This chapter argues that our self-knowledge is often mediated by our affective self-knowledge. In other words, we often know about ourselves by knowing our own emotions. More precisely, what Cassam has called “substantial self-knowledge” (SSK), such as self-knowledge of one's character, one's values, or one's aptitudes, is mediated by affective forecasting, which is the process of predicting one's emotional responses to possible situations. For instance, a person comes to know that she is courageous by predicting her own emotional reactions (...) to possible risks and dangers. This hypothesis explains why attaining substantive self-knowledge tends to be difficult. Attaining substantive self-knowledge is difficult because, first, SSK is mediated by affective forecasting and, second, we tend to be wrong about predicting the intensity and duration of our own emotional reactions. As a result, we can identify what is common to central cases of SSK: such cases require knowledge about complex dispositions whose manifestations involve affective responses that one is not sufficiently familiar with. One thus needs to resort to the highly fallible method of affective forecasting. (shrink)

This article presents a two level hierarchical forecasting model developed in a consulting project for a Brazilian magazine publishing company. The first level uses a VARMA model and considers econometric variables. The second level takes into account qualitative aspects of each publication issue, and is based on polynomial networks generated by Genetic Programming (GP).

Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights (...) into the dynamics of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

Abstract: Accurate stock price prediction is essential for informed investment decisions and financial planning. In this research, we introduce an innovative approach to forecast stock prices using an Artificial Neural Network (ANN). Our dataset, consisting of 5582 samples and 6 features, including historical price data and technical indicators, was sourced from Yahoo Finance. The proposed ANN model, composed of four layers (1 input, 1 hidden, 1 output), underwent rigorous training and validation, yielding remarkable results with an accuracy of 99.84% and (...) an average error of 0.005. Additionally, we conducted a feature importance analysis, identifying the key drivers of stock price prediction, such as "High," "Low," "Open," "Volume"," and "Date." This study not only offers a highly accurate stock price prediction model but also contributes valuable insights into the influential factors affecting stock prices, enhancing the field of financial analysis and investment decision-making that are suitable for the task. (shrink)

The book will be useful for economists, finance and valuation professionals, market researchers, public policy analysts, data analysts, teachers or students in graduate-level classes. The book is aimed at students and beginners who are interested in forecasting modeling and analytics of economic processes and want to get an idea of its implementation.

Analyzing and modeling interconnections between crucial factors of human development, rates of growth thereof and elasticity of the growth rates, the authors have defined specific periods of the development and have made a forecast for the dynamics of the human resources development. Those periods have been defined more exactly and arranged as follows: the first one – «Before Christ»; the second one – «Early Medieval» (1–1100 a.d.); the third one – «Advanced Medieval» (1101–1625); the forth one – «Pioneer’s Modernization» (1626–1970); (...) the fifth one – «Industrialization» (1871–2030) and the sixth one – «Informational society» – after 2030. The results received enable to make forecasts of the global factors dynamics, to find out unified solutions in socio-economic sphere, to define tendencies in social development and to build up unified strategic approaches for modeling global influence on human resources. (shrink)

The purpose of the study is to forecast the number of passengers transported by air in the United States for 2021-2022. The forecast is preceded by a multidimensional comparative analysis of the number of passengers transported by air in the United States from 1 January 2019 to 2 November 2021. To achieve this goal, the data were grouped as dependent variables: years, months-years. The observed similarities, the analysis and evaluation of the literature as well as the own experience made it (...) possible to forecast primary data for the future. The obtained results show a growing trend in the number of passengers transported by air in the United States. The forecast for 3 November 2021 to 31 December 2022 is 837 459 877 prospective air passengers in the United States. The standard deviation of the obtained forecast was 255 680,3, the arithmetic mean was 1 975 141 passengers and the median was 1 998 478 passengers. The observed similar trends in the identical months of July-October in 2019 and 2021 as well as the analysis of the literature and the own experience allowed for the selection of a method for the forecasting of the number of passengers transported by air in the United States for the future. The detected regularities as recurring trends in the number of air passengers transported in the United States on a dynamic basis may be used to forecast them for the future. (shrink)

We investigate the application of Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and a hybrid CNN-LSTM model for forecasting air pollution levels based on historical data. Our experimental setup uses real-world air quality datasets from multiple regions, containing measurements of pollutants like PM2.5, PM10, CO, NO2, and SO2, alongside meteorological data such as temperature, humidity, and wind speed. The models are trained, validated, and tested using a split dataset, and their accuracy is evaluated using performance metrics like (...) Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared. (shrink)

