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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Sudaryono Inayatul Izzati Diana Yusuf Sabda Maulana Aptanta Pratiangga Dwi Apriliasari Department of Informatics Engineering University of Raharja Tangerang Indonesia Department of Informatics Engineering Bina Bangsa University Serang Indonesia Department of Digital Business Bosindo Tangerang Indonesia Department of Computer Science REY Tangerang Indonesia Department of Information System Pandawan Sejahtera Indonesia Tangerang Indonesia

ISBN: (数字)9798350367492

ISBN: (纸本)9798350367508

This study examines the rapid growth of startups integrating artificial intelligence (AI) into their business models, aiming to analyze and compare these startups with traditional IT organizations to understand their differences. Analyzing 162 global startups, this research identifies four unique archetypal business models, introducing novel methodologies in AI integration and data utilization that contrast with conventional IT paradigms. The focus is on technologies providing data analytics solutions, AI products and services, and the expansion of AI use. Key components of AI startup business models are highlighted: (1) advantages of AI in new value propositions, (2) data use to create value, and (3) the impact of AI on business decision-making. This research enhances the understanding of AI startup business models and suggests future research directions in entrepreneurship. The developed taxonomy highlights four distinct AI business models: the Deep Tech Researcher, Data Analytics Provider, AI Product/Service Provider, and AI Development Facilitator, each offering unique value propositions and leveraging AI technologies in different ways to address specific market needs. The research framework fosters entrepreneurial efforts with taxonomies and models as useful instruments.

关键词： Analytical models Data analysis Biological system modeling Taxonomy Entrepreneurship Data models Stakeholders Artificial intelligence Sustainable development Business

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Anatomical information based panel PET image reconstruction using nonlocal means regularization

Anatomical information based panel PET image reconstruction ...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Shuai Wang Xiaoqing Cao Xiangyu Sun Bo Zhang Qingguo Xie Peng Xiao Biomedical Engineering Department Huazhong University of Science and Technology Wuhan China Biomedical Engineering Department Shenzhen city Tencent computer system Co. Ltd Wuhan China Wuhan Digital PET Technology Co.Ltd Wuhan China

In recent years, panel PET is an interesting field in medical imaging. But the major obstacle of panel PET is the limited view problem. Images reconstructed by traditional algorithms will suffer serious artifacts. Time-of-flight (TOF) information can be incorporated into the image reconstruction to remove the artifacts. However, the best system timing resolution available in current commercial PET scanners is about 500 ps, which is not precise enough to achieve satisfactory images. In this paper, a list mode reconstruction algorithm coupled with non-local means regularizer was formulated to improve the panel PET image quality. It incorporates the anatomical information into the non-local means regularizer and modifies the reconstructed image while it is updating. The results show that our proposed method could remove the distortions effectively without TOF information.

关键词： Positron emission tomography Image reconstruction Phantoms Distortion Liver Computed tomography Detectors

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A high efficiency and multi-band/multi-mode power amplifier using a distributed second harmonic termination

A high efficiency and multi-band/multi-mode power amplifier ...

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作者： Kim, Jangheon Mkadem, Farouk Boumaiza, Slim Telecommunication System Division Digital Media and Communication Business Samsung Electronics Co. Ltd. 416 Maetan 3-dong Yeongtong-gu 443-742 Korea Republic of Department of Electrical and Computer Engineering University of Waterloo 200 University Ave West Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9782874870163

This paper proposes a new broadband saturated power amplifier (SPA) with a distributed second harmonic termination supporting multi-band/multi-mode operation. The proposed network is composed of a fundamental matching circuit and multiple second harmonic termination circuits. Due to the multiple harmonic terminations, the proposed PA improves the frequency range where the PA can achieve a high efficiency. The proposed PA is fabricated using a 45 W Cree CGH40045 GaN HEMT. Drain efficiencies of greater than 60% (average 66%) are achieved between about 1.8 GHz and 2.3 GHz (500 MHz bandwidth). When driven with long term evolution (LTE) and two carrier wideband code division multiple access (WCDMA) signals at DCS1800, PCS1900, and WCDMA bands, the linearity specifications of the corresponding standards are satisfied using the digital predistortion linearization technique, and it attains an efficiency of greater than 30%. © 2010 EuMA.

