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This chapter examines the interplay between human resource management theory and human resource management practice. It advocates that effective human resource management practice and theory are intrinsically intertwined, and this indispensable link ought to be central to the pedagogy of management research methods. Through greater embeddedness of the institutional and societal context in research method teaching, students can develop as scholars who understand their roles as facilitators of dialogue between researchers and a significant part of their audience (practitioners). The chapter conceptualizes this perspective as a collaborative model in human resource management research, which then must hold centrality in the teaching of research methods in our university and college classrooms. [ABSTRACT FROM AUTHOR]

Copyright of Apuntes de Psicologia is the property of Colegio Oficial de Psicologia de Andalucia Occidental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this nonrandomized study was to compare several attributes of hereditary cancer risk assessment using a collaborative model of service delivery. Arm 1 included patients seen in‐person by a board‐certified genetic counselor (CGC), Arm 2 included high‐complexity triaged patients from distant sites who received telegenetics with a CGC, and Arm 3 included low‐complexity triaged patients from distant sites who had in‐person risk assessment with a locally placed genetic counselor extender (GCE). A total of 152 patients consented and 98 had complete data available for analysis (35 in Arm 1, 33 in Arm 2, and 30 in Arm 3). The three groups were comparable in age, ethnicity, education, employment, and cancer status. There was no significant difference in median wait time or distance traveled to receive care across all three arms. However, if patients in Arms 2 and 3 had to access the CGC in‐person, they would have had to travel significantly further (p < 0.0001). The time spent in a session was significantly longer in Arm 3 with a GCE than with a CGC in‐person or by telegenetics (p < 0.01). There was no difference in the number of essential elements covered in the appointment, change in cancer worry, or appointment satisfaction across all three arms, although the sample size was small. Employing a collaborative model of service delivery with GCEs and telegenetics is feasible, satisfactory to patients and reduces the distance patients travel to access hereditary cancer genetic services. [ABSTRACT FROM AUTHOR]

The optimization efforts of promotion, prevention, provision of preventive treatment, and infection control are strategies to overcome tuberculosis in Indonesia for the period 2020-2024. This research aims to analyze the effects of a collaborative model between health workers and family support to improve the success of treating patients with pulmonary tuberculosis. This is an experimental research using a one-group pre and post-test design. The study samples were TB patients treated at Bainamu and Bontosunggu Public Health Centers, Jeneponto Regency, from June 2021 to January 2022. Using McNemar's statistical test, the data analysis was conducted to determine the differences in patient behavior on factors that support and inhibit the recovery. The results showed that the collaborative model has an impact on eating, healthy living, and spiritual behaviors that support the recovery and cure rate of TB patients. [ABSTRACT FROM AUTHOR]

Copyright of Revista Española de Orientación y Psicopedagogía (REOP) is the property of Revista Espanola de Orientacion y Psicopedagogia (REOP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present quantitative, non-experimental comparative study, delves into the long-term effects of the collaborative practicum model (specifically the "academy-class" model) on novice teachers. The research aims to discern disparities in the professional self-efficacy of novice educators who underwent training within the collaborative practicum model as opposed to those who adhered to the conventional teaching model. This comparative analysis is based on three variables: perception of the teaching profession, professional self-efficacy, and socio-economic security. Furthermore, the study examines whether the collaborative model contributes to cultivating more favorable attitudes toward the teaching profession and a greater inclination to continue teaching for an extended period exceeding three years. The study encompasses a cohort of 436 Bachelor of Education (B.Ed.) graduates from 22 Israeli Higher Education Institutions who completed their degrees within the past five years. The research findings underscore a higher level of teaching efficacy, socio-economic security, and a more positive outlook among those who participated in the collaborative practicum and expressed their intent to persist in the teaching profession. These outcomes underscore the vital role of the collaborative practicum model, hinting at its potential to positively influence the retention rate within the teaching profession. Furthermore, it underscores the crucial connection between comprehensive and meaningful training within a collaborative practicum framework and the sustainable professional growth of educators. This robust training approach can potentially secure the continued presence of dedicated and enthusiastic educators in the field over the long term. [ABSTRACT FROM AUTHOR]

