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نتیجه جستجو - خوشه ها

تعداد مقالات یافته شده: 37
ردیف عنوان نوع
1 Experts’ multiple criteria evaluations of fuel management options to reduce wildfire susceptibility: The role of closer knowledge of the local socioeconomic context
ارزیابی معیارهای چندگانه کارشناسان گزینه های مدیریت سوخت برای کاهش حساسیت به آتش سوزی:نقش دانش دقیق تر از زمینه اجتماعی-اقتصادی محلی-2021
Expert opinion can be a valuable tool for informed decision making. Concerning wildfire susceptibility reduction at the landscape scale, forest ecosystem experts play a key role in offering advice about appropriate fuel man- agement practices to be applied by forest owners or their organizations, and in shaping public policies. A literature review aimed at identifying fuel management interventions and techniques found multiple and even opposing strategies. Recognizing the interdisciplinary and multi-dimensional nature of fuel management, we go beyond existing studies on forest experts’ opinions by comparing evaluations across forest experts with diverse training and experience, and by considering different evaluation criteria such as technical effectiveness, impact on soil or biodiversity, socioeconomic impact, and preference. Following an online survey to a sample of Por- tuguese experts, distinct socio-professional clusters were established and experts’ evaluations associated with their views on fire, forests, owners’ coordination, and rural development. Results show that experts rank their preferences by weighing effectiveness and impacts in different ways. Closer knowledge of the local context distinguishes expert preference, favouring more active fuels reduction strategies. Since experts with a closer knowledge of socioeconomic context tend to be further from policy-making processes, we urge their more balanced participation in those processes.
keywords: مدیریت منظره | کاهش حساسیت وحشی | مدیریت چند مالکیت | جنگلداری کوچک | تظاهرات کارشناس | Landscape management | Wildfire susceptibility reduction | Multi-ownership management | Small-scale forestry | Expert elicitation
مقاله انگلیسی
2 Past, present, and future of knowledge management for business sustainability
گذشته، حال، و آینده مدیریت دانش برای پایداری کسب و کار-2021
Knowledge management has gained increasing importance and immense research interest for its promise in advancing sustainability. Despite its proliferation in the literature, little is known about the research profile of knowledge management research intertwined with sustainability. Given this gap, this article aims to conduct an extensive review of knowledge management for sustainability research. Using bibliometrics, which is suitable for large-scale reviews, this article reviews 1136 documents published in peer-reviewed journals indexed in the Web of Science between 2001 and 2021. Noteworthily, the review sheds light on the performance of research con- stituents (e.g., most prolific authors, countries, institutions, and journals), as well as the themes and topics underpinning the intellectual structure (i.e., knowledge foundation, knowledge creation) in the field. Specif- ically, the review reveals that knowledge management for sustainability research has relied on nine foundational clusters (i.e., informed sustainability practice, social network, firm performance, knowledge sharing culture, green innovation, sustainability assessment framework, global warming, knowledge management, and innova- tive performance) to generate new knowledge across 10 thematic clusters, (i.e., ecological knowledge, green innovation, the Shanghai Hongqiao district effect, the Agroscope Research Master Plan, food security, sustainable supply chain management, business sustainability, knowledge creation, knowledge management, and technology management). The article concludes with a new theory that encapsulates extant understanding of knowledge management for sustainability along with promising avenues for future research.
keywords: مدیریت دانش | پایداری | بررسی ادبیات | تجزیه و تحلیل کتابشناسی | Knowledge management | Sustainability | Literature review | Bibliometric analysis
مقاله انگلیسی
3 A framework for extracting urban functional regions based on multi prototype word embeddings using points-of-interest data
چارچوبی برای استخراج مناطق عملکردی شهری بر اساس تعبیه چند کلمه نمونه اولیه با استفاده از داده های مورد علاقه-2020
Many studies are in an effort to explore urban spatial structure, and urban functional regions have become the subject of increasing attention among planners, engineers and public officials. Attempts have been made to identify urban functional regions using high spatial resolution (HSR) remote sensing images and extensive geodata. However, the research scale and throughput have also been limited by the accessibility of HSR remote sensing data. Recently, big geo-data are becoming increasingly popular for urban studies since research is still accessible and objective with regard to the use of these data. This study aims to build a novel framework to provide an alternative solution for sensing urban spatial structure and discovering urban functional regions based on emerging geo-data – points of interest (POIs) data and an embedding learning method in the natural language processing (NLP) field. We started by constructing the intraurban functional corpus using a centercontext pairs-based approach. A word embeddings representation model for training that corpus was used to extract multiprototype vectors in the second step, and the last step aggregated the functional parcels based on an introduced spatial clustering method, hierarchical density-based spatial clustering of applications with noise (HDBSCAN). The clustering results suggested that our proposed framework used in this study is capable of discovering the utilization of urban space with a reasonable level of accuracy. The limitation and potential improvement of the proposed framework are also discussed.
