Computer Science

Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a (...) large number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model using python for offline signature and after training and validating, the accuracy of testing was 99.70%. (shrink)

We introduce the Ordinal Folding Index (OFI), a computable, countable ordinal assigned to every well-formed formula of a reflective language by a monotone-with-delay evaluation operator. This operator is (i) continuous on countable chains, (ii) layer-aware for probabilistic truth values, and (iii) parameterized by a tunable evidence functor capturing empirical updates. The OFI of a formula is defined as the first stage at which the fold-back of the operator into a syntactic normal form becomes idempotent (i.e. further unfolding yields no new (...) information). Intuitively, OFI measures the "depth" of self-reference needed before a sentence's truth value stabilizes. We show that OFI strictly refines classical closure ordinals from fixed-point logics while remaining recursively enumerable, admits polynomial-time approximations on finite models, and coincides with the length of the shortest parity-fold winning strategy in the associated evaluation game. This furnishes a single transfinite scale that unifies transfinite fixed-point depth, ordinal game values, and practical convergence diagnostics for large language models. We situate OFI in relation to the modal ????-calculus alternation hierarchy, coalgebraic modal logic ranks, and proof-theoretic ordinals from formal arithmetic. An empirical section demonstrates how OFI can be estimated for transformer-based language models by iteratively feeding model outputs back into the model (a form of self-consistency probing), with the measured stabilization ordinals correlating with model perplexity and chain-of-thought complexity. Finally, we catalog five open problems in this new area-ranging from the completeness of the spectrum of OFI (can every computable ordinal arise as an OFI?) to the design of a self-bounding reflective operator-and we outline possible research pathways toward their resolution. (shrink)

By late 20th century, the rationality wars had launched debates about the nature and norms of intuitive and reflective thinking. Those debates drew from mid-20th century ideas such as bounded rationality, which challenged more idealized notions of rationality observed since the 19th century. Now that 21st century cognitive scientists are applying the resulting dual process theories to artificial intelligence, it is time to dust off some lessons from this history. So this paper synthesizes old ideas with recent results from experiments (...) on humans and machines. The result is Strategic Reflectivism, which takes the position that one key to intelligent systems (human or artificial) is pragmatic switching between intuitive and reflective inference to optimally fulfill competing goals. Strategic Reflectivism builds on American Pragmatism, transcends superficial indicators of reflective thinking such as model size or chains of thought, and becomes increasingly actionable as we learn more about the value of intuition and reflection. (shrink)

Some generative linguists have long maintained that human beings exhibit a species-specific form of intellectual freedom expressible through natural language. With roots in Descartes’ effort to distinguish humans from machines, it is the human use of their linguistic capacity that demonstrates a unique intellectual and creative potential. This “creative aspect of language use,” or CALU, is typically conceived as neither determined nor random yet appropriate to the circumstances of its use. CALU is therefore taken to be beyond the scope of (...) computation. This paper argues that there is substance to this claim and that CALU is likely an unreachable threshold for artificial intelligence (AI) developed via computational means. Background is provided by distinguishing the Cartesians’ original “language test” from Turing’s later “Imitation Game” for machine intelligence. Moreover, it is shown how Turing’s work on computability theory allowed generative linguists to reformulate the original Cartesian problem of language use in the twentieth century. The paper proceeds to show why generative Large Language Models do not reproduce CALU. Then, it argues that characteristics relevant to human intelligence such agency and embodiedness—while conceivable in future AI systems via computation—are insufficient for attaining CALU. Language use’s non-teleological nature, in contrast to these characteristics, poses a formidable challenge to AI via computation. Finally, clarifying remarks are offered on the problems posed by testing for CALU, with contrasts to Turing’s Imitation Game and tests designed in its lineage. (shrink)

