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  1. 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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  2. 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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  3. 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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  4. Money Without State.Andrew M. Bailey, Bradley Rettler & Craig Warmke - forthcoming - Philosophy Compass.
    In this article, we describe what cryptocurrency is, how it works, and how it relates to familiar conceptions of and questions about money. We then show how normative questions about monetary policy find new expression in Bitcoin and other cryptocurrencies. These questions can play a role in addressing not just what money is, but what it should be. A guiding theme in our discussion is that progress here requires a mixed approach that integrates philosophical tools with the purely technical results (...)
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  5. 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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  6. Robots as Powerful Allies for the Study of Embodied Cognition From the Bottom Up.Matej Hoffmann & Rolf Pfeifer - forthcoming - In Albert Newen, Leon De Bruin & Shaun Gallagher (eds.), The Oxford Handbook of 4E Cognition. Oxford University Press.
    A large body of compelling evidence has been accumulated demonstrating that embodiment – the agent’s physical setup, including its shape, materials, sensors and actuators – is constitutive for any form of cognition and as a consequence, models of cognition need to be embodied. In contrast to methods from empirical sciences to study cognition, robots can be freely manipulated and virtually all key variables of their embodiment and control programs can be systematically varied. As such, they provide an extremely powerful tool (...)
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  7. Ranking Theory.Gabriele Kern-Isberner, Niels Skovgaard-Olsen & Wolfgang Spohn - forthcoming - Knauff, M. & Spohn, W. (Eds). The Handbook of Rationality. MIT Press.
    Ranking theory is one of the salient formal representations of doxastic states. It differs from others in being able to represent belief in a proposition (= taking it to be true), to also represent degrees of belief (i.e. beliefs as more or less firm), and thus to generally account for the dynamics of these beliefs. It does so on the basis of fundamental and compelling rationality postulates and is hence one way of explicating the rational structure of doxastic states. Thereby (...)
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  8. Simulation and Controller Design of Thermal Spraying Processes.P. Nylén & U. Snis - forthcoming - Proceedings of Swedish Ai Society, Linköping.
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  9. Classification of A Few Fruits Using Deep Learning.Mohammed Alkahlout, Samy S. Abu-Naser, Azmi H. Alsaqqa & Tanseem N. Abu-Jamie - 2022 - International Journal of Academic Engineering Research (IJAER) 5 (12):56-63.
    Abstract: Fruits are a rich source of energy, minerals and vitamins. They also contain fiber. There are many fruits types such as: Apple and pears, Citrus, Stone fruit, Tropical and exotic, Berries, Melons, Tomatoes and avocado. Classification of fruits can be used in many applications, whether industrial or in agriculture or services, for example, it can help the cashier in the hyper mall to determine the price and type of fruit and also may help some people to determining whether a (...)
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  10. Detection of Brain Tumor Using Deep Learning.Hamza Rafiq Almadhoun & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):29-47.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is used as a (...)
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  11. Computational Logic. Vol. 1: Classical Deductive Computing with Classical Logic. 2nd Ed.Luis M. Augusto - 2022 - London: College Publications.
    This is the 3rd edition. Although a number of new technological applications require classical deductive computation with non-classical logics, many key technologies still do well—or exclusively, for that matter—with classical logic. In this first volume, we elaborate on classical deductive computing with classical logic. The objective of the main text is to provide the reader with a thorough elaboration on both classical computing – a.k.a. formal languages and automata theory – and classical deduction with the classical first-order predicate calculus with (...)
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  12. Problems and Solutions in Researching Computer Game Assisted Dialogues for Persons with Aphasia.Ylva Backman, Viktor Gardelli & Peter Parnes - 2022 - Designs for Learning 1 (14):46–51.
    In this paper, we describe technological advances for supporting persons with aphasia in philosophical dialogues about personally relevant and contestable questions. A computer game-based application for iPads is developed and researched through Living Lab inspired workshops in order to promote the target group’s communicative participation during group argumentation. We outline some central parts of the background theory of the application and some of its main features, which are related to needs of the target group. Methodological issues connected to the design (...)
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  13. The Form in Formal Thought Disorder: A Model of Dyssyntax in Semantic Networking.Farshad Badie & Luis M. Augusto - 2022 - MDPI AI 3:353–370.
    Formal thought disorder (FTD) is a clinical mental condition that is typically diagnosable by the speech productions of patients. However, this has been a vexing condition for the clinical community, as it is not at all easy to determine what “formal” means in the plethora of symptoms exhibited. We present a logic-based model for the syntax–semantics interface in semantic networking that can not only explain, but also diagnose, FTD. Our model is based on description logic (DL), which is well known (...)
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  14. Diagnosis of Pneumonia Using Deep Learning.Alaa M. A. Barhoom & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):48-68.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...)
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  15. Sarcasm Detection in Headline News Using Machine and Deep Learning Algorithms.Alaa Barhoom, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):66-73.
    Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...)
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  16. Sarcasm Detection in Headline News Using Machine and Deep Learning Algorithms.Alaa Barhoom, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):66-73.
    Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...)
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  17. Prediction of Heart Disease Using a Collection of Machine and Deep Learning Algorithms.Ali M. A. Barhoom, Abdelbaset Almasri, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):1-13.
    Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...)
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  18. Prediction of Heart Disease Using a Collection of Machine and Deep Learning Algorithms.Ali M. A. Barhoom, Abdelbaset Almasri, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):1-13.
    Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...)
