The rationality of the human being applied in science-technique in the contemporary capitalist system is distorted; the purpose, which is the good life for human beings, has become the means to sustain and feedback the technicist system of technological capitalism. Thus, the modus operandi of science, aims only to legitimize technology, apart from the ethics applied in this relationship between technology and human beings, and cut off from critical philosophical thinking. With the result presented, the problem lies in the reason (...) of the contemporary human being, who seeks to satisfy his desires and envisions the good life (eudaimonía) in material goods, suppressing the contemplative leisure of life (ataraxia); becoming a slave to the system it fosters. The objective is to demonstrate the need to reformulate the modern system, in order to earn a good life for human beings as a purpose of technical science, which should be the means for this and as technological advances in favor of the quality of human beings. and, not for capitalist reproduction. The research methodology is an exploratory bibliography, exposing and dialoguing with authors on the subject in order to forge our conclusion, that pleads for science-technical that enjoys ethics and human reason in favor of eudaimonia. (shrink)

[ENGLISH] This article discusses the potential of synthetic biology to address fundamental questions in the philosophy of biology regarding the nature of life and biological functions. Synthetic biology aims to reduce living organisms to their simplest forms by identifying the minimal components of a cell and also to create novel life forms through genetic reprogramming, biobrick assembly, or novel proteins. However, the technical success of these endeavors does not guarantee their conceptual success in defining life. There is a lack of (...) consensus among researchers on how to define and classify the entities produced in the lab, whether they should be considered living or categorized differently. The criteria for minimal cells and minimal life are subject to arbitrary choices and varying interpretations. The concept of function, crucial to synthetic biology, is also difficult to define. The article highlights the need to consider the minimal set of functions that characterize life before determining the smallest genomes that code for those functions. The arbitrary nature of defining both life and function complicates the understanding and classification of these entities. The article suggests that the traditional dichotomy between the living and the non-living may no longer be valid and that the concept of life itself may not require precise scientific definition. As synthetic biology advances, the article emphasizes the importance of redefining or constructing new categories to encompass the expanding possibilities and creations in the field. The ability to create new life forms raises questions about recognition, identification, and ethical implications, requiring a conceptual and philosophical engagement beyond the technical achievements of synthetic biology. -/- [FRENCH] L'article aborde le potentiel de la biologie synthétique pour répondre à des questions fondamentales de la philosophie de la biologie concernant la nature de la vie et des fonctions biologiques. La biologie synthétique vise à réduire les organismes vivants à leurs formes les plus simples en identifiant les composants minimaux d'une cellule et à créer de nouvelles formes de vie grâce à la reprogrammation génétique, à l'assemblage de biobriques ou à des protéines nouvelles. Cependant, le succès technique de ces approches ne garantit pas leur réussite conceptuelle dans la définition de la vie. Il n'y a pas de consensus parmi les chercheurs sur la façon de définir et de classer les entités produites en laboratoire, qu'elles doivent être considérées comme vivantes ou catégorisées différemment. Les critères des cellules minimales et de la vie minimale sont soumis à des choix arbitraires et à des interprétations variables. La notion de fonction, essentielle en biologie synthétique, est également difficile à définir. L'article met en évidence la nécessité de prendre en compte l'ensemble minimal de fonctions qui caractérisent la vie avant de déterminer les plus petits génomes qui codent ces fonctions. La nature arbitraire de la définition de la vie et de la fonction complique la compréhension et la classification de ces entités. L'article suggère que la dichotomie traditionnelle entre le vivant et le non-vivant pourrait ne plus être valable et que le concept même de vie ne nécessite pas une définition scientifique précise. À mesure que la biologie synthétique progresse, l'article souligne l'importance de redéfinir ou de construire de nouvelles catégories pour englober les possibilités et créations croissantes dans le domaine. La capacité à créer de nouvelles formes de vie soulève des questions de reconnaissance, d'identification et d'implications éthiques, nécessitant une réflexion conceptuelle et philosophique au-delà des avancées techniques de la biologie synthétique. (shrink)

Stock market prediction is essential and of great interest because success- ful prediction of stock prices may promise smart bene ts. These tasks are highly complicated and very dicult. Many researchers have made valiant attempts in data mining to devise an ecient system for stock market movement analysis. In this paper, we have developed an ecient approach to stock market prediction by employing fuzzy C-means clustering and arti cial neural network. This research has been encouraged by the need of predicting (...) the stock market to facilitate the investors about buy and hold strategy and to make pro t. Firstly, the original stock market data are converted into interpreted historical ( nancial) data i.e. via technical indi-cators. Based on these technical indicators, datasets that are required for analysis are created. Subsequently, fuzzy-clustering technique is used to generate di erent training subsets. Subsequently, based on di erent training subsets, di erent ANN models are trained to formulate di erent base models. Finally, a meta-learner, fuzzy system module, is employed to predict the stock price. The results for the stock market prediction are validated through evaluation metrics, namely mean absolute deviation, mean square error, root mean square error, mean absolute percentage error used to estimate the forecasting accuracy in the stock market. Comparative analysis is carried out for single Neural Network (NN) and existing technique neu- ral. The obtained results show that the proposed approach produces better results than the other techniques in terms of accuracy. (shrink)

