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1 |
Capability token selection algorithms to implement lightweight protocols
قابلیت الگوریتم های انتخاب نشانه برای پیاده سازی پروتکل های سبک وزن-2022 The IoT (Internet of Things) is now one of the most significant infrastructure and has to be
secure against malicious accesses. Especially, it is critical to make devices secure in the IoT.
In the CBAC (Capability-Based Access Control) model adopted to the IoT, device owners issue
subjects capability tokens, i.e. a set of access rights on objects in devices. Objects in devices
are data resource manipulated by subjects. Data are exchanged among subjects and objects
through manipulating objects. Here, if subjects attempt to manipulate objects in accordance with
the capability tokens issued, the subjects can get data which the subjects are not authorized
to get, i.e. illegal information flow and late information flow occur. In our previous studies,
protocols are implemented to prevent both illegal and late types of information flows from
occurring. Here, operations implying such information flows are interrupted. However, the
request processing time gets longer as the number of capability tokens used increases. In this
paper, an MRCTSD (Minimum Required Capability Token Selection for Devices) algorithm is
newly proposed to reduce the number of capability tokens used. In the evaluation, it is shown
that the request processing times and the numbers of capability tokens used in the lightweight
protocols realized with the MRCTSD algorithm are shorter and smaller than the conventional
protocols, respectively.
keywords: CBAC (Capability-Based Access Control) model | Capability token selection algorithm | CoAP (Constrained Application Protocol) | Information flow control | IoT (Internet of Things) | Lightweight protocol |
مقاله انگلیسی |
2 |
Conjugation of border and domestic carbon adjustment and implications under production and consumption-based accounting of India•s National Emission Inventory: A recursive dynamic CGE analysis
ترکیب تنظیمات کربن مرزی و داخلی و پیامدهای آن در حسابداری مبتنی بر تولید و مصرف موجودی انتشار ملی هند: یک تحلیل CGE پویا بازگشتی-2021 India initiated prudent measures voluntarily in the last two decades to combat against excessive carbon
emissions. Acknowledging these initiatives, the study conjoins the policy of ‘border carbon adjustment
(BCA)’ by the developed countries on Indian export with the ‘domestic carbon adjustment (DCA)’ by In-
dia to evaluate its impact on emission reduction and the macroeconomy. The study also raises an in-
consistency in this dual carbon adjustment under the production-based accounting (PBA) of the ‘national
emission inventory (NEI)’ and conducts simulation experiments under the PBA and alternatively proposed
consumption-based accounting (CBA) framework. The results reveal that the closer the rates of BCA and
DCA the more effective the carbon adjustment schemes are. The dual carbon adjustment also found giv-
ing better outcome under the CBA than PBA. The result of carbon-revenue recycling schemes suggest
direct compensation to the enterprises for making the economy recover from the carbon tax-distortions
in the most effective way. keywords: تنظیم کربن مرزی (BCA) | تنظیم کربن داخلی (DCA) | موجودی ملی انتشار (NEI) | حسابداری مبتنی بر تولید (PBA) | حسابداری مبتنی بر مصرف (CBA) | تعادل عمومی محاسبه (CGE) | بازیافت درآمد کربن | هندوستان | Border Carbon Adjustment (BCA) | Domestic Carbon Adjustment (DCA) | National Emission Inventory (NEI) | Production-based Accounting (PBA) | Consumption-based Accounting (CBA) | Computable General Equilibrium (CGE) | Carbon Revenue Recycling | India |
مقاله انگلیسی |
3 |
On the fair accounting of carbon emissions in the global system using an exergy cost formation concept
حسابداری منصفانه انتشار کربن در سیستم جهانی با استفاده از مفهوم تشکیل هزینه اگزرژی-2021 Carbon accounting is necessary for designing effective climate change mitigation policies. A proper and
fair accounting method should motivate both the producers toward cleaner production methods and the
consumers toward reducing the embodied emissions of their consumption. This research work proposes
a new approach to map the production chain of carbon emissions in which every subsystem is
responsible for the level and efficiency of its production activities and embodied emissions for providing
its economic activities or final demands. The exergy cost formation concept is used to track the emissions
in the production chain. The results of this accounting present the total carbon loads on economic
outputs either consumed locally or exported abroad (CExA). The CExA results are then compared to the
results of conventional production-based (PBA) and consumption-based (CBA) carbon inventories. Here
we show that, in addition to the levels of production and consumption, the economic structures of the
countries and the efficiency of the production activities are important factors differentiating the roles of
the countries in the global emissions. Our results show that the share of the imported emissions to the
total CExA varies between 14% for developing countries to 34% for the developed countries. Moreover,
although the ratio of CBA to PBA for the countries is highly dependent on their economic states (0.87 for
developing countries and 1.21 for developed countries), the ratio of CExA to PBA does not follow a unique
trend among developing or developed countries. The results demonstrate that, according to the proposed
sharing approach, the import-oriented developed countries, which have benefited the most from the
carbon leakage effect, are mostly penalized for the embodied emissions associated with the imports to
their economy, and vice versa.
