Context Of Requirements Research Articles

GraphicsAssist: Visual Artist’s Assistant for Narration-to-Illustrative Graphic Composition

Storytelling is an art that very few can carry with ease, putting in proper context the feelings and emotions of the characters, their setting, interactions, etc. This work attempts to recreate storytelling to form a graphic illustration for users so that the essence of the story is not lost in transference from one person to another, from storyteller to graphic illustration reader/user. ‘GraphicsAssist’ is an artist assistance system for graphic artists to help them generate certain options for usage as graphic frames. Text analysis has been exploited to understand contextual requirements or storytelling. Natural language-based learning has been applied to this requirement. The transfer-learning-based model is used to find suitable matches for the characters and visual environment settings. Illustrative drawings and their tags are considered a part of the frame database. Once the narration entities of the story are extracted, they are matched with the drawing tags and presented to the designer for framing and then panelling of graphic illustration. The chosen frames are displayed in panels in grid format. In its current form, manipulation of the selected drawings for the task of forming frames is, as yet, restricted. The aesthetic transition from frame to frame is yet lacking and may be integrated into later works. The work of this artist’s assistance system is validated by the test group, which gave feedback on some pre-defined parameters. Though the system has its drawbacks, it is the first step towards such a system that provides a computational translation model for translating a textual narration to a set of visual composition frames. This work aims to capture the nuances, characters, emotions, story setting, etc., from textual narration as an input of the story and convert it to the graphic illustration in 2D form by incorporating illustrative drawings as its visual translation.

Post-fault restoration of service function chains in fog networks

The network function virtualization (NFV) paradigm is rapidly being adopted by enterprises and service providers as an alternative to proprietary hardware. It enables virtual network functions (VNFs) to be embedded on commercial edge servers for the delivery of highly-specialized service function chains (SFCs). Here embedding SFC requests on fog computing supports clients with stringent delay requirements and contextual service requirements. Now one of the major challenges is the survivability of embedded service chains in fog computing, which may be compromised due to node, link, and application failures. These failures can disrupt service continuity and degrade the quality-of-service. Therefore, there is a demand for SFC provisioning to be more resilient, incorporating rapid restoration techniques that oppose proactive solutions that reserve backup paths, subsequently compromising network capacity. Hence, this paper presents heuristic methods for post-fault SFC restorations due to multiple failures in fog computing. These methods establish post-provisioning restoration for failed requests, known as end-to-end (E2E) and intermediate (IM) restoration, that aim to restore paths with the least delay and cost.

Understanding the Sociocultural Challenges and Opportunities for Affordable Wearables to Support Poststroke Upper-Limb Rehabilitation: Qualitative Study.

People who survive a stroke in many cases require upper-limb rehabilitation (ULR), which plays a vital role in stroke recovery practices. However, rehabilitation services in the Global South are often not affordable or easily accessible. For example, in Bangladesh, the access to and use of rehabilitation services is limited and influenced by cultural factors and patients' everyday lives. In addition, while wearable devices have been used to enhance ULR exercises to support self-directed home-based rehabilitation, this has primarily been applied in developed regions and is not common in many Global South countries due to potential costs and limited access to technology. Our goal was to better understand physiotherapists', patients', and caregivers' experiences of rehabilitation in Bangladesh, existing rehabilitation practices, and how they differ from the rehabilitation approach in the United Kingdom. Understanding these differences and experiences would help to identify opportunities and requirements for developing affordable wearable devices that could support ULR in home settings. We conducted an exploratory study with 14 participants representing key stakeholder groups. We interviewed physiotherapists and patients in Bangladesh to understand their approaches, rehabilitation experiences and challenges, and technology use in this context. We also interviewed UK physiotherapists to explore the similarities and differences between the 2 countries and identify specific contextual and design requirements for low-cost wearables for ULR. Overall, we remotely interviewed 8 physiotherapists (4 in the United Kingdom, 4 in Bangladesh), 3 ULR patients in Bangladesh, and 3 caregivers in Bangladesh. Participants were recruited through formal communications and personal contacts. Each interview was conducted via videoconference, except for 2 interviews, and audio was recorded with consent. A total of 10 hours of discussions were transcribed. The results were analyzed using thematic analysis. We identified several sociocultural factors that affect ULR and should be taken into account when developing technologies for the home: the important role of family, who may influence the treatment based on social and cultural perceptions; the impact of gender norms and their influence on attitudes toward rehabilitation and physiotherapists; and differences in approach to rehabilitation between the United Kingdom and Bangladesh, with Bangladeshi physiotherapists focusing on individual movements that are necessary to build strength in the affected parts and their British counterparts favoring a more holistic approach. We propose practical considerations and design recommendations for developing ULR devices for low-resource settings. Our work shows that while it is possible to build a low-cost wearable device, the difficulty lies in addressing sociotechnical challenges. When developing new health technologies, it is imperative to not only understand how well they could fit into patients', caregivers', and physiotherapists' everyday lives, but also how they may influence any potential tensions concerning culture, religion, and the characteristics of the local health care system.

