Human Thinking Research Articles

Utilization of Artificial Intelligence in Strengthening the Pancasila Student Profile Project Integrated with STEM

As the essence of education, the curriculum will persistently undergo changes and renewal to align with societal needs and the ever-expanding global challenges. The integration of STEM and the Pancasila Student Profile Strengthening Project is essential in the context of education in Indonesia. By utilizing STEM, educators can contextually and relevantly teach Pancasila values, enabling students to comprehend scientific and technological concepts and incorporate these noble values into their daily lives. However, STEM learning in schools often faces challenges, such as limited resources, less innovative methods, and students' difficulties understanding abstract concepts. Technological advances have brought significant changes in various aspects of life in recent years. Artificial intelligence extends beyond computer science and informatics, permeating multiple disciplines. Educators can utilize the introduction of artificial intelligence (AI) in the education sector as a tool to enhance learning. AI is designed to process cognitive modeling of human thinking related to how a machine can record information, imitate, and modify automatically. Therefore, this study aims to investigate the integration of AI in P5 with STEM. We conducted this research at SMP Negeri 1 Purwosari using a qualitative approach. The research results demonstrate the use of AI in the integrated STEM P5 activities, beginning with activity planning, implementation, and evaluation. AI guides activity planning, integrates directly into technology, and functions as an automated assessment tool, delivering prompt and precise feedback. Therefore, overall, AI has outstanding potential to help improve the effectiveness of the learning process and introduce students to technology that will play an essential role in their future.

The Fourth Cognitive R/Evolution

Humans are at a turning point in their evolution. Many individuals and groups realise that there is need for change. This paper illustrates the difficulties evolution has created in human thinking, consequently producing many of the hurdles we face today. Linear problem-solving thinking is no longer adequate when creating a sustainable ecology, economy or society. Humans must look beyond the problem, and be creative about what kind of a world is wanted. Resolving problems using competition and conflict is not effective. Effective change will only take place by using cooperation, community and connection to develop a sustainable world. The paradigm shift in thinking is from problem-focused to possibility-focused approaches.

Process Axiology, Buddhism, Time, and Enduring Selves

Abstract This article explains that, why, and how process thinkers and Hartmanian axiologists affirm most, if not all, that Buddhism denies with respect to the positive goodness of ordinary conscious or aware lives, human and nonhuman. According to mainstream Buddhism, all the intrinsic, extrinsic, and systemic values of ordinary human existence are illusions, so we should avoid being involved with or attaching ourselves to any of them. By contrast, process thought and axiology affirm, cultivate, nurture, and encourage involvement with and attachment to all positive human values. Buddhism insists on the illusory nature of all intrinsic values (e.g., individual human selves, including ourselves), all extrinsic values (e.g., the everyday practical, useful, and sensory objects, processes, and activities of life), and all systemic values (e.g., all human thoughts, beliefs, and systems, except for the Four Noble Truths and the Eightfold Path). Process thinkers and Hartmanian axiologists insist that such things are very real and should be taken with utmost seriousness. By “illusory,” Buddhists may mean nothing more than that all such things are temporal, fleeting, transient. For this reason, they claim, all attachment to or positive valuation of such things leads to suffering. I fully agree with the transience of all momentary actualities, but I react to and deal very differently with the positive values involved in such transience.

Clinical reasoning, the art of medicine and artificial intelligence

"Clinical reasoning" refers to all the thought processes that physicians use to make a diagnosis and determine a treatment and care plan. Artificial intelligence (AI) will enhance, improve, and accelerate human clinical diagnostic thinking, but it is unlikely to replace it. Its application in medicine has the potential to drastically reduce medical diagnostic errors and give doctors more time to care for their patients. Here, we provide an overview of some of the key elements of clinical diagnostic reasoning and the potential impacts of AI on clinical reasoning.

An inherently interpretable deep learning model for local explanations using visual concepts.

