Prediction Of Future Development Research Articles

The Evolution of Artificial Intelligence: From Assistance to Super Mind of Artificial General Intelligence? Article 2. Artificial Intelligence: Terra Incognita or Controlled Force?

The article is devoted to the history of the development of ICT and AI, their current and expected future achievements, and the problems (which have already arisen but will become even more acute in the future) associated with the development of these technologies and their widespread application in society. It shows the close connection between the development of AI and cognitive science, the penetration of ICT and AI into various spheres, particularly health care, and the very intimate areas related to the creation of digital copies of the deceased and posthumous contact with them. A significant part of the article is devoted to the analysis of the concept of ‘artificial intelligence’, including the definition of generative AI. The authors analyse recent achievements in the field of Artificial Intelligence. There are given descriptions of the basic models, in particular the Large Linguistic Models (LLM), and forecasts of the development of AI and the dangers that await us in the coming decades. The authors identify the forces behind the aspiration to create AI, which is increasingly approaching the capabilities of the so-called general/universal AI, and also suggest desirable measures to limit and channel the development of artificial intelligence. It is emphasized that the threats and dangers of the development of ICT and AI are particularly aggravated by the monopolization of their development by the state, intelligence services, major corporations and those often referred to as globalists. The article provides forecasts of the development of computers, ICT and AI in the coming decades, and also shows the changes in society that will be associated with them. The study consists of two articles. The first, published in the previous is-sue of the journal, has provided a brief historical overview and characterized the current situation in the field of ICT and AI. It has also analyzed the concepts of artificial intelligence, including generative AI, changes in the understanding of AI related to the emergence of the so-called large language models and related new types of AI programs (ChatGPT and similar models). The article has discussed the serious problems and dangers associated with the rapid and uncontrolled development of artificial intelligence. This second article describes and comments on the current assessments of breakthroughs in the field of AI, analyzes various predictions, and provides the authors' own assessments and predictions of future developments. Particular attention is paid to the problems and dangers associated with the rapid and uncontrolled development of AI, with the fact that advances in this field become a powerful means of control over the population, imposing ideologies, priorities and lifestyles, influencing the results of elections, and a tool to undermine security and geopolitical struggles.

Extending the boundaries of financial reporting in the extractive industries: Insights from bibliometric analysis

AbstractFinancial reporting in extractive industries (EIs) is a crucial function that warrants further attention in the literature. Previous studies have identified several issues related to financial reporting quality, its impact on stock prices, and the relationship between financial reporting and corporate governance. However, significant gaps remain in understanding the impact of the extractive industry's unique characteristics and the role of regulators in enhancing financial reporting practices. This study aims to illuminate the research trajectory affecting extractive firms by describing the state‐of‐the‐art regarding related accounting standards through a mapping of currently accessible studies. To achieve this, we applied a bibliometric analysis methodology. Bibliometric techniques provide a quantitative approach for objectively assessing literature, offering a comprehensive overview of influential authors, journals, themes, and countries within a specific research field. This approach also facilitates the identification of research trends and the prediction of future developments. The study highlights the growing demand for sustainability reports as the primary formalized means for companies to disclose their sustainable development efforts. Research on sustainability reporting in the mining sector underscores the importance of integrated sustainability reporting, with a focus on understanding the evolution and advancement of reporting methodologies across all dimensions of corporate social responsibility.

