Service users’ participation in mental health community-based organizations

Une grande proportion de personnes aux prises avec des problèmes de santé mentale vit dans l’isolement social. Les infirmières en santé communautaire sont interpellées au premier rang pour accompagner ces personnes dans leur processus de rétablissement et pour atténuer leur isolement social. La participation au sein d’organismes communautaires optimise l’expérience de rétablissement, diminue l’isolement social et renforce les réseaux sociaux de personnes ayant des problèmes de santé mentale. Toutefois, la participation des personnes utilisatrices de services dans la structure d’organisation des organismes communautaires est encore peu documentée. Afin de pallier cette lacune, cette étude avait pour objectifs de documenter, décrire la nature de la participation des personnes utilisatrices de services en santé mentale et d’explorer des facteurs facilitatants et des barrières à cette participation. Un devis de méthodes mixtes, qualitatif et quantitatif, a été utilisé. Dans le premier de deux volets, une enquête impliquant la réalisation d’entretiens semi-dirigés a été menée auprès de douze directeurs d’organismes communautaires œuvrant dans le domaine des services en santé mentale. Une version française du questionnaire « Adapted User Involvement » (Diamond, Parkin, Morris, Bettinis, & Bettesworth, 2003) a été administrée afin de documenter l’étendue de la participation des personnes utilisatrices de services dans les organismes visés. Pour le deuxième volet, deux organismes communautaires ont été sélectionnés à partir des résultats du questionnaire et de l’analyse documentaire de documents publics de ces organismes. Les scores obtenus au questionnaire ont ainsi permis de sélectionner des organismes présentant des résultats contrastés en matière de participation des personnes utilisatrices de services. Les entretiens semi-dirigés ont été menés avec différents groupes de répondants (membres de conseil d’administration, personnes utilisatrices de services, employés, directeurs) afin de recueillir de l’information sur les thèmes suivants: la nature de la participation des personnes utilisatrices de services, ainsi que les facteurs facilitants et les défis qui y sont associés. Les résultats de l’analyse montrent que: (1) les facteurs qui favorisent la participation des personnes utilisatrices sont: l’accès à un espace de participation pour les personnes utilisatrices et l’accompagnement de celles-ci par les intervenants de diverses disciplines pendant leur participation au sein des organismes communautaires, (2) les barrières de la participation des personnes utilisatrices au sein des organismes communautaires sont la stigmatisation sociale et les caractéristiques personnelles reliées aux problèmes de santé mentale chez les personnes utilisatrices, et (3) les avantages principaux de la participation des personnes utilisatrices de services se déclinent en services mieux adaptés à leurs besoins et leurs demandes, en leur appropriation du pouvoir (dans leur participation dans l’organisme communautaire) et en leur sentiment d’appartenance à l’organisme. À la lumière des ces constats, l’accompagnement des personnes utilisatrices de services dans leur participation apparaît une avenue prometteuse pour les infirmières en santé mentale communautaire afin de faciliter leur appropriation du pouvoir et d’améliorer leur bien-être.

