A Computational Model for Processing Lexical Information"

The group analysed some syntactic and phonological phenomena that presuppose the existence of interrelated components within the lexicon, which motivate the assumption that there are some sublexicons within the global lexicon of a speaker. This result is confirmed by experimental findings in neurolinguistics. Hungarian speaking agrammatic aphasics were tested in several ways, the results showing that the sublexicon of closed-class lexical items provides a highly automated complex device for processing surface sentence structure. Analysing Hungarian ellipsis data from a semantic-syntactic aspect, the group established that the lexicon is best conceived of being as split into at least two main sublexicons: the store of semantic-syntactic feature bundles and a separate store of sound forms. On this basis they proposed a format for representing open-class lexical items whose meanings are connected via certain semantic relations. They also proposed a new classification of verbs to account for the contribution of the aspectual reading of the sentence depending on the referential type of the argument, and a new account of the syntactic and semantic behaviour of aspectual prefixes. The partitioned sets of lexical items are sublexicons on phonological grounds. These sublexicons differ in terms of phonotactic grammaticality. The degrees of phonotactic grammaticality are tied up with the problem of psychological reality, of how many degrees of this native speakers are sensitive to. The group developed a hierarchical construction network as an extension of the original General Inheritance Network formalism and this framework was then used as a platform for the implementation of the grammar fragments.

Immigrants in the Czech Republic (With Special Reference to Ukrainian Workers and "Western" Firms Operating in Prague)

International migration has increased rapidly in the Czech Republic, with more than 150,000 legally registered foreign residents at the end of 1996. A large proportion of these are in Prague - 35% of the total in December 1996. The aim of this project was to enrich the fund of information concerning the "environment", reasons and "mechanisms" behind immigration to the Czech Republic. Mr. Drbohlav looked first at the empirical situation and on this basis set out to test certain well-known migration theories. He focused on four main areas: 1) a detailed description and explanation of the stock of foreign citizens legally settled in Czech territory, concentrating particularly on "economic" migrants; 2) a questionnaire survey targeting a total of 192 Ukrainian workers (98 in the fall 1995 and 94 in the fall 1996) working in Prague or its vicinity; 3) a second questionnaire survey of 40 "western" firms (20 in 1996 and 20 in 1997) operating out of Prague; 4) an opinion poll on how the Czech population reacts to foreign workers in the CR. Over 80% of economic immigrants at the end of 1996 were from European countries, 16% from Asia and under 2% from North America. The largest single nationalities were Ukrainians, Slovaks, Vietnamese and Poles. There has been a huge increase in the Ukrainian immigrant community over both space (by region) and time (a ten-fold increase since 1993), and at 40,000 persons this represents one third of all legal immigrants. Indications are that many more live and work there illegally. Young males with low educational/skills levels predominate, in contrast with the more heterogeneous immigration from the "West". The primary reason for this migration is the higher wages in the Czech Republic. In 1994 the relative figures of GDP adjusted for parity of purchasing power were US$ 8,095 for the Czech Republic versus US$ 3,330 for the Ukraine as a whole and US$ 1,600 for the Zakarpatye region from which 49% of the respondents in the survey came. On an individual level, the average Czech wage is about US$ 330 per month, while 50% of the Ukrainian respondents put their last monthly wage before leaving for the Czech Republic at under US$ 27. The very low level of unemployment in the latter country (fluctuating around 4%) was also mentioned as an important factor. Migration was seen as a way of diversifying the family's source of income and 49% of the respondents had made their plans together with partners or close relatives, while 45% regularly send remittances to Ukraine (94% do so through friends or relatives). Looking at Ukrainian migration from the point of view of the dual market theory, these migrants' type and conditions of work, work load and earnings were all significantly worse than in the primary sector, which employs well educated people and offers them good earnings, job security and benefits. 53% of respondents were working and/or staying in the Czech Republic illegally at the time of the research, 73% worked as unqualified, unskilled workers or auxiliary workers, 62% worked more than 12 hours a day, and 40% evaluated their working conditions as hard. 51% had no days off, earnings were low in relation to the number of hours worked. and 85% said that their earnings did not increase over time. Nearly half the workers were recruited in Ukraine and only 4% expressed a desire to stay in the Czech Republic. Network theories were also borne out to some extent as 33% of immigrants came together with friends from the same village, town or region in Ukraine. The number who have relatives working in the Czech Republic is rising, and many wish to invite relatives or children to visit them. The presence of organisations which organised cross-border migration, including some which resort to organising illegal documents, also gives some support for the institutional theory. Mr. Drbohlav found that all the migration theories considered offered some insights on the situation, but that none was sufficient to explain it all. He also points out parallels with many other regions of the world, including Central America, South and North America, Melanesia, Indonesia, East Africa, India, the Middle East and Russia. For the survey of foreign and international firms, those chosen were largely from countries represented by more than one company and were mainly active in market services such as financial and trade services, marketing and consulting. While 48% of the firms had more than 10,000 employees spread through many countries, more than two thirds had fewer than 50 employees in the Czech Republic. Czechs formed 80% plus of general staff in these firms although not more than 50% of senior management, and very few other "easterners" were employed. All companies absolutely denied employing people illegally. The average monthly wage of Czech staff was US$ 850, with that of top managers from the firm's "mother country" being US$ 6,350 and that of other western managers US$ 3,410. The foreign staff were generally highly mobile and were rarely accompanied by their families. Most saw their time in the Czech Republic as positive for their careers but very few had any intention of remaining there. Factors in the local situation which were evaluated positively included market opportunities, the economic and political environment, the quality of technical and managerial staff, and cheap labour and low production costs. In contrast, the level of appropriate business ethics and conduct, the attitude of local and regional authorities, environmental production conditions, the legal environment and financial markets and fiscal policy were rated very low. In the final section of his work Mr. Drbohlav looked at the opinions expressed by the local Czech population in a poll carried out at the beginning of 1997. This confirmed that international labour migration has become visible in this country, with 43% of respondents knowing at least one foreigner employed by a Czech firm in this country. Perception differ according to the region from which the workers come and those from "the West" are preferred to those coming from further east. 49% saw their attitude towards the former as friendly but only 20% felt thus towards the latter. Overall, attitudes towards migrant workers is neutral, although 38% said that such workers should not have the same rights as Czech citizens. Sympathy towards foreign workers tends to increase with education and the standard of living, and the relatively positive attitudes towards foreigners in the South Bohemia region contradicted the frequent belief that a lack of experience of international migration lowers positive perceptions of it.

Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations

PURPOSE: There is a need for valid and reliable short scales that can be used to assess social networks and social supports and to screen for social isolation in older persons. DESIGN AND METHODS: The present study is a cross-national and cross-cultural evaluation of the performance of an abbreviated version of the Lubben Social Network Scale (LSNS-6), which was used to screen for social isolation among community-dwelling older adult populations in three European countries. Based on the concept of lack of redundancy of social ties we defined clinical cut-points of the LSNS-6 for identifying persons deemed at risk for social isolation. RESULTS: Among all three samples, the LSNS-6 and two subscales (Family and Friends) demonstrated high levels of internal consistency, stable factor structures, and high correlations with criterion variables. The proposed clinical cut-points showed good convergent validity, and classified 20% of the respondents in Hamburg, 11% of those in Solothurn (Switzerland), and 15% of those in London as at risk for social isolation. IMPLICATIONS: We conclude that abbreviated scales such as the LSNS-6 should be considered for inclusion in practice protocols of gerontological practitioners. Screening older persons based on the LSNS-6 provides quantitative information on their family and friendship ties, and identifies persons at increased risk for social isolation who might benefit from in-depth assessment and targeted interventions.

Information integration and management through the design and construction phases of a project life cycle

Information management is a key aspect of successful construction projects. Having inaccurate measurements and conflicting data can lead to costly mistakes, and vague quantities can ruin estimates and schedules. Building information modeling (BIM) augments a 3D model with a wide variety of information, which reduces many sources of error and can detect conflicts before they occur. Because new technology is often more complex, it can be difficult to effectively integrate it with existing business practices. In this paper, we will answer two questions: How can BIM add value to construction projects? and What lessons can be learned from other companies that use BIM or other similar technology? Previous research focused on the technology as if it were simply a tool, observing problems that occurred while integrating new technology into existing practices. Our research instead looks at the flow of information through a company and its network, seeing all the actors as part of an ecosystem. Building upon this idea, we proposed the metaphor of an information supply chain to illustrate how BIM can add value to a construction project. This paper then concludes with two case studies. The first case study illustrates a failure in the flow of information that could have prevented by using BIM. The second case study profiles a leading design firm that has used BIM products for many years and shows the real benefits of using this program.

