scholarly journals THE IMPORTANTS OF CLUSTERING IN LOGISTIC SYSTEMS

Author(s):  
Peter Veres

Nowadays, the development of higher efficient processes and procedures is the key for success in industrial environment. The companies have machines, production lines, software and hardware tools with high level principles of efficient working. Example: the Industry 4.0 concept use the machines and methods of the near past, upgrade them, and gave them new purpose, as a more efficient tool. Some of the bases of those tools are not as efficient as which many would think, like in group generating or in other word clustering. Clustering is a very hard process, and it is in almost every decision making in every company’s lives. It is important to sometimes examine its significance and flaws. This paper presents the clustering briefly and shows its errors through an example.

2020 ◽  
Author(s):  
S. Economides ◽  
C.J. Hourdakis ◽  
C. Pafilis ◽  
G. Simantirakis ◽  
P. Tritakis ◽  
...  

This paper concerns an analysis regarding the performance of X-ray equipment as well as the radiological safety in veterinary facilities. Data were collected from 380 X-ray veterinary facilities countrywide during the on-site regulatory inspections carried out by the Greek Atomic Energy Commission. The analysis of the results shows that the majority of the veterinary radiographic systems perform within the acceptable limits; moreover, the design and shielding of X-ray rooms as well as the applied procedures ensure a high level of radiological safety for the practitioners, operators and the members of the public. An issue that requires specific attention in the optimization process for the proper implementation of veterinary radiology practices in terms of radiological safety is the continuous training of the personnel. The above findings and the regulatory experience gained were valuable decision-making elements regarding the type of the regulatory control of veterinary radiology practices in the new radiation protection framework.


2018 ◽  
Vol 9 (01) ◽  
Author(s):  
Parul Gill ◽  
Poonam Malik ◽  
Pankaj Gill

The present study was undertaken to explore the decision making patterns of college girls in relation to clothing and their satisfaction level with these decision making patterns. Thirty under graduate college girls from Panipat city were approached to record their responses regarding decision making in relation to clothing and satisfaction level through a well structured questionnaire. It was found that most of the girls (56.66%) themselves made the decisions about the type of garment (Indian, western or both) they wear and majority of girls (70%) were highly satisfied with this decision making. Parents performed the role of buyers for their college going daughters' garments in most of the cases (63.33%) and the 73.33% girls had high level of satisfaction with this. In most of the cases (60%) the decision about the garment design was made by the girls themselves and they were highly satisfied with it. Keywords: clothing, college, girls, decision making.


Author(s):  
Nataliya Ryvak ◽  
Anna Kernytska

In this paper, digital technologies development was analyzed as the basis for the so-called “fourth industrial revolution” with the potential for the qualitative transformation of the Ukrainian economy based on EU countries’ experience. Industry 4.0 is a new control chain over the entire chain of creating value throughout the product lifecycle. When developing an economic policy, it is important to pay attention to Industry 4.0. It increases productivity, produces new, better, and individualized products, and implements new business models based on “undermining” innovations. A comparative analysis of national initiatives I4.0 with their characteristics according to the main dimensions, including funding, focus, direction, was conducted. Particular attention was paid to considering deterrents to the successful implementation and enforcement of the I4.0 initiative in European countries. The factors of successful implementation of I4.0 initiatives in the EU countries were analyzed. Drawing on the analysis of the European experience of digital transformations in industry and national economies in general, the necessity of critical focus of such transformations in Ukraine was highlighted, and the need for state support of industrial transformation was substantiated. The emphasis was placed on the cooperation development between stakeholders within the implementation of Industry 4.0 – it is necessary to create national and regional 4.0 platforms, following the example of EU countries, which would bring together government institutions, businesses, and academics. The successful positioning of the Ukrainian modern industrial complex on the world markets depends on the high level of the interconnected system providing factors that characterize its development process. Considering the influence of a list of inhibiting factors on implementing the country’s industry accelerated development, a set of measures needed to transform Ukraine’s industry based on European experience was substantiated.


2021 ◽  
pp. 002224372199837
Author(s):  
Walter Herzog ◽  
Johannes D. Hattula ◽  
Darren W. Dahl

This research explores how marketing managers can avoid the so-called false consensus effect—the egocentric tendency to project personal preferences onto consumers. Two pilot studies were conducted to provide evidence for the managerial importance of this research question and to explore how marketing managers attempt to avoid false consensus effects in practice. The results suggest that the debiasing tactic most frequently used by marketers is to suppress their personal preferences when predicting consumer preferences. Four subsequent studies show that, ironically, this debiasing tactic can backfire and increase managers’ susceptibility to the false consensus effect. Specifically, the results suggest that these backfire effects are most likely to occur for managers with a low level of preference certainty. In contrast, the results imply that preference suppression does not backfire but instead decreases false consensus effects for managers with a high level of preference certainty. Finally, the studies explore the mechanism behind these results and show how managers can ultimately avoid false consensus effects—regardless of their level of preference certainty and without risking backfire effects.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2617
Author(s):  
Catalin Dumitrescu ◽  
Petrica Ciotirnae ◽  
Constantin Vizitiu

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.


2020 ◽  
Vol 53 (2) ◽  
pp. 11237-11242
Author(s):  
Tibor Horak ◽  
Zuzana Cervenanska ◽  
Ladislav Huraj ◽  
Pavel Vazan ◽  
Jan Janosik ◽  
...  

2021 ◽  
Vol 31 (3) ◽  
pp. 1-26
Author(s):  
Aravind Balakrishnan ◽  
Jaeyoung Lee ◽  
Ashish Gaurav ◽  
Krzysztof Czarnecki ◽  
Sean Sedwards

Reinforcement learning (RL) is an attractive way to implement high-level decision-making policies for autonomous driving, but learning directly from a real vehicle or a high-fidelity simulator is variously infeasible. We therefore consider the problem of transfer reinforcement learning and study how a policy learned in a simple environment using WiseMove can be transferred to our high-fidelity simulator, W ise M ove . WiseMove is a framework to study safety and other aspects of RL for autonomous driving. W ise M ove accurately reproduces the dynamics and software stack of our real vehicle. We find that the accurately modelled perception errors in W ise M ove contribute the most to the transfer problem. These errors, when even naively modelled in WiseMove , provide an RL policy that performs better in W ise M ove than a hand-crafted rule-based policy. Applying domain randomization to the environment in WiseMove yields an even better policy. The final RL policy reduces the failures due to perception errors from 10% to 2.75%. We also observe that the RL policy has significantly less reliance on velocity compared to the rule-based policy, having learned that its measurement is unreliable.


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