pole that reached heights of up to 7 meters; the position of the scanner was inverted so that the characteristic shadow circle does not exist when the scanner is in direct position. To ensure that the accuracy of the PCref is greater than that of the PCpro, the georeferencing of the PCref has been carried out with real-time GNSS, and its accuracy positioning was better than 4 cm; this accuracy is much better than the altimetric mean square error estimated for the PCpro (<15 cm); The kind of DEM of interest is the corresponding to the bare earth, so that it was necessary to apply a filter to eliminate vegetation and auxiliary elements such as poles, tripods, etc. After the postprocessing tasks the PCref is ready to be compared with the PCpro using different techniques: cloud to cloud or after a resampling process DEM to DEM.

Keywords: data quality, DEM, LiDAR, terrestrial laser scanner, accuracy

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Authors: Zeynep Karacor, Rahime Hulya Ozturk

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In recent years, the rise of population density and the problem of aging population took attention to the health expenditures. In Turkey, some regulations and infrastructure changes in health sector have occurred. These changes are called Health Transformation Program. The productivity of health services, patient satisfaction, quality of services are tried to be improved with this program. Some radical changes are applied in Turkish economy in this context. The aim of this paper is to present the effects of Health Transformation Program on health expenditures. In the first part of the paper, some information’s about health system and applications in Turkey are discussed. In the second part, the aims of Health Transformation Program are explained. And in the third part the effects of Health Transformation Program on health expenditures are examined.

Keywords: health transformation program, Turkey, health services, health expenditures

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Authors: Hironori Karachi, Haruka Yamashita

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Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: data science, non-negative matrix factorization, missing data, quality of services

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Authors: Ha Hai Duong, Amnon Levy Livermore, Kankesu Jayanthakumaran, Oleg Yerokhin

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The issues of economic development, the environment and human health have been investigated since 1990s. Previous researchers have found different empirical evidences of the relationship between income and environmental pollution, health as determinant of economic growth, and the effects of income and environmental pollution on health in various regions of the world. This paper concentrates on integrative relationship analysis of GDP, carbon dioxide emissions, and health services and population health in context of Vietnam. We applied the dynamic generalized method of moments (GMM) estimation on datasets of Vietnam’s sixty-three provinces for the years 2000-2010. Our results show the significant positive effect of GDP on emissions and the dependence of population health on emissions and health services. We find the significant relationship between population health and GDP. Additionally, health services are significantly affected by population health and GDP. Finally, the population size too is other important determinant of both emissions and GDP.

Keywords: economic development, emissions, environmental pollution, health

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Authors: Joseph Ippolito, David Megenhardt

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In the United States, displaced workers, the unemployed and those seeking to build additional work skills are provided employment training and job placement services through a system of One-Stop Career Centers that are sponsored by the country’s 593 local Workforce Boards. During the period 2010-2015, these centers served roughly 8 million individuals each year. The quality of services provided at these centers rests upon professional employment specialists who work closely with clients to identify their job interests, to connect them to appropriate training opportunities, to match them with needed supportive social services and to guide them to eventual employment. Despite the crucial role these Employment Specialists play, currently there are no broadly accepted standards that establish what these individuals are expected to do in the workplace, nor are there indicators to assess how well an individual performs these responsibilities. Education Development Center (EDC) and the United Labor Agency (ULA) have partnered to create a foundation upon which curriculum can be developed that addresses the skills, knowledge and behaviors that Employment Specialists must master in order to serve their clients effectively. EDC is a non-profit, education research and development organization that designs, implements, and evaluates programs to improve education, health and economic opportunity worldwide. ULA is the social action arm of organized labor in Greater Cleveland, Ohio. ULA currently operates One-Stop Career Centers in both Cleveland and Pittsburgh, Pennsylvania. This case study outlines efforts taken to create standards that define the work of Employment Specialists and to establish indicators that can guide assessment of work performance. The methodology involved in the study has engaged a panel of expert Employment Specialists in rigorous, structured dialogues that analyze and identify the characteristics that enable them to be effective in their jobs. It has also drawn upon and integrated reviews of the panel’s work by more than 100 other Employment Specialists across the country. The results of this process are two documents that provide resources for developing training curriculum for future Employment Specialists, namely: an occupational profile of an Employment Specialist that offers a detailed articulation of the skills, knowledge and behaviors that enable individuals to be successful at this job, and; a collection of performance based indicators, aligned to the profile, which illustrate what the work responsibilities of an Employment Specialist 'look like' a four levels of effectiveness ranging from novice to expert. The method of occupational analysis used by the study has application across a broad number of fields.