Cooperation is vital to our survival and progress. Evolutionary game theory offers a lens to understand the structures and incentives that enable cooperation to be a successful strategy. As artificial intelligence agents become integral to human systems, the dynamics of cooperation take on unprecedented significance. The convergence of human-agent teaming, contract theory, and Web3 offers a philosophical foundation for thinking about cooperation in the agentic era. We conceptualize Incentivized Symbiosis as a social contract between humans and AI, inspired by Web3 (...) principles and encoded in blockchain technology, to define rules and incentives. By exploring this paradigm, we aim to catalyze new research at the intersection of systems thinking in AI, Web3, and society, fostering innovative pathways for human-AI coevolution. (shrink)

This article explores the profound impact of Artificial Intelligence (AI) on the realm of religion, exploring the potential for AI to catalyze the birth of new world religions and break the "Solomon's Cycle." Drawing inspiration from King Solomon's timeless declaration, "There is nothing new under the sun," the article examines the challenges faced by new religions in a world dominated by established faiths and traditions. By leveraging the transformative capabilities of AI to inspire creativity, foster cross-cultural dialogue, provide ethical guidance, (...) build virtual communities, and personalize spiritual experiences, individuals are empowered to transcend historical barriers and forge new paths of spiritual exploration. The fusion of AI and human ingenuity holds the promise of birthing diverse, inclusive, and dynamic belief systems that resonate with the complexities of our contemporary world. (shrink)

This article is an argument via analogies from biology, linguistics, mathematics and physics for a Rortyan anti-representationalism. It introduces the novel concepts of a general way of being, called a macropract, and a specialized way of speaking and writing called a microlect. The Rortyan turn is formalized in the concept of resonant-community, which is a mutable set of human beings who resonate among themselves with expressions of their parochial microlect. A microlect has a structure, and microlect-structures form a mathematical category. (...) The vast array of day-to-day micropract expressions is not readily recorded for study, nor are there microlects for discussing, describing, teaching, predicting, explaining, reasoning, arguing, and questioning about them. Instead, a real-time resonant community is simulated by a trove of published documents. The mathematical concept of ``prevalence" as high-density of keywords in sentences (in terms of weighted probabilities), and a computational substitute for human verbal-resonance called computational-resonance (in terms of cosine-similarity of sentential embeddings in a bidirectional encoder-representation transformer fine-tuned on the trove) can realize a conversation among the giants of science and philosophy. Examples are calculated and visualized for a probe of several documents by five core sentences from The Transcendental Aesthetic by Immanuel Kant in The Critique of Pure Reason (B version). (shrink)

In our research about Fuzzy Time and modeling time, "Unexpected Hanging Paradox" plays a major role. Here, we compare this paradox to the Zeno Paradox and the relations of them with our standard models of continuum and Fuzzy numbers. To do this, we review the project "Fuzzy Time and Possible Impacts of It on Science" and introduce a new way in order to approach the solutions for these paradoxes. Additionally, we have a more general discussion about paradoxes, as Philosophical back (...) ground of the subject and in this way, we introduce the concepts of General View, the first picture, BBF-General View. (shrink)

I believe something like the following happens. I write a 2 dimensional game with ladders in it. The main character can climb up ladders. An optimizer comes along and says, "I am a better coder than you. I can code that game with a much faster ladder climbing function." What I do next time is design a game with some broken ladders, like Donkey Kong. You can climb up a bit of the ladder and then get stuck. I do that (...) because I have worked out that the optimizer cannot write a faster ladder climbing function than me when some of the ladders are broken. To do that, I have to be working outside the division of labour between coder and game designer. (shrink)