keywords: تغییرات اقلیمی | حسابداری کربن | مسیولیت تقسیم شده | انتشار کربن اضافه شده است | تجزیه و تحلیل ExergoEnviremental | هزینه اگزرژی | Climate change | Carbon accounting | Shared responsibility | Carbon emission added | Exergoenvironmental analysis | Exergy cost |
مقاله انگلیسی |
4 |
Maize production and environmental costs: Resource evaluation and strategic land use planning for food security in northern Ghana by means of coupled emergy and data envelopment analysis
تولید ذرت و هزینه های زیست محیطی: ارزیابی منابع و برنامه ریزی استراتژیک کاربری اراضی برای امنیت غذایی در شمال غنا با استفاده از تجزیه و تحلیل آمیخته و پوشش داده ها-2020 This paper applies an integrated methodology which is constituted of the following: (i) the Emergy-Data
Envelopment Analysis (EM-DEA), (ii) environmental Cost-Benefit Analysis (CBA), (iii) Value Chain Analysis
(VCA), and (iv) Sustainability Balanced Scorecard (SBSC) approaches, -to support multicriteria decision analysis
(MCDA) for strategic agricultural land use planning, which could contribute to improve food security in northern
Ghana. Five scenarios of land use and resource management practices for maize production were modelled. The
business-as-usual scenario was based on primary data, which were collected using semi-structured questionnaires administered to 56 small-scale maize farmers through personal interviews. The dominant land use was
characterised by an external input ≤12 kg/ha/yr inorganic fertilizer with/without the addition of manure in
rainfed maize systems. The project scenarios were based on APSIM simulations of maize yield response to 0, 20,
50 and 100 kg/ha/yr urea dosages, with/without supplemental irrigation. The scenarios were dubbed as follows:
(1) no/low input systems were denoted by Extensive0, Extensive12, and Intercrop20, and (2) moderate/high input
systems were denoted by Intensive50, and Intensive100. The EM-DEA approach was used to assess the resource
use efficiency (RUE) and sustainability in maize production systems, Ghana. The measured RUE and sustainability were used as a proxy for further analyses by applying the environmental CBA and VCA approaches to
calculate: (a) the environmental costs of producing maize, i.e. resource use measured as total emergy (U), and (b)
benefits from the yielded maize, i.e. (b i) food provision from grain measured in kcal/yr, and (b ii) potential
electricity (bioenergy) which could be generated from residue measured in MWh/yr. The information which was
derived from the applications of the EM-DEA, CBA and VCA approaches was aggregated by applying the SBSC
approach to do a sustainability appraisal of the scenarios. The results show that, when labour and services are
included in the assessment of RUE and sustainability, Intercrop20 and Intensive50 achieved greater marginal
yield, better RUE, sustainability and appraisal score. The same scenarios caused lesser impacts in terms of expansion of area cultivated compared to Extensive0 and Extensive12. Meanwhile the impacts of Intercrop20 and
Intensive50 in terms of ecotoxicity, emissions, and demand for resources (energy, materials, labour and services)
were lesser compared to Intensive100. The implications of the various scenarios are discussed. The environmental
