8,700 research outputs found

    Jordan and the Refugee Crisis: Impact on the Host Nation

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    This thesis investigated the effect of refugee populations of the culture and society of Jordan with emphasis placed on Jordanian social acceptance of refugee populations as measured through intermarriage. Data was collected quantitatively from 100 female respondents at each of three Jordanian universities regarding values and acceptance of refugee populations as potential spouses using a simple survey. Data was also collected qualitatively by semi-structured interviews with select individuals to provide context. Universities were geographically diverse to allow observation of regional disparities in response. Whitney Mann U test was used to compare significance of answers across universities. Survey data showed that Jordanian acceptance of refugees through intermarriage was low unless they had Jordanian citizenship. There were also indicators that wealth may play a greater role in acceptance than ethnic origin or traditions. I found while societal acceptance of refugees may be growing, especially in the urban areas, governmental restrictions on citizenship, while understandable on the pragmatic level, will continue to create a hurdle for integration. Other factors that affect integration of refugees in Jordan are also discussed

    Inovação na diplomacia cultural: o caso da China

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    This study focuses on the innovation of China’s cultural diplomacy (CCD) by means of the Confucius Institute (CI). The main contents revolve around the following research goals: 1) to understand the strategic framework and practical path of CCD, and to clarify the context of its inheritance and innovation; 2) to analyze whether the CI, epitomized as a crucial innovation of CCD, has improved China’s national image in Portuguese-speaking countries (PSCs) and enhanced the attraction and international competitiveness of Chinese culture; and 3) to explore how China can better formulate its CD strategy in line with the exigencies of the modern era. The study combines the methods of literature review, case study, and questionnaire research to explore the topics from different perspectives to strengthen the scientific nature of the research results. In addition to the introduction and conclusion, the thesis is divided into five chapters. Chapter 1 discusses the connotation and value of CD. Chapter 2 expounds the development and innovation of CCD. Chapter 3 systematically summarizes China’s cultural interaction in its diplomatic process with PSCs. Chapter 4 elaborates on the CI in terms of its operation mode and diplomatic means. Chapter 5 forms the core of the study and involves empirical analysis of case-study and questionnaire data. It aims to investigate the functions, public image, influence, and practical means of CIs in the process of CD. Major findings indicate that CIs in PSCs have achieved ideal social feedback and play a positive role in shaping the image of China. However, according to the different continents where CIs are located, the survey results show distinct characteristics which are closely related to China’s different foreign policies towards Latin America, Europe, and Africa and are determined by the historical experiences and national conditions of the various countries. The future task for CCD is to clarify China’s institutional roots and the cultural genes behind its development by using cultural exchanges and China’s fluid culture to convey a message of China’s pursuit of peace, development, and cooperation.Este estudo tem como foco a inovação da Diplomacia Cultural da China (DCC) através do Instituto Confúcio (IC). Os principais conteúdos giram em torno dos seguintes objetivos de investigação: 1) compreender o enquadramento estratégico e o percurso prático da Diplomacia Cultural da China e clarificar o contexto da sua herança e inovação; 2) analisar se o IC, exemplo de inovação crucial da Diplomacia Cultural da China, melhorou a imagem nacional da China nos Países de Língua Oficial Portuguesa (PALOP) e aumentou a atração e competitividade internacional da cultura chinesa; e 3) explorar como a China pode formular melhor a sua estratégia de Diplomacia Cultural, de acordo com as exigências da era moderna. O estudo combina os métodos de revisão de literatura, estudo de caso e pesquisa de questionário para explorar os tópicos de diferentes perspetivas com o objetivo de fortalecer a natureza científica dos resultados de investigação. Além da introdução e da conclusão, a tese está dividida em cinco capítulos. O Capítulo 1 discute a conotação e o valor de Diplomacia Cultural (DC). O Capítulo 2 expõe o desenvolvimento e a inovação da Diplomacia Cultural da China (DCC). O Capítulo 3 resume sistematicamente a interação cultural da China no seu processo diplomático com os Países de Língua Oficial Portuguesa (PALOP). O Capítulo 4 discorre sobre o papel do IC em termos do seu modo de operar e dos seus meios diplomáticos. O Capítulo 5 constitui o núcleo da tese e envolve a análise empírica dos dados do estudo de caso e do questionário. Tem como objetivo investigar as funções, a imagem pública, a influência e os meios práticos dos IC no processo de Diplomacia Cultural (DC). As principais descobertas indicam que os IC nos PALOP alcançaram o feedback social ideal e desempenham um papel positivo na formação da imagem da China. No entanto, de acordo com os diferentes continentes onde os IC estão situados, os resultados da pesquisa apresentam caraterísticas distintas que estão intimamente relacionadas com as diferentes políticas externas da China para a América Latina, a Europa e a África e são determinadas pelas experiências históricas e pelas condições nacionais dos vários países. A futura tarefa da Diplomacia Cultural da China (DCC) será a de esclarecer as raízes institucionais da China e os genes culturais por trás do seu desenvolvimento, usando intercâmbios culturais e a cultura fluida da China para transmitir uma mensagem de busca de paz, de desenvolvimento e de cooperação por parte da China.Programa Doutoral em Políticas Pública

