An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.

Summary of over Fifty Years with Brain-Computer Interfaces-A Review.

Traffic has become more complex in recent years and therefore the expectations that are placed on automobiles have also risen sharply. Support for drivers and the protection of the occupants of vehicles and other persons involved in road traffic have become essential. Rapid technical developments and innovative advances in recent years have enabled the development of plenty of Advanced Driver Assistance Systems that are based on different working principles such as radar, lidar or camera techniques. Some systems only warn the drivers via a visual, audible or haptical signal of a danger. Other systems are used to actively engage in the control of a vehicle in emergency situations. Although technical development is already quite mature, there are still many development opportunities for improving road safety. The further development of current applications and the creation of new applications that are based on sensor fusion are essential for the future. A short summary of capabilities of ADAS systems and selected ADAS modules was presented in this paper. The review was selected toward the future perspective of sensors fusion applied on the autonomous mobile platform.

A Survey of ADAS Technologies for the Future Perspective of Sensor Fusion

Computer vision based indoor localization methods use either an infrastructure of static cameras to track mobile entities (e.g., people, robots) or cameras attached to the mobile entities. Methods in the first category employ object tracking, while the others map images from mobile cameras with images acquired during a configuration stage or extracted from 3D reconstructed models of the space. This paper offers an overview of the computer vision based indoor localization domain, presenting application areas, commercial tools, existing benchmarks, and other reviews. It provides a survey of indoor localization research solutions, proposing a new classification based on the configuration stage (use of known environment data), sensing devices, type of detected elements, and localization method. It groups 70 of the most recent and relevant image based indoor localization methods according to the proposed classification and discusses their advantages and drawbacks. It highlights localization methods that also offer orientation information, as this is required by an increasing number of applications of indoor localization (e.g., augmented reality).

https://www.mdpi.com/1424-8220/20/9/2641/pdf

A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision.

In 1940s, Claude Shannon developed the information theory focusing on quantifying the maximum data rate that can be supported by a communication channel. Guided by this, the main theme of wireless system design up until 5G was the data rate maximization. In his theory, the semantic aspect and meaning of messages were treated as largely irrelevant to communication. The classic theory started to reveal its limitations in the modern era of machine intelligence, consisting of the synergy between IoT and AI. By broadening the scope of the classic framework, in this article we present a view of semantic communication (SemCom) and conveying meaning through the communication systems. We address three communication modalities, human-to-human (H2H), human-to-machine (H2M), and machine-to-machine (M2M) communications. The latter two, the main theme of the article, represent the paradigm shift in communication and computing. H2M SemCom refers to semantic techniques for conveying meanings understandable by both humans and machines so that they can interact. M2M SemCom refers to effectiveness techniques for efficiently connecting machines such that they can effectively execute a specific computation task in a wireless network. The first part of the article introduces SemCom principles including encoding, system architecture, and layer-coupling and end-to-end design approaches. The second part focuses on specific techniques for application areas of H2M (human and AI symbiosis, recommendation, etc.) and M2M SemCom (distributed learning, split inference, etc.) Finally, we discuss the knowledge graphs approach for designing SemCom systems. We believe that this comprehensive introduction will provide a useful guide into the emerging area of SemCom that is expected to play an important role in 6G featuring connected intelligence and integrated sensing, computing, communication, and control.

What is Semantic Communication? A View on Conveying Meaning in the Era of Machine Intelligence.

Nowadays many Internet of Things solutions used embedded systems that are not equipped with real-time clock. Some of them are used in Unmanned Ground Vehicle platforms that require precise measurements and calculations to move properly and safely. Often such systems are realised as soft real-time Linux systems equipped with real-time path. To improve quality of such systems it is necessary to determine a minimum cycle of time that will allow a stable work of embedded system. In this paper, the authors focus on approaches to verify the performance of Rasbian system in various use cases to obtain a minimum jitter and duration of cycle time for real–time applications that requires a guaranteed response within strict timing constraints of UGV. Additionally, was described a simple approach to determine a minimum cycle time period for a soft real-time system implemented on Raspberry Pi3 based on the maximum confidence interval.

The Cycle Time Determination for a Soft Real-Time System

Globalne uszkodzenia parametryczne w testowaniu analogowych układów scalonych

Dobór pobudzenia testującego PWL za pomocą algorytmu SA z neuronową funkcją celu

A fuzzy logic controller to seat comfort correction for manually propelled wheelchair - a case study

This paper discusses the basic concept of analog functional test approach. Recently, most on going research has been focused on distinguishing faulty or healthy circuit - from the manufacturer's point of view, this is more important than locating particular faulty element. The article shows the concept of fuzzy theory approach to functional test creation. To find and locate faulty circuit (system) the sensitivity matrix can be used. It has been observed that for most practical circuits the sensitivity matrix is sparse. This observation has been utilized in the fuzzy expert system and the system modification based on the reduction of the sensitivity matrix size has been proposed. The modified system can effectively decide whether the system is faulty or healthy. The results obtained and presented here are promising and tend to prove that the proposed strategy can improve fault detection on a production line.

Analog fault AC dictionary creation - the fuzzy set approach

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