The autotelic experience : a design approach to user experience

Si les principes d’utilisabilité guident la conception de solutions de design interactif pour s’assurer que celles-ci soient « utilisables », quels principes guident la conception d’objets interactifs pour s’assurer que l’expérience subjective de l’usager (UX) soit adéquate et mémorable? Que manque-t-il au cadre de l‘UX pour expliquer, comprendre, et anticiper en tant que designer une expérience mémorable (‘an experience’; Dewey, 1934)? La question centrale est issue d’une double problématique : (1) le cadre théorique de l’UX est incomplet, et (2) les processus et capacités des designers ne sont pas considérés et utilisés à leur pleine capacité en conception UX. Pour répondre à cette question, nous proposons de compléter les modèles de l’UX avec la notion d’expérience autotélique qui appartient principalement à deux cadres théoriques ayant bien cerné l’expérience subjective, soit l’expérience optimale (ou Flow) de Csikszentmihalyi (1988) et l’expérience esthétique selon Schaeffer (2001). L’autotélie est une dimension interne du Flow alors qu’elle couvre toute l’expérience esthétique. L’autotélie est une expérience d’éveil au moment même de l’interaction. Cette prise de conscience est accompagnée d’une imperceptible tension de vouloir faire durer ce moment pour faire durer le plaisir qu’il génère. Trois études exploratoires ont été faites, s’appuyant sur une analyse faite à partir d’un cadre théorique en trois parties : le Flow, les signes d’activité non verbale (les gestes physiques) et verbale (le discours) ont été évalués pour voir comment ceux-ci s’associent. Nos résultats tendent à prouver que les processus spatiaux jouent un rôle de premier plan dans l’expérience autotélique et par conséquent dans une UX optimale. De plus, ils suggèrent que les expériences pragmatique et autotélique sont ancrées dans un seul et même contenu, et que leur différence tient au type d’attention que le participant porte sur l’interaction, l’attention ordinaire ou de type autotélique. Ces résultats nous ont menés à proposer un modèle pour la conception UX. L’élément nouveau, resté jusqu’alors inaperçu, consiste à s’assurer que l’interface (au sens large) appelle une attitude réceptive à l’inattendu, pour qu’une information puisse déclencher les processus spatiaux, offrant une opportunité de passer de l’attention ordinaire à l’attention autotélique. Le nouveau modèle ouvre la porte à une meilleure valorisation des habiletés et processus du designer au sein de l’équipe multidisciplinaire en conception UX.

Elementary School Principals in Low-Socioeconomic-Status Schools: A University-Based Research Program Designed to Support Mandated Reform

This paper presents a reform initiative, the Supporting Montreal Schools Program (SMSP), created by the government of Quebec to assist 184 low socio-economic-status schools in Montreal implement seven reform strategies prescribed by the government. On a regular basis, the professional team of the SMSP engages in reflection and research with universities concerning one or more of the strategies they are charged with helping schools implement or the functioning of the SMSP more generally. The present research programme is part of the team’s ongoing reflection on a component of Strategy 4: professional development of school administrators and the school team. In this paper, we detail results from this initial and subsequent studies on the work of principals in low-performing schools. We also describe our collaborative relationship with the SMSP team, discuss the effectiveness of the SMSP in promoting the implementation of the seven governmentmandated strategies and critique the utility of our partnership with the SMSP and our use of that programme as a vehicle for linking research to practice.

Semiautomatic Detection of Scoliotic Rib Borders From Posteroanterior Chest Radiographs

3-D assessment of scoliotic deformities relies on an accurate 3-D reconstruction of bone structures from biplanar X-rays, which requires a precise detection and matching of anatomical structures in both views. In this paper, we propose a novel semiautomated technique for detecting complete scoliotic rib borders from PA-0° and PA-20° chest radiographs, by using an edge-following approach with multiple-path branching and oriented filtering. Edge-following processes are initiated from user starting points along upper and lower rib edges and the final rib border is obtained by finding the most parallel pair among detected edges. The method is based on a perceptual analysis leading to the assumption that no matter how bent a scoliotic rib is, it will always present relatively parallel upper and lower edges. The proposed method was tested on 44 chest radiographs of scoliotic patients and was validated by comparing pixels from all detected rib borders against their reference locations taken from the associated manually delineated rib borders. The overall 2-D detection accuracy was 2.64 ± 1.21 pixels. Comparing this accuracy level to reported results in the literature shows that the proposed method is very well suited for precisely detecting borders of scoliotic ribs from PA-0° and PA-20° chest radiographs.