Universities often struggle to translate theory of inclusive education into real life practices for pre-service teachers (PSTs). In this paper, we evaluate an innovative partnership between Australian secondary school teachers and university academics where they co-designed and co-taught an undergraduate inclusive education course. We used a quasi-experimental design where 67 PSTs were grouped into two cohorts: one co-taught by the team of school educators and university academics (n = 26), the other taught only by university academics (n = 41). PSTs' scores on teaching efficacy, attitudes and intentions to teach in inclusive classrooms were measured at the pre and posttest stages of the course. Our evaluation showed significant increases in positive attitudes and teaching efficacy skills, decreased concerns and higher intentions to teach in inclusive classrooms among PSTs who were co-taught. The co-teaching team also identified various professional and personal benefits of collaborating. We further discuss the implications of our research for teacher education programmes and the usefulness of including school educators' expertise in bridging the gaps between theory and practice. [ABSTRACT FROM AUTHOR]

Purpose: Unfortunately, the occurrence of natural disasters is inevitable all over the world. Hence, this paper aims to analyze a scenario-based collaborative problem in a relief supply chain (RSC), where nongovernmental organizations can participate in relief activities with governmental organizations. This study focuses on location-allocation, inventory management and distribution planning under uncertain demand, budget, transportation and holding costs where government and private distribution centers receive relief items from suppliers then send them to affected areas. The performance of the proposed model is surveyed in a real case study in Dorud. Design/methodology/approach: This paper develops a nonlinear mixed-integer programming model that seeks to maximize the coverage of demand points and minimize operating costs and traveled distance. The linear programming-metric technique and grasshopper optimization algorithm are applied to survey the model's applicability and efficiency. Findings: This study compares noncollaborative and collaborative cases in terms of the number of applied distribution centers and RSC's goals, then demonstrates that the collaborative model not only improves the coverage of demand points but also minimizes cost and traveled distance. In fact, the presented approach helps governments efficiently surmount problems created after a disaster, notwithstanding existing uncertainties, by determining a strategic plan for collaboration with nongovernmental organizations for relief activities. Originality/value: Relief strategies considered in previous research have not been sufficiently examined from the perspective of collaboration of governmental and nongovernmental organizations and provided an approach to develop the coverage of affected areas and reducing costs and traveled distance despite various uncertainties. Hence, the authors aim to manage RSCs better by offering a mathematical model whose performance has been proved in a real case study. [ABSTRACT FROM AUTHOR]

With a renewed global scientific and technological revolution and industrial reform, the digital economy, with data resources as the key element, has rapidly developed. This study proposes a data-driven measurement and evaluation method to promote the coordinated development of the digital economy and logistics industry. An evaluation index system is constructed, which comprehensively considers the index dimensions that reflect the development level of the digital economy and logistics industry. A Z-score standardisation method is applied to data processing, to carry out dimensionless standardisation processing of the original index data. A collaborative degree model is constructed to evaluate the collaborative development level of the digital economy and logistics industry composite system. We demonstrate the implementation process of these models using data from Anhui province from 2013 to 2020. The results verify the feasibility of the research method and emphasise that the development level of the composite system of the digital economy and logistics industry in Anhui province shows a fluctuating growth trend, with variations between the types and degrees of collaboration policy; suggestions are made accordingly. This study provides theoretical and methodological support for the coordinated development of the regional digital economy and logistics industry. [ABSTRACT FROM AUTHOR]

Background: Neurocritical care (NCC) and neuropalliative care (NPC) clinicians provide care in specialized intensive care units (ICU). There is a paucity of data regarding the impact of NCC and NPC collaboration in smaller, community-focused settings. Objective: To determine the clinical impact of introducing a NCC/NPC collaborative model in a mixed ICU community-based teaching hospital. Design: Retrospective pre/post cohort study. Subjects: Patients ≥18 years of age admitted to the ICU who received neurology and palliative care consultations between September 1, 2015 and August 31, 2017 at a 300 bed community-focused hospital were included. Intervention: The addition of a NCC/NPC collaborative model took place in September of 2016. The time periods before (9/1/2015 to 8/31/2016) and after (9/1/2016 to 8/31/2017) the addition were compared. Results: A total of 274 admissions (pre: 130, post: 144) were included. There were significantly more NCC consultations provided in the post-period (44.6% vs 57.6%; P =.03). NPC consultation increased (55.4% vs 66.7%; P =.056) Median LOS was significantly shorter after implementation of the collaborative model (11 vs 8 days; P =.01). Median ICU LOS was also shorter by 1 ICU-day in the post-period, though this was not statistically significant (P =.23). Mortality rates were similar (P =.95). Conclusions: Our findings suggest NCC/NPC collaboration in a community-focused teaching hospital was associated with more NCC consultations, as well as shorter LOS without increasing mortality. These data highlight the importance of supporting collaborative models of care in community settings. Further research is warranted. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to design a collaborative model amongst faculty and librarian to support teaching and research congruent with the Vietnamese context. Design/methodology/approach: The mix-method research is used in three stages to (1) study the situation and problems of faculty-librarian collaboration by using semi-structured interviews with 29 participants, (2) survey factors influencing the collaboration from 455 samples, (3) evaluate and arrange the influence level of factors from 18 experts' perspectives. Findings: The research results show that in order to enhance the quality and gain goals of the collaboration, it is necessary to meet three elements, in which universities must (1) meet essential conditions and factors, (2) identify collaborative objectives and activities, collaborative process/guidelines, and evaluating collaboration; and (3) clarify the participation and support of stakeholders to achieve common outcomes. Research limitations/implications: This study carried out with representatives for key informant group at four universities in Vietnam, thus, the research results could not cover all current situation of the faculty–librarian collaboration at universities. Originality/value: This paper provides the detail picture of faculty–librarian collaboration practices and factors having influence this activity at Vietnamese universities. Then, the findings help administrators, faculty and librarians understand and deploy a reasonable plan in accordance with the university's features to enhance the effectiveness and success of the faculty–librarian collaboration. [ABSTRACT FROM AUTHOR]

