EIBC - Anniversary newsletter - 2013

Magazine Overview

This document is the "Anniversary Bulletin" (Юбилейный бюллетень) from the EIBC (Extraterrestrial Intellectual Biological Creatures), published in Rovno in 2013. It marks the 3rd anniversary of the organization, which was founded on October 15, 2009. The bulletin contains research and analysis related to UFO sightings and alleged encounters with non-human entities.

Content and Articles

The bulletin's table of contents outlines several key articles:

1. Igor Kalytyuk: Analytical Approach to Verifying the Motivational-Psychological State of Individuals who Observed 'Landing-Hovering' of Unknown Origin Transport Vehicles (TC) with Biological Beings (BS) or were 'Abducted' onto TC BS. This article, starting on page 1, delves into the challenges of scientifically analyzing witness accounts of UFOs and alleged abductions. Kalytyuk identifies three main problems: the lack of scientific rigor among amateur investigators, the low credibility of witness testimonies often filled with fantastical elements and signs of deception, and the prevalence of falsifications and mystifications in mass media driven by profit motives. He proposes a multi-faceted approach to discerning truth from fiction, emphasizing the need for professional specialists and outlining methods like analyzing micro-expressions, body language, and handwriting.

2. A. Bilyk: Information Volume and Factors of Anomaly in the Study of Anomalous Aerospace Phenomena. This article, starting on page 10, likely discusses the quantity and types of information available when investigating unusual aerial events and the factors that contribute to their anomalous nature.

3. V. Mantulin: Methodology for Detecting Anomalous Objects (AO) by Civil Aviation Radar Stations. Beginning on page 23, this piece focuses on the technical aspects of UFO detection, specifically how radar systems used in civil aviation can identify anomalous objects.

4. A. Mykolyhyn: Investigating the Phenomena of the Subjective Factor in the Measurement of Socio-Informational Systems. Starting on page 33, this article explores how subjective perceptions and the way information is presented and received within social systems can influence the understanding of phenomena, likely including UFO-related reports.

Detailed Analysis of Kalytyuk's Article (Pages 3-9)

Igor Kalytyuk's article forms the core of the bulletin, presenting a detailed methodology for evaluating the reliability of UFO witnesses. He criticizes the unscientific methods often employed by independent researchers, highlighting issues like:

• Lack of Clear Methodology: Amateur investigators often lack a defined approach, confusing physical reality with altered states of consciousness.
• Low Credibility of Testimonies: Witnesses may present elaborate, unverifiable stories, sometimes exhibiting signs of deception, arrogance, or a belief in their own expertise.
• Media Manipulation: The media can exploit UFO phenomena for sensationalism and profit, creating "UFO cults" and spreading misinformation.

Kalytyuk proposes six methods for verification:

1. Statistical Approach: Analyzing large datasets for correlations and patterns, building on the work of researchers like Jacques Vallee and David Webb.
2. Psychotherapeutic Examination: Using techniques like regression hypnosis to explore witness memories, referencing figures like Budd Hopkins and David Jacobs.
3. Psychological Approach: A novel method developed by Kalytyuk and his colleagues, involving deception detection through dialogue, analysis of gestures, facial expressions, and handwriting. This includes assessing the witness's motivation and the credibility of their account.
4. Handwriting Analysis: Examining a witness's handwriting to assess their psychological state and the veracity of their statements.
5. Subject-Oriented Analysis: Developed by Alina Mykolyhyn, this method analyzes the interplay between systemic and non-systemic elements, reality and unreality, intuition and logic, and other psychological parameters. Tests like "Point of Support" are mentioned.
6. Psychiatric Expertise: The most complex method, involving a commission of experts to diagnose potential psychological deviations using the ICD-10 classification.

Kalytyuk emphasizes that a combination of these methods is crucial for a thorough investigation. He also provides a table (Table 1) illustrating the combination of analytical verification methods across different disciplines.