REGULATION OF FINTECH INNOVATIONS THROUGH POLICY FRAMEWORKS: ENSURING CONSUMER PROTECTION WHILST PROMOTING INNOVATION

The emergence of FinTech technologies has prompted the creation of extensive regulatory frameworks that safeguard consumer interests while promoting an atmosphere that is supportive of technical progress. This study explores the complex regulatory environments that shape FinTech advances, primarily emphasizing the need to find a careful balance between protecting consumer interests and promoting innovation. This paper investigates crucial steps intended to strengthen consumer protection by undertaking a thorough review of worldwide regulatory procedures, including variances among countries and the crucial roles of governmental agencies. These controls cover a wide range of tactics, from the application of know-your-customer (KYC) and anti-money laundering (AML) procedures to strict transparency requirements and strong privacy protections. The report also looks at the procedures in place in the FinTech industry for handling customer complaints and guaranteeing accountability. In addition, the study explores different approaches to innovation in the regulatory environment, including the creation of regulatory sandboxes and the encouragement of joint ventures between industry players and regulatory bodies. This paper illustrates both effective regulatory interventions and difficulties found in regulating FinTech developments through the analysis of relevant case studies. These observations are combined to provide a set of practical suggestions that legislators can use to successfully navigate the changing regulatory environment around fintech. The report also provides predictions for future developments in FinTech legislation, giving decision-makers the insight they need to adjust to the ever-changing FinTech landscape.

Testate amoebae (Protozoa) in lakes of the Qinghai-Tibet Plateau: Biodiversity, community structures, and protozoic biosilicification in relation to environmental properties and climate warming

The Qinghai-Tibet Plateau (QTP) is characterized by a vast number of frozen and unfrozen freshwater reservoirs, which is why it is also called “the third pole” of the Earth or “Asian Water Tower”. We analyzed testate amoeba (TA) biodiversity and corresponding protozoic biosilicification in lake sediments of the QTP in relation to environmental properties (freshwater conditions, elevation, and climate). As TA are known as excellent bio-indicators, our results allowed us to derive conclusions about the influence of climate warming on TA communities and microbial biogeochemical silicon (Si) cycling. We found a total of 113 TA taxa including some rare and one unknown species in the analyzed lake sediments of the QTP highlighting the potential of this remote region for TA biodiversity. >1/3 of the identified TA taxa were relatively small (<30 μm) reflecting the relatively harsh environmental conditions in the examined lakes. TA communities were strongly affected by physico-chemical properties of the lakes, especially water temperature and pH, but also elevation and climate conditions (temperature, precipitation). Our study reveals climate-related changes in TA biodiversity with consequences for protozoic biosilicification. As the warming trend in the QTP is two to three times faster compared to the global average, our results provide not only deeper insights into the relations between TA biodiversity and environmental properties, but also predictions of future developments in other regions of the world. Moreover, our results provide fundamental data for paleolimnological reconstructions. Thus, examining the QTP is helpful to understand microbial biogeochemical Si cycling in the past, present, and future.

A review of visual SLAM with dynamic objects

PurposeThis paper aims to provide a better understanding of the challenges and potential solutions in Visual Simultaneous Localization and Mapping (SLAM), laying the foundation for its applications in autonomous navigation, intelligent driving and other related domains.Design/methodology/approachIn analyzing the latest research, the review presents representative achievements, including methods to enhance efficiency, robustness and accuracy. Additionally, the review provides insights into the future development direction of Visual SLAM, emphasizing the importance of improving system robustness when dealing with dynamic environments. The research methodology of this review involves a literature review and data set analysis, enabling a comprehensive understanding of the current status and prospects in the field of Visual SLAM.FindingsThis review aims to comprehensively evaluate the latest advances and challenges in the field of Visual SLAM. By collecting and analyzing relevant research papers and classic data sets, it reveals the current issues faced by Visual SLAM in complex environments and proposes potential solutions. The review begins by introducing the fundamental principles and application areas of Visual SLAM, followed by an in-depth discussion of the challenges encountered when dealing with dynamic objects and complex environments. To enhance the performance of SLAM algorithms, researchers have made progress by integrating different sensor modalities, improving feature extraction and incorporating deep learning techniques, driving advancements in the field.Originality/valueTo the best of the authors’ knowledge, the originality of this review lies in its in-depth analysis of current research hotspots and predictions for future development, providing valuable references for researchers in this field.

Problems related to critical terminology and educational efforts to reduce them

The current research aims primarily to identify the various issues related to the critical terminology and the educational efforts to mitigate them, by discussing the nature of critical terminology, its main functions, formulation mechanisms, and the multiple problems associated with it. This research also offers recommendations to overcome these issues. To achieve these objectives, a historical methodology is employed to analyze and interpret the problems of critical terminology, based on past experiences and predictions of future developments. The study concludes that there is chaos and ambiguity in the field of Arabic criticism, due to the lack of consensus on translating and transferring Arabic terminologies. Additionally, the translation of terminologies is afflicted with disruption and disorder resulting from language challenges and the neglect of proper methods for translation and formulation of terminologies, emphasizing the role of education through linguistic institutions, linguistic committees, and the efforts of Arab researchers in mitigating these problems related to critical terminology.

