scholarly journals Conductor Reconstruction for Dynamic Line Rating Using Vehicle-Mounted LiDAR

2020 ◽  
Vol 12 (22) ◽  
pp. 3718
Author(s):  
Josh McCulloch ◽  
Richard Green
Keyword(s):  
Linear Problem ◽  
Lower Cost ◽  
State Of The Art ◽  
Load Capacity ◽  
Urban Environments ◽  
Airborne Lidar ◽  
Electrical Network ◽  
High Tension ◽  
Utility Poles ◽  
The Cost

Dynamic Line Rating (DLR) is a process which electrical network operators can implement to improve efficiency by dynamically adjusting the load capacity as conditions allow. To implement DLR an accurate model of the conductors and their clearances is needed. Airborne LiDAR, while expensive, is the most common method of collecting line data as it is fast and is of high quality. State of the art methods for automatically reconstructing conductors first classify conductor points before fitting conductor models. This approach works well for high tension lines with significant separation between conductors but tends to perform poorly in urban environments where conductors are packed tightly together and surrounded by clutter. The method presented in this article attempts to overcome these challenges by performing an informed search for the conductors, anchored to the utility poles. Before the conductors are classified, their layout and sag are estimated, converting conductor segmentation into a linear problem; and a 3D to 2D projection is used to improve density and simplify clustering. The work also attempts to reduce the cost of conductor reconstruction by utilising lower-cost vehicle-mounted LiDAR. By avoiding point classification, higher precision can be achieved in scenarios where previous methods have suffered from significantly degraded performance.

Offloading as a Service Middleware for Mobile Cloud Apps

2020 ◽  
Vol 10 (2) ◽  
pp. 36-55 ◽  
Author(s):  
Hamid A Jadad ◽  
Abderezak Touzene ◽  
Khaled Day
Keyword(s):  
Large Scale ◽  
Lower Cost ◽  
Performance Metrics ◽  
State Of The Art ◽  
Mobile App ◽  
Minimum Number ◽  
Computing Platforms ◽  
Load Balancing Algorithm ◽  
The Cost ◽  
Multiple Load

Recently, much research has focused on the improvement of mobile app performance and their power optimization, by offloading computation from mobile devices to public cloud computing platforms. However, the scalability of these offloading services on a large scale is still a challenge. This article describes a solution to this scalability problem by proposing a middleware that provides offloading as a service (OAS) to large-scale implementation of mobile users and apps. The proposed middleware OAS uses adaptive VM allocation and deallocation algorithms based on a CPU rate prediction model. Furthermore, it dynamically schedules the requests using a load-balancing algorithm to ensure meeting QoS requirements at a lower cost. The authors have tested the proposed algorithm by conducting multiple simulations and compared our results with state-of-the-art algorithms based on various performance metrics under multiple load conditions. The results show that OAS achieves better response time with a minimum number of VMs and reduces 50% of the cost compared to existing approaches.

Server Allocation for Massively Multiplayer Online Cloud Games Using Evolutionary Optimization

2021 ◽  
Vol 17 (2) ◽  
pp. 1-23
Author(s):  
Meiqi Zhao ◽  
Jianmin Zheng ◽  
Elvis S. Liu
Keyword(s):  
Lower Cost ◽  
Data Transfer ◽  
State Of The Art ◽  
Portable Devices ◽  
Massively Multiplayer Online Games ◽  
Network Latency ◽  
Server Allocation ◽  
The Cost ◽  
Massively Multiplayer

In recent years, Massively Multiplayer Online Games (MMOGs) are becoming popular, partially due to their sophisticated graphics and broad virtual world, and cloud gaming is demanded more than ever especially when entertaining with light and portable devices. This article considers the problem of server allocation for running MMOG on cloud, aiming to reduce the cost on cloud gaming service and meanwhile enhance the quality of service. The problem is formulated into minimizing an objective function involving the cost of server rental, the cost of data transfer and the network latency during the gaming time. A genetic algorithm is developed to solve the minimization problem for processing simultaneous server allocation for the players who log into the system at the same time while many existing players are playing the same game. Extensive experiments based on the player behavior in “World of Warcraft” are conducted to evaluate the proposed method and compare with the state-of-the-art as well. The experimental results show that the method gives a lower cost and a shorter network latency in most of the time.