Other Sections

The bulletin also includes:

• Editorial Staff and Contact Information: Lists Igor Kalytyuk as the editor-compiler and provides contact details for correspondence, including an email address and a website (http://ufology-news.com/mic-eibc).
• Current EIBC Staff: Details the roles and backgrounds of Igor Kalytyuk, Alina Mykolyhyn, Sergey Petrov, and Ivan Pristavko.
• List of Collaborators: Acknowledges numerous individuals who assisted the EIBC.
• Bibliography: A comprehensive list of references, including books and articles on UFOs, psychology, media influence, and related topics.

Recurring Themes and Editorial Stance

The recurring themes in this bulletin are the critical analysis of UFO phenomena, the challenges of discerning truth from deception in witness testimonies, and the importance of employing rigorous scientific and psychological methods in ufological research. The editorial stance is one of skepticism towards unsubstantiated claims and a strong emphasis on methodological soundness. The EIBC positions itself as an organization dedicated to the scientific investigation of anomalous phenomena, aiming to separate credible evidence from sensationalism and misinformation. The bulletin advocates for a systematic and evidence-based approach to understanding UFOs and related experiences.

This issue of the magazine, dated 1977, focuses on the study of anomalous aerospace phenomena. The main article, titled 'Quantity of Information and Factors of Anomaly in the Study of Anomalous Aerospace Phenomena' by Bilyk Artem, explores the methodologies and theoretical frameworks for understanding these events.

Quantity of Information and Factors of Anomaly in the Study of Anomalous Aerospace Phenomena

The article begins by discussing the rapid development of science and the availability of powerful tools for understanding the world. It posits that any discovery starts with understanding anomalies – events that deviate from expected patterns. The process of cognition is described as a continuous uncovering of anomalies, which highlights the incompleteness of existing paradigms. For anomalous facts to be explained, a revolution in theory or an adaptation of existing paradigms is necessary.

The author distinguishes between 'phenomenon' (existential, descriptive essence) and 'explanatory aspect' or 'cause of occurrence.' Anomalous phenomena are characterized as non-periodic, rapidly occurring events that are phenomenological in nature. When their explanation falls outside the boundaries of current scientific paradigms, they remain purely descriptive.

Forming a Knowledge Base for Anomalous Phenomena

The primary goal of researching anomalous aerospace phenomena is to form a scientific picture of the phenomenon as part of the overall scientific understanding of the world. The current state of research is characterized by a large accumulation of data from various organizations, but this alone is insufficient for a qualitative leap in knowledge. True knowledge involves not just data but also the interconnections between them, representing the result of human thought and experience.

Knowledge is distinguished from information by its hierarchical structure, procedurality, compositionality, and descriptiveness. Knowledge can be declarative (facts, phenomena, relationships) or procedural (actions, procedures). It can also be factual (known facts) or heuristic (based on expert experience).

A 'knowledge base' is defined as a subject-oriented segmented model that organizes data for convenient representation. It consists of a database and a mechanism for deriving new knowledge. The process of filling a knowledge base involves three stages: formalization and data accumulation, data analysis, and processing and presentation of results. Each stage involves qualitative changes and inevitable losses of information.

Identification of Aerospace Phenomena

The core task in studying aerospace phenomena is their identification with phenomena of known origin. Early attempts involved classifying qualitative parameters and assigning weights to messages. Later, methods for accumulating and coding a priori information were developed, with analysis performed by expert groups.

A significant development was the creation of a comprehensive mathematical model for identifying anomalous aerospace phenomena by the Ukrainian Scientific Research Center for the Study of Anomalies 'Zond' in 2004. This model is based on fuzzy set theory. It involves defining sets of a priori data representing the parameters of a phenomenon and comparing them to known hypotheses.

The model uses a 'membership function' to characterize the degree to which a set of observed parameters matches a given hypothesis. The degree of 'identifiability' is a quantitative parameter that determines the best-matching hypothesis. The degree of non-identifiability is calculated as 1 minus the maximum identifiability.

Quantity and Quality of Information in the Study of Aerospace Phenomena

The identifiability parameter helps reduce the time and subjectivity in analyzing messages. However, it has limitations. While fuzzy set theory can handle both quantitative and qualitative data, establishing a clear correspondence between them is challenging. Developing standardized scales for discretizing qualitative data remains a difficulty.

Another problem is that identifiability does not indicate how informative or important a phenomenon is for building a knowledge base. To determine informativeness, a universal measure of information quantity is needed, independent of parameter specifics. The classical approach defines information as a measure of uncertainty reduction. Incomplete data in a UAP report leads to a combinatorial explosion of possible interpretations.

Information Measure and Anomalous Factors

The article discusses the concept of information measure, tracing its origins to R. Hartley and later refined by C. Shannon. Hartley proposed that information measure should grow monotonically with the uniformity of a message, measured by the number of symbols. Shannon's definition incorporated probabilistic parameters.

The authors propose a formula for the information measure of a UAP registration message, based on fuzzy sets and probability theory. This measure is influenced by the degree of non-identification and the number of parameters involved.

'Factors of anomaly' are defined as manifestations of a phenomenon whose characteristics do not fit within the array of known phenomena-hypotheses. These factors can be related to parameters that exceed the limits of known phenomena (e.g., an object moving much faster than any known aircraft) or entirely new manifestations (e.g., beams of finite length, sudden disappearance).

The Search for Reliable Information Sources

To minimize uncertainty, it is crucial to consider information sources that have minimal 'reduction factors' – meaning the least loss of information during perception, processing, and presentation. Monitoring and registration systems are identified as such sources. These include global, local, and individual electronic-mechanical systems that measure and record environmental conditions.

While the increasing use of technical means for observation (optical, radar, etc.) provides more comprehensive and reliable information, it also presents new challenges for data processing and analysis. Currently, access to such information is often restricted to military and government institutions. However, these organizations often have limited resources and operational capacity for processing the vast amounts of data collected.

Recurring Themes and Editorial Stance

The recurring themes in this issue revolve around the scientific methodology for studying anomalous phenomena, particularly UAPs. There is a strong emphasis on quantitative analysis, the development of mathematical models (especially using fuzzy sets), and the importance of reliable data sources. The editorial stance appears to be one of rigorous scientific inquiry, aiming to move beyond anecdotal evidence towards a more structured and data-driven understanding of UAPs. The issue highlights the challenges of information processing and the need for robust systems to analyze complex data, suggesting that a systematic approach is key to advancing the field.

This issue of "Anomaly" (№1/2013) focuses on the challenges and methodologies of detecting and analyzing anomalous aerospace phenomena (UAP), with a strong emphasis on radar detection and the necessity of a global monitoring network. The publication highlights the shortcomings in current organizational preparedness and advocates for greater public access to data.

The Need for Public Oversight and Global Monitoring

The lead article argues that the inadequate response to the 2013 Chelyabinsk meteorite event demonstrates a low level of readiness among organizations to process and analyze such events. This underscores a critical need for public oversight and open access to existing aerospace monitoring systems. The authors posit that such transparency will foster more informative reports and contribute to a better understanding of UAP. They foresee the inevitable evolution towards a Global Near-Earth Monitoring Network, which would not only enhance the detection, localization, and information gathering capabilities for aerospace phenomena but also improve prediction and forecasting. This global network is deemed essential for the safety and sustainable development of civilization, leveraging existing ground-based, sea-based, and space-based monitoring systems. While acknowledging the potential increase in data flow, the article stresses the need to improve procedural aspects, particularly signal and image processing algorithms, to handle this information effectively and generate uniform, real-time data for timely response strategies.

Despite advancements in monitoring, the article asserts that there will always be room for unidentified aerospace phenomena, as Earth and its surrounding space form an open system where measurements are inherently incomplete. The phenomenon of anomalous aerospace events is described as reflexive, operating with feedback, and likely to adapt to human actions, implying that humanity will also change in response.

Radar Detection of Anomalous Objects (AO)

Vladimir Mantulin's article delves into the practical aspects of detecting anomalous objects (AO) using radar stations, particularly those employed by Civil Aviation. The article begins by acknowledging that radar significantly expands human perception but also presents operators with enigmatic effects. While some phenomena are explained by equipment imperfections or natural causes, a persistent issue is the periodic detection of unidentified aerial objects on radar screens.

