Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.

Min-BDeu and Max-BDeu Scores for Learning Bayesian Networks

This work presents two new score functions based on the Bayesian Dirichlet equivalent uniform (BDeu) score for learning Bayesian network structures. They consider the sensitivity of BDeu to varying parameters of the Dirichlet prior. The scores take on the most adversary and the most beneficial priors among those within a contamination set around the symmetric one. We build these scores in such way that they are decomposable and can be computed efficiently. Because of that, they can be integrated into any state-of-the-art structure learning method that explores the space of directed acyclic graphs and allows decomposable scores. Empirical results suggest that our scores outperform the standard BDeu score in terms of the likelihood of unseen data and in terms of edge discovery with respect to the true network, at least when the training sample size is small. We discuss the relation between these new scores and the accuracy of inferred models. Moreover, our new criteria can be used to identify the amount of data after which learning is saturated, that is, additional data are of little help to improve the resulting model.

Max Weber and the First World War: Protestant and Catholic living standards in Germany, 1914-1919

We assess informal institutions of Protestants and Catholics by investigating their economic resilience in a natural experiment. The First World War constitutes an exogenous shock to living standards since the duration and intensity of the war exceeded all expectations. We assess the ability of Protestant and Catholic communities to cope with increasing food prices and wartime black markets. Literature based on Weber (1904, 1905) suggests that Protestants must be more resilient than their Catholic peers. Using individual height data on some 2,800 Germans to assess levels of malnutrition during the war, we find that living standards for both Protestants and Catholics declined; however, the decrease of Catholics’ height was disproportionately large. Our empirical analysis finds a large statistically significant difference between Protestants and Catholics for the 1915–19 birth cohort, and we argue that this height gap cannot be attributed to socioeconomic background and fertility alone.

Max Weber and the First World War: Protestant and Catholic living standards in Germany, 1915-1919

We assess informal institutions of Protestants and Catholics by investigating their economic
resilience in a natural experiment. The First World War constitutes an exogenous shock to living standards since the duration and intensity of the war exceeded all expectations. We assess the ability of Protestant and Catholic communities to cope with increasing food prices and wartime black markets. Literature based on Weber (1904, 1905) suggests that Protestants must be more resilient than their Catholic peers. Using individual height data on some 2,800 Germans to assess levels of malnutrition during the war, we find that living standards for both Protestants and Catholics declined; however, the decrease of Catholics’ height was disproportionately large. Our empirical analysis finds a large statistically significant difference between Protestants and Catholics for the 1914-19 birth cohort, and we argue that this height gap cannot be attributed to socioeconomic background and fertility alone.

ANNUAL REPORT OF THE State Board of Health OF SOUTH CAROLINA FOR THE PERIOD BEGINNING JULY I, 1943, AND ENDING JUNE 30, 1944

This annual report from the South Carolina State Board of Health includes reports from its various divisions, statistical data concerning health issues and a list of board members.

A comparative study on the modified Max-Log-MAP turbodecoding by extrinsic information scaling

A simple but effective technique to improve the performance of the Max-Log-MAP algorithm is to scale the extrinsic information exchanged between two MAP decoders. A comprehensive analysis of the selection of the scaling factors according to channel conditions and decoding iterations is presented in this paper. Choosing a constant scaling factor for all SNRs and iterations is compared with the best scaling factor selection for changing channel conditions and decoding iterations. It is observed that a constant scaling factor for all channel conditions and decoding iterations is the best solution and provides a 0.2-0.4 dB gain over the standard Max- Log-MAP algorithm. Therefore, a constant scaling factor should be chosen for the best compromise.

The modified Max-Log-MAP turbo decoding algorithm by extrinsic information scaling for wireless applications

The iterative nature of turbo-decoding algorithms increases their complexity compare to conventional FEC decoding algorithms. Two iterative decoding algorithms, Soft-Output-Viterbi Algorithm (SOVA) and Maximum A posteriori Probability (MAP) Algorithm require complex decoding operations over several iteration cycles. So, for real-time implementation of turbo codes, reducing the decoder complexity while preserving bit-error-rate (BER) performance is an important design consideration. In this chapter, a modification to the Max-Log-MAP algorithm is presented. This modification is to scale the extrinsic information exchange between the constituent decoders. The remainder of this chapter is organized as follows: An overview of the turbo encoding and decoding processes, the MAP algorithm and its simplified versions the Log-MAP and Max-Log-MAP algorithms are presented in section 1. The extrinsic information scaling is introduced, simulation results are presented, and the performance of different methods to choose the best scaling factor is discussed in Section 2. Section 3 discusses trends and applications of turbo coding from the perspective of wireless applications.

A Program of Original Compositions, May 6, 1943

Concert Program for A Program of Original Compositions, May 6, 1943

Exploiting a prioritized MAC protocol to efficiently compute min and max in multihop networks

Consider a wireless sensor network (WSN) where a broadcast from a sensor node does not reach all sensor nodes in the network; such networks are often called multihop networks. Sensor nodes take sensor readings but individual sensor readings are not very important. It is important however to compute aggregated quantities of these sensor readings. The minimum and maximum of all sensor readings at an instant are often interesting because they indicate abnormal behavior, for example if the maximum temperature is very high then it may be that a fire has broken out. We propose an algorithm for computing the min or max of sensor reading in a multihop network. This algorithm has the particularly interesting property of having a time complexity that does not depend on the number of sensor nodes; only the network diameter and the range of the value domain of sensor readings matter.

A marketing plan for the ice cream brand Max Adventures in food service

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics