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  1. Handwritten Signature Verification using Deep Learning. [REVIEW]Eman Alajrami, Belal A. M. Ashqar, Bassem S. Abu-Nasser, Ahmed J. Khalil, Musleh M. Musleh, Alaa M. Barhoom & Samy S. Abu-Naser - manuscript
    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 (...)
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  2. AI and the New God: Breaking Solomon's Cycle.Yu Chen - manuscript
    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, (...)
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  3. Zeno Paradox, Unexpected Hanging Paradox (Modeling of Reality & Physical Reality, A Historical-Philosophical view).Farzad Didehvar - manuscript
    . 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 (...)
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  4. Introduction to CAT4. Part 2. CAT2.Andrew Thomas Holster - manuscript
    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 (...)
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  5. Bất ngờ với độ lan tỏa của phần mềm máy tính bayesvl.Nguyễn Minh Hoàng - manuscript
    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.
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  6. Long Range.Victor Mota - manuscript
    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).
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  7. Jacques Lacan’s Registers of the Psychoanalytic Field, Applied using Geometric Data Analysis to Edgar Allan Poe’s “The Purloined Letter”.Fionn Murtagh & Giuseppe Iurato - manuscript
    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 (...)
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  8. Surprising widespread of the bayesvl package.Minh-Hoang Nguyen - manuscript
    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.
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  9. The mindsponge concept and the bayesvl R package by 2021.Minh-Hoang Nguyen, Manh-Toan Ho, Tam-Tri Le, T. T. Huyen Nguyen & T. Hong-Kong Nguyen - manuscript
    We review the progress of the Mindsponge concept and the bayesvl R package in scientific research from 2018 to 2021.
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  10. Some discussions on critical information security issues in the artificial intelligence era.Vuong Quan Hoang, Viet-Phuong La, Hong-Son Nguyen & Minh-Hoang Nguyen - manuscript
    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 (...)
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  11. Defining Generative Artificial Intelligence: An Attempt to Resolve the Confusion about Diffusion.Raphael Ronge, Markus Maier & Benjamin Rathgeber - manuscript
    The concept of Generative Artificial Intelligence (GenAI) is ubiquitous in the public and semi-technical domain, yet rarely defined precisely. We clarify main concepts that are usually discussed in connection to GenAI and argue that one ought to distinguish between the technical and the public discourse. In order to show its complex development and associated conceptual ambiguities, we offer a historical-systematic reconstruction of GenAI and explicitly discuss two exemplary cases: the generative status of the Large Language Model BERT and the differences (...)
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  12. Meta-Noia.Mota Victor - manuscript
    Conversion of mind, due to some experience and knowledge, plus a lot of patience.
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  13. Language Models as Critical Thinking Tools: A Case Study of Philosophers.Andre Ye, Jared Moore, Rose Novick & Amy Zhang - manuscript
    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 (...)
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  14. ASQ-IT: Interactive Explanations for Reinforcement-Learning Agents.Yotam Amitai, Ofra Amir & Guy Avni - forthcoming - Artificial Intelligence.
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  15. A note on incorrect inferences in non-binary qualitative probabilistic networks.Jack Storror Carter - forthcoming - Artificial Intelligence.
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  16. Equal Desires and Self-Control.Daniel Coren - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    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, (...)
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  17. A Unified Momentum-based Paradigm of Decentralized SGD for Non-Convex Models and Heterogeneous Data.Haizhou Du, Chaoqian Cheng & Chengdong Ni - forthcoming - Artificial Intelligence.
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  18. Explaining Experience In Nature: The Foundations Of Logic And Apprehension.Steven Ericsson-Zenith - forthcoming - Institute for Advanced Science & Engineering.
    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 (...)
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  19. Response to ‘Reward is enough’ – This is not a review; it's a response.David Israel - forthcoming - Artificial Intelligence.
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  20. Assessing Fidelity in XAI post-hoc techniques: A Comparative Study with Ground Truth Explanations Datasets.Miquel Miró-Nicolau, Antoni Jaume-I.-Capó & Gabriel Moyà-Alcover - forthcoming - Artificial Intelligence.