    Digitalization and Development

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    This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents. The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term. This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    The Application of Data Analytics Technologies for the Predictive Maintenance of Industrial Facilities in Internet of Things (IoT) Environments

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    In industrial production environments, the maintenance of equipment has a decisive influence on costs and on the plannability of production capacities. In particular, unplanned failures during production times cause high costs, unplanned downtimes and possibly additional collateral damage. Predictive Maintenance starts here and tries to predict a possible failure and its cause so early that its prevention can be prepared and carried out in time. In order to be able to predict malfunctions and failures, the industrial plant with its characteristics, as well as wear and ageing processes, must be modelled. Such modelling can be done by replicating its physical properties. However, this is very complex and requires enormous expert knowledge about the plant and about wear and ageing processes of each individual component. Neural networks and machine learning make it possible to train such models using data and offer an alternative, especially when very complex and non-linear behaviour is evident. In order for models to make predictions, as much data as possible about the condition of a plant and its environment and production planning data is needed. In Industrial Internet of Things (IIoT) environments, the amount of available data is constantly increasing. Intelligent sensors and highly interconnected production facilities produce a steady stream of data. The sheer volume of data, but also the steady stream in which data is transmitted, place high demands on the data processing systems. If a participating system wants to perform live analyses on the incoming data streams, it must be able to process the incoming data at least as fast as the continuous data stream delivers it. If this is not the case, the system falls further and further behind in processing and thus in its analyses. This also applies to Predictive Maintenance systems, especially if they use complex and computationally intensive machine learning models. If sufficiently scalable hardware resources are available, this may not be a problem at first. However, if this is not the case or if the processing takes place on decentralised units with limited hardware resources (e.g. edge devices), the runtime behaviour and resource requirements of the type of neural network used can become an important criterion. This thesis addresses Predictive Maintenance systems in IIoT environments using neural networks and Deep Learning, where the runtime behaviour and the resource requirements are relevant. The question is whether it is possible to achieve better runtimes with similarly result quality using a new type of neural network. The focus is on reducing the complexity of the network and improving its parallelisability. Inspired by projects in which complexity was distributed to less complex neural subnetworks by upstream measures, two hypotheses presented in this thesis emerged: a) the distribution of complexity into simpler subnetworks leads to faster processing overall, despite the overhead this creates, and b) if a neural cell has a deeper internal structure, this leads to a less complex network. Within the framework of a qualitative study, an overall impression of Predictive Maintenance applications in IIoT environments using neural networks was developed. Based on the findings, a novel model layout was developed named Sliced Long Short-Term Memory Neural Network (SlicedLSTM). The SlicedLSTM implements the assumptions made in the aforementioned hypotheses in its inner model architecture. Within the framework of a quantitative study, the runtime behaviour of the SlicedLSTM was compared with that of a reference model in the form of laboratory tests. The study uses synthetically generated data from a NASA project to predict failures of modules of aircraft gas turbines. The dataset contains 1,414 multivariate time series with 104,897 samples of test data and 160,360 samples of training data. As a result, it could be proven for the specific application and the data used that the SlicedLSTM delivers faster processing times with similar result accuracy and thus clearly outperforms the reference model in this respect. The hypotheses about the influence of complexity in the internal structure of the neuronal cells were confirmed by the study carried out in the context of this thesis

