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1 |
Utilizing LiDAR data to map tree canopy for urban ecosystem extent and condition accounts in Oslo
با استفاده از داده های LIDAR به نقشه سایبان درخت برای اکوسیستم های شهری و حساب های وضعیت در اسلو-2021 LiDAR-based segmentation of urban tree canopies and their physical properties (canopy height, canopy diameter,
3D surface and volume) is a replicable, complementary and useful information source for urban ecosystem
condition accounts, and an important basis for ecosystem service modeling and valuation. However, using
available LiDAR data collected for municipal purposes other than vegetation mapping (such as for example
engineering) entails a level of accuracy which may limit the usefulness of the data for change detection in
ecosystem accounts. To account for changes in the urban tree canopy of Oslo (capital city of Norway) between
2011 and 2017, a segmentation model was developed based on available airborne LiDAR data scanned for
general purposes. The results from the entire built-up area of Oslo indicate a general increase in the number of
tall trees (>15 m) and a moderate increase in the number of small trees (<15 m), with the exception of trees
between 6 and 10 m which seem to have a relatively constant development over the given period. The total tree
canopy area within the built-up area increased by 17.15%, with a corresponding 21.35% increase in the tree
canopy volume. The results for the Small House plan area, a policy focus area subject to urban densification and
special regulations for felling of large trees, indicate a large increase in small trees (<10 m) and a moderate
decrease in tall trees (>10 m). The total tree canopy area within the Small House plan area decreased by 1.04%,
with a corresponding 2.13% decrease in the tree canopy volume. With respect to the segmentation accuracy, the
changes in aggregate tree canopy cover are too small to determine canopy change with confidence. This study
demonstrates the potential for identifying ecosystem condition indicators as well as the limitations of using
general purpose LiDAR data to improve the precision of urban ecosystem accounting. For future ecosystem
service accounting in urban environments, we recommend that municipalities implement data acquisition programs that combine concurrent field data sampling and LiDAR campaigns designed for urban tree canopy
detection, as part of general urban structural inventorying. We recommend using LiDAR and satellite remote
sensing data depending on canopy densities. We also recommend that future tree canopy segmentation is done
within a cloud-computing environment to ensure sufficient geoprocessing capacity.
keywords: تشخیص نور و محدوده (LIDAR) | سیستم های اطلاعات جغرافیایی (GIS) | سنجش از راه دور | حسابداری اکوسیستم | خدمات محیط زیستی | تقسیم بندی سایبان درخت | Light Detection And Ranging (LiDAR) | Geographical Information Systems (GIS) | Remote sensing | Ecosystem accounting | Ecosystem services | Tree canopy segmentation |
مقاله انگلیسی |
2 |
Problems of Poison: New Paradigms and "Agreed" Competition in the Era of AI-Enabled Cyber Operations
مسئله سم: پارادایم های جدید و رقابت "توافق شده" در عصر عملیات سایبری با هوش مصنوعی-2020 Few developments seem as poised to alter the characteristics of security in
the digital age as the advent of artificial intelligence (AI) technologies. For national
defense establishments, the emergence of AI techniques is particularly worrisome,
not least because prototype applications already exist. Cyber attacks augmented by
AI portend the tailored manipulation of human vectors within the attack surface of
important societal systems at great scale, as well as opportunities for calamity resulting
from the secondment of technical skill from the hacker to the algorithm. Arguably
most important, however, is the fact that AI-enabled cyber campaigns contain great
potential for operational obfuscation and strategic misdirection. At the operational
level, techniques for piggybacking onto routine activities and for adaptive evasion of
security protocols add uncertainty, complicating the defensive mission particularly
where adversarial learning tools are employed in offense. Strategically, AI-enabled
cyber operations offer distinct attempts to persistently shape the spectrum of cyber
contention may be able to pursue conflict outcomes beyond the expected scope of
adversary operation. On the other, AI-augmented cyber defenses incorporated into
national defense postures are likely to be vulnerable to “poisoning” attacks that
predict, manipulate and subvert the functionality of defensive algorithms. This article
takes on two primary tasks. First, it considers and categorizes the primary ways in
which AI technologies are likely to augment offensive cyber operations, including the
shape of cyber activities designed to target AI systems. Then, it frames a discussion
of implications for deterrence in cyberspace by referring to the policy of persistent engagement, agreed competition and forward defense promulgated in 2018 by the United States. Here, it is argued that the centrality of cyberspace to the deployment
and operation of soon-to-be-ubiquitous AI systems implies new motivations for
operation within the domain, complicating numerous assumptions that underlie
current approaches. In particular, AI cyber operations pose unique measurement
issues for the policy regime. Keywords: deterrence | persistent engagement | cyber | AI | machine learning |
مقاله انگلیسی |
3 |
