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Recommending software features for mobile applications based on user interface comparison

Requirements engineering 2019年第4期24卷 545-559页

作者： Chen, Xiangping Zou, Qiwen Fan, Bitian Zheng, Zibin Luo, Xiaonan Institute of Advanced Technology National Engineering Research Center of Digital Life Sun Yat-sen University Guangzhou China School of Data Science and Computer National Engineering Research Center of Digital Life Sun Yat-sen University Guangzhou China

App features are one of the most important factors that people consider when choosing apps. In order to satisfy users’ needs and attract their eyes, deciding what features should be added in next release becomes very important. Different from traditional requirement elimination, app stores provide a new platform for developers to gather requirements and perform market-wide analysis. Considering that software features provided to users can be found out by exploring existing apps, an important way to elicit requirements is analyzing existing features provided by products which offer related functions and then finding new trends and fashions promptly. In this context, we propose a data-driven approach for recommending software features of mobile applications based on user interface comparison. Our approach mines similar user interfaces (UIs) from publicly available online repository. To calculate UI similarity through the best matches of components of two UIs, text similarity is used to measure the similarity of UI components and genetic algorithm is introduced to improve the comparison efficiency. Then, we develop an algorithm to extract features from similar UIs based on a set of identification rules. These features are further clustered with text similarity algorithm and finally recommended to developers. The approach is empirically validated with 44 features from 10 UIs. The experiment results indicate that our recommended features are valuable for requirement elicitation. © 2018, Springer-Verlag London Ltd., part of Springer Nature.

关键词： Genetic algorithms

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mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary research Collaborations

arXiv

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arXiv 2022年

作者： Suzumura, Toyotaro Sugiki, Akiyoshi Takizawa, Hiroyuki Imakura, Akira Nakamura, Hiroshi Taura, Kenjiro Kudoh, Tomohiro Hanawa, Toshihiro Sekiya, Yuji Kobayashi, Hiroki Matsushima, Shin Kuga, Yohei Nakamura, Ryo Jiang, Renhe Kawase, Junya Hanai, Masatoshi Miyazaki, Hiroshi Ishizaki, Tsutomu Shimotoku, Daisuke Miyamoto, Daisuke Aida, Kento Takefusa, Atsuko Kurimoto, Takashi Sasayama, Koji Kitagawa, Naoya Fujiwara, Ikki Tanimura, Yusuke Aoki, Takayuki Endo, Toshio Ohshima, Satoshi Fukazawa, Keiichiro Date, Susumu Uchibayashi, Toshihiro Information Technology Center The University of Tokyo Japan Information Initiative Center Hokkaido University Japan Cyberscience Center Tohoku University Japan Faculty of Engineering Information and Systems University of Tsukuba Japan Division for Information and Communication Systems The University of Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Japan Center for Cloud Research and Development National Institute of Informatics Japan Research and Development Center for Academic Networks National Institute of Informatics Japan Research Center for Open Science and Data Platform National Institute of Informatics Japan Digital Architecture Research Center National Institute of Advanced Industrial Science and Technology Japan Global Scientific Information and Computing Center Tokyo Institute of Technology Japan Information Technology Center Nagoya University Japan Academic Center for Computing and Media Studies Kyoto University Japan Cybermedia Center Osaka University Japan Research Institute for Information Technology Kyushu University Japan

The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability to couple with supercomputers and edge devices through high-performance networks. We have built such a nation-wide cloud platform, called "mdx" to meet this need. The mdx platform’s virtualization service, jointly operated by 9 national universities and 2 national research institutes in Japan, launched in 2021, and more features are in development. Currently mdx is used by researchers in a wide variety of domains, including materials informatics, geo-spatial information science, life science, astronomical science, economics, social science, and computer science. This paper provides an the overview of the mdx platform, details the motivation for its development, reports its current status, and outlines its future plans. © 2022, CC BY.

