A scalable and efficient approach for obtaining measurements in CAN-Based control systems

The availability of small inexpensive sensor elements enables the employment of large wired or wireless sensor networks for feeding control systems. Unfortunately, the need to transmit a large number of sensor measurements over a network negatively affects the timing parameters of the control loop. This paper presents a solution to this problem by representing sensor measurements with an approximate representation-an interpolation of sensor measurements as a function of space coordinates. A priority-based medium access control (MAC) protocol is used to select the sensor messages with high information content. Thus, the information from a large number of sensor measurements is conveyed within a few messages. This approach greatly reduces the time for obtaining a snapshot of the environment state and therefore supports the real-time requirements of feedback control loops.

Training executive functions in the laboratory and in real life : cognitive consequences of computer-based exercises and bilingualism

The question of the trainability of executive functions and the impact of such training on related cognitive skills has stirred considerable research interest. Despite a number of studies investigating this, the question has not yet been solved. The general aim of this thesis was to investigate two very different types of training of executive functions: laboratory-based computerized training (Studies I-III) and realworld training through bilingualism (Studies IV-V). Bilingualism as a kind of training of executive functions is based on the idea that managing two languages requires executive resources, and previous studies have suggested a bilingual advantage in executive functions. Three executive functions were studied in the present thesis: updating of working memory (WM) contents, inhibition of irrelevant information, and shifting between tasks and mental sets. Studies I-III investigated the effects of computer-based training of WM updating (Study I), inhibition (Study II), and set shifting (Study III) in healthy young adults. All studies showed increased performance on the trained task. More importantly, improvement on an untrained task tapping the trained executive function (near transfer) was seen in Study I and II. None of the three studies showed improvement on untrained tasks tapping some other cognitive function (far transfer) as a result of training. Study I also used PET to investigate the effects of WM updating training on a neurotransmitter closely linked to WM, namely dopamine. The PET results revealed increased striatal dopamine release during WM updating performance as a result of training. Study IV investigated the ability to inhibit task-irrelevant stimuli in bilinguals and monolinguals by using a dichotic listening task. The results showed that the bilinguals exceeded the monolinguals in inhibiting task-irrelevant information. Study V introduced a new, complementary research approach to study the bilingual executive advantage and its underlying mechanisms. To circumvent the methodological problems related to natural groups design, this approach focuses only on bilinguals and examines whether individual differences in bilingual behavior correlate with executive task performances. Using measures that tap the three above-entioned executive functions, the results suggested that more frequent language switching was associated with better set shifting skills, and earlier acquisition of the second language was related to better inhibition skills. In conclusion, the present behavioral results showed that computer-based training of executive functions can improve performance on the trained task and on closely related tasks, but does not yield a more general improvement of cognitive skills. Moreover, the functional neuroimaging results reveal that WM training modulates striatal dopaminergic function, speaking for training-induced neural plasticity in this important neurotransmitter system. With regard to bilingualism, the results provide further support to the idea that bilingualism can enhance executive functions. In addition, the new complementary research approach proposed here provides some clues as to which aspects of everyday bilingual behavior may be related to the advantage in executive functions in bilingual individuals.

Promoting Healthy Lifestyles with Personalized, APOE Genotype Based Health Information: The Effects on Psychological-, Health Behavioral and Clinical Factors

