با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
---|---|---|
71 |
Blockchain and AI amalgamation for energy cloud management: Challenges, solutions, and future directions
ادغام بلاکچین و هوش مصنوعی برای مدیریت ابر انرژی: چالش ها ، راه حل ها و مسیرهای آینده-2020 In the recent years, the Smart Grid (SG) system faces various challenges like the ever-increasing energy
demand, the enormous growth of renewable energy sources (RES) with distributed energy generation
(EG), the extensive Internet of Things (IoT) devices adaptation, the emerging security threats, and
the foremost goal of sustaining the SG stability, efficiency and reliability. To cope up these issues
there exists, the energy cloud management (ECM) system, which combines the infrastructure for
energy, with intelligent energy usage and value-added services as per consumers demand. To achieve
these, efficient demand-side forecasting and secure data transmission are the key factors. The energy
management issues pose extreme gravity in finding sustainable solutions by using the blockchain
(BC) and Artificial Intelligence (AI). AI-based techniques support various services such as energy load
prediction, classification of the consumer, load management, and analysis where the BC provides
data immutability and trust mechanism for secure energy management. Therefore, this paper reviews
several existing AI-based approaches along with the advantages and challenges of integrating the BC
technology and AI in the ECM system. We presented a decentralized AI-based ECM framework for
energy management using BC and validate it using a case study. It is shown that how BC and AI can
be used to mitigate ECM with security and privacy issues. Finally, we highlighted the open research
issues and challenges of the BC-AI-based ECM system. Keywords: Blockchain | AI | Energy cloud management | Smart grid |
مقاله انگلیسی |
72 |
Data protection law beyond identifiability? Atmospheric profiles, nudging and the Stratumseind Living Lab
قانون حفاظت از داده ها فراتر از قابلیت شناسایی؟ پروفایل های جوی، تلنگر زدن و آزمایشگاه زنده Stratumseind-2020 The deployment of pervasive information and communication technologies (ICTs) within
smart city initiatives transforms cities into extraordinary apparatuses of data capture. ICTs
such as smart cameras, sound sensors and lighting technology are trying to infer and affect
persons’ interests, preferences, emotional states, and behaviour. It should be no surprise
then that contemporary legal and policy debates on privacy in smart cities are dominated
by a debate focused on data and, therefore, on data protection law. In other words, data protection law is the go-to legal framework to regulate data processing activities within smart
cities and similar initiatives. While this may seem obvious, a number of important hurdles
might prevent data protection law to be (successfully) applied to such initiatives. In this contribution, we examine one such hurdle: whether the data processed in the context of smart
cities actually qualifies as personal data, thus falling within the scope of data protection
law. This question is explored not only through a theoretical discussion but also by taking
an illustrative example of a smart city-type initiative – the Stratumseind 2.0 project and its
living lab in the Netherlands (the Stratumseind Living Lab; SLL). Our analysis shows that the
requirement of ‘identifiability’ might be difficult to satisfy in the SLL and similar initiatives.
