Rescheduling of Distributed Manufacturing System with Machine Breakdowns

This study attempts to explore the dynamic scheduling problem from the perspective of operational research optimization. The goal is to propose a rescheduling framework for solving distributed manufacturing systems that consider random machine breakdowns as the production disruption. We establish a mathematical model that can better describe the scheduling of the distributed blocking flowshop. To realize the dynamic scheduling, we adopt an “event-driven” policy and propose a two-stage “predictive-reactive” method consisting of two steps: initial solution pre-generation and rescheduling. In the first stage, a global initial schedule is generated and considers only the deterministic problem, i.e., optimizing the maximum completion time of static distributed blocking flowshop scheduling problems. In the second stage, that is, after the breakdown occurs, the rescheduling mechanism is triggered to seek a new schedule so that both maximum completion time and the stability measure of the system can be optimized. At the breakdown node, the operations of each job are classified and a hybrid rescheduling strategy consisting of “right-shift repair + local reorder” is performed. For local reorder, we designed a discrete memetic algorithm, which embeds the differential evolution concept in its search framework. To test the effectiveness of DMA, comparisons with mainstream algorithms are conducted on instances with different scales. The statistical results show that the ARPDs obtained from DMA are improved by 88%.

On Addressing Heterogeneity in Federated Learning for Autonomous Vehicles Connected to a Drone Orchestrator

In this paper we envision a federated learning (FL) scenario in service of amending the performance of autonomous road vehicles, through a drone traffic monitor (DTM), that also acts as an orchestrator. Expecting non-IID data distribution, we focus on the issue of accelerating the learning of a particular class of critical object (CO), that may harm the nominal operation of an autonomous vehicle. This can be done through proper allocation of the wireless resources for addressing learner and data heterogeneity. Thus, we propose a reactive method for the allocation of wireless resources, that happens dynamically each FL round, and is based on each learner’s contribution to the general model. In addition to this, we explore the use of static methods that remain constant across all rounds. Since we expect partial work from each learner, we use the FedProx FL algorithm, in the task of computer vision. For testing, we construct a non-IID data distribution of the MNIST and FMNIST datasets among four types of learners, in scenarios that represent the quickly changing environment. The results show that proactive measures are effective and versatile at improving system accuracy, and quickly learning the CO class when underrepresented in the network. Furthermore, the experiments show a tradeoff between FedProx intensity and resource allocation efforts. Nonetheless, a well adjusted FedProx local optimizer allows for an even better overall accuracy, particularly when using deeper neural network (NN) implementations.

Obstacle Avoidance in a Three-Dimensional Dynamic Environment Based on Fuzzy Dynamic Windows

This paper presents a real-time path planning approach for controlling the motion of space-based robots. The algorithm can plan three-dimensional trajectories for agents in a complex environment which includes numerous static and dynamic obstacles, path constraints, and/or performance constraints. This approach is extended based on the dynamic window approach (DWA). As the classic reactive method for obstacle avoidance, DWA uses an optimized function to select the best motion command. The original DWA optimization function consists of three weight terms. Changing the weights of these terms will change the behavior of the algorithm. In this paper, to improve the evaluation ability of the optimization function and the robot’s ability to adapt to the environment, a new optimization function is designed and combined with fuzzy logic to adjust the weights of each parameter of the optimization function. Given that DWA has the defect of local minima, which makes the robot hard to escape U-shaped obstacles, a dual dynamic window method and local goals are adopted in this article to help the robot escape local minima. By comparison, the proposed method is superior to traditional DWA and fuzzy DWA (F_DWA) in terms of computational efficiency, smoothness and security.

Andragogy reflection - contemporary specifics of the discipline

Andragogy, as a young discipline, is faced with a number of theories of theory and methodology. The aim of the study was to identify the dominant threads in andragogists' publications and to determine what complexes of problems and thematic issues determine today's specificity of the sub-discipline. In the process of analyzing the content of articles from the area of social sciences published in the pages of andragogical journals, a non-reactive method of document analysis was used. Five analytical andragogical categories were identified and included in the typology developed for the purposes of the study.

