872 research outputs found

    Автоматизация ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ аэронавигационной ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ Π½Π° основС ΠΌΠ½ΠΎΠ³ΠΎΠ°Π³Π΅Π½Ρ‚Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ

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    Progress in the development of computer engineering provides an opportunity to address a wider variety of challenges using computer software systems. The task of automatic aeronautical navigation information processing is referred to the number of such issues. This stipulates the necessity to adopt new approaches to design and develop similar systems. One of these approaches is based on the application of the collective activity idea of a set of agents – multi-agent technologies. In this regard, the purpose of the article is to consider the features of the automated aeronautical navigation information processing implementation on the basis of multi-agent technologies. To achieve this goal, the problem-structural methodology of hybrid systems synthesis, which allows us to create self-organizing models, was selected. Each element of which develops, obtaining data and knowledge from other elements. In the research process, a formal definition of the multi-agent system of automatic aeronautical information processing is presented, which involves a set of agents, environment of agent functioning, a set of permissible relations between agents, description of rules for forming a network of agents, a set of individual and joint actions, communication interactions, behavior and actions strategies, a possibility of system evolution. Furthermore, an emphasis is placed on the description of each agent. For this purpose, the authors propose to use four elements: a set of variables, inputs and outputs, an autonomous technique that performs appropriate changes over a set of variables. As agents, the paper comes up with the idea to use the following: Pilots Notification Agent, Preflight Information Bulletin Agent, Data Generation Agent, Aviation Processes Agent, Aviation Database Generation Agent, Aeronautical Maps Creation Agent, Aeronautical Data Set Export/Import Agent, Publications and References Agent. In addition, the article presents the multi-agent system diagram of automated aeronautical information processing and describes in detail processing an application in the agent using the mathematical expression. The results, obtained in the course of investigations, can be used to improve the effectiveness of the analytical component in the structure of the system to form the direct and reverse coordination relationship while solving aerial navigation problems.ΠŸΡ€ΠΎΠ³Ρ€Π΅ΡΡ Π² Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠΈ срСдств Π²Ρ‹Ρ‡ΠΈΡΠ»ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠΉ Ρ‚Π΅Ρ…Π½ΠΈΠΊΠΈ обСспСчиваСт Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ Ρ€Π΅ΡˆΠ°Ρ‚ΡŒ всС Π±ΠΎΠ»Π΅Π΅ ΡˆΠΈΡ€ΠΎΠΊΠΈΠΉ класс Π·Π°Π΄Π°Ρ‡ с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ½Ρ‹Ρ… систСм, ΠΊ числу Ρ‚Π°ΠΊΠΈΡ… Π·Π°Π΄Π°Ρ‡ относится Π·Π°Π΄Π°Ρ‡Π° автоматичСской ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ аэронавигационной ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ. Π­Ρ‚ΠΎ обусловливаСт Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎΡΡ‚ΡŒ использования Π½ΠΎΠ²Ρ‹Ρ… ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ΠΎΠ² ΠΊ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΡŽ ΠΈ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠ΅ Ρ‚Π°ΠΊΠΈΡ… систСм. Один ΠΈΠ· этих ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ΠΎΠ² основан Π½Π° ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠΈ ΠΈΠ΄Π΅ΠΈ ΠΊΠΎΠ»Π»Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΠΉ Π΄Π΅ΡΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ совокупности Π°Π³Π΅Π½Ρ‚ΠΎΠ² – ΠΌΠ½ΠΎΠ³ΠΎΠ°Π³Π΅Π½Ρ‚Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ. Π’ связи с этим Ρ†Π΅Π»ΡŒ ΡΡ‚Π°Ρ‚ΡŒΠΈ Π·Π°ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ΡΡ Π² рассмотрСнии особСнностСй Ρ€Π΅Π°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ Π°Π²Ρ‚ΠΎΠΌΠ°Ρ‚ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ аэронавигационной ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ Π½Π° основС ΠΌΠ½ΠΎΠ³ΠΎΠ°Π³Π΅Π½Ρ‚Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ. Для достиТСния ΠΎΠ±ΠΎΠ·Π½Π°Ρ‡Π΅Π½Π½ΠΎΠΉ Ρ†Π΅Π»ΠΈ Π±Ρ‹Π»Π° Π²Ρ‹Π±Ρ€Π°Π½Π° ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΠ½ΠΎ-структурная мСтодология синтСза Π³ΠΈΠ±Ρ€ΠΈΠ΄Π½Ρ‹Ρ… систСм, которая позволяСт ΡΠΎΠ·Π΄Π°Π²Π°Ρ‚ΡŒ ΡΠ°ΠΌΠΎΠΎΡ€Π³Π°Π½ΠΈΠ·ΡƒΡŽΡ‰ΠΈΠ΅ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ, ΠΊΠ°ΠΆΠ΄Ρ‹ΠΉ элСмСнт ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… развиваСтся, получая Π΄Π°Π½Π½Ρ‹Π΅ ΠΈ знания ΠΎΡ‚ Π΄Ρ€ΡƒΠ³ΠΈΡ… элСмСнтов. Π’ процСссС исслСдования прСдставлСно Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½ΠΎΠ΅ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠ³ΠΎΠ°Π³Π΅Π½Ρ‚Π½ΠΎΠΉ систСмы автоматичСской ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ аэронавигационной ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ, ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠ΅ Π²ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ Π² сСбя мноТСство Π°Π³Π΅Π½Ρ‚ΠΎΠ²; срСду функционирования Π°Π³Π΅Π½Ρ‚ΠΎΠ²; ΡΠΎΠ²ΠΎΠΊΡƒΠΏΠ½ΠΎΡΡ‚ΡŒ допустимых Π²Π·Π°ΠΈΠΌΠΎΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠΉ ΠΌΠ΅ΠΆΠ΄Ρƒ Π°Π³Π΅Π½Ρ‚Π°ΠΌΠΈ; описаниС ΠΏΡ€Π°Π²ΠΈΠ» формирования сСти Π°Π³Π΅Π½Ρ‚ΠΎΠ²; Π½Π°Π±ΠΎΡ€ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡƒΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΈ совмСстных дСйствий, ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… взаимодСйствий, стратСгий повСдСния ΠΈ поступков; Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ ΡΠ²ΠΎΠ»ΡŽΡ†ΠΈΠΈ систСмы. Π’Π°ΠΊΠΆΠ΅ Π΄Π΅Ρ‚Π°Π»ΡŒΠ½ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΡƒΠ΄Π΅Π»Π΅Π½ΠΎ описанию ΠΊΠ°ΠΆΠ΄ΠΎΠ³ΠΎ Π°Π³Π΅Π½Ρ‚Π°, для Ρ‡Π΅Π³ΠΎ Π°Π²Ρ‚ΠΎΡ€Π°ΠΌΠΈ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒ Ρ‡Π΅Ρ‚Ρ‹Ρ€Π΅ элСмСнта: мноТСство ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹Ρ…, Π²Ρ…ΠΎΠ΄Ρ‹ ΠΈ Π²Ρ‹Ρ…ΠΎΠ΄Ρ‹, Π°Π²Ρ‚ΠΎΠ½ΠΎΠΌΠ½Ρ‹ΠΉ ΠΌΠ΅Ρ‚ΠΎΠ΄, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΉ выполняСт ΡΠΎΠΎΡ‚Π²Π΅Ρ‚ΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠ΅ измСнСния Π½Π°Π΄ мноТСством ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹Ρ…. Π’ качСствС Π°Π³Π΅Π½Ρ‚ΠΎΠ² ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒ ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΠ΅: Π°Π³Π΅Π½Ρ‚ увСдомлСния для Π»Π΅Ρ‚Ρ‡ΠΈΠΊΠΎΠ², Π°Π³Π΅Π½Ρ‚ ΠΏΡ€Π΅Π΄ΠΏΠΎΠ»Π΅Ρ‚Π½Ρ‹Ρ… ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Π±ΡŽΠ»Π»Π΅Ρ‚Π΅Π½Π΅ΠΉ, Π°Π³Π΅Π½Ρ‚ создания Π΄Π°Π½Π½Ρ‹Ρ…, Π°Π³Π΅Π½Ρ‚ Π°Π²ΠΈΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… процСссов, Π°Π³Π΅Π½Ρ‚ формирования Π°Π²ΠΈΠ°Ρ†ΠΈΠΎΠ½Π½ΠΎΠΉ Π±Π°Π·Ρ‹ Π΄Π°Π½Π½Ρ‹Ρ…, Π°Π³Π΅Π½Ρ‚ создания аэронавигационных ΠΊΠ°Ρ€Ρ‚, Π°Π³Π΅Π½Ρ‚ экспорта (ΠΈΠΌΠΏΠΎΡ€Ρ‚Π°) Π½Π°Π±ΠΎΡ€Π° аэронавигационных Π΄Π°Π½Π½Ρ‹Ρ…, Π°Π³Π΅Π½Ρ‚ ΠΏΡƒΠ±Π»ΠΈΠΊΠ°Ρ†ΠΈΠΉ ΠΈ справочников. ΠšΡ€ΠΎΠΌΠ΅ Ρ‚ΠΎΠ³ΠΎ, Π² ΡΡ‚Π°Ρ‚ΡŒΠ΅ прСдставлСно схСматичСскоС ΠΈΠ·ΠΎΠ±Ρ€Π°ΠΆΠ΅Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠ³ΠΎΠ°Π³Π΅Π½Ρ‚Π½ΠΎΠΉ систСмы Π°Π²Ρ‚ΠΎΠΌΠ°Ρ‚ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ аэронавигационной ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ ΠΈ Π² матСматичСском Π²Ρ‹Ρ€Π°ΠΆΠ΅Π½ΠΈΠΈ ΠΏΠΎΠ΄Ρ€ΠΎΠ±Π½ΠΎ описан процСсс ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ заявки Π² Π°Π³Π΅Π½Ρ‚Π΅. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Π² процСссС исслСдования Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ ΠΌΠΎΠ³ΡƒΡ‚ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒΡΡ для ΠΏΠΎΠ²Ρ‹ΡˆΠ΅Π½ΠΈΡ эффСктивности аналитичСской ΡΠΎΡΡ‚Π°Π²Π»ΡΡŽΡ‰Π΅ΠΉ Π² структурС систСмы формирования прямых ΠΈ ΠΎΠ±Ρ€Π°Ρ‚Π½Ρ‹Ρ… ΠΊΠΎΠΎΡ€Π΄ΠΈΠ½Π°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… связСй ΠΏΡ€ΠΈ Ρ€Π΅ΡˆΠ΅Π½ΠΈΠΈ Π·Π°Π΄Π°Ρ‡ аэронавигации