scholarly journals Costs and Benefits of Autonomous Shipping—A Literature Review

2021 ◽  
Vol 11 (10) ◽  
pp. 4553
Author(s):  
Ewelina Ziajka-Poznańska ◽  
Jakub Montewka
Keyword(s):  
Literature Review ◽  
Business Models ◽  
Financial Models ◽  
State Of The Art ◽  
Costs And Benefits ◽  
Capital Costs ◽  
Research Activities ◽  
Benefit Estimation ◽  
Autonomous Ship ◽  
The Cost

The development of autonomous ship technology is currently in focus worldwide and the literature on this topic is growing. However, an in-depth cost and benefit estimation of such endeavours is in its infancy. With this systematic literature review, we present the state-of-the-art system regarding costs and benefits of the operation of prospective autonomous merchant ships with an objective for identifying contemporary research activities concerning an estimation of operating, voyage, and capital costs in prospective, autonomous shipping and vessel platooning. Additionally, the paper outlines research gaps and the need for more detailed business models for operating autonomous ships. Results reveal that valid financial models of autonomous shipping are lacking and there is significant uncertainty affecting the cost estimates, rendering only a reliable evaluation of specific case studies. The findings of this paper may be found relevant not only by academia, but also organisations considering to undertake a challenge of implementing Maritime Autonomous Surface Ships in their operations.

scholarly journals A review on the properties, reinforcing effects, and commercialization of nanomaterials for cement-based materials

2020 ◽  
Vol 9 (1) ◽  
pp. 303-322 ◽  
Author(s):  
Zhifang Zhao ◽  
Tianqi Qi ◽  
Wei Zhou ◽  
David Hui ◽  
Cong Xiao ◽  
...  
Keyword(s):  
Cement Hydration ◽  
State Of The Art ◽  
Research Progress ◽  
Market Survey ◽  
Future Perspectives ◽  
Nano Silica ◽  
Physical Processes ◽  
Existing Problems ◽  
Cement Based Materials ◽  
The Cost

AbstractThe behavior of cement-based materials is manipulated by chemical and physical processes at the nanolevel. Therefore, the application of nanomaterials in civil engineering to develop nano-modified cement-based materials is a promising research. In recent decades, a large number of researchers have tried to improve the properties of cement-based materials by employing various nanomaterials and to characterize the mechanism of nano-strengthening. In this study, the state of the art progress of nano-modified cement-based materials is systematically reviewed and summarized. First, this study reviews the basic properties and dispersion methods of nanomaterials commonly used in cement-based materials, including carbon nanotubes, carbon nanofibers, graphene, graphene oxide, nano-silica, nano-calcium carbonate, nano-calcium silicate hydrate, etc. Then the research progress on nano-engineered cementitious composites is reviewed from the view of accelerating cement hydration, reinforcing mechanical properties, and improving durability. In addition, the market and applications of nanomaterials for cement-based materials are briefly discussed, and the cost is creatively summarized through market survey. Finally, this study also summarizes the existing problems in current research and provides future perspectives accordingly.

scholarly journals Stochastic methods defeat regular RSA exponentiation algorithms with combined blinding methods

2021 ◽  
Vol 15 (1) ◽  
pp. 408-433
Author(s):  
Margaux Dugardin ◽  
Werner Schindler ◽  
Sylvain Guilley
Keyword(s):  
State Of The Art ◽  
Stochastic Methods ◽  
Rsa Algorithm ◽  
Montgomery Ladder ◽  
Channel Information ◽  
Probability Mass ◽  
The Cost ◽  
Noisy Measurements ◽  
Mass Functions ◽  
Larger Sample

