Lattices in generative classes

We define and study lattices in generative classes associated with generic structures. It is shown that these lattices can be non-distributive and, moreover, arbitrary enough. Heights and wights of the lattices are described. A model-theoretic criterion for the linear ordering is proved and these linear orders are described. Boolean algebras generated by the considered lattices are also described. © 2019 Kiouvrekis Y., Stefaneas P., Sudoplatov S.V

On the Transformations of the Square of Opposition from the Point of View of Institution Model Theory

In recent decades, research in the square of opposition has been increased. New interpretations, extensions, and generalizations have been suggested, both Aristotelian and non-Aristotelian ones. The paper attempts at comparing different versions of the square of opposition. For this reason, we appeal to the wider categorical model-theoretic framework of the theory of institutions. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG

Computational Argumentation for Medical Device Regulatory Classification

This work implements argumentation as the basis for modeling the relevant EU legislation concerning medical devices classification. Stakeholders can consult a web application for determining the risk-based class of a medical device based on the relevant legislation. The described approach is generally applicable to any other analogous cases of decision-making based on legislative regulations. One of the main advantages of using argumentation is the explainability and the high modularity of software permitting the extension and/or modification of the code when new relevant regulations become available. © 2022 World Scientific Publishing Company

Artificial Intelligence, Big Data Analytics, and Smart Cities

Modern urban life is seeing an increasing rate of adoption of artificial intelligence and smart solutions; however, citizens are still struggling to keep up the pace, and the rate at which they acquire skills and knowledge around artificial intelligence and data analysis in smart cities is lagging behind. This paper is an attempt to determine which digital skills are necessary when dealing with smart cities. This article is structured as follows: we first refer to the two basic and fundamental branches of artificial intelligence and continue with applications that exist in these branches regarding smart environments. The research contribution of this article is important since it is one of the few in the international literature dealing with all branches of AI and big data (e.g., machine learning and rule-based applications) in smart cities. The conclusion of the present work is that there is an urgent need to create an education system in the new concepts of AI and big data analysis not only for scientists but also for citizens. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG

Limiting the impact of statistics as a proverbial source of falsehood

This paper presents an early version of a decision-making “eco” system. We refer to it as an “eco” system because it is primarily based on mathematical logic and combines concepts and principles from the fields of statistics, decision theory, artificial intelligence and modeling of human behavior. The primary goal of the proposed approach is to address errors that occur resulting from the misuse of statistical methods. In practice, such errors often occur either owning to the use of inappropriate statistical methods or wrong interpretations of results. The proposed approach relies on the LPwNF (Logic Programming without Negation as Failure) framework of non-monotonic reasoning as provided by Gorgias. The proposed system enables automatic selection of the appropriate statistical method, based on the characteristics of the problem and the sample. The expected impact could be twofold: it can enhance the use of statistical systems like R and, combined with a Java-based interface to Gorgias, make non-monotonic reasoning easy to use in the proposed context. © 2019, Springer Nature Switzerland AG

Forecasting Winter Precipitation based on Weather Sensors Data in Apache Spark

The proposed paper introduces an approach providing weather information on winter precipitation types using machine learning techniques. The proposed methodology takes as input the data received from weather sensors and in following the winter precipitation model aims at forecasting the weather type given three precipitation classes, namely rain, freezing rain, and snow, as registered in the Automated Surface Observing System (ASOS). To enable the proposed classification, six supervised machine learning models were selected: Naive Bayes, Decision Stump, Hoeffding Tree, HoeffdingOption Tree, HoeffdingAdaptive Tree, and OzaBag. Results depicted that all the models performed well in terms of accuracy and computation time, while some achieved even better outcomes. Specifically, among all six models, OzaBag presented the best classification results, followed by HoeffdingOption Tree. © 2021 IEEE

Telemedicine in Shipping Made Easy - Shipping eHealth Solutions

This research study aims to highlight the main weak and strong points of existing telemedicine technologies as well as to propose the creation of a new, innovative and financially efficient system of telemedicine which can be used in the maritime industry. In addition to main applications and details of the new system, the article describes and expounds on necessary equipment as well as personnel training. © 2020, Springer Nature Switzerland AG

A statistical analysis for RF-EMF exposure levels in sensitive land use: A novel study in Greek primary and secondary education schools