Integrated geological assessment and numerical simulation for Olkaria's East and Southeast geothermal fields

Olkaria East and Southeast geothermal fields are located in the East African Rift System and are approximately 120 km from Nairobi, Kenya. It was the first geothermal field in the country to start power production in 1981 Unit I (15 MWe). It has steadily increased its capacity from Olkaria I-VI units to 278.3 MWe (2022). Despite the steady increase in power generation, there has been a notable pressure decline of 10–15 bars. To ensure optimum resource utilization, a frequent appraisal is necessary to track productivity and management practices that will guide future investments. Reservoir simulation using TOUGH 2 computational code was employed to assess natural geo-controlling structures for optimal productivity and prediction of future developments in the geothermal field. A summarized review of geological and geochemical features was used to determine input parameters for the numerical model and assigned fault and reservoir rock properties were computed using temperature-dependent fluid movement equations which reduce the ambiguity involved in the trial-and-error approach used to construct a conceptual model. The initial state model was calibrated using measured temperature and pressure profiles from 16 wells. Subsequently, the production and reinjection model was set up to investigate reservoir performances before and after reinjection. Different water reinjection scenarios were tested with changing well location (infield and outfield), well depth and recharge rate. It was discovered that declining pressure trends up to 19 bars after a period of 29 years when 1656 t/hr mass is extracted while 42% water reinjection occurs. The extraction of 717 t/hr from new wells caused a further decline in production life to 13 years. The optimum reinjection program depended on recharge rate, well location and depth interval to mitigate reservoir pressure decline and thermal breakthrough. This study suggested hot and condensate water reinjection of 1530 t/hr (74% of extracted fluid) south of Olkaria East field.

Mapping the global research landscape and hotspot of exercise therapy and chronic obstructive pulmonary disease: A bibliometric study based on the web of science database from 2011 to 2020.

Background: The application of exercise therapy (ET) in chronic obstructive pulmonary disease (COPD) is generating increasing clinical efficacy and social-economic value. In this study, research trends, evolutionary processes and hot topics in this field are detailed, as well as predictions of future development directions. Methods: Search for literature in the field of COPD and ET and analyze data to generate knowledge graphs using VOSiewer and CiteSpace software. The time frame for the search was from 2011 to January 2021. Then we extracted full-text key information (such as title, journal category, publication date, author, country and institution, abstract, and keyword) and obtained the co-citation analysis. Use hierarchal clustering analysis software developed by VOSviewer to map common citations, and use Citespace software to plot trend networks. Results: The United States topped the list with 27.91% of the number of articles posted, followed by the UK at 25.44%. Imperial College London was the highest number of article publications in institutions, followed by Maastricht University and the University of Toronto. The Royal Brompton Harefield NHS Foundation Trust was one of many research institutions and currently holds the highest average citations per item (ACI) value, followed by Imperial College London and the University of Leuven. Judging from the number of publications related to ET and COPD, it is mainly published in cell biology, respiratory pulmonary diseases, and rehabilitation experiments study medicine. The European Respiration Journal is the most widely published in this field, followed by the International Journal of Chronic Obstructive Pulmonary Disease and Respiratory Medicine. Conclusion: COPD combined with ET is widely used in clinical practice and is on the rise. A distinctive feature of the field is multidisciplinary integration. Rehabilitation research for COPD involves multidisciplinary collaboration, tissue engineering, and molecular biology mechanism studies to help patients remodel healthy breathing. Multidisciplinary rehabilitation measures provide a solid foundation for advancing clinical efficacy in the field of COPD.