Supervising teachers, as a basic component of an educational plan, has positive effects on teachers’ classroom behaviors. Following the tenets of Sociocultural theory of mind, this qualitative study delvd into the perception of EFL teachers regarding their worldviews of what supervision is and what it must be like. For this purpose, 25 participants (10 supervisors,10 in-service teachers, and 5 pre-service teachers) were recruited and interviewed. Their responses to a semi-structured interview were recorded by mobile phone, transcribed, and then translated into English for ease of interpretation. To analyze the data, thematic analysis was used. The emerged themes showed that the participants preferred supervision with feedback which is constructive, timely, with effective solution in challenging situations, effective in identifying tecaher’s strengths and weaknesses, suggestive and non-judgemental. They also believed that supervision must be with no imposition, with prior notice, with a checklist, in a relaxed atmosphere, with a competent supervisor and without supervisor presence. Criticizing the running model of supervision, they believed that the feedback offered is judgemental and inappropriate, offers no solution to the problems, and has no purpose for improvement. Finally, some valuable implications for TTC holders, supervisors, and on-thejob mentors, and also several recommendations for further research are presented. [ABSTRACT FROM AUTHOR]

Copyright of Revista Española de Orientación y Psicopedagogía (REOP) is the property of Revista Espanola de Orientacion y Psicopedagogia (REOP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Currently, the discriminative correlation filter‐based trackers have achieved higher tracking accuracy. However, visual tracking still faces challenges in terms of heavy occlusion, scale variation and so on. In this study, the authors intend to solve heavy occlusion by introducing collaborative model into classifier‐box. Firstly, they introduce complex colour features into correlation filter tracker to improve the effect of the tracker. Secondly, they introduce a multi‐scale method into their tracker to ease the scale problem. Thirdly, in order to solve the heavy occlusion in the tracking process, they adopt the locally weighted distance and classifier‐box. Their algorithm achieves distance precision rates of 81.7 and 77.4% on OTB2013 dataset and OTB2015 dataset, respectively. Their contribution focuses on solving heavy occlusion by using colour features, locally weighted distance and classifier‐box. The experimental results on OTB2013 and OTB2015 datasets demonstrate their algorithm to perform better than state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

We propose a novel collaborative discriminative model based on extreme learning machine (ELM) for object tracking in this paper. In order to represent the object more precisely, we first propose a new collaborative discriminative representation model, which includes both a global discriminative sub-model and a local discriminative sub-model. Different from traditional local representation models, in particular, our local sub-model integrates several classifiers which have structural relations to improve the expression. The global discriminative model represents the appearance comprehensively while the local discriminative sub-model can effectively address occlusions and assist the update. Second, to have better combination of these sub-models, we propose a novel collaboration strategy based on the Kullback-Leibler (KL) distance. The novel strategy can determine the weights of the sub-models adaptively by measuring their KL distances reciprocally. Third, we introduce ELM into tracking and adopt it to build both the global and the local discriminative sub-models simultaneously. Since ELM has a good generalization performance and is robust to the imbalance of the training samples, it is suitable to be used for tracking. Experimental results demonstrate that our method can achieve comparable performance to many state-of-the-art tracking approaches. [ABSTRACT FROM AUTHOR]