Over the past decade, deep learning has become the leading approach for various computer vision tasks and decision support systems. However, the opaque nature of deep learning models raises significant concerns about their fairness, reliability, and the underlying inferences they make. Many existing methods attempt to approximate the relationship between low-level input features and outcomes. However, humans tend to understand and reason based on high-level concepts rather than low-level input features. To bridge this gap, several concept-based interpretable methods have been developed. Most of these methods compute the importance of each discovered concept for a specific class. However, they often fail to provide local explanations. Additionally, these approaches typically rely on labeled concepts or learn directly from datasets, leading to the extraction of irrelevant concepts. They also tend to overlook the potential of these concepts to interpret model predictions effectively. This research proposes a two-stream model called the Cross-Attentional Fast/Slow Thinking Network (CA-SoftNet) to address these issues. The model is inspired by dual-process theory and integrates two key components: a shallow convolutional neural network (sCNN) as System-I for rapid, implicit pattern recognition and a cross-attentional concept memory network as System-II for transparent, controllable, and logical reasoning. Our evaluation across diverse datasets demonstrates the model's competitive accuracy, achieving 85.6%, 83.7%, 93.6%, and 90.3% on CUB 200-2011, Stanford Cars, ISIC 2016, and ISIC 2017, respectively. This performance outperforms existing interpretable models and is comparable to non-interpretable counterparts. Furthermore, our novel concept extraction method facilitates identifying and selecting salient concepts. These concepts are then used to generate concept-based local explanations that align with human thinking. Additionally, the model's ability to share similar concepts across distinct classes, such as in fine-grained classification, enhances its scalability for large datasets. This feature also induces human-like cognition and reasoning within the proposed framework.

Sejarah Perkembangan Filsafat dan Sains pada Zaman Yunani

Ancient Greece was an important milestone in the history of the development of philosophy and science. This article will summarize the historical development of these two fields in Greece. In the 6th to 4th centuries BC, an intellectual culture grew in Greece known as the Classical Age. This research uses a library approach (library research). According to Mushtofa et al. (2020) bibliography research is research carried out in order to obtain information data obtained from various written sources. This research shows that the development of science in Ancient Greece and beyond was driven by the spirit of understanding the philosophy of humanism. The philosophy of humanism teaches that humans have the ability to regulate themselves and the universe around them. This belief has been present since ancient Greece and has been one of the main factors in the evolution of human thinking about nature.

Application and Use of Rhetoric in the Scientific Field of Civic Education

Studying rhetoric means discussing the concept and application of a philosophy of science in a particular scientific field. The philosophy of science is all human thoughts spontaneously respond to every problem in the context of the basic concept of the formation of a science or the relationship between one science and another for the good of mankind In this method to be able to study rhetoric as a use and application in the scientific field of civic education we can use literature study or literature study. A systematic scientific method of literature. In the explanation above, the application of rhetoric in the scientific field of civic education is a form of branch of science that aims to form good and smart citizenship in civic life. So in the delivery of civic education science in delivering learning material can be done by providing logical arguments by showing evidence directly or indirectly to be able to prove scientific Civic education application of rhetoric in scientific midwives Civic education is a branch of the discipline of law and politics packaged in education which aims to form Smart and Good Citizenship. With good, ethical, and emotional delivery supported by the delivery of strong and accurate evidence, and can argue logically in presenting the evidence.

Answering, Fast and Slow: Strategy enhancement of visual understanding guided by causality

In his classic book Thinking, Fast and Slow (Daniel, 2017), Kahneman points out that human thinking can be categorized into two main modes of thinking: a system that displays intuition and emotion (i.e., System 1), and a system that is more planned and relies more on logic, defined as System 2. This idea explains both rational and irrational motivations. In this paper, we revisit visual comprehension tasks based on this idea. At the theoretical level, we focus on the relationship between intuitive thinking, prior knowledge, and environmental information, and build a causal graph between the three. Further, inspired by the constructed causal graph, an intuitive optimization strategy with clear interpretability is proposed. In the validation session, we provide conclusions consistent with the theoretical analyses through extensive experiments on public datasets based on a visual quizzing task. Excitingly, our scheme demonstrates strong competitiveness in terms of generalizability without adding new technologies.