Keywords: assessment, employability, job standards, workforce development

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Authors: Mohamed Hashelaf, Ahmed Al-Osdody

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In this paper, we focused our efforts on one of the vaguest subjects in astrophysics that is the formation and evolution of the universe until the arrival of humans. Through an in-depth exploration of the origins of the universe, understanding what has happened since the Big Bang until now and checking the history of creation, we can answer questions about the future of life, the possibility of its existence elsewhere in the universe and to be able to understand how we came, what our role in the circle of life is and what the future of our development will be. Here is where we used systematic steps that allowed us first and foremost to identify the reason behind the big bang itself that formed a large cloud of cosmic dust. Then after a period of time from the expansion of the universe and its coolness, the initial molecules of gases from the cosmic cloud began to condense, forming a very dense field of gravity that after millions of years led to the formation of stars, galaxies, even earth and the else planets. Finally, it became clear before us that after the earth has formed, the existence of liquid water made it possible for life to form, starting from the bacteria all the way until the appearance of the humans that we know today. But it does not stop here. If we look and contemplate in ourselves as humans, we will understand that the universe is inside us and that’s what makes us exceptional. All of this means that just as life on earth was created, it could have been on other planets as well. It also means that we are the universe’s key to understand itself.

Keywords: Big Bang, cosmic dust, primary elements, universe

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Authors: Wan-I Lee, Nelio Mendoza Figueredo

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The impact of COVID-19 has a significant effect on all sectors of society globally. Health information technology (HIT) has become an effective health strategy in this age of distancing. In this regard, Mobile Health (mHealth) plays a critical role in managing patient and provider workflows during the COVID-19 pandemic. Therefore, the users' perception of service quality about mHealth services plays a significant role in shaping confidence and subsequent behaviors regarding the mHealth users' intention of use. This study's objective was to explore levels of user attributes analyzed by a qualitative method of how health practitioners and patients are satisfied or dissatisfied with using mHealth services; and analyzed the users' intention in the context of Taiwan during the COVID-19 pandemic. This research explores the experienced usability of a mHealth services during the Covid-19 pandemic. This study uses qualitative methods that include in-depth and semi-structured interviews that investigate participants' perceptions and experiences and the meanings they attribute to them. The five cases consisted of health practitioners, clinic staff, and patients' experiences using mHealth services. This study encourages participants to discuss issues related to the research question by asking open-ended questions, usually in one-to-one interviews. The findings show the positive and negative attributes of mHealth service quality. Hence, the significant importance of patients' and health practitioners' issues on several dimensions of perceived service quality is system quality, information quality, and interaction quality. A concept map for perceptions regards to emergency uses' intention of mHealth services process is depicted. The findings revealed that users pay more attention to "Medical care", "ease of use" and "utilitarian benefits" and have less importance for "Admissions and Convenience" and "Social influence". To improve mHealth services, the mHealth providers and health practitioners should better manage users' experiences to enhance mHealth services. This research contributes to the understanding of service quality issues in mHealth services during the COVID-19 pandemic.

Keywords: COVID-19, mobile health, service quality, use intention

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Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

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Authors: Till Gramberg, Max Kellner, Erwin Gross

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This paper presents a comprehensive investigation into the topic of smart services and IIoT-Platforms, focusing on their selection and prioritization in manufacturing organizations. First, a literature review is conducted to provide a basic understanding of the current state of research in the area of smart services. Based on discussed and established definitions, a definition approach for this paper is developed. In addition, value propositions for smart services are identified based on the literature and expert interviews. Furthermore, the general requirements for the provision of smart services are presented. Subsequently, existing approaches for the selection and development of smart services are identified and described. In order to determine the requirements for the selection of smart services, expert opinions from successful companies that have already implemented smart services are collected through semi-structured interviews. Based on the results, criteria for the evaluation of existing methods are derived. The existing methods are then evaluated according to the identified criteria. Furthermore, a novel method for the selection of smart services in manufacturing companies is developed, taking into account the identified criteria and the existing approaches. The developed concept for the method is verified in expert interviews. The method includes a collection of relevant smart services identified in the literature. The actual relevance of the use cases in the industrial environment was validated in an online survey. The required data and sensors are assigned to the smart service use cases. The value proposition of the use cases is evaluated in an expert workshop using different indicators. Based on this, a comparison is made between the identified value proposition and the required data, leading to a prioritization process. The prioritization process follows an established procedure for evaluating technical decision-making processes. In addition to the technical requirements, the prioritization process includes other evaluation criteria such as the economic benefit, the conformity of the new service offering with the company strategy, or the customer retention enabled by the smart service. Finally, the method is applied and validated in an industrial environment. The results of these experiments are critically reflected upon and an outlook on future developments in the area of smart services is given. This research contributes to a deeper understanding of the selection and prioritization process as well as the technical considerations associated with smart service implementation in manufacturing organizations. The proposed method serves as a valuable guide for decision makers, helping them to effectively select the most appropriate smart services for their specific organizational needs.