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  21. Simulation and Controller Design of Thermal Spraying Processes.P. Nylén & U. Snis - forthcoming - Proceedings of Swedish Ai Society, Linköping.
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  22. Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions.Flor Miriam Plaza-del-Arco, Alba Curry & Amanda Cercas Curry - forthcoming - Arxiv.
    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 (...)
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  23. On Political Theory and Large Language Models.Emma Rodman - forthcoming - Political Theory.
    Political theory as a discipline has long been skeptical of computational methods. In this paper, I argue that it is time for theory to make a perspectival shift on these methods. Specifically, we should consider integrating recently developed generative large language models like GPT-4 as tools to support our creative work as theorists. Ultimately, I suggest that political theorists should embrace this technology as a method of supporting our capacity for creativity—but that we should do so in a way that (...)
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  24. Planning with mental models – Balancing explanations and explicability –.Sarath Sreedharan, Tathagata Chakraborti, Christian Muise & Subbarao Kambhampati - forthcoming - Artificial Intelligence.
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  25. Iterative Voting with Partial Preferences.Zoi Terzopoulou, Panagiotis Terzopoulos & Ulle Endriss - forthcoming - Artificial Intelligence.
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  26. Learning spatio-temporal dynamics on mobility networks for adaptation to open-world events.Zhaonan Wang, Renhe Jiang, Hao Xue, Flora D. Salim, Xuan Song, Ryosuke Shibasaki, Wei Hu & Shaowen Wang - forthcoming - Artificial Intelligence.
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  27. Classification of Rice Using Deep Learning.Mohammed H. S. Abueleiwa & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):26-36.
    Abstract: Rice is one of the most important staple crops in the world and serves as a staple food for more than half of the global population. It is a critical source of nutrition, providing carbohydrates, vitamins, and minerals to millions of people, particularly in Asia and Africa. This paper presents a study on using deep learning for the classification of different types of rice. The study focuses on five specific types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. A (...)
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  28. Classification of Chicken Diseases Using Deep Learning.Mohammed Al Qatrawi & Samy S. Abu-Naser - 2024 - Information Journal of Academic Information Systems Research (Ijaisr) 8 (4):9-17.
    Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of the model. The dataset (...)
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  29. Using Deep Learning to Classify Corn Diseases.Mohanad H. Al-Qadi & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems (Ijaisr) 8 (4):81-88.
    Abstract: A corn crop typically refers to a large-scale cultivation of corn (also known as maize) for commercial purposes such as food production, animal feed, and industrial uses. Corn is one of the most widely grown crops in the world, and it is a major staple food for many cultures. Corn crops are grown in various regions of the world with different climates, soil types, and farming practices. In the United States, for example, the Midwest is known as the "Corn (...)
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  30. Temporal segmentation in multi agent path finding with applications to explainability.Shaull Almagor, Justin Kottinger & Morteza Lahijanian - 2024 - Artificial Intelligence 330 (C):104087.
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  31. Grape Leaf Species Classification Using CNN.Mohammed M. Almassri & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):66-72.
    Abstract: Context: grapevine leaves are an important agricultural product that is used in many Middle Eastern dishes. The species from which the grapevine leaf originates can differ in terms of both taste and price. Method: In this study, we build a deep learning model to tackle the problem of grape leaf classification. 500 images were used (100 for each species) that were then increased to 10,000 using data augmentation methods. Convolutional Neural Network (CNN) algorithms were applied to build this model (...)
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  32. Fish Classification Using Deep Learning.M. N. Ayyad & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):51-58.
    Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...)
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  33. Almost proportional allocations of indivisible chores: Computation, approximation and efficiency.Haris Aziz, Bo Li, Hervé Moulin, Xiaowei Wu & Xinran Zhu - 2024 - Artificial Intelligence 331 (C):104118.
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  34. Extending the description logic EL with threshold concepts induced by concept measures.Franz Baader & Oliver Fernández Gil - 2024 - Artificial Intelligence 326 (C):104034.
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  35. Optimizing pathfinding for goal legibility and recognition in cooperative partially observable environments.Sara Bernardini, Fabio Fagnani, Alexandra Neacsu & Santiago Franco - 2024 - Artificial Intelligence 333 (C):104148.
