scholarly journals Link-Based Signalized Arterial Progression Optimization with Practical Travel Speed

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Wu Xianyu ◽  
Hu Peifeng ◽  
Yuan Zhenzhou
Keyword(s):  
Optimization Algorithm ◽  
Travel Speed ◽  
Maximum Amount ◽  
Fine Tuning ◽  
Signal Timing ◽  
Additional Measure ◽  
Bandwidth Optimization ◽  
Initial Signal ◽  
Pass Through

Bandwidth is defined as the maximum amount of green time for a designated movement as it passes through an arterial. In most previous studies, bandwidth has been referred to arterial bandwidth. In practice, a balance between link bandwidth and arterial bandwidth has proven to be important in optimizing coordinated signal timing plans, because not all drivers need to pass through all the intersections on an arterial. This study proposes an algorithm on how to obtain an optimal coordinated signal timing plan with both optimal link bandwidth and optimal arterial bandwidth considering practical vehicles’ speed. The weighted link bandwidth attainability is introduced as an additional measure of effectiveness for assessing the optimization results. The link bandwidth optimization is built based on the improvement of Messer’s algorithm about bandwidth optimization. The arterial bandwidth optimization algorithm takes into consideration the weighted link bandwidth attainability while selecting phase sequences. The proposed algorithm is demonstrated in a case study, and many improvements are archived when a balanced consideration is given to both link bandwidth and arterial bandwidth. Fine-tuning of initial signal timing plan is done using practical travel speed. The evaluation results show a rather significant improvement which is achieved.

Modeling and optimizing logistics, information, economic and financial intercluster cooperation using the ant colony optimization algorithm

2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Population Decline ◽  
Innovation System ◽  
Federal District ◽  
Original Model ◽  
Ant Colony ◽  
Industrial Agglomeration ◽  
Ant Colony Optimization Algorithm

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.

scholarly journals Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Zhe Yang ◽  
Dejan Gjorgjevikj ◽  
Jianyu Long ◽  
Yanyang Zi ◽  
Shaohui Zhang ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Supervised Classification ◽  
Deep Neural Networks ◽  
Activation Function ◽  
Reconstruction Error ◽  
Fine Tuning ◽  
Fault Diagnostics ◽  
Sparse Autoencoder

AbstractSupervised fault diagnosis typically assumes that all the types of machinery failures are known. However, in practice unknown types of defect, i.e., novelties, may occur, whose detection is a challenging task. In this paper, a novel fault diagnostic method is developed for both diagnostics and detection of novelties. To this end, a sparse autoencoder-based multi-head Deep Neural Network (DNN) is presented to jointly learn a shared encoding representation for both unsupervised reconstruction and supervised classification of the monitoring data. The detection of novelties is based on the reconstruction error. Moreover, the computational burden is reduced by directly training the multi-head DNN with rectified linear unit activation function, instead of performing the pre-training and fine-tuning phases required for classical DNNs. The addressed method is applied to a benchmark bearing case study and to experimental data acquired from a delta 3D printer. The results show that its performance is satisfactory both in detection of novelties and fault diagnosis, outperforming other state-of-the-art methods. This research proposes a novel fault diagnostics method which can not only diagnose the known type of defect, but also detect unknown types of defects.

scholarly journals Comparative Life Cycle Impact Assessment between the Productions of Zinc from Conventional Concentrates Versus Waelz Oxides Obtained from Slags

2021 ◽  
Vol 13 (2) ◽  
pp. 580
Author(s):  
Voicu-Teodor Muica ◽  
Alexandru Ozunu ◽  
Zoltàn Török
Keyword(s):  
Life Cycle ◽  
Impact Assessment ◽  
Life Cycle Impact Assessment ◽  
Fine Tuning ◽  
Process Data ◽  
Medicinal Uses ◽  
Zinc Metal ◽  
Real Process ◽  
Life Cycle Impact

(1) Background: The importance of Zinc in today’s world can hardly be exaggerated—from anticorrosion properties, to its durability, aesthetic, and even medicinal uses—zinc is ever-present in our daily lives ever since its discovery in ancient times. The natural, essential, durable, and recyclable features of zinc make it a prized material with uses in many applications across a wide array of fields. The purpose of this study was to compare two life cycle impact assessments of zinc production by using two different main raw materials: (A) zinc concentrates (sulfide ore) and (B) Waelz oxides (obtained through recycling existing imperial smelting process furnace slags). The Waelz oxide scenario was based on a case study regarding the existing slag deposit located in Copsa Mica town, Sibiu county, Romania. (2) Methods: consequential life cycle impact assessment methods were applied to each built system, with real process data obtained from the case study enterprise. (3) Results: Overall, the use of slags in the Waelz kiln to produce zinc oxides for use in the production of zinc metal is beneficial to the environment in some areas (acidification, water, and terrestrial eutrophication), whereas in other areas it has a slightly larger impact (climate change, photochemical ozone formation, and ozone depletion). (4) Conclusions: The use of slags (considered a waste) is encouraged to produce zinc metal, where available. The results are not absolute, suggesting the further need for fine-tuning the input data and other process parameters.