Case Study 1: December 1981 Observation

In December 1981, between 17:00 and 19:00, a cross-shaped glowing object was tracked for approximately 15 minutes alongside a Tu-154 aircraft and two other preceding aircraft flying at 12,000 meters. The object exhibited extremely rapid changes in speed and altitude, maintaining a trajectory eastward of the main route. It eventually accelerated, reportedly reaching up to 20,000 meters, overtook the other aircraft, and moved towards Belgorod at an estimated speed exceeding 2,000 km/h. This object was consistently tracked by a long-range surveillance radar.

Case Study 2: August 1983 Observation

On August 13, 1983, at 00:10:00, a visual observation of a reddish anomalous object near Kharkiv airport at an altitude of about 250 meters was corroborated by radar tracking. The object, tracked by a high-resolution dispatch radar (DRLс-9 "Narva-S"), moved on a course of approximately 45 degrees and was lost at a distance of about 27 km to the northeast, seemingly gaining altitude. The observation lasted no more than two minutes. A distinct reddish halo was visible, and the object appeared to fade as it entered cloud cover. Simultaneously, a target mark similar to that of the AO was detected. A second target appeared north of the first, on a parallel course about 8 km apart, at a distance of 6 km and an azimuth of approximately 55 degrees. This second target later altered its trajectory to a more northerly direction with a radius of about 15-20 km and an azimuth of approximately 60 degrees.

Further Radar Analysis and Object Characteristics

The second target disappeared at a distance of about 28.5 km, likely due to better radio wave propagation or a larger reflective surface. This distance was covered in approximately 2 minutes, with intermittent disappearances of 6-12 seconds. Later, another target appeared at an azimuth of 20-30 degrees and a distance of about 12-15 km, following a similar course and speed, and disappeared at about 20 km and an azimuth of 30-40 degrees. The speed of these objects was estimated at around 600±50 km/h. No significant active or passive interference was noted. The estimated size of the objects was about 5 meters (effective scattering area ~2m²). The reflection of radio waves was influenced by atmospheric conditions, with observations occurring after strong thunderstorms (indicating moving target selection).

Radar (DRL) operated in "Passive"-"Active" mode. Weak marks from AOs appeared as short dashes (1.5-2 mm long, 0.1-0.2 mm thick), visible for only 1.5-2 seconds out of an 8-second antenna rotation. Given the high reliability of the DRL-9, these objects were considered to be small in size with significant electrical activity.

The observers included V.S. Mantulin (dispatcher, Kharkiv United Air Traffic Control), S.A. Khatov (dispatcher), and A.A. Tarasenko (head of airfield operations).

Radar Systems and UAP Detection

Civil Aviation radar systems (ORL, DRL, PRL, and MRL) are capable of reliably detecting aerial objects across a wide range of distances, speeds, and altitudes, aiding in the identification of anomalous phenomena. Radar systems typically operate by receiving reflected waves. Active radars, in passive mode, detect all reflecting objects, including storm clouds and bird flocks. The accuracy of these radars for distance is no worse than 150 meters.

Radar Principles and Limitations

The article explains that the distance to a target is determined by the time delay of the reflected signal. The Doppler principle, used in moving target indication (MTI) or moving target detection (MTD) modes, helps distinguish moving targets from stationary clutter. However, MTI/MTD systems have limitations, including reduced detection range (60-75% of passive mode) and the phenomenon of "blind speeds," where the target's velocity causes its phase shift to remain constant, making it undetectable. "Blind speeds" can be determined by the formula S = K · λ / 2, where K is a multiplier (1, 2, 3...) and λ is the wavelength.

The synchronization of the radar sweep with antenna rotation is achieved through mechanical and electrical components. The accuracy of mechanical parts in modern radars can reach 0.1 degrees, with a directional pattern width of 0.5 degrees. The accuracy of coordinate determination is higher for pulse-Doppler radars (DRL) than for other types.

The article discusses the optimal frequency range for radar application, noting that radio wave attenuation is significant near wavelengths of 0.25 and 0.5 cm for oxygen and 1.8-1.35 cm for water vapor. Peaks in the graph indicate resonant absorption of energy at specific frequencies. Small particles (like fog) primarily absorb energy, while larger particles (like rain) cause scattering. Attenuation due to rain and fog is shown in curves 3-8. The article notes that for wavelengths over 10 cm, attenuation is negligible and can be ignored for decimeter and meter band radars. However, centimeter-band radars are susceptible to atmospheric interference.