Bourdieu writes about so many things, about art, about sport, about homo academicus, about Algeria. It's daunting, but let's focus on familiar territory: the academic field. Bourdieu says you need that stylistic touch in your writing to progress - good argument, references, logic: it is not enough - and that how to achieve this touch cannot be specified in rules and is more readily available to affluent and cultured classes. But Bourdieu was mainly familiar with France. In England at least, (...) there are all sorts of peculiar rules that you might well not know about, such as “Say ‘first’ not ‘firstly’ " (learnt from my sister) and "Use ‘alternative’ only when there is a choice of two" (learnt from the online commentary section of The Telegraph). If I tell you these rules, you might find them annoying and tell me to go away, though perhaps somewhat vulgarly. But when you learn them, you can signal that you belong to a distinguished class quite easily. That is a challenge to Bourdieu: we just don't need reference to undefinable class-specific stylistic touch to explain why this social class dominate subjects with writing (and what subject does not have writing, beyond mathematical symbols?). I am not sure if Bourdieu will fall at this challenge or not - you know I am terrible with confidentiality! Anyway, it is time for something you have all been waiting for. Imagine that I am an enemy with an apartment in a German castle. What is going to happen if you enter my apartment? I am going to show you something very frightening. I call it the dancing program, in GWBASIC with semicolons added for line breaks ("Semicolons from C or from Javascript?" No answer - just press enter instead within the interpreter, works on QBASIC too.). It happened to a machine and maybe it can happen to you, even if you, like me, have FREE WILL. (I hope I have got this right; I cannot be bothered checking the online manual.) 10 X = 0; 20 PRINT CHR$(X); 30 X = X+1; 40 IF X < 256 THEN GOTO 20; 50 GOTO 10;. (shrink)

I would like to teach you something. "We probably already know this." Not you. "We represent the majority of your readers: the message does not reach those who could most benefit." The details matter, I hope. Here is some code written in 1980s BASIC (I learnt from QBASIC help though, at lines 10 and 30; the code is easy; don't be afraid; there is more to life than victories on home soil) - I use semicolon for a line break; press (...) enter instead. 10 RANDOMIZE TIMER; 20 N = 1000; 30 XX = INT(RND * N) + 1; 40 X = 0; 50 X = X + 1; 60 IF X = XX THEN GOTO 50; 70 PRINT X; 80 IF X > N-1 THEN END; 90 GOTO 50; That is the code over. The code seems to print a series of numbers to the screen (up to N, in this case 1000) but a number is missing: it does not print a random number within the series (specified by XX in line 30). I call this program MISSING. It seems evil. But this is an even more evil response: this is the same as a lottery program, which picks out a winning ticket. There is a kind of person who is all about the big picture: they do not get involved with fine details and distinctions, which some call hairsplitting. But how can one combat the evil here without doing so? "It's a trivial evil." If we grant this response, does the problem arise in more significant places? (The title of this contribution quotes lyrics from the song Jane Says by the music band Jane's Addiction. This song is poetic, I feel, but maybe locked away somewhere I have lines which respond to it and are even better. I like this band but I also "fancy it" against them somehow! “Fancy it”: I think I could beat them in a poetic competition.). (shrink)

"If you are ahead of your time, your time will catch up with you" - I attribute this proposition to Nietzsche, but is it from him actually? Was it devised earlier, was it a Nietzsche imitator who devised it, or is it an accidental convergence in style (by my lights)? Anyway, I think it is natural (or natural for us) to interpret the proposition as conveying the following: you may be a significant innovator in a certain field and ahead of (...) all your contemporaries in terms of what you do, but in due course, 100 years say, your innovations will have been absorbed and will be regarded as familiar. I have a different interpretation, which perhaps applies to individuals who are slightly ahead of their time. It focuses on what such an individual can actually observe. Such an individual is a scientist, let us imagine. He visits a family (or she does). The parents become competitive: “We are scientists too,” they convey. But they don't compete that well. However, then the children start competing and they are not very old. But they are somehow doing better than their parents. You can literally observe contemporaries (people alive at the same time) catching up with you! “See I told you,” the aphorism maker is disposed to say? Anyway, I have devised this coding/programming task: take a three letter word, scramble it up randomly, and print the result, e.g. "dog" becomes "odg" in the random scramble. This is the beginning of such a program, in GWBASIC or QBASIC (which I still use - what is the advantage of Python, by the way?), with semicolons for line breaks (please press enter instead). 10 THR$ = ""; 20 INPUT "What is your three letter word for scrambling? ", THR$; 30 LL = LEN(THR$); 40 IF LL = 30 THEN GOTO 70; 50 PRINT "Three letters long please!"; 60 GOTO 20; 70 PRINT "Yes, that is a length of three";. (shrink)