Abstract Background The first live birth following the use of a new reproductive technique, maternal spindle transfer (MST), which is a mitochondrial replacement technique (MRT), was accomplished by dividing the execution of the MST procedure between two countries, the USA and Mexico. This was done in order to avoid US legal restrictions on this technique. -/- Sources of data Academic articles, news articles, documents obtained through freedom of information requests, laws, regulations and national reports. -/- Areas of agreement MRTs are (...) new reproductive techniques that present novel ethical and legal challenges, since genetic material from three people is employed to create a child. -/- Areas of controversy Could the first MST procedure that culminated in a live birth negatively impact reproductive medicine in Mexico? -/- Growing points The USA and Mexico need specific and clear legislation on MRTs, in order for such techniques not to be governed by prior existing legislation on assisted reproduction that is inadequate for dealing with the new challenges that these techniques present. -/- Areas timely for developing research There is a pressing need for work to be done on the international governance of new reproductive techniques. (shrink)

The author considers the model-theoretic character of proofs and disproofs by means of attempted counterexample constructions, distinguishes this proof format from formal derivations, then contrasts two approaches to semantic tableaux proposed by Beth and Lambert-van Fraassen. It is noted that Beth's original approach has not as yet been provided with a precisely formulated rule of closure for detecting tableau sequences terminating in contradiction. To remedy this deficiency, a technique is proposed to clarify tableau operations.

“Dialectic” has been a matter of growing interest in contemporary philosophy. The present article analyzes dialectical methods and positions them by reference to two paradigmatic texts of German idealism and analytic philosophy, i.e. J.G. Fichte’s Science of Knowing (1804) and J. McDowell’s Mind and World. Both dialectical approaches will be interpreted with regard to their contribution in the debate on reductionism and anti-reductionism: both Fichte and McDowell claim that philosophical positions and logical terms stand in a dualistic relationship to one (...) another, on the one hand, but are separated by a gulf, on the other. I will argue that for McDowell dialectic seems to be an alternative to one-sided reductionisms as well as to normal anti-reductionistic holism. Furthermore, for Fichte dialectic is an adequate method for describing the relationship of reductionism and anti-reductionism itself. Both see in dialectic a technique for bridging the gulf between binary opposite terms of logic as well as mutually exclusive positions, such as mind and world, subject and object, or idealism and realism. (shrink)

In this paper, we discuss three translation techniques: literal, cultural, and artistic. Literal translation is a well-known technique, which means that it is quite easy to find sources on the topic. Cultural and artistic translation may be new terms. Whilst cultural translation focuses on matching contexts, artistic translation focuses on matching reactions. Because literal translation matches only words, it is not hard to find situations in which we should not use this technique. Because artistic translation focuses on reactions, judging (...) the quality of an artistic translation work is one of the most difficult things one can do. We end up having a score of complexity and humanity for each one of the mentioned techniques: Literal translation would be the closest thing we have to the machines world and artistic translation would be the closest thing we have to the purely human world. By creating these classifications and studying the subtleties of each one of them, we are adding degrees of quality to our courses and to translation as a professional field. The main contribution of this paper is then the formalization of such a piece of knowledge. We, however, also lay the foundations for studies of this type. (shrink)

Legislative technique encompasses a system of methods and means associated with the preparation of draft legal acts in the most perfect form in terms of structure and form. In the legislative technique, not only national, but also the established legal practice of foreign countries for hundreds of years is widely used. The special legal means of legislative technique include the following: 1) legal language; 2) legal structures; 3) the procedure for registering a legislative act, the process of lawmaking; 4) systematization (...) of legislation. The legislative process provides for the existence of separate stages leading to the emergence of a new legislative act. And the problem of systematization of legislation and its main components is described in a separate way. (shrink)

Making “the familiar strange and the strange familiar” is what anthropology has long claimed as its expertise. The Internet and its broader technological problem space pose methodological challenges, however, for a discipline that has traditionally drawn on the authority of “being there” to ground its claims to knowledge.

News about the first baby born after a mitochondrial replacement technique (MRT; specifically maternal spindle transfer) broke on September 27, 2016 and, in a matter of hours, went global. Of special interest was the fact that the mitochondrial replacement procedure happened in Mexico. One of the scientists behind this world first was quoted as having said that he and his team went to Mexico to carry out the procedure because, in Mexico, there are no rules. In this paper, we explore (...) Mexico's rule of law in relation to mitochondrial replacement techniques and show that, in fact, certain instances of MRTs are prohibited at the federal level and others are prohibited at the state level. According to our interpretation of the law, the scientists behind this first successful MRT procedure broke federal regulations regarding assisted fertilization research. (shrink)

Tarkovsky s’est opposé au montage et a considéré que la base de l’art cinématographique (l’art du film) est le rythme interne des images. Il a considèré le cinéma comme une représentation des courants distinctifs ou des ondes de temps, transmis dans le film par son rythme interne. Le rythme est au cœur du « film poétique ». Un rythme comme un mouvement dans le cadre (« la sculpture dans le temps »), pas comme une séquence d'images dans le temps. Le (...) temps passé dans le cadre exprime quelque chose de significatif et de vrai, qui dépasse les événements eux-mêmes et est reçu différemment par chaque spectateur. DOI: 10.13140/RG.2.2.30568.62727. (shrink)

Holding students to high standards and assessing, measuring and evaluating their learning with challenging, authentic problems in the midterm and final exams is the goal of the professors who teach core signal processing concepts. However, the heavy reliance of these subjects on mathematics makes it difficult for students to genuinely grasp the concepts and relate to a conceptual framework. Specifically, analyzing the signals and the functionality of systems in Fourier domain; separating the system level analysis from signal level analysis; and (...) understanding how they are related in time domain and frequency domain are among the most challenging concepts. Students’ lower grades observed over past years in the introductory signal processing course exposed a potential disconnect between the actual level of learning and the high expectations set by the professors. In this paper, we present the active learning techniques that we implemented in one of the summer session offerings of this course in our department. The research explored Peer Instruction, pre-class reading quizzes and post-lecture quizzes. In addition to the mid and end of the quarter survey results, the comparison analysis of the grades students achieved in the active learning integrated course in the second summer session and the standard course offered in first summer session is discussed. According to our results, the developed techniques helped students in the active classroom perform significantly better than their peers participating in standard lectures when tested by challenging questions in their exams. (shrink)