关键词： III-V semiconductors

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Self-Adaptive End-Point Mutation Technique Based on Adversary Strategy Awareness

Self-Adaptive End-Point Mutation Technique Based on Adversar...

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Conference on Local computer Networks (LCN)

作者： Yong Zhao Cheng Lei Yingjie Yang Hongqi Zhang Tong Yang Zongyi Zhao Xiaomei Sun China National Digital Switching System Engineering and Technological Research Center Zhengzhou China Henan Key Laboratory of Information Sccurity Zhenazhou China Department of Computer and Science Peking University Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

Moving target defense is a revolutionary technology to change the pattern of attack and defense, and end-point information mutation is one of the hotspots belonging to this field. In order to counterpoise the defense benefit of end-point information mutation and service quality of network system, the self-adaptive end-point mutation technique based on adversary strategy awareness is proposed. Directed at the blindness problem of mutation mechanism in the course of defense, adversary strategy awareness based on Sibson entropy algorithm is proposed for guiding the choice of mutation mode by discriminating the scanning attack strategy. Aimed at the low availability problem caused by limited network resource and high mutation overhead, satisfiability modulo theories are used to formally describe the constraints of mutation. Finally, theoretical and experimental analysis shows the ability to resist scanning attack and mutation overhead.

关键词： Entropy Information systems IP networks Network topology Resists Security Engines

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Wavelet and entropy analysis combination to evaluate diffusion and correlation behaviours

Wavelet and entropy analysis combination to evaluate diffusi...

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Brazilian Symposium on computer Graphics and Image Processing (SIBGRAPI)

作者： R.C.H. Chiou M.A.G.V. Ferreira C.T. Silva A.E. Kaufman Center for Visual Computing State University of New York Stony Brook Stony Brook NY USA Department of Computer and Digital System Engineering Polytechnic School of University of Sao Paulo Sao Paulo Brazil

Diffusion and correlation effects are two principal phenomena which have been studied for years and several visualization techniques have been proposed to help scientists to understand them. The analysis of these phenomena will help to extract important information from data sets. To understand these problems we combine wavelet and entropy analysis to evaluate the evolution of these behaviours through scale and time. We present image case studies to show several different kinds of behaviours of these effects. Some of them are fallible cases and not reliable, as the images do not show the desired information. We calculate entropy of smooth and detail coefficient sets, generated by wavelet transform of these sample images in each scale, to obtain measures that allow us to evaluate these behaviours according to the organization complexity. These measures can provide an indication about the quality of the rendered images.

关键词： Wavelet analysis Entropy Information analysis Wavelet transforms Multiresolution analysis Data visualization Rendering (computer graphics) digital systems systems engineering and theory Data mining

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Monitoring the video use for learning support

Monitoring the video use for learning support

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Frontiers in Education (FIE) Conference

作者： Itana Stiubiener Regina M. Silveira Reinaldo Matushima Wilson V. Ruggiero Mathematics Computing and Cogniton Center Universidade Federal do ABC (UFABC) Santo André Brazil Department of Computer and Digital System Engineering Universidade de São Paulo São Paulo Brazil

ISBN: (纸本)9781467352598

The video consumption tends to grow in coming years and it will be increasingly imperative to know the validity and effectiveness of using this type of media especially in teach and learn activities. It is very important to be able to assess how much knowledge a particular didactic video content was effective in building students knowledge. In this paper we present a tool we developed and an experiment we realized with two classes of computer engineering course related to network computer subjects, totalizing 140 students. In our experiment we divided our students in two groups: half of them attended a video explanation and half of them had the same explanation but only in a traditional classroom format. Our experiments show that video can be a great ally in the teaching and learning processes. Nevertheless, our investigation must continue in order to understand all video potential in this purpose.