MoJo refers to the emerging framework of covering news reporting workflows using smart mobile devices with dedicated software or hardware. However, a fully integrated and dedicated computing environment that can address the individual needs of both professional and citizen journalists is still missing. We introduce MoJo--MATE, (Mobile Journalism Machine AssisTEd reporting) a platform that integrates tools concerning all workflows at all stages of news reporting (content creation, editing, fact-checking, content management and publishing), thus providing interconnection of the newsroom collaborators and the public. We distinguish the client-/terminal-side and the server-side as two discrete components of the platform. The so-called jReporter mobile application includes tools and automations to support journalists in audiovisual capturing and editing along with semantic metadata extraction by making use of the smart devices. This is essential, since, in MOJO, the reporter has full responsibility of correct camera and microphone handling, without the assistance of a professional operator. Dedicated editing tools enhance portability, allowing at the same time the collection of log files with editing history, for authentication purposes. The created content is uploaded from the mobile devices to the server-side repositories, where Graphical User Interfaces are provided for accessing and managing media assets. A database containing information about the registered contributors and their respective types of engagement is maintained, controlling content rights and functionalities depending on the discrete users' roles (e.g. reporter, technical stuff, editor, journalist, and contributor). The metadata created in client-side is utilized for intelligent Multimedia Asset Management, efficient and comprehensible content publishing, including cross-validation and fact-checking aspects. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Investigación Agraria y Ambiental is the property of Revista de Investigacion Agraria y Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Visual tracking is a challenging task since it involves developing an effective appearance model to deal with numerous factors. In this paper, we propose a robust object tracking algorithm based on a collaborative model with adaptive selection scheme. Specifically, based on the discriminative features selected from the feature selection scheme, we develop a sparse discriminative model (SDM) by introducing a confidence measure strategy. In addition, we present a sparse generative model (SGM) by combining ℓ1 regularization with PCA reconstruction. In contrast to existing hybrid generative discriminative tracking algorithms, we propose a novel adaptive selection scheme based on the Euclidean distance as the joint mechanism, which helps to construct a more reasonable likelihood function for our collaborative model. Experimental results on several challenging image sequences demonstrate that the proposed tracking algorithm leads to a more favorable performance compared with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The rapid development of information technologies provided unprecedented big data environments for condition monitoring and degradation analyses. However, the available big data sets are often sparse with a limited number of observations per recorded unit. For example, in many healthcare systems, data are collected from a large number of patients, but the available observations from each patient are quite limited. Unfortunately, most of the existing approaches for data-driven degradation modeling may not work well in this scenario as they either pool the information from the population or require rich historical observations in each unit. To address the challenges in “sparse data environments,” this paper proposes a structural degradation modeling framework (SDM). The SDM is inspired by the recommender system, which provides recommendations about specific items for the user. In addition, it is also tailored to the needs of degradation modeling. In particular, the framework takes into consideration: 1) the available data from the unit of interest; 2) the population characteristics; 3) the relationship between the available units; and 4) the precision of the available units. Simulation studies and a case study that involves the Alzheimer’s disease (AD) neuroimaging initiative data set are conducted, which shows satisfactory performance of the proposed method. Note to Practitioners—This paper proposes a framework for modeling and predicting the degradation level and/or condition of units with time. Our framework is particularly useful where many units have missing and/or limited degradation observations. Essentially, our proposed method integrates two important ideas: 1) leveraging the available data from the unit of interest to improve the modeling fitting of the individual unit over the observed time domain and 2) considering the relationship between the available units to extract proper and accurate population characteristics to address the challenge of limited observations. The proposed approach is validated via simulation studies as well as a healthcare case study based on AD. In the future research, we will further explore the extension of the proposed method such as considering more generic degradation models and optimal parameter tunings. [ABSTRACT FROM AUTHOR]

In this paper, robust visual tracking scheme is achieved through a novel sparse tracking via collaborative motion and appearance (TCMA). A coarse-to-fine framework with both motion and holistic appearance information is taken into consideration. In coarse search, we employ an optical flow map for the generation of motion particles. A rough estimation of target image patch is obtained using $l_2$ -regularized least square method in coarse search stage. In fine search, a novel smooth term is proposed in the cost function to improve the robustness of the tracker. With this smooth term, the object appearance in the previous frame will also affect the calculation of sparse coefficient in the current frame. It allows the tracker involving temporal information between consecutive frames instead of only considering single frame appearance information as in the conventional sparse coding-based tracking algorithms. In order to reserve the original and latest appearance information simultaneously in the template, a quadratic-function-like weight allocation scheme combining with particle contributed histogrammic correlation is developed in the updating stage. Both qualitative and quantitative studies are conducted on a set of challenging image sequences. The superior performance over other state-of-the-art algorithms is verified through the experiment. [ABSTRACT FROM PUBLISHER]