This research aims at examining three important things, i.e. students’ technique in paraphrasing, paraphrasing acceptability and obstacles in paraphrasing. A qualitative approach was used to carry out this study by purposively selecting 26 Indonesian college students of English as respondents. The data were collected by giving a paraphrasing task (consisted of 5 paragraphs) to the students and interviewed them to find out in-depth information on paraphrasing acceptably and obstacles. The research revealed that synonym technique was the most frequent technique sued (...) by the respondents due to the easiness of using this technique. On the other hand, the technique of changing positive into negative (vice versa), changing structure of idea, combining two sentences, and changing clause into phrase (vice versa) were found to be the less frequent techniques used for paraphrasing. The research also found that all students are not able to produce good paraphrasing sentences due to their incompetence to satisfy the criteria of good paraphrasing such as not giving citation sources, the tendency for doing plagiarism (changing words with their synonyms and keep the sentence structures still the same as the original. Regarding the respondents’ obstacles in paraphrasing, this study found some obstacles: (1) difficult to find out the appropriate synonyms to change words on original text, (2) difficult to understand unfamiliar terms (3) unable to restructure sentences in new ones, and (4) no idea on how to paraphrase texts effectively. All the obstacles occur due to some causal factors, i.e. (1) lack of vocabulary, (2) lack of paraphrasing practice, (3) ineffective class when learning, (4) teaching technique of lecturers, and (5) limited knowledge of paraphrasing techniques. (shrink)

For those familiar with Machiavelli’s texts, Foucault’s interpretation of Macchiavelli in his 1978 lecture series Sécurité, Territoire, Population1 is surprising. Although Machiavelli figures prominently in five of the thirteen lectures,2 Foucault treats Machiavelli as if he were the author of only one book—The Prince—and his reading treats this complex text as if it covered only one topic: how to guarantee the security of the Prince. Clearly Foucault did not intend his interpretation of Machiavelli as a close exegesis. Other discussions of (...) Foucault’s treatment of Machiavelli have acknowledged the role Machiavelli plays in these lectures and even note the inadequacy of the interpretation given by Foucault, but most commentators do not pursue Foucault’s reading further.3 This investigation is not concerned with whether Foucault got Machiavelli right. Rather, Foucault’s reading of Machiavelli is noteworthy because it is partial and incomplete in a way reminiscent of Foucault’s reading of Hobbes in, Il faut défendre la société. This fragmentary character of Foucault’s inscription of Machiavelli as a forerunner of the history of biopolitique allows an innovative reading of the Florentine that connects Machiavelli’s thinking, however indirectly, on a trajectory that encounters, for instance, Foucault’s analysis of populations, the police state, and even his reading of liberalism during the 1978-­‐ 1979 lectures. My argument here is that the specific way Foucault’s inscribes Machiavelli in the history of gouvernementalité, while seeming to reject him, in fact acts to resuscitate, and thereby relay, a reading of Machiavelli as a thinker who articulates encounters among political practices engaged within a horizon of radical immanence. (shrink)

Lecturing is the only educational form inherited from the universities of the middle ages that is still in use today. However, it seems that lecturing is under threat, as recent calls to do away with lecturing in favour of more dynamic settings, such as the flipped classroom or pre-recorded talks, have found many adherents. In line with the post-critical approach of this book, this chapter argues that there is something in the university lecture that needs to be affirmed: at its (...) best, the university lecture functions as a technique for thinking together or for making collective thinking happen in a lecture hall. The lecture offers the set-up, both technological and architectural, to forge a common experience that binds together the listeners and the speakers; that experience can be characterised as visualising ideas or seeing things as if they had taken on a ‘bodily form’. By looking at several examples of lecturing moments experienced by Gadamer as a student and later recounted in his autobiography, we can better understand the paradigmatic experience that characterises the lecture – as an ideal to be sought, even if, perhaps, not always actualised in everyday lectures. (shrink)

Desire for status, for power, here it is the realm of capitalism, since Marcuse, after Freud, everyone produces his own theory about the world, his own world..

Progress in science and technology of global society these days enables humans to have easy and quick access to information occurring in this borderless world. There is a need in the modification of education to keep up with political, economic and social changes so that students can become good citizens and live happily with others. This forces social studies teachers to develop their learning processes in a regular basis using the lessons from the past as a case study in order (...) to make learning atmosphere enjoyable and challenging. Learners are encouraged to appreciate their cultural roots, see their own values including those of others in order to live in the society of diversity so that they can be instilled with patriotism, retain their ancestral heritage, become good citizens and fully aware of Thai nationhood. Students are taught to be proud of being Thai as a sustained concept. (shrink)

In 2015 the United Kingdom (UK) became the first nation to legalize egg and zygotic nuclear transfer procedures using mitochondrial replacement techniques (MRTs) to prevent the maternal transmission of serious mitochondrial DNA diseases to offspring. These techniques are a form of human germline genetic modification and can happen intentionally if female embryos are selected during the MRT clinical process, either through sperm selection or preimplantation genetic diagnosis (PGD). In the same year, an MRT was performed by a United (...) States (U.S.)-based physician team. This experiment involved a cross-border effort: the MRT procedure per se was carried out in the US, and the embryo transfer in Mexico. The authors examine the ethics of MRTs from the standpoint of genetic relatedness and gender implications, in places that lack adequate laws and regulation regarding assisted reproduction. Then, we briefly examine whether MRTs can be justified as a reproductive option in the US and Mexico, after reassessing their legalization in the UK. We contend that morally inadequate and ineffective regulations regarding egg donation, PGD, and germline genetic modifications jeopardize the ethical acceptability of the implementation of MRTs, suggesting that MRTs are currently difficult to justify in the US and Mexico. In addition to relevant regulation, the initiation and appropriate use of MRTs in a country require a child-centered follow-up policy and more evidence for its safety. (shrink)

