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Prototype, Method, and Experiment for Evaluating Usability of Smart Home User Interfaces

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SSRN

SSRN 2024年

作者： Faizrakhmanov, Renat Bahrami, Mohammad Reza Platunov, Alexey Cyberphysical Systems Laboratory Innopolis University 1 Universitetskaya Str. Innopolis420500 Russia Research Center for Artificial Intelligence 1 Universitetskaya Str. Innopolis420500 Russia Samarkand International University of Technology 270 Spitamen Ave. Samarkand140100 Uzbekistan Faculty of Software Engineering and Computer Systems ITMO University Kronverksky Pr. 49 bldg. A St. Petersburg197101 Russia

Despite the widespread adoption of smart devices and home automation systems, users still face usability challenges. Additionally, evaluating the usability of smart home systems is not straightforward. Our paper focuses on building a Smart Home Prototype, selecting, and evaluating software User Interfaces (UI). We have chosen the smart home heating system as the basis, but the principles are applicable to other applications. To discuss smart home UIs, it is necessary to understand the components, implementation scenarios, configuration, and operation of smart home systems. Therefore, we devote considerable attention to these topics in the paper. Our smart home system utilizes a Raspberry Pi computer, temperature sensors, servo drives, an Android-based smartphone, and other necessary hardware. We installed and configured open-source software and third-party services on the experimental setup. We provided a brief description of each selected software. We used the Home Assistant operating system, its mobile application, voice assistant Alice, and Telegram chatbot. In our study, we described a methodology for evaluating user interfaces in smart homes and conducted an experiment to assess their usability. The experiment results indicated which interface was more user-friendly and identified the drawbacks of each. In conclusion, we discuss UI features that can improve usability and available options for building a smart home based on capabilities. © 2024, The Authors. All rights reserved.

关键词： User interfaces

Variability Modeling of Products, Processes, and Resources in Cyber-Physical Production systems engineering

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arXiv 2024年

作者： Meixner, Kristof Feichtinger, Kevin Fadhlillah, Hafiyyan Sayyid Greiner, Sandra Marcher, Hannes Rabiser, Rick Biffl, Stefan Christian Doppler Laboratory SQI TU Wien Favoritenstraße 9-11 Vienna1040 Austria Information Systems Engineering TU Wien Favoritenstraße 9-11 Vienna1040 Austria CRC 1608 KASTEL – Dependability of Software-intensive Systems Karlsruhe Institute of Technology Am Fasanengarten 5 Karlsruhe76131 Germany Christian Doppler Laboratory VaSiCS Johannes Kepler University Linz Altenberger Straße 69 Linz4040 Austria Software Engineering Group Institute of Computer Science University of Bern Neubrückstraße 10 Bern3012 Switzerland LIT CPS Lab Johannes Kepler University Linz Altenberger Straße 69 Linz4040 Austria

Cyber-Physical Production systems (CPPSs), such as automated car manufacturing plants, execute a configurable sequence of production steps to manufacture products from a product portfolio. In CPPS engineering, domain experts start with manually determining feasible production step sequences and resources based on implicit knowledge. This process is hard to reproduce and highly inefficient. In this paper, we present the Extended Iterative Process Sequence Exploration (eIPSE) approach to derive variability models for products, processes, and resources from a domain-specific description. To automate the integrated exploration and configuration process for a CPPS, we provide a toolchain which automatically reduces the configuration space and allows to generate CPPS artifacts, such as control code for resources. We evaluate the approach with four real-world use cases, including the generation of control code artifacts, and an observational user study to collect feedback from engineers with different backgrounds. The results confirm the usefulness of the eIPSE approach and accompanying prototype to straightforwardly configure a desired CPPS. © 2024, CC BY.

