2020. 1st Issue
Volume XII, Number 1
Full issue (11,8 MB)
MESSAGE FROM THE GUEST EDITORS
Special Issue on Cognitive Infocommunications Theory and Applications – Guest Editorial
COGNITIVE infocommunications (CogInfoCom) investigates the link between the research areas of infocommunications and cognitive sciences, as well as the various engineering applications which have emerged as the synergic combination of these sciences. The primary goal of CogInfo-Com is to provide a systematic view of how cognitive processes can co-evolve with infocommunications devices so that the capabilities of the human brain may not only be extended through these devices, irrespective of geographical distance but may also be blended with the capabilities of any artificially cognitive system. This merging and extension of cognitive capabilities are targeted towards engineering applications in which artificial and/or natural cognitive systems are enabled to work together more effectively. The special issue presents the latest results in this scientific field.
Carl Vogel and Anna Esposito
Interaction Analysis and Cognitive Infocommunications
Cognitive infocommunications encompasses both scientific and engineering oriented approaches to examining extensions of human cognitive capabilities that may be assimilated within the concept of humanity. Necessary (but not sufficient) conditions for the success of any candidate technology include solving problems within private and public spheres of existence, in thought and communication. Exemplar cognitive infocommunication technologies that have been assimilated in to the concept of humanitiy are examined: emotion, gesture, language. Implications for research programmes conducted within the cognitive infocommunications discipline are outlined.
Nelson Mauro Maldonato, Benedetta Muzii, Mario Bottone, Raffaele Sperandeo, Donatella Di Corrado, Grazia Isabella Continisio, Teresa Rea, Anna Esposito
Unitas Multiplex. Biological architectures of consciousness
The so-called Posthuman question - the birth of organisms generated by the encounter of biological and artificial entities (humanoid robots, cyborgs and so on) – is now on the agenda of science and, more generally, of contemporary society. This is an issue of enormous importance, which not only poses ethical questions but also, and above all, methodological questions about how it will be achieved on a scientific plane. How such entities will be born and what their functions will be? For example, what kind of consciousness will they be equipped with, in view of the function of consciousness for distinguishing the Self from others, which is the foundation of the interactive life of relationships? Many scholars believe that rapid technological progress will lead to the emergence of organisms that will simulate the functions of the mind, learn from their experiences, decode real-world information, and plan their actions and choices based on their own values elaborated from vast amounts of data and metadata. In the not-too-distant future, it is believed that these entities will acquire awareness and, consequently, decisional freedom, and perhaps even their own unique morals. In this paper, we try to show that the path towards this goal cannot avoid clarification of the problems that neuroscience has ahead of it. These problems concern: a) the way in which consciousness comes about on the basis of well-defined brain processes; b) how it represents its own organization and not a simple brain function; c) how simultaneously contains multiple distinct contents, each with its own intentionality; d) how it expresses dynamic evolutionary relations and not a set of phenomena that may be isolated; e) finally, how its order is not rigidly hierarchical, but is supported by a multiplicity of horizontal levels, each of which is in structural and functional continuum with different phenomenal events. The empirical and theoretical research effort on this topic provides an intensive contribution to the development of IC Technologies.
Masakazu Kanazawa, Atsushi Ito, Kazuyuki Yamasawa, Takehiko Kasahara, Yuya Kiryu and Fubito Toyama
Method to Predict Confidential Words in Japanese Judicial Precedents Using Neural Networks With Part-of-Speech Tags
Cognitive Infocommunications involve a combination of informatics and telecommunications. In the future, infocommunication is expected to become more intelligent and life supportive. Privacy is one of the most critical concerns in infocommunications. Encryption is a well-recognized technology that ensures privacy; however, it is not easy to completely hide personal information. One technique to protect privacy is by finding confidential words in a file or a website and changing them into meaningless words. In this paper, we investigate a technology used to hide confidential words taken from judicial precedents. In the Japanese judicial field, details of most precedents are not made available to the public on the Japanese court web pages to protect the persons involved. To ensure privacy, confidential words, such as personal names, are replaced by other meaningless words. This operation takes time and effort because it is done manually. Therefore, it is desirable to automatically predict confidential words. We proposed a method for predicting confidential words in Japanese judicial precedents by using part-of-speech (POS) tagging with neural networks. As a result, we obtained 88% accuracy improvement over a previous model. In this paper, we describe the mechanism of our proposed model and the prediction results using perplexity. Then, we evaluated how our proposed model was useful for the actual precedents by using recall and precision. As a result, our proposed model could detect confidential words in certain Japanese precedents.