Keywords: Urban functional regions | Word embeddings | Points-of-interest | Spatial clusters
مقاله انگلیسی
4 A hierarchical energy management system for islanded multi-microgrid clusters considering frequency security constraints
یک سیستم مدیریت انرژی سلسله مراتبی برای خوشه های چند ریزشبکه جزیره با توجه به محدودیت های امنیتی فرکانس-2020
With the widespread development of microgrids (MGs) in future smart distribution networks, a number of neighboring MGs can be connected and form a multi-microgrid (MMG) cluster. In this regard, the energy management of a MMG is challenging due to more complex components and higher degrees of uncertainty in a small region of power system. Likewise, in the islanded MMG (IMMG) clusters, due to the low-inertia and high intermittent energy delivery of renewable resources, the frequency security should be considered in the energy management. To address this issue, this paper proposes an energy management system (EMS) in which hierarchical control structure of IMMG clusters is precisely modeled. The proposed EMS aims to minimize total operation cost of IMMG cluster while sufficient primary and secondary reserves are scheduled to preserve frequency security in a predefined range. Besides, the proposed EMS provides optimal strategies for MGs to exchange energy and reserves during scheduling horizon. To consider operational uncertainties, the proposed EMS is formulated as a two-stage stochastic mixed-integer linear programming problem that guaranties the global optimal solution. The obtained results verify that through the proposed EMS, total operation cost of the IMMG cluster is minimized while the frequency can be cost-effectively preserved within a pre-defined secure range.
Keywords: Energy and reserve scheduling | Energy management system | Islanded multi-microgrid clusters | Hierarchical control | Two-stage stochastic optimization
مقاله انگلیسی
5 Competitor orientation and value co-creation in sustaining rural New Zealand wine producers
جهت گیری رقابتی و ایجاد ارزش مشترک در پایداری تولیدکنندگان شراب روستای نیوزیلند-2020
This study, underpinned by the Resource-Based View and its association with the Relational View, contributes to the existing cross-disciplinary literature involving economic geography, tourism and marketing by extending the current understanding of the relationship between firms value co-creation activities and sales performance in the context of rural wine producing firms. Specifically, by investigating how a firms competitor orientation (possessing and acting upon knowledge of competitors) affects the relationship between firms capabilities to engage in value co-creation activities and sales performance. This investigation utilises a multi-level qualitative investigation within small-to-medium-sized, New Zealand wine producers engaging in various value co-creation activities (wine hospitality and tourism such as accommodation and restaurants through to wine sales, including at cellar doors). The methods employed involved 40 interviews across 20 businesses; observations of cellar door employees in all 20 firms; and collection of archival data. The findings reveal that by having a high degree of a competitor orientation, the enhanced value co-creation activities can help individual companies improve sales performance and support cluster sustainability, including via repeat tourism. However, results vary among competing businesses based on the product-markets served, where illustrations of potential tensions highlight the need for the management of complementary relationships, within and across clusters (the latter typically being to serve overseas markets). This study consequently offers new unique insights that explain strategies affecting not just an individual firms performance, but also, the sustainability of other businesses.
Keywords: Co-creation | Competitor orientation | Rural clusters | Performance
مقاله انگلیسی
6 Advanced damage detection technique by integration of unsupervised clustering into acoustic emission
تکنیک پیشرفته تشخیص آسیب با ادغام خوشه های بدون نظارت در انتشار آکوستیک-2019
The use of acoustic emission (AE) technique for damage diagnostic is typically challenging due to difficulties associated with discrimination of events that occur during different stages of damage that take place in a material or a structure. In this study, an unsupervised kernel fuzzy c-means pattern recognition analysis and the principal component method were utilized to categorize various damage stages in plain and steel fiber reinforced concrete specimens monitored by AE technique. Enhancement of the discrimination and characterization of damage mechanisms were achieved by processing time and frequency domain data. Both domains (time and frequency) were taken into account to propose new descriptors for crack classification purposes. A cluster of AE data in three classes of Kernel Fuzzy c-means (KFCM) was obtained. The clustered data was subsequently correlated with each particular damage stage for identifying the peak frequency range corresponding to the respective damage stages. Moreover, a novel quantitative technique called Spatial Intelligent b-value (SIb) Analysis was proposed to quantify damage for each stage.