    Big Five Technologies in Aeronautical Engineering Education: Scoping Review

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    The constant demands that technology creates in aerospace engineering also influence education. The identification of the technologies with practical application in aerospace engineering is of current interest to decision makers in both universities and industry. A social network approach enhances this scoping review of the research literature to identify the main topics using the Big Five technologies in aerospace engineering education. The conceptual structure of the dataset (n=447) was analyzed from different approaches: at macro-level, a comparative of the digital technology identified by cluster analysis with the number of co-words established in 3 and 8 and, a keyword central structure (n=8) at micro-level. The articles were categorized by the type of digital technology and, those related to the educational context (n=86) were co-word analyzed to study the relationships between basic and applied research. A total of 18 selected studies were analyzed from a design-based research approach. Findings reveal that Big Data, IoT (2002-2008) and, cloud computing (2010-) were initially applied in the aerospace engineering field. Only Cloud computing (2012) and, Big Data (2017) were transferred towards more educational research. Cloud computer appears related to collaborative work and classroom education. Big data is related to computer-aided design in engineering education. Only Web 2.0 (n=3) is used in the teaching of aeronautical engineering, without any interaction identified in the basic research. Most of the selected studies addressed the undergraduates students and the instructional approach strategy with the result of the potential for improved student learning

    Aeronautical Networks for In-Flight Connectivity : A Tutorial of the State-of-the-Art and Survey of Research Challenges

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    Barriers to the adoption of digital twin in the construction industry : a literature review

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    Digital twin (DT) has gained significant recognition among researchers due to its potential across industries. With the prime goal of solving numerous challenges confronting the construction industry (CI), DT in recent years has witnessed several applications in the CI. Hence, researchers have been advocating for DT adoption to tackle the challenges of the CI. Notwithstanding, a distinguishable set of barriers that oppose the adoption of DT in the CI has not been determined. Therefore, this paper identifies the barriers and incorporates them into a classified framework to enhance the roadmap for adopting DT in the CI. This research conducts an extensive review of the literature and analyses the barriers whilst integrating the science mapping technique. Using Scopus, ScienceDirect, and Web of Science databases, 154 related bibliographic records were identified and analysed using science mapping, while 40 carefully selected relevant publications were systematically reviewed. From the review, the top five barriers identified include low level of knowledge, low level of technology acceptance, lack of clear DT value propositions, project complexities, and static nature of building data. The results show that the UK, China, the USA, and Germany are the countries spearheading the DT adoption in the CI, while only a small number of institutions from Australia, the UK, Algeria, and Greece have established institutional collaborations for DT research. A conceptual framework was developed on the basis of 30 identified barriers to support the DT adoption roadmap. The main categories of the framework comprise stakeholder-oriented, industryrelated, construction-enterprise-related, and technology-related barriers. The identified barriers and the framework will guide and broaden the knowledge of DT, which is critical for successful adoption in the construction industry