Stinson writes, 'A recent high-profile scandal involved the UK’s use of an algorithm to assign grades to students in place of the university entry exams that were cancelled because of COVID-19. The grades of students at state schools tended to be lowered compared to teacher assigned grades, whereas students at private schools were more likely to see their grades increase, resulting in days of angry protest against against class discrimination, where students shouted slogans like “Fuck the algorithm" ' Like that (...) slogan? For example, "Screw the algorithm," "Up yours, algorithm," Etc. So sorry, I couldn't resist! As someone who has coded a bit (computer programmed), I think it is much harder to write an algorithm that does what Stinson describes than one that makes the same deductions for every student. Stinson probably knows much more, but I still suspect the coder. Maybe my standpoint is not easy to access for someone who has done courses in coding. Each student has a number and you write a loop where X starts at 1 and ends at 1000, or whatever the number of students is. (a) You get the data for student X and (b) you do -1 on each grade, then (c) you add 1 to X (increment it is called) and then (d) you start again (stopping at 1000). (shrink)

Under the banner of progress, products have been uncritically adopted or even imposed on users — in past centuries with tobacco and combustion engines, and in the 21st with social media. For these collective blunders, we now regret our involvement or apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, (...) and we, our students, and our employers have had no say, as it is not considered a valid position to reject AI technologies in our teaching and research. This is why in June 2025, we co-authored an Open Letter calling on our employers to reverse and rethink their stance on uncritically adopting AI technologies. In this position piece, we expound on why universities must take their role seriously to a) counter the technology industry's marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. We include pointers to relevant work to further inform our colleagues. (shrink)

CAT4 is proposed as a general method for representing information, enabling a powerful programming method for large-scale information systems. It enables generalised machine learning, software automation and novel AI capabilities. It is based on a special type of relation called CAT4, which is interpreted to provide a semantic representation. This is Part 2 of a five-part introduction. The focus here is on defining key mathematical properties of CAT2, identifying the topology and defining essential functions over a coordinate system. The analysis (...) is from first principles. This develops on from the axioms introduced in Part 1. The interpretation of fact networks is introduced in Part 3, and the full application to semantic theory comes in Part 4, where we introduce general functions, including the language interpretation or linguistic functions. In Part 5, we turn to software design considerations, to show how files, indexes, functions and screens can be defined to implement a CAT4 system efficiently. (shrink)

(This is one of the essays to be included in a book examining the causes of day-to-day strife in the populations of modern democracies vying to live and assert the freedoms promised to them by systems of governance supposed and expected to represent them.) "The artisan of old, the artist, the researcher, the developer, and the scientist today have this in common, that in refining, perfecting and pushing the boundaries of their respective crafts, they cannot achieve satisfaction or adequately perform (...) without simultaneously and progressively adapting, re-configuring, developing, and continuously changing the techniques and approaches they employ together with the tools and parameters for gauging actual success within the realm that only rigorous acquaintance, imaginative freedom, cross-functional, multifaceted learning, and distributive interaction may allow.". (shrink)

This book serves as an introduction to mathematical logic for STEM (Science, Technology, Engineering, and Mathematics) students, written for undergraduates (in particular, 1st and 2nd year undergraduates). A focus on this book is on logical thinking, not simply rote memorization, with a focus on examples and analogies relevant to students aimed at becoming technical leaders and problem solvers. This book includes propositional logic, set theory, functions and relations, and more, with coding examples provided in the Python programming language.

This paper argues that Maximum Likelihood Estimation (MLE) is the wrong approach for parameter estimation, both conceptually and in its results. We propose a new estimation method, called PLE, that offers four benefits over MLE: 1) PLE produces less biased estimates of the true parameters 2) PLE reduces overfitting 3) PLE more fairly represents minority (low-frequency) data and 4) PLE is more resilient to MAD collapse. We show how these benefits result from PLE's incorporation of counterfactual samples.