Tibor Ujbányi, Attila Kővári, Gergely Sziládi and József Katona
Examination of the eye-hand coordination related to computer mouse movement
Eye-hand coordination means the ability to combine seeing and hand movement. Eye-hand coordination is a complex process consisting of a series of conscious actions. The fine motor skills of the hand were not born with us but learned. The development of eye-hand coordination has begun in infancy through various ball games, construction games and puzzle games. Co-ordinated work of eye and hand movement is the basis for many activities. The proper functioning of eye-hand coordination is necessary for many everyday activities such as writing, reading or driving. The joint work of the eyes and hands is vital for certain forms of movement (ball-catching, kicking). The eye plays an essential role in regulating fine movements. In this paper a general eye-hand coordination task is examined in relation to mouse cursor movement on computer screen. An eye-hand tracking system was used to observe the gaze and hand path during the mouse cursor movement and the acquired data were analyzed by statistical t-test.
Emőke Kiss, Marianna Zichar, István Fazekas, Gergő Karancsi and Dániel Balla
Categorization and geovisualization of climate change strategies using an open-access WebGIS tool
The focus of our paper is to present the power of collaboration of databases in a web environment, where data contain or are related to different types of social geography spatial data. Implementing different data gained from the Climate Change Laws of the World, the United Nations Treaty Collection, the World Bank and The World Factbook, we ourselves developed the Climate Change Strategies of the world’s countries (called CCS). Our purpose is to publish and demonstrate the spatial visualization and categorization of the climate change strategies (CCS) of the world’s countries, and also highlight the power of geovisualization in terms of cognitive InfoCommunications, using open-access WebGIS tools and geoinformatics software. The evolved geographic database is able to provide information for users about the different types of climate change strategies of the world’s countries in a visual way, but can also be extended by uploading new data.
Mohammad Moghadasi and Gabor Fazekas
Multiple sclerosis Lesion Detection via Machine Learning Algorithm based on converting 3D to 2D MRI images
In the twenty first century, there have been various scientific discoveries which have helped in addressing some of the fundamental health issues. Specifically, the discovery of machines which are able to assess the internal conditions of individuals has been a significant boost in the medical field. This paper or case study is the continuation of a previous research which aimed to create artificial models using support vector machines (SVM) to classify MS and normal brain MRI images, analyze the effectiveness of these models and their potential to use them in Multiple Sclerosis (MS) diagnosis. In the previous study presented at the Cognitive InfoCommunication (CogInfoCom 2019) conference, we intend to show that 3D images can be converted into 2D and by considering machine learning techniques and SVM tools. The previous paper concluded that SVM is a potential method which can be involved during MS diagnosis, however, in order to confirm this statement more research and other potentially effective methods should be included in the research and need to be tested. First, this study continues the research of SVM used for classification and Cellular Learning Automata (CLA), then it expands the research to other method such as Artificial Neural Networks (ANN) and k-Nearest Neighbor (k-NN) and then compares the results of these.
PAPERS FROM OPEN CALL
Roman N. Ipanov
Phase-Code Shift Keyed Probing Signals with Discrete Linear Frequency Modulation and Zero Autocorrelation Zone
Modern synthesized aperture radars (SAR), e.g. space SARs for remote sensing of the Earth, use signals with linear frequency modulation and signals with phase-code shift keying (PCSK) coded by M-sequence (MS) as probing signals. Utilization of PCSK-signals permits an essential improvement of the radar image quality at the stage of its compression on azimuthal coordinate. In this paper, probing signals with zero autocorrelation zone (ZACZ) are synthesized, which signals represent a sequence of two PCSK-pulses with additional linear frequency modulation of sub-pulses in the pulses. A comparative analysis of the correlation characteristics of the synthesized signal and the PCSK-signal coded by MS has been performed. It is shown that in ZACZ, at a mismatch in the Doppler frequency, the level of all side lobes (SL) of the autocorrelation function (ACF) of the synthesized signal is less than the ACF SL level of the PCSK-signal coded by MS. The total ACF of the ensemble of 4 signals has zero SL along the whole time axis τ, and at a mismatch in frequency in ZACZ, it has a lower SL level than the total ACF SLs of the ensemble of 4 PCSK-signals coded by MS.
Balazs Solymos and Laszlo Bacsardi
Real-time Processing System for a Quantum Random Number Generator
Quantum random number generators (QRNG) provide quality random numbers, which are essential for cryptography by utilizing the unpredictable nature of quantum mechanics. Advancements in quantum optics made multiple different architectures for these possible. As part of a project aiming to realize a QRNG service, we developed a system capable of providing real-time monitoring and long term data collection while still fulfilling regular processing duties for these devices. In most cases, hardware validation is done by simply running a battery of statistical tests on the final output. Our goal, however, was to create a system allowing more flexible use of these tests, realizing a tool that can also prove useful during the construction of our entropy source for detecting and correcting unique imperfections. We tested this flexibility and the system’s ability to adequately perform the required tasks with simulated sources while further examining the usability of available verification tools within this new custom framework.