A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

A palaeoecological attempt to classify fire sensitivity of trees in the southern Alps

Using pollen percentages and charcoal influx to reconstruct the Holocene vegetation and fire history, we differentiate six possible responses of plants to fire of medium and high frequency: fire-intolerant, fire damaged, fire-sensitive, fire-indifferent, fire-enhanced and fire-adapted. The fire sensitivity of 17 pollen types, representing 20 woody species in the southern Alps, is validated by comparison with today's ecological studies of plant chronosequences. A surprising coincidence of species reaction to fire of medium frequency is character istic for completely different vegetation types, such as woodlands dominated byAbies alba (7000 years ago) andCastanea sativa (today). The temporal persistence of post-fire behaviour of plant taxa up to thousands of years suggests a generally valid species-related fire sensitivity that may be influenced only in part by changing external conditions. A non-analogous behaviour of woody taxa after fire is documented for high fire frequencies. Divergent behaviour patterns of plant taxa in response to medium and high fire frequencies (e.g., increases and decreases ofAlnus glutinosa) also indicate that post-fire plant reactions may change with increasing fire fre quency.

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (SO2) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of SO2 concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

Unsupervised method to classify PM10 pollutant concentrations

In this paper a method based mainly on Data Fusion and Artificial Neural Networks to classify one of the most important pollutants such as Particulate Matter less than 10 micrometer in diameter (PM10) concentrations is proposed. The main objective is to classify in two pollution levels (Non-Contingency and Contingency) the pollutant concentration. Pollutant concentrations and meteorological variables have been considered in order to build a Representative Vector (RV) of pollution. RV is used to train an Artificial Neural Network in order to classify pollutant events determined by meteorological variables. In the experiments, real time series gathered from the Automatic Environmental Monitoring Network (AEMN) in Salamanca Guanajuato Mexico have been used. The method can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.

Complete manual of parsing; including also a synoptical table of the system; a full ilucidation of English idioms; a discussion on words difficult to classify; and a glossary of grammatical terms.

Mode of access: Internet.

Using Bayesian neural networks to classify segmented images

We present results that compare the performance of neural networks trained with two Bayesian methods, (i) the Evidence Framework of MacKay (1992) and (ii) a Markov Chain Monte Carlo method due to Neal (1996) on a task of classifying segmented outdoor images. We also investigate the use of the Automatic Relevance Determination method for input feature selection.

Intellect Sensing of Neural Network that Trained to Classify Complex Signals

An experimental comparison of information features used by neural network is performed. The sensing method was used. Suboptimal classifier agreeable to the gaussian model of the training data was used as a probe. Neural nets with architectures of perceptron and feedforward net with one hidden layer were used. The experiments were carried out with spatial ultrasonic data, which are used for car’s passenger safety system neural controller learning. In this paper we show that a neural network doesn’t fully make use of gaussian components, which are first two moment coefficients of probability distribution. On the contrary, the network can find more complicated regularities inside data vectors and thus shows better results than suboptimal classifier. The parallel connection of suboptimal classifier improves work of modular neural network whereas its connection to the network input improves the specialization effect during training.

High body mass index is not a barrier to physical activity: Analysis of international rugby players' anthropometric data

Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.

Staking a claim : the role of stakeholders in government

The stakeholder approach which emerged under the auspices of new public management has been in use in public agencies for the past 25 years. However it remains a difficult and demanding task for agencies to determine who their stakeholders are and how to optimise interactions with them. This paper will examine how government agencies identify, classify and engage with stakeholders who have competing demands, differing access to resources and the ability to exert political pressure. To do this, the stakeholder approaches of nine agencies at three levels of government in Queensland were studied. The contribution of this paper is the development of a Stakeholder Classification Model for Public Agencies which could be used to create more focused and relevant stakeholder interventions.

