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تعداد مقالات یافته شده: 47
ردیف عنوان نوع
1 Social movement activists’ conceptions of political action and counter-accounting through a critical dialogic accounting and accountability lens
تصورات فعالان جنبش اجتماعی از کنش سیاسی و مقابله با حسابداری از طریق یک دریچه حسابداری گفتگوی انتقادی و پاسخگویی-2021
In the face of growing disaffection with neoliberalism and corporate social and environmental accounting, critical accounting recognizes the potential of counter-accounting to open spaces for democratic contestation and to advance progressive change. Critical dialogic accounting and accountability (CDAA), for example, views counter-accounting as providing social movements with opportunities to challenge neoliberal hegemony, to mobilize multiple publics and to construct new social realities. However, the democratizing potential of counter-accounting is contested within academia, and social movements’ views of counter-accounting as a politicizing practice are not well understood. We extend CDAA theorizing by elaborating on the value of counter-accounting in advancing democratic struggles against neoliberalism and illustrating how an agonistic lens can be useful in framing social movements’ actions in these struggles. Social movements’ conceptualizations of political action and counter-accounting are empirically investigated through interviews with 25 social movement activists. Based on the interviews and our CDAA lens, we propose possible areas for critical accounting collaborations with social movements as they seek to effect progressive change.
keywords: حسابداری دیجیتالی انتقادی و پاسخگویی | مبنی بر حسابداری | عذاب | جنبش های اجتماعی | نئولیبرالیسم | Critical dialogic accounting and accountability | Counter-accounting | Agonistics | Social movements | Neoliberalism
مقاله انگلیسی
2 Formalizing and analyzing security ceremonies with heterogeneous devices in ANP and PDL
رسمیت و تجزیه و تحلیل مراسم امنیتی با دستگاههای ناهمگن در ANP و PDL-2021
In today’s security protocols (also called “security ceremonies” when humans play a key role), different nodes may have different capabilities: computers can encrypt and decrypt messages, whereas humans cannot; a biometric device can capture biometric information, whereas a random number generator used in e-banking cannot; and so on. Furthermore, even if a node has the decryption capability, it must also know the encryption key to decrypt a message. Actor-network procedures (ANPs) are a well-known formal model of heterogeneous security protocols by Meadows and Pavlovic, and their procedure derivation logic (PDL) supports the logical reasoning about ANPs. However, ANPs do not support explicitly specifying node capabilities, and PDL does not support reasoning explicitly about the knowledge of the participants at different points in time. In this paper, we extend ANPs to deal with heterogeneous devices by explicitly specifying the nodes’ capabilities, as well as by adding new types of events. We also modify PDL to take into account the knowledge of participants at different points in time, and extend PDL to reason both from a “bird’s- eye” view of the system, as well from a “node’s-eye” view. All this allows us to reason about secrecy and authentication in security protocols/ceremonies with different kinds of devices and human users. We illustrate the use of our modeling notation ANP-C and our logics PDL-CK and PDL-CKL to specify and reason about a number of scenarios involving different kinds of devices, including: scenarios for updating someone’s data in a smart card reader; an SSL/TLS ceremony involving a user, a smartphone with a fingerprint reader, anda remote computer/server; and scenarios involving the YubiKey authentication device used by companies such as Google, Facebook, and Bank of America. 2021 Elsevier Inc. All rights reserved.
