The main intention of the work that deals with the Nicolo Machiavelli thought is to point out the obvious paradox between the high political goal and the legitimating of all possible means for its realization. Are evil deeds inevitable in the sphere of politics and under what circumstances the immorality contained in political acts could be transformed into common good? The text asks additional questions such as about the accomplishments of ambitious political projects, the relationship among the ideologist and the (...) representative of political power, the transformations of the means into the ends, the use of violence and indoctrination in political acts, revolutionary and evolutionary political methods, etc. The author claims that political technologies recommended by Machiavelli basically haven't diminished, but have taken on more modern and more adequate forms. Osnovna namera teksta je da prateci misao Nikola Makijavelija ukaze na ociti paradoks izmedju visoko postavljenog cilja i opravdanja svih sredstava da bi se taj cilj realizovao. Da li je cinjenje zla neminovni ulog u sferi politike i pod kojim uslovima se amoralnost sadrzana u politickim cinovima moze transformisati u opste dobro? Tekst postavlja i dodatna pitanja, poput ostvarljivosti ambicioznih politickih projekata, odnosa ideologa i nosioca politicke moci, transformacije sredstava u ciljeve, koriscenja nasilja i indoktrinacije u politickim preokretima, revolucionarne i evolutivne metode politickog postupanja i sl. Autor iznosi zakljucak da politicke tehnologije koje je Makijaveli preporucavao u osnovi nisu iscezle, vec su zadobile samo zadobile modernije i adekvatnije oblike. (shrink)

Optimization, in general, is regarded as the process of finding optimal values for the variables of a given problem in order to minimize or maximize one or more objective function(s). Brain storm optimization (BSO) algorithm solves a complex optimization problem by mimicking the human idea generating process, in which a group of people solves a problem together. The aim of this paper is to present hybrid BSO algorithm solutions in the past 5 years. This study could be divided into two (...) parts: strategies and applications. In the first part, different strategies for the hybrid BSO algorithms intended to improve the various ability of the original BSO algorithm are displayed. In the second part, the real-world applications in the past five years in optimization, prediction and feature selection processes are presented. (shrink)

The skin, uniquely positioned at the interface between the human body and the external world, plays a multifaceted immunologic role in human life. In medical practice, early accurate detection of all types of skin tumours is essential to guide appropriate management and improve patients’ survival. The most important issue is to differentiate between malignant skin tumours and benign lesions. The aim of this research is the classification of skin tumours by analysing medical skin tumour dermoscopy images. This paper is focused (...) on a new strategy based on deep convolutional neural networks which have recently shown a state-of-the-art performance to define strategy to automatic classification for skin tumour images. The proposed system is tested on well-known HAM10000 data set. For experimental results, verification is performed and the results are compared with similar researches. (shrink)

Clustering is one of the most fundamental and essential data analysis tasks with broad applications. It has been studied in various research fields: data mining, machine learning, pattern recognition and in engineering, economics and biomedical data analysis. Headache is not a disease that typically shortens one’s life, but it can be a serious social as well as a health problem. Approximately 27 billion euros per year are lost through reduced work productivity in the European community. This paper is focused on (...) a new strategy based on a hybrid model for combining fuzzy partition method and maximum likelihood estimation clustering algorithm for diagnosing primary headache disorder. The proposed hybrid system is tested on two data sets for diagnosing headache disorder collected from Clinical Centre of Vojvodina in Serbia. (shrink)

Headache disorders can be considered as the predominant neurological condition. In the field of neurological diseases, migraine was estimated to cost a total of €27 billion per year for the loss through reduced work productivity in the European Community. Medical data and information in turn provide knowledge based on which physicians make scientific decisions for diagnosis and treatments. It is, therefore, very useful to create diagnostic tools to help physicians make better decisions. This paper is focused on a new hybrid (...) clustering system combining analytic hierarchy process and weighted fuzzy c-means clustering method for diagnosing children with primary headache disorder. The proposed three-stage hybrid diagnosing system is tested on data set collected from hospitalized children in the Clinical Centre of Vojvodina, Novi Sad, Serbia. (shrink)