Object Characteristics and Detection Factors

To overcome interference from precipitation, designers use vibrators that alter radio wave polarization, enabling the detection of aircraft against heavy rain or snow. Modern radar altitudes reach mid-atmospheric layers. The formula for line-of-sight range is given as Dpv ≈ 113 (√h + √H) km, where R3 is the Earth's radius, h is antenna height, and H is the aircraft's flight altitude.

Besides altitude, the object's surface area and material significantly influence detection. The article lists potential objects and their approximate radar cross-sections (in m²): Rocket warhead (0.2), Human (0.8), Submarine conning tower (1), Fighter jet (3-5), Front-line bomber (7-10), Heavy bomber (15-20), Transport aircraft (50).

A diagram illustrates the relationship between perceived diameter and distance to an object, paradoxically showing that perceived size increases with distance. This is hypothesized to be due to air compressibility at high speeds creating an energy field around the object, enhancing its aerodynamic characteristics and apparent size.

Plasma Hypothesis and Radar Types

The hypothesis that AOs move within an artificially created plasma layer is presented. Plasma, under certain conditions, acts as an ideal radio wave reflector, potentially explaining radar observations without visual confirmation. The article correlates visual observations of different shapes (triangles, squares, rectangles, rhomboids) with specific radar types (MPL, PRL, DRL, ORL, and specialized radars).

Early, less sophisticated radars often experienced signal fluctuations due to insufficient interference protection. Modern radars can still encounter "rings" and false target marks. Reflected signals from sea waves, received by low-altitude radars, can align with the "wave channel" theory, where radar beams can follow the surface over significant distances in inversion layers. Other phenomena like turbulent vortices, flocks of birds, insect swarms, and electrification zones are now commonly detected by various radar types.

References

The issue includes an extensive bibliography, listing 35 references, primarily in Russian, covering topics such as the structure of scientific revolutions, scientific uncertainty, information theory, cybernetics, Ufology, anomalous phenomena research, radar systems, and aerospace monitoring. Notable authors include A.S. Bilyk, V. Mantulin, J. Allen Hynek, Jacques Vallee, and others.

Recurring Themes and Editorial Stance

The recurring themes in this issue are the critical importance of robust aerospace monitoring, the need for transparency and public access to data, and the ongoing challenge of identifying and understanding anomalous aerial phenomena. The editorial stance appears to be one of advocating for scientific rigor in UAP research, exploring technological solutions like advanced radar systems, and promoting a more open and collaborative approach to studying these unexplained events. There is a clear emphasis on the scientific and technical aspects of UAP detection and analysis.

This document appears to be a collection of articles from a Russian-language publication, likely a scientific journal or specialized magazine, focusing on topics related to radar detection of anomalous objects (AOs) and the theoretical framework of the 'subjective factor' in socio-information systems.

Radar Detection of Anomalous Objects (AOs) Several sections discuss the use of various radar systems, including DRL (Directional Radar), MRL (Meteorological Radar), PRL (Pulse Radar), and ORL (Omnidirectional Radar), for detecting and tracking unidentified aerial phenomena. The text highlights how these systems identify 'marks' on screens that may indicate anomalous objects.

Key Incidents and Observations: * Speed Records: The publication cites several instances of high-speed detections in the 1980s: * August 1984: An AO detected by radar at Kharkiv Airport moving at approximately 4000 km/h. * November 3, 1984: An AO detected with a speed of approximately 4500 km/h. * Gorky: AOs detected at speeds of approximately 2 km/sec (3600 km/h). * Detection Characteristics: Anomalous objects are typically identified by radar operators based on several criteria: * Absence of known civilian or military aircraft in the area. * Anomalous flight trajectories. * Hovering. * Unusually high speeds. * Abnormal changes in altitude and speed. * Anomalous interference or electromagnetic effects. * Unusual formations during group flights. * System Integration: The text emphasizes the importance of integrating radar systems with air traffic control (ATC) systems (Unified ATC System - ДП ЕС УВД) to enhance flight safety. It suggests that a combination of radar and meteorological locators could form a base model for detecting AOs. * Recommendations: The authors recommend equipping DRL systems with video indicators and utilizing the entire radar complex to inform dispatchers. They also suggest familiarizing dispatchers with the methodology for observing AOs and using photo-recorders for documentation and analysis.