Keywords: Formal methods | Security protocols | Security ceremonies | Actor-network procedures | Procedure derivation logic | Authentication devices
مقاله انگلیسی
3 Knowledge management and humanitarian organisations in the Asia-Pacific: Practices, challenges, and future pathways
مدیریت دانش و سازمان های بشردوستانه در آسیا و اقیانوس آرام: شیوه ها، چالش ها و مسیرهای آینده-2021
While there is growing recognition amongst humanitarians that knowledge sharing and exchange are essential components of organisational efficiency and effectiveness, knowledge management processes in many human- itarian organisations are still inadequate. The review of knowledge management and international relations literature reveals limited research on the institutional memory of humanitarian organisations. This article aims to start filling this research gap by examining the use of explicit and tacit knowledge transfer in the humanitarian sector in the Asia-Pacific. It points to the embryonic stage of knowledge management and the reliance on tacit knowledge management consistent with the early stage of sector professionalization in the region. It reviews and analyses existing scholarly literature and manuals and draws on fieldwork interviews with key humanitarian personnel that primarily focus on natural hazards. The findings suggest institutional memory in the humanitarian sector remains ad hoc with limited long-term capture. There is a broad tendency in the region to rely on tacit knowledge transfer – interpersonal relationships and informal decision-making – as the dominant knowledge management practice. This reliance challenges knowledge management at the institutional level and indicates a weakness in the institutional memory of humanitarian organisations in the region. Our research raises questions about how to improve knowledge management practices within humanitarian organisations in the Asia-Pacific with significant implications for the sector more generally. A recalibration of tacit and explicit knowledge management would build institutional memory in humanitarian organisations. This requires a dual-track approach with codified documentation of experiences and greater emphasis on an institutional culture of knowledge sharing.
keywords: آسیا و اقیانوسیه | حافظه نهادی | مدیریت بحران | مدیریت دانش | امور بشردوستانه | حکومت | Asia-pacific | Institutional memory | disaster management | Knowledge management | Humanitarian affairs | governance
مقاله انگلیسی
4 Indigenous flood control and management knowledge and flood disaster risk reduction in Nigerias coastal communities: An empirical analysis
دانش کنترل و مدیریت سیل بومی و کاهش خطر بلایای سیل در جوامع ساحلی نیجریه: یک تحلیل تجربی-2021
Flooding is one of the major global challenges today. The role of indigenous knowledge in offering an effective risk reduction strategy towards flood disaster disregarded for many decades is now gaining global recognition. There is a growing call for empirical identification of the effectiveness of indigenous knowledge in flood risk reduction. Consequently, this paper empirically examines indigenous flood control and management knowledge with the intent to identify its effectiveness in risk reduction of flood disasters in Nigeria’s coastal communities. This is to provide empirical bases for the formulation of appropriate strategies for enhancing flood risk reduction in Nigeria’s coastal communities. The research engaged focus group discussion and questionnaire methods to generate primary data. The research proceeds with principal component analysis to classify and measure the effectiveness of indigenous flood control and management knowledge in flood risk reduction. The result shows the existence of eight types of indigenous flood control and management knowledge in the coastal communities and they were 61.2% effective in flood risk reduction. This implies that indigenous flood control and manage- ment knowledge practiced in Nigeria’s coastal communities is effective in flood risk reduction. This study pro- posed a sustainable approach to risk reduction in flood disasters based on the integration of indigenous knowledge systems and modern flood management strategies.
keywords: دانش بومی | کنترل سیل | جوامع ساحلی | مدیریت | فاجعه سیل | کاهش خطر | Indigenous knowledge | Flood control | Coastal communities | Management | Flood disaster | Risk reduction
مقاله انگلیسی
5 An entity-relationship model of the flow of waste and resources in city-regions: Improving knowledge management for the circular economy
یک مدل ارتباط برقراری ارتباط از جریان ضایعات و منابع در مناطق شهری: بهبود مدیریت دانش برای اقتصاد دایره ای-2021
Waste and resources management is one of the domains where urban and regional planning can transition to- wards a Circular Economy, thus slowing environmental degradation. Improving waste and resources manage- ment in cities requires an adequate understanding of multiple systems and how they interact. New technologies contribute to improve waste management and resource efficiency, but knowledge silos hinder the possibility of delivering sound holistic solutions. Furthermore, lack of compatibility between data formats and diverse defi- nitions of the same concept reduces information exchange across different urban domains. This paper addresses the challenge of organising and standardising information about waste and resources management in city regions. Given the amount and variety of data constantly captured, data models and standards are a crucial element of Industry 4.0. The paper proposes an Entity-Relationship Model to harmonise definitions and integrate infor- mation on waste and resources management. Furthermore, it helps to formalise the components of the system and their relationships. Semi-structured interviews with government officials, mobile app developers and aca- demics provided insights into the specific system and endorsed the model. Finally, the paper illustrates the translation of the ERM into a relational database schema and instantiates Waste Management and industrial Symbiosis cases in Buenos Aires (ARG) and Helsingborg (SWE) to validate its general applicability. The data model for the Circular Flow of Waste and Resources presented here enhances traditional waste management perspectives by introducing Circular Economy strategies and spatial variables in the model. Thus, this research represents a step towards unlocking the true potential of Industry 4.0.