Keywords: smart services, IIoT, industrie 4.0, IIoT-platform, big data

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Authors: Md. Rashed Aalm, Md. Nuruzzaman Khan, Yothin Sawangdee

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Background: Around 47% of the total pregnancies are unintended in Bangladesh, which lead to several adverse consequences, including maternal and child mortality. Use of menstrual regulation (MR) can help women to reduce unintended pregnancy related adverse consequences. We explored the prevalence and determinants of MR services among ever-married women in Bangladesh. Methods: Total of 14,346 ever-married women data were analysed from the 2017 Bangladesh Demographic and Health Survey. Our study variable was use or non-use of MR services. Individual, household, and community level factors were the explanatory factors. Multilevel mixed-effect Poisson regression model was used to determine the factors associated with MR services in Bangladesh. Results: Nearly 7% of the total women in Bangladesh use MR services. Use of MR services was found higher among women who were aged 20-30 ages (IRR 1.60, 95% CI: 1.17–2.17), who were overweight (IRR 1.43, 95% CI: 1.13–1.81), had at least 1 child (IRR 2.97, 95% CI: 2.34– 3.77) or > 2 children (IRR 3.22, 95% CI: 2.45–4.20), and the birth preceding birth interval was(2 – 4) years (IRR 1.56, 95% CI: 1.13–2.15). Around 1.39 times (95% CI: 1.11–1.73) higher likelihood of MR was found among women whose husbands were engage with business. At the community level, MR service was found lower among the women who resided in the community with higherilliteracy (IRR 0.67, 95% CI: 0.42–0.96) and the Mymensingh division (IRR 0.39, 95% CI: 0.31–0.91). Conclusion: Use of MR service is comparatively low, which indicate a significant proportion of unintended pregnancy continued toward life-birth. This could be responsible for higher adverse maternal and child health outcomes in Bangladesh. Initiatives should be taken to ensure MR services is available when women need this service.

Keywords: menstrual regulation, pattern, risk, maternal health, Bangladesh

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Authors: Aisha F. Bushager

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Today we are more exposed than ever to cyber threats and attacks at personal, community, organizational, national, and international levels. More aspects of our lives are operating on computer networks simply because we are living in the fifth domain, which is called the Cyberspace. One of the most sensitive areas that are vulnerable to cyber threats and attacks is the Electronic Banking (e-Banking) area, where the banking sector is providing online banking services to its clients. To be able to obtain the clients trust and encourage them to practice e-Banking, also, to maintain the services provided by the banks and ensure safety, cyber security and risks control should be given a high priority in the e-banking area. The aim of the study is to carry out risk assessment on the e-banking services and determine the cyber threats, cyber attacks, and vulnerabilities that are facing the e-banking area specifically in the Kingdom of Bahrain. To collect relevant data, structured interviews were taken place with e-banking experts in different banks. Then, collected data where used as in input to the risk management framework provided by the National Institute of Standards and Technology (NIST), which was the model used in the study to assess the risks associated with e-banking services. The findings of the study showed that the cyber threats are commonly human errors, technical software or hardware failure, and hackers, on the other hand, the most common attacks facing the e-banking sector were phishing, malware attacks, and denial-of-service. The risks associated with the e-banking services were around the moderate level, however, more controls and countermeasures must be applied to maintain the moderate level of risks. The results of the study will help banks discover their vulnerabilities and maintain their online services, in addition, it will enhance the cyber security and contribute to the management and control of risks that are facing the e-banking sector.

