There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

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

Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

Survey of Wireless Indoor Positioning Techniques and Systems

The PASCAL Visual Object Classes Challenge

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

This study aims to advance hardware-level computations for travel-time tomography applications in which the wavelength is close to the diameter of the information that has to be recovered. Such can be the case, for example, in the imaging applications of (1) biomedical physics, (2) astro-geophysics and (3) civil engineering. Our aim is to shed light on the effect of that preprocessing the digital waveform signal has on the inversion results and to find computational solutions that guarantee robust inversion when there are incomplete and/or noisy measurements. We describe a hardware-level implementation for integrated and thresholded travel-time computation (ITT and TTT). We compare the ITT and TTT approaches in inversion analysis with experimental acoustic travel-time data recorded using a ring geometry for the transmission and measurement points. The results obtained suggest that ITT is essential for maintaining the robustness of the inversion with imperfect signal digitization and sparsity. In order to ensure the relevance of the results, the specifications of the test setup were related to those of applications (1)-(3).

The effect of hardware-computed travel-time on localization accuracy in the inversion of experimental (acoustic) waveform data

This paper describes a demonstration setup to visualize dynamic resource allocation for real-time HEVC encoding services in FPGA-accelerated cloud. The demonstrated application is Kvazaar HEVC intra encoder, whose functionality is partitioned between FPGAs and processors. During the demonstration, several encoding services can be invoked with requests to the resource manager, which is responsible for allocation, deallocation, and load balancing of resources in the network. The manager provides JSON data to the visualizer, which uses D3 JavaScript library to visualize 1) the physical network structure; 2) running services; and 3) performance of the network elements. This interactive demonstration allows users to request new video streams, view the encoded streams, observe the visualization of the network and services, and manually turn on/off resources to test the robustness of the system.

Visualization of Dynamic Resource Allocation for HEVC Encoding in FPGA-Accelerated SDN Cloud

This paper summarizes a low-complexity rate-distortion optimization (RDO) scheme for Kvazaar HEVC intra encoder (github.com/ultravideo/kvazaar). Our work particularly addresses RDO quantization (RDOQ) since it is the most complex intra coding tool taking almost 60% of the Kvazaar complexity.

Rate-Distortion-Complexity Optimized Coding Scheme for Kvazaar HEVC Intra Encoder

Recent development of wireless communication systems and standards is characterized by constant increase of allocated spectrum resources. Since lower frequency ranges cannot provide sufficient amount of bandwidth, new bands are allocated at higher frequencies, for which operators might resort for deploying more base stations to ensure the same coverage. Connecting increased number of base stations to the backhaul network with wired connections becomes a non-trivial task and requires more capital investments. To overcome this challenge, it is possible to consider relaying technologies and in particular multi-hop relays for higher operating frequency ranges. However, multi-hop relays become more complex in deployment and configuration as several different options exist on where to deploy them and how to partition frame resources.

Simulation and performance analysis of frame structures for multi-hop relay systems

Keynotes.- Reconfigurable Platform for Digital Convergence Terminals.- European Research in Embedded Systems.- System Design and Modeling.- Interface Overheads in Embedded Multimedia Software.- A UML Profile for Asynchronous Hardware Design.- Automated Distribution of UML 2.0 Designed Applications to a Configurable Multiprocessor Platform.- Towards a Transformation Chain Modeling Language.- Key Research Challenges for Successfully Applying MDD Within Real-Time Embedded Software Development.- Domain-Specific Modeling of Power Aware Distributed Real-Time Embedded Systems.- Mining Dynamic Document Spaces with Massively Parallel Embedded Processors.- Efficient Automated Clock Gating Using CoDeL.- An Optimization Methodology for Memory Allocation and Task Scheduling in SoCs Via Linear Programming.- Wireless Sensor Networks.- Designing Wireless Sensor Nodes.- Design, Implementation, and Experiments on Outdoor Deployment of Wireless Sensor Network for Environmental Monitoring.- LATONA: An Advanced Server Architecture for Ubiquitous Sensor Network.- An Approach for the Reduction of Power Consumption in Sensor Nodes of Wireless Sensor Networks: Case Analysis of Mica2.- Energy-Driven Partitioning of Signal Processing Algorithms in Sensor Networks.- Preamble Sense Multiple Access (PSMA) for Impulse Radio Ultra Wideband Sensor Networks.- Security in Wireless Sensor Networks: Considerations and Experiments.- On Security of PAN Wireless Systems.- Processor Design.- Code Size Reduction by Compiler Tuning.- Energy Optimization of a Multi-bank Main Memory.- Probabilistic Modelling and Evaluation of Soft Real-Time Embedded Systems.- Hybrid Functional and Instruction Level Power Modeling for Embedded Processors.- Low-Power, High-Performance TTA Processor for 1024-Point Fast Fourier Transform.- Software Pipelining Support for Transport Triggered Architecture Processors.- SAD Prefetching for MPEG4 Using Flux Caches.- Effects of Program Compression.- Integrated Instruction Scheduling and Fine-Grain Register Allocation for Embedded Processors.- Compilation and Simulation Tool Chain for Memory Aware Energy Optimizations.- A Scalable, Multi-thread, Multi-issue Array Processor Architecture for DSP Applications Based on Extended Tomasulo Scheme.- Reducing Execution Unit Leakage Power in Embedded Processors.- Memory Architecture Evaluation for Video Encoding on Enhanced Embedded Processors.- Advantages of Java Processors in Cache Performance and Power for Embedded Applications.- Dependable Computing.- CARROT - A Tool for Fast and Accurate Soft Error Rate Estimation.- A Scheduling Strategy for a Real-Time Dependable Organic Middleware.- Autonomous Construction Technology of Community for Achieving High Assurance Service.- Preventing Denial-of-Service Attacks in Shared CMP Caches.- Architectures and Implementations.- A Method for Router Table Compression for Application Specific Routing in Mesh Topology NoC Architectures.- Real-Time Embedded System for Rear-View Mirror Overtaking Car Monitoring.- Design of Asynchronous Embedded Processor with New Ternary Data Encoding Scheme.- Hardware-Based IP Lookup Using n-Way Set Associative Memory and LPM Comparator.- A Flash File System to Support Fast Mounting for NAND Flash Memory Based Embedded Systems.- Rescheduling for Optimized SHA-1 Calculation.- Software Implementation of WiMAX on the Sandbridge SandBlaster Platform.- High-Radix Addition and Multiplication in the Electron Counting Paradigm Using Single Electron Tunneling Technology.- Area, Delay, and Power Characteristics of Standard-Cell Implementations of the AES S-Box.- Embedded Sensor Systems.- Integrated Microsystems in Industrial Applications.- A Solid-State 2-D Wind Sensor.- Fault-Tolerant Bus System for Airbag Sensors and Actuators.

Embedded computer systems : architectures, modeling, and simulation : 6th International Workshop, SAMOS 2006 Samos, Greece, July 17-20, 2006 : proceedings

Timo Hämäläinen

Papers

The effect of hardware-computed travel-time on localization accuracy in the inversion of experimental (acoustic) waveform data

Visualization of Dynamic Resource Allocation for HEVC Encoding in FPGA-Accelerated SDN Cloud

Rate-Distortion-Complexity Optimized Coding Scheme for Kvazaar HEVC Intra Encoder

Simulation and performance analysis of frame structures for multi-hop relay systems

Embedded computer systems : architectures, modeling, and simulation : 6th International Workshop, SAMOS 2006 Samos, Greece, July 17-20, 2006 : proceedings