The rapid advancement of intelligent computing has revolutionized the field of economic forecasting, providing unprecedented capabilities for developing, implementing, and analyzing advanced prediction models. This paper explores the comprehensive process of harnessing intelligent computing for economic forecasting, emphasizing the critical stages of model development, integration, and evaluation. Initially, it discusses data collection and preprocessing techniques essential for building robust models, followed by the selection of suitable statistical, machine learning, and deep learning algorithms. The paper then outlines the practical (...) aspects of model implementation, including real-time data integration, deployment strategies, and scalability considerations. Further, it delves into the continuous monitoring and maintenance required to ensure model accuracy and reliability over time. The analysis section evaluates model performance using various accuracy metrics, scenario analyses, and visualization techniques to provide actionable insights. Through case studies across the financial sector, government policy, and business planning, the paper illustrates the transformative impact of intelligent computing on economic forecasting. The findings underscore the potential of advanced prediction models to enhance decision-making, anticipate economic trends, and respond proactively to dynamic economic environments. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...) % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

Bakery products are very important in human nutrition and are the basis of any daily diet. Their social significance is determined by the traditions and habits of the population of the countries, accessibility for all groups of the population, diverse assortment, including bakery products for functional and specialized purposes. The up-to-date trend is to expand the assortment of functional bakery products, the use of which will provide the body’s need for the necessary macro- and micronutrients for an active and healthy (...) lifestyle. In the bread and bakery products market, consumer preferences are constantly changing. Consumers prefer products that contain less fat and sugar. The market is in demand for bakery products that are healthy, while taste remains an important success factor. Manufacturers include popular healthy additives (grains, seeds and legumes) in their products. Particularly popular at present are ingredients from Eastern Europe and Asia: yuzu, sesame, matcha, shiso. Tropical fruits (passion fruit, mango, bergamot) and fragrances (dried hibiscus, lavender and rose) are predicted to become popular. This causes the complexity of demand segmentation, features of merchandising and pricing policy, features of consumer behavior and consumption psychology, etc. An assessment is given of the dynamics of production and consumption of bread and exports of products, and a forecast is made for the development of the world market for bread and bakery products. The results of the analysis are necessary to assess the level of food safety and to develop a strategy that takes into account the current trends in the global bread and bakery products market. Prospective trends for sustainable production of frozen bakery products have been developed. (shrink)

Generally, we confidently ascribe valuing states to ourselves. We make statements such as “I value democracy” or “I value my best friend” - our sense of who we are depends on doing so. Yet what justifies that confidence? If you were asked “Do you value philosophy, or are you just doing it for the money?”, how might you go about generating such knowledge? I will operate with the notion that valuing involves, at a minimum, a set of distinctive emotional dispositions (...) toward the valued object. Given this view of valuing, a plausible explanation stemming from Tooming and Miyazono is the following: to know whether we value, we need to predict our potential or future emotional reactions. That is, they suggest that affective forecasting is necessary to generate knowledge of valuing states. I argue that, despite its intuitive appeal, affective forecasting is not necessary. I then consider a more modest claim, namely that affective forecasting is still explanatorily powerful when it comes to self-knowledge of valuing states, as it explains the difficulty of generating such knowledge. I reject this further claim, arguing that there is a stronger available explanation: the use of theories about valuing. (shrink)

For more than a decade, an aura of discontentment has challenged existing models and theories that have established the structures in various fields of human endeavours such as philosophy, architecture, political science, media, literature, arts and the humanities in general. For instance, the architectural design of what was hitherto referred to as modern building has at least a sitting room (parlour), a kitchen, a bathroom and a toilet as well as two or more number of bedrooms depending on the size (...) of the family, including the master's bedroom. This design was a view that transcended from the old traditional caves and all manner of living spaces that were devised by the early man. The modern concept arose out of man's need to assume a better living status based on his new initiatives. In the field of media and communication, the period of technological evolvement and development that brought about the coinage of descriptive terms such as 'electronic age' and now 'computer age', was preceded by a 'stone age' where the means of communication was prototypical of that archaic society. Though nothing has changed tremendously in interpersonal communication, there are modern means of interpersonal communication made possible by the advent of the telephone. Prior to the advent of this modern technology, interpersonal communication was only made possible in a face-to-face situation or mere errand. Mass Communication in early traditional societies was done with the use of smoke or town-criers who were employed to go round the communities with their gongs to make announcements. This means of communication hardly made it possible for ideas or information to be shared among people who resided in different parts of the world, unlike today. (shrink)

In this paper I argue that J. L. Schellenberg’s Divine Hiddenness Argument is committed to a problematic implication that is weakened by research in cognitive psychology on affective forecasting. Schellenberg’s notion of a nonresistant nonbeliever logically implies that for any such person, it is true that she would form the proper belief in God if provided with what he calls “probabilifying” evidence for God’s existence. In light of Schellenberg’s commitment to the importance of both affective and propositional belief components (...) for entering into the proper relationship with God, this implication of his argument becomes an affective prediction or forecast. However, research in cognitive psychology has shown that in multiple and varied circumstances humans often make inaccurate predictions of their future affective states or reactions. Thus, this research provides strong empirical reasons to doubt that the implication is warranted. (shrink)