Theoretical Framework: The 'Subjective Factor' Another significant portion of the document is dedicated to a theoretical analysis of the 'subjective factor' within socio-information systems, authored by Mykolyshyn Alina. This section explores:

Definitions and Concepts: * Subjective Factor: Defined as a concept of the subjective, or the 'human factor,' in research. It encompasses elements like perception, thinking, analysis, ability, and usefulness. * Objective Factor: Contrasted with the subjective factor, representing the objective aspects of a system. * System Analysis: The research employs systemic and methodological analysis, distinguishing between the 'subject-nature' (empirical level), 'subject-socium' (social dynamics, norms, rules), and 'subject-system' (program, algorithm, goals). * Interchangeability: The terms 'human factor' and 'subjective factor' are considered interchangeable. However, 'consciousness' is noted as a factor that can introduce systemic errors due to linguistic and functional-logical complexities.

Methodological Approach: * The study uses a structured-logical summary, defining concepts, principles, terms, and their application. * It differentiates between a methodological (theoretical) part and a mathematical-analytical (empirical) part. * The research aims to analyze, evaluate, calculate, compare, and confirm the structural elements of systems. * Key concepts explored include 'uniqueness,' 'regularity,' 'necessity,' 'activity,' 'utility,' and 'potentiality.' * The analysis distinguishes between 'manifested' ('proyavlennoye') and 'unmanifested' ('neproyavlennoye') states of systems and their elements. * The dynamics of systems are examined, considering 'manifested' and 'unmanifested' states, and how they relate to the 'subjective factor.'

Bibliography A list of 8 references is provided, primarily consisting of handwritten materials and reports related to anomalous aerospace phenomena, with authors like Mantulin V.S., Tarasenko A.A., and Belenky A.V. The dates range from 1983 to 1985, with locations like Kharkiv and the Ukrainian SSR mentioned.

Recurring Themes and Editorial Stance The recurring themes are the detection and analysis of anomalous aerial objects (UAP) using radar technology and the theoretical exploration of the 'subjective factor' in understanding complex systems. The editorial stance appears to be analytical and research-oriented, aiming to provide both empirical data from UAP sightings and a theoretical framework for understanding human and systemic interactions. There's a clear emphasis on improving flight safety through better detection and analysis of unidentified phenomena.

This issue of "Nauka i Tekhnika" (Science and Technology) from October 1993, issue number 10, delves into complex theoretical concepts related to system analysis, methodology, and the nature of subjectivity. The articles explore the distinction between 'manifested' and 'unmanifested' states within systems, the role of intellect and the 'subjective factor,' and various modeling approaches.

Key Concepts and Methodologies

The central theme revolves around the 'subjective factor' and its implications for understanding systems. The issue introduces the idea of 'manifested' (проявленное) and 'unmanifested' (не проявленное) states. 'Manifested' states are characterized by visible functionality and positive values, representing what is observable and measurable. In contrast, 'unmanifested' states are associated with negative values, indicating processes that are not readily apparent or are hidden. These concepts are illustrated with graphical representations showing the relationship between variables like Z (state) and t (time).

Methodologically, the articles emphasize the importance of abstract analysis and modeling. The concept of 'game modeling' (Игромоделирование), developed by O.S. Anisimov, is presented as a tool for understanding these complex phenomena. This approach aims to create abstract representations of systems and their dynamics, considering both the 'manifested' and 'unmanifested' aspects.

The Role of the Subject and Intellect

A significant portion of the content is dedicated to the role of the subject in research and within systems. The articles identify three primary roles for a subject: the researcher, the passive observer, and the witness. Each role influences how a system is perceived and analyzed. The concept of 'intellect' is discussed extensively, particularly its increasing attribution to systems themselves, leading to the development of artificial intelligence. The authors note that the 'subjective factor' is becoming a critical element in understanding both living and non-living systems.

