Jari Yli-Hietanen

Low-complexity angle of arrival estimation of wideband signals using small arrays

When the signal to noise ratio is relatively high, the angle of arrival of the strongest signal can be estimated with a very simple method and a small 3D sensor array. The differences in the arrival times of the wideband signal received by spatially separated sensors are estimated using the polarity coincidence correlation. These time differences, i.e. time delays, determine the angle of arrival. In this paper the effects of quantization of the time delays are studied. It is found out that this simple method gives comparable performance to the conventional direct correlation based methods in the case of a relatively high signal to noise ratio.

Toward Reflective Management of Emergency Department Chief Complaint Information

An approach coined as ldquoreflective information managementrdquo is presented as a technique for the management of emergency department chief complaint information. The architecture of a system integrating principles from this approach is described and its performance is evaluated in providing categorical information from free-text chief complaints for use, e.g., in automated syndromic surveillance.

Mathematical Modeling in Systems Biology

In this opinion paper we describe how mathematical models can serve as the foundation for communication within multidisciplinary research teams by providing a useful joint context. First we consider the role of mathematical modeling in systems biology in the light of our experiences in cancer research and other biological disciplines in the realm of big data. We examine the methodologies of machine learning, observing the differences between the modeling approach and the black box approach. Next, we consider the role of mathematical models in natural sciences, observing three simultaneous goals: prediction, knowledge accumulation, and communication. Finally, we consider the differences of the pathway model and the attractor model in describing genetic networks, and explore the long-standing criticality hypothesis, discussing its value in multidisciplinary research.

Domain-specific analytical language modeling--the chief complaint as a case study.

PURPOSE A large share of the information in electronic medical records (EMRs) consists of free-text compositions. From a computational point-of-view, the continuing prevalence of free-text entry is a major hindrance when the goal is to increase automation in EMRs. However, the efforts in developing standards for the structured representation of medical information have not proven to be a panacea. The information space of clinical medicine is very diverse and constantly evolving, making it challenging to develop standards for the domain. This paper reports a study aiming to increase automation in the EMR through the computational understanding of specific class of medical text in English, namely emergency department chief complaints. METHODS We apply domain-specific analytical modeling for the computational understanding of chief complaints. We evaluate the performance of this approach in the automatic classification of chief complaints, e.g., for use in automatic syndromic surveillance. RESULTS The evaluation in a multi-hospital setting showed that the presented algorithm was accurate in terms of classification correctness. Also, use of approximate matching in the algorithm to cope with typographic variance did not affect classification correctness while increasing classification completeness.

Cancer research in the era of next-generation sequencing and big data calls for intelligent modeling

We examine the role of big data and machine learning in cancer research. We describe an example in cancer research where gene-level data from The Cancer Genome Atlas (TCGA) consortium is interpreted using a pathway-level model. As the complexity of computational models increases, their sample requirements grow exponentially. This growth stems from the fact that the number of combinations of variables grows exponentially as the number of variables increases. Thus, a large sample size is needed. The number of variables in a computational model can be reduced by incorporating biological knowledge. One particularly successful way of doing this is by using available gene regulatory, signaling, metabolic, or context-specific pathway information. We conclude that the incorporation of existing biological knowledge is essential for the progress in using big data for cancer research.

Open Information Management: Applications of Interconnectivity and Collaboration

Contemporary digital tools have revolutionized the storing, transfer, and processing of information management. Open Information Management: Applications of Interconnectivity and Collaboration provides a practical-level reference discussing the impact of emerging trends in information technology towards solutions capable of managing information within open, principally unbounded, operational environments. This book can be utilized in advanced courses in knowledge management, information technology, and business education, and also serve as an excellent addition to library reference sections and research collections.

Analysis of robust time-delay based angle-of-arrival estimation methods

The use of small sensor arrays in modern signal processing systems has recently become more common due to the increase in computational processing power and growing interest in intelligent sensing and surveillance. In this paper we address the analysis of robust time-delay based angle-of-arrival (AOA) estimation methods. It is often difficult to compare different robust methods using analytical measures. This is because the robustness of the algorithms is usually achieved by applying some nonlinear signal processing methods. Thus, another approach is proposed which is based on the distributions of the error in the AOA estimate given the distribution of the time-delay-estimates (TDE).

Natural Language and Biological Information Processing

Our ability to use natural language to communicate and co-operate with others is one of the defining characteristics of human intelligence. Much work has been put into developing theories which would explain the structure of language and how it relates to the information processing capabilities of the human mind. In this chapter we philosophically discuss natural language faculty as a being a mechanism conveying embodied information and natural language as such information.

Experiences from the Architectural Migration of a Joint Replacement Surgery Information System

The goal of this study is to present the experiences gathered from the migration of an existing and deployed joint replacement surgery information system from a classical 2-tier architecture to a 4-tier architecture. These include discussion on the motivation for the migration and on the technical benefits of the chosen technical migration path and an evaluation of user experiences. The results from the analysis of clinical end-user and administrator experiences show an increase in the perceived performance and maintainability of the system and a high level of acceptance for the new system version.

Reflective Information Management in the Dissemination of Health Care Practices

The compounding advances in medical science and clinical practice create a need to develop efficient means of disseminating the resulting knowledge to and from all facets and levels of health care. We discuss the use of an approach coined as reflective information management in increasing efficiency in this domain