The objective of this paper was to identify the level of demand in the Vietnamese fisheries sector for e-Nav – weather and sea condition forecast application developed by NASCA Geosystems. NASCA Geosystems is a small company of five people operating in the field of information technology consulting. Management at NASCA Geosystems wanted to study the Vietnamese market in order to expand their operation in Vietnam. In this thesis, both qualitative and quantitative methods were applied. The quantitative data was gathered from (...) the official statistic sources namely the General Statistics Office of Vietnam, Indexmundi, the United Nations and the World Bank. The qualitative research includes an email interview with the director of NASCA Geosystems and a personal interview with Mr. Tran Dinh Lan from the Institute of Marine Environment and Resources. (shrink)

We investigate the application of Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and a hybrid CNN-LSTM model for forecasting air pollution levels based on historical data. Our experimental setup uses real-world air quality datasets from multiple regions, containing measurements of pollutants like PM2.5, PM10, CO, NO2, and SO2, alongside meteorological data such as temperature, humidity, and wind speed. The models are trained, validated, and tested using a split dataset, and their accuracy is evaluated using performance metrics like (...) Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared. (shrink)

The purpose of this investigation is to develop a new methodological basis for studying the market opportunities of the multinational corporation (MNC) on the basis of the synthesis of modern scientific methods for further forecasting their change. The results showed the degree of dependence of the effectiveness of business management on the trends in the field development and competitor’s actions, market access opportunities, the use of MNC opportunities, their strategic positions, and the totality of internal factors that determine the (...) profitability of activities. The practical value of the obtained results is to identify areas for increasing the efficiency of MNC business management and forecasting the dynamics of sales volumes of their products on the market. (shrink)

The purpose of the research is to study the feasibility of using the combined modeling method in evaluation of business value. Modern approaches and methods of evaluating business value and the possibilities of combining them are explored. The peculiarities of the methodology of evaluating the business value by methods of Gordon Growth Model and Exit Multiple are disclosed. During the research the fair value of Luxoft company and the reasons for its deviation from the cost of sale are found. Luxoft’s (...) business value forecast is calculated by 2023. Recommendations for further development of the field of knowledge of modern business analyst are given. (shrink)

: COVID-19 has proliferated over the earth, exposing mankind at risk. The assets of the world's most powerful economies are at stake due to the disease's high infectivity and contagiousness. The capacity of machine learning algorithms can estimate the amount of future COVID-19 cases, which is now considered a possible threat to civilization. Five conventional measuring models, notably LR, LASSO, SVM, ES, and LSTM, were utilised in this work to examine COVID-19's undermining variables. Each model contains three sorts of expectations: (...) the number of newly contaminated cases, the number of passings, and the number of recoveries. However, it is hard to anticipate the patients' real outcomes. To address the issue, a suggested approach based on long transient memory (LSTM) forecasts the number of COVID-19 cases in the next 10 days as well as the impact of preventative measures such as social isolation and lockdown on COVID-19 spread. (shrink)

This paper adopts two modeling tools, namely, multiple linear regression (MLR) and artificial neural networks (ANNs), to predict the concentrations of heavy metals (zinc, boron, and manganese) in surface waters of the Oued Inaouen watershed flowing towards Inaouen, using a set of physical-chemical parameters. XLStat was employed to perform multiple linear and nonlinear regressions, and Statista 10 was chosen to construct neural networks for modeling and prediction. The effectiveness of the ANN- and MLR-based stochastic models was assessed by the determination (...) coefficient (R²), the sum squared error (SSE) and a review of fit graphs. The results demonstrate the value of ANNs for prediction modeling. Drawing on supervised learning and back propagation, the ANN-based prediction models adopt an architecture of [18-15-1] for zinc, [18-11-1] for manganese, and [18-8-1] for boron, and perform effectively with a single cached layer. It was found that the MLR-based prediction models are substantially less accurate than those based on the ANNs. In addition, the physical-chemical parameters being investigated are nonlinearly correlated with the levels of heavy metals in the surface waters of the Oued Inaouen watershed flowing towards Inaouen. (shrink)

COVID-19 began in China in December 2019. As of January 2021, over a hundred million instances had been reported worldwide, leaving a deep socio-economic impact globally. Current investigation studies determined that artificial intelligence (AI) can play a key role in reducing the effect of the virus spread. The prediction of COVID-19 incidence in different countries and territories is important because it serves as a guide for governments, healthcare providers, and the general public in developing management strategies to battle the disease. (...) The prediction proved beneficial in the early months of 2020 to alert nations and territories in danger of an outbreak, allowing them to take preventative measures. Despite the fact that the COVID-19 outbreak has expanded to practically every location on the planet, the prediction has value in terms of monitoring the intensity of the spread and recovery, as well as determining the likelihood of a sequel or tertiary epidemic. COVID-19, like influenza, could become a seasonal or recurring epidemic in the future. COVID-19 activity must so be predicted and monitored now and in the future. (shrink)

The authors of the scientific monograph have come to the conclusion that мanagement of socio-economic transformations of business processes requires the use of mechanisms to support of entrepreneurship, sectors of the national economy, the financial system, and critical infrastructure. Basic research focuses on assessment the state of social service provision, analysing economic security, implementing innovation and introducing digital technologies. The research results have been implemented in the different models of costing, credit risk and capital management, tax control, use of artificial (...) intelligence and blockchain. The results of the study can be used in the developing of policies, programmes and strategies for economic security, development of the agricultural sector, transformation of industrial policy, implementation of employment policy in decision-making at the level of ministries and agencies that regulate the management of socio-economic and European integration processes. The results can also be used by students and young scientists in the educational process and conducting scientific research on global challenges and creation scenarios for the development of socio-economic processes. (shrink)

According to sentimental perceptualism, affect grounds evaluative or normative knowledge in a similar way to the way perception grounds much of descriptive knowledge. In this paper, we present a novel challenge to sentimental perceptualism. At the centre of the challenge is the assumption that if affect is to ground knowledge in the same way as perception does, it should have a function to accurately represent evaluative properties, and if it has that function, it should also have it in its future-directed (...) imaginative use. As the data on affective forecasting errors indicates, however, the affect system does not have that function. As a result, it is doubtful if affect can do the kind of knowledge-grounding work that sentimental perceptualism assumes it does. (shrink)

This paper is concerned with learners who aim to learn patterns in infinite binary sequences: shown longer and longer initial segments of a binary sequence, they either attempt to predict whether the next bit will be a 0 or will be a 1 or they issue forecast probabilities for these events. Several variants of this problem are considered. In each case, a no-free-lunch result of the following form is established: the problem of learning is a formidably difficult one, in that (...) no matter what method is pursued, failure is incomparably more common that success; and difficult choices must be faced in choosing a method of learning, since no approach dominates all others in its range of success. In the simplest case, the comparison of the set of situations in which a method fails and the set of situations in which it succeeds is a matter of cardinality (countable vs. uncountable); in other cases, it is a topological matter (meagre vs. co-meagre) or a hybrid computational-topological matter (effectively meagre vs. effectively co-meagre). (shrink)

The GOLEM XIV’s forecast for the development of the human civilisation and a typology of technological singularities: In the paper, a conceptual analysis of technological singularity is conducted and results in the concept differentiated into convergent singularity, existential singularity, and forecasting singularity, based on selected works of Ray Kurzweil, Nick Bostrom, and Vernor Vinge respectively. A comparison is made between the variants and the forecast of GOLEM XIV (a quasi-alter ego and character by Stanisław Lem) for the possible development (...) of Homo sapiens civilisation. According to the prediction, the scientific and technological progress is to bring humanity to transfer its civilisational primacy to a nonhuman superhuman intelligence xor a posthuman one. Both scenarios are best described by forecasting singularity, yet all variants are applicable only conditionally. As GOLEM did not undertake, the trajectories may also intersect or combine. (shrink)

The paper deals with the topical issue of studying cyclic patterns in the economy and their practical application for the forecasts on the development of financial markets. The work aims to establish the features of the seasonal-cyclic patterns "The January barometer" and "The first five days of January" in the international financial markets in current conditions and to develop recommendations for the practical application of these patterns in the investment activities. The US stock market as an integral part of the (...) World financial market was chosen as a basis for research. The research was conducted by statistical processing of data on the values of the broad market index Standard & Poor's-500 for the period from 1950 to 2019. The study showed that the formation of forecasts about the annual growth or decline of the stock market index using the seasonal-cyclic patterns "The January barometer" and "The first five days of January" can show a high result in cases where the growth of the Standard & Poor's-500 index by the results of both the first five days of January and the results of the entire month of January of this year is a positive value. Otherwise, forecasting based on these instruments is not advisable. The best results (the forecast efficiency was 93.3%) were achieved with the joint application of both cyclic patterns. The practical application of the research results makes it possible to improve the efficiency of investment activities in international financial markets. (shrink)

Introduction: There is a general agreement among previous studies that gender, merit and catchment area criteria allows for access to university education, but the pattern of these variables over the years has not been proven in these studies. Purpose: This study used a times series approach to evaluate the enrolment patterns in federally owned universities in South-South Zone, Nigeria, based on the gender, merit and catchment area criteria. Methodology: The descriptive survey design was adopted for this study. A purposive sampling (...) technique was adopted to choose three universities based on the generation of their establishment. The evaluation covered from 2010 to 2019 using stationary time-bound data collected from the academic planning units of the institutions through a checklist. Future enrolment forecasts were made to 2031 using the moving average forecasting technique. Results: A gender-based difference in enrolment, in favour of males was recorded between 2010 and 2019; there were notable fluctuations in the enrolment pattern based on the merit criterion from 2010 to 2019; the enrolment pattern in terms of the catchment area criterion was consistent from 2010 – 2019. In terms of the projection, it was predicted that enrolment at the aggregate level would rise continuously across federal universities, but not at the institutional level. more women than men are expected to be enrolled in academic programmes at federal institutions, while at the institutional level, gender-based enrolment can fluctuate. Recommendations/Classroom Implications: Based on these findings, implications are discussed for future enrolment decisions at both the institutional and national levels. (shrink)