Keywords: Acoustic emission | Torsional loading | Structural health monitoring | Unsupervised pattern recognition | Damage detection | Non-destructive testing
مقاله انگلیسی
7 Deep Learning Clusters in the Cognitive Packet Network
خوشه های یادگیری عمیق در شبکه بسته های شناختی-2019
The Cognitive Packet Network (CPN) bases its routing decisions and flow control on the Random Neural Network (RNN) Reinforcement Learning algorithm; this paper proposes the addition of a Deep Learning (DL) Cluster management structure to the CPN for Quality of Service metrics (Delay Loss and Bandwidth), Cyber Security keys (User, Packet and Node) and Management decisions (QoS, Cyber and CEO). The RNN already models how neurons transmit information using positive and negative impulsive signals whereas the proposed additional Deep Learning structure emulates the way the brain learns and takes decisions; this paper presents a brain model as the combination of both learning algorithms, RNN and DL. The pro- posed model has been simulated under different network sizes and scenarios and it has been validated against the CPN itself without DL clusters. The simulation results are promising; the presented CPN with DL clusters as a mechanism to transmit, learn and make packet routing decisions is a step closer to em- ulate the way the brain transmits information, learns the environment and takes decisions.
Keywords: Random Neural Network | Deep Learning Clusters | Cognitive Packet Network | QoS | Cybersecurity | Routing
مقاله انگلیسی
8 The Random Neural Network with Deep Learning Clusters in Smart Search
شبکه عصبی تصادفی با خوشه های یادگیری عمیق در جستجوی هوشمند-2019
This paper proposes a Neurocomputing application that reorders the Web results obtained from different Web Search Engines emulating the way our brain takes decisions. The proposed application is based on the Random Neural Network with Deep Learning Clusters that evaluates and adapts Web result relevance by associating independently each Deep Learning Cluster to a specific Web Search Engine. In addition, this paper presents a Deep Learning Cluster to perform as a Management Cluster that decides the final result relevance based on the inputs from each independent Deep Learning cluster. The performance of the proposed Management Cluster is evaluated when included as an additional layer to the Deep Learning Clusters. On average; the proposed Deep Learning cluster structure improves Smart Search performance
Keywords: Intelligent search | World wide web | Random Neural Network | Clusters | Deep learning | Management clusters
مقاله انگلیسی
9 چه چیزی گردشگران اجدادی را به "میهن" می کشاند؟ تحلیلی روی انگیزه های گردشگری اجدادی
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 22
دودمان و تبار در منابع علمی گردشگری، توجه محدودی را به خود جلب کرده است اما نشان داده شده است که نقشی مهم در گردشگری میراثی به ویژه برای کشورهایی با پراکندگی گسترده یهودیان مثل ایرلند، ایتالیا، هند، چین و اسکاتلند ایفا می کند. هدف این مطالعه بررسی انگیزه های گردشگران اجدادی و به دست آوردن یک درک مبسوط از این بازار می باشد. یک ارزیابی روی 282 گردشگر اجدادی اجازه شناسایی سه عامل کلیدی را داد: انگیزه گردشگر اجدادی؛ انگیزه های گردشگر میراثی؛ و انگیزه گردشگر توده ای. این موضوعات، تحلیل جزئیات خوشه ها و شناسایی 4 بخش اجدادی را امکانپذیر کرد: فرو رفتن در میراث کامل؛ مشتاق اجداد؛ علاقه عمومی؛ و میراث متمرکز. باتوجه به فقدان سرمایه گذاری و منابعی که در حال حاضر دردسترس تامین کننده های گردشگری اجدادی باشد، شناسایی این عوامل، راه درازی است تا حوزه های سازنده تمرکز برای کارهای تبلیغی منابع را پررنگ کند.
کلیدواژه ها: گردشگری اجدادی | انگیزه ها | تحلیل خوشه ای | تحلیل عاملی توضیحی
مقاله ترجمه شده
10 SERAC3: Smart and economical resource allocation for big data clusters in community clouds
SERAC3: تخصیص منابع هوشمند و اقتصادی برای خوشه های داده بزرگ در ابرهای جامعه-2018
Big data analysis jobs on clouds are gaining more and more popularity in recent years. It is critical but challenging to pick the right configuration for an incoming job, since the configuration space is too large, and the relationship between allocated resources and job performance is not deterministic. In this paper, we propose SERAC3 to allocate resources smartly and economically for big data clusters in community clouds. SERAC3 is a system that can automatically extract representative workloads from incoming big data analysis jobs, smartly decide an optimal configuration for each job, and adjust its assigning strategy in a quasi-realtime mode. With experiments on a community cloud built on OpenStack, we show that on average, SERAC3 can smartly select a configuration within 2.2% of the exact optimal one, while saving about 80.1% search cost compared to the exhaustive search.
Keywords: Resource allocation ، Big data clusters ، Representative workloads ، Community clouds
مقاله انگلیسی
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