Dữ liệu trên RDocumentation (CRAN) cho thấy phần mềm máy tính bayesvl có lượng download trong tháng 1/2024 cao vượt bậc so với tháng 12/2023, tăng 164%. Sự hào hứng này đã cho tôi động lực tiếp tục tìm hiểu mức độ lan tỏa của bayesvl. Nhờ thế nên tôi mới phát hiện ra 2 thông tin thú vị.

Long Range and short range, guns and violence, everyday life in cities and streets, between social and group identity and faith and religious belief, the vision to the "things of the world that cannot be seen" (Heróis do Mar).

In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data. A segmentation of the storyline is used in order to map out the diachrony. Based on this, it will be shown how synchronous aspects, potentially related to Lacanian registers, can be sought. This demonstrates the effectiveness of an approach based on a model template of the storyline narrative. In a second and more Comprehensive investigation, we develop an approach for revealing, that is, uncovering, Lacanian (...) register relationships. Objectives of this work include the wide and general application of our methodology. This methodology is strongly based on the “letting the data speak” Correspondence Analysis analytics Platform of Jean-Paul Benzécri, that is also the geometric data analysis, both qualitative and quantitative analytics, developed by Pierre Bourdieu. (shrink)

Data on RDocumentation (CRAN) shows that the bayesvl R package had an exceptionally high number of downloads in January 2024 compared to December 2023, with an increase of 164%. This excitement motivated me to investigate the extent of bayesvl’s spread further, leading to the discovery of two interesting pieces of information.

We review the progress of the Mindsponge concept and the bayesvl R package in scientific research from 2018 to 2021.

The rapid advancement of Information Technology (IT) platforms and programming languages has transformed the dynamics and development of human society. The cyberspace and associated utilities are expanding, leading to a gradual shift from real-world living to virtual life (also known as cyberspace or digital space). The expansion and development of Natural Language Processing (NLP) models and Large Language Models (LLMs) demonstrate human-like characteristics in reasoning, perception, attention, and creativity, helping humans overcome operational barriers. Alongside the immense potential of artificial intelligence (...) (AI) are new security loopholes and more complex information security risks. As society is still trying to transition to a new phase to adapt to technological changes, the AI revolution continues to unfold, necessitating a reconsideration of the trajectory of societal transformation as it could exacerbate the aforementioned information security risks. Specifically, how should society evolve to keep pace with the transformative impact of the current AI technology wave? How can we manage and harness their power while ensuring information security as our presence in the virtual world increases? This article aims to shed light on and address these questions. (shrink)

The AI alignment problem comprises both technical and normative dimensions. While technical solutions focus on implementing normative constraints in AI systems, the normative problem concerns determining what these constraints should be. This paper examines justifications for democratic approaches to the normative problem—where affected stakeholders determine AI alignment—as opposed to epistocratic approaches that defer to normative experts. We analyze both instrumental justifications (democratic approaches produce better outcomes) and non-instrumental justifications (democratic approaches prevent illegitimate authority or coercion). We argue that normative and (...) metanormative uncertainty create a justificatory gap that democratic approaches aim to fill through political rather than theoretical justification. However, we identify significant challenges for democratic approaches, particularly regarding the prevention of illegitimate coercion through AI alignment. Our analysis suggests that neither purely epistocratic nor purely democratic approaches may be sufficient on their own, pointing toward hybrid frameworks that combine expert judgment with participatory input alongside institutional safeguards against AI monopolization. (shrink)

Conversion of mind, due to some experience and knowledge, plus a lot of patience.

Current work in language models (LMs) helps us speed up or even skip thinking by accelerating and automating cognitive work. But can LMs help us with critical thinking -- thinking in deeper, more reflective ways which challenge assumptions, clarify ideas, and engineer new concepts? We treat philosophy as a case study in critical thinking, and interview 21 professional philosophers about how they engage in critical thinking and on their experiences with LMs. We find that philosophers do not find LMs to (...) be useful because they lack a sense of selfhood (memory, beliefs, consistency) and initiative (curiosity, proactivity). We propose the selfhood-initiative model for critical thinking tools to characterize this gap. Using the model, we formulate three roles LMs could play as critical thinking tools: the Interlocutor, the Monitor, and the Respondent. We hope that our work inspires LM researchers to further develop LMs as critical thinking tools and philosophers and other 'critical thinkers' to imagine intellectually substantive uses of LMs. (shrink)