Revisiting the conceptualization and measurement of service quality

Since the 1980s, industries and researchers have sought to better understand the quality of services due to the rise in their importance (Brogowicz, Delene and Lyth 1990). More recent developments with online services, coupled with growing recognition of service quality (SQ) as a key contributor to national economies and as an increasingly important competitive differentiator, amplify the need to revisit our understanding of SQ and its measurement. Although ‘SQ’ can be broadly defined as “a global overarching judgment or attitude relating to the overall excellence or superiority of a service” (Parasuraman, Berry and Zeithaml 1988), the term has many interpretations. There has been considerable progress on how to measure SQ perceptions, but little consensus has been achieved on what should be measured. There is agreement that SQ is multi-dimensional, but little agreement as to the nature or content of these dimensions (Brady and Cronin 2001). For example, within the banking sector, there exist multiple SQ models, each consisting of varying dimensions. The existence of multiple conceptions and the lack of a unifying theory bring the credibility of existing conceptions into question, and beg the question of whether it is possible at some higher level to define SQ broadly such that it spans all service types and industries. This research aims to explore the viability of a universal conception of SQ, primarily through a careful re-visitation of the services and SQ literature. The study analyses the strengths and weaknesses of the highly regarded and widely used global SQ model (SERVQUAL) which reflects a single-level approach to SQ measurement. The SERVQUAL model states that customers evaluate SQ (of each service encounter) based on five dimensions namely reliability, assurance, tangibles, empathy and responsibility. SERVQUAL, however, failed to address what needs to be reliable, assured, tangible, empathetic and responsible. This research also addresses a more recent global SQ model from Brady and Cronin (2001); the B&C (2001) model, that has potential to be the successor of SERVQUAL in that it encompasses other global SQ models and addresses the ‘what’ questions that SERVQUAL didn’t. The B&C (2001) model conceives SQ as being multidimensional and multi-level; this hierarchical approach to SQ measurement better reflecting human perceptions. In-line with the initial intention of SERVQUAL, which was developed to be generalizable across industries and service types, this research aims to develop a conceptual understanding of SQ, via literature and reflection, that encompasses the content/nature of factors related to SQ; and addresses the benefits and weaknesses of various SQ measurement approaches (i.e. disconfirmation versus perceptions-only). Such understanding of SQ seeks to transcend industries and service types with the intention of extending our knowledge of SQ and assisting practitioners in understanding and evaluating SQ. The candidate’s research has been conducted within, and seeks to contribute to, the ‘IS-Impact’ research track of the IT Professional Services (ITPS) Research Program at QUT. The vision of the track is “to develop the most widely employed model for benchmarking Information Systems in organizations for the joint benefit of research and practice.” The ‘IS-Impact’ research track has developed an Information Systems (IS) success measurement model, the IS-Impact Model (Gable, Sedera and Chan 2008), which seeks to fulfill the track’s vision. Results of this study will help future researchers in the ‘IS-Impact’ research track address questions such as: • Is SQ an antecedent or consequence of the IS-Impact model or both? • Has SQ already been addressed by existing measures of the IS-Impact model? • Is SQ a separate, new dimension of the IS-Impact model? • Is SQ an alternative conception of the IS? Results from the candidate’s research suggest that SQ dimensions can be classified at a higher level which is encompassed by the B&C (2001) model’s 3 primary dimensions (interaction, physical environment and outcome). The candidate also notes that it might be viable to re-word the ‘physical environment quality’ primary dimension to ‘environment quality’ so as to better encompass both physical and virtual scenarios (E.g: web sites). The candidate does not rule out the global feasibility of the B&C (2001) model’s nine sub-dimensions, however, acknowledges that more work has to be done to better define the sub-dimensions. The candidate observes that the ‘expertise’, ‘design’ and ‘valence’ sub-dimensions are supportive representations of the ‘interaction’, physical environment’ and ‘outcome’ primary dimensions respectively. The latter statement suggests that customers evaluate each primary dimension (or each higher level of SQ classification) namely ‘interaction’, physical environment’ and ‘outcome’ based on the ‘expertise’, ‘design’ and ‘valence’ sub-dimensions respectively. The ability to classify SQ dimensions at a higher level coupled with support for the measures that make up this higher level, leads the candidate to propose the B&C (2001) model as a unifying theory that acts as a starting point to measuring SQ and the SQ of IS. The candidate also notes, in parallel with the continuing validation and generalization of the IS-Impact model, that there is value in alternatively conceptualizing the IS as a ‘service’ and ultimately triangulating measures of IS SQ with the IS-Impact model. These further efforts are beyond the scope of the candidate’s study. Results from the candidate’s research also suggest that both the disconfirmation and perceptions-only approaches have their merits and the choice of approach would depend on the objective(s) of the study. Should the objective(s) be an overall evaluation of SQ, the perceptions-only approached is more appropriate as this approach is more straightforward and reduces administrative overheads in the process. However, should the objective(s) be to identify SQ gaps (shortfalls), the (measured) disconfirmation approach is more appropriate as this approach has the ability to identify areas that need improvement.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

State-of-the-Art Review on Opinion Mining from Online Customers’ Feedback

Dealing with the ever-growing information overload in the Internet, Recommender Systems are widely used online to suggest potential customers item they may like or find useful. Collaborative Filtering is the most popular techniques for Recommender Systems which collects opinions from customers in the form of ratings on items, services or service providers. In addition to the customer rating about a service provider, there is also a good number of online customer feedback information available over the Internet as customer reviews, comments, newsgroups post, discussion forums or blogs which is collectively called user generated contents. This information can be used to generate the public reputation of the service providers’. To do this, data mining techniques, specially recently emerged opinion mining could be a useful tool. In this paper we present a state of the art review of Opinion Mining from online customer feedback. We critically evaluate the existing work and expose cutting edge area of interest in opinion mining. We also classify the approaches taken by different researchers into several categories and sub-categories. Each of those steps is analyzed with their strength and limitations in this paper.

Analysis of authenticated encryption stream ciphers

Authenticated Encryption (AE) is the cryptographic process of providing simultaneous confidentiality and integrity protection to messages. AE is potentially more efficient than applying a two-step process of providing confidentiality for a message by encrypting the message and in a separate pass, providing integrity protection by generating a Message Authentication Code (MAC) tag. This paper presents results on the analysis of three AE stream ciphers submitted to the recently completed eSTREAM competition. We classify the ciphers based on the methods the ciphers use to provide authenticated encryption and discuss possible methods for mounting attacks on these ciphers.

XML Schema Element Similarity Measures: A Schema Matching Context

In this paper, we classify, review, and experimentally compare major methods that are exploited in the definition, adoption, and utilization of element similarity measures in the context of XML schema matching. We aim at presenting a unified view which is useful when developing a new element similarity measure, when implementing an XML schema matching component, when using an XML schema matching system, and when comparing XML schema matching systems.