This is so for two main reasons. First, a large amount of the data at stake do not qualify
as personal data, at least at first blush. Most of it relates to the environment, such as, data
about the weather, air quality, sound and crowding levels, rather than to identified or even
likely identifiable individuals. This is connected to the second reason, according to which,
the aim of many smart city initiatives (including the SLL) is not to identify and target specific
individuals but to manage or nudge them as a multiplicity – a combination of the environment, persons and all of their interactions. This is done by trying to affect the ‘atmosphere’
on the street. We thus argue that a novel type of profiling operations is at stake; rather than
relying on individual or group profiling, the SLL and similar initiatives rely upon what we have called ‘atmospheric profiling’. We conclude that it remains highly uncertain, whether
smart city initiatives like the SLL actually process personal data. Yet, they still pose risks for
a wide variety of rights and freedoms, which data protection law is meant to protect, and a
need for regulation remains. Keywords: Data protection | Personal data | Smart city | Profiling | Nudging | Stratumseind |
مقاله انگلیسی |
73 |
Dead ringers? Legal persons and the deceased in European data protection law
زنگ های مرده؟ اشخاص حقوقی و متوفی در قانون حفاظت از داده های اروپا-2020 Notwithstanding suggestions that the concrete treatment of legal and deceased person data
during European data protection’s development has been broadly comparable, this article
finds that stark divergences are in fact apparent. Justification for the inclusion of both categories has rested on a claimed linkage to living natural person interests. However, despite
early fusion, legal persons have been increasingly seen to have qualitatively different information entitlements compared to natural persons, thereby leaving European data protection with a very limited and indirect role here. In contrast, living natural persons and the
deceased have not been conceived as normatively dichotomous and since the 1990s there
has been growing interest both in establishing sui generis direct protection for deceased person data and also indirect inclusion through a link with living natural persons. Whilst the
case for some indirect inclusion is overwhelming, a broad approach to the inter-relational
nature of data risks further destabilizing the personal data concept even in relation to living persons alone. Given that jurisdictions representing almost half of the EEA’s population
now provide some direct protection and the challenges of managing digital data on death
continue to grow, the time may be ripe for a ‘soft’ recommendation on direct protection in
this area. Drawing on existing law and scholarship, such a recommendation could seek to
specify the role of both specific control rights and diffuse confidentiality obligations, the criteria for time-limits in each case and the need for a balance with other rights and interests
which recognises the significantly decreasing interest in protection over time.
Keywords: Companies | Confidentiality | Personal data | Privacy | Testamentary interests | Reputation |
مقاله انگلیسی |
74 |
Managing complex engineering projects: What can we learn from the evolving digital footprint?
مدیریت پروژه های مهندسی پیچیده: از رد پای دیجیتال در حال تکامل چه می توان یاد گرفت؟-2020 The challenges of managing large complex engineering projects, such as those involving the design of infra- structure, aerospace and industrial systems; are widely acknowledged. While there exists a mature set of project management tools and methods, many of todays projects overrun in terms of both time and cost. Existing literature attributes these overruns to factors such as: unforeseen dependencies, a lack of understanding, late changes, poor communication, limited resource availability (inc. personnel), incomplete data and aspects of culture and planning. Fundamental to overcoming these factors belies the challenge of how management in- formation relating to them can be provided, and done so in a cost effective manner. Motivated by this challenge, recent research has demonstrated how management information can be automatically generated from the evolving digital footprint of an engineering project, which encompasses a broad range of data types and sources. In contrast to existing work that reports the generation, verification and application of methods for generating management information, this paper reviews all the reported methods to appraise the scope of management information that can be automatically generated from the digital footprint. In so doing, the paper presents a reference model for the generation of managerial information from the digital footprint, an appraisal of 27 methods, and a critical reflection of the scope and generalisability of data-driven project management methods. Key findings from the appraisal include the role of email in providing insights into potential issues, the role of computer models in automatically eliciting process and product dependencies, and the role of project documentation in assessing project norms. The critical reflection also raises issues such as privacy, highlights the enabling technologies, and presents opportunities for new Business Intelligence tools that are based on real-time monitoring and analysis of digital footprints. Keywords: Big Data | Project Management | Business Intelligence | Knowledge Workers |