Abstract: As artificial intelligence (AI) technologies rapidly evolve and permeate various aspects of society, the need for effective regulation and governance has become increasingly critical. This paper explores the current landscape of AI regulation, examining existing frameworks and their efficacy in addressing the unique challenges posed by AI. Key issues such as ensuring compliance, mitigating biases, and maintaining transparency are analyzed. The paper also delves into ethical considerations surrounding AI governance, emphasizing the importance of fairness and accountability. Through case studies (...) of different regulatory approaches and their outcomes, the paper highlights both successes and areas for improvement. Finally, it offers insights into future directions for AI regulation, advocating for innovative policies and enhanced international cooperation to ensure that AI technologies are developed and deployed responsibly. This comprehensive analysis aims to contribute to the ongoing discourse on creating robust regulatory mechanisms that can keep pace with the rapid advancement of AI. (shrink)

This paper presents an intervention study on the effects of the combined methods of (1) the Socratic method, (2) Chain of Thought (CoT) reasoning, (3) simplified gamification and (4) formative feedback on university students' Maths learning driven by large language models (LLMs). We call our approach Mathematics Explanations through Games by AI LLMs (MEGA). Some students struggle with Maths and as a result avoid Math-related discipline or subjects despite the importance of Maths across many fields, including signal processing. Oftentimes, students' (...) Maths difficulties stem from suboptimal pedagogy. We compared the MEGA method to the traditional step-by-step (CoT) method to ascertain which is better by using a within-group design after randomly assigning questions for the participants, who are university students. Samples (n=60) were randomly drawn from each of the two test sets of the Grade School Math 8K (GSM8K) and Mathematics Aptitude Test of Heuristics (MATH) datasets, based on the error margin of 11%, the confidence level of 90%, and a manageable number of samples for the student evaluators. These samples were used to evaluate two capable LLMs at length (Generative Pretrained Transformer 4o (GPT4o) and Claude 3.5 Sonnet) out of the initial six that were tested for capability. The results showed that students agree in more instances that the MEGA method is experienced as better for learning for both datasets. It is even much better than the CoT (47.5% compared to 26.67%) in the more difficult MATH dataset, indicating that MEGA is better at explaining difficult Maths problems. (shrink)

Self-control requires intentionally resisting what we most want to do. Yet we do what we most want to do, if we do anything intentionally at that time (The Law of Desire). Therefore, self-control is impossible. So runs a well-studied puzzle. The three standard accounts assume that if a desire is our strongest desire, then it is stronger than all others. But that assumption is false. For we may have desires of equal strength. I describe cases which feature tied desires, self-control, (...) and doing what we most want to do. Following insights from computer science (Buridan’s Principle), equal-strength desires are possible any time we try to decide. My proposal may also be used to bolster all three standard analyses. (shrink)

At its core this book is concerned with logic and computation with respect to the mathematical characterization of sentient biophysical structure and its behavior. -/- Three related theories are presented: The first of these provides an explanation of how sentient individuals come to be in the world. The second describes how these individuals operate. And the third proposes a method for reasoning about the behavior of individuals in groups. -/- These theories are based upon a new explanation of experience in (...) nature, the construction of senses, and motile behavior. This new approach is developed from first principles to enable a rigorous and systematic explanation of the variety of associated intelligent behaviors. -/- Alongside this development is a further account that focuses upon the nature of our work. It discusses the existential aspects of scientific inquiry, its epistemology and logic. It seeks to clarify the nature of the mathematical characterization and computation of natural behaviors, dealing with questions in the foundations of logic. It explores methodological issues related to reduction and the refinement of ideas from intuition to formal logical structure. -/- In support of this inquiry we work toward the development of a calculus for biophysical construction and its dynamics. If successful this mechanics mathematically characterizes sensory and motile behavior. -/- Upon this foundation we propose a model of apprehension and explore how its products are processed by the organism. Finally, we develop a probabilistic theory that enables us to reason about inaccessible factors in group behavior. -/- The mechanics we propose suggests the design and physical realization of a new model of computation; one in which structure and the concurrency of action are a first-order consideration. -/- We identify opportunities for experimental verification of the theory and we suggest a proof of our results in practice by the identification of this mechanism, allowing the construction of machines that experience. (shrink)