关键词： Least squares approximations Monitoring Context Databases Servers Absorption Blogs

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A Secure Communication Approach for Mobile Intelligent Terminal

A Secure Communication Approach for Mobile Intelligent Termi...

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International Conference on computer Sciences and Applications (CSA)

作者： Fan Zhang Cong Zhang Mingdi Xu Minghui Yang School of Mathematics & Computer Science Wuhan Polytechnic University Wuhan China System Software Department Wuhan Digital Engineering Institute Wuhan China Third Research Institute of Ministry of Public Security Shanghai China

Currently, various mobile intelligent terminals have penetrated into our daily life. But at the same time, security and privacy issues of mobile intelligent terminals become a serious problem. In this paper, we present an approach to ensure the secure communication between mobile intelligent terminals. Our idea is to restrict that plaintext information can only exist inside mobile intelligent terminals, and any information outside of mobile intelligent terminals must be automatically encrypted. Experimental results show that our approach is efficient, and incur only 2%~3% performance losses.

关键词： Mobile communication Servers Encryption Protocols Mobile handsets

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Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

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The Lancet digital Health 2025年第5期7卷 100868页

作者： Meng, Ziyao Guan, Zhouyu Yu, Shujie Wu, Yilan Zhao, Yaoning Shen, Jie Lim, Cynthia Ciwei Chen, Tingli Yang, Dawei Ran, An Ran He, Feng Hamzah, Haslina Singh, Sarkaaj Abd Raof, Anis Syazwani Lee-Boey, Jian Wen Samuel Lim, Soo-Kun Sun, Xufang Ge, Shuwang Xu, Gang Su, Hua Cheng, Yang Lu, Feng Liao, Xiaofei Jin, Hai Deng, Chenxin Ruan, Lei Zhang, Cuntai Wu, Chan Dai, Rongping Jin, Yixiao Wang, Wenxiao Li, Tingyao Liu, Ruhan Li, Jiajia Shu, Jia Lu, Yuwei Wang, Xiangning Wu, Qiang Qin, Yiming Tang, Jin Sheng, Xiaohua Jiao, Qiong Yang, Xiaokang Guo, Minyi McKay, Gareth J Hogg, Ruth E Liew, Gerald Chee, Evelyn Yi Lyn Hsu, Wynne Lee, Mong Li Szeto, Simon Luk, Andrea O Y Chan, Juliana C N Cheung, Carol Y Tan, Gavin Siew Wei Tham, Yih-Chung Cheng, Ching-Yu Sabanayagam, Charumathi Lim, Lee-Ling Jia, Weiping Li, Huating Sheng, Bin Wong, Tien Yin Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Institute for Proactive Healthcare Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Centre for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Beijing Tsinghua Changgung Hospital Eye Center School of Clinical Medicine Tsinghua Medicine Tsinghua University Beijing China Medical Records and Statistics Office Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Renal Medicine Singapore General Hospital SingHealth-Duke Academic Medical Centre Singapore Singapore Department of Ophthalmology Shanghai Health and Medical Center Wuxi China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong Special Administrative Region China Singapore Eye Research Institute Singapore National Eye Centre Singapore Department of Medicine Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia Department of Ophthalmology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Hubei Wuhan China Department of Nephrology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Nephrology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Ophthalmology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Centre for Big Dat

