Hidden Markov Model Identifiability via Tensors

The prevalence of hidden Markov models (HMMs) in various applications of statistical signal processing and communications is a testament to the power and flexibility of the model. In this paper, we link the identifiability problem with tensor decomposition, in particular, the Canonical Polyadic decomposition. Using recent results in deriving uniqueness conditions for tensor decomposition, we are able to provide a necessary and sufficient condition for the identification of the parameters of discrete time finite alphabet HMMs. This result resolves a long standing open problem regarding the derivation of a necessary and sufficient condition for uniquely identifying an HMM. We then further extend recent preliminary work on the identification of HMMs with multiple observers by deriving necessary and sufficient conditions for identifiability in this setting.Comment: Accepted to ISIT 2013. 5 pages, no figure

Coping Mechanisms Of Elderly, Ill, Homebound Clients

This study was a descriptive one whose purpose was to identify coping mechanisms used by elderly, ill, homebound clients. The sample included 30 home health clients in a small southern community. The average age of the subjects was 76 years. Data were collected using Coping Resources Inventory (Hammer & Mart i n g , 1988) and a demographic and health history form. Data were analyzed using the mean, standard deviation, and Pearson r_. Analysis of the data revealed that the elders utilized spiritual/philosophical , cognitive, social, and emotional coping skills equally and more often than physical coping skills. There were significant correlations between social coping skills and sex, marriage, and previous home health experience ; between cognitive coping skills and the need for assistance with activities of daily living; between physical coping skills and diagnoses of diabetes or bone and joint disorders ; and between total coping skills and p r e v i o u s ho m e h e a l t h experience. Recommendations for further study include investigation of the coping mechanisms of well and ill elders and the impact of nursing care on coping. Geriatric Nurse Clinicians should promote the use of a broad range of coping mechanisms to prevent crises

Field Analyses for the Detection and Enumeration of Coliform Bacteria in Drinking Water During a Public Health Assessment Study

The microbiological contaminant concentrations of drinking water are typically analyzed using a customary membrane filtration method approved by the U.S. Environmental Protection Agency (EPA) and the World Health Organization (WHO), as well as the European Economic Community (EEC). The membrane filtration method is well documented providing highly reproducible water quality data at a relatively high cost in terms of preparation time, in situ procedure, and money. The commercially available Coliscan EasyGel method for the detection and enumeration of Escherichia coliand total coliforms costs much less. However, the usability of the field data may be uncertain when the results are qualitatively and quantitatively compared to duplicate membrane filtration results. Drinking water samples collected during a public health assessment study in Chichicastenago Guatemala will be analyzed using the Coliscan EasyGel method to measure concentrations of indicator coliform bacteria and the effect of the temperature stability on incubation time. A subset of the samples will be split for duplicate membrane filtration analysis. Linear regression analysis and relative percent difference analysis will be performed on the duplicate results to evaluate the comparability of the Coliscan EasyGel and membrane filtration data

The neurocognitive processing of plausibility and real-world knowledge:A cross-linguistic investigation