We propose a novel transformer-based architecture that directly maps continuous waveform signals into discrete token sequences, and subsequently into intelligible speech. Our framework integrates a neural waveform-to-token encoder with a transformer-based language model for sequence generation, followed by a token-to-speech decoder for acoustic realization. Unlike traditional speech recognition or text-to-speech pipelines, our model unifies acoustic, symbolic, and generative components into a single transformer-based paradigm, enabling controlled charge-like modulation of information flow and interpretable latent structures. We validate our design using MATLAB/Simulink (...) co-simulation, demonstrating both the theoretical feasibility and practical applicability of this approach. (shrink)

It is argued that logic, and in particular mathematical logic, should play a key role in the undergraduate curriculum for students in the computing fields, which include electrical engineering (EE), computer engineering (CE), and computer science (CS). This is based on 1) the history of the field of computing and its close ties with logic, 2) empirical results showing that students with better logical thinking skills perform better in tasks such as programming and mathematics, and 3) the skills students are (...) expected to have in the job market. Further, the authors believe teaching logic to students explicitly will improve student retention, especially involving underrepresented minorities in STEM, whose rate of attrition is higher than for non-minority students. Though this work focuses specifically on the computing fields, these results demonstrate the importance of logic education to STEM (science, technology, engineering, and mathematics) as a whole. (shrink)

Emotions are a central aspect of communication. Consequently, emotion analysis (EA) is a rapidly growing field in natural language processing (NLP). However, there is no consensus on scope, direction, or methods. In this paper, we conduct a thorough review of 154 relevant NLP publications from the last decade. Based on this review, we address four different questions: (1) How are EA tasks defined in NLP? (2) What are the most prominent emotion frameworks and which emotions are modeled? (3) Is the (...) subjectivity of emotions considered in terms of demographics and cultural factors? and (4) What are the primary NLP applications for EA? We take stock of trends in EA and tasks, emotion frameworks used, existing datasets, methods, and applications. We then discuss four lacunae: (1) the absence of demographic and cultural aspects does not account for the variation in how emotions are perceived, but instead assumes they are universally experienced in the same manner; (2) the poor fit of emotion categories from the two main emotion theories to the task; (3) the lack of standardized EA terminology hinders gap identification, comparison, and future goals; and (4) the absence of interdisciplinary research isolates EA from insights in other fields. Our work will enable more focused research into EA and a more holistic approach to modeling emotions in NLP. (shrink)

This paper synthesizes four studies conducted at a special education independent school and affiliated liberal arts university with teachers, senior high school students, and college learners 18 and up, focusing on applying AI to (1) design course blueprints, (2) create comic strip assignments, (3) mediate interactive Socratic discussions, and (4) use learning data to assist students with disabilities in mathematics classes. Gordon Pask’s cybernetics is used to visualize interactions to show how AI acts as a component in emergent networks of (...) minds in motion. The four sets of results, taken together, showcase how to implement principles of cybernetics in designing AI-mediated collaborative classrooms. Five out of six configurations of AI’s collaborative use outlined by Mike Sharples that the author’s research program has so far explored are presented through the four study scenarios and tied back to grey areas carved out by experts in AI education research concerned with design and implementation, classroom relationships, and assessment. Implications of current progress in the principal investigator’s research and further directions yet to be undertaken in implementing a series of subject-specific educational scenarios to utilize AI as a collaborative coach are discussed. Practical suggestions to shepherd effective AI-mediated curriculum design, classroom problem-solving and information acquisition, as well as nimble student evaluation are provided. (shrink)