EEGER – A Model for Recognition of Human Emotion Using Brain Signal

Emotions significantly impact human thinking, judgment, health, and communication. EEG-based emotion detection has advanced with the use of Brain-Computer Interface (BCI) technology, proving more effective than other physiological data. Despite progress in affective computing, emotion recognition remains a challenge. However, it's increasingly common in brain–machine interfaces, and research shows EEG brain waves are valuable in identifying emotional states. This research introduces a novel automated system for emotion recognition using deep learning techniques on EEG data collected from the GAMEEMO dataset, where participants played emotional assessment games. The system is designed to identify four emotions experienced during gameplay. The proposed model, called EEGER, was trained exclusively on EEG signals and demonstrated a 99.99% accuracy with minimal computational time. Key to its efficiency is the use of LSTM (Long Short-Term Memory) classifiers, which simplify the process by automatically extracting relevant features. The system was tested across different learning rates and epoch values, showing that 10 epochs with a learning rate of 0.0001 were sufficient to achieve the best accuracy. EEGER was also compared with other methods like K-Nearest Neighbor (KNN), Linear Discriminant Analysis (LDA), and Adaptive Boosting (AdaBoost), outperforming them in both accuracy and efficiency. These findings suggest that EEGER offers a promising new approach to EEG-based emotion recognition, optimizing performance with lower complexity and computation time.

An optimized decentralized peer-to-peer energy trading system for smart grids incorporating uncertain renewable energy sources through fuzzy optimization

The significant issue in today's world is that the power system is undergoing on account of unafforded power generation and distribution. Consequently, improper utilization of renewable energy, as well as its pricing mechanism of electrical energy, is also a vital issue in transmission and distribution systems (TDS). In addition, in the context of upcoming power systems, ensuring energy stability and effective energy management have become paramount. This paper introduces a novel approach to address these challenges by proposing an optimal demand response grid-connected decentralized peer-to-peer (P2P) energy trading system. This system efficiently manages energy transactions among prosumers, the grid, and renewable energy sources (RES) under uncertain conditions. Fuzzy optimization (FO) is employed to facilitate interconnections between these entities. A fuzzy logic controller with intelligent rules governs the overall strategy and pricing mechanism based on prosumer power deviation (PPD). Inspired by human thinking, these rules prioritize P2P transactions, with surplus energy exported to the main grid (MG) and energy imported from the MG when necessary. Pricing adjusts dynamically with load demand. Simulation results demonstrate the effectiveness of the fuzzy rules across various conditions, ensuring proper system operation. The proposed model also proves that the P2P energy trading system has reduced power consumption by balancing the generated power and the load demand. The proposed system is environmentally friendly, emitting no harmful gases.