关键词： Cyber Physical System

Not all fabrics are created equal: Exploring eFPGA parameters for IP redaction

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arXiv 2021年

作者： Bhandari, Jitendra Khader Thalakkattu Moosa, Abdul Tan, Benjamin Pilato, Christian Gore, Ganesh Tang, Xifan Temple, Scott Gaillardon, Pierre-Emmanuel Karri, Ramesh Center for Cybersecurity New York University New York CityNY11201 United States Department of Electrical and Software Engineering University of Calgary CalgaryABT2N 1N4 Canada Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Milano20133 Italy Laboratory for NanoIntegrated Systems Electrical and Computer Engineering Department University of Utah Salt Lake CityUT84112 United States

Semiconductor design houses rely on third-party foundries to manufacture their integrated circuits (IC). While this trend allows them to tackle fabrication costs, it introduces security concerns as external (and potentially malicious) parties can access critical parts of the designs and steal or modify the Intellectual Property (IP). Embedded FPGA (eFPGA) redaction is a promising technique to protect critical IPs of an ASIC by redacting (i.e., removing) critical parts and mapping them onto a custom reconfigurable fabric. Only trusted parties will receive the correct bitstream to restore the redacted functionality. While previous studies imply that using an eFPGA is a sufficient condition to provide security against IP threats like reverse-engineering, whether this truly holds for all eFPGA architectures is unclear, thus motivating the study in this paper. We examine the security of eFPGA fabrics generated by varying different FPGA design parameters. We characterize the power, performance, and area (PPA) characteristics and evaluate each fabric’s resistance to SAT-based bitstream recovery. Our results encourage designers to work with custom eFPGA fabrics rather than off-the-shelf commercial FPGAs and reveals that only considering a redaction fabric’s bitstream size is inadequate for gauging security. Copyright © 2021, The Authors. All rights reserved.

关键词： Field programmable gate arrays (FPGA)

Secure Beamforming Design for MISO SWIPT systems: An Indirectly Optimized Approach

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Secure Beamforming Design for MISO SWIPT Systems: An Indirec...

2019 IEEE Global Communications Conference (GLOBECOM)

作者： Yao Yu Siyu Wang Shumei Liu Lei Guo Zhaolong Ning Shimin Gong Mohammad S. Obaidat School of Computer Science and Engineering Northeastern University Shenyang China Chongqing University of Posts and Telecommunications China State Key Laboratory for Novel Software Technology Nanjing University China School of Intelligent Systems Engineering Sun Yat-sen University China ECE Department Nazarbayev University Astana Kazakhstan College of Computing and Informatics University of Sharjah UAE The King Abdullah II School of Information Technology The University of Jordan Amman Jordan University of Science and Technology Beijing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

By considering the Simultaneous Wireless Information and Power Transfer (SWIPT) schemes, this paper focuses on secure transmission model design in multiple-input-single-output (MISO) channels. In these channels, the channel state information is assumed to be perfect. Our objective is to maximize the worst-case secrecy rate with respect to both potential eavesdroppers and obvious eavesdroppers under the constraints of energy-harvesting and total transmission power. We present an optimization model to indirectly obtain maximum security rate in a single receiver system. Due to the high computational complexity of the solution process caused by the formulated non-convex optimization problem, we propose a novel indirect method to handle this issue. Then, a Semi-Definite Programming (SDP) relaxation method is used to approach the optimal solution. Moreover, we reveal the conditions for ensuring that the above semi-definite relaxation is compact. Simulation results demonstrate that the gained performance in our system is much better than those of the existing competing schemes.

关键词： Receivers Interference Signal to noise ratio Transmitters Optimization Security Communication system security

SGNet: Salient Geometric Network for Point Cloud Registration

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SGNet: Salient Geometric Network for Point Cloud Registratio...