Background: The increasing popularity of mobile phones and the expansion of network infrastructure in Greece have given rise to public concerns about potential adverse health effects on sensitive groups, such as children, from long-term radio-frequency (RF) electromagnetic fields (EMFs) exposure. According to Greek law the RF limit values for sensitive land use (schools, hospitals, etc) have been set to 60% of those recommended by EU standard and 70% for the general population. Aims: The objective of this study is to estimate mean RF-EMF exposure levels of Greek primary and secondary edu-cation schools located in urban environments. Methods: In selecting the minimum sample size we observed that the variance of the random variable was unknown, as there has been no similar previous study in Greece with schools as the target population. For this reason, a pilot study was conducted in 65 schools in order to estimate the standard deviation of the population and use that value to calculate the minimum sample size. Using a random machine num-ber generator contracted in R based on pseudo-random number algorithms, we obtained a sample of 492 schools in order to estimate the mean value for RF-EMF radiation sources in the 27 MHz-3GHz range in schools within urban environments in Greece. Results: We have performed the appropriate hypothesis test to get that there is sufficient evidence at the α = 0.05 level to conclude that the mean value for RF-EMF radiation sources in the 27 MHz-3GHz range, in schools within urban environments in Greece, is equal to 0.42 V/m, also a 95% confidence interval for the mean value is (0.4024, 0.4395)] with central value equal to the sample mean 0.4209. Conclusion: In conclusion, the exposure level in the locations tested are both below 60% of the highest limit set by ICNIRP (International Commision on Non-Ionizing Radiation Protection) regarding sensitive land use. © 2020 Elsevier Inc

Extensive Use of RFID in Shipping

Radio Frequency Identification (RFID) Technology is a part of supply chain systems but has not been fully integrated in the shipping industry to date. Port and terminal management teams already make use of this technology to verify cargo information, reduce waiting times and prevent bottlenecks. The adoption of RFID technology in the shipping industry can provide invaluable real-time information about a ship’s crew and cargo. This study deals with RFID-based solutions concerning issues of cargo security and handling, as well as tracking of the crew in emergency situations. Although some maritime companies have upgraded their fleet with modern management systems, there is still much to be gained by the wide use of more RFID applications in shipping. We will expound on some of the most useful RFID applications in the maritime sector and discuss their respective advantages and disadvantages. © 2020, Springer Nature Switzerland AG

Dosimetric and radiobiological evaluation of four radiation techniques in preoperative rectal cancer radiotherapy

Purpose: To compare tumour dose distribution, conformality, homogeneity, normal tissue avoidance, tumour control probability (TCP) and normal tissue complication probability (NTCP) using 3D conformal radiation therapy (3DCRT), 3- and 4-field intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) in patients with locally advanced rectal cancer. Materials and methods: Twenty-four patients staged T 1-3 N + M 0 with locally advanced rectal cancer underwent neoadjuvant chemoradiation therapy. Four different radiotherapy plans were prepared for each patient: 3DCRT, 3- and 4-field IMRT and VMAT are evaluated for target distribution using CI and homogeneity index (HI), normal tissue avoidance using D max, V 45, V 40, V 50 and TCP and NTCP using the Lyman-Kutcher-Burman model. Results: VMAT has better HI (HI = 1·32) and 3DCRT exhibited better conformality (CI = 1·05) than the other radiotherapy techniques. With regard to normal tissue avoidance, all radiotherapy plans met the constraints. D max in the 3DCRT plans was statistically significant (p = 0·04) for bladder and no significant differences in V 40 and V 50. In the bowel bag, no significant differences in D max for any radiotherapy plan and V 40 was lower in 3DCRT than VMAT (p = 0·024). In the case of femoral heads, 3DCRT has a statistically significant lower dose on D max than 4-field IMRT (p = 0·00 « 0·05). VMAT has the biggest TCP (80·76%) than the other three radiotherapy plans. With regard to normal tissue complications, probabilities were shown to be very low, of the order of 10-14 and 10-41 for bowel bag and femoral heads respectively. Conclusions: It can be concluded that 3DCRT plan improves conformity and decreases radiation sparing in the organ at risks, but the VMAT plan exhibits better homogeneity and greater TCP. © 2021 Cambridge University Press. All rights reserved