Design Techniques for Sigmadelta based ADC for Wireless Applications

Analog-to digital Converters (ADC) have an important impact on the overall performance of signal processing system. This research is to explore efficient techniques for the design of sigma-delta ADC,specially for multi-standard wireless tranceivers. In particular, the aim is to develop novel models and algorithms to address this problem and to implement software tools which are avle to assist the designer's decisions in the system-level exploration phase. To this end, this thesis presents a framework of techniques to design sigma-delta analog to digital converters.A2-2-2 reconfigurable sigma-delta modulator is proposed which can meet the design specifications of the three wireless communication standards namely GSM,WCDMA and WLAN. A sigma-delta modulator design tool is developed using the Graphical User Interface Development Environment (GUIDE) In MATLAB.Genetic Algorithm(GA) based search method is introduced to find the optimum value of the scaling coefficients and to maximize the dynamic range in a sigma-delta modulator.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Development of nitrifying and photosynthetic sulfur bacteria based bioaugmentation systems for the bioremediation of ammonia and hydrogen sulphide in shrimp culture

This thesis entitled Development of nitrifying ans photosynthetic sulfur bacteria based bioaugmentation systems for the bioremediation of ammonia and hydregen sulphide in shrimp culture. the thesis is to propose a sustainable, low cost option for the mitigation of toxic ammonia and hydrogen sulphide in shrimp culture systems. Use of ‘bioaugmentors’ as pond additives is an emerging field in aquaculture. Understanding the role of organisms involved in the ‘bioaugmentor’ will obviously help to optimize conditions for their activity.The thesis describes the use of wood powder immobilization of nitrifying consortia.Shrimp grow out systems are specialized and highly dynamic aquaculture production units which when operated under zero exchange mode require bioremediation of ammonia, nitrite nitrogen and hydrogen sulphide to protect the crop. The research conducted here is to develop an economically viable and user friendly technology for addressing the above problem. The nitrifying bacterial consortia (NBC) generated earlier (Achuthan et al., 2006) were used for developing the technology.Clear demonstration of better quality of immobilized nitrifiers generated in this study for field application.

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

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

A novel Sigma–Delta based parallel analogue-to-residue converter

Animportant step in the residue number system(RNS) based signal processing is the conversion of signal into residue domain. Many implementations of this conversion have been proposed for various goals, and one of the implementations is by a direct conversion from an analogue input. A novel approach for analogue-to-residue conversion is proposed in this research using the most popular Sigma–Delta analogue-to-digital converter (SD-ADC). In this approach, the front end is the same as in traditional SD-ADC that uses Sigma–Delta (SD) modulator with appropriate dynamic range, but the filtering is doneby a filter implemented usingRNSarithmetic. Hence, the natural output of the filter is an RNS representation of the input signal. The resolution, conversion speed, hardware complexity and cost of implementation of the proposed SD based analogue-to-residue converter are compared with the existing analogue-to-residue converters based on Nyquist rate ADCs

Intelligent Agent-based Multilingual Information Retrieval System

The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India

Content-Based Image Retrieval of Axial Brain Slices Using a Novel LBP with a Ternary Encoding

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain MR image database. The ternary encoding depends on a threshold, which is a user-specified one or calculated locally, based on the variance of the pixel intensities in each window. The variancebased local threshold makes the MOD-LTP more robust to noise and global illumination changes. The retrieval performance is shown to improve by taking region-based moment features of MODLTP and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback. The average rank obtained using iterated and weighted moment features of MOD-LTP with a local variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin, A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images. IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images

User Profile Management and Selection in Context-Aware Service Platforms for Networks Beyond 3G

