Structure of marketing channels of selected manufacturing industries in Kerala

The study evolved from the basic premise that the existing distribution structure is not adequate or adaptive to meet the needs of the expanding manufacturing sector and the emerging mass market. The hypothised causes of the problem are the following: marketing channels are not used for strategy differentiation by manufacturers: there are too many intermediaries in the channels; the distributive institutions are not adaptive; and there is very little control over the flow of products through the channels. These assumptions about the causes of the problem have been translated into specific hypotheses and tested with data. Empirical analysis, while supporting some of these hypotheses, challenges certain widely held notions. The ensuing summary presents the important findings, in the sequence in which they are discussed in the study.

RRNS-convolutional encoded concatenated code for OFDM based wireless communication

The modern telecommunication industry demands higher capacity networks with high data rate. Orthogonal frequency division multiplexing (OFDM) is a promising technique for high data rate wireless communications at reasonable complexity in wireless channels. OFDM has been adopted for many types of wireless systems like wireless local area networks such as IEEE 802.11a, and digital audio/video broadcasting (DAB/DVB). The proposed research focuses on a concatenated coding scheme that improve the performance of OFDM based wireless communications. It uses a Redundant Residue Number System (RRNS) code as the outer code and a convolutional code as the inner code. The bit error rate (BER) performances of the proposed system under different channel conditions are investigated. These include the effect of additive white Gaussian noise (AWGN), multipath delay spread, peak power clipping and frame start synchronization error. The simulation results show that the proposed RRNS-Convolutional concatenated coding (RCCC) scheme provides significant improvement in the system performance by exploiting the inherent properties of RRNS.

Marketing Channels in Ornamental Fish Trade in West Bengal

A lucrative export market and high domestic demand has made ornamental fish industry in West Bengal a potential source for income generation. The study aimed to identify: (i) the commercially important size groups of main ornamental fish varieties available in the state; (ii) the existing supply chain; (iii) major constraints for development of the industry; (iv) and to anlayse price spread of commercially important varieties; and (v) to evaluate the profitability of operation at different stakeholder levels in the marketing chain. Export market of ornamental fishes in the state followed a single supply channel while three different distribution channels existed in the domestic market. High electricity charges was the major problem faced by breeders (producers/rearers) whereas lack of technical knowledge regarding transportation was the major constraint for wholesalers. Lack of knowledge on proper health management inhibited the growth of retail industry. The fresh water catfish, angel, molly, arowana, gold fish, tetras, and gouramis showed comparatively higher breeders’ share in consumers’ rupee. Wholesalers were earning comparatively higher annual profit than the other stakeholders due to moderate initial investment and also due to the comparatively lower risk involved.

Estimators and Tests based on Likelihood-Depth with Application to Weibull Distribution, Gaussian and Gumbel Copula

