Neural community-primarily based time series analysis (NNTSA) is an effective technique for research records collected from wireless sensor networks (WSNs). NNTSA uses models stimulated by means of biological neural n...
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In wireless sensor networks (WSN), data collection is a crucial and complex issue. Especially when the objective function is unknown, designing an effective data collection optimization algorithm has become a huge cha...
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This article presents a protocol for conducting online think-aloud interviews as well as the reflections of the participants and interviewer on this process. The interviewer and participants commenced the interviews i...
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A storage structure C-L Matrix based on linked lists and matrices is proposed to address the issue of spatiotemporal data not fully utilizing its temporal and spatial attributes in blockchain, and efficient queries ar...
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Purpose: This paper is focused on the role of ChatGPT an artificial intelligence (AI) language model in the area of sports trauma. Sports trauma represents some significant concerns due to its prevalence and impacts. ...
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The general increase in data size and data sharing motivates the adoption of Big Data strategies in several scientific disciplines. However, while several options are available, no particular guidelines exist for sele...
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This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine *** map demonstrates remarkable chaotic dynamics over a wide range of *** employ nonlinear analytical t...
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This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine *** map demonstrates remarkable chaotic dynamics over a wide range of *** employ nonlinear analytical tools to thoroughly investigate the dynamics of the chaotic map,which allows us to select optimal parameter configurations for the encryption *** findings indicate that the proposed sine-cosine map is capable of generating a rich variety of chaotic attractors,an essential characteristic for effective *** encryption technique is based on bit-plane decomposition,wherein a plain image is divided into distinct bit *** planes are organized into two matrices:one containing the most significant bit planes and the other housing the least significant *** subsequent phases of chaotic confusion and diffusion utilize these matrices to enhance *** auxiliary matrix is then generated,comprising the combined bit planes that yield the final encrypted *** results demonstrate that our proposed technique achieves a commendable level of security for safeguarding sensitive patient information in medical *** a result,image quality is evaluated using the Structural Similarity Index(SSIM),yielding values close to zero for encrypted images and approaching one for decrypted ***,the entropy values of the encrypted images are near 8,with a Number of Pixel Change Rate(NPCR)and Unified Average Change Intensity(UACI)exceeding 99.50%and 33%,***,quantitative assessments of occlusion attacks,along with comparisons to leading algorithms,validate the integrity and efficacy of our medical image encryption approach.
Image synthesis and generation is an important research direction in the fields of computer vision and deep learning. These generative models not only enrich visual content and reduce acquisition difficulty, but also ...
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Background: QoS parameters are volatile in nature and possess high nonlinearity, thus making the IoT-based service and recommendation process challenging. Methods: An efficient and accurate forecasting model is lackin...
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In this paper we consider the following 2-Central Path Problem (2CPP): Given a set of m polygonal curves = {P1,P2,...,Pm} in the plane, find two curves Pu and Pl, called 2-central paths, that best represent all curves...
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In this paper we consider the following 2-Central Path Problem (2CPP): Given a set of m polygonal curves = {P1,P2,...,Pm} in the plane, find two curves Pu and Pl, called 2-central paths, that best represent all curves in . Despite its theoretical interest and a wide range of practical applications, 2CPP has not been well studied. In this paper, we first establish criteria that Pu and Pl ought to meet in order for them to best represent . In particular, we require that there exists parametrizations fu(t) and fl(t) (t [a,b]) of Pu and Pl respectively such that the maximum distance from {fu(t),fl(t)} to curves in is minimized. Then an efficient algorithm is presented to solve 2CPP under certain realistic assumptions. Our algorithm constructs Pu and Pl in O(nmlog4n2α(n)α(n)) time, where n is the total complexity of (i.e., the total number of vertices and edges), m is the number of curves in , and α(n) is the inverse Ackermann function. Our algorithm uses parametric search technique and is considerably faster than arrangement-related algorithms (i.e. ω(n2)) when m ≪ n as in most real applications.
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