PARD: Hybrid Proactive and Reactive Method Eliminating Flow Setup Latency in SDN

Advantages of Software Defined Networking are unquestionable and are widely described in numerous scientific papers, business white papers and press articles. However, to achieve full maturity, crucial impediments to this concept and its shortcomings must be overcame. One of the most important issues regards significant setup latency of a new flow. To address this issue we propose PARD: a hybrid proactive and reactive method to manage flow table entries. Additional advantages of the proposed solution are, among the others, its ability to preserve all capabilities of Software Defined Networking, utilization of multiple flow tables, a possibility to employ fine-grained traffic engineering and, finally, compatibility with existing protocol and hardware design. It is shown that the proposed solution is able to significantly reduce latency of first packets of a new flow, which directly impacts packet loss and perceived throughput. Thus, our solution is expected to enable a wide deployment of Software Defined Networking concept without any need for protocol changes or, what is extremely important, hardware modifications.

Novelty circular neighboring technique using reactive fault tolerance method

The availability of the data in a distributed system can be increase by implementing fault tolerance mechanism in the system. Reactive method in fault tolerance mechanism deals with restarting the failed services, placing redundant copies of data in multiple nodes across network, in other words data replication and migrating the data for recovery. Even if the idea of data replication is solid, the challenge is to choose the right replication technique that able to provide better data availability as well as consistency that involves read and write operations on the redundant copies. Circular Neighboring Replication (CNR) technique exploits neighboring policy in replicating the data items in the system performs well with regards to lower copies needed to maintain the system availability at the highest. In a performance analysis with existing techniques, results show that CNR improves system availability by average 37% by offering only two replicas needed to maintain data availability and consistency. The study demonstrates the possibility of the proposed technique and the potential of deploying in larger and complex environment.

Metal nanoparticles as effective promotors for Maize production

Zero-valent metal nanoparticles (Cu, Fe and Co) were prepared by the reactive method from their oxide with hydrogen. The energy-rich solutions of metal nanoparticles were used for treatment Maize seeds prior to sowing. The treatment significantly improved the germination rate and early growth. Furthermore, both SOD and APX enzyme activity in leaves were improved, and enhanced the metabolism of superoxide, leading to increased drought resistance. The method was applied to the field over three seasons and greatly improved the harvest. In particular, the implementation of Cu particles at 4 mg/kg increased the productivity of the two Maize species more than 20%.

Pengaruh Jumlah Kasus HIV/AIDS dan Cakupan Rumah Sehat terhadap Jumlah Kasus Tuberkulosis di Provinsi Jawa Timur

Tuberculosis is a disease caused by bacterial infection of Mycobacterium tuberculosis that can be transmitted from the patient to the surrounding environment including humans, which attacks the lung organ and other organs in the body. Based on the epidemiological triangle, infectious diseases are caused by 3 factors such as agent factor, host and environment. One of the host factors of Tuberculosis is HIV/AIDS, where many Tuberculosis infections are common in people with HIV/AIDS. From environmental factors causing Tuberculosis disease is a condition of less healthy house. Tuberculosis incidence in East Java Province in 2015 amounted to 44,063 which increased from 2014 that is as much as 42,475. This research was conducted to analyze the influence between HIV/AIDS and healthy house case against Tuberculosis incident in East Java Province. This research is a kind of analytical research using non-reactive method. The research sample used is total population consist of 29 regencies and 9 cities in East Java Province. Technical analysis of the research using multiple linear regression test. The results showed that there was a significant influence between HIV/AIDS cases on Tuberculosis occurrence in East Java (p-value = 0,000), and there was no significant influence between healthy house on Tuberculosis incidence in East Java Province. The conclusion of this study is that there is a significant relationship between HIV/AIDS cases and Tuberculosis cases in East Java Province. The HIV / AIDS and tuberculosis cases in East Java need to be improved by the Provincial Government of East Java such as providing information related to HIV/AIDS and Tuberculosis and screening HIV/AIDS.