Abstract Extra-reductions occurring in Montgomery multiplications disclose side-channel information which can be exploited even in stringent contexts. In this article, we derive stochastic attacks to defeat Rivest-Shamir-Adleman (RSA) with Montgomery ladder regular exponentiation coupled with base blinding. Namely, we leverage on precharacterized multivariate probability mass functions of extra-reductions between pairs of (multiplication, square) in one iteration of the RSA algorithm and that of the next one(s) to build a maximum likelihood distinguisher. The efficiency of our attack (in terms of required traces) is more than double compared to the state-of-the-art. In addition to this result, we also apply our method to the case of regular exponentiation, base blinding, and modulus blinding. Quite surprisingly, modulus blinding does not make our attack impossible, and so even for large sizes of the modulus randomizing element. At the cost of larger sample sizes our attacks tolerate noisy measurements. Fortunately, effective countermeasures exist.

scholarly journals State of the Art in Open Platforms for Collaborative Urban Design and Sharing of Resources in Districts and Cities

2021 ◽  
Vol 13 (9) ◽  
pp. 4875
Author(s):  
Barry Hayes ◽  
Dorota Kamrowska-Zaluska ◽  
Aleksandar Petrovski ◽  
Cristina Jiménez-Pulido
Keyword(s):  
Urban Design ◽  
Local Community ◽  
State Of The Art ◽  
Sharing Economy ◽  
Peer To Peer ◽  
Urban Environments ◽  
The State ◽  
Smart Technology ◽  
Technological Advances ◽  
Technology Platforms

This work discusses recent developments in sharing economy concepts and collaborative co-design technology platforms applied in districts and cities. These developments are being driven both by new technological advances and by increased environmental awareness. The paper begins by outlining the state of the art in smart technology platforms for collaborative urban design, highlighting a number of recent examples. The case of peer-to-peer trading platforms applied in the energy sector is then used to illustrate how sharing economy concepts and their enabling technologies can accelerate efforts towards more sustainable urban environments. It was found that smart technology platforms can encourage peer-to-peer and collaborative activity, and may have a profound influence on the future development of cities. Many of the research and development projects in this area to date have focused on demonstrations at the building, neighbourhood, and local community scales. Scaling these sharing economy platforms up to the city scale and beyond has the potential to provide a number of positive environment impacts. However, significant technical and regulatory barriers to wider implementation exist, and realising this potential will require radical new approaches to the ownership and governance of urban infrastructure. This paper provides a concise overview of the state of the art in this emerging field, with the aim of identifying the most promising areas for further research.

scholarly journals A trade-off between classical and quantum circuit size for an attack against CSIDH

2020 ◽  
Vol 15 (1) ◽  
pp. 4-17
Author(s):  
Jean-François Biasse ◽  
Xavier Bonnetain ◽  
Benjamin Pring ◽  
André Schrottenloher ◽  
William Youmans
Keyword(s):  
Endomorphism Ring ◽  
State Of The Art ◽  
Quantum Circuit ◽  
List Type ◽  
Hard Problem ◽  
Trade Off ◽  
Classical State ◽  
Security Parameter ◽  
The Cost ◽  
Quadratic Order

AbstractWe propose a heuristic algorithm to solve the underlying hard problem of the CSIDH cryptosystem (and other isogeny-based cryptosystems using elliptic curves with endomorphism ring isomorphic to an imaginary quadratic order 𝒪). Let Δ = Disc(𝒪) (in CSIDH, Δ = −4p for p the security parameter). Let 0 < α < 1/2, our algorithm requires:A classical circuit of size $2^{\tilde{O}\left(\log(|\Delta|)^{1-\alpha}\right)}.$A quantum circuit of size $2^{\tilde{O}\left(\log(|\Delta|)^{\alpha}\right)}.$Polynomial classical and quantum memory.Essentially, we propose to reduce the size of the quantum circuit below the state-of-the-art complexity $2^{\tilde{O}\left(\log(|\Delta|)^{1/2}\right)}$ at the cost of increasing the classical circuit-size required. The required classical circuit remains subexponential, which is a superpolynomial improvement over the classical state-of-the-art exponential solutions to these problems. Our method requires polynomial memory, both classical and quantum.