performance of the scenarios are compared to maize production systems in other developing regions in order to
put this study within a broader context. We conclude that, the EM-DEA approach is useful for assessing RUE and
sustainability of agricultural production systems at farm and regional scales, as well as in connecting the
management planning level and regional development considerations. Keywords: Food security | Sustainable agriculture | Strategic land use planning | Emergy-Data envelopment analysis | Environment-biomass-food-energy nexus | Sub-Saharan Africa |
مقاله انگلیسی |
5 |
نقش مدیران دولتی در انطباق سیاست دستورالعملهای حمل و نقل: چگونه دانش ایجاد و بازتولید میشود
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 9 - تعداد صفحات فایل doc فارسی: 30 اتحادیه اروپا (EU)، و همچنین بسیاری از دولتهای ملی، دستورالعملهایی را برای کاهش اثرات زیست محیطی حمل و نقل اتخاذ کردهاند. به عنوان مثال، استراتژی سوخت پاک اتحادیه اروپا، کشورهای عضو را ملزم میکند تا چارچوبهای سیاست ملی را برای توسعه بازار سوختهای جایگزین و زیرساختهای آنها میکند. با توجه به این دستورالعملها، راهحلهای سیاستی باید توسط کشورهای عضو تدوین و پیشنهاد شود. این مقاله بر مرحله انطباق خط مشی یک فرآیند خط مشی متمرکز است، به ویژه بر دانشسازی مدیران به هنگام ایجاد پیشنهادهای خط مشی توجه دارد. این مقاله تئوری خط مشی را با تئوری برنامهریزی ادغام میکند و چارچوبی نظری برای مطالعه انطباق سیاست، به ویژه، ساخت دانش مدیران در چنین فرآیندهایی ارائه میکند. مطالعه تجربی بر اساس دو مورد است که هر دو درباره سوئد است. در نتیجه مدیران از چندین منبع دانش استفاده میکنند: دانش فرآیند، دانش پروژه و دانش زمینه. راهحلهای خط مشی جدید با استفاده مجدد از دادههای گزارشهای موجود و پیشنهادات خط مشی ساخته میشوند. تمرکز خاصی بر استفاده از تحلیل اقتصادی به عنوان ابزاری برای ارزیابی راهحلها بوده است. این مقاله نشان میدهد که در مرحله انطباق سیاست، هیچ تحلیل جدیدی انجام نمیشود و از استراتژیهای جداسازی هنگام پرداختن به تحلیل اقتصادی استفاده میشود.
کلید واژه ها: انطباق سیاست | حمل و نقل عمومی | مدیریت عمومی | دانش | حمل و نقل پایدار | CBA |
مقاله ترجمه شده |
6 |
نقش مدیران دولتی در انطباق سیاست دستورالعملهای حمل و نقل: چگونه دانش ایجاد و بازتولید میشود
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 9 - تعداد صفحات فایل doc فارسی: 30 اتحادیه اروپا (EU)، و همچنین بسیاری از دولتهای ملی، دستورالعملهایی را برای کاهش اثرات زیست محیطی حمل و نقل اتخاذ کردهاند. به عنوان مثال، استراتژی سوخت پاک اتحادیه اروپا، کشورهای عضو را ملزم میکند تا چارچوبهای سیاست ملی را برای توسعه بازار سوختهای جایگزین و زیرساختهای آنها میکند. با توجه به این دستورالعملها، راهحلهای سیاستی باید توسط کشورهای عضو تدوین و پیشنهاد شود. این مقاله بر مرحله انطباق خط مشی یک فرآیند خط مشی متمرکز است، به ویژه بر دانشسازی مدیران به هنگام ایجاد پیشنهادهای خط مشی توجه دارد. این مقاله تئوری خط مشی را با تئوری برنامهریزی ادغام میکند و چارچوبی نظری برای مطالعه انطباق سیاست، به ویژه، ساخت دانش مدیران در چنین فرآیندهایی ارائه میکند. مطالعه تجربی بر اساس دو مورد است که هر دو درباره سوئد است. در نتیجه مدیران از چندین منبع دانش استفاده میکنند: دانش فرآیند، دانش پروژه و دانش زمینه. راهحلهای خط مشی جدید با استفاده مجدد از دادههای گزارشهای موجود و پیشنهادات خط مشی ساخته میشوند. تمرکز خاصی بر استفاده از تحلیل اقتصادی به عنوان ابزاری برای ارزیابی راهحلها بوده است. این مقاله نشان میدهد که در مرحله انطباق سیاست، هیچ تحلیل جدیدی انجام نمیشود و از استراتژیهای جداسازی هنگام پرداختن به تحلیل اقتصادی استفاده میشود.