The entire world community, since 2019, affected by the global pandemic COVID-19. The pandemic caused by this virus, led not only to significant human losses worldwide, but also imposed significant restrictions on the socio-cultural life of the population and radically changed the trends of the global economy and the further functioning of socio-economic systems. Now, huge economic losses have been recorded, which affected almost all sectors of the national economy and the state in the short, medium and long term. However, (...) it is important to consider individual economic development forecasts and measures developed by the governments of the world’s leading countries to overcome the negative effects of the COVID-19 pandemic. This will allow to form a real vision of the possible course of economic processes that will directly affect the living standards of the population and the restoration of socio-economic systems. To further restore the socio-economic system it is necessary to developing modern strategies and forecasts to ensure the effective functioning of economic entities through innovation, digitalization, marketing and use of competitive advantages in the consumer markets in conditions of limited resources, development promising sectors of the national economy, etc. The purpose of writing this scientific monograph is to substantiate the theoretical and methodological foundations, the formation new strategies for restoring socio-economic systems and overcoming the negative consequences of the caused by the COVID-19 pandemic, taking into account changes and challenges in the modern world. The object of the authors’ research is the process of forming new approaches, strategies and mechanisms for managing socio-economic systems in the context of the COVID-19 pandemic, eliminating the negative consequences in the activities of economic entities. The subject of research is socio-economic, organizational and institutional processes of formation and effective implementation of approaches, strategies and mechanisms for managing socio-economic systems; stabilization of the functioning of economic entities; introduction of innovative processes and digital technologies; implementation of best practices in the managing of socio-economic systems using world experience in various sectors of the economy caused by the COVID-19 pandemic. (shrink)

(Third edition with additions) -/- This is a collection of short stories centering around the protagonist character, Kingfisher, originally written in Vietnamese by myself. -/- The book aims to introduce international readers to snippets of Vietnamese culture through the ordinary yet humorous life of the bird village. -/- The first 15 of these short stories were published in the Khoảng Lặng (Quiet Moment) column of the Vietnamese magazine Kinh Tế và Dự Báo (Economy and Forecast Review) from 2017 to 2019. (...) -/- However, this is the first time that the collection of all the Kingfisher stories has been published in its entirety, covering stories that have not been published elsewhere, including new stories written during 2023-2024. -/- The stories of Kingfisher are full of humor and satire while also deep in social commentary. I hope that the book brings readers joy and some food for thought, for beyond satire is genuine contemplation of the humanistic values in our lives. -/- Hanoi, August 21, 2024 -/- Quan-Hoang Vuong -/- (Incld. Artworks by Bui Quang Khiem and Dam Thi Thu Ha). (shrink)

In Fact, Fiction and Forecast, Nelson Goodman claims that the problem of justifying induction is not something over and above the problem of describing valid induction. Such claim, besides suggesting his commitment to the collapse of the distinction between the context of description and the context of justification, seems to open the possibility that the new riddle of induction could be addressed empirically. Discoveries about psychological preferences for projecting certain classes of objects could function as a criterion for determining which (...) predicates are after all projectible. In this paper, I argue that Goodman's claim must be construed within his project for constructional definitions, which is methodologically oriented by reflective equilibrium. The description of inductive practice is committed to the articulation of the extension of the class selected by the predicate ‘valid induction’. The mutual adjustment between theoretical considerations and inductive practice involved in the proposal of a definition of ‘valid induction’ must preserve that practice as much as possible, there is no way to get rid of entrenchment. Empirical discoveries about the psychological mechanism that underlies projections may help that adjustment but they cannot substitute the role played by the entrenchment of predicates. (shrink)

The article offers forecasts of the geopolitical and geo-economic development of the world in the forthcoming decades. One of the main accusations directed toward globalization is that it deepens the gap between the developed and developing countries dooming them to eternal backwardness. The article demonstrates that the actual situation is very different. It is shown that this is due to the globalization that the developing countries are generally growing much faster than the developed states, the World System core starts weakening (...) and its periphery begins to strengthen. At the same time there is a continuing divergence between the main bulk of developing countries and the group of the poorest developing states. The article also explains why the globalization was bound to lead to the explosive rise of many developing countries and the relative weakening of the developed economies. In the forthcoming decades this trend is likely to continue (though, of course, not without certain interruptions). It is also demonstrated that this convergence constitutes a necessary condition for the next technological breakthrough. (shrink)