How signal intensity of behavioral orientations affects crowdfunding performance: The role of entrepreneurial orientation in crowdfunding business ventures
چگونه شدت سیگنال جهت گیری های رفتاری بر عملکرد سرمایه گذاری جمعی تأثیر می گذارد: نقش جهت گیری کارآفرینی در سرمایه گذاری های سرمایه گذاری جمعی-2020 Backers assess a crowdfunding campaign description not merely for a project’s capacity to deliver a reward, but also for the manner in which that reward is delivered. Viewed through the lens of signalling theory, crowd- funding performance depends on the signals of behavioural orientations. While earlier research has explored the positive and negative effects of signals of behavioural orientation, signal intensity merits exploration. We ex- plored signal intensity among 48,628 reward-based crowdfunding campaigns and focused on entrepreneurial orientation to categorize signals of behavioural orientations. We show that signals of autonomy, innovativeness, competitive aggressiveness, and risk-taking have an inverted-U-shaped relationship with crowdfunding perfor- mance. Signals of proactiveness have a positive non-monotonic relationship with crowdfunding performance. Keywords: Crowdfunding | Entrepreneurship | Entrepreneurial orientation | Signalling | Entrepreneurial financing | Kickstarter |
مقاله انگلیسی |
4 |
Investigating the impact of multidimensional social capital on equity crowdfunding performance
بررسی تأثیر سرمایه اجتماعی چند بعدی بر عملکرد سرمایه گذاری جمعی سهام-2020 This research explores how social capital, in the multidimensional perspective using cognitive, relational and structural dimensions influences equity-crowdfunding (ECF) performance considering both the number of investors engaged and the funds collected. Our results demonstrate that cognitive dimensions in part affects ECF performance, in fact shared meaning has a little positive impact on both funding collected and the number of investors, while shared language has a negative effect on the investors involved. Both obligation and trust- worthiness (relational dimension) positively influence ECF performance. Regarding the structural dimension, social network ties has positive effects on ECF performance, while social interactions has a positive impact on funding collected. The research contributes to the current literature on ECF and highlights new factors affecting ECF performance. The study has implications from both a theoretical and a practical perspective. The study findings will be relevant for entrepreneurs, platforms managers and policymakers and offers avenues for further research. Keywords: Crowdfunding | Entrepreneurship | Social capital | Equity | Campaigns |
مقاله انگلیسی |
5 |
Explainability and Dependability Analysis of Learning Automata based AI Hardware
تحلیل توضیح و قابلیت اطمینان یادگیری سخت افزار هوش مصنوعی مبتنی بر Automata-2020 Explainability remains the holy grail in designing
the next-generation pervasive artificial intelligence (AI) systems.
Current neural network based AI design methods do not
naturally lend themselves to reasoning for a decision making
process from the input data. A primary reason for this is the
overwhelming arithmetic complexity.
Built on the foundations of propositional logic and game
theory, the principles of learning automata are increasingly
gaining momentum for AI hardware design. The lean logic based
processing has been demonstrated with significant advantages
of energy efficiency and performance. The hierarchical logic
underpinning can also potentially provide opportunities for bydesign
explainable and dependable AI hardware. In this paper,
we study explainability and dependability using reachability
analysis in two simulation environments. Firstly, we use a behavioral
SystemC model to analyze the different state transitions.
Secondly, we carry out illustrative fault injection campaigns in
a low-level SystemC environment to study how reachability is
affected in the presence of hardware stuck-at 1 faults. Our
analysis provides the first insights into explainable decision
models and demonstrates dependability advantages of learning
automata driven AI hardware design. Keywords: Rainfall | Artificial | Computing | Simulation | Architecture |
مقاله انگلیسی |
6 |
Big data analytics for supply chain relationship in banking
تجزیه و تحلیل داده های بزرگ برای رابطه زنجیره تأمین در بانکداری-2020 This paper reports how a commercial bank in Asia uses big data analytic as a tool to explore the internal B2B
data to improve supply chain finance and the efficiency of marketing tactics and campaigns. A case study was
conducted by analyzing two types of supply chain relationships: (1) supply chain relationships in the credit
reports; (2) e-wiring transactions among supply chain companies. The results show that big data analytics is very
useful in terms of improving the commercial banks marketing and risk management performances. The case
study also set a good example for B2B firms seeking to understand how they could leverage big data analytics to
differentiate customer solutions, sustain profitability and generate new business values. Theorical and practical
implications are also discussed. Keywords: Supply chain finance | B2B analytics |
مقاله انگلیسی |
7 |
China’s green future and household solid waste: Challenges and prospects
آینده سبز چین و ضایعات جامد خانگی: چالش ها و چشم انداز-2020 China is facing the dual challenge of economic development and environment protection. Recently,
Shanghai (tier-1 city) implemented the pilot project of household solid waste (HSW) management and
