A new method of image coding by autoregressive (AR) synthesis is presented. The physics of image formation suggests that an image may be considered as a power spectrum. Using this formulation a Cosine transform of the...
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A new method of image coding by autoregressive (AR) synthesis is presented. The physics of image formation suggests that an image may be considered as a power spectrum. Using this formulation a Cosine transform of the sampled image is shown to yield a set of autocorrelations. These are used to find an equivalent AR model whose parameters are encoded for transmission. Compared to conventional Cosine transform coding, this method is shown to give superior resolution and is shown to suppress the "block-effects" present in block-by-block transform coding methods. Distinction between this method and linear predictive coding (LPC) used for speech data compression is made. Extensions and examples for two dimensional images are given.
Low-resource languages are challenging to process intelligent decision systems due to limited data and resources. As an effective way of processing low-resource languages in intelligent decision systems, fuzzy linguis...
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Low-resource languages are challenging to process intelligent decision systems due to limited data and resources. As an effective way of processing low-resource languages in intelligent decision systems, fuzzy linguistic approaches excel in transforming original uncertain linguistic information into highly structured data and learning valid decision rules between complex data structures. However, existing fuzzy linguistic methods may not fully capture realistic features of multi-attribute group decision-making (MAGDM), such as incomplete and hesitant linguistic expressions, stable information fusion, and bounded rationality of decision-makers (DMs). Therefore, it is necessary to develop a collaborative fuzzy language learning system based on bounded rationality, low-resource and robust decision-making. Specifically, we present a new multi-granularity (MG) group decision-making (GDM) scheme by using MULTIMOORA (Multi-Objective Optimization by Ratio Analysis plus the full MULTIplicative form) and PT (Prospect Theory) for incomplete hesitant fuzzy linguistic information systems (I-HFL-ISs), where MG GDM aims to discover knowledge from complex MAGDM problems with MG features. To achieve the above goal, we first introduce the concept of MG-I-HFL-ISs to represent incomplete, hesitant and imprecise linguistic evaluation information offered by multiple decision-makers (DMs). Then, we apply a valid transformation scheme to convert MG-I-HFL-ISs into MG-HFL-ISs, and use the MG probability rough set (PRS) to develop a series of MG-HFL-PRSs with the support of MULTIMOORA. Afterwards, an HFL MG GDM method is designed by integrating MULTIMOORA and PT for solving MAGDM problems with MG-I-HFL-ISs. The proposed method can effectively synthesize low-resource languages and mine useful decision-making knowledge. At last, a drug selection case and a simulated case are performed for showing the rationality of the designed HFL MG GDM scheme.
Visual informatics is a field of interest not just among the information technology and computer science community, but also other related fields such as engineering, me- cal and health informatics and education start...
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ISBN:
(数字)9783642050367
ISBN:
(纸本)9783642050350
Visual informatics is a field of interest not just among the information technology and computer science community, but also other related fields such as engineering, me- cal and health informatics and education starting in the early 1990s. Recently, the field is gaining more attention from researchers and industry. It has become a mul- disciplinary and trans-disciplinary field related to research areas such as computer vision, visualization, information visualization, real-time image processing, medical image processing, image information retrieval, virtual reality, augmented reality, - pressive visual mathematics, 3D graphics, multimedia-fusion, visual data mining, visual ontology, as well as services and visual culture. Various efforts has been - vested in different research, but operationally, many of these systems are not pro- nent in the mass market and thus knowledge and research on these phenomena within the mentioned areas need to be shared and disseminated. It is for this reason that the Visual Informatics Research Group from Universiti - bangsaan Malaysia (UKM) decided to spearhead this initiative to bring together experts in this very diversified but important research area so that more concerted efforts can be undertaken not just within the visual informatics community in Malaysia but from other parts of the world, namely, Asia, Europe, Oceania, and USA. This first International Visual Informatics Conference (IVIC 2009) was conducted collaboratively, by the visual informatics research community from the various public and private institutions of higher learning in Malaysia, and hosted by UKM.
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific ...