    Applications of Mixed Reality for Smart Aviation Industry: Opportunities and Challenges

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    Nowadays, mixed reality has improved operational efficiency and enhanced passenger experience in the aviation industry. Integrated with advanced machine learning and artificial intelligence techniques, mixed reality can easily deal with tons of aviation data to support decision-making processes in this industry. The chapter presents the state-of-the-art applications of mixed reality in smart aviation industry. Opportunities and challenges of integrating mixed reality with advanced machine learning and artificial intelligence techniques into the aviation industry are introduced. This chapter focuses on how the integrated mixed reality can improve the quality and reliability of maintenance, operation, piloting, training, and product design in smart aerospace engineering. It also describes autonomous, self-service, and data visualization systems in smart airports to enhance passenger experience. Finally, this chapter discusses airline’s digital-based responses to the COVID-19 crisis

    Comparing Training Effects of Virtual Reality Flight Simulation to Conventional PC-Based Flight Simulation

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    The purpose of the current project was to investigate the effect of utilizing Virtual Reality (VR) technologies for flight training by comparing the training results when using conventional desktop flight simulation versus VR flight simulation. Additionally, this project examined the user experience of VR flight simulation and how users’ motivation and satisfaction with VR simulations. This research employed a quasi-transfer of training experiment including 48 participants. Analyses indicated that VR group participants performed better in the post-training maneuver performance on an FTD than in the conventional desktop simulation group. Findings also supported that VR flight simulation could provide a better user experience and generate a higher motivation for usage. This work contributed positive evidence that VR flight simulation has a large potential to be an effective flight training and provided a foundation for future research to continue exploring the training effect of VR flight simulation. Keywords: virtual reality, flight training, user experience, self-efficac

    Tahap penguasaan, sikap dan minat pelajar Kolej Kemahiran Tinggi MARA terhadap mata pelajaran Bahasa Inggeris

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    Kajian ini dilakukan untuk mengenal pasti tahap penguasaan, sikap dan minat pelajar Kolej Kemahiran Tinggi Mara Sri Gading terhadap Bahasa Inggeris. Kajian yang dijalankan ini berbentuk deskriptif atau lebih dikenali sebagai kaedah tinjauan. Seramai 325 orang pelajar Diploma in Construction Technology dari Kolej Kemahiran Tinggi Mara di daerah Batu Pahat telah dipilih sebagai sampel dalam kajian ini. Data yang diperoleh melalui instrument soal selidik telah dianalisis untuk mendapatkan pengukuran min, sisihan piawai, dan Pekali Korelasi Pearson untuk melihat hubungan hasil dapatan data. Manakala, frekuensi dan peratusan digunakan bagi mengukur penguasaan pelajar. Hasil dapatan kajian menunjukkan bahawa tahap penguasaan Bahasa Inggeris pelajar adalah berada pada tahap sederhana manakala faktor utama yang mempengaruhi penguasaan Bahasa Inggeris tersebut adalah minat diikuti oleh sikap. Hasil dapatan menggunakan pekali Korelasi Pearson juga menunjukkan bahawa terdapat hubungan yang signifikan antara sikap dengan penguasaan Bahasa Inggeris dan antara minat dengan penguasaan Bahasa Inggeris. Kajian menunjukkan bahawa semakin positif sikap dan minat pelajar terhadap pengajaran dan pembelajaran Bahasa Inggeris semakin tinggi pencapaian mereka. Hasil daripada kajian ini diharapkan dapat membantu pelajar dalam meningkatkan penguasaan Bahasa Inggeris dengan memupuk sikap positif dalam diri serta meningkatkan minat mereka terhadap Bahasa Inggeris dengan lebih baik. Oleh itu, diharap kajian ini dapat memberi panduan kepada pihak-pihak yang terlibat dalam membuat kajian yang akan datang
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