THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

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

The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling technologies, protocols, and applications. Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant protocols and application issues to enable researchers and application developers to get up to speed quickly on how the different protocols fit together to deliver desired functionalities without having to go through RFCs and the standards specifications. We also provide an overview of some of the key IoT challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and other emerging technologies including big data analytics and cloud and fog computing. We also present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different protocols presented in the paper fit together to deliver desired IoT services.

Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications

An often heard critique on the use of ICT in a heritage context is the individualized nature of the experience. Group communication is an important aspect within a cultural experience, because it can encourage participants to interact with one another and to stimulate each other. Another aspect of great importance is the blending in of the virtual and the real achieved by using context based information to provide relevant information and services to the user. Nowadays, there is no square and ready solution for the transferring of context information and visitor related data. There is a clear need for a high-level network architecture, reusable for the mobile opening up of historical heritage locations. In this paper we present such an architecture, which will be mapped to a specific heritage site. We also focus on the location info collection of the users, which makes it possible to create location-aware services. Therefore, we implemented and evaluated a location determination system containing three algorithm classes which use receiver signal strength information to infer locations.

Location-based service enabling platform for cultural heritage environments

When planning how to roll out a new network or extend an existing one, the operator has several possibilities for minimizing the costs. A first approach is to optimize the introduction time of new switching equipment (e.g. OXC) in the network, considering the estimated traffic-growth and evolution of the equipment-cost. We study the costs of a network-wide migration of introducing OXCs at a single point in time, as well as a so-called island-based migration in which the OXCs are introduced gradually. Another approach is to find the most economical way to realize the bandwidth in the network. There is the possibility to lease dark fiber on a per year basis or to acquire fiber via an IRU (Indefeasible Right of Use) for a longer period. We compare the total cost for dark fiber with the cost for leased wavelengths. In the case-studies, we use a planning period of multiple years.

https://biblio.ugent.be/publication/331596/file/563797.pdf

Techno-economical optimizations in optical backbone networks

The work described here was aimed towards high efficiency light emitting diodes (LEDs), thereby compromising on directionality and narrow spectrum At present our efforts have yielded devices which have an external quantum efficiency (QE) of over 22% This is believed to be a record QE for planar LEDs This result relies on both careful design and material growth For the design we developed a simulation tool which proves useful in selecting interesting structures and interpreting experimental results The theoretical analysis includes the guided modes, reabsorption of light by the active material and subsequent photon recycling The material is grown with MOVPE, which yields high quality material as well as allowing excellent control over layer thickness and composition In the first part we highlight the main characteristics of the theoretical model and deal with some key issues in the design of high efficiency microcavity LEDs (MCLEDs) In part two the main experimental results are discussed (6 pages)

High Efficiency Microcavity LEDs

Tourist beaches on the southern coast of Turkey are surveyed in order to facilitate a standardised fuzzy approach to be used in litter prediction and to assess the aesthetic state of the coastal environment for monitoring programs. During these surveys the number of litter items on beaches were counted and recorded in different categories. The main source of litter on beaches was determined as “beach users”. A fuzzy system was developed to predict the classification of the beaches, since uncertainty was generally inherent in beach work due to the high variability of beach characteristics and the sources of litter categories. This resulted in effective utilization of “the judgment and knowledge of beach users” in the evaluation of beach gradings.

/pdf/computational-complexity-and-distributed-execution-in-water-golf69n7b1.pdf

Computational complexity and distributed execution in water quality management

Despite the fact that many electronic devices are equipped with wireless interfaces and a lot of publications on wireless ad hoc and mesh networking exist, these networks are seldom used in our everyday life. A possible explanation is the fact that only few of the numerous theoretically promising proposals lead to practical solutions on real systems. Currently, wireless network design is mostly approached from a purely theoretical angle. In this paper, common theoretical assumptions are challenged and disproved, and key problems that are faced when putting theory to practice are determined by experiment. We show how these problems can be mitigated, and motivate why a heterogeneous hierarchical wireless mesh architecture can help in making wireless ad hoc networking a reality.

https://biblio.ugent.be/publication/389099/file/584845.PDF

Piet Demeester

Papers

Location-based service enabling platform for cultural heritage environments

Techno-economical optimizations in optical backbone networks

High Efficiency Microcavity LEDs

Computational complexity and distributed execution in water quality management

Problems when realizing ad hoc networks: how a hierarchical architecture can help