Low-rank models have been successfully applied to background modeling and achieved promising results on moving object detection. However, the assumption that moving objects are modelled as sparse outliers limits the performance of these models when the sizes of moving objects are relatively large. Meanwhile, inspired by the visual system of human brain which can cognitively perceive the physical size of the object with different sizes of retina imaging, we propose a novel approach, called Collaborative Low-Rank And Sparse Separation (CLASS), for moving object detection. Given the data matrix that accumulates sequential frames from the input video, CLASS detects the moving objects as sparse outliers against the low-rank structure background while pursuing global appearance consistency for both foreground and background. The sparse and the global appearance consistent constraints are complementary but simultaneously competing, and thus CLASS can detect the moving objects with different sizes effectively. The smoothness constraints of object motion are also introduced in CLASS for further improving the robustness to noises. Moreover, we utilize the edge-preserving filtering method to substantially speed up CLASS without much losing its accuracy. The extensive experiments on both public and newly created video sequences suggest that CLASS achieves superior performance and comparable efficiency against other state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Copyright of Application Research of Computers / Jisuanji Yingyong Yanjiu is the property of Application Research of Computers Edition and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents a novel discriminative, generative, and collaborative appearance model for robust object tracking. In contrast to existing methods, we use different appearance manifolds to represent the target in the discriminative and generative appearance models and propose a novel collaborative scheme to combine these two components. In particular: 1) for the discriminative component, we develop a graph regularized discriminant analysis (GRDA) algorithm that can find a projection to more effectively distinguish the target from the background; 2) for the generative component, we introduce a simple yet effective coding method for object representation. The method involves no optimization, and thus better efficiency can be achieved; and 3) for the collaborative model, we apply GRDA again to find a subspace for discriminating the likelihood features (generated from the discriminative and generative appearance models) and use the nearest neighbor criterion to determine the final likelihood. Besides, all the components are online updated so that our tracker can deal with appearance changes effectively. The experimental results over 23 challenging image sequences demonstrate that the proposed algorithm achieves better performance compared with other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Segmenting organisms or tumors from medical data (e.g., computed tomography volumetric images, ultrasound, or magnetic resonance imaging images/image sequences) is one of the fundamental tasks in medical image analysis and diagnosis, and has received long-term attentions. This paper studies a novel computational framework of interactive segmentation for extracting liver tumors from image sequences, and it is suitable for different types of medical data. The main contributions are twofold. First, we propose a collaborative model to jointly formulate the tumor segmentation from two aspects: 1) region partition and 2) boundary presence. The two terms are complementary but simultaneously competing: the former extracts the tumor based on its appearance/texture information, while the latter searches for the palpable tumor boundary. Moreover, in order to adapt the data variations, we allow the model to be discriminatively trained based on both the seed pixels traced by the Lucas–Kanade algorithm and the scribbles placed by the user. Second, we present an effective inference algorithm that iterates to: 1) solve tumor segmentation using the augmented Lagrangian method and 2) propagate the segmentation across the image sequence by searching for distinctive matches between images. We keep the collaborative model updated during the inference in order to well capture the tumor variations over time. We have verified our system for segmenting liver tumors from a number of clinical data, and have achieved very promising results. The software developed with this paper can be found at http://vision.sysu.edu.cn/projects/med-interactive-seg/ [ABSTRACT FROM PUBLISHER]

This paper adds to the growing remanufacturing literature by investigating a collaborative model in which the manufacturer serves as the remanufacturer's distributor while selling its own product. The paper extends the collaborative model that we have studied previously by characterizing it as a channel power structure under which the manufacturer plays the leader role in the collaboration. Furthermore, the paper compares this collaborative model with a competitive model in which the manufacturer competes with the remanufacturer in the market on pricing, sales volume and profit and finds that even if the manufacturer chooses to collaborate with the remanufacturer, it does not give up its market position; the manufacturer keeps the price of its product unchanged as the remanufactured product becomes increasingly acceptable to the consumer, and its product's sales volume remains unchanged in both models. Finally, this paper observes that the collaborative model benefits the manufacturer more than the competitive model, whereas the competitive model benefits the remanufacturer more than the collaborative model. Obviously, if collaboration benefits both of the manufacturer and remanufacturer, they will choose to collaborate, and the manufacturer will transfer part of its profit to the remanufacturer, but if competition brings them more profit, they will choose to compete in the market, and the remanufacturer will transfer part of its profit to the manufacturer. [ABSTRACT FROM AUTHOR]