The Pivotal Role of Libraries in Sustainable AI Development

Artificial Intelligence (AI) has gained exceptional public and media coverage since the launch of the ChatGPT platform, a generative conversational intelligence, in November 2022. Nevertheless, AI is already an integral part of our digital daily lives, as we navigate through social networks, use our GPS, or consult recommendations on e-commerce websites. Due to its pervasive influence across all sectors of our societies, AI is gradually becoming a pivotal subject in terms of regulation, societal direction, and legislation. As early as 2021, UNESCO published a report presenting avenues for ethical considerations in AI. In June 2023, the European Union also established a regulatory framework outlining requirements and obligations for AI usage. As a digital manifestation and given the "new ways in which its use influences human thinking, interaction and decision-making and affects education, human, social and natural sciences, culture, and communication and information" (UNESCO. General Conference, 41st, 2021), public libraries have a role to play in enabling residents within their communities to grasp this technology. Their role is all the more significant as AI generates concerns and distrust (Gillath et al., 2021) among populations when "libraries also continue to enjoy a high level of trust and appreciation in most of their communities" (Arlitsch \& Newell, 2017). Understanding AI thus constitutes a new cornerstone for accessing the necessary information to advance sustainable development, as outlined in the Lyon Declaration (2014). Moreover, comprehension of AI aligns with the ethical concerns articulated by UNESCO in terms of explainability and transparency and aligns with several Sustainable Development Goals (SDGs) of the 2030 Agenda. These goals include quality education (4), industry, innovation and infrastructure (9), reduced inequalities (10), sustainable cities and communities (11), as well as responsible consumption and production (12). The role of public libraries in advancing the goals of the 2030 Agenda is beyond dispute (IFLA, 2016), and various digital literacies are already integral to their actions. As AI is predominantly developed by global economic giants and permeates all of our practices, "Shouldn’t [libraries] be the bastions of information literacy and information privacy in an AI world?" (Cox et al., 2018). Thus, to what extent can public libraries take on this subject to promote and offer relevant literacy? For this study, we will conduct a cross-analysis among three European countries—Spain, France, and Italy—to provide insights into the diverse ways in which AI influences professional practices. Through a literature review and semi-structured interviews, the objective is to delineate the challenges of Artificial Intelligence within the framework of the Agenda 2030 program. Subsequently, we will delve into the specificity of AI Literacy in comparison to Information Literacy, a practice already adopted by libraries. Finally, we will analyze the current and prospective role of AI in libraries to propose avenues for implementing concrete actions.

The impact of educational programmes on building safety culture in modern society

Safety culture is an important element in the development of human thinking before making decisions in emergency situations. The aim of the study is to determine the specifics of the impact of educational programmes on building safety culture in modern society. The authors achieved the aim of the study by employing of the method of analysis, the Likert scale, the impact ratio calculations, the criterion of psychological training, the response coefficient, the J. Phillips’ correlation coefficient. The study determined that it is necessary to take into account the development of psychological stability, the impact of possible risks for building a safety culture. It is also necessary to ensure consideration of simulated situations for identifying response mechanisms. The study established that the influence of educational programmes on building safety culture is related to the development of logical thinking. The practical significance of the work consists in determining the mechanisms that have the greatest impact on the possibility of forming a safety culture in the educational process. The research prospects will be related to the comparison of the effectiveness of the proposed mechanisms during the management of emergency situations in the context of martial law and the influence of adverse weather conditions.

KRITIK TERHADAP PENGAJARAN VISUALIASI DAN AFIRMASI TEOLOGI KEMAKMURAN BERDASARKAN EKSPOSISI KEJADIAN 15:5-6

What faith is and how to express it are two essential questions that seem easy but are complicated to answer. According to the prosperity gospel adherents, faith must be expressed through imagining (visualization) and saying (affirmation), as written in Genesis 15:5-6. However, for some groups, this teaching deviates from the truth according to the Bible and is more similar to the law of attraction. This article intends to criticize the visualization concept and to explore what is faith according to Genesis 15:5-6 by using the library research method combined with text exposition. The conclusion is that according to Genesis 15:5-6, true faith focuses on God's will entirely without the help of the power of human thoughts and words. Thus, visualization teaching, apart from being unbiblical, is also humanistic and tends to lead to syncretism.