Static vs. Dynamic States

The issue also explores the dichotomy of static and dynamic states within systems. 'Static' aspects relate to the stable, inherent properties and functionality, while 'dynamic' aspects concern the processes of change and development over time. The interplay between these two is crucial for a comprehensive understanding of a system's behavior and its 'rule' or 'law' of operation.

Modeling and Abstraction

Subject-oriented modeling is highlighted as a key methodology. This approach involves creating abstract schemes and representations that reflect the system's properties and the subject's interaction with it. The process of interpreting these schemes, whether as visual aids or as objects of study, is influenced by the subject's perception and 'responsibility' for identification. The diagrams provided illustrate how abstract concepts are translated into visual models and how these models can be used to analyze complex processes.

Challenges and Future Directions

The authors acknowledge the difficulty in fully describing the complexities of 'subjective factors' and system dynamics. They point out that while modern technologies like artificial intelligence can account for errors and simulate 'static' rules, understanding the full spectrum of 'unmanifested' phenomena remains a challenge. The research aims to develop new concepts and methodologies to address these complexities, particularly in the context of rapidly evolving socio-informational systems.

Recurring Themes and Editorial Stance

The recurring themes in this issue include the philosophical and methodological exploration of systems, the nature of reality as perceived by a subject, and the application of abstract modeling techniques. The editorial stance appears to be one of rigorous academic inquiry, seeking to define and understand complex phenomena through systematic analysis and theoretical frameworks. The emphasis is on developing a deeper understanding of how systems function, particularly when subjective elements are involved, and how these can be accounted for in scientific research and technological development.

This issue of EIBC, published in 2013, is a "samizdat" (self-published) work focusing on methodological and analytical approaches to understanding complex systems. It delves into the concepts of uniqueness and typicality, exploring how these states manifest within systems and how they can be analyzed.

Schematization and Intellectual Processes

The text begins by discussing the importance of organized and structured forms in visual material, which, when processed through schematization, acquire qualities like structure, permanence, and objectness. This process of image construction is presented as the construction of schemes with their object identification. Schematization is identified as the foundation of all cognitive-intellectual processes.

The Dual Existence of Thought Tools

It is argued that the prototype for the dual existence of thought tools (concepts, ideas) lies here. A tool can exist as a 'predicate' or be used as an object ('subject'). Identification corresponds to a judgment or 'subjectivization of the predicate.' This requires a basis for comparing the content of direct perception (the subject) with the content of the thought tool, accepting them as corresponding under certain assumptions. This comparison provides the basis for selecting the appropriate predicate.

Modeling and System Functioning

Modeling is presented as leading to identified images of system functioning, which would be impossible without abstract-associative analysis. This allows for abstract definition of non-manifest structural elements in their form and meaning, reflecting the rules or norms of system functioning. This process proceeds from the smallest to the most holistic and unique.

When a process is seen as a manifestation of a system's activity and its structural elements, its visibility or invisibility is merely the "tip of the iceberg." 'Manifestation' and 'non-manifestation' are factors of the process, as are statics and dynamics. These factors, along with the subjective factor, create a system prototype that can be mapped directly or inversely onto human perception.

Mathematical-Analytical Part

This section connects the structural-methodological concepts and the understanding of various factors in the measurement of 'human-system' or 'subjective factor' to empirical data from socio-informatics, sociology, information systems, and systems analysis.

Errors and Uniqueness

The research aims to identify 'perceptual errors' or functional systemic errors in the measurement of 'human-system' or 'subjective factor.' These will be investigated within a complex set of data and their sequences. The concepts of uniqueness and usefulness are explored through the lens of human abilities in social dynamics, leading to a framework of 'activity – dynamics – regularity.'

Conceptual Content of 'Ability' and 'Uniqueness'

The identification of subjective perception errors or activity errors, and subsequently, dynamic errors, is examined through the prism of 'abilities' and 'uniqueness.'

'Uniqueness' is described as a phenomenon, a chance occurrence, an unpredictability in any process, determined by action. For science investigating abstract forms and associations, 'uniqueness' is a phenomenon that can be studied and analyzed. Similarly, a 'phenomenon' as a state of a system in its dynamic development can be empirically studied.