Keywords: cyber security, e-banking, risk assessment, threats identification

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Authors: Radul Shishkov, Orlin Davchev

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

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

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Authors: Mona Almanasef, Dalia Almaghaslah, Geetha Kandasamy, Rajalakshimi Vasudevan, Sadia Batool

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Background: Community pharmacists are one of the most accessible healthcare practitioners worldwide and their services are used by a large proportion of the population. Expanding the roles of community pharmacists could contribute to reducing pressure on general health practice and other areas of health services. This research aimed to evaluate the contribution of community pharmacists in the provision of public health services and to investigate the perceived barriers to the provision of these services in Saudi Arabia. Materials and Methods: This study followed a cross-sectional design using an online anonymous self-administered questionnaire. The study took place in the Asir region, Saudi Arabia, between September 2019 and February 2020. A convenience sampling strategy was used to select and recruit the study participants. The questionnaire was adapted from previous research and involved three sections: demographics, involvement in public health services and barriers to practicing public health roles. Results: The total number of respondents was 193. The proportion of respondents who reported that they were “very involved” or “involved” in each service was 61.7% for weight management, 60.6% for sexual health, 57.5% for healthy eating, 53.4% for physical activity promotion, 51.3% for dental health, 46.1% for smoking cessation, 39.4% for screening for diabetes, 35.7% for screening for hypertension, 31.1% for alcohol dependence and drug misuse counseling, 30.6% for screening for dyslipidaemia, and 21.8% for vaccination and immunization. Most of the barriers in the current research were rated as having low relevance to the provision of public health services. Conclusion: Findings in the current research suggest that community pharmacists in the Asir region have varying levels of involvement in public health roles. Further research needs to be undertaken to understand the barriers to the provision of public health services and what strategies would be beneficial for enhancing the public health role of community pharmacists in Saudi Arabia.

Keywords: community pharmacist, public health, Asir region, Saudi Arabia

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Authors: Ruo-Qian Wang

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Open-source CFD has become increasingly popular and promising. The recent progress in multiphase flow enables new CFD applications, which provides an economic and flexible research tool for complex flow problems. Our numerical study using four-way coupling Euler-Lagrangian Large-Eddy Simulations to resolve particle cloud dynamics with OpenFOAM and CFDEM will be introduced: The fractioned Navier-Stokes equations are numerically solved for fluid phase motion, solid phase motion is addressed by Lagrangian tracking for every single particle, and total momentum is conserved by fluid-solid inter-phase coupling. The grid convergence test was performed, which proves the current resolution of the mesh is appropriate. Then, we validated the code by comparing numerical results with experiments in terms of particle cloud settlement and growth. A good comparison was obtained showing reliability of the present numerical schemes. The time and height at phase separations were defined and analyzed for a variety of initial release conditions. Empirical formulas were drawn to fit the results.

Keywords: four-way coupling, dredging, land reclamation, multiphase flows, oil spill

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Authors: Soma Sarkar

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A number of authors have recently argued that there are strong links between ecosystem services and sustainable development, particularly development efforts that aim to reduce rural poverty. We see two distinct routes by which the science of ecosystem services can contribute to both nature conservation and sustainable development. First, a thorough accounting of ecosystem services and a better understanding of how and at what rates ecosystems produce these services can be used to motivate payment for nature conservation. At least part of the generated funds can be used to compensate people who suffer lost economic opportunities to protect these services. For example, if rural poor are asked to take actions that reduce farm productivity to protect and regulate water supply, those farmers could be compensated for the reduced productivity they experience. When the benefits of natural ecosystems are explicitly quantified, those benefits are more valued both by the people who directly interact with the ecosystems and the governmental and other agencies that would have to pay for substitute sources of these services if these ecosystems should become impaired. Appreciating the value of ecosystem services can motivate increased conservation investment to prevent having to pay for substitutes later. This approach could be characterized as a ‘‘government investment’’ approach because the payments will generally come from beneficiaries outside of the local area, and a governmental or other agency is typically responsible for collecting and redistributing the funds. Second, a focus on the conservation of ecosystem services could improve the success of projects that attempt to both conserve nature and improve the welfare of the rural poor by fostering markets for the goods and services that local people produce or extract from ecosystems. These projects could be characterized as more ‘‘community based’’ because the goal is to foster the more organic, or grassroots, development of cottage industries, such as ecotourism, or the production of non-timber forest products, that are enhanced by better protection of local ecosystems. Using this framework, we discuss the factors that may have contributed to failure or success for several projects in the district of Purulia, one of the most backward districts of India and inhabited by indigenous group of people. A large majority of people in this district are dependent on environment based incomes for their sustenance. The erosion of natural resource base owing to poor governance in the district has led to the reductions in the household incomes of these people. The scale of our analysis is local or project level. The plight of poor has little to do with the production functions of ecosystem services. But for rural poor, at the local level, the status of ecosystem services can make a big difference in their daily lives.

