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Do We Like Majority Decisions? Aspects of the Majority Principle in Voting on the Different Levels of Political Systems

Péter Smuk

Publication Name: Hungarian Yearbook of International Law and European Law

Publication Date: 2022-01-01

Volume: 10

Issue: 1

Page Range: 409-423

Description:

This article aims to review the constitutional justifications for majority requirements arising from the democratic principle, and to analyze some current controversial cases. Although the qualified majority requirement is not a new institution in either the national constitutional systems or the functioning of the EU institutions, the democratic legitimacy of majority voting faces several challenges. In order to present aspects that should be re-evaluated in the light of certain new political strategies, this paper analyses the majoritarian requirements in the Treaties, in the rules of procedures of the European Parliament and also case studies pertaining to the constitution-making majority in Hungary and the controversial case of voting on the Sargentini-report. On the basis of this assessment, we may confirm but also reconsider the majority principle.

Open Access: Yes

DOI: 10.5553/HYIEL/266627012022010001023

Investigation of Possibilities of λ = 1 Full Load Operation for Gasoline Engines in the Light of Future Emission Regulation

György Szabados H. Szűcs Jozefin Hézer Brian Sanders

Publication Name: Periodica Polytechnica Transportation Engineering

Publication Date: 2022-01-01

Volume: 50

Issue: 2

Page Range: 111-127

Description:

To date, huge amounts of money have been invested in the development of internal combustion engines to reach the current level of technology. High specific power and good thermal efficiency have been achieved, thanks to which, internal combustion engines are now widely used. However, the driving force behind the developments is no longer the high performance, but the compliance with strict emission standards. Future emissions regulation, namely Euro 7, will be challenging for engine and vehicle manufacturers. One possible technical solution may be to use a stoichiometric air-fuel mixture on the entire engine map to meet the requirements of the Euro 7 emission standard. This article analyzes the change in Euro regulations in the light of Euro 7, as well as the theoretical background of the λ = 1 operation. Several technical possibilities to achieve the stoichiometric ratio, such as e.g. water injection or variable compression ratio are presented.

Open Access: Yes

DOI: 10.3311/PPtr.17433

Road Safety Analysis of Autonomous Vehicles

H. Szűcs Jozefin Hézer

Publication Name: Periodica Polytechnica Transportation Engineering

Publication Date: 2022-01-01

Volume: 50

Issue: 4

Page Range: 426-434

Description:

For the widespread use of Autonomous Vehicles (AVs), a huge number of challenges must be solved by vehicle manufacturers, in contrast they do have significant potential to increase road safety in both passenger and freight transport. In addition to reducing road traffic accidents and traffic jams, AVs also offer a major opportunity to reduce pollutant emissions and CO2 emissions from environmental point of view. In order to implement accident-free traffic, also called Vision Zero, it is essential to examine the safety and reliability of AVs. This article analyzes road traffic accident data and the potential safety benefits of AVs. Furthermore, the paper also sets the safety of the conventional vehicles against AVs and examines the type, location, causes, and dynamics of the accidents. The article also provides an overview over the current development trends and challenges, such as the risk of cyber-attacks, the necessary improvements in sensing technologies, and the not insignificant moral issue of AVs.

Open Access: Yes

DOI: 10.3311/PPtr.19605

A Clothoid-based Local Trajectory Planner with Extended Kalman Filter

Ernö Horváth Gergo Igneczi

Publication Name: Sami 2022 IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics Proceedings

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 467-472

Description:

The paper introduces a local trajectory planner designed specifically for lateral guidance of autonomous vehicles. The inputs of the planner are the lane edges in the form of corner point coordinates in a two-dimensional plane. The aim of the planner is to provide a series of trajectory points ahead of the vehicle. The trajectory shall be well-conditioned which means no border violation (safety), no high lateral acceleration (comfort) and good tracking properties. The optimal conditions for driving have been found in using clothoid curves. The curvature of the clothoid is a linear function of the distance, which resolves the biggest disadvantage of circle conjunction: the discontinuity of the lateral acceleration. Clothoids have constant lateral jerk profile. In our work an Extended Kalman Filter is used with a clothoid model to consolidate inaccuracies of the lane detection system. The paper is presented as the first part of a research process. The algorithm introduced in this paper is planned to be continued with research on its automatized calibration procedures.