A Design Vocabulary for Scaffolding Group Interaction Archetypes through Synchronous Telephony

Multiple HCI projects have demonstrated the potential of digitally-enhanced, synchronous telephony platforms for use with and by resource-limited communities. However, these platforms were each designed to only facilitate a single archetype of community engagement, limiting their capacity for adaptation when contextual or stakeholder requirements change. This paper builds upon these projects to introduce a design vocabulary, grounded in a formal ontology describing the core components necessary to run adaptable, structured engagements through synchronous group telephony. Through a series of scenarios, we present how this design vocabulary can be used to: help design and communicate different models of synchronous audio engagements, describe existing technologies, and highlight other novel ways in which such platforms could be used. We discuss how while under-explored to this point, synchronous telephony platforms can be designed to orchestrate stakeholder engagements with a degree of flexibility previously impossible in remote, offline contexts.

Steps to Prepare Bilingual Data for Analysis: A Methodological Approach

This methodological paper offers a five-step model for preparing bilingual data for analysis. The article is guided by research in translating bilingual data into qualitative research. A systematic analysis of the research studies was conducted to identify workable options for preparing bilingual data for analysis. The proposed five-step model is comprised of (1) translator’s worldview and professionalism, (2) epistemological, ontological, and methodological considerations, (3) line of translation, (4) responsiveness to cultural terms and (5) eagerness to trustworthiness and reliability of the data. Researcher’s worldviews encompass the visibility of translator’s positionality for reflexivity, avoidance of biasness, and demonstration of professionalism. The bilingual data needs treatment based on epistemological, ontological, and methodological orientations which the translators need to be mindful of. The researcher must be clear on the line of translation in opting for direct translation, back-translation, single translation, or multiple translations. The translated data must be responsive to the cultural contexts to carry on sense and meaning. Depending on the methodological approaches and contextual requirements, the translation work must meet the needs of trustworthiness and validity. The literature is silent on the translations of non-verbal cues. Therefore, this problem should be dealt with separately in future research endeavors. Similarly, future research on linguistic contexts and translation work in diverse research approaches such as quantitative, qualitative, and mixed methods is needed.

Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units

Weaning patients from ventilation in intensive care units (ICU) is a complex task. There is a growing desire to build decision-support tools to help clinicians during this process, especially those employing Artificial Intelligence (AI). However, tools built for this purpose should fit within and ideally improve the current work environment, to ensure they can successfully integrate into clinical practice. To do so, it is important to identify areas where decision-support tools may aid clinicians, and associated design requirements for such tools. This study analysed the work context surrounding the weaning process from mechanical ventilation in ICU environments, via cognitive task and work domain analyses. In doing so, both what cognitive processes clinicians perform during weaning, and the constraints and affordances of the work environment itself, were described. This study found a number of weaning process tasks where decision-support tools may prove beneficial, and from these a set of contextual design requirements were created. This work benefits researchers interested in creating human-centred decision-support tools for mechanical ventilation that are sensitive to the wider work system.

Building consensus on common features and interoperability use cases for community health information systems: a Delphi study

IntroductionInformation systems for community health have become increasingly sophisticated and evidence-based in the last decade and they are now the most widely used health information systems in many low-income and...

