Working Arrangements of Fruit and Vegetable Processing Cooperatives

Organization and operations of nine working arrangements developed by fruit and vegetable processing cooperatives are described and evaluated. Three distinct approaches are identified - contractual agreement, affiliation through membership status, and formation of separate business entity. The specific structure and functions of joint undertakings reflect the needs and preferences of the participants. Benefits perceived in the cases cited included scale economies in processing and marketing, capital cost avoidance, product diversification, assured commodity supply, and enhanced market entry.Fruit and vegetable cooperatives, joint ventures, contractual agreements, marketing services, processing services, Agribusiness,

Graphs, Friends and Acquaintances

As is well known, a graph is a mathematical object modeling the existence of a certain relation between pairs of elements of a given set. Therefore, it is not surprising that many of the first results concerning graphs made reference to relationships between people or groups of people. In this article, we comment on four results of this kind, which are related to various general theories on graphs and their applications: the Handshake lemma (related to graph colorings and Boolean algebra), a lemma on known and unknown people at a cocktail party (to Ramsey theory), a theorem on friends in common (to distanceregularity and coding theory), and Hall’s Marriage theorem (to the theory of networks). These four areas of graph theory, often with problems which are easy to state but difficult to solve, are extensively developed and currently give rise to much research work. As examples of representative problems and results of these areas, which are discussed in this paper, we may cite the following: the Four Colors Theorem (4CTC), the Ramsey numbers, problems of the existence of distance-regular graphs and completely regular codes, and finally the study of topological proprieties of interconnection networks.Preprin

FPGA based Speech Separation using IPD Features

The problem of speaker separation is an established field in science and goes back to the cocktail party problem defined in 1953. For decades, methods have been improved and developed, but the computational complexity is rarely considered just as the possibility to use hardware acceleration mechanisms. For this reason, this paper addresses the research question: how speaker separation can be realized on embedded systems by exploiting parallelization and intelligent hardware/software partitioning. For this purpose, a concept is described which uses an FPGA for parallelization to separate a speech signal from an intended direction providing a constant throughput rate. The implementation results show the independence of FPGA resources except BRAM size, proving the scalability of the concept, just as the real-time capabilities

Distance-generalized Core Decomposition

The $k$-core of a graph is defined as the maximal subgraph in which every vertex is connected to at least $k$ other vertices within that subgraph. In this work we introduce a distance-based generalization of the notion of $k$-core, which we refer to as the $(k,h)$-core, i.e., the maximal subgraph in which every vertex has at least $k$ other vertices at distance $\leq h$ within that subgraph. We study the properties of the $(k,h)$-core showing that it preserves many of the nice features of the classic core decomposition (e.g., its connection with the notion of distance-generalized chromatic number) and it preserves its usefulness to speed-up or approximate distance-generalized notions of dense structures, such as $h$-club. Computing the distance-generalized core decomposition over large networks is intrinsically complex. However, by exploiting clever upper and lower bounds we can partition the computation in a set of totally independent subcomputations, opening the door to top-down exploration and to multithreading, and thus achieving an efficient algorithm

Online source separation in reverberant environments exploiting known speaker locations

This thesis concerns blind source separation techniques using second order statistics and higher order statistics for reverberant environments. A focus of the thesis is algorithmic simplicity with a view to the algorithms being implemented in their online forms. The main challenge of blind source separation applications is to handle reverberant acoustic environments; a further complication is changes in the acoustic environment such as when human speakers physically move. A novel time-domain method which utilises a pair of finite impulse response filters is proposed. The method of principle angles is defined which exploits a singular value decomposition for their design. The pair of filters are implemented within a generalised sidelobe canceller structure, thus the method can be considered as a beamforming method which cancels one source. An adaptive filtering stage is then employed to recover the remaining source, by exploiting the output of the beamforming stage as a noise reference. A common approach to blind source separation is to use methods that use higher order statistics such as independent component analysis. When dealing with realistic convolutive audio and speech mixtures, processing in the frequency domain at each frequency bin is required. As a result this introduces the permutation problem, inherent in independent component analysis, across the frequency bins. Independent vector analysis directly addresses this issue by modeling the dependencies between frequency bins, namely making use of a source vector prior. An alternative source prior for real-time (online) natural gradient independent vector analysis is proposed. A Student's t probability density function is known to be more suited for speech sources, due to its heavier tails, and is incorporated into a real-time version of natural gradient independent vector analysis. The final algorithm is realised as a real-time embedded application on a floating point Texas Instruments digital signal processor platform. Moving sources, along with reverberant environments, cause significant problems in realistic source separation systems as mixing filters become time variant. A method which employs the pair of cancellation filters, is proposed to cancel one source coupled with an online natural gradient independent vector analysis technique to improve average separation performance in the context of step-wise moving sources. This addresses `dips' in performance when sources move. Results show the average convergence time of the performance parameters is improved. Online methods introduced in thesis are tested using impulse responses measured in reverberant environments, demonstrating their robustness and are shown to perform better than established methods in a variety of situations

A binaural grouping model for predicting speech intelligibility in multitalker environments

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model.R01 DC000100 - NIDCD NIH HH

Auditory Cortical Contrast Enhancing by Global Winner-Take-All Inhibitory Interactions

Brains decompose the world into discrete objects of perception, thereby facing the problem of how to segregate and selectively address similar objects that are concurrently present in a scene. Theoretical models propose that this could be achieved by neuronal implementations of so-called winner-take-all algorithms where neuronal representations of objects or object features interact in a competitive manner. Here we present evidence for the existence of such a mechanism in an animal species. We present electrophysiological, neuropharmacological and neuroanatomical data which suggest a novel view of the role of GABAA-mediated inhibition in primary auditory cortex (AI), where intracortical GABAA-mediated inhibition operates on a global scale within a circular map of sound periodicity representation in AI, with functionally inhibitory projections of similar effect from any location throughout the whole map. These interactions could underlie the proposed competitive “winner-take-all” algorithm to support object segregation, e.g., segregation of different speakers in cocktail-party situations

The Rise and Fall of Tri Valley Growers Cooperative

This paper examines the market and organizational factors that led to the bankruptcy in July 2000 of Tri Valley Growers (TVG), a California tomato- and fruit-processing cooperative owned by more than 500 growers. TVG’s bankruptcy was caused by a confluence of organizational and market-related factors including a low productivity of assets due to high inventory levels and obsolete facilities, high operating costs relative to competition, high raw product transport costs due to the geographic mismatch of production and processing capacity, particularly in tomato operations, and a poor information system. TVG was also highly leveraged. Re-organization as a new-generation cooperative in 1996 failed to stabilize the equity base.Agribusiness,