'Uniqueness' is synonymous with 'non-repeatability.' It is a state where a system can acquire properties of 'regularity,' even under conditions of unpredictability. This leads to a 'rule': 'form' and 'content' that constitute a holistic 'law,' an algorithm of 'action,' or the action itself, which has a direction (tendency) – a vector, and is driven by one system state to another. The phenomenon of activity arises at the level of the holistic object, defining 'regularity.' Consequently, 'regularity' is limited in time.

If a system enters a 'non-manifest' state, it may cease to exist or become invisible. The 'rule' that generates 'law' and 'regularity' is defined in time, giving rise to the phenomenon of uniqueness. If such states of 'uniqueness' occur with some periodicity within a certain time frame, the process of system 'action' will have 'regularity,' as there is a basis for the 'rule' or 'law' according to which it arises.

Law, Regularity, and System States

It is stated that even without knowing the content of a 'law,' by defining its form, outlines, and dynamics, one can ascertain its existence. By confirming 'regularity,' one confirms the 'law' or their sum.

'Regularity' is a phenomenon that can arise in different systems and have different formulas depending on the system's properties. The focus is on the 'subjective factor.'

Two types of regularities are discussed: those based on conditions of 'uniqueness' and those based on conditions of 'typicality.'

'Uniqueness' (U) is a function of time change (Δt), where Δt represents the time of change in the system's state. Typicality (t) is a constant, meaning the system's state remains unchanged in its development, or its dynamics are stable.

'D=const' signifies that the system's 'form' and 'structure' (content) are morphologically unchanging.

'Uniqueness' and 'typicality' are described as variable forms of a system, representing states where 'uniqueness' is the period of the system's 'emergence,' and 'typicality' is non-variability and relativity of time.

Empirical Part

The examples provided serve as conceptual preparation for mathematical processing and data analysis. The analysis procedure and monitoring use a simple mathematical language.

Figures illustrate the research algorithm and different stages of reaction (situational, critical, problem-oriented, value-problem-oriented).

In the functional-based semantic division of data, a system is divided into directly and inversely reflected parts: 'subjective' and 'objective.' The subjective system is identified with the 'subjective factor,' and the objective with 'norm' (H) – a methodological regularity.

Findings

1. The research has deeply analyzed the concept of formation and development of socio-information systems, their internal structure ('content'), while subtly addressing their 'form.' The focus is on what is within the system, not the system as a whole.
2. The 'subjective factor' was chosen as the primary concept because the measurement involves a multitude of socio-information systems. Combining phenomena into a single concept of 'subjective factor' simplifies the analysis.
3. The concept of the 'subjective factor' arises from the beginning of the research process and its formation within this measurement.
4. Analytical methodology is preferred over other analysis methods because it forms a new concept and its factors. It requires comparison and identification with the terminology of related sciences.
5. The empirical part is included in the mathematical-analytical structure to determine not only the set of factors but also their functioning over time, revealing the quantitative composition of the system in its dynamics. The dynamics of any system, its norms, and rules establish its regularity over time.
6. The emphasis on an abstract-associative format (drawings, models, schemes) is due to the analysis of the methodology, concepts, and the new concept itself, simultaneously at the level of methodological 'norms,' 'predicates,' and other analytical forms, including constant identification.
7. The empirical part provides a concrete level of information representation, moving beyond abstract embodiment. Digital format is a scientifically grounded form of abstract representation, allowing for analysis at a different level using mathematical-statistical tasks.

The analytical algorithm used structurally measures the analysis format and delves into the relevant scientific and methodological areas.

Recurring Themes and Editorial Stance

The recurring themes revolve around the philosophical and methodological underpinnings of system analysis, particularly the distinction and interplay between subjective and objective factors. The issue emphasizes the importance of rigorous analytical methods, including abstract-associative analysis and mathematical modeling, to understand complex phenomena like uniqueness and typicality. The editorial stance appears to be one of promoting a scientific and analytical approach to understanding complex systems and phenomena, as exemplified by the work of the EIBC organization.