مقاله انگلیسی |
75 |
Mapping the development of China’s data protection law: Major actors, core values, and shifting power relations
ترسیم توسعه قانون حفاظت از داده های چین: بازیگران اصلی، ارزش های اصلی و تغییر روابط قدرت-2020 This Article seeks to map the possible paths of the development of China’s data protection law by examining the changing power relations among three major actors - the State, digital enterprises and the public in the context of China’s booming data-driven economy. We argue that focusing on different core values, these three major actors are the key driving forces shaping China’s data protection regime. Their dynamic and multidimensional power relations have been casting the development of China’s data protection law with various uncertainties. When persuing different, yet not always conflicting values, these three major actors may both cooperate and compete with each other. Based on our careful analysis of the shifting power relations, we identify and assess three possible paths of the development of China’s data protection law. We are much concerned that the proposed comprehensive data protection law might be a new attempt of the State to win legitimacy abroad, while actually trying to reinforce massive surveillance besides economic goals. We argue that a modest alternative may be that this law might show some genuine efforts for protecting data privacy, but still with poor enforcement. Last, we argue that the most desirable development would be that this law could provide basic but meaningful and effective protection for data privacy, and lay a good foundation for further development.© 2020 Bo Zhao and Yang Feng. Published by Elsevier Ltd. All rights reserved. |
مقاله انگلیسی |
76 |
Struggling to strike the right balance between interests at stake: The ‘Yarovaya’, ‘Fake news’ and ‘Disrespect’ laws as examples of ill-conceived legislation in the age of modern technology
تلاش برای ایجاد تعادل مناسب بین منافع در خطر: قوانین "Yarovaya"، "Fake News" و "بی احترامی" به عنوان نمونه هایی از قوانین نادرست در عصر فناوری مدرن-2020 The article deals with the legislative amendments that have been recently adopted in the Russian Federation, the so-called ‘Yarovaya’ law, the ‘fake news’ law and the ‘disrespect’ law. It explains the essence and problems of implementation of the above-mentioned legal instruments and assesses them from the human rights angle. It is established that the rather complex laws under analysis pose significant threats to the human rights and fundamental freedoms of individuals, including privacy, data protection and freedom of expression, and introduce other additional negative effects to the Russian society and economy. While in the adoption of such legislation it is crucial to give due weight to the involved interests, the used examples indicate that the State’s interests seem to prevail at the cost of the rights and freedoms of those who need to be adequately protected.© 2020 E. Moyakine and A. Tabachnik. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Keywords: Russian legislation | Yarovaya law | Fake news law | Disrespect law | Human rights | Privacy | Data protection | Freedom of expression | Public safety | Public security |
مقاله انگلیسی |
77 |
Towards privacy preserving AI based composition framework in edge networks using fully homomorphic encryption
به سمت حفظ حریم خصوصی و حفظ چارچوب ترکیب مبتنی بر هوش مصنوعی در شبکه های لبه ای با استفاده از رمزنگاری کاملاً همگن-2020 We present a privacy-preserving framework for Artificial Intelligence (AI) enabled composition for the edge
networks. Edge computing is a very promising technology for provisioning realtime AI services due to low
response time and network bandwidth requirements. Due to the lack of computational capabilities, an edge
device alone cannot provide the complex AI services. Complex AI tasks should be divided into multiple subtasks
and distributed among multiple edge devices for efficient service provisioning in the edge network.
AI-enabled or automatic service composition is one of the essential AI tasks in the service provisioning.