The study investigated principals’ supervisory techniques for combating corruption and the attainment of quality school governance. Two null hypotheses were formulated. The ex-post facto research design was adopted for the study. Census technique was used to draw the entire population of 81 principals from all the public secondary schools in Aba Education Zone of Abia State. Data collection was carried out with the use of a research instrument titled: “Principals’ Supervisory Techniques for Combating Corruption and Attainment of Quality (...) School Governance Questionnaire (PSTCCAQSGQ)”. The instrument was validated by two experts of Test and Measurement in the Department of Educational Foundations, University of Calabar. The reliability value obtained was .88 using Cronbach Alpha technique. One-way analysis of variance was used in testing the null hypotheses at .05 level of significance. Findings revealed that there is a significant influence of principals’ clinical and demonstration techniques of supervision for combating corruption on quality school governance. Based on the findings, it was concluded that school governance should be enhanced with supervisory techniques by principals for the attainment of anti-corruption culture in Aba education zone of Abia State, Nigeria. (shrink)

Concerns about threats to human autonomy feature prominently in the field of AI ethics. One aspect of this concern relates to the use of AI systems for problematically manipulative influence. In response to this, the European Union’s draft AI Act (AIA) includes a prohibition on AI systems deploying subliminal techniques that alter people’s behavior in ways that are reasonably likely to cause harm (Article 5(1)(a)). Critics have argued that the term ‘subliminal techniques’ is too narrow to capture the (...) target cases of AI-based manipulation. We propose a definition of ‘subliminal techniques’ that (a) is grounded on a plausible interpretation of the legal text; (b) addresses all or most of the underlying ethical concerns motivating the prohibition; (c) is defensible from a scientific and philosophical perspective; and (d) does not over-reach in ways that impose excessive administrative and regulatory burdens. The definition is meant to provide guidance for design teams seeking to pursue responsible and ethically aligned AI innovation. (shrink)

Mitochondrial DNA (mtDNA) diseases are a group of neuromuscular diseases that often cause suffering and premature death. New mitochondrial replacement techniques (MRTs) may offer women with mtDNA diseases the opportunity to have healthy offspring to whom they are genetically related. MRTs will likely be ready to license for clinical use in the near future and a discussion of the ethics of the clinical introduction ofMRTs is needed. This paper begins by evaluating three concerns about the safety of MRTs for (...) clinical use on humans: (1) Is it ethical to use MRTs if safe alternatives exist? (2) Would persons with three genetic contributors be at risk of suffering? and (3) Can society trust that MRTs will be made available for humans only once adequate safety testing has taken place, and that MRTs will only be licensed for clinical use in a way that minimises risks? It is then argued that the ethics debate about MRTs should be reoriented towards recommendingways to reduce the possible risks of MRT use on humans. Two recommendations are made: (1) licensed clinical access to MRTs should only be granted to prospective parents if they intend to tell their children about their MRT conception by adulthood; and (2) sex selection should be used in conjunction with the clinical use ofMRTs, in order to reduce transgenerational health risks. (shrink)

Climate data analysis performed in order to understand climate change process and effect of different environmental factors in that change, has been focus of interest of researches for many years. Climate change disturbs natural balance, leading to endangerment of many species and their habitats. Data mining techniques provide better and faster analysis of large amounts of data in climatology. Data Mining is a technology that blends traditional data analysis methods with sophisticated algorithms for processing large volumes of data. It (...) has also opened up exciting opportunities for exploring and analyzing new types of data and for analyzing old types of data in new ways. This paper focused on applying few clustering techniques on Climatic data and inferences are studied. Developed solution represents climate data from different points of view in order to provide a complete view of the data for researchers from which they can draw their own conclusions and perform detailed climate data analysis. (shrink)

Generative AI has proven itself as an efficient innovation in many fields including writing and even analyzing data. For spatial computing, it provides a potential solution for solving such issues related to data manipulation and analysis within the spatial computing domain. This paper aims to discuss the probabilities of applying generative AI to graph-based spatial computing; to describe new approaches in detail; to shed light on their use cases; and to demonstrate the value that they add. This technique thus incorporates (...) graph theory, generative models to model spatial relations, generate new spatial forms and improve on spatial decision-making processes. The paper surveys such methods, describes typical applications, and outlines further development of the subject. (shrink)

High-Performance Computing (HPC) has become a cornerstone for enabling breakthroughs in artificial intelligence (AI) by offering the computational resources necessary to process vast datasets and optimize complex algorithms. As AI models continue to grow in complexity, traditional HPC systems, reliant on central processing units (CPUs), face limitations in scalability, efficiency, and speed. Emerging technologies like quantum computing and specialized hardware such as Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), and Field Programmable Gate Arrays (FPGAs) are poised to address these (...) challenges. This research paper explores various HPC techniques used to optimize and accelerate AI algorithms, focusing on quantum computing’s potential for parallelism and specialized hardware's capabilities in delivering faster computation and energy efficiency. It delves into current advancements, comparative analyses of different HPC methods, and the integration of hybrid quantum-classical approaches to further enhance AI optimization. The study also examines the challenges of implementing these technologies at scale, with an eye toward the future of AI acceleration and the role of HPC in maintaining energy efficiency while meeting computational demands. Through this investigation, we aim to provide a comprehensive overview of how quantum computing and specialized hardware are reshaping the landscape of AI, paving the way for more advanced, efficient, and sustainable AI solutions. (shrink)