关键词： Internet of things

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Universal noise-precision relations in variational quantum algorithms

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Physical Review research 2023年第2期5卷 023025-023025页

作者： Kosuke Ito Wataru Mizukami Keisuke Fujii Center for Quantum Information and Quantum Biology International Advanced Research Institute Osaka University Osaka 560-8531 Japan Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka 560-8531 Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama 332-0012 Japan RIKEN Center for Quantum Computing (RQC) Hirosawa 2-1 Wako Saitama 351-0198 Japan

Variational quantum algorithms (VQAs) are expected to become a practical application of near-term noisy quantum computers. Although the effect of the noise crucially determines whether a VQA works, the heuristic nature of VQAs makes it difficult to establish analytic theories. Analytic estimations of the impact of the noise are urgent for searching for quantum advantages, as numerical simulations of noisy quantum computers on classical computers are heavy and quite limited to small-scale problems. In this paper, we establish analytic estimations of the error in the cost function of VQAs due to the noise. The estimations are applicable to any typical VQAs under Gaussian noise, which is equivalent to a class of stochastic noise models. Notably, depolarizing noise is included in this model. As a result, we obtain estimations of the noise level to guarantee a required precision. Our formulas show how the Hessian of the cost function, the spectrum of the target operator, and the geometry of the ansatz affect the sensitivity to the noise. This insight implies trade-off relations between the trainability and the noise resilience of the cost function. We also obtain rough estimations which can be easily calculated without detailed information of the cost function. As a highlight of the applications of the formula, we propose a quantum error mitigation method which is different from the extrapolation and the probabilistic error cancellation.

关键词： Quantum algorithms Quantum computation

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Physics informed neural network (PINN) for noise-robust phase-based magnetic resonance electrical properties tomography

Physics informed neural network (PINN) for noise-robust phas...

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Radio Science Meeting (AT-AP-RASC), URSI Atlantic and Asia Pacific

作者： Adan J. Garcia Inda Shao Y. Huang Nevrez Immamoglu Wenwei Yu Department of Medical Engineering Chiba University Chiba Japan Department of Surgery National University of Singapore Singapore Singapore Engineering Product Development Department Singapore University of Technology and Design Singapore Singapore Digital Architecture Research Center National Institute of Advanced Industrial Science and Technology Tokyo Japan Center for Frontier Medical Engineering Chiba University Chiba Japan

Electrical properties could become a source of contrast for non-calcified tumor tissues. Magnetic Resonance Electrical Property Tomography (MREPT) relies on numerical differentiation to solve the partial differential equations (PDEs) to reconstruct electrical properties. However, the numerical differentiation for derivatives produces artifacts near tissue edges and amplifies noise. In this work, Physics-informed neural networks (PINNs), are employed to estimate derivatives for MREPT with automatic differentiation enabled by neural networks to improve noise robustness and reduce edge artifacts. PINNs require the balance of various loss functions and information from collocation points of ground truth and image boundary to learn to estimate the derivatives. In this work, a warm-up mechanism is used to reduce the complexity of the multiple loss balance. Results showed that even with only three collocation points and boundary conditions, reconstructions can be made from noise-contaminated source images (SNR 50). This proves that PINNs achieved noise-robust estimate of partial derivatives, thus leding to noise-robust conductivity reconstruction.

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PELE scores: Pelvic X-ray Landmark Detection by Pelvis Extraction and Enhancement

arXiv

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arXiv 2023年

作者： Huang, Zhen Li, Han Shao, Shitong Zhu, Heqin Hu, Huijie Cheng, Zhiwei Wang, Jianji Zhou, S. Kevin Computer Science Department University of Science and Technology of China Hefei230026 China School of Biomedical Engineering Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China Southeast University Nanjing China Institute of Computing Technology CAS Beijing100190 China Z2Sky Technologies Inc. Suzhou215123 China Affiliated Hospital of Guizhou Medical University Guiyang550000 China