Providing environmental flows is increasingly a management obligation in many water resource systems. Evaluating the impacts of environmental flow alternatives on other water uses in a basin can be a challenge, especially when collaborating with stakeholders. We demonstrate the use of system dynamics (SD) modeling to assess the impacts of four environmental flow alternatives in the Rio Chama, New Mexico. The model was developed to examine impacts of each alternative on reservoir storage and releases, hydropower production and revenue, and whitewater boating access. We simulated each alternative within a stochastic framework in order to explicitly incorporate hydrologic uncertainty into the analyses. The environmental flow alternatives were developed at a collaborative workshop of geomorphology, hydrology, and ecology experts. Results from the model indicate that the proposed flow recommendations on the Rio Chama will generally decrease annual reservoir storage, increase median flows, and have minimal impacts on hydropower production and whitewater rafting on the system. The Rio Chama case study is a promising example of how SD modeling can be used in the early stages of environmental flow studies and why it is compatible with collaborative modeling. [ABSTRACT FROM AUTHOR]

The paper presents the way one can create a cluster-type collaborative model, specific to the field of defense using methods specific to modeling. In this demarche we have opted for the IDEF method (a functional modeling method) so that the developed model should highlight its stages and activities, the input data, the control elements, the mechanisms governing the system and, finally, the output data. For this, we used the iGrafx Process 2013 software, which is the easiest-to-use tool for the analysis and simulation of processes specific to quality management and more. [ABSTRACT FROM AUTHOR]

Collaboration between Students, Educators and Business has always shown positive student experiences, but one pilot course for the Advanced Diploma of Management, organised by the NSW Waratahs rugby player development manager, has seen 12 students experience traditional classroom lectures, combined with Industry Guest speakers and Industry Site visits. A "Collaborative" model, this pilot course involves the shared campus of the University of Newcastle and the Central Coast Community College, along with businesses to help the students with site visits to sustain and compliment classroom learning. The pilot model also uses guest lectures from industry to give their own perspectives, including CEOs, CFOs, Board members and Chairpersons to give their experiences of business to the students. This model of "engagement and collaboration" has seen the students gain positive experiences, reflected in their learning and implemented in their classroom experience. A model of pedagogy sought by non- traditional learners who are not used to classroom lectures, the combination of industry visits and guest lectures is a model that keeps the students actively engaged. [ABSTRACT FROM AUTHOR]

This poetic, visual essay describes a collaborative, visual performance enacted by a cohort of Visual Arts pre-service teachers. The students mapped memories and experiences of their first teaching experience from practicum, motivated by discussion, stimuli and feedback. The mapping process had several loops where the students worked collectively to map their visual reflections onto large-scale canvases. These performance paintings became palimpsests, portraying layers of collaborative practice and learning. The networks of interactions, dialogue, relationships and group dynamics were exposed in the material practice of the participants. As an a/r/tographical rendering, the process simultaneously documented the group's subjective expressions as well as their emergent teacher identities. The collaborative model was at once both powerful and provocative as the dynamics of collective art-making evolved into reflections of developing pedagogy. This representation is a multivocal portrayal of the research; the voices of the researchers, students and artworks compete with and complement the other. [ABSTRACT FROM AUTHOR]

In today's society engineer professionals play a crucial role in tackling challenges such as climate change or economic constraints, in order to promote economical development and increase of quality of life ensuring principles like sustainability or safety. It is fundamental to prepare the future engineers to these and future challenges. According to the literature, traditional engineering educational strategies used to prepare the future engineers (lectures, lab experiences and homework) have two main drawbacks. Firstly, they inadequately prepare engineering students to engage in collaborative partnerships (essential for the practicing engineer) and, secondly, they promote passive learning and contribute to a compartmentalized curriculum. As such, the traditional deductive learning may not adequately prepare students for their innovative and flexible role as future engineers. An alternative approach is the use of nontraditional learning strategies, as in the case study hereby presented. Active learning strategies, namely project-based learning, were used to contribute to enhancing problem solving and higher order thinking skills of the graduates in Civil Engineering program of University of Aveiro, Portugal. Seizing the opportunity created by the Bologna process, two complementary courses on Geotechnical subjects (Soil Mechanics I and II) have been redesigned. The nontraditional strategies implemented include project-based learning using cooperative and collaborative models, put into practice since 2007/2008. The learning strategies referred are described and discussed. Their contribution to the development of problem solving and high order thinking skills of students is pointed out. Several strategies used to promote acceptance by students are put forward. The models were assessed using three strategies: students' feedback during the semester; academic performance; questionnaires at the end of the semester. The evolution of the students' response to these models is discussed using data collected in the courses. The models have been adapted to overcome some of the difficulties faced during their implementation. [ABSTRACT FROM AUTHOR]