Cloud computing is the computing technology which provides resources like software, hardware, services over the internet. Cloud computing provides computation, software, data access, and storage services that do not require end- user knowledge of the physical location and configuration of the system that delivers the services. Cloud computing enables the user and organizations to store their data remotely and enjoy good quality applications on the demand without having any burden associated with local hardware resources and software managements but it possesses (...) a new security risk towards correctness of data stored at cloud. The data storage in the cloud has been a promising issue in these days. This is due to the fact that the users are storing their valuable data and information in the cloud. The users should trust the cloud service providers to provide security for their data. Cloud storage services avoid the cost storage services avoids the cost expensive on software, personnel maintains and provides better performance less storage cost and scalability, cloud services through internet which increase their exposure to storage security vulnerabilities however security is one of the major drawbacks that preventing large organizations to enter into cloud computing environment. This work surveyed on several storage techniques and this advantage and its drawbacks. (shrink)

The rapid digitalization of financial services has driven the adoption of artificial intelligence (AI) for automating decision-making, fraud detection, risk assessment, and personalized financial offerings. However, these AI models often require access to sensitive user data, leading to significant concerns around data privacy, security, and regulatory compliance. Federated Learning (FL) has emerged as a transformative approach to address these concerns by enabling collaborative model training across decentralized data sources without exposing raw data to central servers. This paper explores the application (...) of federated learning techniques specifically tailored for secure AI model training in the FinTech domain. We present an in-depth analysis of FL architecture, system design considerations, privacy-preserving mechanisms, and optimization strategies for heterogeneous and non-IID data distributions. Real-world use cases are studied to demonstrate the feasibility of integrating FL with existing financial systems. The evaluation also compares FL’s effectiveness against centralized models, considering parameters like model accuracy, data leakage resistance, and convergence performance. This work aims to provide FinTech developers and researchers with a practical blueprint for implementing secure and scalable federated AI systems that meet evolving data protection standards. (shrink)

The study aims to identify the impact of the use of artificial intelligence techniques in improving the outputs of higher education in Business Administrative Colleges in the universities under study that formed the research community. As for the sample, it consisted of (130) academic respondents in these universities under study. The research concluded that there is a statistically significant effect of using artificial intelligence techniques (expert systems, neural networks) in improving the outputs of higher education in Business Administrative (...) Colleges under study. It was found that artificial intelligence technologies contribute to finding graduates who are able to carry out the process of modernization and professional development in various fields of work. These technologies also contribute to improving and developing the skills of graduates in the labor market and providing them with new skills and characteristics to perform their duties. The research recommended increasing interest in the expert systems technology by the universities under study because of its scientific importance in improving the outputs of higher education by reformulating them in the form of programs embraced by computers. (shrink)

The aim of this paper is to demonstrate the applicability of multivariate mapping techniques to the exploration of the rhetorical semiotic brand image structure of ad films. By drawing on correspondence analysis and multidimensional scaling, two techniques that are amply used in corpus linguistics and in marketing research, but also on the data reduction technique of factor analysis, it will be displayed how a set of nuclear semes and classemes or an intended semic structure that underlies ad filmic (...) discursive structures may be projected alongside rhetorical figures by its internal stakeholders (i.e., a brand management team, an account planning team or a marketing research team) with view to attaining differential brand associations. The illustration of the exploratory analytical methods takes place by recourse to a corpus of 62 ad filmic texts from 13 sub-brands of the 3 major brands in the UK cereals market and 321 ad filmic segments that resulted from the segmentation procedure. This paper seeks to contribute to advancements in the brand image and advertising rhetoric research streams by addressing distinctive modes of advertising rhetorical configuration at the level of the ad filmic text (as against print ads where the bulk of research on advertising rhetoric has concentrated), and moreover on a segment-by-segment level, rather than treating the ad film as a standalone unit of analysis, by adopting a multimodal outlook to advertising configurations that takes into account not only the verbal or the visual mode, but also interactions among modes, by adopting a product category-specific approach to advertising/brand textuality that draws on rhetorical semiotics and by employing exploratory statistical methods against the background of content analytic output. (shrink)

The Pomodoro technique is a timed-based strategy used in fighting procrastination and found to increase academic performance. However, its effect on academic learning in a synchronous remote learning modality has yet to be investigated. The study used a mixed triangulation semiexperimental design using a whole sample (N=46), following all ethical equivalence procedures. The genetics concept mastery of the students was tested using a researcher-made test. ANCOVA results revealed that students taught using Pomodoro yielded significantly better concept mastery in genetics than (...) the lecture method. This study contributes to the evaluation of one science teaching strategy compatible with remote learning modality. (shrink)

This article explores the transformative potential of improvisational techniques in reshaping interdisciplinary and transdisciplinary (ITD) learning environments offering art-based exercises and tools for this work. By integrating active research with improvisational methods from theatre and music, we propose a pedagogical shift that transcends traditional academic roles and disciplinary boundaries, fostering a culture of co-creation, mutual learning and innovation. This approach aims to tackle the inherent challenges of ITD research and thus enhance ITD research groups’ ability to address complex societal (...) ‘Grand Challenges’. We argue that improvisation within both ITD research and educational communities serves as a crucial catalyst for nurturing trust, embracing failure as a growth opportunity, and redefining success. Embodied practices based on improvisation help bridge the gap between theoretical knowledge and practical applications, enabling academics to navigate the complexities of collaboration and engage in shared learning experiences. This article introduces techniques from improvisational theatre aimed at fostering trust and collaboration in transdisciplinary research and educational settings. Drawing on over 25 years of combined research experience, we show how these tools enhance mutual understanding and collective problem-solving among students and research teams. Ultimately, we advocate integrating conventional knowledge delivery models with a framework characterised by regenerative practices, care and explorative processes. This integrated approach would offer new opportunities for addressing the intertwined wicked problems our world faces today, promoting a more inclusive, participatory and creatively fulfilling academic community. (shrink)