The pelvis, the lower part of the trunk, supports and balances the trunk. Landmark detection from a pelvic X-ray (PXR) facilitates downstream analysis and computer-assisted diagnosis and treatment of pelvic diseases. Although PXRs have the advantages of low radiation and reduced cost compared to computed tomography (CT) images, their 2D pelvis-tissue superposition of 3D structures confuses clinical decision-making. In this paper, we propose a PELvis Extraction (PELE) module that utilizes 3D prior anatomical knowledge in CT to guide and well isolate the pelvis from PXRs, thereby eliminating the influence of soft tissue. We conduct an extensive evaluation based on two public datasets and one private dataset, totaling 850 PXRs. The experimental results show that the proposed PELE module significantly improves the accuracy of PXRs landmark detection and achieves state-of-the-art performances in several benchmark metrics, thus better serving downstream tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Extraction

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Variational learning of integrated quantum photonic circuits

arXiv

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arXiv 2024年

作者： Zhang, Hui Yang, Chengran Mok, Wai-Keong Wan, Lingxiao Cai, Hong Li, Qiang Gao, Feng Luo, Xianshu Lo, Guo-Qiang Chin, Lip Ket Shi, Yuzhi Thompson, Jayne Gu, Mile Liu, Ai Qun The Hong Kong Polytechnic University Hong Kong Nanyang Technological University Singapore Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 117543 Singapore California Institute of Technology PasadenaCA91125 United States Singapore Advanced Micro Foundry 11 Science Park Rd Singapore Department of Electrical Engineering City University of Hong Kong Kowloon Tong Hong Kong Institute of Precision Optical Engineering School of Physics Science and Engineering Tongji University Shanghai200092 China Institute of High Performance Computing Agency for Science Technology and Research 138632 Singapore Complexity Institute Nanyang Technological University Singapore Nanyang Quantum Hub School of Physical and Mathematical Sciences Nanyang Technological University Singapore

Integrated photonic circuits play a crucial role in implementing quantum information processing in the noisy intermediate-scale quantum (NISQ) era. Variational learning is a promising avenue that leverages classical optimization techniques to enhance quantum advantages on NISQ devices. However, most variational algorithms are circuit-model-based and encounter challenges when implemented on integrated photonic circuits, because they involve explicit decomposition of large quantum circuits into sequences of basic entangled gates, leading to an exponential decay of success probability due to the non-deterministic nature of photonic entangling gates. Here, we present a variational learning approach for designing quantum photonic circuits, which directly incorporates post-selection and elementary photonic elements into the training process. The complicated circuit is treated as a single nonlinear logical operator, and a unified design is discovered for it through variational learning. engineering an integrated photonic chip with automated control, we adjust and optimize the internal parameters of the chip in real time for task-specific cost functions. We utilize a simple case of designing photonic circuits for a single ancilla CNOT gate with improved success rate to illustrate how our proposed approach works, and then apply the approach in the first demonstration of quantum stochastic simulation using integrated photonics. © 2024, CC BY.

关键词： Cost functions

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Analysis of Cascaded Z-Source Topology Implementing DC-Link Voltage Balancing 9

Analysis of Cascaded Z-Source Topology Implementing DC-Link ...

引用

9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020

作者： Roomi, Muhammad M. Tariq, Mohd Zhao, Bin Advanced Digital Sciences Center Illinois at Singapore Pte Ltd Singapore Singapore ZHCET Aligarh Muslim University Department of Electrical Engineering Aligarh India Aerospace Research Institute Chinese Academy of Sciences China

ISBN: (纸本)9781728156729

Cascaded Z-Source topology coupled with a three-level diode clamped inverter provides an alternative multilevel buck-boost power conversion. Z-Source Inverter utilizes the shoot through states to conjoin the diode clamped inverter with one of the sources in the cascaded Z-Source topology. This unique integration during the shoot through states of the inverter facilitates the boosting of the three-level output voltage. In this paper, de-link voltage balancing of the cascaded topology when the input sources are non-identical is proposed. Reference disposition modulation method is utilized to couple the inverter to the Z-Source topology. The mathematical modelling of the cascaded impedance networks for the non-identical condition is derived in this paper. The circuit analysis proves that the de-link voltage balancing is attainable by carefully adjusting the duty cycle of the shoot through states. Subsequently, simulations results carried out in MATLAB/Simulink platforms validate the mathematical modelling of the cascaded Z-Source topology. © 2020 IEEE.