This article illustrates issues that community radio stations in the stricken area of Northern Japan have faced, and discusses the necessity of social collaboration for supporting these radio stations. As of 1 December 2011, the Japanese Ministry of Internal Affairs and Communications had granted permission to operate special emergency-broadcast FM stations, providing earthquake-related information, to residents of 27 communities in the Tōhoku and North Kanto regions. Ten such community stations have used existing FM radio frequencies in their community for emergency broadcasting while 15 local governments set up newly established community-based radio stations by themselves, relying on: conventional community radio stations nationwide; national and international non-profit organizations; and voluntarily organized civic groups. Despite playing such an important role, community radio stations themselves have struggled to survive, not because of damage caused by the disaster, but as a result of the current social system based upon economic stability. Many of these stations have faced financial problems, such as losing advertising revenue and funding needed for equipment damaged by the disaster. It has become more difficult, particularly for the stations newly set up, to produce a variety of programs when the operation becomes prolonged. As the community radio plays a vital role as a lifeline to provide disaster-related information to residents, we need to establish a supportive system in society that allows community radio to function as intended. [ABSTRACT FROM AUTHOR]

Common mental health problems such as depression are an increasing source of disability worldwide. One key policy recommendation of the World Health Organisation is that treatment for mental health problems such as depression should be based in primary care However, there is less agreement about the best way to achieve effective collaboration between primary care and specialist services to meet key policy goals such as access, equity, cost effectiveness and patient-centredness. This paper describes the main models of collaborative working for depression, and examines evidence concerning the effectiveness of these different collaborative models in meeting policy goals. [ABSTRACT FROM AUTHOR]

Alcohol, tobacco and other drugs (ATOD) abuse and addiction are serious problems among Lebanese youth. Peer education on ATOD abuse in several settings has been found to be an effective way of prevention. This paper describes a collaborative project which trained 30 young activists to lead awareness campaigns in the Lebanon about ATOD abuse and healthy alternatives for relieving stress. The project was initiated by the Armenian Relief Cross in Lebanon (ARCL), funded by the Oxfam Canadian Fund for Social Development and implemented in collaboration with stakeholders in the Armenian community and Oum El Nour organization. Following training, the activists offered awareness sessions to a total audience of 5200:1250 secondary students, 50 university students, 1050 scouts, 300 working adolescents, 50 policemen and 2500 parents. Workshop objectives were met and awareness campaigns evaluated positively by the activists, parents of young people, ARCL and other stakeholders: leaders of Armenian institutions dealing with adolescents and the mayor of Bourj Hammoud. Resource constraints precluded seeking feedback from the young people who participated. Collaboration was deemed to have enhanced the capacity of ARCL, Oum El Nour, and the stakeholders in training young trainees to offer awareness campaigns. The author recommends continuing the project; offering another workshop to support the trainees and building in ways to evaluate the impact of the awareness campaigns on knowledge, attitude and behaviors of the young people taking part. To this effect, evaluation of the impact of the awareness campaigns is already started among school students with the use of control/comparison group design. [ABSTRACT FROM AUTHOR]

Two institutions representing two BSW and one MSW program and a geriatric education center collaborated in a John A. Hartford geriatric enrichment project. Sharing the risks and benefits of a collaborative model, 75 percent of faculty participated in mini faculty fellowships, and bi-monthly dinner meetings with colleagues from each of the three programs, and actively engaged in the curricula revisions. Faculty report pervasive geriatric enrichment in each program's foundation content areas, and increases in students placed in geriatric enriched field practicum settings, from pre-project levels of 8. 1 percent to a high of 24 percent. The features of the collaborative project include: respecting each program's autonomy while actively sharing ideas, resources and partnering with community's aging experts; and strengthening mutually reciprocal relationships among faculty and the gerontologic practice community. This model of shared risks and benefits also provides opportunities for innovation, diverse thinking, and shared decision making. [ABSTRACT FROM AUTHOR]

