Simultaneous Identification of Number, Location, and Release History of Groundwater Contamination Sources

In previous studies, a 0-1 mixed integer nonlinear programming optimization model (0-1MINLPOM) could only identify the location and release intensity for groundwater contamination sources (GCSs), and the location of each GCS was regarded as a 0-1 integer variable, selected from several locations determined in advance. However, in actual situations, the locations usually cannot be accurately isolated to a few GCSs and the number of GCSs is often unknown, so 0-1MINLPOM was improved in this study. Based on the estimation that there is a maximum of three GCSs in the study area, an improved 0-1 MINLPOM was established to simultaneously identify the number of GCSs (treated as 0-1 integer variable), the location (treated as integer variable) and release history of GCS (treated as continuous variables). The simulation model was constructed as an equality constraint embedded improved 0-1 MINLPOM. In the improved 0-1 MINLPOM solution process, repeatedly calling the simulation model would have incurred a massive computational load and taken a long time. Thus, a surrogate model based on kriging and extreme learning machine (ELM) was established respectively for the simulation model to avoid this shortcoming. The results show that the accuracy of the kriging surrogate model (Krig-SM) was higher compared with the ELM surrogate model (ELM-SM). The improved 0-1 MINLPOM could identify the number, location, and release history of GCSs simultaneously. The accuracy of identifying the number of GCSs was 100%, and the accuracies of identifying the locations and release history were above 91.67% and 90.14%, respectively.

Data-driven prognosis for COVID-19 patients based on symptoms and age

In this article, we develop an algorithm and a computational code to extract, analyze and compress the relevant information from the publicly available database of Canadian COVID-19 patients. We digitize the symptoms, that is, we assign a label/code as an integer variable for all possible combinations of various symptoms. We introduce a digital code for individual patient and divide all patients into a myriad of groups based on symptoms and age. In addition, we develop an electronic application (app) that allows for a rapid digital prognosis of COVID-19 patients, and provides individual patient prognosis on chance of recovery, average recovery period, etc. using the information, extracted from the database. This tool is aimed to assist health specialists in their decision regarding COVID-19 patients, based on symptoms and age of the patient. This novel approach can be used to develop similar applications for other diseases.

Dining Philosophers Theory and Concept in Operating System Scheduling

This research describes how to avoid deadlock condition in dining philosophers problem. It is the undesirable condition of concurrent systems. It is marked as in a circular waiting state. At first, most people wear concepts simple synchronization is supported by the hardware, such as user or user interrupt routines that may have been implemented by hardware. In 1967, Dijkstra proposed a concept wearer an integer variable to count the number of processes that are active or who are inactive. This type of variable is called semaphore. The mostly semaphore also be used to synchronize the communication between devices in the device. In this journal, semaphore used to solve the problem of synchronizing dining philosophers problem. Dining itself is a situation where five philosophers are sitting at the dinner table to eat spaghetti, every philosopher is given a plate of spaghetti and one chopstick to eat spaghetti the two chopsticks are needed to resolve the issue semaphore variable is then applied to each chopstick chopsticks that can be shared all the other philosopher. This paper presents the efficient distributed deadlock avoidance scheme using lock and release method that prevents other thread in the chain to make race condition.

An Optimization Design Method of Gear Transmission

For solving the continuous and integer variable optimization problems in gear transmission, this article to establish a gear transmission optimization mathematical model, study the influence of modulus, tooth width, helix angle and tooth number on objective function by genetic algorithm, and the digit results is well.

Optimal Policies for a Finite-Horizon Production Inventory Model

This paper is concerned with the problem of finding the optimal production schedule for an inventory model with time-varying demand and deteriorating items over a finite planning horizon. This problem is formulated as a mixed-integer nonlinear program with one integer variable. The optimal schedule is shown to exist uniquely under some technical conditions. It is also shown that the objective function of the nonlinear obtained from fixing the integrality constraint is convex as a function of the integer variable. This in turn leads to a simple procedure for finding the optimal production plan.