expects to execute a similar project in 45 cities across China by 2020. The current research’s aim is to
examine the pilot project’s progress by comparing it with existing HSW management practice in other
cities. From a theoretical perspective, a socio-ecological framework is used to examine citizens’ HSW
sorting behavior (HSWSB), which is further mapped based on the theory of planned behavior to enrich
the findings. A total of 1409 citizen responses are utilized to generalize the findings. The study concludes
that replicating tier-1 practices in other cities could produce unsatisfactory results. The regulatory environment
should focus on comparatively long-lasting citizen behavior change by designing a citizencentric
approach (i.e., awareness campaigns) related to ecological concerns (i.e., climate change) because
it could define the future of HSWSB practice in Chinese society. Keywords: Socio-ecological framework | Theory of planned behavior | Household solid waste | Waste sorting | China |
مقاله انگلیسی |
8 |
Free-play impact by customer segment
تأثیر بازی رایگان توسط بخش مشتری-2020 Little is known about the effectiveness of casino free-play campaigns, despite hundreds of millions of dollars in
annual redemptions. These costly play incentives are awarded to individual players, based largely on management’s
evaluation of their historical play. Extant campaign-level research suggests these incentives may not be
effective in driving spend per visit, but there has been no attempt to examine efficacy across player tiers (e.g.,
light, medium, and heavy users). Analysis of 365 days of performance data from a Las Vegas Strip casino produced
varied results across tiers, but all tier-level findings indicated a failure to recover the face value of the freeplay
incentives. While no support was garnered for the house money effect, the results were consistent with the
notion of loss aversion. The methodological approach outlined herein provides the means to critically evaluate
free-play offers at the tier level, fast-tracking campaign optimization via more targeted revisions. Keywords: Casino marketing | Casino management | Free-play offers | House money effect | Loss aversion | Endowment effect | Reverse house money effect | rospect-theory-with-memory effect |
مقاله انگلیسی |
9 |
Energy management strategy to reduce pollutant emissions during the catalyst light-off of parallel hybrid vehicles
استراتژی مدیریت انرژی برای کاهش انتشار آلاینده ها در هنگام خاموش شدن کاتالیزور وسایل نقلیه هیبریدی موازی-2020 The transportation sector is a major contributor to both air pollution and greenhouse gas emissions. Hybrid
electric vehicles can reduce fuel consumption and CO2 emissions by optimizing the energy management of the
powertrain. The purpose of this study is to examine the trade-off between regulated pollutant emissions and
hybrid powertrain efficiency. The thermal dynamics of the three-way catalyst are taken into account in order to
optimize the light-off. Experimental campaigns are conducted on a spark-ignition engine to introduce simplified
models for emissions, exhaust gas temperature, catalyst heat transfers and efficiency. These models are used to
determine the optimal distribution of a power request between the thermal engine and the electric motor with
three-dimensional dynamic programming and a weighted objective function. A pollution-centered scenario is
compared with a consumption-centered scenario for various driving cycles. The optimal torque distribution for
the emissions-centered scenario on the world harmonized light-duty vehicles test cycle shows an 8–33% decrease
in pollutant emissions while the consumption remains stable (0.1% increase). The consistency of the results is
analyzed with respect to the discretization parameters, driving cycle, electric motor and battery sizing, as well as
emission and catalyst models. The control strategies are promising but will have to be adapted to online engine
control where the driving cycle and the catalyst efficiency are uncertain.. Keywords: Hybrid electric vehicle | Energy management strategy | Dynamic programming | Catalyst thermal behavior | Fuel consumption | Pollutant emissions |
مقاله انگلیسی |
10 |
User engagement for mobile payment service providers : introducing the social media engagement model
تعامل کاربر برای ارائه دهندگان خدمات پرداخت تلفن همراه: معرفی مدل تعامل رسانه های اجتماعی-2020 Twitter is being used by mobile wallet firms for customer acquisition, relationship management, marketing and
promotional purposes. This study examines service advertisement and promotional tweets by mobile wallet
firms on Twitter. For this study, timeline data of top four mobile wallet firms of India, Paytm, MobiKwik,
Freecharge and Oxigen Wallet were extracted from their Twitter screen (firm generated tweets). The user
generated tweets were also extracted, using the search terms as firms name. This study proposes a Social Media
Engagement model for understanding user dynamics. The study provides three interesting inputs for promotional
marketing tweets, firstly, firm should post mix of the tweets with respect to content type (i.e. informational,
entertainment, remuneration and social). Secondly, a periodic campaigning is needed by the firms; and
lastly, firms should focus on increasing their network size. The implications of these findings can help firms
managers and marketers in planning effective social media marketing campaigns. Keywords: Social media marketing | Digital payments | Twitter analytics | Mobile wallets | Customer engagement |
مقاله انگلیسی |