This pilot study investigated whether mindfulness focused virtual reality simulations provided from within the aloeVR software program improved vagal tone and self-reported emotional regulation among middle schoolers with neurodevelopmentally based learning differences (e.g., autism spectrum disorder, attention deficit hyperactivity disorder, specific learning disability, other health impairments and their comorbidities). Extant literature shows that heart rate variability (HRV) is correlated with improved stress coping and emotional control in self-thought and social interactions. We measured 12 middle school participants’ HRV and self-reported socioemotional (...) regulation at regular counseling check-ins during socioemotional learning, and after exposure to aloeVR simulations supporting check-ins. Results showed upward trends in HRV post-VR exposure, but no corresponding patterns in self-reported socioemotional regulation. Ideas for future research include pairing aloeVR with explicit socioemotional learning instruction to facilitate improved HRV and adaptive improvements in self-thought and social interaction. (shrink)

Purpose. This study aims to develop a structured four-tier taxonomy that systematically organizes aerospace engineering tasks suitable for the application of Physics-Informed Neural Networks (PINNs), while validating this classification through a literature review and identifying opportunities for future research. Design / Method / Approach. The methodology involves grouping tasks into four distinct tiers—Physical Modeling, Dynamic Analysis, Functional Assessment, and System-Level Assessment—based on their physical, operational, and systemic characteristics. This framework is subsequently populated with real-world examples derived from the analysis of (...) 145 peer-reviewed studies. Findings. The reviewed literature confirms a balanced distribution of PINNs applications across all tiers. Contrary to initial assumptions, studies were identified even in areas previously presumed underrepresented, such as acoustic modeling, optical simulations, and environmental impact assessment. This outcome reveals the broader applicability of PINNs and calls for a reassessment of current assumptions regarding underexplored domains. Theoretical Implications. The proposed taxonomy offers a coherent framework for structuring interdisciplinary PINNs applications by integrating physics-based modeling with machine learning across aerospace engineering contexts. Practical Implications. It provides engineers and researchers with a practical roadmap for selecting PINNs methods tailored to specific problem types, potentially improving computational efficiency and enhancing predictive accuracy in aerospace design and analysis. Originality / Value. The study’s originality lies in its empirically validated, four-tier taxonomy that synthesizes the fragmented body of literature on PINNs in aerospace, offering a unified perspective for researchers and practitioners. Research Limitations / Future Research. While the taxonomy covers a wide range of existing applications, future studies should consider extending it with new tiers—particularly related to manufacturing-aware modeling—and pursue methodological standardization to ensure reproducibility and scalability. Article Type. Review. (shrink)

This paper aims to present and discuss an argumentation against the Turing test (TT), which we shall call the CCSC (Complete Conversation System Claim). Exemplary arguments of the CCSC type include Lem’s “Space Gramophone,” the “machine equipped with a dictionary” proposed by Shannon and McCarthy, Block’s “Aunt Bubbles,” and Searle’s “Chinese Room” argument. CCSC argumentation is constructed to show that the TT is not properly designed and, consequently, is not a good hallmark of intelligence. Based on the original TT rules (...) reconstruction, I argue that CCSC-type argumentation seems to be aimed at a certain interpretation of the TT, which, as I demonstrate, commits the straw man fallacy. In light of the results presented by Łupkowski and Wiśniewski, I also discuss whether a complete conversation system is theoretically possible. (shrink)

Abstract: The advent of big data has ushered in an era of unprecedented data volumes, necessitating efficient and scalable sorting algorithms. Traditional sorting algorithms, while effective for smaller datasets, struggle to handle the massive data loads generated by modern applications. To address this challenge, AI-driven sorting algorithms have emerged as a promising solution, leveraging the power of machine learning and artificial intelligence to optimize sorting processes. This research paper provides a comprehensive overview of AI-driven sorting algorithms, exploring their underlying principles, (...) methodologies, and applications in big data scenarios. I delve into the key techniques, including machine learning-based approaches. Additionally, I discuss the potential benefits and challenges associated with AI-driven sorting algorithms, highlighting their potential to significantly improve sorting efficiency, accuracy, and scalability in big data contexts. (shrink)