ADVANTAGES AND DISADVANTAGES OF THE RESOURCE MANAGEMENT SYSTEM IN THE HIGHER EDUCATION SYSTEM OF KAZAKHSTAN

Resource management is crucial for ensuring quality education and research in higher education institutions. The higher education system in Kazakhstan has undergone various reforms to improve resource allocation and utilization. This paper examines the advantages and disadvantages of the current resource management system in Kazakhstan's higher education. The centralized governance model concentrates decision-making powers regarding resource allocation with the Ministry of Education and Science. This allows aligned strategic development and coordinated quality assurance across all higher education institutions. However, centralized control limits institutional autonomy and flexibility in resource utilization. The norms-based financing methodology promotes equitable distribution of resources based on objective workload indicators. But it overlooks qualitative outcomes and contextual requirements of individual institutions. The focus on per capita financing norms overlooks the need for optimal allocation across different expenditure heads. The analysis suggests that the resource management system has ensured stability and quality control in Kazakhstan's higher education system. However, there is a need for calibrated reforms to allow greater institutional autonomy along with accountability; balanced financing across different inputs; and linking resource allocation with qualitative outcomes. The recommendations include development of institutional leadership capabilities, clustered/differentiated approach to financing, linking funding with outcomes, and adoption of total quality management principles in resource governance.

Word order and context in sentence processing: evidence from L1 and L2 Russian.

In this paper, we studied how native (L1) speakers of Russian and speakers of Mandarin Chinese learning Russian as a foreign language (L2) process Russian sentences with different word orders. We compared SVO (canonical) and OVS (non-canonical) orders in isolation and in context. Experiments focusing on the L2 processing of different word orders are still not very numerous, and those using context are extremely rare. In Experiment 1, target sentences were presented in isolation. In Experiment 2, one-sentence contexts introduced one NP mentioned in the target sentence, either the first (so that given information preceded new information, which is characteristic for Russian and many other languages) or the second. As a result, two factors could be compared: the syntactic (word order) and the contextual (whether the context is appropriate from the information-structural perspective). We used different measures to capture online and offline effects: word-by-word reading times, question-answering accuracy and sentence rating on a 1 to 5 scale (for L1 participants). In both experiments, RTs and question-answering accuracy data showed that non-canonical orders were difficult for L2 participants, but not for L1 participants. However, L1 participants gave non-canonical orders lower ratings in isolation, presumably because in naturally occurring texts, they are used only in particular contexts. As for the context factor in Experiment 2, some effects were the same for L1 and L2 processing: all participants read given NPs faster than new ones and preferred sentences with a 'given - new' word order. The latter may reflect the universal principles of narrative coherence. However, unlike native speakers, L2 readers are not sensitive to more subtle contextual requirements of different word orders.

Cross‐network service recommendation in smart cities

SummaryNowadays, Internet of Things, artificial intelligence, cloud computing, and other revolutionary technologies (e.g., edge and fog computing) have become the pillar of smart cities. These latter make users' lives easier, thanks to a wide variety of smart services offered in different dimensions (e.g., smart living, smart mobility, smart economy, smart governance). However, the rapid adoption of smart services by users and the full servicelization of several cities around the world is faced with two major issues: the lack of knowledge regarding smart services' capacities (e.g., features, contextual requirements, pricing models, privacy policies, provisioning terms, etc.), and the lack of unified rating and quantification of smart services' QoS behavior. Indeed, interested users often exploit traditional search tools (e.g., Web search engines, social networks) to find and rate the needed services. This behavior has scattered the smart services' usage data (e.g., users contexts, ratings) across multiple providers platforms, which makes the search task beyond the capacity of users and, even, other service providers. Although recommender systems are a natural solution to exempt users from exploring the huge space of the offered smart services, current recommendation approaches for smart city environments are unable to deliver correct recommendations. In fact, they have been initially designed to single‐network settings (a single service repository), while smart services' consumers often are involved in multiple provider platforms. To the best of our knowledge, there exists no approach that treated smart service recommendation across multiple information networks. Therefore, the goal of this paper is to propose a cross‐network recommender system for smart cities. We first model the multiplex network of smart services' providers as a multirelational fuzzy lattice family thanks to fuzzy relational concept analysis (fuzzy RCA), which is a powerful mathematical method for data analysis and clustering. We also use the concept of anchor users to connect providers networks via the users involved in more than one provider platform. Guided by anchors' cross‐network relations, we compute the similarity between users and we define algorithms for exploring the smart services' information network, i.e. lattice family. Extensive experiments have proved the effectiveness of cross‐network recommendation and the quality of produced recommendations, compared to state‐of‐the‐art single‐network recommendation.