Body sensor network for in-home personal healthcare

A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment. The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance.

Tracking a non-cooperative target using a Doppler radar wireless sensor network

Tracking or target localization is used in a wide range of important tasks from knowing when your flight will arrive to ensuring your mail is received on time. Tracking provides the location of resources enabling solutions to complex logistical problems. Wireless Sensor Networks (WSN) create new opportunities when applied to tracking, such as more flexible deployment and real-time information. When radar is used as the sensing element in a tracking WSN better results can be obtained; because radar has a comparatively larger range both in distance and angle to other sensors commonly used in WSNs. This allows for less nodes deployed covering larger areas, saving money. In this report I implement a tracking WSN platform similar to what was developed by Lim, Wang, and Terzis. This consists of several sensor nodes each with a radar, a sink node connected to a host PC, and a Matlab© program to fuse sensor data. I have re-implemented their experiment with my WSN platform for tracking a non-cooperative target to verify their results and also run simulations to compare. The results of these tests are discussed and some future improvements are proposed.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.

BOLD correlates of EEG alpha phase-locking and the fMRI default mode network

Phase locking or synchronization of brain areas is a key concept of information processing in the brain. Synchronous oscillations have been observed and investigated extensively in EEG during the past decades. EEG oscillations occur over a wide frequency range. In EEG, a prominent type of oscillations is alpha-band activity, present typically when a subject is awake, but at rest with closed eyes. The spectral power of alpha rhythms has recently been investigated in simultaneous EEG/fMRI recordings, establishing a wide-range cortico-thalamic network. However, spectral power and synchronization are different measures and little is known about the correlations between BOLD effects and EEG synchronization. Interestingly, the fMRI BOLD signal also displays synchronous oscillations across different brain regions. These oscillations delineate so-called resting state networks (RSNs) that resemble the correlation patterns of simultaneous EEG/fMRI recordings. However, the nature of these BOLD oscillations and their relations to EEG activity is still poorly understood. One hypothesis is that the subunits constituting a specific RSN may be coordinated by different EEG rhythms. In this study we report on evidence for this hypothesis. The BOLD correlates of global EEG synchronization (GFS) in the alpha frequency band are located in brain areas involved in specific RSNs, e.g. the 'default mode network'. Furthermore, our results confirm the hypothesis that specific RSNs are organized by long-range synchronization at least in the alpha frequency band. Finally, we could localize specific areas where the GFS BOLD correlates and the associated RSN overlap. Thus, we claim that not only the spectral dynamics of EEG are important, but also their spatio-temporal organization.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Opportunistic Content-Centric Data Transmission During Short Network Contacts

In this paper, we investigate content-centric data transmission in the context of short opportunistic contacts and base our work on an existing content-centric networking architecture. In case of short interconnection times, file transfers may not be completed and the received information is discarded. Caches in content-centric networks are used for short-term storage and do not guarantee persistence. We implemented a mechanism to extend caching on persistent storage enabling the completion of disrupted content transfers. The mechanisms have been implemented in the CCNx framework and have been evaluated on wireless mesh nodes. Our evaluations using multicast and unicast communication show that the implementation can support content transfers in opportunistic environments without significant processing and storing overhead.

Anticoagulation in primary care - a cross sectional study in 14 heterogeneous countries

Background: New oral anticoagulants (NOACs) are predicted to become the new standard treatment for stroke prevention in patients with atrial fibrillation, and may replace vitamin K antagonists (VKAs). NOACs are prescribed less than expected, even though they do not require international normalised ratio (INR) monitoring. In this study we assessed methods for INR monitoring after the introduction of NOACs a in heterogeneous sample of countries. Methods: We asked representatives of the Vasco da Gama Movement, a network of junior and future gen- eral practitioners (GPs) in Europe, and WONCA, the World Organization of Family Doctors, to describe the way INR is monitored in their respective countries. Results: Representatives of 14 countries responded. In most countries, the INR is monitored by GPs; in some countries, these patients are treated by other specialists or in specialised anticoagulation centres. In only a few countries, anticoagulated patients monitor the INR themselves. Conclusion: Our study showed several strategies for managing anticoagulation in different countries. In most countries, the INR is monitored by GPs. These consultations offer opportunities to address other is- sues, such as blood pressure control or medication adherence. These factors may be considered when de- ciding to switch patients from VKAs to NOACs.