Keywords: ecosystem services, governance, rural poor, community based natural resource management

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Authors: J.Pozuelo-Muñoz, E. Cascarosa-Salillas, C. Rodríguez-Casals, A. de Echave, E. Terrado-Sieso

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This study focuses on the development, implementation, and evaluation of an instructional sequence aimed at 16–17-year-old students, involving the design and use of a cloud chamber—a device that allows observation of subatomic particles. The research addresses the limited presence of particle physics in Spanish secondary and high school curricula, a gap that restricts students' learning of advanced physics concepts and diminishes engagement with complex scientific topics. The primary goal of this project is to introduce particle physics in the classroom through a practical, interdisciplinary methodology that promotes autonomous learning and critical thinking. The methodology is framed within Design-Based Research (DBR), an approach that enables iterative and pragmatic development of educational resources. The research proceeded in several phases, beginning with the design of an experimental teaching sequence, followed by its implementation in high school classrooms. This sequence was evaluated, redesigned, and reimplemented with the aim of enhancing students’ understanding and skills related to designing and using particle detection instruments. The instructional sequence was divided into four stages: introduction to the activity, research and design of cloud chamber prototypes, observation of particle tracks, and analysis of collected data. In the initial stage, students were introduced to the fundamentals of the activity and provided with bibliographic resources to conduct autonomous research on cloud chamber functioning principles. During the design stage, students sourced materials and constructed their own prototypes, stimulating creativity and understanding of physics concepts like thermodynamics and material properties. The third stage focused on observing subatomic particles, where students recorded and analyzed the tracks generated in their chambers. Finally, critical reflection was encouraged regarding the instrument's operation and the nature of the particles observed. The results show that designing the cloud chamber motivates students and actively engages them in the learning process. Additionally, the use of this device introduces advanced scientific topics beyond particle physics, promoting a broader understanding of science. The study’s conclusions emphasize the need to provide students with ample time and space to thoroughly understand the role of materials and physical conditions in the functioning of their prototypes and to encourage critical analysis of the obtained data. This project not only highlights the importance of interdisciplinarity in science education but also provides a practical framework for teachers to adapt complex concepts for educational contexts where these topics are often absent.

Keywords: cloud chamber, particle physics, secondary education, instructional design, design-based research, STEM

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Nusrat T. Chowdhury, M. F. Baki, A. Azab

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The production planning problem is concerned with specifying the optimal quantities to produce in order to meet the demand for a prespecified planning horizon with the least possible expenditure. Making the right decisions in production planning will affect directly the performance and productivity of a manufacturing firm, which is important for its ability to compete in the market. Therefore, developing and improving solution procedures for production planning problems is very significant. In this paper, we develop a Dantzig-Wolfe decomposition of a multi-item hierarchical production planning problem with capacity constraint and present a column generation approach to solve the problem. The original Mixed Integer Linear Programming model of the problem is decomposed item by item into a master problem and a number of subproblems. The capacity constraint is considered as the linking constraint between the master problem and the subproblems. The subproblems are solved using the dynamic programming approach. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any kind of infeasibility that arises while solving the problem. We compare the computational performance of the developed solution approach against the state-of-the-art heuristic procedure available in the literature. The results show that the proposed heuristic-based decomposition approach improves the solution quality by 20% as compared to the literature.

Keywords: inventory, multi-level capacitated lot-sizing, emission control, setup carryover

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Authors: Bing Li, Zhi Li, Yilong Yang

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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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Authors: Ademola Ibukunolu Atanda, Gbenga Nathaniel Adeola

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The study examined awareness of child rights as a determinant of effective student personnel services in public secondary schools in Southwestern Nigeria. It was survey research. The sample comprised 433 teachers, 137 school administrators, and 968 students who were drawn by simple random sampling techniques. The respondents were given copies of questionnaires tagged “school administrator/teacher’s awareness of child’s rights and student personnel services elements inventory.” Key Informant Interview (KII) was also employed. The data were analysed using frequency count, percentages, weighted average, grand mean, standard deviation, and Pearson Product Moment Correlation, while KII was qualitatively analysed. The findings of the study revealed that public secondary school administrator awareness of child rights was at a moderate level, but the awareness of child rights was low among the teachers. The study equally revealed that student personnel services are moderately provided in public secondary schools in Southwestern Nigeria, but security remains a major challenge. It was also found that there was a significant relationship between awareness of child rights and effective student personnel services. It was therefore recommended, based on the findings, that attention should be given to heightening awareness of child rights among public secondary school administrators and teachers for effective student personnel services. Copies of the Child Right Act 2003 should also be made available in all public secondary schools in Southwestern Nigeria, as the study revealed that the documents were not available.

Keywords: student personnel, child right, administrator awareness, practice of child right

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Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

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