Background: Improving the accessibility of screening diabetic kidney disease (DKD) and differentiating isolated diabetic nephropathy from non-diabetic kidney disease (NDKD) are two major challenges in the field of diabetes care. We aimed to develop and validate an artificial intelligence (AI) deep learning system to detect DKD and isolated diabetic nephropathy from retinal fundus images. Methods: In this population-based study, we developed a retinal image-based AI-deep learning system, DeepDKD, pretrained using 734 084 retinal fundus images. First, for DKD detection, we used 486 312 retinal images from 121 578 participants in the Shanghai Integrated Diabetes Prevention and Care system for development and internal validation, and ten multi-ethnic datasets from China, Singapore, Malaysia, Australia, and the UK (65 406 participants) for external validation. Second, to differentiate isolated diabetic nephropathy from NDKD, we used 1068 retinal images from 267 participants for development and internal validation, and three multi-ethnic datasets from China, Malaysia, and the UK (244 participants) for external validation. Finally, we conducted two proof-of-concept studies: a prospective real-world study with 3 months' follow-up to evaluate the effectiveness of DeepDKD in screening DKD;and a longitudinal analysis of the effectiveness of DeepDKD in differentiating isolated diabetic nephropathy from NDKD on renal function changes with 4·6 years' follow-up. Findings: For detecting DKD, DeepDKD achieved an area under the receiver operating characteristic curve (AUC) of 0·842 (95% CI 0·838–0·846) on the internal validation dataset and AUCs of 0·791–0·826 across external validation datasets. For differentiating isolated diabetic nephropathy from NDKD, DeepDKD achieved an AUC of 0·906 (0·825–0·966) on the internal validation dataset and AUCs of 0·733–0·844 across external validation datasets. In the prospective study, compared with the metadata model, DeepDKD could detect DKD wit

关键词： Deep learning

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Known User Continuous Authentication system

Known User Continuous Authentication System

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Ines Brosso Fernando Ferreira Graca Bressan Wilson V. Ruggiero College of Computation and Informatics Mackenzie Presbyterian University Sao Paulo Brazil Laboratory of Computer Architecture and Networks Polytechnic School of São Paulo University Brazil Laboratory of Computer Architecture and Networks Department of Computer and Digital System Engineering Polytechnic of São Paulo University Brazil

This work presents KUCAS (Known User Continuous Authentication system), a work-in-progress security system, that has a continuous authentication mechanism of users in software application. The KUCAS system makes use of environmental context information, users behavior analysis, the behavior theories of Skinner and the Mathematical Confidence of Dempster-Shafer Evidences Theory, that establishes trust levels to authenticate the user by his behavior analysis, during an application software, in a specific domain of the computer networks, in a period of time. The dynamics of enclosed management in this system compares the current behavior with the user's previous behaviors description and with the trust restrictions. In case of indications of changes in the user's behavior, the system provides the behavior analysis of the user using database restrictions information. If there are uncertainties and divergences, mechanisms of security and alert signals are triggered.

关键词： Authentication Application software Information security Data security Information analysis computer security Humans Communication system software Databases Context-aware services

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Anaesthesia Monitoring: From Conventional to AI-Enabled Data Acquisition Methods

Anaesthesia Monitoring: From Conventional to AI-Enabled Data...

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Eurocon

作者： Xiaoxiao Liu Sean McGrath Colin Flanagan Yiming Lei Liaoyuan Zeng Electronic and Computer Engineering University of Limerick Limerick Ireland Ministry of education engineering research center on mobile digital hospital system School of electronics Peking University Beijing China Department of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

It is widely recognized that the timely acquisition and presentation of accurate physiological data is a vital aid to the anaesthesiologist in monitoring and maintaining the well-being of a patient undergoing surgery. Collecting, storing, synchronizing, integrating, evaluating, and retrieving pertinent information from patient data remains very difficult due to limited computer power, the need for specialized software, inconsistency between monitoring devices, and inadequate data storage. This paper introduces the general steps of data acquisition in anaesthesia and summarizes some data acquisition systems. It also introduces some applications of the burgeoning field of artificial intelligence (AI) to data acquisition, illustrating how AI techniques may be used to advantage to assist the anaesthesiologist in monitoring and interpreting such data.

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