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.

Efficient automatic scheduling of imaging and vision pipelines for the GPU

We present a new algorithm to quickly generate high-performance GPU implementations of complex imaging and vision pipelines, directly from high-level Halide algorithm code. It is fully automatic, requiring no schedule templates or hand-optimized kernels. We address the scalability challenge of extending search-based automatic scheduling to map large real-world programs to the deep hierarchies of memory and parallelism on GPU architectures in reasonable compile time. We achieve this using (1) a two-phase search algorithm that first ‘freezes’ decisions for the lowest cost sections of a program, allowing relatively more time to be spent on the important stages, (2) a hierarchical sampling strategy that groups schedules based on their structural similarity, then samples representatives to be evaluated, allowing us to explore a large space with few samples, and (3) memoization of repeated partial schedules, amortizing their cost over all their occurrences. We guide the process with an efficient cost model combining machine learning, program analysis, and GPU architecture knowledge. We evaluate our method’s performance on a diverse suite of real-world imaging and vision pipelines. Our scalability optimizations lead to average compile time speedups of 49x (up to 530x). We find schedules that are on average 1.7x faster than existing automatic solutions (up to 5x), and competitive with what the best human experts were able to achieve in an active effort to beat our automatic results.

Automatic Scheduling Tool for Balloon-Borne Planetary Optical Remote Sensing

The balloon-borne Planetary Atmosphere Spectroscopic Telescope (PAST), China’s first planetary optical remote-sensing project, will be launched for testing and conducting scientific flights during 2021 and 2022. Images of the planetary atmosphere and plasma in ultraviolet and visible wavelengths will be used to investigate the diversity of the planetary space environment in the solar system and their different drivers. Because simultaneous observation of multiple target planets in the solar system is possible, effective observation scheduling is critical to acquire high scientific merit spectroscopic imaging data. Herein, we demonstrate an automatic scheduling tool (AST) to aid the planning of observation schedules. The AST is primarily based on a planetary ephemeris and is realized on the basis of the geometrical information and optical requirements of the telescope. The temporal variations of the planetary reference frames can also be obtained to assist in the positioning and data processing of the telescope. As a part of the Chinese deep-space exploration plan, several ground-based planetary optical telescopes will be constructed in China in the future. With the use of the proposed AST, such telescopes can achieve maximum efficiency.

A Real-Time, Automatic, and Dynamic Scheduling and Control System for PET Patients Based on Wearable Sensors

Positron emission tomography (PET) is one of the commonly used scanning techniques. Medical staff manually calculate the estimated scan time for each PET device. However, the number of PET scanning devices is small, the number of patients is large, and there are many changes including rescanning requirements, which makes it very error-prone, puts pressure on staff, and causes trouble for patients and their families. Although previous studies proposed algorithms for specific inspections, there is currently no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with wearable sensors. The system can automatically schedule, estimate and instantly update the time of various tasks, and automatically allocate beds and announce schedule information in real time. We implemented this system, collected time data of 200 actual patients, and put these data into the implementation program for simulation and comparison. The average time difference between manual and automatic scheduling was 7.32 min, and it could reduce the average examination time of 82% of patients by 6.14 ± 4.61 min. This convinces us the system is correct and can improve time efficiency, while avoiding human error and staff pressure, and avoiding trouble for patients and their families.

PEMBERI MAKAN OTOMATIS PADA KUCING MENGGUNAKAN RASPBERRY PI BERBASIS ANDROID

Keep a pet at home takes time and effort. For people who have very dense flurry of activity certainly keep a pet such as a cat would be very hard to do. A Raspberry Pi microcontroller is designed for the purpose of automatic feeding so it is easy to use. The workings of the tool are automatic scheduling using an Android-based smartphone so that the servo motor will open and close so that the cat food is taken out into the food container that has been provided. By using an Android-based smartphone, the feeding schedule can be set by the hour for each funnel. Equipped with a buzzer as a reminder of cat owners if the available food stock is low and must be immediately refilled. The programming language used is Python language. Based on testing and performance of "Automatic Cat Feeding Using Raspberry Pi Android Based" has shown results in accordance with the design that is able to open and close the funnel that fills the cat food container with a servo motor automatically by setting a predetermined time.

A Real-time Approach for Dynamic Scheduling Pet Activities in a Hospital

Background: At present, medical personnel use manual scheduling methods to calculate usage times of PET devices, hospital beds, operating rooms, and other treatment spaces. However, as patient treatment and recovery times are unequal and uncertain, arriving times of the scheduled/temporary patients are unexpected, examination items, beds requirements, and drugs waiting times are different, and scan-again requirements are unexpected. Manual scheduling arrangements are easy to make mistakes and put pressure on employees. With changing scheduling arrangements, it is difficult to announce the estimated time to patients and their families in real time. As a result, family members keep asking medical staff about various situations and waiting time. This makes the process unstable and exhausts the medical staff. Although previous researches proposed algorithms for specific inspections to solve the equipment resource allocation problems and calculate outpatient visit time for outpatient clinics, there is no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with Bluetooth Beacon positioning. Results: This system can automatically schedule, estimate, and instantly update the start and end time of various tasks of PET patients during examinations, and automatically allocate beds and real-time announce schedule information, allowing the schedule being automated, instant and almost optimized. Moreover, this system promptly reminds medical staffs in each area. This can greatly reduce the work of medical staff, avoid human error, improve the safety of drugs, and provide medical staff, patients and family members to view the inspection progress and estimated waiting time in real time, reducing the number of patients and family members to query medical staff. We implemented this system in an application for the Android system to prove the feasibility of the system. We also collected time data of 200 actual patients for 2 weeks in the Department of Nuclear Medicine of Chang Gung Memorial Hospital, Linkou, and put these data into the implementation program for simulation and comparison. It was found that the average time difference between manual and automatic scheduling was 7.32 minutes, and it could reduce the average examination time of 82% of patients by 6.14 minutes, proving the system's correctness and efficiency. To our knowledge, this paper is the first to propose a real-time automatic scheduling and control system for PET patients.

Weaving scheduling based on an improved ant colony algorithm

Weaving enterprises are faced with problems of small batches and many varieties, which leads to difficulties in manual scheduling during the production process, resulting in more delays in delivery. Therefore, an automatic scheduling method for the weaving process is proposed in this paper. Firstly, a weaving production scheduling model is established based on the conditions and requirements during actual production. By introducing flexible model constraints, the applicability of the model has been greatly expanded. Then, an improved ant colony algorithm is proposed to solve the model. To address the problem of the traditional ant colony algorithm that the optimizing process usually traps into local optimum, the proposed algorithm adopts an iterative threshold and the maximum and minimum ant colony system. In addition, the initial path pheromone distribution is formed according to the urgency of the order to balance each objective. Finally, the simulation experiments confirm that the proposed method achieves superior performance compared with manual scheduling and other automatic methods. The proposed method shows a certain guiding significance for weaving scheduling in practice.