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"Systems planning"
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A Review of Medical Image Segmentation Algorithms
INTRODUCTION: Image segmentation in medical physics plays a vital role in image analysis to identify the affected tumour. The process of subdividing an image into its constituent parts that are homogeneous in feature is called Image segmentation, and this process concedes to extract some useful information. Numerous image segmentation techniques have been developed, and these techniques conquer different restrictions on conventional medical segmentation techniques. This paper presents a review of medical image segmentation techniques and statistical mechanics based on the novel method named as Lattice Boltzmann method (LBM). The beauty of LBM is to augment the computational speed in the process of medical image segmentation with an accuracy and specificity of more than 95% compared to traditional methods. As there is not much information on LBM in medical physics, it is intended to present a review of the research progress of LBM.OBJECTIVE: As there is no review paper on the research progress of the LB method, this paper presents a review with an objective to give some thought regarding the different segmentation for medical image and novel LB method to advance interest for future investigation and exploration in medical image segmentation.METHODS: This paper in attendance a short review of medical image segmentation techniques based on Thresholding, Region-based, Clustering, Edge detection, Model-based and the novel method Lattice Boltzmann method (LBM).CONCLUSION: In this paper, we outlined various segmentation techniques applied to medical images, emphasize that none of these problem areas has been acceptably settled, and all of the algorithms depicted are available for broad improvement. Since LBM has the benefits of speed and adaptability of modelling to guarantee excellent image processing quality with a reasonable amount of computer resources, we predict that this method will become a new research hotspot in image processing.
Journal Article
Critical success factors of strategic information systems planning: a Delphi approach
PurposeStrategic information systems planning (SISP) has been identified as a key strategy underpinning an effective utilization of information systems (IS) to achieve the core objectives of an organization. This study aims at identifying, ranking and prioritizing factors that IS and business executives consider critical for the success of IS projects.Design/methodology/approachThis study adopted a qualitative research approach with a 3-round Delphi process to get experts' opinions on critical success factors (CSFs) necessary for successful SISP. A forty-two panel of experts was selected using defined criteria. Quantitative analyses of the data were performed using Kendall's coefficient of concordance and chi-square to obtain a consensus among the experts.FindingsThe findings revealed the top managers' understanding of strategic priorities, aligning IS strategies with the organizational strategic plan and availability of internal resources to deliver IS services as the first three key CSFs of SISP. Other highly ranked CSFs were the management's understanding of the role of IS and the need to educate top management on the importance of IT in supporting the business strategy.Originality/valueThe CSFs factors obtained in this study would lay a foundation for future research and could be incorporated into a new theoretical model of IS planning.
Journal Article
Healthy people, healthy land: driving sustainable food systems transformation with community agroecological values and Indigenous food systems planning in Kakisa, Northwest Territories, Canada
Food systems in northern Canada are under severe pressure brought on by climate change, colonial policies, resource extraction, settler migration, dispossession from ancestral lands, and changing ways of life. As communities seek to nurture more resilient food systems, agroecology is emerging as a relevant food system framing to address these challenges as it balances new forms of sustainable food production with traditional food practices and connects them to on-going struggles for self-sufficiency and Indigenous food sovereignty. This article showcases insights from a community-driven, food systems planning project in Northwest Territories, Canada that incorporates agroecology rooted in Indigenous values, principles, and Traditional Knowledge of the region. Using participatory action research, the Ka’a’gee Tu First Nation (KTFN) designed a vision for their food system structured by the Community Agroecological Values Framework (CAVF). The CAVF, co-created with KTFN, builds on the community capitals framework and northern agroecology dialogues to foster a holistic approach to Indigenous food systems planning. Through a workshop, participatory mapping, and storytelling, community members reflected on existing food projects and provided input on future developments. KTFN used this process to connect their food system with multiple components of agroecology in the North, including land stewardship, sustainable livelihoods, cultural resurgence, social cohesion, good governance, and human capacity, aligning them with Dene values of holistic well-being for people and the environment. This article shares a case study of how KTFN is combining participatory, values- and place-based planning with agroecology to strengthen their food system, advance self-sufficiency, and promote food sovereignty in the face of climate uncertainties.
Journal Article
Electric vehicles in a smart grid: a comprehensive survey on optimal location of charging station
The burning of fossil fuels and the emission of greenhouse gases motivates policymakers to think about the transition in their approach towards electric vehicles (EVs) from conventional ones. Transportation vehicles’ electrification drives the attention of various researchers and scientists towards the emergence of charging stations (CSs). CS placement is a matter of great concern for large scale penetration of EVs. Old infrastructure causes several challenges in planning the ideal placement of the CS since EVs have not prevailed in recent years. Recently, a lot of studies have been performed on CS placement, which attracts the attention of researchers. Various approaches, objective functions, constraints and range of optimisation techniques are addressed by researchers for optimal placement of CS. This study provides the research outcomes in respect of the placement of CS over the past few years based on objective functions, solution methods, geographic conditions and demand-side management.
Journal Article
Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions
Big data has potential to unlock novel groundbreaking opportunities in power grid that enhances a multitude of technical, social, and economic gains. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data. In particular, computational complexity, data security, and operational integration of big data into power system planning and operational frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. In this context, suitable big data analytics combined with visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into power system planning and operational frameworks. Detailed information for utilities looking to apply big data analytics and insights on how utilities can enhance revenue streams and bring disruptive innovation are discussed. General guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.
Journal Article