کلید واژه: انطباق سیاست | حمل و نقل عمومی | مدیریت عمومی | دانش | حمل و نقل پایدار | CBA |
مقاله ترجمه شده |
7 |
Optimal energy management with balanced fuel economy and battery life for large hybrid electric mining truck
مدیریت بهینه انرژی با مصرف سوخت متعادل و عمر باتری برای کامیون های بزرگ برقی هیبریدی-2020 With the addition of an energy storage system (ESS) and advanced controls, a hybrid electric propulsion system
can considerably improve the fuel economy over a pure mechanical powertrain. However, the high cost and
relatively short operating life of the battery ESS constitute a significant portion of the total operation cost (TOC)
of an electrified vehicle, particularly for heavy-duty vehicles with a larger ESS. In this work, a new method for
generating the optimal energy management strategy (EMS), considering the TOC of a hybrid electric mining
truck (HEMT), is introduced. The cost associated with battery performance degradation and operation lifeshortening
under different battery use patterns is added to form the globally optimal, TOC-based EMS. The
optimal EMS under different vehicle operation profiles are identified using dynamic programming (DP) to serve
as benchmarks. An intelligent optimal ESS energy management method for achieving the minimum TOC during
real-time, open-pit HEMT operations is introduced by combining an artificial neural network (ANN) model and a
fuzzy-logic controller (FLC). The new, real-time intelligent optimal EMS led to twenty-one percent TOC reduction
of the HEMT over the traditional, pure fuel economy-oriented optimal EMS, and formed the foundation of TOCbased,
optimal EMS development for hybrid electric vehicles (HEVs). Keywords: Hybrid electric mining truck | Online energy management strategy | Battery performance degradation | Neural network | Hybrid electric vehicles |
مقاله انگلیسی |
8 |
Identifying mutation positions in all segments of influenza genome enables better differentiation between pandemic and seasonal strains
شناسايي موقعيت جهش در تمامي بخش هاي ژنوم آنفلوانزا باعث تمايز بهتر ميان سويه ها و بيماري هاي فصلي مي شود-2019 Influenza has a negative sense, single-stranded, and segmented RNA. In the context of pandemic influenza research,
most studies have focused on variations in the surface proteins (Hemagglutinin and Neuraminidase).
However, new findings suggest that all internal and external proteins of influenza viruses can contribute in
pandemic emergence, pathogenicity and increasing host range. The occurrence of the 2009 influenza pandemic
and the availability of many external and internal segments of pandemic and non-pandemic sequences offer a
unique opportunity to evaluate the performance of machine learning models in discrimination of pandemic from
seasonal sequences using mutation positions in all segments. In this study, we hypothesized that identifying
mutation positions in all segments (proteins) encoded by the influenza genome would enable pandemic and
seasonal strains to be more reliably distinguished. In a large scale study, we applied a range of data mining
techniques to all segments of influenza for rule discovery and discrimination of pandemic from seasonal strains.