In dieser Arbeit werden mithilfe der Likelihood-Tiefen, eingeführt von Mizera und Müller (2004), (ausreißer-)robuste Schätzfunktionen und Tests für den unbekannten Parameter einer stetigen Dichtefunktion entwickelt. Die entwickelten Verfahren werden dann auf drei verschiedene Verteilungen angewandt. Für eindimensionale Parameter wird die Likelihood-Tiefe eines Parameters im Datensatz als das Minimum aus dem Anteil der Daten, für die die Ableitung der Loglikelihood-Funktion nach dem Parameter nicht negativ ist, und dem Anteil der Daten, für die diese Ableitung nicht positiv ist, berechnet. Damit hat der Parameter die größte Tiefe, für den beide Anzahlen gleich groß sind. Dieser wird zunächst als Schätzer gewählt, da die Likelihood-Tiefe ein Maß dafür sein soll, wie gut ein Parameter zum Datensatz passt. Asymptotisch hat der Parameter die größte Tiefe, für den die Wahrscheinlichkeit, dass für eine Beobachtung die Ableitung der Loglikelihood-Funktion nach dem Parameter nicht negativ ist, gleich einhalb ist. Wenn dies für den zu Grunde liegenden Parameter nicht der Fall ist, ist der Schätzer basierend auf der Likelihood-Tiefe verfälscht. In dieser Arbeit wird gezeigt, wie diese Verfälschung korrigiert werden kann sodass die korrigierten Schätzer konsistente Schätzungen bilden. Zur Entwicklung von Tests für den Parameter, wird die von Müller (2005) entwickelte Simplex Likelihood-Tiefe, die eine U-Statistik ist, benutzt. Es zeigt sich, dass für dieselben Verteilungen, für die die Likelihood-Tiefe verfälschte Schätzer liefert, die Simplex Likelihood-Tiefe eine unverfälschte U-Statistik ist. Damit ist insbesondere die asymptotische Verteilung bekannt und es lassen sich Tests für verschiedene Hypothesen formulieren. Die Verschiebung in der Tiefe führt aber für einige Hypothesen zu einer schlechten Güte des zugehörigen Tests. Es werden daher korrigierte Tests eingeführt und Voraussetzungen angegeben, unter denen diese dann konsistent sind. Die Arbeit besteht aus zwei Teilen. Im ersten Teil der Arbeit wird die allgemeine Theorie über die Schätzfunktionen und Tests dargestellt und zudem deren jeweiligen Konsistenz gezeigt. Im zweiten Teil wird die Theorie auf drei verschiedene Verteilungen angewandt: Die Weibull-Verteilung, die Gauß- und die Gumbel-Copula. Damit wird gezeigt, wie die Verfahren des ersten Teils genutzt werden können, um (robuste) konsistente Schätzfunktionen und Tests für den unbekannten Parameter der Verteilung herzuleiten. Insgesamt zeigt sich, dass für die drei Verteilungen mithilfe der Likelihood-Tiefen robuste Schätzfunktionen und Tests gefunden werden können. In unverfälschten Daten sind vorhandene Standardmethoden zum Teil überlegen, jedoch zeigt sich der Vorteil der neuen Methoden in kontaminierten Daten und Daten mit Ausreißern.

An Analysis of the Effect of Gaussian Error in Object Recognition

Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers

The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special cases. In the RBF case, the SV algorithm automatically determines centers, weights and threshold such as to minimize an upper bound on the expected test error. The present study is devoted to an experimental comparison of these machines with a classical approach, where the centers are determined by $k$--means clustering and the weights are found using error backpropagation. We consider three machines, namely a classical RBF machine, an SV machine with Gaussian kernel, and a hybrid system with the centers determined by the SV method and the weights trained by error backpropagation. Our results show that on the US postal service database of handwritten digits, the SV machine achieves the highest test accuracy, followed by the hybrid approach. The SV approach is thus not only theoretically well--founded, but also superior in a practical application.

On Convergence Properties of the EM Algorithm for Gaussian Mixtures

"Expectation-Maximization'' (EM) algorithm and gradient-based approaches for maximum likelihood learning of finite Gaussian mixtures. We show that the EM step in parameter space is obtained from the gradient via a projection matrix $P$, and we provide an explicit expression for the matrix. We then analyze the convergence of EM in terms of special properties of $P$ and provide new results analyzing the effect that $P$ has on the likelihood surface. Based on these mathematical results, we present a comparative discussion of the advantages and disadvantages of EM and other algorithms for the learning of Gaussian mixture models.

"Functional Upregulation of Ca2+ -Activated K+ Channels in the Development of Substantia Nigra Dopamine Neurons"

Many connections in the basal ganglia are made around birth when animals are exposed to a host of new affective, cognitive, and sensori-motor stimuli. It is thought that dopamine modulates cortico-striatal synapses that result in the strengthening of those connections that lead to desired outcomes. We propose that there must be a time before which stimuli cannot be processed into functional connections, otherwise it would imply an effective link between stimulus, response, and reward in uterus. Consistent with these ideas, we present evidence that early in development dopamine neurons are electrically immature and do not produce high-frequency firing in response to salient stimuli. We ask first, what makes dopamine neurons immature? and second, what are the implications of this immaturity for the basal ganglia? As an answer to the first question, we find that at birth the outward current is small (3nS-V), insensitive to Ca2z, TEA, BK, and SK blockers. Rapidly after birth, the outward current increases to 15nS-V and becomes sensitive to Ca2z, TEA, BK, and SK blockers. We make a detailed analysis of the kinetics of the components of the outward currents and produce a model for BK and SK channels that we use to reproduce the outward current, and to infer the geometrical arrangement of BK and Ca2z channels in clusters. In the first cluster, T-type Ca2z and BK channels are coupled within distances of *20 nm (200 A˚). The second cluster consists of L-type Ca2z and BK channels that are spread over distances of at least 60 nm. As for the second question, we propose that early in development, the mechanism of action selection is in a ‘‘locked-in’’ state that would prevent dopamine neurons from reinforcing cortico-striatal synapses that do not have a functional experiential- based value.