keywords: شهرهای دایره ای | مدیریت زباله | اقتصاد دایره ای | صنعت 4.0 | مدل ارتباط برق | sql | Circular cities | Waste management | Circular economy | Industry 4.0 | Entity-relationship model | SQL
مقاله انگلیسی
6 A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
مروری بر به رسمیت شناختن فعالیتهای چندمنظوره انسان با تأکید ویژه بر طبقه بندی ، کاربردها ، چالشها و جهت های آینده-2021
Human activity recognition (HAR) is one of the most important and challenging problems in the computer vision. It has critical application in wide variety of tasks including gaming, human– robot interaction, rehabilitation, sports, health monitoring, video surveillance, and robotics. HAR is challenging due to the complex posture made by the human and multiple people interaction. Various artifacts that commonly appears in the scene such as illuminations variations, clutter, occlusions, background diversity further adds the complexity to HAR. Sensors for multiple modalities could be used to overcome some of these inherent challenges. Such sensors could include an RGB-D camera, infrared sensors, thermal cameras, inertial sensors, etc. This article introduces a comprehensive review of different multimodal human activity recognition methods where different types of sensors being used along with their analytical approaches and fusion methods. Further, this article presents classification and discussion of existing work within seven rational aspects: (a) what are the applications of HAR; (b) what are the single and multi-modality sensing for HAR; (c) what are different vision based approaches for HAR; (d) what and how wearable sensors based system contributes to the HAR; (e) what are different multimodal HAR methods; (f) how a combination of vision and wearable inertial sensors based system contributes to the HAR; and (g) challenges and future directions in HAR. With a more and comprehensive understanding of multimodal human activity recognition, more research in this direction can be motivated and refined.© 2021 Elsevier B.V. All rights reserved.
Keywords: Activity recognition | Computer vision | Wearable sensors | Fusion of vision and inertial sensors | Smart-shoes | Multimodality
مقاله انگلیسی
7 Multi-level transfer learning for improving the performance of deep neural networks: Theory and practice from the tasks of facial emotion recognition and named entity recognition
یادگیری انتقال چند سطحی برای بهبود عملکرد شبکه های عصبی عمیق: نظریه و عمل از وظایف تشخیص احساسات چهره و شناسایی موجودیت-2021
Transfer learning has become a promising field in machine learning owing to its wide application prospects. Its effectiveness has spawned various methodologies and practices. Transfer learning refers to improving the performance of target learners in the target domain by transferring the knowledge contained in different yet related source domains. In other words, we can use data from additional domains or tasks to train a model with superior generalization. Using transfer learning, the dependence on considerable target-domain data can be reduced, thereby constructing target learners. Recently, the fields of computer vision (CV) and natural language processing (NLP) have witnessed the emergence of transfer learning, which has significantly improved the most advanced technology on a wide range of CV and NLP tasks. A typical approach of applying transfer learning to deep neural networks is to fine-tune a pretrained model of the source domain with data obtained from the target domain. This paper proposes a novel framework, based on the fine-tuning approach, called multilevel transfer learning (mLTL). Under this framework, we concluded the crucial findings and principles regarding the training sequence of related domain datasets and demonstrated its effectiveness by performing facial emotion and named entity recognition tasks. According to the experimental results, the deep neural network models using mLTL outperformed the original models on the target tasks.© 2021 Elsevier B.V. All rights reserved.