Legal Information Culture in the Context of Digital Transformation of Society and the State

Introduction. Technosocial transformations resulting from the industrial and digital revolution Industry 4.0 initiate multiple changes in the organization of social life, culture, law, ways of thinking, activities, values, and worldview. There is reason to believe that there is a process of formation of a new kind of culture, which is not a subspecies or part of information or legal culture. Theoretical Basis. Methods. Information, technological, and digital transformations have become general social factors that are not localized at the level of tools, auxiliary means of organizing human activities and thinking. Culture is undergoing a change as a social phenomenon. The stage of development of the pre-digital legal culture has been completed. The conceptual range: culture, law, information, information culture, legal culture is complemented by a new concept: legal information culture. The methodological tools of interdisciplinarity only partially meet the needs of studying the changing statuses of culture and law. Conceptual, analog, and comparative thinking is in conflict with the so-called “digital thinking”, which is not related either to the new methodology or to its search. Results. Technological innovations given to man as a result of the industrial and digital revolution are not accompanied by the formation of an adequate culture and are capable of transforming the ontological status of man as a rational being, thinking independently, setting goals, making decisions and being able to bear responsibility for his actions. Law as a socio-valuable institution is experiencing the risks of its preservation on the same axiological and moral grounds. One of the risks is its replacement with a set of algorithmic functions for regulating relations. A person who owns a legal information culture is able to contribute to the preservation of rights focused on legal equality, freedom, justice, implemented under the condition of goal-setting, creative, conscious human activity. Discussion and Conclusion. The necessity of forming a legal information culture as a set of principles, values, knowledge, and competencies that ensure participants in information relations to achieve a model of lawful/ unlawful behavior based on awareness of the value of law and the priority value of a person is argued.

Аксиологический аспект воли в научном познании

Introduction. The article presents the axiological aspect of will as a phenomenon of a person's regulation of his behavior and scientific activity, in particular. The study of the mechanisms of volitional decisions in scientific knowledge is necessary, first of all, because the will is responsible for the formation of goals and the implementation of efforts to realize them. The purpose of philosophical research is to identify the ontological sources of the phenomenon of will and their axiological analysis in scientific activity leading to creative judgments. Theoretical analysis. The axiological approach allows us to explore the possibilities of the mind, as opposed to impulsive desires, in conditions of making volitional decisions both in science and other forms of knowledge. The ontological basis of will is the presence of an obstacle, overcoming which becomes the fulfillment of a goal. In scientific activity, the will prevents the manifestation of emotional excitement, acting as a determinant of scientific research activity. An axiological analysis of will as a value and a source of positive emotions demonstrates the achievement of a goal by satisfying the need to overcome an obstacle that has a correlation with the category of singularity. Conclusion. A value analysis of the phenomenon of will shows the possibilities of human thinking for the most productive scientific activity, expressed in a combination of the optimal level of emotional stress and strong will.

Misunderstandings Regarding Sampling and the Role of Statistics in AI.

Efforts in Artificial Intelligence (AI) to mimic human thinking often seem unbound. Therefore, creating proper guardrails in this context is the responsibility of the collective scientific community. Missteps in this process are inevitable. This Viewpoint is intended to correct two such missteps regarding the use of basic statistical methods and the role of statistics in AI. The criticality of statistics in the scientific enterprise encourages us to get it right.

Machine Learning-Driven GCC Loop Unrolling Optimization: Compiler Performance Enhancement Strategy Based on XGBoost

In contemporary compilers, the determination of the loop unrolling factor is traditionally based on manually crafted heuristic rules. This approach heavily relies on human intuition, which limits its ability to achieve optimized performance across diverse architectures and can sometimes even lead to performance declines. Additionally, developers face challenges in achieving cross-platform compatibility, often necessitating extensive redesign efforts. In response, this study introduces a method leveraging the XGBoost algorithm to predict the optimal loop unrolling factor for compiler optimization, thereby aiming to replace human thinking with machine learning methods and standardize development processes. Initially, the study gathers data on the loop unrolling factors as determined by profile guided optimization technology, analyzes program-specific loop feature vectors and employs cross-validation, including the Pearson correlation coefficient and feature importance ranking, to construct a dataset. Subsequent use of XGBoost to train this dataset models the decision-making process for selecting the most effective loop unrolling factor. The final step involves integrating XGBoost’s trained decision tree model into GCC to calculate the optimal loop unrolling factor during actual compilation. Empirical results on the RISC-V platform indicate that this new method, when tested against the SPEC CPU 2006 benchmark suite, offers up to 6.18% improvement in performance over the existing heuristic approach. It provides a new method for loop unrolling in compilers, and provides an innovative guide for the application of machine learning in compilers.