Functional Upregulation of Ca2+ -Activated K+ Channels in the Development of Substantia Nigra Dopamine Neurons

Many connections in the basal ganglia are made around birth when animals are exposed to a host of new affective, cognitive, and sensori-motor stimuli. It is thought that dopamine modulates cortico-striatal synapses that result in the strengthening of those connections that lead to desired outcomes. We propose that there must be a time before which stimuli cannot be processed into functional connections, otherwise it would imply an effective link between stimulus, response, and reward in uterus. Consistent with these ideas, we present evidence that early in development dopamine neurons are electrically immature and do not produce high-frequency firing in response to salient stimuli. We ask first, what makes dopamine neurons immature? and second, what are the implications of this immaturity for the basal ganglia? As an answer to the first question, we find that at birth the outward current is small (3nS-V), insensitive to Ca2+, TEA, BK, and SK blockers. Rapidly after birth, the outward current increases to 15nS-V and becomes sensitive to Ca2+, TEA, BK, and SK blockers. We make a detailed analysis of the kinetics of the components of the outward currents and produce a model for BK and SK channels that we use to reproduce the outward current, and to infer the geometrical arrangement of BK and Ca2+ channels in clusters. In the first cluster, T-type Ca2+ and BK channels are coupled within distances of similar to 20 nm (200 parallel to). The second cluster consists of L-type Ca2+ and BK channels that are spread over distances of at least 60 nm. As for the second question, we propose that early in development, the mechanism of action selection is in a "locked-in" state that would prevent dopamine neurons from reinforcing cortico-striatal synapses that do not have a functional experiential-based value.

Changes in heron and egret populations on the Laurentian Great Lakes and connecting channels, 1977-2009

Canadian and U.S. federal wildlife agencies completed four decadal surveys, spanning the years 1977 to 2009, to census colonial waterbirds breeding on the Great Lakes and adjoining bodies of water. In this paper, we reports abundance, distribution, and general population trends of three species: Black-crowned Night-Heron (Nycticorax nycticorax), Great Egret (Ardea alba), and Great Blue Heron (Ardea herodias). Estimates of nest numbers ranged from approximately 4000-6100 for the Black-crowned Night-Heron, 250-1900 for the Great Egret, and 3800-6400 for the Great Blue Heron. Average annual rates of change in nest numbers between the first (1977) and fourth (2008) census were −1% for the Black-crowned Night-Heron, +23% for the Great Egret, and −0.27% for the Great Blue Heron. Across the 30-year census, Black-crowned Night-Heron estimates decreased in U.S. (−57%) but increased (+18%) in Canadian waters, Great Egret nests increased 1381% in Canadian waters with a smaller, but still substantial increase in the number of nests at U.S. colonies (+613%), and Great Blue Heron numbers increased 148% in Canadian waters and 713% in U.S. waters. Although a single factor cannot be clearly linked to changes observed in each species’ distribution, hydrological variation, habitat succession, nest competition with Double-crested Cormorants (Phalacrocorax auritus), and land use changes likely all contributed. Management activities should support both breeding and foraging conditions including restoration of early successional habitats and anticipate continued northward expansions in the distributions of these waterbirds.

The representation of conditional expectations of non-Gaussian noise

For Wiener spaces conditional expectations and $L^{2}$-martingales w.r.t. the natural filtration have a natural representation in terms of chaos expansion. In this note an extension to larger classes of processes is discussed. In particular, it is pointed out that orthogonality of the chaos expansion is not required.