Models not only represent but may also influence their targets in important ways. While models’ abilities to influence outcomes has been studied in the context of economic models, often under the label ‘performativity’, we argue that this phenomenon also pertains to epidemiological models, such as those used for forecasting the trajectory of the Covid-19 pandemic. After identifying three ways in which a model by the Covid-19 Response Team at Imperial College London may have influenced scientific advice, policy, and individual (...) responses, we consider the implications of epidemiological models’ performative capacities. We argue, first, that performativity may impair models’ ability to successfully predict the course of an epidemic; but second, that it may provide an additional sense in which these models can be successful, namely by changing the course of an epidemic. (shrink)

In light of the recent emergence of predictive techniques in law enforcement to forecast crimes before they occur, this paper examines the temporal operation of power exercised by predictive policing algorithms. I argue that predictive policing exercises power through a paranoid style that constitutes a form of temporal governmentality. Temporality is especially pertinent to understanding what is ethically at stake in predictive policing as it is continuous with a historical racialized practice of organizing, managing, controlling, and stealing time. After first (...) clarifying the concept of temporal governmentality, I apply this lens to Chicago Police Department’s Strategic Subject List. This predictive algorithm operates, I argue, through a paranoid logic that aims to preempt future possibilities of crime on the basis of a criminal past codified in historical crime data. (shrink)

Longtermists claim that what we ought to do is mainly determined by how our actions might affect the very long-run future. A natural objection to longtermism is that these effects may be nearly impossible to predict — perhaps so close to impossible that, despite the astronomical importance of the far future, the expected value of our present actions is mainly determined by near-term considerations. This paper aims to precisify and evaluate one version of this epistemic objection to longtermism. To that (...) end, I develop two simple models for comparing ‘longtermist’ and ‘neartermist’ interventions, incorporating the idea that it is harder to make a predictable difference to the further future. These models yield mixed conclusions: if we simply aim to maximize expected value, and don’t mind premising our choices on minuscule probabilities of astronomical payoffs, the case for longtermism looks robust. But on some prima facie plausible empirical worldviews, the expectational superiority of longtermist interventions depends heavily on these ‘Pascalian’ probabilities. So the case for longtermism may depend either on plausible but non-obvious empirical claims or on a tolerance for Pascalian fanaticism. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method (...) is suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

The article analyzes the technological shifts which took place in the second half of the 20th and early 21st centuries and forecasts the main shifts in the next half a century. On the basis of the analysis of the latest achievements in inno-vative technological directions and also on the basis of the opportunities pro-vided by the theory of production revolutions the authors present a detailed analysis of the latest production revolution which is denoted as ‘Сybernetic’. The authors give some forecasts (...) about its development in the nearest five decades and up to the end of the 21st century. It is shown that the development of various self-regulating systems will be the main trend of this revolution. The authors argue that at first the transition to the beginning of the final phase of the Cybernetic Revolution will start in the field of medicine (in its some innovative directions). In future we will deal with the start of convergence of innovative technologies which will form the system of MBNRIC-technologies (i.e. the technological paradigm based on medicine, bio- and nanotechnologies, robotics, IT and cognitive technologies). The article gives a detailed analysis of the future breakthroughs in medicine, bio- and nanotechnologies as well as some other technologies in terms of the development of self-regulating systems with their growing ability to select optimum modes of functioning as well as of other characteristics of the Cybernetic Revolution (resources and energy saving, miniaturization, individualization, etc.). (shrink)

In domains like stock brokerage, clinical psychiatry, and long‐term political forecasting, experts generally fail to outperform novices. Empirical researchers agree on why this is: experts must receive direct or environmental learning feedback during training to develop reliable expertise, and these domains are deficient in this type of feedback. A growing number of philosophers resource this consensus view to argue that, given the absence of direct or environmental philosophical feedback, we should not give the philosophical intuitions or theories of expert (...) philosophers greater credence than those of novice philosophers. This article has three objectives. The first is to explore several overlooked issues concerning the strategy of generalizing from empirical studies of non‐philosophical expertise to the epistemic status of philosophical expertise. The second is to explain why empirical research into a causal relationship between direct learning feedback and enhanced expert performance does not provide good grounds for abandoning a default optimism about the epistemic superiority of expert philosophical theories. The third is to sketch a positive characterization of learning feedback that addresses developmental concerns made salient by the empirical literature on expert performance for specifically theory‐driven or “armchair” domains like philosophy. (shrink)

According to the forecast that billions of devices will get connected to the Internet by 2020. All these devices will produce a huge amount of data that will have to be handled rapidly and in a feasible manner. It will become a challenge for real-time applications to handle this huge data while considering security issues as well as time constraints. The main highlights of cloud computing are on-demand service and scalability; therefore the data generated from IoT devices are generally handled (...) in cloud infrastructure. Though, dealing with IoT application requests on the cloud exclusively is not a proficient result for some IoT applications particularly time-sensitive ones. These issues can be settled by utilizing another idea called, Fog computing. Fog computing has become one of the major fields of research from both academia and industry perspectives. The ongoing research commitments on few issues in fog computing are figuring out in this paper. At long last, this paper also highlights some open issues in fog with IoT, which will determine the future research direction for implementing Fog computing paradigm. (shrink)