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Qianliang Wu Yaqing Ding Lei Luo Haobo Jiang Shuo Gu Chuanwei Zhou Jin Xie Jian Yang PCA 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 Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic State Key Laboratory for Novel Software Technology Nanjing University Nanjing China School of Intelligence Science and Technology Nanjing University Suzhou China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Point Cloud Registration (PCR) is a critical and challenging task in computer vision and robotics. One of the primary difficulties in PCR is identifying salient and meaningful points that exhibit consistent semantic and geometric properties across different scans. Previous methods have encountered challenges with ambiguous matching due to the similarity among patch blocks throughout the entire point cloud and the lack of consideration for efficient global geometric consistency. To address these issues, we propose a new framework that includes several novel techniques. Firstly, we introduce a semantic-aware geometric encoder that combines object-level and patch-level semantic information. This encoder significantly improves registration recall by reducing ambiguity in patch-level superpoint matching. Additionally, we incorporate a prior knowledge approach that utilizes an intrinsic shape signature to identify salient points. This enables us to extract the most salient super points and meaningful dense points in the scene. Secondly, we introduce an innovative transformer that encodes High-Order (HO) geometric features. These features are crucial for identifying salient points within initial overlap regions while considering global high-order geometric consistency. We introduce an anchor node selection strategy to optimize this high-order transformer further. By encoding inter-frame triangle or polyhedron consistency features based on these anchor nodes, we can effectively learn high-order geometric features of salient super points. These high-order features are then propagated to dense points and utilized by a Sinkhorn matching module to identify critical correspondences for successful registration. The experiments conducted on the 3DMatch/3DLoMatch and KITTI datasets demonstrate the effectiveness of our method.

关键词： Point cloud compression computer vision Accuracy Shape Semantics Transformers Feature extraction Encoding Intelligent robots

Exploring representativeness and informativeness for active learning

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arXiv 2019年

作者： Du, Bo Wang, Zengmao Zhang, Lefei Zhang, Liangpei Liu, Wei Shen, Jialie Tao, Dacheng State Key Laboratory of Software Engineering School of Computer Wuhan University China Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong Collaborative Innovation Center of Geospatial Technology State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University China IBM T. J. Watson Research Center Yorktown HeightsNY10598 United States School of Information Systems Singapore Management University Singapore QCIS University of Technology SydneyNSW2007 Australia

How can we find a general way to choose the most suitable samples for training a classifier? Even with very limited prior information? Active learning, which can be regarded as an iterative optimization procedure, plays a key role to construct a refined training set to improve the classification performance in a variety of applications, such as text analysis, image recognition, social network modeling, etc. Although combining representativeness and informativeness of samples has been proven promising for active sampling, state-of-the-art methods perform well under certain data structures. Then can we find a way to fuse the two active sampling criteria without any assumption on data? This paper proposes a general active learning framework that effectively fuses the two criteria. Inspired by a two-sample discrepancy problem, triple measures are elaborately designed to guarantee that the query samples not only possess the representativeness of the unlabeled data but also reveal the diversity of the labeled data. Any appropriate similarity measure can be employed to construct the triple measures. Meanwhile, an uncertain measure is leveraged to generate the informativeness criterion, which can be carried out in different ways. Rooted in this framework, a practical active learning algorithm is proposed, which exploits a radial basis function together with the estimated probabilities to construct the triple measures and a modified Best-versus-Second-Best strategy to construct the uncertain measure, respectively. Experimental results on benchmark datasets demonstrate that our algorithm consistently achieves superior performance over the state-of-the-art active learning algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： Classification (of information)

Modal regression based structured low-rank matrix recovery for multi-view learning

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arXiv 2020年

作者： Xu, Jiamiao Wang, Fangzhao Peng, Qinmu You, Xinge Wang, Shuo Jing, Xiao-Yuan Philip Chen, C.L. School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute China State Key Laboratory of Software Engineering School of Computer Wuhan University China Department of Computer and Information Science Faculty of Science and Technology University of Macau 99999 China Dalian Maritime University Dalian116026 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods are incapable of well handling view discrepancy and discriminancy simultaneously, which thus leads to the performance degradation when there is a large discrepancy among multi-view data. To circumvent this drawback, motivated by the block-diagonal representation learning, we propose Structured Low-rank Matrix Recovery (SLMR), a unique method of effectively removing view discrepancy and improving discriminancy through the recovery of structured low-rank matrix. Furthermore, recent low-rank modeling provides a satisfactory solution to address data contaminated by predefined assumptions of noise distribution, such as Gaussian or Laplacian distribution. However, these models are not practical since complicated noise in practice may violate those assumptions and the distribution is generally unknown in advance. To alleviate such limitation, modal regression is elegantly incorporated into the framework of SLMR (term it MR-SLMR). Different from previous LMvSL based methods, our MR-SLMR can handle any zero-mode noise variable that contains a wide range of noise, such as Gaussian noise, random noise and outliers. The alternating direction method of multipliers (ADMM) framework and half-quadratic theory are used to efficiently optimize MR-SLMR. Experimental results on four public databases demonstrate the superiority of MR-SLMR and its robustness to complicated noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