Much work in MKM depends on the application of formal logic to mathematics. However, much mathematical knowledge is informal. Luckily, formal logic only represents one tradition in logic, specifically the modeling of inference in terms of logical form. Many inferences cannot be captured in this manner. The study of such inferences is still within the domain of logic, and is sometimes called informal logic. This paper explores some of the benefits informal logic may have for the management of informal mathematical (...) knowledge. (shrink)

Abstract—Breast cancer is considered the second most common cancer in women compared to all other cancers. It is fatal in less than half of all cases and is the main cause of mortality in women. It accounts for 16% of all cancer mortalities worldwide. Early diagnosis of breast cancer increases the chance of recovery. Data mining techniques can be utilized in the early diagnosis of breast cancer. In this paper, an academic experimental breast cancer dataset is used to perform (...) a data mining practical experiment using the Waikato Environment for Knowledge Analysis (WEKA) tool. The WEKA Java application represents a rich resource for conducting performance metrics during the execution of experiments. Pre-processing and feature extraction are used to optimize the data. The classification process used in this study was summarized through thirteen experiments. Additionally, 10 experiments using various different classification algorithms were conducted. The introduced algorithms were: Naïve Bayes, Logistic Regression, Lazy IBK (Instance-Bases learning with parameter K), Lazy Kstar, Lazy Locally Weighted Learner, Rules ZeroR, Decision Stump, Decision Trees J48, Random Forest and Random Trees. The process of producing a predictive model was automated with the use of classification accuracy. Further, several experiments on classification of Wisconsin Diagnostic Breast Cancer and Wisconsin Breast Cancer, were conducted to compare the success rates of the different methods. Results conclude that Lazy IBK classifier k-NN can achieve 98% accuracy among other classifiers. The main advantages of the study were the compactness of using 13 different data mining models and 10 different performance measurements, and plotting figures of classifications errors. (shrink)

Data cleaning and preprocessing are fundamental steps in the data analysis pipeline. These processes involve transforming raw data into a usable format by identifying and rectifying inconsistencies, errors, and missing values. Given the importance of data quality in achieving accurate and reliable analytical results, understanding the best practices for these stages is crucial. This paper outlines key techniques for data cleaning and preprocessing, including handling missing data, detecting and managing outliers, data normalization, encoding categorical variables, and dealing with noisy (...) data. Additionally, it explores the importance of these practices in ensuring robust and insightful analysis. (shrink)

Generative AI refers to a class of models capable of creating new data from a given distribution. These models can generate diverse forms of data, including text, images, audio, and videos. The key techniques in generative AI include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based models like GPT. This paper explores the underlying principles of these generative techniques, their applications in various fields, and their current challenges. We will review the significant advancements in these areas, compare (...) different generative methods, and discuss future directions for enhancing the quality and applicability of generative models. (shrink)

Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in dvance regarding: on-going construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall (...) prediction. In our proposed system we propose a new forecasting method that uses a Convolutional Neural Network monthly rainfall for a selected location. In our proposed system we are going to forecast the rainfall result based on the mean square error, mean absolute error and root mean square error, which we get in train and test of the dataset based deep learning technique. (shrink)

Cloud computing is the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet. It is a broad and deep platform that helps customers builds sophisticated, scalable applications. To get the full benefits, research on a wide range of topics is needed. While resource over provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the (...) cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning. (shrink)

Tasks, tools, and techniques that we perform, use, and acquire, define the elements of expertise which we value as the hallmarks of goal-driven behavior. Somehow, the creation of tools enables us to define new tasks, or is it that the envisioning of new tasks drives us to invent new tools? Or maybe it is that new tools engender new techniques which then result in new tasks? This jumble of issues will be explored and discussed in this diverse collection (...) of papers. Individually, few of the papers are related to each other by topic or by techniques of analysis. Collectively, all focus on tasks performed using tools and discuss the techniques of tool use which enable differences in performance and expertise across individuals, societies, and (even) species. -/- . (shrink)

Coronary Heart Disease (CHD) is one of the leading causes of death nowadays. Prediction of the disease at an early stage is crucial for many health care providers to protect their patients and save lives and costly hospitalization resources. The use of machine learning in the prediction of serious disease events using routine medical records has been successful in recent years. In this paper, a comparative analysis of different machine learning techniques that can accurately predict the occurrence of CHD (...) events from clinical data was performed. Four machine learning classifiers, namely Logistic Regression, Support Vector Machine (SVM), K- Nearest Neighbor (KNN), and Multi-Layer Perceptron (MLP) Neural Networks were identified and applied to a dataset of 462 medical instances and 9 features as well as the class feature from the South African Heart Disease data retrieved from the KEEL repository. The dataset consists of 302 records of healthy patients and 160 records of patients who suffer from CHD. In order to handle the imbalanced classification problem, the K-means algorithm along with Synthetic Minority Oversampling TEchnique (SMOTE) was used in this study. The empirical results of applying the four machine learning classifiers on the oversampled dataset have been very promising. The results reported using different evaluation metrics showed that SVM has achieved the highest overall prediction performance. (shrink)