On the phase detrending to disentangle refraction and diffraction on GNSS signals: a case study over Antarctica

2021 ◽  
Author(s):  
Luca Spogli ◽  
Hossein Ghobadi ◽  
Antonio Cicone ◽  
Lucilla Alfonsi ◽  
Claudio Cesaroni ◽  
...  
Keyword(s):  
Single Case ◽  
Cutoff Frequency ◽  
Satellite System ◽  
Fine Tuning ◽  
Scintillation Index ◽  
Ionospheric Scintillation ◽  
Iterative Filtering ◽  
Global Navigation Satellite ◽  
Value Changes

<p>We investigate the reliability of the phase scintillation index determined by receiving Global Navigation Satellite System (GNSS) signals at ground in the high-latitudes. To the scope, we report about the capabilities of recently introduced detrending scheme based on the signal decomposition provided by the Fast Iterative Filtering (FIF) technique. This detrending scheme enables a fine tuning of the cutoff frequency for phase detrending used in the phase scintillation index definition, aimed at disentangling diffraction and refraction effects. On a single case study based on GPS and Galileo data taken by a GNSS Ionospheric Scintillation Monitor Receiver (ISMR) in Concordia Station (Antarctica), we show how the FIF-based detrending allows deriving adaptive cutoff frequencies, whose value changes minute-by-minute. They are found to range between 0.4 Hz and 1.2 Hz. This allows better accounting for diffractive effects in phase scintillation index calculation and also showing the limitations on the use of such index, being still widely used in the community, both to characterize the features of ionospheric irregularities and to adopt mitigation solutions.</p>

scholarly journals Hidden Technologies of the Great Siberian Migration: Newcomers Breaking Into the Old Residents Community (Kharlova Village Conflict of 1893)

2018 ◽  
Vol 19 (4) ◽  
pp. 479-513 ◽  
Author(s):  
Alexey Kirillov ◽  
Anastasiya Karavayeva
Keyword(s):  
Case Study Method ◽  
Narrow Channels ◽  
Chain Migration ◽  
Mass Migration ◽  
Tide Height ◽  
Voronezh Region ◽  
To Come ◽  
Pass Through ◽  
To Receive

Peasant migration to Siberia in the second half of the 19th - the first half of the 20th century was a chronological parallel to the mass migration of Europeans across the Atlantics. One of the issues of the Great Siberian migration is the reasons for which it did not reach the proportions sufficient to defuse the land crisis in European Russia. The authors of the article are trying to solve this problem by studying the conflicts between the old Siberian residents and the migrants. By applying the case study method, the authors draw attention to one particular case, a clash in Kharlova village (Altai District of Cabinet of His Majesty Emperor) in 1893. It is one of the few conflicts described in detail. The mechanism of the conflict origination is discovered by confronting mutually exclusive statements of both parties and reconstructing hidden facts. It is proved that the resettlement of the Voronezh region peasants to the Altai village was a bright example of chain migration. New migrants would come on the advice of their predecessors. Thus, a group of the new old residents sympathetic to the newcomers was formed among the peasants belonging to the Kharlova community. The immediate reason for the conflict was an attempt of a big group of migrants to get a right to live in Kharlova village by cheating. A delegate of this group obtained the community council permission to come with a couple more of adult peasants and returned next year with six dozen of his compatriots. Though untypical, this method of penetration into an old residents community highlights a common issue: the ground for the conflicts was created by the two peasant groups contradiction of interests. It was important for the newcomers to start new life with the help of those who had already put down roots in Siberia; but the old residents were ready to receive only a small number of new neighbors. The rising tide of peasant migration could not spread evenly over the Siberian expanse; it had to pass through narrow channels of the already inhabited places - which considerably restricted the tide height.

