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Meet the bus driver = Te presento a los conductores de autobús
Easy-to-follow text, presented in both English and standard Latin American Spanish, introduces beginning readers to a variety of bus drivers, and a helpful picture glossary is included to strengthen vocabulary skills.
Book
Numerical observability method for optimal phasor measurement units placement using recursive Tabu search method
Phasor measurement units (PMUs) are essential tools for monitoring, protection and control of power systems. The optimal PMU placement (OPP) problem refers to the determination of the minimal number of PMUs and their corresponding locations in order to achieve full network observability. This paper introduces a recursive Tabu search (RTS) method to solve the OPP problem. More specifically, the traditional Tabu search (TS) metaheuristic algorithm is executed multiple times, while in the initialisation of each TS the best solution found from all previous executions is used. The proposed RTS is found to be the best among three alternative TS initialisation schemes, in regard to the impact on the success rate of the algorithm. A numerical method is proposed for checking network observability, unlike most existing metaheuristic OPP methods, which are based on topological observability methods. The proposed RTS method is tested on the IEEE 14, 30, 57 and 118-bus test systems, on the New England 39-bus test system and on the 2383-bus power system. The obtained results are compared with other reported PMU placement methods. The simulation results show that the proposed RTS method finds the minimum number of PMUs, unlike earlier methods which may find either the same or even higher number of PMUs.
Journal Article
On a bus
Introduces bus travel, including the parts of a bus, the different types, and how they help people travel from place to place.
Book
Bus drivers
Introduces the work of the bus driver, who helps people by taking them where they want to go.
Book
Revisiting the power flow problem based on a mixed complementarity formulation approach
A novel optimisation-based model of the power flow (PF) problem is proposed using complementarity conditions to properly represent generator bus voltage controls, including reactive power limits and voltage recovery processes. This model is then used to prove that the Newton–Raphson (NR) solution method for solving the PF problem is basically a step of the generalised reduced gradient algorithm applied to the proposed optimisation problem. To test the accuracy, flexibility and the numerical robustness of the proposed model, the IEEE 14-bus, 30-bus, 57-bus, 118-bus and 300-bus test systems and large real 1211-bus and 2975-bus systems are used, benchmarking the results of the proposed PF model against the standard NR method. It is shown that the proposed model yields adequate solutions, even in the case when the NR method fails to converge.
Journal Article
Are we there, Yeti?
\"When Yeti, the school bus driver, takes the class on a surprise trip, everyone wants to know: 'Are we there, Yeti?'\"-- Provided by publisher.
Book
Models of Bus Queueing at Curbside Stops
We consider curbside bus stops of the kind that serve multiple bus routes and that are isolated from the effects of traffic signals and other stops. A Markov chain embedded in the bus queueing process is used to develop steady-state queueing models of this stop type, as illustrated by two special cases. The models estimate the maximum number of buses that can arrive at and serve a stop and still satisfy a specified target of average bus delay. These models can be used to determine, for example, a stop’s suitable number of bus berths, given the bus demand and the specified delay target. The solutions for the two cases are used to derive a closed-form, parsimonious approximation model for general cases. This approximation matches simulations reasonably well for many conditions that arise in real settings; differences of less than 10% were common. Our results unveil how suitable choices for the number of bus berths are influenced by both the variation in the time that buses spend serving passengers at the stop and the specified delay target. The models further show why the proxy measure commonly used for the delay target in previous bus stop studies is a poor one.
Journal Article
Dog on his bus
Dog loves being a bus driver as he diligently drops off animal passengers at their stops.
Book
An Enhanced Transportation System for People of Determination
Visually Impaired Persons (VIPs) have difficulty in recognizing vehicles used for navigation. Additionally, they may not be able to identify the bus to their desired destination. However, the bus bay in which the designated bus stops has not been analyzed in the existing literature. Thus, a guidance system for VIPs that identifies the correct bus for transportation is presented in this paper. Initially, speech data indicating the VIP’s destination are pre-processed and converted to text. Next, utilizing the Arctan Gradient-activated Recurrent Neural Network (ArcGRNN) model, the number of bays at the location is detected with the help of a Global Positioning System (GPS), input text, and bay location details. Then, the optimal bay is chosen from the detected bays by utilizing the Experienced Perturbed Bacteria Foraging Triangular Optimization Algorithm (EPBFTOA), and an image of the selected bay is captured and pre-processed. Next, the bus is identified utilizing a You Only Look Once (YOLO) series model. Utilizing the Sub-pixel Shuffling Convoluted Encoder–ArcGRNN Decoder (SSCEAD) framework, the text is detected and segmented for the buses identified in the image. From the segmented output, the text is extracted, based on the destination and route of the bus. Finally, regarding the similarity value with respect to the VIP’s destination, a decision is made utilizing the Multi-characteristic Non-linear S-Curve-Fuzzy Rule (MNC-FR). This decision informs the bus conductor about the VIP, such that the bus can be stopped appropriately to pick them up. During testing, the proposed system selected the optimal bay in 247,891 ms, which led to deciding the bus stop for the VIP with a fuzzification time of 34,197 ms. Thus, the proposed model exhibits superior performance over those utilized in prevailing works.
Journal Article