Our knowledge about concepts and meanings is at the very heart of human cognition. In everyday life, we have to interact with our environment in a variety of different ways. Our actions are guided by what we know and believe about the world and this knowledge derives primarily from previous sensory and perceptual experiences. The fact that we are capable of engaging with our environment in an appropriate and efficient way means that we have learnt (how) to make sense of the events and entities we are faced with in day-to-day life. We are thus able to recognise and name both physical objects and abstract concepts, to categorise and associate them based on their specific properties, to interpret other people’s intentions, and to judge cause and effect of their actions as well as our own. Moreover, the ability to represent this wealth of knowledge about the real world in the conceptualised and symbolic form of language is believed to be exclusive to humans. Our language capacity allows us to communicate with others about past and future events or to describe fictitious scenarios by combining previously acquired concepts in a novel way without the need for external stimulation. Thus language forms a primary means of interacting with those around us by allowing us to express our own thoughts and comprehend those of others. As long as language processing proceeds in an undisturbed manner, we are largely unaware of the underlying mechanisms that support the seemingly effortless interpretation of linguistic input. The importance of these processes for successful communication, however, becomes all the more apparent when language processing is disrupted, for example, by brain lesions that render semantic analysis difficult or impossible. Scientific research that aims to uncover and define cognitive or neural mechanisms underlying semantic processing is inevitably faced with the complexity and wealth of semantic relationships that need to be taken into account. In absence of noninvasive neurocognitive methods and insights gleaned from modern neurobiology, early research had a limited impact on our understanding of how semantic processing is implemented in the human brain. Traditional neurological models of language have been based primarily on lesion-deficit data, and thus supported the view that certain areas of the brain were exclusively dedicated to the processing of language-specific functions (Geschwind, 1970; Lichtheim, 1885; Wernicke, 1874). Furthermore, classical theories of sensory processing viewed the brain as a purely stimulus-driven system that retrieves and combines individual low-level aspects or features in an automated, passive and context-independent manner (Biederman, 1987; Burton & Sinclair, 1996; Hubel & Wiesel, 1965; Massaro, 1998). After a recent paradigm shift in the cognitive neurosciences, current theories of sensory processing are now based on the concept of the brain as a highly active, adaptive and dynamic device. In this sense, language comprehension, like many other higher-cognitive functions, is shaped by a flexible interaction of a number of different processes and information sources that include so-called bottom-up signals, i.e., the actual sensory input and processes related to their forward propagation, and top-down processes that generate predictions and expectations based on prior experience and perceived probabilities. Therefore, accounts that view semantic processing as a dynamic and active construction of meaning that is highly sensitive to contextual influences seem most probable from a neurobiological perspective. Results from electrophysiological and neuroimaging research on semantic analysis in sentence and discourse context have provided evidence for top-down influences from the very beginning. In addition, recent ERP results have suggested that the interaction between topdown and bottom-up information is more flexible and dynamic than previously assumed. Yet, the importance of predictions and expectations has long been neglected in models of semantic processing and language comprehension in general. Neuroimaging data have provided us with a long list of brain regions that have been implicated in different aspects of semantic analysis. We are only beginning to understand the role(s) that these regions play and how they interact to support the flexible and efficient construction of meaning. The aim of the present thesis is to gain a more comprehensive view on the computational mechanisms underlying language processing by investigating how bottom- up and top-down information and processes interactively contribute to the semantic analysis in sentences and discourse. To this end, we conducted a total of five studies that used either event-related potentials or functional neuroimaging to shed light on this matter from different perspectives. The thesis is divided into two main parts: Part I (chapters 1-5) provides an overview on previous results from electrophysiology and neuroimaging on semantic processing as well as a description and discussion of the studies conducted in the present thesis. Part II (chapters 6-9) consists of three research articles that describe and discuss the results of five experimental studies. In Part I, Chapter 2 gives a brief introduction to the event-related potential and functional neuroimaging techniques and reviews the most relevant results and theories that have emerged from studies on sentence and discourse processing. Chapter 3 highlights the research questions targeted in each of the experimental studies and describes and discusses the most relevant findings against the background established by Chapter 2. Chapters 4 and 5 conclude Part I by placing the presented results in a broader context and by briefly outlining future directions. Part II begins with a survey of the three studies reported in the subsequent chapters. Chapter 7 highlights the results of the first study, a German ERP experiment that investigated the impact of capitalisation, i.e., a purely form-based and contextually independent bottom-up manipulation, on the processing of semantic anomalies in single sentences. Chapter 8 comprises three ERP experiments that used both easy and hard to detect semantic anomalies in German and English to corroborate the assumption that the weighting of top-down and bottom-up information cues might be determined in a language-specific way. Chapter 9, the final chapter of the thesis, describes and discusses the results of the third study, in which the impact of embedding context on the required depth of semantic processing was examined using functional neuroimaging

An Assessment of Electronics Tax Register System Implementation and Challenges, Case of Nekemt Town Value Added Tax

The main purpose of this study is to assess Electronics tax register system implementation challenges in process of Value added tax in Nekemt town. In order to maintain the desired objectives descriptive survey research is designed for the study. Using systematic sampling method 226 tax payers were selected from the total population of 521 and purposive sampling were used to take 8 experts from ERCA office. The main data of this study was both primary and secondary data. The Statistical Package for Social Sciences (SPSS) version 20 was used to analyze data using descriptive statistics like percentage and frequencies of the variables, and arithmetic mean.  The results reveal that, there are major challenges which are confronted by VAT payers for using ETRs such as; incur additional cost (machine purchase, maintenance cost) no adequate training regarding ETRs. The paper suggests that attention should be given to training regarding ETRs and Introduce ETR machine that is not expensive to tax payers. Keywords: Value added tax, Electronics tax register machine DOI: 10.7176/EJBM/12-10-03 Publication date: April 30th 202