CBA (classification based on association rule mining), Ripper and Decision tree algorithms were utilized to
extract association rules among mutations. CBA outperformed the other models. Our approach could discriminate
pandemic sequences from seasonal ones with more than 95% accuracy for PA and NP, 99.33% accuracy
for NA and 100% accuracy, precision, specificity and sensitivity (recall) for M1, M2, PB1, NS1, and NS2.
The values of precision, specificity, and sensitivity were more than 90% for other segments except PB2. If
sequences of all segments of one strain were available, the accuracy of discrimination of pandemic strains was
100%. General rules extracted by rule base classification approaches, such as M1-V147I, NP-N334H, NS1-V112I,
and PB1-L364I, were able to detect pandemic sequences with high accuracy. We observed that mutations on
internal proteins of influenza can contribute in distinguishing the pandemic viruses, similar to the external ones. Keywords: Association rule mining | CBA | Expert system | Hot spots | Ripper algorithm | Pandemic influenza |
مقاله انگلیسی |
9 |
Hybrid fast unsupervised feature selection for high-dimensional data
انتخاب ویژگی بدون نظارت هیبریدی سریع برای داده های با ابعاد بالا-2019 The emergence of “curse of dimensionality”issue as a result of high reduces datasets deteriorates the ca- pability of learning algorithms, and also requires high memory and computational costs. Selection of fea- tures by discarding redundant and irrelevant features functions as a crucial machine learning technique aimed at reducing the dimensionality of these datasets, which improves the performance of the learning algorithm. Feature selection has been extensively applied in many application areas relevant to expert and intelligent systems, such as data mining and machine learning. Although many algorithms have been developed so far, they are still unsatisfying confronting high-dimensional data. This paper presented a new hybrid filter-based feature selection algorithm based on acombination of clustering and the modi- fied Binary Ant System (BAS), called FSCBAS, to overcome the search space and high-dimensional data processing challenges efficiently. This model provided both global and local search capabilities between and within clusters. In the proposed method, inspired by genetic algorithm and simulated annealing, a damped mutation strategy was introduced that avoided falling into local optima, and a new redundancy reduction policy adopted to estimate the correlation between the selected features further improved the algorithm. The proposed method can be applied in many expert system applications such as microar- ray data processing, text classification and image processing in high-dimensional data to handle the high dimensionality of the feature space and improve classification performance simultaneously. The perfor- mance of the proposed algorithm was compared to that of state-of-the-art feature selection algorithms using different classifiers on real-world datasets. The experimental results confirmed that the proposed method reduced computational complexity significantly, and achieved better performance than the other feature selection methods. Keywords: Feature selection | High-dimensional data | Binary ant system | Clustering | Mutation |
مقاله انگلیسی |
10 |
Optimal LEACH protocol with modified bat algorithm for big data sensing systems in Internet of Things
پروتکل LEACH بهینه با الگوریتم خفاش اصلاح شده برای سیستم های سنجش از داده های بزرگ در اینترنت اشیا-2018 Big data sensing system (BDSS) plays an important role in the Internet of Things, in which how to reduce
power consumption is one crucial problem. Currently, low energy adaptive clustering hierarchy (LEACH)
protocol is one well-known algorithm used in BDSS with low energy cost. In this paper, a new variant of
bat algorithm combined with centroid strategy is introduced. Three different centroid strategies with six
different designs are introduced. In addition, the velocity inertia-free update equation is also provided.
The optimization performance is verified by CEC2013 benchmarks in those designs against standard BA.
Simulation results prove that the bat algorithm with weighted harmonic centroid (WHCBA) strategy is
superior to other algorithms. By integrating WHCBA into LEACH protocol, we develop a two-stage cluster
head node selection strategy and can save more energy compared to the standard LEACH protocol.
Keywords: LEACH protocol ، Bat algorithm with centroid strategy ، Inertia-free ، Big data sensing systems |
مقاله انگلیسی |