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ISBN:
(数字)9783642157028
ISBN:
(纸本)9783642157011
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific Rim, namely Sydney (PCM 2000), Beijing (PCM 2001), Hsinchu (PCM 2002), Singapore (PCM 2003), Tokyo (PCM 2004), Jeju (PCM 2005), Zhejiang (PCM 2006), Hong Kong (PCM 2007), Tainan (PCM 2008), and Bangkok (PCM 2009). PCM is a major annual international conference organized as a forum for the dissemination of state-of-the-art technological advances and research results in the fields of theoretical, experimental, and applied multimedia analysis and processing. PCM 2010 featured a comprehensive technical program which included 75 oral and 56 poster presentations selected from 261 submissions from Australia, Canada, China, France, Germany, Hong Kong, India, Iran, Italy, Japan, Korea, Myanmar, Norway, Singapore, Taiwan, Thailand, the UK, and the USA. Three distinguished researchers, Prof. Zhi-Hua Zhou from Nanjing University, Dr. Yong Rui from Microsoft, and Dr. Tie-Yan Liu from Microsoft Research Asia delivered three keynote talks to the conference. We are very grateful to the many people who helped to make this conference a s- cess. We would like to especially thank Hong Lu for local organization, Qi Zhang for handling the publication of the proceedings, and Cheng Jin for looking after the c- ference website and publicity. We thank Fei Wu for organizing the special session on large-scale multimedia search in the social network settings.
The rise of the digital economy and e-commerce has fostered a movement towards efficient low-resource medical information processing, a trend that holds great importance in the healthcare sector. Diabetes, being a wid...
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The rise of the digital economy and e-commerce has fostered a movement towards efficient low-resource medical information processing, a trend that holds great importance in the healthcare sector. Diabetes, being a widespread chronic condition, has witnessed the introduction of glucometers, which offer patients a convenient method of monitoring their blood sugar levels. However, it is worth noting that a considerable proportion of online comments may be subject to emotional bias or contain inaccurate information. Furthermore, the performance of glucometers can be influenced by several attributes, including price, accuracy and portability, thereby potentially complicating the decision-making process for consumers. Semantic analysis can be employed to acquire valuable information, aiding consumers in reasonably choosing the suitable glucometer. This paper utilizes the benefits of granular computing, an emerging computing paradigm, to effectively handle incomplete and uncertain medical information. It employs generalized fuzzy sets, rough sets and three-way decisions (TWD) techniques to boost the accuracy and reliability of medical information fusion. Subsequently, the MABAC (Multi-Attribute Border Approximation Area Comparison) method is utilized to evaluate the reviews of every glucometer, calculate their aggregated scores, and rank and compare them. Ultimately, in light of consumers’ needs and trade-offs, the glucometer with the highest score can be selected. The proposed approach comprehensively considers the weight and priority of multiple attributes, reduces information overload and mitigates selection difficulties, thereby enhancing the accuracy and reliability of low-resource medical information processing.
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific ...
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ISBN:
(数字)9783642156960
ISBN:
(纸本)9783642156953
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific Rim, namely Sydney (PCM 2000), Beijing (PCM 2001), Hsinchu (PCM 2002), Singapore (PCM 2003), Tokyo (PCM 2004), Jeju (PCM 2005), Zhejiang (PCM 2006), Hong Kong (PCM 2007), Tainan (PCM 2008), and Bangkok (PCM 2009). PCM is a major annual international conference organized as a forum for the dissemination of state-of-the-art technological advances and research results in the fields of theoretical, experimental, and applied multimedia analysis and processing. PCM 2010 featured a comprehensive technical program which included 75 oral and 56 poster presentations selected from 261 submissions from Australia, Canada, China, France, Germany, Hong Kong, India, Iran, Italy, Japan, Korea, Myanmar, Norway, Singapore, Taiwan, Thailand, the UK, and the USA. Three distinguished researchers, Prof. Zhi-Hua Zhou from Nanjing University, Dr. Yong Rui from Microsoft, and Dr. Tie-Yan Liu from Microsoft Research Asia delivered three keynote talks to the conference. We are very grateful to the many people who helped to make this conference a s- cess. We would like to especially thank Hong Lu for local organization, Qi Zhang for handling the publication of the proceedings, and Cheng Jin for looking after the c- ference website and publicity. We thank Fei Wu for organizing the special session on large-scale multimedia search in the social network settings.
作者：
ORMSBY, JOSEPH F. A.THE AUTHOR Graduated from Rensselaer Polytechnic Institute in 1950. From then until the Spring of 1955
he worked at R.P.I. in the various capacities of instructor in the Department of Electrical Engineering assistant project engineer on a Signal Corps project and research associate in the Computer (analogue) Laboratory Department. During this period he also received his M.E.E. and M.S. (math) degrees from R.P.I. He entered the United States Naval Officers Candidate School in May 1955 and received his commission as an Ensign in the Naval Reserve in September 1955. Upon assignment to Boston Naval Shipyard he worked as a ship superintendent. Later he was assigned to the Production Analysis Officer as an assistant on electronic data processing. His interest in this area is reflected in the present article.
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