Efficient collective search by BRT algorithm using fast rising threshold agent

2021 ◽  
pp. 102-108
Author(s):  
Phung Nhu Hai
Keyword(s):  
Search Time ◽  
Computer Experiments ◽  
Distributed Robots ◽  
Time Required

The BRT algorithm is a method for the best-of-n problem that allows a group of distributed robots to find out the most appropriate collective option among many alternatives. Computer experiments show that the time required for finding out the best option is proportional to the number of options. In this paper, we aim to shorten this search time by introducing a few agents whose threshold increases faster than the normal one to achieve higher scalability of the BRT algorithm. The results show that the search time is reduced, and the variance is improved, especially under challenging problems where robots are required to make decisions out of a large number of options.

Network Model of Urban Taxi Services: Improved Algorithm

1998 ◽  
Vol 1623 (1) ◽  
pp. 27-30 ◽  
Author(s):  
S. C. Wong ◽  
Hai Yang
Keyword(s):  
Mathematical Model ◽  
Logit Model ◽  
Road Network ◽  
Search Time ◽  
Random Variable ◽  
Taxi Driver ◽  
Movement Model ◽  
Transportation Services ◽  
Type Distribution ◽  
Time Required

A mathematical model is proposed to describe how vacant and occupied taxis will cruise in a road network to search for customers and provide transportation services. The model assumes that a taxi driver, once having picked up a customer, will move to the customer’s destination by the shortest path; and that a taxi driver, once having dropped a customer, will try to minimize individual expected search time required to meet the next customer. The probability that a vacant taxi meets a customer in a particular zone is specified by a logit model by assuming that the expected search time in each zone is an identically distributed random variable due to variations in perceptions and the random arrival of customers. The whole movement of all empty and occupied taxis is formulated as an optimization model, from which a gravity-type distribution of empty taxis is derived. Consequently, the taxi movement model can be solved efficiently by the established iterative balancing method and can be incorporated into any standard transportation planning packages.

Search Performance as a Function of Peripheral Acuity

1965 ◽  
Vol 7 (6) ◽  
pp. 527-537 ◽  
Author(s):  
Dorothy M. Johnston
Keyword(s):  
Visual Field ◽  
Visual Fields ◽  
Search Time ◽  
Apparent Size ◽  
Search Performance ◽  
Small Fields ◽  
Time Required ◽  
The Relationship ◽  
And Training

This study was made to investigate the relationship between the size of visual fields of observers and time required to locate targets on static displays. The findings, which indicate that people with large visual fields can find targets more rapidly than observers with small fields, have practical selection and training application. Equations are presented which can be used to determine search time that can be expected as a function of the size of the visual field of the observer and the apparent size of the area being searched.

A Novel Energy Efficient and SLA-Aware Approach for Cloud Resource Management

2019 ◽  
Vol 11 (2) ◽  
pp. 63-84 ◽  
Author(s):  
Madhukar Shelar ◽  
Shirish Sane ◽  
Vilas Kharat
Keyword(s):  
Empirical Evaluation ◽  
Search Time ◽  
Server Virtualization ◽  
Cloud Resource Management ◽  
Efficient Management ◽  
Sla Violation ◽  
Novel Approach ◽  
Cloud Resource ◽  
Time Required ◽  
Selection Of

Server virtualization is a well-known technique for virtual machine (VM) placement and consolidation and has been studied extensively by several researchers. This article presents a novel approach called aiCloud that advocates segmentation of hosts or physical machines (PMs) into four different classes that facilitates quick selection of PMs to reduce the time required to search host machines, called host search time (HST). The framework also introduces VM_Acceptance_State, a condition that avoids host overloading, which leads to significant reduction of SLA time per active host (SLATAH) that in turn reduces SLA violation (SLAV). The performance of aiCloud has been compared with other approaches using standard workload traces. Empirical evaluation presented shows that aiCloud has least HST and outperforms other approaches in terms of SLA violations and ESV (Energy and SLA Violation) and therefore may be an attractive strategy for efficient management of cloud resources.

scholarly journals Global MPPT Based on Machine-Learning for PV Arrays Operating under Partial Shading Conditions