There is an increasing demand for individualized, genotype-based health advice. The general population-based dietary recommendations do not always motivate people to change their life-style, and partly following this, cardiovascular diseases (CVD) are a major cause of death in worldwide. Using genotype-based nutrition and health information (e.g. nutrigenetics) in health education is a relatively new approach, although genetic variation is known to cause individual differences in response to dietary factors. Response to changes in dietary fat quality varies, for example, among different APOE genotypes. Research in this field is challenging, because several non-modifiable (genetic, age, sex) and modifiable (e.g. lifestyle, dietary, physical activity) factors together and with interaction affect the risk of life-style related diseases (e.g. CVD). The other challenge is the psychological factors (e.g. anxiety, threat, stress, motivation, attitude), which also have an effect on health behavior. The genotype-based information is always a very sensitive topic, because it can also cause some negative consequences and feelings (e.g. depression, increased anxiety). The aim of this series of studies was firstly to study how individual, genotype-based health information affects an individual’s health form three aspects, and secondly whether this could be one method in the future to prevent lifestyle-related diseases, such as CVD. The first study concentrated on the psychological effects; the focus of the second study was on health behavior effects, and the third study concentrated on clinical effects. In the fourth study of this series, the focus was on all these three aspects and their associations with each other. The genetic risk and health information was the APOE gene and its effects on CVD. To study the effect of APOE genotype-based health information in prevention of CVD, a total of 151 volunteers attended the baseline assessments (T0), of which 122 healthy adults (aged 20 – 67 y) passed the inclusion criteria and started the one-year intervention. The participants (n = 122) were randomized into a control group (n = 61) and an intervention group (n = 61). There were 21 participants in the intervention Ɛ4+ group (including APOE genotypes 3/4 and 4/4) and 40 participants in the intervention Ɛ4- group (including APOE genotypes 2/3 and 3/3). The control group included 61 participants (including APOE genotypes 3/4, 4/4, 2/3, 3/3 and 2/2). The baseline (T0) and follow-up assessments (T1, T2, T3) included detailed measurements of psychological (threat and anxiety experience, stage of change), and behavioral (dietary fat quality, consumption of vegetables, - high fat/sugar foods and –alcohol, physical activity and health and taste attitudes) and clinical factors (total-, LDL- HDL cholesterol, triglycerides, blood pressure, blood glucose (0h and 2h), body mass index, waist circumference and body fat percentage). During the intervention six different communication sessions (lectures on healthy lifestyle and nutrigenomics, health messages by mail, and personal discussion with the doctor) were arranged. The intervention groups (Ɛ4+ and Ɛ4-) received their APOE genotype information and health message at the beginning of the intervention. The control group received their APOE genotype information after the intervention. For the analyses in this dissertation, the results for 106/107 participants were analyzed. In the intervention, there were 16 participants in the high-risk (Ɛ4+) group and 35 in the low-risk (Ɛ4-) group. The control group had 55 participants in studies III-IV and 56 participants in studies I-II. The intervention had both short-term (≤ 6 months) and long-term (12 months) effects on health behavior and clinical factors. The short-term effects were found in dietary fat quality and waist circumference. Dietary fat quality improved more in the Ɛ4+ group than the Ɛ4- and the control groups as the personal, genotype-based health information and waist circumference lowered more in the Ɛ4+ group compared with the control group. Both these changes differed significantly between the Ɛ4+ and control groups (p<0.05). A long-term effect was found in triglyceride values (p<0.05), which lowered more in Ɛ4+ compared with the control group during the intervention. Short-term effects were also found in the threat experience, which increased mostly in the Ɛ4+ group after the genetic feedback (p<0.05), but it decreased after 12 months, although remaining at a higher level compared to the baseline (T0). In addition, Study IV found that changes in the psychological factors (anxiety and threat experience, motivation), health and taste attitudes, and health behaviors (dietary, alcohol consumption, and physical activity) did not directly explain the changes in triglyceride values and waist circumference. However, change caused by a threat experience may have affected the change in triglycerides through total- and HDL cholesterol. In conclusion, this dissertation study has given some indications that individual, genotypebased health information could be one potential option in the future to prevent lifestyle-related diseases in public health care. The results of this study imply that personal genetic information, based on APOE, may have positive effects on dietary fat quality and some cardiovascular risk markers (e.g., improvement in triglyceride values and waist circumference). This study also suggests that psychological factors (e.g. anxiety and threat experience) may not be an obstacle for healthy people to use genotype-based health information to promote healthy lifestyles. However, even in the case of very personal health information, in order to achieve a permanent health behavior change, it is important to include attitudes and other psychological factors (e.g. motivation), as well as intensive repetition and a longer intervention duration. This research will serve as a basis for future studies and its information can be used to develop targeted interventions, including health information based on genotyping that would aim at preventing lifestyle diseases. People’s interest in personalized health advices has increased, while also the costs of genetic screening have decreased. Therefore, generally speaking, it can be assumed that genetic screening as a part of the prevention of lifestyle-related diseases may become more common in the future. In consequence, more research is required about how to make genetic screening a practical tool in public health care, and how to efficiently achieve long-term changes.

A Document Browsing Tool Based on Book Indexes

This research project is a contribution to the global field of information retrieval, specifically, to develop tools to enable information access in digital documents. We recognize the need to provide the user with flexible access to the contents of large, potentially complex digital documents, with means other than a search function or a handful of metadata elements. The goal is to produce a text browsing tool offering a maximum of information based on a fairly superficial linguistic analysis. We are concerned with a type of extensive single-document indexing, and not indexing by a set of keywords (see Klement, 2002, for a clear distinction between the two). The desired browsing tool would not only give at a glance the main topics discussed in the document, but would also present relationships between these topics. It would also give direct access to the text (via hypertext links to specific passages). The present paper, after reviewing previous research on this and similar topics, discusses the methodology and the main characteristics of a prototype we have devised. Experimental results are presented, as well as an analysis of remaining hurdles and potential applications.