Teachers’ Strategies in ESP Learning Program in Indonesia: A Comparative Study

This research article examines various strategies utilized by English teachers in English for Specific Purposes (ESP) learning programs in Indonesia, focusing on the Social and Science study programs. The study used a qualitative research design to conduct in-depth interviews with 25 English teachers, which aim to investigate and compare the pedagogical approaches used to satisfy the unique linguistic and contextual requirements of these two academic disciplines. Through purposive sampling, English teachers from both Social and Science study programs participate in semi-structured interviews, providing rich insights into their instructional methods. The purpose of the qualitative analysis is to reveal trends, similarities, and differences in the strategies used, providing a detailed understanding of the complexities of ESP teaching methods. The findings reveal illumination on the specific strategies employed by English teachers in the Social and Science study programs, demonstrating how these strategies are shaped by curriculum complexity and the backgrounds of the learners. The comparative study highlights the significance of pedagogical techniques tailored to individual contexts and serves as a basis for making well-informed decisions in curriculum development and teacher training. This study has wider implications for improving English for Specific Purposes (ESP) learning programs in Indonesia and adds to the continuing discussion on effective language teaching. This study also provides helpful recommendations for educators, curriculum developers, and policymakers aiming to enhance language learning experiences in ESP environments.

Understanding via exemplification in XAI: how explaining image classification benefits from exemplars

AbstractArtificial intelligent (AI) systems that perform image classification tasks are being used to great success in many application contexts. However, many of these systems are opaque, even to experts. This lack of understanding can be problematic for ethical, legal, or practical reasons. The research field Explainable AI (XAI) has therefore developed several approaches to explain image classifiers. The hope is to bring about understanding, e.g., regarding why certain images are classified as belonging to a particular target class. Most of these approaches use visual explanations. Drawing on Elgin’s work (True enough. MIT Press, Cambridge, 2017), I argue that analyzing what those explanations exemplify can help to assess their suitability for producing understanding. More specifically, I suggest to distinguish between two forms of examples according to their suitability for producing understanding. I call these forms samples and exemplars, respectively. Samples are prone to misinterpretation and thus carry the risk of leading to misunderstanding. Exemplars, by contrast, are intentionally designed or chosen to meet contextual requirements and to mitigate the risk of misinterpretation. They are thus preferable for bringing about understanding. By reviewing several XAI approaches directed at image classifiers, I show that most of them explain with samples. If my analysis is correct, it will be beneficial if such explainability methods use explanations that qualify as exemplars.

BSCSML: Design of an Efficient Bioinspired Security &Privacy Model for Cyber Physical System using Machine Learning

With the increasing prevalence of Smart Grid Cyber Physical Systems with Advanced Metering Infrastructure (SG CPS AMI), securing their internal components has become one of the paramount concerns. Traditional security mechanisms have proven to be insufficient in defending against sophisticated attacks. Bioinspired security and privacy models have emerged as promising solutions due to their stochastic solutions. This paper proposes a novel bio-inspired security and privacy model for SG CPS AMI that utilizes machine learning to strengthen their security levels. The proposed model is inspired by the hybrid Grey Wolf Teacher Learner based Optimizer (GWTLbO) Method’s ability to detect and respond to threats in real-time deployments. The GWTLbO Model also ensures higher privacy by selecting optimal methods between k-privacy, t-closeness & l-diversity depending upon contextual requirements. This study improves system accuracy and efficiency under diverse attacks using machine learning techniques. The method uses supervised learning to teach the model to recognize known attack trends and uncontrolled learning to spot unknown attacks. Our model was tested using real-time IoT device data samples. The model identified Zero-Day Attacks, Meter Bypass, Flash Image Manipulation, and Buffer-level attacks. The proposed model detects and responds to attacks with high accuracy and low false-positive rates. In real-time operations, the proposed model can handle huge volumes of data efficiently. The bioinspired security and privacy model secures CPS efficiently and is scalable for various cases. Machine learning techniques can improve the security and secrecy of these systems and revolutionize defense against different attacks.