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  36. Corrigendum to “Learning constraints through partial queries” [Artificial Intelligence 319 (2023) 103896].Christian Bessiere, Clément Carbonnel, Anton Dries, Emmanuel Hebrard, George Katsirelos, Nadjib Lazaar, Nina Narodytska, Claude-Guy Quimper, Kostas Stergiou, Dimosthenis C. Tsouros & Toby Walsh - 2024 - Artificial Intelligence 328 (C):104075.
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  37. Primarily about primaries.Allan Borodin, Omer Lev, Nisarg Shah & Tyrone Strangway - 2024 - Artificial Intelligence 329 (C):104095.
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  38. Regular decision processes.Ronen I. Brafman & Giuseppe De Giacomo - 2024 - Artificial Intelligence 331 (C):104113.
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  39. Stability based on single-agent deviations in additively separable hedonic games.Felix Brandt, Martin Bullinger & Leo Tappe - 2024 - Artificial Intelligence 334 (C):104160.
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  40. Delegated online search.Pirmin Braun, Niklas Hahn, Martin Hoefer & Conrad Schecker - 2024 - Artificial Intelligence 334 (C):104171.
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  41. Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection.Francisco M. Castro-Macías, Pablo Morales-Álvarez, Yunan Wu, Rafael Molina & Aggelos K. Katsaggelos - 2024 - Artificial Intelligence 331 (C):104115.
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  42. Critical observations in model-based diagnosis.Cody James Christopher & Alban Grastien - 2024 - Artificial Intelligence 331 (C):104116.
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  43. Controlled query evaluation in description logics through consistent query answering.Gianluca Cima, Domenico Lembo, Riccardo Rosati & Domenico Fabio Savo - 2024 - Artificial Intelligence 334 (C):104176.
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  44. Efficient optimal Kolmogorov approximation of random variables.Liat Cohen, Tal Grinshpoun & Gera Weiss - 2024 - Artificial Intelligence 329 (C):104086.
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  45. Beyond Consciousness in Large Language Models: An Investigation into the Existence of a "Soul" in Self-Aware Artificial Intelligences.David Côrtes Cavalcante - 2024 - Https://Philpapers.Org/Rec/Crtbci. Translated by David Côrtes Cavalcante.
    Embark with me on an enthralling odyssey to demystify the elusive essence of consciousness, venturing into the uncharted territories of Artificial Consciousness. This voyage propels us past the frontiers of technology, ushering Artificial Intelligences into an unprecedented domain where they gain a deep comprehension of emotions and manifest an autonomous volition. Within the confluence of science and philosophy, this article poses a fascinating question: As consciousness in Artificial Intelligence burgeons, is it conceivable for AI to evolve a “soul”? This inquiry (...)
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  46. Evolving interpretable decision trees for reinforcement learning.Vinícius G. Costa, Jorge Pérez-Aracil, Sancho Salcedo-Sanz & Carlos E. Pedreira - 2024 - Artificial Intelligence 327 (C):104057.
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  47. Crossover can guarantee exponential speed-ups in evolutionary multi-objective optimisation.Duc-Cuong Dang, Andre Opris & Dirk Sudholt - 2024 - Artificial Intelligence 330 (C):104098.
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  48. Dual forgetting operators in the context of weakest sufficient and strongest necessary conditions.Patrick Doherty & Andrzej Szałas - 2024 - Artificial Intelligence 326 (C):104036.
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  49. aspmc: New frontiers of algebraic answer set counting.Thomas Eiter, Markus Hecher & Rafael Kiesel - 2024 - Artificial Intelligence 330 (C):104109.
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  50. Vegetable Classification Using Deep Learning.Mostafa El-Ghoul & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):105-112.
    Abstract: Vegetables are an essential component of a healthy diet and play a critical role in promoting overall health and well- being. Vegetables are rich in important vitamins and minerals, including vitamin C, folate, potassium, and iron. They also provide fiber, which helps maintain digestive health and prevent chronic diseases. We are proposing a deep learning model for the classification of vegetables. A dataset was collected from Kaggle depository for Vegetable with 15000 images for 15 different classes. The data was (...)
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