An Optimization Analysis Model of Tourism Specialized Villages Based on Neural Network and System Dynamics

With the rapid development of tourism, professional tourism villages emerge one after another, which has become the focus of the tourism industry. At present, there are some problems in tourism professional villages, such as imperfect management and inaccurate prediction of future development, which affect the rational allocation of tourism resources. In order to improve the distribution of tourism resources and better predict the development of tourism professional villages, it is necessary to make comprehensive judgment and analysis, especially the analysis of indicators such as the prediction and development judgment of tourism professional villages. This paper discusses the optimization analysis of the agglomeration of tourism specialized villages by backpropagation (BP) neural network and system dynamics model, analyzes the system structure of the agglomeration factors of tourism specialized villages, and promotes the intelligent integration of the agglomeration factors. The development of clusters of professional villages promotes data integration among resources, economy, society, and other elements and presents the characteristics of big data. As the level of concentration of professional villages increases, the complexity of the associated factors also increases, which increases the difficulty and effectiveness of tourism analysis. In view of this situation, taking mountain tourism as the research object, this paper proposes an improved system dynamics model based on BP, extracts features from cross factor (resource, economic, and social) data, and optimizes the relationship between professional village agglomeration and various factors. The MATLAB simulation results show that based on the improved system dynamics analysis, the simplification rate of (resources, economy, and society) data can be controlled at more than 24%, the degree of agglomeration is more than 95%, and the construction time of the relationship map of related factors is less than 40 s. Therefore, the analysis method proposed in this paper is suitable for the calculation of the agglomeration of tourism professional villages in the mountain area and can meet the needs of the development of tourism professional villages in the mountain area.

Climatic and Anthropogenic Drivers of Forest Succession in the Iberian Pyrenees during the Last 500 Years: A Statistical Approach

Anticipating future successional forest trends in the face of ongoing global change is an essential conservation target. Mountain forests are especially sensitive to environmental shifts, and their past responses to climatic and anthropogenic (external) drivers may provide a basis for improving predictions of future developments. This paper uses independent high-resolution palynological and paleoclimatic reconstructions to statistically analyze the long-term effects of external drivers on regional forest succession in the central Iberian Pyrenees during the last 500 years. The statistical methods used are Gaussian response analysis, cluster analysis, rate-of-change analysis, principal component analysis, and redundancy analysis. The dominant taxa of these forests (Quercus, Betula, Pinus) showed significant relationships with summer temperature, summer drought, and autumn precipitation. Immediate and delayed (by two or more decades) responses of these trees to climatic drivers were identified. Regional succession showed a closed path, starting at the end points around the attraction domain of pine-dominated forests. This trajectory was determined by a trend toward anthropogenic forest clearing (16th to 18th centuries) and a reverse trend of natural forest recovery (18th to 20th centuries). Forest clearing was due to burning, facilitated by drought, and was followed by the expansion of cropping and grazing lands. Forest recovery was fostered by reduced human pressure and rising temperatures. The statistical approach used in this work has unraveled ecological relationships that remained unnoticed in previous works and would be important for predicting future successional trends under changing climates. The reported response lags of individual taxa to climatic drivers may complicate the establishment of reliable ecological relationships and should be addressed in future studies.

Prediction of supply and demand for jobs in the Czech Republic

The topic of supply and demand for jobs is a very current and important topic, as their prediction contributes to the future operation of an organization. The base source of data is information and data obtained from online databases of the Ministry of Labor and Social Affairs of the Czech Republic. The aim of this work is to predict the supply and demand for jobs up to 2022, using the method of exponential alignment of time series. With the existence of natural unemployment, not all job positions will be filled. In such a situation, organizations will have to demand labor from abroad. In the event that organizations are unable to secure labor from abroad, they will have to reduce their activities and the associated volume of production they produce. Last but not least, the organization can start going bankrupt. In the forecast, we do not address the structure of unemployment by the highest attained education or by profession. We see the application benefits of the work in companies that manage human resources. At present, the prediction of future development is mostly at the national level and in the Czech Republic it is at the beginning of its journey. The developed methodology will enable organizations to monitor the current situation on the labor market and respond to changes in the short and long term.