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements

A key based cache replacement policy for cooperative caching in mobile ad hoc networks

Cooperative caching in mobile ad hoc networks aims at improving the efficiency of information access by reducing access latency and bandwidth usage. Cache replacement policy plays a vital role in improving the performance of a cache in a mobile node since it has limited memory. In this paper we propose a new key based cache replacement policy called E-LRU for cooperative caching in ad hoc networks. The proposed scheme for replacement considers the time interval between the recent references, size and consistency as key factors for replacement. Simulation study shows that the proposed replacement policy can significantly improve the cache performance in terms of cache hit ratio and query delay

INFO2009 Group23 CW2 Freedom of Information

the coursework2 for INFO2009 by group23. This resource contains a poster and a questionnaire(web page based).Please access following website for the questionnaire: http://users.ecs.soton.ac.uk/rrs4g10/info2009

Information architecture for healthcare organizations: the case of a NHS Hospital in UK

Healthcare organizations are known for their complex and intense information environment. Healthcare information is facilitated via heterogeneous information systems or paper-based sources. Access to the right information under increasing time pressure is extremely challenging. This paper proposes an information architecture for healthcare organizations. It facilitates the provision of the right information to the right person in the right place and time tailored to their requirements. It adapts an abductive reasoning research approach. Organizational semiotics serves as its theoretical underpinning, guiding the data collection process through direct observation in the ophthalmology outpatient clinics of a UK hospital. It results the norm and information objects that form the information architecture. This is modeled by Archimate. The contribution of the information architecture can be seen from organizational, social and technical perspective. It clearly shows how information is facilitated within a healthcare organization, reducing duplicated data entry, and guiding the future technological implementation.

Estimation of tool pose based on force-density correlation during robotic drilling

The application of image-guided systems with or without support by surgical robots relies on the accuracy of the navigation process, including patient-to-image registration. The surgeon must carry out the procedure based on the information provided by the navigation system, usually without being able to verify its correctness beyond visual inspection. Misleading surrogate parameters such as the fiducial registration error are often used to describe the success of the registration process, while a lack of methods describing the effects of navigation errors, such as those caused by tracking or calibration, may prevent the application of image guidance in certain accuracy-critical interventions. During minimally invasive mastoidectomy for cochlear implantation, a direct tunnel is drilled from the outside of the mastoid to a target on the cochlea based on registration using landmarks solely on the surface of the skull. Using this methodology, it is impossible to detect if the drill is advancing in the correct direction and that injury of the facial nerve will be avoided. To overcome this problem, a tool localization method based on drilling process information is proposed. The algorithm estimates the pose of a robot-guided surgical tool during a drilling task based on the correlation of the observed axial drilling force and the heterogeneous bone density in the mastoid extracted from 3-D image data. We present here one possible implementation of this method tested on ten tunnels drilled into three human cadaver specimens where an average tool localization accuracy of 0.29 mm was observed.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

Mutual Information and Perplexity based Clustering of Dialogue Information for Dynamic Adaptation of Language Models

We present two approaches to cluster dialogue-based information obtained by the speech understanding module and the dialogue manager of a spoken dialogue system. The purpose is to estimate a language model related to each cluster, and use them to dynamically modify the model of the speech recognizer at each dialogue turn. In the first approach we build the cluster tree using local decisions based on a Maximum Normalized Mutual Information criterion. In the second one we take global decisions, based on the optimization of the global perplexity of the combination of the cluster-related LMs. Our experiments show a relative reduction of the word error rate of 15.17%, which helps to improve the performance of the understanding and the dialogue manager modules.

DAEDALUS at PAN 2014: Guessing tweet author's gender and age

This paper describes our participation at PAN 2014 author profiling task. Our idea was to define, develop and evaluate a simple machine learning classifier able to guess the gender and the age of a given user based on his/her texts, which could become part of the solution portfolio of the company. We were interested in finding not the best possible classifier that achieves the highest accuracy, but to find the optimum balance between performance and throughput using the most simple strategy and less dependent of external systems. Results show that our software using Naive Bayes Multinomial with a term vector model representation of the text is ranked quite well among the rest of participants in terms of accuracy.

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.

Cache River Area Assessment /

"Critical Trends Assessment Program."--Cover.

Chicago River/Lake Shore area assessment /

The Chicago River/Lake Shore area assessment, part of a series of statewide regional assessments, examines approximately 348 square miles in northeastern Illinois that falls within portions of two counties-- Cook and Lake. The area is defined by the watershed of the Chicago River and the areas of Cook and Lake counties that drain to Lake Michigan, excluding the area in southern Cook County that drains to the Calumet River. The report provides information on the natural and human resources of the area as a basis for managing and improving its ecosystems. The development of ecosystem-based information and management programs in Illinois are the result of three processes-- the Critical Trends Assessment Program, Conservation Congress, and Water Resources and Land Use Priorities Task Force.