关键词： Buck-Boost converter

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Weighted p-Rényi Entropy Power Inequality: Information Theory to Quantum Shannon Theory

arXiv

引用

arXiv 2023年

作者： Lee, Junseo Yeo, Hyeonjun Jeong, Kabgyun School of Electrical and Electronic Engineering Yonsei University Seoul03722 Korea Republic of Quantum Computing R&D Norma Inc. Seoul04799 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Research Institute of Mathematics Seoul National University Seoul08826 Korea Republic of School of Computational Sciences Korea Institute for Advanced Study Seoul02455 Korea Republic of

We study the p-Rényi entropy power inequality with a weight factor t on two independent continuous random variables X and Y . The extension essentially relies on a modulation on the sharp Young’s inequality due to Bobkov and Marsiglietti. Our research provides a key result that can be used as a fundamental research finding in quantum Shannon theory, as it offers a Rényi version of the entropy power inequality for quantum systems. Copyright © 2023, The Authors. All rights reserved.

关键词： Information theory

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Automatic extraction of coronary arteries using deep learning in invasive coronary angiograms

arXiv

引用

arXiv 2022年

作者： Meng, Yinghui Du, Zhenglong Zhao, Chen Dong, Minghao Pienta, Drew Xu, Zhihui Zhou, Weihua School of Computer and Communication Engineering Zhengzhou University of Light Industry Henan Zhengzhou China Department of Applied Computing Michigan Technological University HoughtonMI49931 United States DepartmentMechanical Engineering-Engineering Mechanics Michigan Technological University HoughtonMI49931 United States Department of Cardiology The First Affiliated Hospital of Nanjing Medical University Jiangsu Nanjing210000 China Center for Biocomputing and Digital Health Institute of Computing and Cybersystems Health Research Institute Michigan Technological University HoughtonMI49931 United States

Background. Accurate extraction of coronary arteries from invasive coronary angiography (ICA) is important in clinical decision-making for the diagnosis and risk stratification of coronary artery disease (CAD). In this study, we develop a method using deep learning to automatically extract the coronary artery lumen. Methods. A deep learning model U-Net 3+, which incorporates the full-scale skip connections and deep supervisions, was proposed for automatic extraction of coronary arteries from ICAs. Transfer learning and a hybrid loss function were employed in this novel coronary artery extraction framework. Results. A data set containing 616 ICAs obtained from 210 patients was used. In the technical evaluation, the U-Net 3+ achieved a Dice score of 0.8942 and a sensitivity of 0.8735, which is higher than U-Net ++ (Dice score: 0.8814, the sensitivity of 0.8331) and U-net (Dice score: 0.8799, the sensitivity of 0.8305). Conclusion. Our study demonstrates that the U-Net 3+ is superior to other segmentation frameworks for the automatic extraction of the coronary arteries from ICAs. This result suggests great promise for clinical use. © 2022, CC BY.

关键词： Image segmentation

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Network Topology Overlapping Group Detection Based on h-Core Pruning

Network Topology Overlapping Group Detection Based on h-Core...

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6th International Conference on Intelligent computing and Signal Processing (ICSP)

作者： Qi Zhang Yan Liu Yuheng Cai Zhong Yuan Network Security Research Institute Zhengzhou University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Support Force Information Engineering University Zhengzhou China

ISBN: (纸本)9781665447300

The network group detection has a large number of application researches and has achieved certain results in network security, IP entity location and load balancing. However, due to the large scale of the network topology graph and the large number of terminal nodes, most of the existing overlapping group detection algorithms are relatively complex, and the data size that can be processed is limited, and cannot be directly applied to the network topology. This paper proposes a network topology overlapping group detection algorithm based on h-core pruning. This algorithm decomposes the network into smaller strong connected components, reduces the interference of noisy nodes to overlapping group discovery, and more efficiently detect the largest k-plex group on the target network. A large number of experiments show that the method in this paper is effective. Compared with the full-enum algorithm, our method increases the network size that can be handled by the largest k-plex group by two orders of magnitude, and can detect overlapping groups in the network topology more efficiently.

关键词： Network topology Signal processing algorithms Interference Signal processing Load management Topology Noise measurement

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