The contextual information requirements for collection and use of occupant feedback in BIM-enabled FM

PurposeOccupant feedback is crucial for healthy, comfortable and productive offices. Existing facility management (FM) systems are limited in effective use of occupant feedback, as they fail to collect the vital contextual information (e.g. related building element, space) associated with the feedback. The purpose of this study is to formalise the contextual information requirements for structured collection of occupant feedback for rapid diagnosis and resolution of problems and integrating occupant feedback with building information modelling (BIM) for making use of its visualisation and analysis capabilities, and eventually for effective use of occupant feedback in FM operations.Design/methodology/approachA mixed-methods approach was conducted in four steps: (1) identifying occupant feedback types (e.g. echo in meeting room) in office buildings, (2) examining the current practice in collecting and processing occupant feedback via use cases, (3) determining the contextual information requirements via expert interviews and (4) validation of the information requirements via a BIM-integrated prototype.FindingsThe findings present the contextual information requirements for 107 occupant feedback types grouped under thermal comfort, indoor air quality, acoustic comfort, visual comfort, building design and facility services.Practical implicationsFeedback-specific contextual information items enable structured data collection and help to avoid missing data and minimise the time lost in manual data entry and recursive interaction with the occupants during FM operations.Originality/valueThe contextual information requirements determined are expected to enhance occupant satisfaction and FM performance in office buildings by better use of the occupant feedback and integration into BIM-enabled FM and can be extended to other building types in future studies by using the proposed methodology.

Defending explicability as a principle for the ethics of artificial intelligence in medicine

The difficulty of explaining the outputs of artificial intelligence (AI) models and what has led to them is a notorious ethical problem wherever these technologies are applied, including in the medical domain, and one that has no obvious solution. This paper examines the proposal, made by Luciano Floridi and colleagues, to include a new ‘principle of explicability’ alongside the traditional four principles of bioethics that make up the theory of ‘principlism’. It specifically responds to a recent set of criticisms that challenge the supposed need for such a principle to perform an enabling role in relation to the traditional four principles and therefore suggest that these four are sufficient without the addition of explicability. The paper challenges the critics’ premise that explicability cannot be an ethical principle like the classic four because it is explicitly subordinate to them. It argues instead that principlism in its original formulation locates the justification for ethical principles in a midlevel position such that they mediate between the most general moral norms and the contextual requirements of medicine. This conception of an ethical principle then provides a mold for an approach to explicability on which it functions as an enabling principle that unifies technical/epistemic demands on AI and the requirements of high-level ethical theories. The paper finishes by anticipating an objection that decision-making by clinicians and AI fall equally, but implausibly, under the principle of explicability’s scope, which it rejects on the grounds that human decisions, unlike AI’s, can be explained by their social environments.

Reflection on visioning as a leadership practice

This reflective essay argues that public school principals in China and Southeast Asia often demonstrate an inadequate understanding of their visioning responsibilities. They overlook the importance of creating a unique school vision that is tailored to their contextual requirements. Setting direction through a clear vision for the school is one of the four core leadership practices and has been extensively explored around the world. By drawing on personal reflection, this essay highlights the imperative for school principals from the regions to actively participate in developing a school vision that is contextually responsive for their school and also aligns with the guidelines of the department of education. Using three personal examples, it underscores the crucial role that visioning plays in a school's success and the indispensability of stakeholder's involvement in the visioning process.

Connecting the Dot: Understanding the Link between Secondary School Heads' Leadership Styles and Teacher Performance

School Heads assume the ultimate obligation of accountability for student Academic excellence and teachers' performance in their institutions. The current Research exploration endeavored to analyze how the different leadership styles of school heads affect the performance of their teachers at public secondary schools in Multan. A descriptive research approach was employed in the current investigation. Data was collected using a questionnaire from a sample of four hundred and nineteen (419), including 187 male and 232 female teachers selected through stratified random sampling from secondary schools in the district of Multan, South Punjab, Pakistan. According to key highlighted observations of the study, Heads practiced all mixed leadership styles according to contextual requirements. However, no statistically significant differences were observed between teachers in terms of their professional and academic backgrounds or on the basis of their teaching experience. Moreover, according to manifested results, teachers' performance varied significantly according to their locations and gender. This study may help identify leadership approaches that inspire and empower teachers, leading to higher levels of productivity and overall job performance. Additionally, it is recommended that training for cultivating leadership styles that positively impact teacher performance be provided in educational institutions.