Impact of COVID 19 on the provision of services by public administration

Research background: The digitization of public administration processes has helped the functioning of the public sector at a time when the health of citizens is threatened by the virus. The economic sustainability of public administration has its place in government programs as an important means of modernizing, supporting, and optimizing the functioning of the public sector, improving public services. It focuses on a sustainable state in an emergency, or in times of crisis. Purpose of the article: The aim of the paper is to analyze and compare electronic services provided by public administration to citizens, businesses before and after the corona virus. The above analysis was supplemented by a questionnaire survey among citizens, entrepreneurs of the Slovak Republic focusing on the satisfaction of electronic public administration services at the time of the corona virus. Methods: The article applied the analysis and comparison of the state of provided electronic services before and after the corona virus. Prediction of future development was determined based on available data, by ex-ante analysis using the method of simple moving averages. An additional method of research was primary research satisfaction. Findings &amp; Value added: An important milestone in the time of the coronary virus pandemic is the optimization of systems, services, and the strengthening of intervention capacities for emergency management. The findings presented in the paper point to changes related to the economic development of the state economy, changes in employment in the labor market and planned measures to rehabilitate the damage caused by COVID 19.

The Concept of Railway Transport in the Czech Republic

The contribution focuses on the position of rail logistics in the transport market in the Czech Republic. In the context of the drive for an even division of transport work between modes, a survey has been carried out on the development of rail transport since 2010. Based on correlation and regression analysis, predictions for future development have been established concerning to transport flows of goods on import or export by rail. These predictions are very important in the feasibility studies of track reconstruction. The lack of capacity of the main corridors should be addressed in the light of the development and need for capacity enhancement of individual lines, rather than the current estimates of the transport companies, which do not have information on their future contracts.

Prediction of Underground Space Development Function of Existing Industrial District in City Based on CA-Markov Model

Scientific analysis of the spatial evolution of existing industrial areas in cities and prediction of future development needs will help to rationally allocate land resources in existing industrial areas in urban renewal, scientifically and rationally develop underground space, and promote the sustainable development of existing industrial areas. First of all, the development mode and leading function type of the existing industrial zone in the city are sorted out, and its corresponding underground space development function is further sorted out. It is found that the underground space development of the existing industrial zones in the city is closely related to the dominant functions and location of the ground renewal. To scientifically guide the development of underground space in existing industrial areas in cities, this study proposes a method based on the dynamics model and the CA-Markov model to predict the functions of underground space development in existing industrial areas in cities, which will improve the efficiency and Benefits to promote the rational allocation of land resources is of great significance.

A Survey of Nash Equilibrium Strategy Solving Based on CFR

Recently, with the rapid development of artificial intelligence technology, there are growing researchers drawing their attention on the field of computer game. In two-player zero-sum extensive games with imperfect information, counterfactual regret (CFR) method is one of the most popular method to solve Nash equilibrium strategy. Therefore, we have carried on a wide range of research and analysis on the CFR and its related improved methods in recent years. In this paper, we firstly introduce the process of solving the strategy of Nash equilibrium based on CFR method. Then, some related improved methods of CFR are reviewed. The bare extended experiments are carried out to help researchers to understand these methods more conveniently. Further, some successful applications and common test platforms are described. Finally, the paper is ended with a conclusion of CFR-based methods and a prediction of future development.

Medical Image Intelligent Recognition Predicts the Recessivity Variation of Human Tissue

By analyzing and predicting the latent variation of human tissues, the concept of iterative programming of heavy kernel clustering is introduced to solve the problem of intelligent recognition of medical images of inflammation and cancer. Inflammatory cells modify the accumulation of cancer cells and leap to the early stage of cancer, which is called image entropy. The hypercomplex symmetric structure of the edge sliding kernel of the entropy kernel of high-dimensional <i>s</i>≥ 6 image. As well as the fusion of image entropy nucleus dumbbell double sphere complex sphere, the exchangeability of the central source extreme compression line sink; the central source superstring sink compresses to the critical point, and the unconstrained <i>2N + 1</i> laminated incision will cause the high-dimensional superstring sink to break up and release the exfoliated cells. Non analytic exploitation is the inverse kernel factor of aidicom that can judge the entropy of latent tissue variation image from inflammation to early cancer. It is a foundation of revealing (predicting) system recognition data array, and can carry the first-order and second-order partial differential carriers of kernel core area. In the medical image, the identification of inflammation and cancer often troubles doctors. Based on the inherent logic between cell modification fluctuation and image, aidicom system gives the concept of image entropy, and uses the dieg algorithm to complete the classification of focus detection and recognition, as well as the prediction of future development.

