We propose an original approach to describe the scientific progress in a quantitative way. Using innovative Machine Learning techniques we create a vector representation for the PACS codes and we use them to represent...
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Business Model Canvas (BMC) is a tool widely used to describe startup business models. Despite the various business aspects described, BMC pays a little emphasis on team- related factors. The importance of team-relate...
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ISBN:
(数字)9781728195322
ISBN:
(纸本)9781728195339
Business Model Canvas (BMC) is a tool widely used to describe startup business models. Despite the various business aspects described, BMC pays a little emphasis on team- related factors. The importance of team-related factors in software development has been acknowledged widely in literature. While not as extensively studied, the importance of teams in software startups is also known in both literature and among practitioners. In this paper, we propose potential changes to BMC to have the tool better reflect the importance of the team, especially in a software startup environment. Based on a literature review, we identify various components related to the team, which we then further support with empirical data. We do so by means of a qualitative case study of five startups.
In recent years, mobile devices have taken a significant role in improving the quality of people’s life. In order to enhance the usability of those devices, more and more sensors have been built in. Furthermore, the ...
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AbstractDetecting pharyngeal acid reflux (PAR) episodes from 24-h ambulatory hypopharyngeal multichannel intraluminal impedance-pH (HMII-pH) signals is crucial for diagnosing laryngopharyngeal reflux (LPR). Currently,...
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AbstractDetecting pharyngeal acid reflux (PAR) episodes from 24-h ambulatory hypopharyngeal multichannel intraluminal impedance-pH (HMII-pH) signals is crucial for diagnosing laryngopharyngeal reflux (LPR). Currently, a lack of effective software for PAR episode detection requires time-consuming manual interpretation, which is prone to inter-rater variability. This study introduces a deep learning-based artificial intelligence (AI) system for PAR episode detection and diagnosis using HMII-pH signals. Ninety patients with suspected LPR and 28 healthy volunteers underwent HMII-pH testing in three Taiwanese medical centers. Candidate PAR episodes were defined as esophagopharyngeal pH drops exceeding 2 units, with nadir pH below 5 within 30 seconds during esophageal acidification. A consensus review by three experts validated 84 PAR episodes in 17 subjects. Data preprocessing identified 225 candidate PAR episodes, including 84 PAR episodes and 141 swallows/artifacts, were divided into training, validation, and test datasets (6:2:2 ratio). Three cascade deep learning AI models were trained. Among them, the cascade Multivariate Long Short-Term Memory with Fully Convolutional Network (MLSTM-FCN) model performed best in the test dataset. At the episode level, this model achieved 0.936 accuracy, 0.941 precision, 0.889 recall, 0.966 specificity, 0.914 F 1 score, and 0.864 Matthew's correlation coefficient (MCC). For subject-level evaluation, the corresponding metrics were 0.917 accuracy, 1.000 precision, 0.818 recall, 1.000 specificity, 0.900 F 1 score, and 0.842 MCC. In conclusion, the cascade MLSTM-FCN model demonstrates robust accuracy in diagnosing PAR episodes from HMII-pH signals, offering a promising tool for efficient and consistent PAR episode detection in LPR diagnosis.
In this paper, we investigate the energy-efficient hybrid precoding design for integrated multicast-unicast millimeter wave (mmWave) system, where the simultaneous wireless information and power transform is considere...
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Graphical User Interface(GUI) visualizes computer programs for the purpose of facilitating interaction between users and various computing devices. Today's computers, smart phones and even small devices such as wa...
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Graphical User Interface(GUI) visualizes computer programs for the purpose of facilitating interaction between users and various computing devices. Today's computers, smart phones and even small devices such as watches are equipped with GUIs. Unlike command based interaction, GUI uses images, labels, push buttons, radio buttons, etc. for the effective communication of users with a software system. GUI testing is a critical part of software testing as it is the door to the actual functionality of software. For the quality assurance, GUI functional testing of a software validates proper interaction between the interface and the user without considering any coding details. In this paper, a strategy based on fuzzy Adaptive Teaching Learning-based Optimization(ATLBO) algorithm, a variant of the basic Teaching Learning-based Optimization(TLBO) algorithm, for GUI functional testing is proposed. ATLBO utilizes Event-Interaction Graph(EIG) for the generation of quality test cases. The proposed strategy has produced competitive experimental results against the basic TLBO and other test case generation algorithms.
作者：
Li, XiangWang, WenhaiHu, XiaolinYang, JianPCA Lab
Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology China MomentaNational Key Lab for Novel Software Technology
Nanjing University
Department of Computer Science and Technology Tsinghua University China
In standard Convolutional Neural Networks (CNNs), the receptive fields of artificial neurons in each layer are designed to share the same size. It is well-known in the neuroscience community that the receptive field s...
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作者：
Dutt, NikilRegazzoni, Carlo S.Rinner, BernhardYao, XinNikil Dutt (Fellow
IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member
IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and
Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In c...
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Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computersystems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.
Formal methods (in a broad sense) have been around almost since the beginning of computerscience. Nonetheless, there is a perception in the formal methods community that take-up by industry is low considering the pot...
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The industrial supply chain networks basically capture the circulation of social resource, dominating the stability and efficiency of the industrial system. In this paper, we provide an empirical study of the topology...
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The industrial supply chain networks basically capture the circulation of social resource, dominating the stability and efficiency of the industrial system. In this paper, we provide an empirical study of the topology of smartphone supply chain network. The supply chain network is constructed using open online data. Our experimental results show that the smartphone supply chain network has small-world feature with scale-free degree distribution, in which a few high degree nodes play a key role in the function and can effectively reduce the communication cost. We also detect the community structure to find the basic functional unit. It shows that information communication between nodes is crucial to improve the resource utilization. We should pay attention to the global resource configuration for such electronic production management.
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