Balancing efficiency and homogeneity of biomaterial transport in networks

2021 ◽  
Vol 135 (5) ◽  
pp. 58001
Author(s):  
Susanne Liese ◽  
L. Mahadevan ◽  
Andreas Carlson
Keyword(s):  
2006 ◽  
Author(s):  
Rob Baltussen ◽  
E. Stolk ◽  
D. Chisholm ◽  
M. Aikins

Open Physics ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 439-447
Author(s):  
Lijie Yan ◽  
Xudong Liu

AbstractTo a large extent, the load balancing algorithm affects the clustering performance of the computer. This paper illustrated the common load balancing algorithms and elaborated on the advantages and drawbacks of such algorithms. In addition, this paper provides a kind of balancing algorithm generated on the basis of the load prediction. Due to the dynamic exponential smoothing model, such an algorithm helps obtain the corresponding smoothing coefficient with the server node load time series of current phrase and allows researchers to make prediction with the load value at the next moment of this node. Subsequently, the dispatcher makes the scheduling with the serve request of users according to the load predicted value. OPNET Internet simulated software is applied to the test, and we may conclude from the results that the application of such an algorithm acquires a higher load balancing efficiency and better load balancing effect.


2014 ◽  
Vol 13 (02) ◽  
pp. 113-131 ◽  
Author(s):  
P. Sivasankaran ◽  
P. Shahabudeen

Balancing assembly line in a mass production system plays a vital role to improve the productivity of a manufacturing system. In this paper, a single model assembly line balancing problem (SMALBP) is considered. The objective of this problem is to group the tasks in the assembly network into a minimum number of workstations for a given cycle time such that the balancing efficiency is maximized. This problem comes under combinatorial category. So, it is essential to develop efficient heuristic to find the near optimal solution of the problem in less time. In this paper, an attempt has been made to design four different genetic algorithm (GA)-based heuristics, and analyze them to select the best amongst them. The analysis has been carried out using a complete factorial experiment with three factors, viz. problem size, cycle time, and algorithm, and the results are reported.


Author(s):  
Bian XIONG ◽  
Fen LIN

LANGUAGE NOTE | Document text in Chinese; abstract also in English.新冠病毒疫情催生了以中國的“健康碼”和新加坡的“TraceTogether”為代表的接觸者追蹤應用程式在全球的應用和擴散。如何利用人工智慧科技,在資料治理中平衡效率與隱私倫理的闢係,成為使用數位追蹤工具進行疫情治理的國家共同面對的難題。兩國法律都規定,在收集個人資訊前必須向個人資訊主體明確告知所收集的個人資訊類型、使用個人資訊的規則,並獲得個人資訊主體的授權同意。本文通過對“健康碼”和“TraceTogether”隱私政策的對比分析發現,在應用 上,中國健康碼的使用有效幫助防控疫情,但是收集的個人資訊範園廣、處理目的多、存儲時間不明確、隱私政策内容較含糊、知情同意流於形式。新加坡的“TraceTogether”則更好地遵守了資訊收集最少夠用、資訊處理目的限定、資訊存儲時間最小化、隱私政策公開透明、知情同意等原則。中國和新加坡兩種利用資料抗疫的糢式表明,風險社會裡的資料治理需要進一步調和公共利益與個人權利,平衡治理效率和資料倫理的邊界。The COVID-19 pandemic has spawned the spread of contact-tracing applications such as China's “Health Code” and Singapore’s “TraceTogether.” Balancing efficiency and privacy ethics in data governance has become a common problem faced by all countries using digital tracing tools to control the pandemic. The laws of both China and Singapore stipulate that prior to collecting personal information, organizations and institutions must clearly inform individuals about the types of personal information collected and the rules for the use of personal information, and must obtain authorized user consent. This article analyzes the privacy policies of Health Code in China and TraceTogether in Singapore and identifies five potential problems in Health Code’s privacy policies: the broad collection of personal information, multiple processing purposes, indeterminate storage time, ambiguous privacy policy content, and the ineffectiveness of informed consent, although Health Code has been deemed an efficient tool to fight against the pandemic. Singapore’s TraceTogether adheres to the principles of minimum information collection, limited information processing purposes, minimum duration of information storage, openness and transparency of privacy policies, and informed consent. These two models for using big data in the fight against the pandemic in China and Singapore suggest that data governance needs to reconcile public interests and individual rights, and should balance governance efficiency and data ethics.DOWNLOAD HISTORY | This article has been downloaded 69 times in Digital Commons before migrating into this platform.


Author(s):  
John Archibald

While DNA sequencing is faster and cheaper than ever before, genome assembly remains a significant challenge. ‘Making sense of genes and genomes’ explores how laboratory and computational methods are used in combination to elucidate the true physical nature of DNA molecules inside living cells, and how genes are identified among the vast quantities of chemical letters making up an organism’s genome. It begins with shotgun sequencing—a method that has stood the test of time in balancing efficiency and accuracy. It then considers the problems and solutions of genome assembly; gene finding with transcriptomics; the BLAST algorithm; how to find where proteins carry out their functions; and genome re-sequencing.


2019 ◽  
Vol 9 (16) ◽  
pp. 3251 ◽  
Author(s):  
Runze Wu ◽  
Haobo Guo ◽  
Liangrui Tang ◽  
Bing Fan

Recent progress in wireless charging technologies has greatly promoted the development of rechargeable wireless sensor networks (RWSN). The network lifetime of RWSN can be commonly extended through routing strategy and wireless charging technology. However, the node accepts the relay request of its neighbor unconditionally, and it cannot remove its overload on its own in a timely manner in traditional routing strategies. The energy balancing efficiency of the network may be limited by this passive mechanism, which poses a great challenge to obtaining optimal joint efficiency of routing and charging strategies. In this paper, we propose an autonomous load regulation mechanism-based energy balanced routing algorithm (ALRMR) for RWSN. In addition to an efficient framework of joint wireless energy transfer and multi-hop routing where the routing strategy is adapted to the charging scheme, an innovative load regulation mechanism is proposed. Under this mechanism, each node can actively adjust its own load by controlling its relay radius. The simulation demonstrates the advantages of our algorithm for energy balance efficiency and improving the network lifetime through the charging scheme and the innovative mechanism.


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