Achieving operational resilience through kaizen practice: a case in a commercial livestock farm in Nigeria

PurposeThis study is focused on achieving operational resilience through the practices of kaizen across the operational structure. The research is based on a case study of a commercial livestock farm in Nigeria. The study views the practice of kaizen from the perspective of the commitment of the members of the case study organisation who are directly involved with the operations of the organisation.Design/methodology/approachThe study applies a qualitative approach to explore the topic, engaging members of the case study organisation in the research to gather relevant data on the implementation of kaizen practices and the drive to attain resilience in the case study organisation. Semi-structured personal interviews and workshops were used for data collection. The study adopts systems theory to explore the topic, identifying and engaging relevant stakeholders.FindingsParts of the findings relating to kaizen are the issues with the livestock production process, aggressive leadership and the issue of livestock mortality in the case study organisation. These were discussed based on extant literature. The study affirms the importance of organisational members' commitment and adequate leadership support to achieve sustainable kaizen practices. The study highlights the need to align kaizen practices with relevant organisational practices, such as reward systems and contextual requirements for its implementation in an operational process. The study suggests that further study can focus on the dynamics of the legal system on the implementation of kaizen, especially from a developing economic background like Nigeria, where this study was conducted.Originality/valueThe study projects learning about the spatial factors that can affect the practices of kaizen in critical sectors like livestock management.

Comparison of the forward and sideways locomotor patterns in children with Cerebral Palsy

Switching locomotion direction is a common task in daily life, and it has been studied extensively in healthy people. Little is known, however, about the locomotor adjustments involved in changing locomotion direction from forward (FW) to sideways (SW) in children with cerebral palsy (CP). The importance of testing the ability of children with CP in this task lies in the assessment of flexible, adaptable adjustments of locomotion as a function of the environmental context. On the one hand, the ability of a child to cope with novel task requirements may provide prognostic cues as to the chances of modifying the gait adaptively. On the other hand, challenging the child with the novel task may represent a useful rehabilitation tool to improve the locomotor performance. SW is an asymmetrical locomotor task and requires a differential control of right and left limb muscles. Here, we report the results of a cross-sectional study comparing FW and SW in 27 children with CP (17 diplegic, 10 hemiplegic, 2–10 years) and 18 age-matched typically developing (TD) children. We analyzed gait kinematics, joint moments, EMG activity of 12 pairs of bilateral muscles, and muscle modules evaluated by factorization of EMG signals. Task performance in several children with CP differed drastically from that of TD children. Only 2/3 of children with CP met the primary outcome, i.e. they succeeded to step sideways, and they often demonstrated attempts to step forward. They tended to rotate their trunk FW, cross one leg over the other, flex the knee and hip. Moreover, in contrast to TD children, children with CP often exhibited similar motor modules for FW and SW. Overall, the results reflect developmental deficits in the control of gait, bilateral coordination and adjustment of basic motor modules in children with CP. We suggest that the sideways (along with the backward) style of locomotion represents a novel rehabilitation protocol that challenges the child to cope with novel contextual requirements.

Accreditation Approaches for Professional Education Programs: Toward Best Practice.

Accreditation has a central role in the quality assurance of professional education programs, but research on the effectiveness of different models of accreditation is limited. The purpose of this study was to rapidly appraise the evidence for the effectiveness, impact, and feasibility of different accreditation approaches, in order to inform best practices for the accreditation of professional education programs. The study focused on accreditation for programs that produce practice-ready graduates, including for veterinary programs. The authors searched several databases for articles published from 2000 to 2020, using search terms identified during a scoping phase, and applied a "rapid review" methodology in line with contextual, time, and resource requirements. Relevant articles that were classed as empirical or conceptual were included in the study, while papers appraised as solely commentaries or descriptive were excluded from the evidence base. The full-text review included 32 articles. We identified a clear transition in the literature from input- and process-based models (pre- and early 2000s) to outcomes-based models (in the 2000s and early 2010s). Continuous quality improvement and targeted models (including risk-based and thematic) represent more recent approaches in accreditation practice. However, as noted by other scholars, we identified limited empirical evidence for the relative effectiveness of different accreditation approaches in professional education, although evidence for the more recent accreditation approaches is emerging. In terms of best practice in view of the current lack of definitive evidence for the adoption of any specific model of accreditation, we argue that accrediting authorities adopt a contextual approach to accreditation that includes clearly articulating the purpose and focus of their regulatory activities, and selecting and implementing accreditation methods that are consistent with their underlying principles.