Massive Speech Recognition Resource Scheduling System based on Grid Computing

Nowadays, there are too many large-scale speech recognition resources, which makes it difficult to ensure the scheduling speed and accuracy. In order to improve the effect of large-scale speech recognition resource scheduling, a large-scale speech recognition resource scheduling system based on grid computing is designed in this paper. In the hardware part, microprocessor, Ethernet control chip, controller and acquisition card are designed. In the software part of the system, it mainly carries out the retrieval and exchange of information resources, so as to realize the information scheduling of the same type of large-scale speech recognition resources. The experimental results show that the information scheduling time of the designed system is short, up to 2.4min, and the scheduling accuracy is high, up to 90%, in order to provide some help to effectively improve the speed and accuracy of information scheduling.

Research on Combined Electricity and Heating System Scheduling Method Considering Multi-Source Ring Heating Network

Heating network constraint is one of the important factors that affect the scale of electro-thermal coupling scheduling. This paper first establishes an electrothermal coupling scheduling model considering the multi-source ring heating network pipe structure and then proposes a method of simplifying a multi-source cyclic heating network topology approximation. Second, the electrothermal coupling scheduling system is coordinated and solved. Finally, Through the simulation example results, the annular heating network topological approximate equivalent can simplify the model complexity of the original heating network while also retaining the thermal dynamic characteristics of the initial multi-source ring heating network. This study will greatly improve the efficiency of solving the electrothermal coupling system.

Construction Project Planning and Scheduling: A Case of Inlet Separator Fabrication

Project construction activities must be analyzed from the planning stage to the execution stage so that they can be achieved optimally and achieve the best performance point. Project planning relies on a project scheduling system, of course requiring updates and modifications that show the project conditions in real time. The aims of this paper is propose a project scheduling system that can accommodate projects that have large-scale activities by proposing scheduling and risk analysis using Primavera P6 and Primavera risk analysis. A case study was conducted on the construction of an inlet separator fabrication project in Batam, Indonesia. The proposed method aims to calculate the optimal project completion time through automatic scheduling with primavera software. The method demonstrates practical value for project managers in identifying the shortest project duration and estimating the most optimal time duration for carrying out activities. In addition, using automatic scheduling can provide more complex information including successors and predecessors of activities, critical times, estimates of the overall duration of the project.

Automatic Course Scheduling System in Universities Based on Hybrid Genetic-Ant Colony Algorithm

Scheduling is the daily work of the Ministry of Education in Colleges and universities. In the past ten years, the scale of our colleges and universities has expanded rapidly, but the teaching resources are relatively limited. Many schools are facing the problem of insufficient classroom resources and teachers resources. The current way of organizing courses is increasingly difficult to make full use of existing resources to solve the changing needs and inefficiencies, which need to be improved urgently. This paper applies the hybrid Genetic-Ant algorithm to the automatic course scheduling system in Colleges and universities, and uses the cross-function to design and build the automatic course scheduling system in Colleges and universities. And select a college’s course scheduling system from this city for research, and use the Genetic-Ant hybrid algorithm to improve the original system to form a new system, called the original system A, and called the improved new system B, to compare the operation time and system suitability of the two systems. The results show that the fitness of system B is better than that of system A. When the scheduling unit is 100, the fitness of system A is 181, and system B is 203. When the scheduling unit is 400, the fitness of system B is 14 higher than that of system A. When the scheduling unit is 800, the fitness of system B is 64 higher than that of system A. Thus, the hybrid algorithm of genetic ant colony can improve the rationality of the curriculum.

Timetable Scheduling System using Genetic Algorithm for School of Computing (tsuGA)

Current timetable scheduling system in School of Computing(SC), Universiti Teknologi Malaysia(UTM) is done manually which consumes time and human effort. In this project, a Genetic Algorithm (GA) approach is proposed to aid the timetable scheduling process. GA is a heuristic search algorithm which finds the best solution based on current individual characteristics. Using GA and scheduling info such as rooms available and timeslots needed, it is shown that scheduling can be done more efficiently, with less time, effort and errors. As a testbed, a web application is developed to maintain records needed and generate timetables. Introduction of GA helps in generating a timetable automatically based on information such as rooms, subjects, lecturers, student group and timeslot. GA reduces human error and human efforts in the timetable scheduling process.