Design of sample adaptive product quantizers for noisy channels

Channel-optimized vector quantization (COVQ) has proven to be an effective joint source-channel coding technique that makes the underlying quantizer robust to channel noise. Unfortunately, COVQ retains the high encoding complexity of the standard vector quantizer (VQ) for medium-to-high quantization dimensions and moderate-to-good channel conditions. A technique called sample adaptive product quantization (SAPQ) was recently introduced by Kim and Shroff to reduce the complexity of the VQ while achieving comparable distortions. In this letter, we generalize the design of SAPQ for the case of memoryless noisy channels by optimizing the quantizer with respect to both source and channel statistics. Numerical results demonstrate that the channel-optimized SAPQ (COSAPQ) achieves comparable performance to the COVQ (within 0.2 dB), while maintaining considerably lower encoding complexity (up to half of that of COVQ) and storage requirements. Robustness of the COSAPQ system against channel mismatch is also examined.     

城市管理项目前景光明

瑞典国际发展合作署（SIDA）支持城市管理项目（UMP）有许多原因。瑞典国际发展合作署发现城市管理项目在减轻贫困、良好治理、环境、性别平等和艾滋病防治等问题上的主要观点、关注重点与其发展重点相近。     

Low-Field Nuclear Magnetic Resonance Time Domain Characterization of Polyunsaturated Fatty Acid–Rich Linseed and Fish Oil Emulsions during Thermal Air Oxidation

Linseed contains high levels of polyunsaturated fatty acids (PUFA), such as α-linolenic acid (> 50% ALA-18:3), that are naturally protected against thermal oxidation by their encapsulation within linseed oil bodies (OB) by multiple components including antioxidant proteins and mucilage emulsifying agents. Linseed OB emulsions (LSE) can be produced by grinding linseed seeds, adding water, adjusting pH, and sonication. This is a process that can encapsulate externally added PUFA to minimize their thermal oxidation, as it does for the intrinsic ALA PUFA. Fish oil (FO) encapsulation into this LSE platform to form linseed fish oil emulsions (LSFE) offers the possibility of a nutritive delivery system of the biologically essential FO PUFA eicosapentaenoic acid and docosahexaenoic acid. In this study, ¹H low-field nuclear magnetic resonance (LF-NMR) is used to characterize LSE's and LSFE's chemical and structural properties as well as their stability and changes under thermal oxidation (55 °C for 96 hours). ¹H LF-NMR data processing was developed to generate one-dimensional (1D) T₁ (spin–lattice), 1D T₂ (spin–spin), and 2D (T₁ vs. T₂) relaxation time spectra that can characterize OB emulsions and monitor their time domain fingerprints (spectrum peaks) of chemical and structural changes during the oxidation process. The ¹H LF-NMR analysis were further supported and correlated with conventional peroxide value test, self-diffusion, droplet size distribution, zeta potential estimation of surface stability, and gas chromatography–mass spectrometry analysis of fatty acid profile changes under thermal oxidation conditions. The 1D and 2D LF-NMR relaxation spectra showed that the LSE and LSFE did not suffer intense oxidation process, due to PUFA assembly in OB oxidative protection. These results were further confirmed by the supportive analytical methodologies. The results of this study demonstrate the efficacy of ¹H LF-NMR methodology to monitor PUFA's rich oil and emulsion thermal oxidation.     

Industry evaluation of the Requirements Abstraction Model

Software requirements are often formulated on different levels and hence they are difficult to compare to each other. To address this issue, a model that allows for placing requirements on different levels has been developed. The model supports both abstraction and refinement of requirements, and hence requirements can both be compared with each other and to product strategies. Comparison between requirements will allow for prioritization of requirements, which in many cases is impossible if the requirements are described on different abstraction levels. Comparison to product strategies will enable early and systematic acceptance or dismissal of requirements, minimizing the risk for overloading. This paper presents an industrial evaluation of the model. It has been evaluated in two different companies, and the experiences and findings are presented. It is concluded that the requirements abstraction model provides helpful improvements to the industrial requirements engineering process.

Is MT translation? Reflections on a recent assault

This essay discusses the claims made by Hofstadter (1997) that machine translation research, as a result of its commercial aims, is based on a ‘pure content’ view of language, which is unrealistic even for specialized domains. The paper argues that this simplified view of language and translation cannot be blamed solely on industrial research; it is a tenet of basic research MT as well, and one that MT shares with much of AI. The question of whether there is a fundamental difference between narrow domain and general translation is discussed in the light of Melby's (1995) notion of a ‘wall’ between terms and general vocabulary.