This paper may be read as a sequel of a 1995 paper, published in this journal, in which I predicted what sort of transformations and problems were likely to affect the development of the Internet and our system of organised knowledge in the medium term. In this second attempt, I look at the future developments of Information and Communication Technologies and try to guess what their impact on our lives will be. The forecast is that, in information societies, the threshold (...) between online and offline will soon disappear, and that once there won't be any difference, we shall become not cyborgs but rather inforgs, i.e. connected informational organisms. (shrink)

Consider two epistemic experts—for concreteness, let them be two weather forecasters. Suppose that you aren’t certain that they will issue identical forecasts, and you would like to proportion your degrees of belief to theirs in the following way: first, conditional on either’s forecast of rain being x, you’d like your own degree of belief in rain to be x. Secondly, conditional on them issuing different forecasts of rain, you’d like your own degree of belief in rain to be some weighted (...) average of the forecast of each. Finally, you’d like your degrees of belief to be given by an orthodox probability measure. Moderate ambitions, all. But you can’t always get what you want. (shrink)

This article articulates a framework for normatively assessing influence operations, undertaken by national security institutions. Section I categorizes the vast field of possible types of influence operations according to the communication’s content, its attribution, the rights of the target audience, the communication’s purpose, and its secondary effects. Section II populates these categories with historical examples and section III evaluates these cases with a moral framework. I argue that deceptive or manipulative communications directed at non-liable audiences are presumptively immoral and illegitimate (...) for liberal states, as are deceptive operations aimed at an unjust end, or even operations aimed at a just end where secondary effects are forecast to be disproportionate to the proximate end. (shrink)

Justice in production is concerned with ensuring the benefits and burdens of work are distributed in a way that is reflective of persons' status as moral equals. While a variety of accounts of productive justice have been offered, insufficient attention has been paid to the distribution of work's benefits and burdens in the future. In this article, after granting for the sake of argument forecasts of widespread future technological unemployment, we consider the implications this has for egalitarian requirements of productive (...) justice. We argue that in relation to all the benefits affiliated with work, other than undertaking social contribution, the technological replacement of work is unproblematic as these benefits could in principle be attained elsewhere. But because social contribution uniquely corresponds to work (when work is understood as more than a paid job), the normative assessment of technological unemployment will turn on the value that theories of justice give to contributive activity. We then argue that despite technological replacement being plainly beneficial insofar as it relieves persons from the burdens of work, such as dangerous work or drudgery, because the nature of care work makes it less susceptible to technological replacement, egalitarian concern will require the burdens of care work to be shared equally between individuals. (shrink)

Can purely predictive models be useful in investigating causal systems? I argue ‘yes’. Moreover, in many cases not only are they useful, they are essential. The alternative is to stick to models or mechanisms drawn from well-understood theory. But a necessary condition for explanation is empirical success, and in many cases in social and field sciences such success can only be achieved by purely predictive models, not by ones drawn from theory. Alas, the attempt to use theory to achieve explanation (...) or insight without empirical success therefore fails, leaving us with the worst of both worlds – neither prediction nor explanation. Best go with empirical success by any means necessary. I support these methodological claims via case studies of two impressive feats of predictive modelling: opinion polling of political elections, and weather forecasting. (shrink)

This article presents possible answers, and their respective probabilities, to the question, ‘What are the consequences of the present global crisis in the proximate future of the World System?’ It also attempts to describe the basic characteristics of the forthcoming ‘Epoch of New Coalitions’ and to forecast certain future conditions. Among the problems analyzed in this paper are the following: What does the weakening of the economic role of the USA as the World System centre mean? Will there be a (...) leader in the future World System? Will the deficit of global governance and world fragmentation continue to worsen? How can national sovereignty be transformed? (shrink)

The predictive capacity of the model is evaluated using evaluation measures, such as accuracy, precision, recall, F1-score, and the area under the ROC curve (AUC-ROC). Our findings show that improved machine learning models perform better than conventional methods, offering trustworthy forecasts that can help medical practitioners with early diagnosis and individualized treatment planning. In order to achieve even higher predicted accuracy, the study's conclusion discusses the significance of its findings for clinical practice as well as future improvements that might be (...) made, like adding wearable device data in real-time or investigating deep learning techniques. (shrink)