2020 ◽  
Vol 10 (2) ◽  
pp. 700 ◽  
Author(s):  
Christos Kalogerakis ◽  
Eftichis Koutroulis ◽  
Michail G. Lagoudakis
Keyword(s):  
Machine Learning ◽  
Search Time ◽  
Convergence Time ◽  
Global Maximum ◽  
Pv System ◽  
Partial Shading ◽  
Pv Systems ◽  
Pv Array ◽  
Time Required ◽  
Global Mppt

A global maximum power point tracking (GMPPT) process must be applied for detecting the position of the GMPP operating point in the minimum possible search time in order to maximize the energy production of a photovoltaic (PV) system when its PV array operates under partial shading conditions. This paper presents a novel GMPPT method which is based on the application of a machine-learning algorithm. Compared to the existing GMPPT techniques, the proposed method has the advantage that it does not require knowledge of the operational characteristics of the PV modules comprising the PV system, or the PV array structure. Additionally, due to its inherent learning capability, it is capable of detecting the GMPP in significantly fewer search steps and, therefore, it is suitable for employment in PV applications, where the shading pattern may change quickly (e.g., wearable PV systems, building-integrated PV systems etc.). The numerical results presented in the paper demonstrate that the time required for detecting the global MPP, when unknown partial shading patterns are applied, is reduced by 80.5%–98.3% by executing the proposed Q-learning-based GMPPT algorithm, compared to the convergence time required by a GMPPT process based on the particle swarm optimization (PSO) algorithm.

scholarly journals Query Optimization in a Blockchain-Based Land Registry Management System

2021 ◽  
Vol 26 (1) ◽  
pp. 13-21
Author(s):  
Amrendra Singh Yadav ◽  
Dharmender Singh Kushwaha
Keyword(s):  
Network Architecture ◽  
Hash Table ◽  
Search Time ◽  
Consensus Algorithm ◽  
Decentralized System ◽  
Blockchain Technology ◽  
Time Required ◽  
Technical Discussion ◽  
Search Approach ◽  
Land Records

Digitization of land records is not sufficient for preventing fraud cases, time delay, and brokers' involvement. Distributed Ledger Technology (DLT) is used for making this digitized record more secure and process it in a decentralized way, and reduces paperwork in selling and buying of land. Blockchain technology has come to the fore in recent years and is the center of technical discussion, with intuitive applications driven by its network architecture. It has been firmly established as one of the most important emerging technologies. This article aims to implement a land registry mechanism using blockchain technology and optimize searching of land records in blockchain. Interplanetary File System (IPFS) provides an infrastructure that offers a precise portrayal of all the members' roles. The application interacts with the blockchain network, which is built using IPFS. This paper will help in providing a secure and decentralized system for the land registry process. The proposed consensus algorithm MRRCM achieves less time required to generated a block on an average by 3.06% round-robin and 96.48% PoW approach. The proposed modified hash table search approach requires less time to search the blockchain's land record block than the extensive liner searches and hash table search approach. A search for a land record in the blockchain reduces the search time on an average by 59.5% compared to the traditional extensive liner search approach and by 18.68% as compared with the hash table search approach.

The Critical Point Drying Method Applied to Scanning Electron Microscopy of L-929 Cells

1970 ◽  
Vol 28 ◽  
pp. 278-279
Author(s):  
Charles TurnbiLL ◽  
Delbert E. Philpott
Keyword(s):  
Electron Microscopy ◽  
Carbon Dioxide ◽  
Surface Tension ◽  
Critical Point ◽  
Freeze Drying ◽  
Attractive Alternative ◽  
Crystal Formation ◽  
Critical Point Drying ◽  
Time Required ◽  
Scanning Electron

The advent of the scanning electron microscope (SCEM) has renewed interest in preparing specimens by avoiding the forces of surface tension. The present method of freeze drying by Boyde and Barger (1969) and Small and Marszalek (1969) does prevent surface tension but ice crystal formation and time required for pumping out the specimen to dryness has discouraged us. We believe an attractive alternative to freeze drying is the critical point method originated by Anderson (1951; for electron microscopy. He avoided surface tension effects during drying by first exchanging the specimen water with alcohol, amy L acetate and then with carbon dioxide. He then selected a specific temperature (36.5°C) and pressure (72 Atm.) at which carbon dioxide would pass from the liquid to the gaseous phase without the effect of surface tension This combination of temperature and, pressure is known as the "critical point" of the Liquid.