Open Access: Yes

DOI: 10.1109/SAMI54271.2022.9780857

Increasing Patient Specificity of the Recurrent Neural Network Based Insulin Sensitivity Prediction by Transfer Learning

B. Benyo J. Geoffrey Chase Bálint Szabó K. Kovacs Ákos Szlávecz Béla Paláncz

Publication Name: Ines 2022 26th IEEE International Conference on Intelligent Engineering Systems 2022 Proceedings

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 27-32

Description:

Insulin therapy is a frequently applied treatment in intensive care to normalize the patient's blood glucose level increased by stress-induced hyperglycaemia. This therapy is generally referred to as Tight Glycaemic Control (TGC). The STAR (Stochastic-TARgeted) protocol is a TGC which uses the patient's insulin sensitivity (SI) as a key parameter to describe the patient's actual state. Prediction of the future patient's state, i.e. prediction of the patient's future SI value, is a crucial step of the protocol currently implemented by using the so-called Intensive Care INsulin Glucose (ICING) model of the human glucose-insulin system and an associated stochastic model. In our previous studies, we have shown that the Recurrent Neural Network (RNN) models are efficient alternative methods of SI prediction. In this paper, we suggest applying the so-called transfer learning technique to further enhance the accuracy of the SI prediction by using the SI history of the current patient. The paper presents the proposed methodology for applying transfer learning in SI prediction and the evaluation of the method's accuracy by comparing the outcomes with the currently applied solution. Insilico validation using real patients' data is involved in this validation.

Open Access: Yes

DOI: 10.1109/INES56734.2022.9922645

Outlines of a Graph-Tensor Based Adaptive Associative Search Model for Internet of Digital Reality Applications

Adam Csapo Tarek Setti

Publication Name: 2022 IEEE 1st International Conference on Internet of Digital Reality Iod 2022

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 49-54

Description:

Internet of Digital Reality (IoD) is a technological vision that promises to radically transform existing digital ecosystems in a way that enables users to access all the content and capabilities - whether physical or digital - relevant to a goal-driven purpose in a highly integrated single environment. In this paper, we focus on a specific challenge that we expect will be crucial in making advances in this field: namely, the challenge of developing an effective search method that is personalized, adaptive and associative. As a possible solution to this challenge, we propose a graph-tensor based information model that incorporates the history of search keywords and inferred associations between them across potentially multiple search dimensions. We provide a brief discussion on why we assume this model to have advantageous properties and provide a short use-case example to motivate further research.

Open Access: Yes

DOI: 10.1109/IoD55468.2022.9987234

Probability-based Vendor Selection Model for the Hungarian Automotive Supply Network

István A. Harmati Akos Domotorfi Zoltan Andras Nagy

Publication Name: Periodica Polytechnica Transportation Engineering

Publication Date: 2022-01-01

Volume: 50

Issue: 2

Page Range: 216-222

Description:

The aim of this paper is to investigate the structure of the Hungarian automotive supply network and provide a possible solution that mathematically describes the connections between the interested parties. In the study an approximate model is introduced to determine the links between hubs (car manufacturers), nodes (Tier1 suppliers) and edges, combining probability random graph and scale free network theory. During the simulation some main drivers were applied for selection purposes, such as location, turnover, product profile. As a result of the study a potential tool has been designed to support decision-making.

Open Access: Yes

DOI: 10.3311/PPtr.17966

INTUITIVE DECISION: WHEN TO BEGIN THE SUCCESSION PROCESS

Katalin Darabos

Publication Name: Corvinus Journal of Sociology and Social Policy

Publication Date: 2022-01-01

Volume: 13

Issue: 2

Page Range: 79-105

Description:

The aim of the paper is to increase understanding of the succession decision-making process in family businesses. In understanding this phenomenon on the personal level of reality and understanding the decision-making process involved in succession, the decision-maker’s thought process and aspirations have to be taken into consideration. Based on a survey, a knowledge-based expert system tool (Doctus) was used to order successors’ intuitive knowledge and aspirations in order to deepen our understanding of the succession decision-making phenomenon. The diversity of the identified rules suggests that first generational change does not happen according to a single model but rather a variety of pathways are followed, depending on the context.

Open Access: Yes

DOI: 10.14267/CJSSP.2022.2.4

Generative Hypergraph-based Kinematic Models for Virtual-Reality Applications

Adam Csapo Csaba Hajdu

Publication Name: 2022 1st IEEE International Conference on Cognitive Aspects of Virtual Reality Cvr 2022

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 11-16

Description:

Recently, virtual reality applications have become a prominent research area, along with related topics such as digital-twin applications and simulation of devices such as vehicles or cyber-physical systems. These topics are intimately linked with computer-based simulations and computer graphics. Consequently, accurately describing entities populating simulated worlds is a critical task. Relevant properties include but are not limited to an object's visual appearance and kinematic constraints. This paper proposes a hypergraph-based kinematic model aiming to describe virtual entities used in virtual reality applications and simulations. Compared to other popular schematics (e.g., URDF, SDF), a primary advantage of this approach is its reduced language element set, which is capable of minimally describing a conceptually very simple kind of hypergraph. This reduction, in turn, enables the description of simple graph triplets amenable to storage in graph databases or ontologies. The introduced format is aimed at enabling the flexible and efficient real-time exchange of visual and physical information on cognitive channels between entities. The possibility of transforming an instance of this model into other schematics (SDF, MaxWhere) is further demonstrated in the paper, which constructively proves the expressive capabilities of the model and helps support the claim that it is equivalent in expressive power to other widely used description models.

Open Access: Yes

DOI: 10.1109/CVR55417.2022.9967632