Developing Guidelines for Implementing Transit Signal Priority and Freight Signal Priority Using Simulation Modeling and a Decision Tree Algorithm

2021 ◽  
pp. 036119812110575
Author(s):  
Shahadat Iqbal ◽  
Taraneh Ardalan ◽  
Mohammed Hadi ◽  
Evangelos Kaisar
Keyword(s):  
Decision Tree ◽  
Signal Control ◽  
Signal Timing ◽  
Transit Signal Priority ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
Traffic Demand ◽  
Capacity Ratio ◽  
The Impact

Transit signal priority (TSP) and freight signal priority (FSP) allow transportation agencies to prioritize signal service allocations considering the priority of vehicles and, potentially, decrease the impact signal control has on them. However, there have been no studies to develop guidelines for implementing signal control considering both TSP and FSP. This paper reports on a study conducted to provide such guidelines that employed a literature review, a simulation study, and a decision tree algorithm based on the simulation results. The guideline developed provides recommendations in accordance with the signal timing slack time, the proportion of major to minor street hourly volume, hourly truck volume per lane for the major street, hourly truck volume per lane for the minor street, the proportion of major to minor street hourly truck volume, the proportion of major to minor street hourly bus volume, the volume-to-capacity ratio for the major street, and the volume-to-capacity ratio for the minor street. The guideline developed was validated by implementing it for a case study facility. The validation result showed that the guideline works correctly for both high and low traffic demand.

Study of grasp-energy based optimal distribution of contact forces on a humanoid robotic hand during object grasp

Robotica ◽  
2021 ◽  
pp. 1-26
Author(s):  
Sourajit Mukherjee ◽  
Abhijit Mahapatra ◽  
Amit Kumar ◽  
Avik Chatterjee
Keyword(s):  
Optimization Algorithm ◽  
Degrees Of Freedom ◽  
Simulated Data ◽  
Performance Measure ◽  
Contact Forces ◽  
Contact Model ◽  
Robotic Hand ◽  
Net Energy ◽  
Optimal Distribution

Abstract A novel grasp optimization algorithm for minimizing the net energy utilized by a five-fingered humanoid robotic hand with twenty degrees of freedom for securing a precise grasp is presented in this study. The algorithm utilizes a compliant contact model with a nonlinear spring and damper system to compute the performance measure, called ‘Grasp Energy’. The measure, subject to constraints, has been minimized to obtain locally optimal cartesian trajectories for securing a grasp. A case study is taken to compare the analytical (applying the optimization algorithm) and the simulated data in MSC.Adams $^{^{\circledR}}$ , to prove the efficacy of the proposed formulation.

Jaya Optimization Algorithm Implemented on A New Novel Design of 6-DOF AUV Body: A Case Study

2021 ◽  
Author(s):  
Noorulden Basil ◽  
Hamzah M. Marhoon ◽  
Ahmed R. Ibrahim
Keyword(s):  
Optimization Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Optimization Technique ◽  
Pid Controllers ◽  
The Novel ◽  
Proportional Integral Derivative ◽  
New Novel ◽  
Novel Design ◽  
Optimum Output

Abstract The Novel Jaya Optimization Algorithm (JOA) was utilized in this research to evaluate the efficiency of a new novel design of Autonomous Underwater Vehicle (AUV). The Three Proportional Integral Derivative (PID) controllers were used to obtain the optimum output for the AUV Trajectory, which can be considered as a main side of the research for solving the AUV Performance. The optimization technique has been developed to solving the motion model of the AUV in order to reduce the rotations of trajectory for the AUV 6-DOF Body in the axis’s in x, y and z for the overall positions, velocity... etc., and to execute the optimum output for the dynamic kinematics model based on the Novel Euler-6 DOF AUV Body Equation implemented on MATLAB R2021a Version.

Sparse Autoencoder-Based Multi-Head Deep Neural Networks for Machinery Fault Diagnostics With Novelty Detection

2020 ◽  
Author(s):  
Zhe Yang ◽  
Dejan Gjorgjevikj ◽  
Jian-Yu Long ◽  
Yan-Yang Zi ◽  
Shao-Hui Zhang ◽  
...  
Keyword(s):  
Supervised Classification ◽  
Deep Neural Networks ◽  
State Of The Art ◽  
Novelty Detection ◽  
Activation Function ◽  
Reconstruction Error ◽  
Fine Tuning ◽  
Sparse Autoencoder

Abstract Novelty detection is a challenging task for the machinery fault diagnosis. A novel fault diagnostic method is developed for dealing with not only diagnosing the known type of defect, but also detecting novelties, i.e. the occurrence of new types of defects which have never been recorded. To this end, a sparse autoencoder-based multi-head Deep Neural Network (DNN) is presented to jointly learn a shared encoding representation for both unsupervised reconstruction and supervised classification of the monitoring data. The detection of novelties is based on the reconstruction error. Moreover, the computational burden is reduced by directly training the multi-head DNN with rectified linear unit activation function, instead of performing the pre-training and fine-tuning phases required for classical DNNs. The addressed method is applied to a benchmark bearing case study and to experimental data acquired from a delta 3D printer. The results show that it is able to accurately diagnose known types of defects, as well as to detect unknown defects, outperforming other state-of-the-art methods.

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