A Scalable Redefined Stochastic Blockmodel

2021 ◽  
Vol 15 (3) ◽  
pp. 1-28
Author(s):  
Xueyan Liu ◽  
Bo Yang ◽  
Hechang Chen ◽  
Katarzyna Musial ◽  
Hongxu Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Network Science ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Real World Data ◽  
Computational Overhead ◽  
Stochastic Blockmodel ◽  
Np Hard Problem ◽  
Large Scale Networks ◽  
The Cost

Stochastic blockmodel (SBM) is a widely used statistical network representation model, with good interpretability, expressiveness, generalization, and flexibility, which has become prevalent and important in the field of network science over the last years. However, learning an optimal SBM for a given network is an NP-hard problem. This results in significant limitations when it comes to applications of SBMs in large-scale networks, because of the significant computational overhead of existing SBM models, as well as their learning methods. Reducing the cost of SBM learning and making it scalable for handling large-scale networks, while maintaining the good theoretical properties of SBM, remains an unresolved problem. In this work, we address this challenging task from a novel perspective of model redefinition. We propose a novel redefined SBM with Poisson distribution and its block-wise learning algorithm that can efficiently analyse large-scale networks. Extensive validation conducted on both artificial and real-world data shows that our proposed method significantly outperforms the state-of-the-art methods in terms of a reasonable trade-off between accuracy and scalability. 1

Computing Robust Principal Components by A* Search

2018 ◽  
Vol 27 (07) ◽  
pp. 1860013 ◽  
Author(s):  
Swair Shah ◽  
Baokun He ◽  
Crystal Maung ◽  
Haim Schweitzer
Keyword(s):  
State Of The Art ◽  
Principal Component ◽  
Low Rank ◽  
A Algorithm ◽  
Running Time ◽  
Current State ◽  
Dimensionality Reduction Technique ◽  
Related Variant ◽  
Low Rank Representation ◽  
The Cost

Principal Component Analysis (PCA) is a classical dimensionality reduction technique that computes a low rank representation of the data. Recent studies have shown how to compute this low rank representation from most of the data, excluding a small amount of outlier data. We show how to convert this problem into graph search, and describe an algorithm that solves this problem optimally by applying a variant of the A* algorithm to search for the outliers. The results obtained by our algorithm are optimal in terms of accuracy, and are shown to be more accurate than results obtained by the current state-of-the- art algorithms which are shown not to be optimal. This comes at the cost of running time, which is typically slower than the current state of the art. We also describe a related variant of the A* algorithm that runs much faster than the optimal variant and produces a solution that is guaranteed to be near the optimal. This variant is shown experimentally to be more accurate than the current state-of-the-art and has a comparable running time.

Light Rail Versus Guided Light Transit in Medium-Sized Cities: A Comparative Study for Ioannina, Greece

2017 ◽  
Vol 22 (3) ◽  
pp. 253-274
Author(s):  
Konstantinos Kepaptsoglou ◽  
Eleni Vlahogianni ◽  
Nikolaos Giannoulis ◽  
Aristeidis G. Karlaftis
Keyword(s):  
Public Transportation ◽  
Lower Cost ◽  
Negative Impact ◽  
Urban Environments ◽  
Social Benefits ◽  
Light Rail ◽  
Transit Systems ◽  
Additional Advantage ◽  
Transportation Services ◽  
High Investment

Light rail transit systems (LRTs) are attractive options for modern communities as they offer high quality, sustainable public transportation services. However, investment costs often may make their application for medium-sized cities prohibitive, particularly if no significant social benefits are achieved. Guided light transit (GLT) has been introduced in the recent years, as a lower cost alternative to LRT, with the additional advantage of being suitable for urban environments with space limitations. In this study, a systematic comparison of LRT and GLT is offered, in the context of a mid-size city in Greece. Results indicate that high investment costs, coupled with low ridership can have a negative impact to the introduction of LRT in a medium-sized city. However, under certain conditions, GLT may be a viable alternative, while its nature and characteristics are not that different to those of LRT.

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