When someone hosts a party, when governments choose an aid program, or when assistive robots decide what meal to serve to a family, decision‐makers must determine how to help even when their recipients have very different preferences. Which combination of people’s desires should a decision‐maker serve? To provide a potential answer, we turned to psychology: What do people think is best when multiple people have different utilities over options? We developed a quantitative model of what people consider desirable behavior, characterizing (...) participants’ preferences by inferring which combination of “metrics” (maximax, maxsum, maximin, or inequality aversion [IA]) best explained participants’ decisions in a drink‐choosing task. We found that participants’ behavior was best described by the maximin metric, describing the desire to maximize the happiness of the worst‐off person, though participant behavior was also consistent with maximizing group utility (the maxsum metric) and the IA metric to a lesser extent. Participant behavior was consistent across variation in the agents involved and tended to become more maxsum‐oriented when participants were told they were players in the task (Experiment 1). In later experiments, participants maintained maximin behavior across multi‐step tasks rather than shortsightedly focusing on the individual steps therein (Experiment 2, Experiment 3). By repeatedly asking participants what choices they would hope for in an optimal, just decision‐maker, and carefully disambiguating which quantitative metrics describe these nuanced choices, we help constrain the space of what behavior we desire in leaders, artificial intelligence systems helping decision‐makers, and the assistive robots and decision‐makers of the future. (shrink)

The travelling salesman problem (TSP) belongs to the class of NP-hard problems, in which an optimal solution to the problem cannot be obtained within a reasonable computational time for large-sized problems. To address TSP, we propose a hybrid algorithm, called GA-TCTIA-LBSA, in which a genetic algorithm (GA), tour construction and tour improvement algorithms (TCTIAs) and a list-based simulated annealing (LBSA) algorithm are used. The TCTIAs are introduced to generate a first population, and after that, a search is continued with the (...) GA. The problem of premature convergence of the GA to local optimum is tackled by a method called social disaster technique. Afterwards, the LBSA is applied to generate a new population based on one of two proposed operators called packing and judgement day. The proposed algorithm is implemented in the MATLAB environment, and its two variants, called GA-TCTIA-LBSA packing and GA-TCTIA-LBSA judgement day, are tested on symmetric and asymmetric instances from TSPLIB. The overall results demonstrate that the proposed GA-TCTIA-LBSAs offer promising results, particularly for small-sized instances. (shrink)

In the past 50 years nurse scheduling has received considerable attention in the research community. There are two cases regarding the nurse scheduling problem : the static and dynamic. Dynamic NSP, is often called nurse rerostering problem, which presents reconstruction or modification of the predetermined roster for the current scheduling horizon. The aim of this paper is to present new hybrid strategy for nurse NRRP problem. The proposed methodology is based on efficient cooperation between fuzzy logic, ordered weighted averaging and (...) variable neighbourhood descent search. Complete system is tested, and experimental results are based on real-world dataset obtained from the Oncology Institute of Vojvodina in Serbia. (shrink)

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from (...) social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic. (shrink)

New trends in the economic systems management in the context of modern global challenges: collective monograph / scientific edited by M. Bezpartochnyi, in 2 Vol. // VUZF University of Finance, Business and Entrepreneurship. – Sofia: VUZF Publishing House “St. Grigorii Bogoslov”, 2020. – Vol. 1. – 309 p.

The mature cerebral cortex contains a staggering variety of projection neuron subtypes, and a number of complementary studies have recently begun to define their identity and embryonic origin. Among the different types of cortical projection neurons, subcerebral projection neurons, including corticospinal motor neurons (CSMN), have been extensively studied and some of the molecular controls over their differentiation have been elucidated. Here, we first provide an overview of the approaches used to purify and molecularly profile neuronal populations of the neocortex and, (...) more broadly, of the central nervous system (CNS). Next, we specifically review recent progress in understanding the genes that define and control development of the CSMN population. Finally, we briefly discuss the relevance of this work to current questions regarding the mechanisms of the establishment of projection neuron subtype identity in the neocortex and its implications to direct the differentiation of CSMN for therapeutic benefit. (shrink)

Originally published in 1936, this book presents the ancient Greek text of the paraphrases and quotations of Zeno's philosophical arguments, together with a facing-page English translation and editorial commentary. Detailed notes are incorporated throughout and a bibliography is also included. This book will be of value to anyone with an interest in Zeno and ancient philosophy.