Search mode for rapid detection of virus particles

1991 ◽  
Vol 49 ◽  
pp. 286-287
Author(s):  
O. E. Bradfute
Keyword(s):  
Electron Microscopy ◽  
Rapid Detection ◽  
Plant Virus ◽  
Low Dose ◽  
Search Mode ◽  
Virus Diseases ◽  
Virus Particles ◽  
Focus Image ◽  
Time Required ◽  
Rapid Switching

Electron microscopy is frequently used in preliminary diagnosis of plant virus diseases by surveying negatively stained preparations of crude extracts of leaf samples. A major limitation of this method is the time required to survey grids when the concentration of virus particles (VPs) is low. A rapid survey of grids for VPs is reported here; the method employs a low magnification, out-of-focus Search Mode similar to that used for low dose electron microscopy of radiation sensitive specimens. A higher magnification, in-focus Confirm Mode is used to photograph or confirm the detection of VPs. Setting up the Search Mode by obtaining an out-of-focus image of the specimen in diffraction (K. H. Downing and W. Chiu, private communications) and pre-aligning the image in Search Mode with the image in Confirm Mode facilitates rapid switching between Modes.

Microwaves: Application in Electron Microscopy

1990 ◽  
Vol 48 (3) ◽  
pp. 140-141
Author(s):  
Anthony S-Y Leong ◽  
David W Gove
Keyword(s):  
Electron Microscopy ◽  
Light Microscopy ◽  
Chemical Reactions ◽  
Electromagnetic Waves ◽  
Tissue Fixation ◽  
Primary Method ◽  
Dipolar Molecules ◽  
Wide Range ◽  
Time Required ◽  
Cryostat Sections

Microwaves (MW) are electromagnetic waves which are commonly generated at a frequency of 2.45 GHz. When dipolar molecules such as water, the polar side chains of proteins and other molecules with an uneven distribution of electrical charge are exposed to such non-ionizing radiation, they oscillate through 180° at a rate of 2,450 million cycles/s. This rapid kinetic movement results in accelerated chemical reactions and produces instantaneous heat. MWs have recently been applied to a wide range of procedures for light microscopy. MWs generated by domestic ovens have been used as a primary method of tissue fixation, it has been applied to the various stages of tissue processing as well as to a wide variety of staining procedures. This use of MWs has not only resulted in drastic reductions in the time required for tissue fixation, processing and staining, but have also produced better cytologic images in cryostat sections, and more importantly, have resulted in better preservation of cellular antigens.

Clinical Update: Functional Capacity Evaluations—An Update

1999 ◽  
Vol 4 (5) ◽  
pp. 4-7 ◽  
Author(s):  
Laura Welch
Keyword(s):  
Job Performance ◽  
Functional Capacity ◽  
Injury Risk ◽  
Disability Evaluation ◽  
Time Period ◽  
Submaximal Effort ◽  
Lack Of Sleep ◽  
Overall Performance ◽  
Time Required ◽  
Specific Limitation

Abstract Functional capacity evaluations (FCEs) have become an important component of disability evaluation during the past 10 years to assess an individual's ability to perform the essential or specific functions of a job, both preplacement and during rehabilitation. Evaluating both job performance and physical ability is a complex assessment, and some practitioners are not yet certain that an FCE can achieve these goals. An FCE is useful only if it predicts job performance, and factors that should be assessed include overall performance; consistency of performance across similar areas of the FCE; consistency between observed behaviors during the FCE and limitations or abilities reported by the worker; objective changes (eg, blood pressure and pulse) that are appropriate relative to performance; external factors (illness, lack of sleep, or medication); and a coefficient of variation that can be measured and assessed. FCEs can identify specific movement patterns or weaknesses; measure improvement during rehabilitation; identify a specific limitation that is amenable to accommodation; and identify a worker who appears to be providing a submaximal effort. FCEs are less reliable at predicting injury risk; they cannot tell us much about endurance over a time period longer than the time required for the FCE; and the FCE may measure simple muscular functions when the job requires more complex ones.

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