In edge computing-based service provisioning, service composition related tasks need to be offloaded to
several edge nodes for efficient service. Edge nodes can be used for monitoring services, storing Qualityof-
Service (QoS) data, and composing services to find the best composite service. Existing service composition
methods use plaintext QoS data. Hence, attackers may compromise edge devices to reveal QoS data of
services and modify them for giving an advantage to particular edge service providers, and the AI-based
service composition becomes biased. From that point of view, a privacy-preserving framework for AI-based
service composition is required for the edge networks. In our proposed framework, we introduce an AI-based
composition model for edge services in the edge networks. Additionally, we present a privacy-preserving
AI service composition framework to perform composition on encrypted QoS data using fully homomorphic
encryption (FHE) algorithm. We conduct several experiments to evaluate the performance of our proposed
privacy-preserving service composition framework using a synthetic QoS dataset. Keywords: Edge-AI | Artificial Intelligence | Privacy in edge networks | Privacy-preserving AI | Privacy-preserving AI-based service | composition | Privacy-preserving service composition |
مقاله انگلیسی |
78 |
Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits
بهبود هماهنگی مراقبت از سرطان پستان و مدیریت علائم با استفاده از ابزارهای پیش بینی کننده هوش مصنوعی-2020 Integrated breast cancer care is complex, marked by multiple hand-offs between primary care and
specialists over an extensive period of time. Communication is essential for treatment compliance,
lowering error and complication risk, as well as handling co-morbidity. The director role of care, however,
becomes often unclear, and patients remain lost across departments. Digital tools can add significant
value to care communication but need clarity about the directives to perform in the care team. In
effective breast cancer care, multidisciplinary team meetings can drive care planning, create directives
and structured data collection. Subsequently, nurse navigators can take the director’s role and become a
pivotal determinant for patient care continuity. In the complexity of care, automated AI driven planning
can facilitate their tasks, however, human intervention stays needed for psychosocial support and
tackling unexpected urgency. Care allocation of patients across centres, is often still done by hand and
phone demanding time due to overbooked agenda’s and discontinuous system solutions limited by
privacy rules and moreover, competition among providers. Collection of complete outcome information
is limited to specific collaborative networks today. With data continuity over time, AI tools can facilitate
both care allocation and risk prediction which may unveil non-compliance due to local scarce resources,
distance and costs. Applied research is needed to bring AI modelling into clinical practice
Keywords: Care coordination | Symptom management | Predictive tools | Care allocation | Nurse navigator | Multidisciplinary discussion |
مقاله انگلیسی |
79 |
Adversarial behaviours in mixing coins under incomplete information
رفتارهای خصمانه در اختلاط سکه در زیر اطلاعات ناقص-2020 Criminals can launder crypto-currencies through mixing coins, whose original purpose is preservation
of privacy in the presence of traceability. Therefore, it is essential to elaborately design mixing polices
to achieve both privacy and anti-money laundering. Existing work on mixing policies relies on the
knowledge of a blacklist. However, these policies are paralysed under the scenario where the blacklist
is unknown or evolving. In this paper, we regard the above scenario as games under incomplete
information where parties put down a deposit for the quality of coins, which is suitably managed by
a smart contract in case of mixing bad coins. We extend the poison and haircut policies to incomplete
information games, where the blacklist is updated after mixing. We prove the existence of equilibria
for the improved polices, while it is known that there is no equilibria in the original poison and haircut
policies, where blacklist is public known. Furthermore, we propose a seminal suicide policy: the one
who mixes more bad coins will be punished by not having the deposit refunded. Thus, parties have
no incentives to launder money by leveraging mixing coins. In effect, all three policies contrast money
laundering while preserving privacy under incomplete information. Finally, we simulate and verify the
validity of these policies. Keywords: Mixing coins | Incomplete information | Smart contract | Equilibrium |
مقاله انگلیسی |
80 |
South Africa’s PNR regime: Privacy and data protection
رژیم PNR آفریقای جنوبی: حریم خصوصی و داده ها حفاظت-2020 There has been an increase in the collection and use of Passenger Name Record (PNR) data
for security purposes globally. Though academic analysis of this trend has remained focused
largely on the North American and European context, the Government of South Africa has
been using PNRs since 2014 for security purposes. South Africa was the first country on the
African continent to implement such a regime and is one of only thirteen states internationally to link its Advanced Passenger Information (API) and PNR systems. While there has
been little attention on South Africa’s use of PNRs, an inquiry into the country’s PNR practices reveals striking privacy concerns, including the potential permanent retention of PNR
data and a failure of the state to fully disclose if, and under what conditions, PNR data can
be shared with other states. While South Africa has implemented a PNR regime that is comparable to the highest international standards, the data protection requirements appear to
be far less developed. In fact, South Africa’s PNR regime remains enigmatic as all indications
and mention of PNR are elusive and scattered across government publications. As such, this
paper aims to provide an introduction into the elements of South African PNR use, including
the implications as they relate to law, data protection, and privacy.
Keywords: PNR | Passenger name record | South Africa | Security | Personal data | Privacy | Data |
مقاله انگلیسی |