Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Computing Fourier Transforms and Convolutions on the 2-Sphere

The history and fundamentals of distributed arithmetic (DA) are presented. Ways to increase the speed of DA multiplication are described. DA is applied to a biquadratic digital filter, providing an example of vector dot-product and vector-matrix-product mechanization. Applications to transformers and nonlinear and/or nonstationary processing with DA are discussed. It is seen that DA is a very efficient means to mechanize computations that are dominated by inner products. >

Applications of distributed arithmetic to digital signal processing: a tutorial review

Purpose




The purpose of this paper is to present a methodology to analyze the risks present in perishable food supply chain and to determine the most effective risk mitigation strategies. It is achieved by understanding the dynamics between various risks in perishable food supply chain and modeling them using interpretive structural modeling (ISM).




Design/methodology/approach




Four categories and 17 types of risk are established from literature and conducting brainstorming sessions with managers/engineers in Indian dairy firms. A methodology is proposed using ISM, risk priority number and risk mitigation number to prioritize risk mitigation strategy decisions for the dairy industry.




Findings




For a perishable food supply chain, risk positioned at lower levels (levels 1 or 2) in the hierarchy should be targeted first, while formulating mitigation strategies. To investigate further, risk- enabling factors which are identified for an Indian dairy firm for these levels 1 and 2 risks and mitigation strategy prioritization show that supplier side risks are more dominant followed by market risks and process risks.




Research limitations/implications




This proposed methodology has not been statistically validated or empirically tested, and factors taken are in the Indian context, but the authors believe that the study is highly relevant to other markets as well because the ISM-based analysis is for generic perishable food supply chain environment.




Practical implications




This study provides a useful approach to managers/decision makers to identify, analyze and prioritize risk in the supply chain. It also provides insights into the mutual relationships of supply chain risks which would help them to focus on the effective risk mitigation strategies formulation. The study provides the insights to benchmark and risk management in the dairy industry environment with priority considerations.




Originality/value




This paper provides an integrated approach to identifying, quantify, analyze, evaluate and mitigate the risks of perishable food (in the dairy environment) in the Indian context.

Risk analysis and mitigation for perishable food supply chain: a case of dairy industry

This paper presents an efficient ear recognition technique which derives benefits from the local features of the ear and attempt to handle the problems due to pose, poor contrast, change in illumination and lack of registration. It uses (1) three image enhancement techniques in parallel to neutralize the effect of poor contrast, noise and illumination, (2) a local feature extraction technique (SURF) on enhanced images to minimize the effect of pose variations and poor image registration. SURF feature extraction is carried out on enhanced images to obtain three sets of local features, one for each enhanced image. Three nearest neighbor classifiers are trained on these three sets of features. Matching scores generated by all three classifiers are fused for final decision. The technique has been evaluated on two public databases, namely IIT Kanpur ear database and University of Notre Dame ear database (Collections E). Experimental results confirm that the use of proposed fusion significantly improves the recognition accuracy.

/pdf/an-efficient-ear-recognition-technique-invariant-to-2m4ey3xvt2.pdf

An efficient ear recognition technique invariant to illumination and pose

Purpose




The research on supply chain risk management (SCRM) is visibly on the rise, although its literature still lacks the state of the art that critically analyzes its content. The SCRM literature seems to require studies that utilize risk typology, sources of risk, etc. for reviewing the topic. The purpose of this paper is to bridge the gap by synthesizing the information obtained from 343 articles across 85 journals. This study also presents a critical analysis of the content of SCRM in a structured manner to identify the directions for future research.




Design/methodology/approach




A systematic literature review (SLR) was devised and adopted, which involved the selection, classification, and evaluation of 343 research articles published over a period of 11 years (2004-2014). The content of extant SCRM literature was critically analyzed and synthesized from the perspective of the risk management process (RMP).




Findings




The analysis of extant literature shows that there is a marked rise in research in the SCRM area, especially after the year 2005. It was observed that not only risk but also different forms of uncertainties make supply chain (SC) operations difficult to manage. The SCRM actions yielded most benefits when their implementation was at chain or network level and managed strategically. The analysis also reveals that the manufacturing sector is most affected by risks and highly investigated by researchers.




Practical implications




A complete process for SCRM based on risk stratification, objectives of risk management, and RMP will be a guiding model for firms to manage risks. The research gaps identified and future directions provided here will encourage researchers and managers to devise new methods, tools, and techniques to address the risks in modern SC operations.




Originality/value




An SLR and risk-based content classification of SCRM literature were performed. To identify, locate, select, and analyze the SCRM literature, a structured and systematic process was adopted with some very rarely used methods such as two levels of search keywords, and strings were formulated to locate the most relevant articles in major academic databases.

A critical analysis of supply chain risk management content: a structured literature review

Closed loop supply chain network design (CL-SCND) is a critical economic and environmental activity. The closing of the loop to handle return, uncertainty in business environment, various supply chain risks, impact network design processes and performance of the firm in the long term. Thus, it is important to design robust and reliable supply chain structures and obtain network configurations which can always outperform the other configurations under the worst cases of risks and uncertainty. A generic closed-loop supply chain network based on mixed integer programming formulation is proposed with direct shipping to the customer from manufacturing plants as well as shipping through distribution centers under supply risks, transportation risk and uncertain demand using a robust optimization (RO) approach. A large number of numerical tests are carried out to test the performance of the model by considering a total of four levels of uncertainty for four different network structures types. The results of the tests confirm that the risk and uncertainty based integrated supply chain network models are more efficient (cost effective) than the other set of network configurations which treats the supply chain risks and uncertainty post-ante. To demonstrate the applicability of the proposed model, the case of an Indian e-commerce firm which wants to redesign its supply chain structure is presented. The results of case study show that the topology obtained from integrated treatment of risk and uncertainty called as RORU model, outperform other supply chain networks on various network performance indicators such as supply chain costs, the number of facilities open or close and the amount of products flowing through supply chain echelon. Thus, RO based mathematical modeling to address risks and its applicability for SCND for close loop supply chain is proposed, demonstrated and applied in practical cases.

Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach

https://www.cse.iitk.ac.in/users/psurya/papers/[2012_IVC]_preprint.pdf

Surya Prakash

Papers

Risk analysis and mitigation for perishable food supply chain: a case of dairy industry

An efficient ear recognition technique invariant to illumination and pose

A critical analysis of supply chain risk management content: a structured literature review

Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach

An efficient ear localization technique