SHAPES - A scalable parallel HW/SW architecture applied to wave field synthesis

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Proceedings of the AES International Conference

Proceedings of the AES International Conference 2007年

作者： Sporer, Thomas Beckinger, Michael Franck, Andreas Bacivarov, Iuliana Wolfgang, Haid Kai, Huang Thiele, Lothar Paolucci, Pier S. Bazzana, Piergiovanni Vicini, Piero Jianjiang, Ceng Kraemer, Stefan Leupers, Rainer Fraunhofer Institut fuer Digitale Medientechnologie Ilmenau 98693 Germany Swiss Federal Institute of Technology Zurich Computer Engineering and Networks Laboratory Zurich CH-8092 Switzerland ATMEL Roma Roma Italy INFN Dip. Fisica Univ. Roma La Sapienza Roma 00185 Italy Institute for Software for Systems on Silicon RWTH Aachen University Aachen 52056 Germany

The usage of advanced audio processing algorithms in products has always been limited by the available processing power. For powerful concepts like the wave field synthesis (WFS) the performance is limited by the execution speed. In the past it was possible to increase the performance of digital signal processors by increasing the clock rate. The next generation will be highly parallel heterogeneous multi-processor systems. This paper presents a now parallel processor architecture and the first stops towards an adequate optimization of WFS. A software development environment which assists in creating scalable programs for highly parallel hardware will be further explained. An enhanced WFS convolution structure is presented which use position dependent filtering and improve the interpolation necessary for moving sound sources.

关键词： Digital signal processors

Evaluating Hashing Algorithms in the Age of ASIC Resistance 3

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Evaluating Hashing Algorithms in the Age of ASIC Resistance

3rd International Workshop on Information Technologies: Theoretical and Applied Problems, ITTAP 2023

作者： Kuznetsov, Oleksandr Kuznetsova, Yelyzaveta Smirnov, Oleksii Kostenko, Oleksii Zvieriev, Volodymyr Department of Political Sciences Communication and International Relations University of Macerata Via Crescimbeni 30/32 Macerata62100 Italy Department of Information and Communication Systems Security School of Computer Sciences V. N. Karazin Kharkiv National University 4 Svobody Sq. Kharkiv61022 Ukraine Department of cyber security and software Central Ukrainian National Technical University 8 University Ave Kropyvnytskyi25006 Ukraine Scientific Laboratory of the Theory of Digital Transformation Law of the Scientific Center for Digital Transformation Law of the State Scientific Institution "Institute of Information Security Law of the National Academy of Legal Sciences of Ukraine" P.Orlyk str. 3 Kyiv01024 Ukraine Department of Software Engineering and Cybersecurity State University of Trade and Economics Kyoto 19 Kyiv02156 Ukraine

In the intricate matrix of cryptographic hashing, two contrasting paradigms vie for precedence: computational swiftness and resilience against specialized hardware, or ASICs. This study undertakes a meticulous exploration into these dueling priorities, juxtaposing conventional stalwarts like SHA-2 and KECCAK against the newer, ASIC-resistant X series. Leveraging detailed performance metrics and visual analytics, we discern the manifest advantage of SHA-2 and KECCAK in terms of computational alacrity. However, as the paper delves deeper, a compelling narrative unfolds. The deliberate design intricacies of the X series, despite their computational latency, emerge as robust bulwarks against potential centralization threats posed by ASIC miners. These algorithms embody a strategic deceleration, ensuring that the cryptocurrency terrain remains hospitable to a broad diaspora of miners. Through this multifaceted lens, we argue that in the cryptographic domain, raw speed is but one facet of a larger, more nuanced picture. The underlying ethos of decentralization and democratic access must guide our trajectory, even if it comes at the expense of pure efficiency. In essence, this paper endeavors to navigate the delicate balance between rapid computation and the overarching principles of an inclusive digital realm. © 2023 CEUR-WS. All rights reserved.

关键词： Computational efficiency