In recent years, progress in the area of mobile telecommunications has changed our way of life, in the private as well as the business domain. Mobile and wireless networks have ever increasing bit rates, mobile network operators provide more and more services, and at the same time costs for the usage of mobile services and bit rates are decreasing. However, mobile services today still lack functions that seamlessly integrate into users’ everyday life. That is, service attributes such as context-awareness and personalisation are often either proprietary, limited or not available at all. In order to overcome this deficiency, telecommunications companies are heavily engaged in the research and development of service platforms for networks beyond 3G for the provisioning of innovative mobile services. These service platforms are to support such service attributes. Service platforms are to provide basic service-independent functions such as billing, identity management, context management, user profile management, etc. Instead of developing own solutions, developers of end-user services such as innovative messaging services or location-based services can utilise the platform-side functions for their own purposes. In doing so, the platform-side support for such functions takes away complexity, development time and development costs from service developers. Context-awareness and personalisation are two of the most important aspects of service platforms in telecommunications environments. The combination of context-awareness and personalisation features can also be described as situation-dependent personalisation of services. The support for this feature requires several processing steps. The focus of this doctoral thesis is on the processing step, in which the user’s current context is matched against situation-dependent user preferences to find the matching user preferences for the current user’s situation. However, to achieve this, a user profile management system and corresponding functionality is required. These parts are also covered by this thesis. Altogether, this thesis provides the following contributions: The first part of the contribution is mainly architecture-oriented. First and foremost, we provide a user profile management system that addresses the specific requirements of service platforms in telecommunications environments. In particular, the user profile management system has to deal with situation-specific user preferences and with user information for various services. In order to structure the user information, we also propose a user profile structure and the corresponding user profile ontology as part of an ontology infrastructure in a service platform. The second part of the contribution is the selection mechanism for finding matching situation-dependent user preferences for the personalisation of services. This functionality is provided as a sub-module of the user profile management system. Contrary to existing solutions, our selection mechanism is based on ontology reasoning. This mechanism is evaluated in terms of runtime performance and in terms of supported functionality compared to other approaches. The results of the evaluation show the benefits and the drawbacks of ontology modelling and ontology reasoning in practical applications.

Master Plan for Renewable Energy based Electricity Generation in The Gambia

The principal objective of this paper is to develop a methodology for the formulation of a master plan for renewable energy based electricity generation in The Gambia, Africa. Such a master plan aims to develop and promote renewable sources of energy as an alternative to conventional forms of energy for generating electricity in the country. A tailor-made methodology for the preparation of a 20-year renewable energy master plan focussed on electricity generation is proposed in order to be followed and verified throughout the present dissertation, as it is applied for The Gambia. The main input data for the proposed master plan are (i) energy demand analysis and forecast over 20 years and (ii) resource assessment for different renewable energy alternatives including their related power supply options. The energy demand forecast is based on a mix between Top-Down and Bottom-Up methodologies. The results are important data for future requirements of (primary) energy sources. The electricity forecast is separated in projections at sent-out level and at end-user level. On the supply side, Solar, Wind and Biomass, as sources of energy, are investigated in terms of technical potential and economic benefits for The Gambia. Other criteria i.e. environmental and social are not considered in the evaluation. Diverse supply options are proposed and technically designed based on the assessed renewable energy potential. This process includes the evaluation of the different available conversion technologies and finalizes with the dimensioning of power supply solutions, taking into consideration technologies which are applicable and appropriate under the special conditions of The Gambia. The balance of these two input data (demand and supply) gives a quantitative indication of the substitution potential of renewable energy generation alternatives in primarily fossil-fuel-based electricity generation systems, as well as fuel savings due to the deployment of renewable resources. Afterwards, the identified renewable energy supply options are ranked according to the outcomes of an economic analysis. Based on this ranking, and other considerations, a 20-year investment plan, broken down into five-year investment periods, is prepared and consists of individual renewable energy projects for electricity generation. These projects included basically on-grid renewable energy applications. Finally, a priority project from the master plan portfolio is selected for further deeper analysis. Since solar PV is the most relevant proposed technology, a PV power plant integrated to the fossil-fuel powered main electrical system in The Gambia is considered as priority project. This project is analysed by economic competitiveness under the current conditions in addition to sensitivity analysis with regard to oil and new-technology market conditions in the future.