“Pick a card, any card. This has to be a completely free choice.” the magician tells you. But is it really? Although we like to think that we are using our free will to make our decisions, research in psychology has shown that many of our behaviours are automatic and unconsciously influenced by external stimuli (Ariely, 2008; Bargh & Chartrand, 1999; Newell & Shanks, 2014; Nisbett & Wilson, 1977), and that we are often oblivious to the cognitive mechanisms that underpin (...) our decision (Wegner, 2002, 2003). Magicians have exploited this illusory sense of agency for a long time, and have developed a wide range of techniques to influence and control spectators’ choices of such things as card, word, or number (Annemann, 1933; Banachek, 2002a; Jones, 1994; Turner, 2015). These techniques are instances of what is called forcing. -/- Many forces are extremely effective, illustrating various weaknesses in our sense of control over decisions and their outcomes. Researchers have started to investigate them in various ways (Kuhn, Pailh s, & Lan, 2020; Olson, Amlani, Raz, & Rensink, 2015; Pailhes & Kuhn, 2020b, 2020c; Shalom et al., 2013) and are beginning to obtain valuable insights into decision-making processes as well as a better understanding of the cognitive mechanisms that lead people to experience an illusory sense of free will and of agency. -/- Although magicians have acquired large amounts of knowledge in covertly controlling people’s choices, much of this knowledge is only discussed in the context of individual magic tricks, or in books that are not readily accessible to non-magicans. As we and others have argued elsewhere (Ekroll, Sayim, & Wagemans, 2017; Kuhn, 2019; Kuhn, Amlani, & Rensink, 2008; Kuhn, Caffaratti, Teszka, & Rensink, 2014; Macknik et al., 2008; Olson et al., 2015; Olson, Landry, Appourchaux, & Raz, 2016; Shalom et al., 2013; Thomas, Didierjean, Maquestiaux, & Gygax, 2015), a particularly effective way of making this knowledge more available is via the creation of taxonomies centered around psychological mechanisms (Rensink & Kuhn, 2015). For example, the psychologically based taxonomy of misdirection (Kuhn et al., 2014) helps draw links between misdirection and formal theories of perception and cognition. -/- Our aim here is to apply a similar process to the knowledge magicians have about forcing. The present paper develops a psychologically based taxonomy of forcing techniques with two goals in mind. Firstly, it should help uncover the various psychological mechanisms that underlie forcing techniques. Secondly, it should facilitate knowledge transfer between magicians and psychologists. Among other things, this knowledge will allow researchers to gain new insights into the mechanisms underlying decision-making, and the feeling of free will and of agency over choice. We start by defining the magician’s force and then look at some of the past classifications of forcing. (shrink)

Effective ethics teaching and training must cultivate both the critical thinking skills and the character traits needed to deliberate effectively about ethical issues in personal and professional life. After highlighting some cognitive and motivational obstacles that stand in the way of this task, the article draws on educational research and the author's experience to demonstrate how cooperative learning techniques can be used to overcome them.

ABSTRACT "Why can’t I decide to be happy?" This is the question that encapsulates the meaning behind Gabriele’s story, the main character of the novel Il film delle emozioni (The Movie of Emotions; Calabretta 2007a, in Italian). Gabriele is a victim of his negative emotions, and is completely in the power of his self-blame and self-devaluative thinking, which he learns to change only at the end of the novel, thanks to creativity and to the artistic expression of his own traumatic (...) experiences (see Sparrow and Wegner 2006). The novel tells of Gabriele’s several attempts at writing, first, the script of an autobiographical "educational" movie on emotion regulation; and then at transforming it into a novel. In reality, it reveals itself as a book popularizing the most recent scientific knowledge on psychology of emotions; as a dramatization of a scientist’s life—of his interior, interpersonal, and social conflicts (as well as political ones); and as a dramatization of the creative process of writing. As we will see in this article, The Movie of Emotions is a very particular novel that has much to do with creativity viewed in three different aspects—creativity in the novel’s structure, creativity in the process of the novel’s creation, and proposed techniques to increase creativity. (shrink)

The importance of Big Data as a foundational component of the AI and ML landscape is not going away anytime soon. As a result, the past fifteen years have seen a tremendous investment in Big Data research. The purpose of this literature review is to compile the most recent results from Big Data studies conducted over the past fifteen years. The study will address questions about the main applications of Big Data analytics, the main challenges and limitations encountered by researchers, (...) and the present and future state of Big Data studies. The review follows a predetermined procedure that automatically examines five major digital libraries. Among the more recent branches of computer science is the study of large amounts of data. Social media, online shopping, blogs, financial institutions, healthcare providers, transactions, websites, applications, opinion forums, and a host of other sources all contribute to the accumulation of data. Various businesses, notably healthcare, make excellent use of it after processing. For data processing and analysis in the industrial sector, these massively generated datasets are indispensable. In order to investigate the value and potential of big data in healthcare and industrial processing applications, this article surveys the published works of numerous writers who have helped with data collecting, analysis, processing, and viewing. Data cleansing, missing value analysis, and outlier analysis are some of the opportunities and problems highlighted, in addition to the benefits and applications of big data. Outlier detection models, as well as methods for detecting and cleaning unclean data, were also suggested in this comprehensive review. (shrink)

I have been lecturing Analytic Philosophy course in English at Oles Honchar Dnipro National University, Ukraine, for three years. Teaching using CLIL (Content and Language Integrated Learning) techniques enables me to do it effectively. All three groups of my master’s-degree students who had learned analytic philosophy by CLIL techniques demonstrated good results of their learning. They not only achieved strong knowledge of analytic philosophy but also sufficiently improved their skills in English writing, speaking, reading, and listening.