Copyright of Estudios Sobre Educacion is the property of Servicio de Publicaciones de la Universidad de Navarra, S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The role of the acute care nurse practitioner in Taiwan has changed significantly since the 1990s due in significant part to a shortage of interns and resident physicians in acute care settings. The first year of professional practice represents an important transitional year during which new professionals develop their competency to provide high-quality care to hospitalized patients. As the actual experience of individuals undergoing this transitional process into their new role has yet to be fully explored, this research studied and categorized the experiences of acute care nurse practitioners during their first year of role transition under the collaborative model of practice. We used a qualitative inquiry method with in-depth interviews to investigate the relevant experiences of 10 acute care nurse practitioners working at a medical center in Taiwan. Results show that the experience of expert nurses in their transition to acute care nurse practitioners passed through three phases during the first year under the collaborative practice model. These phases include the role ambiguity, role acquisition, and role implementation phases. Each phase contained a set of sub-themes which describe the multiple dimensions of this experience. This study highlights the experiences, stresses and accomplishments of acute care nurse practitioners during their initial year of advanced practice. [ABSTRACT FROM AUTHOR]

Conventional clustering algorithms are designed for a single independent dataset, i.e. Fuzzy C-Means (FCM) clustering algorithm. In the real world, a dataset is independent of other datasets but sometimes can be cooperative with others by exchanging information, such as the relationship between subsidiary companies. We should therefore consider the influence from other relative collaborative datasets while performing clustering learning under such collaborative circumstances. In this paper, three different collaborative models are discussed and new correct methods are proposed to quantitatively measure such collaboration between datasets, i.e. information gain. The corresponding collaborative clustering algorithms are presented accordingly and the theoretical analysis shows that the new cooperative clustering algorithms can finally converge to a local minimum. Experimental results demonstrate that the clustering structures obtained by new cooperative algorithms are different from those of conventional algorithms for the consideration of collaboration and the performances of these collaborative clustering algorithms can be much better than those conventional "single" clustering algorithms under the cooperating circumstances. [ABSTRACT FROM AUTHOR]

The Big Buddies' Program is a unique peer mentoring and tutoring project that was able to simultaneously address major service effectiveness issues at three local community organizations. Through a collaborative effort, these agencies designed this innovative approach for preventing school dropout, increasing youth's interest in volunteerism, and expanding real-world learning experiences for university undergraduate students in social work. The article outlines in detail the program set-up, selection of participants, schedule and location of buddy time, content of mentor/tutor training, coordination of the program, use of materials with plans, and the program evaluation design. Future implications of the model are provided along with guidelines for duplicating this innovative collaborative approach in other communities. [ABSTRACT FROM AUTHOR]

Communication is dynamic, social, challenging, and a key quality factor for construction projects. This is especially the case in multinational and inter-organizational infrastructure projects where factors like culture and language differ among the involved actors. As infrastructure projects usually extend over longer periods of time, collaborative relationships need to be established in which the actors can develop, for example, mutual understanding, learning, and efficient working routines. By building on empirical data from contemporary infrastructure projects, we explore how international contractors and a large public client communicate in multinational infrastructure projects (i.e., what the challenges are and what competences are needed). The analysis is based on the linguistic framework of communicative competence, and we contribute to the development of collaborative models in construction project management by suggesting the concept of contextual communicative competence. [ABSTRACT FROM AUTHOR]

Copyright of Psycho-Oncologie is the property of Tech Science Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: General practitioners (GPs) play an important role in the physical care of patients with severe mental illness, so our aim was to analyse the relationships between GPs' sociodemographic status and worked-related variables and their perceptions about mental illness. Methods: A descriptive, cross-sectional study was conducted in the Clinical Management Unit of Mental Health (CMU-MH) of the Regional Hospital of Malaga (Spain). The eligible population comprised all GPs working in the 13 primary care centres (PCCs) in the hospital's catchment area during the study period. GPs were interviewed to collect data on their attitudes to and knowledge of mental illness, psychiatry and the local mental health team, as well as their sociodemographic status, professional qualifications and experience. Bivariate analysis was carried out. Results: 145 GPs answered the questionnaire (77%). ANOVA revealed that most of the PCCs with the best relationship with their mental health team and best attitude to mental illness were in the Central Community Mental Health Unit, which operated a collaborative model of care. Conclusions: These results indicated that GPs who worked more closely with their specialist mental health team had a better perception of their relationship with the mental health centre and less stigmatisation in regard to mental illness. [ABSTRACT FROM AUTHOR]

Aim: This paper describes the implementation of a Collaborative Model of Fieldwork Education in a regional hospital occupational therapy department. Methods: The literature on models of fieldwork education for occupational therapy students is reviewed, and an approach to the implementation of the collaborative model with three students to one clinical educator is described after piloting of this model's recommendations, arising from the pilot placement, are proposed. Conclusions: The implementation of a Collaborative Model of Fieldwork Education requires careful planning, close links with the university fieldwork team and a willingness on the behalf of occupational therapist clinical educators to explore alternative approaches to the provision of fieldwork education. [ABSTRACT FROM AUTHOR]