Conducting a single course across international boundaries impacts both the students and the instructors. Interestingly, many of the impacts are the same. In essence, while the international team of students is workin...
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ISBN:
(纸本)9781538695067
Conducting a single course across international boundaries impacts both the students and the instructors. Interestingly, many of the impacts are the same. In essence, while the international team of students is working on their project, the international team of instructors is working on their own project-the course itself. In our case we deliver a joint course for more than 100 students spread across three international campuses on three different continents with three different business cultures. The main course goal is to prepare students for real IT projects that are based on distributed software development, covering all project phases: short definition of project task, gathering the data and creating the requirements list, dividing the team roles, creating the project plan along with time-line and budget-line, developing, testing and deploying the final project, documenting the project and proposing plans for maintenance and further support. At the end of the course students need to peer-review their team members;these evaluations are a significant part of the students' final grades. Our past experience showed that as a whole, students were very satisfied with the experience and knowledge they gained during our Capstone course. This was particularly evident with anecdotal comments by alumni.
Understanding the dynamics of the interaction between railway vehicles and tracks is essential for forecasting vehicle and track conditions and performing maintenance actions to preserve the safety of railway infrastr...
Understanding the dynamics of the interaction between railway vehicles and tracks is essential for forecasting vehicle and track conditions and performing maintenance actions to preserve the safety of railway infrastructure. In this work, physics-based models are deployed to predict the dynamic response of railway vehicles to track alignment and irregularities. Such models comprise a large number of parameters that need to be validated and possibly tuned, a task often accomplished on the basis of expert knowledge or trial-and-error without necessarily reflecting the condition of the operating system as-is. Therefore, model uncertainties persist due to assumptions on the actual system behavior, as well as due to varying operational parameters (e.g., wheel profile, rail profile, rail moisture). To improve modelling accuracy, this study adopts a multi-body vehicle model, realized in SIMPACK software, and performs parameter tuning based on on-board measurement data (accelerations and forces) from an instrumented tilting train, which regularly traverses the Swiss Federal Railways (SBB) network. The pertinent vehicle model is optimized in terms of the interaction forces at the wheel-rail contact using a Bayesian model updating approach, relying on Markov-Chain Monte Carlo (MCMC). Specifically, the MCMC method is applied to estimate both optimal vehicle parameters and their uncertainty by minimizing the mean squared error between simulated and measured contact forces, leading to an improved vehicle twin.
With more than 300 million people depressed worldwide annually, depression is a global problem. The goal of depression detection is to improve diagnostic accuracy and availability, leading to faster intervention. The ...
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ISBN:
(数字)9781728113319
ISBN:
(纸本)9781728113326
With more than 300 million people depressed worldwide annually, depression is a global problem. The goal of depression detection is to improve diagnostic accuracy and availability, leading to faster intervention. The most important and challenging problem here is to design an effective and robust depression detection model. To this end, there are two challenges to overcome: 1) Multi-modal (audio, image, text, etc.) information must be jointly considered to make accurate inferences. 2) Existing deep learning-based work suffers from multi-modal data sufficiency problem. To address these issues, we propose a graph attention model embedded with multi-modal knowledge for depression detection. This approach learns not only reasonable embeddings for nodes in the knowledge graph, but also exploits medical knowledge to improve the performance of classification and prediction with the knowledge attention mechanism. Experimental results on the real-world datasets show that the proposed approach significantly improves the classification and prediction performance compared with other major state-of-the-art approaches, with guaranteed the robustness with each modality of multi-modal data. Overall, this paper shows how multi-modal knowledge attention mechanism and deep-learning-based networks can be combined to assist mental health patients and practitioners.
Within a framework for verifying parametric network protocols through induction, one needs to find invariants based on a protocol instance of a small number of nodes. In this paper, we propose a new approach to accele...
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ISBN:
(数字)9781728197104
ISBN:
(纸本)9781728197111
Within a framework for verifying parametric network protocols through induction, one needs to find invariants based on a protocol instance of a small number of nodes. In this paper, we propose a new approach to accelerate parameterized verification by adopting decision trees to represent the state space of a protocol instance. Such trees can be considered as a knowledge base that summarizes all behaviors of the protocol instance. With this knowledge base, we are able to efficiently construct an oracle to effectively assess candidates of invariants of the protocol, which are suggested by an invariant finder. With the discovered invariants, a formal proof for the correctness of the protocol can be derived in the framework after proper generalization. The effectiveness of our method is demonstrated by experiments with typical benchmarks.
In addition to knowledge of distributed project management techniques, softwareengineering courses need to teach students the intercultural communication skills necessary to cooperate effectively with team members fr...
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The innovative process of implementing BIM in the Russian construction industry began in 2014, characterized by interdisciplinary and intersectoral interaction of participants in the investment and construction proces...
The innovative process of implementing BIM in the Russian construction industry began in 2014, characterized by interdisciplinary and intersectoral interaction of participants in the investment and construction process to create a real construction object and its digital counterpart from the moment of the origin of the project idea to the use of the constructed object, which requires cooperation of participants in the construction market and government authorities, teamwork of participants in the investment and construction project. The institutional component of the development of the information modeling market is the development of rules for interaction in construction: the creation of a regulatory framework, national standards, technical regulations, a comprehensive national eco-platform of the construction industry based on national information systems. The information model (BIM – Building Information Model) based on the software product "Adept: Construction Management" is a computer model, that has the ability to make database of construction process, control, operation and technical service of the object. The digital twin of a real estate object allows you to expand the capabilities of business processes on the life cycle. Firstly, it is traditional to build a real estate object, secondly, to model the state of a real estate object using information and intelligent technologies, to use a database of historical data, a knowledge base, a database of sensor readings, sensors based on Internet of Things technology, as well as to predict the state of a real estate object using a decision support system. software product "Alt-Invest. Construction" allows you to supplement the 3D model of the building based on the calculated in the program "Adept. Construction management" of the calendar plan up to 5D: formation of project indicators during the current operation of the constructed real estate object.
Risks are intrinsic part of any software project. Most software projects face severe risk during the development process, but some finds minor risks. Vulnerabilities of these risks are threat to a quality of a softwar...
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Automatically analysing games is an important challenge for automated game design, general game playing, and cocreative game design tools. However, understanding the nature of an unseen game is extremely difficult due...
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ISBN:
(纸本)9781728118840
Automatically analysing games is an important challenge for automated game design, general game playing, and cocreative game design tools. However, understanding the nature of an unseen game is extremely difficult due to the lack of a priori design knowledge and heuristics. In this paper we formally define hyperstate space graphs, a compressed form of state space graphs which can be constructed without any prior design knowledge about a game. We show how hyperstate space graphs produce compact representations of games which closely relate to the heuristics designed by hand for search-based AI agents;we show how hyperstate space graphs also relate to modern ideas about game design;and we point towards future applications for hyperstates across game AI research.
This paper presents a model for the application of agile requirements engineering. The literature review made it possible to identify the requirements elicitation process based on standards such as capability maturity...
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Due to organic synthesis achievements, the amount of data and knowledge in organic chemistry grows exponentially. Despite the existence of diverse software and information products, there is a need for high-quality in...
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