The present study investigated freehand cutting technique in dressmaking as an entrepreneurial skill among secondary school students for sustainable development in Port Harcourt Metropolis. The researcher employed a descriptive survey research design. The study was conducted in Port Harcourt, Rivers State. The population for the study included all students in eight government secondary schools in Rivers State. A sample of 25 students was randomly selected from each of the schools, resulting in a total of 200 respondents. The researcher created a (...) self-made questionnaire. The results emphasized the importance of teaching freehand cutting technique in dressmaking in secondary schools, as well as the need to provide Nigerian youths with training in various skills, such as creativity and innovation, entrepreneurship skills, managerial experience, and record keeping. (shrink)

We present a framework that we are currently developing, that allows one to extract knowledge from the knowledge discovery in database (KDD) dataset. Data mining is a very active and space growing research area. Knowledge discovery in databases (KDD) is very useful in scientific domains. In simple terms, association rule mining is one of the most well-known methods for such knowledge discovery. Initially, database are divided into training and testing for the aid of fuzzy generating the rules using fuzzy rules (...) generation the set of rules are generated from the given dataset. From the generated rules, we are extracting the significant rules by using the improved artificial bee colony algorithm and cuckoo search algorithm (IABCCS). After extracting optimal knowledge from the dataset via rules, the data will be classified using fuzzy classifier with the aid of this finally we will classify the attack and normal. (shrink)

The technology known as artificial intelligence (AI) has become a game-changer, capable of completely altering a number of facets of civilization. But as AI grows more and more common, significant ethical questions arise that need to be answered. An overview of the main ethical issues surrounding artificial intelligence (AI) is given in this abstract, emphasizing the necessity of developing, implementing, and governing AI systems responsibly. First, fairness, accountability, and openness are the main ethical concerns surrounding AI. Inadvertent bias perpetuation in (...) training data by AI systems can result in unfair hiring, lending, and criminal justice outcomes. Careful design, objective data gathering, and ongoing monitoring to minimize and correct any potential biases are necessary to ensure fairness in AI systems. Second, two essential components of ethical AI are explainability and transparency. Understanding the reasoning behind the decisions made by some AI models is difficult due to their lack of interpretability, especially in high-stakes industries like healthcare and driverless cars. Establishing systems to offer defenses and explanations for AI results is crucial to fostering responsibility and confidence. Thirdly, data security and privacy are issues that AI brings up. AI systems frequently rely on enormous volumes of personal data, therefore their use needs to respect people's autonomy and adhere to privacy laws. To solve these ethical issues, it is essential to protect data from illegal access, obtain informed consent, and put strong security measures in place. Fourth, it's important to closely consider how AI will affect employment and socioeconomic inequality. AI has the potential to increase productivity and open up new opportunities, but it also has the potential to worsen already-existing inequality and cause job displacement. In order to mitigate the possible negative effects, ethical concerns call for developing inclusive economic policies, supporting retraining programs, and making sure that impacted workers have a fair transition. Furthermore, making ethical decisions is necessary when using AI in delicate fields like criminal justice, healthcare, and warfare. Artificial intelligence need to supplement human talents rather than supplant human discernment, and it ought to consistently take moral and ethical factors into account when making consequential decisions. Last but not least, a variety of stakeholders, including developers, legislators, and the general public, are accountable for ethical AI. Establishing ethical standards, codes of conduct, and regulatory frameworks that control the creation, use, and use of AI technology requires cooperation and interdisciplinary methods. (shrink)

One of the most significant challenges encountered by language learners is the fear of making mistakes, especially when speaking. This study evaluated the effectiveness of the Write, Rise, and Respond (WRR) technique in reducing learners’ fear of making oral mistakes. The WRR technique involves writing thoughts, sharing them when ready which requires standing, and receiving constructive feedback from teachers to foster a supportive learning environment. A quasi-experimental design using quantitative data collection, including means and t-tests, was employed. Ten (10) Grade (...) 11 students from the Humanities and Social Sciences (HUMSS) strand enrolled at Immaculate Conception College of Balayan Inc. for the Academic Year 2023-2024 were selected through purposive sampling. A Likert scale survey measured their fear levels. Over a three-week period, results revealed a statistically significant reduction in fear, with a general weighted mean of 3.45 for pre-activity and a general weighted mean of 1.75 for post-activity, respectively (p < 0.05). The WRR technique effectively reduced fear and enhanced confidence among Grade 11 HUMSS students, demonstrating its potential as a valuable tool in education. Building on these findings, future research could explore support programs like confidence-building workshops and one-on-one counseling, while also examining the long-term impact and broader applicability of the WRR technique across diverse student groups and educational settings. (shrink)

This article has highlighted some of the issues related to projects and how to deal with it. So often projects start and its completion becomes a challenge due to some the related issues discussed above. The project manager must monitor and control the human side of his project. This involves utilizing appropriate forms of power in managing the project team to obtain desired results. Project teams also need to manage stakeholder expectations through understanding their expectations, delivering on those expectations, and (...) communicating effectively (Kloppenborg, 2012). This will give the project manager the upper hand to deal with issues that may cause the failure of the project. (shrink)

Today e-commerce has had tremendous growth in the past years primarily due to changes in technology and customer’s buying behavior. One of the big shifts in the process has been the use of ML in advertising which has the capability to transform the marketing domain together with consumer interactions. This paper discusses the viability of using machine learning for designing realistic models of advertising to increase effectiveness of target and personalized advertising, as well as conversion rates in e-commerce. Several (...) class='Hi'>techniques are explored in the study, such as supervised and unsupervised learning, recommender systems, and content optimization with natural language processing. By using case studies and experimental models, we discuss how and to what extent ML is beneficial in e-commerce advertising transformation. The results presented in this paper indicate that using machine learning in advertising has a potential of dramatically improving the customer experience while simultaneously increasing brand recognition and sales. (shrink)