The subject of the present inquiry is the approach-to-the-truth research, which started with the publication of Sir Karl Popper's Conjectures and Refutations. In the decade before this publication, Popper fiercely attacked the ideas of Rudolf Carnap about confirmation and induction; and ten years later, in the famous tenth chapter of Conjectures he introduced his own ideas about scientific progress and verisimilitude. Abhorring inductivism for its apprecia tion of logical weakness rather than strength, Popper tried to show that fallibilism could serve (...) the purpose of approach to the truth. To substantiate this idea he formalized the common sense intuition about preferences, that is: B is to be preferred to A if B has more advantages andfewer drawbacks than A. In 1974, however, David Millerand Pavel Tichy proved that Popper's formal explication could not be used to compare false theories. Subsequently, many researchers proposed alternatives or tried to improve Popper's original definition. (shrink)

In this essay, I claim that certain passages in Book IV of Benedict de Spinoza’s Ethics suggest a novel version of what is known as metaethical constructivism. The constructivist interpretation emerges in the course of attempting to resolve a tension between Spinoza’s apparent ethical egoism and some remarks he makes about the efficacy of collaborating with the right partners when attempting to promote our individual self-interest . Though Spinoza maintains that individuals necessarily aim to promote their self-interest, I argue that (...) Spinoza has an atypical conception of self that allows the interests of other people to be partially constitutive of one's own self-interest. In this way, Spinoza can account for the rationality of concern for the interests of others . This interpretation attributes to Spinoza a form of constructivism that differs in important ways from contemporary Humean and Kantian constructivisms and which can in principle be detached from Spinoza’s particular metaphysical commitments in order to yield a third general category of constructivist view . Though my treatment is necessarily brief, it is my hope that it can serve both to motivate a constructivist reading of Spinoza and, perhaps even more crucially, to suggest a Spinozistic variety of constructivism as a live theoretical option in metaethics. (shrink)

Long-term potentiation (LTP) is a long-lasting increase in synaptic efficacy that many consider the best candidate currently available for a neural mechanism of memory formation and/or storage in the mammalian brain. In our target article, LTP: What's learning got to do with it?, we concluded that there was insufficient data to warrant such a conclusion. In their commentaries, Jeffery and Zhadin raise a number of important issues that we did not raise, both for and against the hypothesis. Although we agree (...) with a number of these issues, we maintain that there remains insufficient evidence that LTP is a memory mechanism. (shrink)

A central theme in western philosophy was to find formal methods that can reliably discover empirical relationships and their explanations from data assembled from experience. As a philosophical project, that ambition was abandoned in the 20th century and generally dismissed as impossible. It was replaced in philosophy by neo-Kantian efforts at reconstruction and justification, and in professional statistics by the more limited ambition to estimate a small number of parameters in pre-specified hypotheses. The influx of “big data” from climate science, (...) neuropsychology, biology, astronomy and elsewhere implicitly called for a revival of the grander philosophical ambition. Search algorithms are meeting that call, but they pose a problem: how are their accuracies to be assessed in domains where experimentation is limited or impossible? Increasingly, the answer is through simulation of data from models of the kind of process in the domain. In some cases, these innovations require rethinking how the accuracy and informativeness of inference methods can be assessed. Focusing on causal inference, we give an example from neuroscience, but to show that the model/simulation strategy is not confined to causal inference, we also consider two classification problems from astrophysics: identifying exoplanets and identifying dark matter concentrations. (shrink)

Surrogate endpoints are a common application of biomarkers to estimate clinical benefit in clinical trials, despite questions about reliability. This article discusses ongoing opportunities for their validation, in the context of a regulatory environment in which they are increasingly championed.

If you do not know the correct answer, guess.Design addresses need, of various types. A designer “designs” to address, to propose a possibility, or to meet a need. A great variety of things are designed: shoes, posters, watches, houses, televisions, keyboards, movies, washing machines, toasters, belts, and cars, to mention only some.A designer, be he or she an architect, interior designer, graphic designer, product designer, or industrial designer, nearly always provides drawings, models, written descriptions, and overarching ideas in response to (...) a need, articulated, stated, by someone. The need might be one that the designer recognizes on his or her own and decides to address, or the need might come to the... (shrink)

Infant language learners are faced with the difficult inductive problem of determining how new words map to novel or known objects in their environment. Bayesian inference models have been successful at using the sparse information available in natural child-directed speech to build candidate lexicons and infer speakers’ referential intentions. We begin by asking how a Bayesian model optimized for monolingual input generalizes to new monolingual or bilingual corpora and find that, especially in the case of the bilingual input, the model (...) shows a significant decrease in performance. In the next experiment, we propose the ME Model, a modified Bayesian model, which approximates infants’ mutual exclusivity bias to support the differential demands of monolingual and bilingual learning situations. The extended model is assessed using the same corpora of real child-directed speech, showing that its performance is more robust against varying input and less dependent than the Intentional Model on optimization of its parsimony parameter. We argue that both monolingual and bilingual demands on word learning are important considerations for a computational model, as they can yield significantly different results than when only one such context is considered. (shrink)