Influence of the Environment on al-Layth bin Sa’d´s School of Islamic Law

The aim of this study is to bring back to the light one of the forgotten Islamic jurist al-Layth bin Sa‘d, and find out how the environment may have influenced his legal reasoning. The first part focuses on the influence of a specific environment on human thinking in general and points to the factors influencing the formation of Islamic law in various areas in paticular. The rest of the paper discusses Layth ibn Sa‘d´s personality and the elements that may have contributed to his conception of legal thought; the very multi-religious nature of early Islamic Egypt has been identified as one of the significant elements that helped shape the central nature of his legal school. The conclusion of the study provides examples of some legal rulings issued by him, in which the key role of his environment is clearly demonstrated, and the different legal approach of other lawyers is pointed out.

Why can’t artificial language contain the truth? A focus on Foucault’s and Heidegger’s discussions

This article seeks to argue that although AI language has developed to the level where it can answer human questions, AI language cannot yet contain the truth. In the AI era, humans who speak their minds will no longer express their thoughts directly in words and will depend more on AI’s artificial language. However, it is only a question for now whether AI will be able to substitute for human speech and whether such a fact will contribute to the expansion of human thinking and the state of being. Accordingly, in this paper, we try to identify the limitations of artificial intelligence language by precisely clarifying the meaning of human language and discourse. Foucault and Heidegger’s discussion of discourse deals with issues of language, subject, existence, and authentic discourse. We use their discussions as a tool to illuminate our own perspectives. Therefore, we will re-analyze the language produced in the AI environment in relation to the issue of truth.

A Group Intuitionistic Fuzzy Exponential TODIM Method Considering Attribute Interactions Applied to Green Building Material Supplier Selection

Green building, driven by the goal of sustainable development, has prompted extensive attention to be paid to the environmental impact of its materials. However, some of the traditional methods of evaluating building material suppliers and attribute systems are not able to adapt to the new issues arising from the green context. This paper aims to provide a new solution for selecting green building material suppliers to enhance the green efficiency of buildings. Specifically, this paper presents a framework for evaluating and selecting suppliers of green building materials that meet the criteria of environmental friendliness and sustainability. A comprehensive evaluation attribute system is established, encompassing cost, quality, service level, delivery capability, and green and sustainable ability. Additionally, a group decision-making method based on the exponential TODIM (an acronym in Portuguese for Interactive and Multi-attribute Decision Making) and intuitionistic fuzzy numbers is developed to integrate expert opinions from diverse domains. Intuitionistic fuzzy numbers represent an extension of traditional fuzzy sets, offering a means of more fully and accurately responding to the inherent vagueness and hesitancy of human thinking. They can often prove invaluable when faced with problems containing uncertainty. Moreover, to obtain more precise attribute weights, the λ-fuzzy measure, Choquet integral, and Shapley value are employed to consider attribute interactions. Subsequently, a selection case involving six timber suppliers was proposed. Subsystem analysis was employed to ascertain the relative strengths and weaknesses of the various suppliers, with a view to facilitating future improvements. The findings indicated that green and sustainability capability attributes exert a considerable influence on the selection of green building material suppliers. Consequently, suppliers distinguished under this standard may encounter challenges in attaining exemplary rankings. Comparative analysis and robustness analysis have demonstrated the efficacy, superiority, and stability of the proposed framework. The findings of this paper can provide a reference for companies engaged in or planning to develop green buildings and help them choose green building material suppliers, which can help them achieve the expected green building efficiency and promote the sustainable development of the industry.