Keywords: Multilevel transfer learning | Computer vision | Natural language processing | Facial emotion recognition | Named entity recognition
مقاله انگلیسی
8 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
9 Analysis of sentiment in tweets addressed to a single domain-specific Twitter account: Comparison of model performance and explainability of predictions
تجزیه و تحلیل احساسات در توییت های خطاب به یک حساب توییتر خاص دامنه: مقایسه عملکرد مدل و توضیح پذیری پیش بینی ها-2021
Many institutions and companies find it valuable to know how people feel about their ventures; hence, scientific research in sentiment analysis has been intensely developed over time. Automated sentiment analysis can be considered as a machine learning (ML) prediction task, with classes representing human affective states. Due to the rapid development of ML and deep learning (DL), improvements in automatic sentiment analysis perfor- mance are achieved almost every year. Since 2013, Semantic Evaluation (SemEval) has hosted a worldwide community-acknowledged competition that allows for comparisons of recent innovations. The sentiment analysis tasks focus on assessing sentiment in Twitter posts authored by various publishers and addressing multiple subjects. Our study aimed to compare selected popular and recent natural language processing methods using a new data set of Twitter posts sent to a single Twitter account. For improved comparability of our experiments with SemEval, we adopted their metrics and also deployed our models on data published for SemEval-2017. In addition, we investigated if an unsupervised ML technique applied for the detection of topics in tweets can be leveraged to improve the predictive performance of a selected transformer model. We also demonstrated how a recent explainable artificial intelligence technique can be used in Twitter sentiment analysis to gain a deeper understanding of the models’ predictions. Our results show that the most recent DL language modeling approach provides the highest quality; however, this quality comes at reduced model transparency.
keywords: پردازش زبان طبیعی | یادگیری عمیق | تجزیه و تحلیل احساسات | فراگیری ماشین | توضیح پذیری | توییتر | Natural language processing | Deep learning | Sentiment analysis | Machine learning | Explainability | Twitter
مقاله انگلیسی
10 A knowledge graph method for hazardous chemical management: Ontology design and entity identification
یک روش نمودار دانش برای مدیریت مواد شیمیایی خطرناک: طراحی هستی شناسی و شناسایی موجودیت-2021
Hazardous chemicals are widely used in the production activities of the chemical industry. The risk management of hazardous chemicals is critical to the safety of life and property. Hence, the effective risk management of hazardous chemicals has always been important to the chemical industry. Since a large quantity of knowledge and information of hazardous chemicals is stored in isolated databases, it is challenging to manage hazardous chemicals in an information-rich manner. Herein, we prompt a knowledge graph to overcome the information gap between decentralized databases, which would improve the hazardous chemical management. In the implementation of the knowledge graph, we design an ontology schema of hazardous chemicals management. To facilitate enterprises to master the knowledge in the full lifecycle of hazardous chemicals, including production, transportation, storage, etc., we jointly use data from companies and open data from the public domain of hazardous chemicals to construct the knowledge graph. The named entity recognition task is one of the key tasks in the implementation of the knowledge graph, which is of great significance for extracting entity information from unstructured data, namely the hazardous chemical accidents records. To extract useful information from multi-source data, we adopt the pre-trained BERT-CRF model to conduct named entity recognition for incidents records. The model achieves good results, exhibiting the effectiveness in the task of named entity recognition in the chemical industry.
keywords: نمودار دانش | هستی شناسی | مدیریت مواد شیمیایی خطرناک | به رسمیت شناختن نهادها | Knowledge graph | Ontology | Hazardous chemicals management | Named entity recognition
مقاله انگلیسی
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