The aim of the article. The aim of the article is to identify the components of social and economic systems life cycle. To achieve this aim, the article describes the traits and characteristics of the system, determines the features of social and economic systems functioning and is applied a systematic approach in the study of their life cycle. The results of the analysis. It is determined that the development of social and economic systems has signs of cyclicity and is explained (...) methodologically by the axiomatics, rules and laws. Understanding of circular patterns has been formed long ago and now is recorded by scientists monitoring the properties of natural and artificial environment of human activity. During the study, it was found out that in scientific literature there is no unified description of the life cycle elements of social and economic systems at personal, micro, meso, macro and global levels. The paper investigates the cyclical patterns in multilevel social and economic systems for a human, employee, family, product, company, city, industry, elite, macroeconomic indicators, humanity, global processes, global economic system and the Universe. It is noted that at grass-roots administrative levels of the global environment of a human life activity system, a thesis about the cyclicity of development and the stages of the life cycle is considered by a wide circle of scientists and is doubtless. On hierarchically higher management levels of the global environment of human activity system, the scientists noticed the similar patterns of the cyclical nature. Problematic and discussion questions about cyclic development of social and economic systems are identified: the uncertainty of the driving force source of repeated changes; the vague distinction between systemic (internal) and off-system (external) influence on development; the lack of a unified description of development nature at different managerial levels; the use of different descriptive terms for the same constituent elements of repeated changes (period, stage, phase, wave, cycle); the uncertainty of the number of repeated changes constituent elements; the absence of an identification mechanism of the exact time of changes in the constituent elements of repeated changes; the surface description of out-of-system period of the subjects activity («before-system» period of creation and «after-system» period of liquidation); attaching more importance to primary and less importance to ultimate component elements of the repeated changes; the lack of reliable mechanism for predicting and forecasting the dynamics of constituent components of repeated changes. It is noted that all social and economic systems are developed within repeated changes and they have the same attributes of cyclicity: the fluctuation of indicators is marked that characterize the condition of the subject; the presence of system (from creation to liquidation) and out-of-system (creation – «design» and liquidation – «disposal») periods are noted; the subjects are created by the actions of other subjects (that is, subjects do not arise «out of nowhere», but are the result of actions of other subjects – «constructors»); after cessation of subjects functioning, their resources are used by other subjects (that is, the subjects do not disappear «nowhere», and they are transformed into the resources of other subjects – «recovery»); a unidirectional life cycle from «birth» to «death» is observed in the subjects; the subjects do not have to undergo the whole life cycle (each time might be the last); the subjects display similar changes of the indicators during their activity; ascending, peak and descending fluctuations of indicators are observed in the subjects; minor fluctuations occur in the constituent elements; the subjects have individual nature of indicator fluctuations and duration of activity. Conclusions and directions of further researches. The scientific novelty of the study is identification structure of life cycle of social and economic system with definitions of: common («before-system state», «growth», «stabilization», «reduction», «after-system state») and specific («creation», «slow growth», «rapid growth», «growth stabilization», «short stabilization», «rapid reduction», «slow reduction», «liquidation») constituent elements of repeated changes; marginal borders of indicators; dynamics of constituent elements of life cycle; key points of changing nature of the indicators dynamics. Identification of the life cycle of social and economic systems characterizes potentially possible limits of their activity in time and provides the possibility of further research of aspects of the cyclical development for methodological basis formation and the development of applied measures of systemic development in the areas of marketing and management innovations. (shrink)

Abstract: This research delves into the utilization of Artificial Neural Networks (ANNs) as a powerful tool for predicting the overall ratings of books by leveraging a diverse set of attributes. To achieve this, we employ a comprehensive dataset sourced from Goodreads, enabling us to thoroughly examine the intricate connections between the different attributes of books and the ratings they receive from readers. In our investigation, we meticulously scrutinize how attributes such as genre, author, page count, publication year, and reader reviews (...) influence a book's overall rating. Through rigorous analysis and experimentation, we construct an advanced ANN model tailored for predictive analysis in the realm of book ratings. The outcomes of our study reveal the remarkable potential of ANNs in this domain. The ANN model exhibits an impressive level of accuracy when it comes to forecasting book ratings, underlining the efficacy and promise of artificial neural networks in enhancing our understanding and prediction of book evaluations. This research opens up new avenues for leveraging machine learning techniques to gain deeper insights into the dynamics of book ratings and reader preferences. (shrink)

This chapter illustrates that in order to reach a decision a leader must decide which persons should be involved in the process and when. A relatively common method of involving others is delegating the decision to a group. A main objective of this is often to generate as many innovative ideas as possible, and different techniques can be employed for this, including brainstorming. The proposal generated must then be validated by the group using different criteria on the basis of which (...) it is then relatively easy to filter out proposals that do not reach the goals that have been set. However, a leader needs to collect additional information in order to reach a decision. By the use of information technology vast amounts of information may be accumulated. Thus, different kinds of filtering or weeding methods must be used in order to quickly obtain relevant information. This information can help leaders create forecasts and minimize risks. They must also be able to present their ideas in the most attractive way possible in order to be heard and arrive at decisions. The design of the presentation is therefore critical. Sometimes it is not enough for leaders just to present an idea, they are then obliged to negotiate in order to reach a decision. -/- . (shrink)