Simulating urban land use and cover dynamics using cellular automata and Markov chain approach in Addis Ababa and the surrounding

Efficient Land Use and Land Cover (LULC) monitoring and management require awareness of previous dynamics, current trends, and predictions of future developments. Understanding such an urban dynamics is, thus, necessary to deliberate a proper urban growth management approach. The study is aimed to simulate the LULC dynamics and develop a scenario-based LULC prediction for sustainable urban growth planning and management in the case of Addis Ababa and the surrounding area. The research employed a hybrid Cellular Automata, Markov chain (CA-Markov) and Multi-criteria Analytical Hierarchy Process (AHP) modeling approach. Accordingly, the research depicted continuous historical increment of Built-up spaces by consuming other ecologically valuable LULC classes. The quantitative measures of landscape metrics confirmed the benefit of Ecologically Sensitive Scenario (ESS) modeling as compared to Business As Usual Scenario (BAUS) as it keeps the dynamism of the city region more sustainable. ESS modeling enables an urban system to grow into a better way by making built-up augmentation relatively mild and controlling water bodies, forests and cultivated land losses. Therefore, this scenario-based simulation of the LULC dynamics providing decision-making options for those who strive for sustainable urban growth planning and management not only in the study region but also other similar cities.

The Future of Concussion

Over the past 2 decades, concussion care is increasingly in demand as research and media attention shed light on the importance of proper diagnosis and medical management to prevent complex, potentially disabling sequelae. The purpose of this review is to discuss the future of clinical concussion care across selected topics under the broad themes of diagnosis/assessment, intervention/treatment, and patient characteristics/presentations with the intent to direct clinicians' attention to important anticipated developments in the field. The current status of biomarkers, clinical settings, models of clinical concussion, return-to-activity, clinical subpopulations, treatment approaches, patient perceptions of injury, and social media are reviewed along with predictions for future developments.

Contrasting patterns of naturalized plant richness in the Americas: Numbers are higher in the North but expected to rise sharply in the South

AbstractWith increasing availability of plant distribution data, the information about global plant diversity is improving rapidly. Recently, Ulloa Ulloa et al. (2017) presented the first comprehensive overview of the native vascular flora of the Americas, yielding a total count of 124,993 native species. Of these, 51,241 occur in North America and 82,052 in South America. By combining these data with the information in the Global Naturalized Alien Flora (GloNAF) database of naturalized alien floras, we point out that for a complete picture of the regional and continental plant richness, the naturalized alien species need to be considered. Ignoring this novel component of regional floras can lead to an inaccurate picture of overall change in biodiversity in the Anthropocene. We show that North and South America might face contrasting challenges in terms of potential threats to biodiversity posed by alien plant species, because of the different past and present dynamics of invasions and predictions of future development. In total, there are 7,042 naturalized alien plants occurring in the Americas, with 6,122 recorded in North America and 2,677 in South America; if only introductions from other continents are considered additions to the native continental flora make up 6.9 and 1.4 %, respectively. Nevertheless, predictions of naturalized plant trajectories based on global trade dynamics and climate change suggest that considerable increases in naturalized plant numbers are expected in the next 20 years for emerging South American economies, which could reverse the present state.

Klippel–Feil syndrome: A rare case and its management

A relatively smaller number of orthodontic patients are affected by known craniofacial anomalies that affect oral and dental tissues. The greatest advantage in knowing that a patient has a particular syndrome is that it allows a much better prediction of future development that might happen in such individual and necessary precautions to be taken while management of these cases. This case report provides features of a patient with Klippel–Feil syndrome and orthosurgical management of an adult male to effectively improve patient esthetics and function.