    Towards A Practical High-Assurance Systems Programming Language

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    Writing correct and performant low-level systems code is a notoriously demanding job, even for experienced developers. To make the matter worse, formally reasoning about their correctness properties introduces yet another level of complexity to the task. It requires considerable expertise in both systems programming and formal verification. The development can be extremely costly due to the sheer complexity of the systems and the nuances in them, if not assisted with appropriate tools that provide abstraction and automation. Cogent is designed to alleviate the burden on developers when writing and verifying systems code. It is a high-level functional language with a certifying compiler, which automatically proves the correctness of the compiled code and also provides a purely functional abstraction of the low-level program to the developer. Equational reasoning techniques can then be used to prove functional correctness properties of the program on top of this abstract semantics, which is notably less laborious than directly verifying the C code. To make Cogent a more approachable and effective tool for developing real-world systems, we further strengthen the framework by extending the core language and its ecosystem. Specifically, we enrich the language to allow users to control the memory representation of algebraic data types, while retaining the automatic proof with a data layout refinement calculus. We repurpose existing tools in a novel way and develop an intuitive foreign function interface, which provides users a seamless experience when using Cogent in conjunction with native C. We augment the Cogent ecosystem with a property-based testing framework, which helps developers better understand the impact formal verification has on their programs and enables a progressive approach to producing high-assurance systems. Finally we explore refinement type systems, which we plan to incorporate into Cogent for more expressiveness and better integration of systems programmers with the verification process

    Comparative Multiple Case Study into the Teaching of Problem-Solving Competence in Lebanese Middle Schools

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    This multiple case study investigates how problem-solving competence is integrated into teaching practices in private schools in Lebanon. Its purpose is to compare instructional approaches to problem-solving across three different programs: the American (Common Core State Standards and New Generation Science Standards), French (Socle Commun de Connaissances, de Compétences et de Culture), and Lebanese with a focus on middle school (grades 7, 8, and 9). The project was conducted in nine schools equally distributed among three categories based on the programs they offered: category 1 schools offered the Lebanese program, category 2 the French and Lebanese programs, and category 3 the American and Lebanese programs. Each school was treated as a separate case. Structured observation data were collected using observation logs that focused on lesson objectives and specific cognitive problem-solving processes. The two logs were created based on a document review of the requirements for the three programs. Structured observations were followed by semi-structured interviews that were conducted to explore teachers' beliefs and understandings of problem-solving competence. The comparative analysis of within-category structured observations revealed an instruction ranging from teacher-led practices, particularly in category 1 schools, to more student-centered approaches in categories 2 and 3. The cross-category analysis showed a reliance on cognitive processes primarily promoting exploration, understanding, and demonstrating understanding, with less emphasis on planning and executing, monitoring and reflecting, thus uncovering a weakness in addressing these processes. The findings of the post-observation semi-structured interviews disclosed a range of definitions of problem-solving competence prevalent amongst teachers with clear divergences across the three school categories. This research is unique in that it compares problem-solving teaching approaches across three different programs and explores underlying teachers' beliefs and understandings of problem-solving competence in the Lebanese context. It is hoped that this project will inform curriculum developers about future directions and much-anticipated reforms of the Lebanese program and practitioners about areas that need to be addressed to further improve the teaching of problem-solving competence
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