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  19. Weakly Free Multialgebras.Marcelo E. Coniglio & Guilherme V. Toledo - 2022 - Bulletin of the Section of Logic 51 (1):109-141.
    In abstract algebraic logic, many systems, such as those paraconsistent logics taking inspiration from da Costa's hierarchy, are not algebraizable by even the broadest standard methodologies, as that of Blok and Pigozzi. However, these logics can be semantically characterized by means of non-deterministic algebraic structures such as Nmatrices, RNmatrices and swap structures. These structures are based on multialgebras, which generalize algebras by allowing the result of an operation to assume a non-empty set of values. This leads to an interest in (...)
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  20. Classification of Anomalies in Gastrointestinal Tract Using Deep Learning.Ibtesam M. Dheir & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):15-28.
    Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques have been proposed (...)
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  21. Retina Diseases Diagnosis Using Deep Learning.Abeer Abed ElKareem Fawzi Elsharif & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):11-37.
    There are many eye diseases but the most two common retinal diseases are Age-Related Macular Degeneration (AMD), which the sharp, central vision and a leading cause of vision loss among people age 50 and older, there are two types of AMD are wet AMD and DRUSEN. Diabetic Macular Edema (DME), which is a complication of diabetes caused by fluid accumulation in the macula that can affect the fovea. If it is left untreated it may cause vision loss. Therefore, early detection (...)
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  22. Constructing a Model for Estimating Learners’ Mental States Using Biometric Information and Reducing Labeling Costs Using Deep Learning生体情報による学習者個人の心的状態推定モデルの精度評価とラベリングコスト低減に関する実験的検討.Yoshihisa Furusawa, Yoshimasa Tawatsuji & Tatsunori Matsui - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):C-L66_1-10.
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  23. A Distributed Asynchronous Heuristic Algorithm in Generalized Mutual Assignment Problem.Kenta Hanada, Yuki Amemiya & Kenji Sugimoto - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):B-L81_1-11.
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  24. Counterfactual Propagation for Treatment Effect Estimation反事実伝播: 介入効果推定のための半教師付き学習.Shonosuke Harada & Hisashi Kashima - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):B-LA3_1-14.
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  25. Removing Partial Mismatches in Unsupervised Image Captioning擬似教師ありキャプション生成における部分的不一致の除去.Ukyo Honda, Atsushi Hashimoto, Taro Watanabe & Yuji Matsumoto - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):H-L82_1-12.
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  26. A Recommendation System for Cloud AI ServicesクラウドAIサービス推薦システムの提案.Atsushi Hoshino, Takumi Saito & Mizuki Oka - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):F-L65_1-8.
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  27. Ethical Risks of Intelligent Dialogue Systems From View of European Trends on AI欧州 AI動向からみる知的対話システムの倫理的リスク.Tagui Ichikawa - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-A_1-9.
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  28. Analysis of Information Search Around the Time of Childbirth: Estimating Probability Distributions of Search Dates Via Mathematical Optimization出産前後の情報検索の分析:数理最適化による検索日の確率分布推定.Jiro Iwanaga, Naoki Nishimura, Noriyoshi Sukegawa & Yuichi Takano - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):D-L74_1-11.
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  29. Diagnosis of Blood Cells Using Deep Learning.Ahmed J. Khalil & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):69-84.
    In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...)
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  30. Slot Filling with Data Augmentation That Allows the Use of Keyword and Context Information for Handling Unknown Slot Valuesキーワード・文脈情報の使い分けを可能にするデータ拡張を利用した未知語に対応する発話理解手法.Yuka Kobayashi, Tsuyoshi Kushima, Takami Yoshida, Hiroshi Fujimura & Kenji Iwata - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-D_1-14.
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  31. Fraudulent Financial Transactions Detection Using Machine Learning.Mosa M. M. Megdad, Samy S. Abu-Naser & Bassem S. Abu-Nasser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):30-39.
    It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...)
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  32. Evaluation of a Daily Interactive Chatbot That Exchanges Information About Others Through Long-Term Use in a Group of Friends友人グループ内での長期間利用による他者情報のやり取りを行う日常対話チャットボットの評価.Seiya Mitsuno, Yuichiro Yoshikawa, Midori Ban & Hiroshi Ishiguro - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-I_1-14.
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  33. A Proposal and Implement in Non-Task-Oriented Dialogue System of Risky Politeness StrategyRisky Politeness Strategyの提案と雑談対話システムへの実装.Tomoki Miyamoto, Nozomu Nagai, Yuto Mitsuta, Motoki Iwashita, Mizuki Endo, Akihiro Suzuki & Daisuke Katagami - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-G_1-16.
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  34. Generation Model for Head Nods Consistent with Features of Verbal Response Tokens相槌の特徴に一致した頷き生成モデル.Taiga Mori & Yasuharu Den - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-H_1-12.
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  35. Conclusion-Supplement Answer Generation for Non-Factoid QuestionsNon-Factoid型質問のための結論と理由で構成される回答文の生成手法.Makoto Nakatsuji & Hirofumi Yashima - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):A-L64_1-9.
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  36. Recent Advances in Crowd Movement Space Design and Control Using Crowd Simulation群集シミュレーションによる歩行空間設計と制御に関する研究動向.Ryo Nishida, Shusuke Shigenaka, Yusaku Kato & Masaki Onishi - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):J-LB1_1-16.
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  37. Input Utterance Complementation Method by Anaphora Resolution for Spontaneous Utterances on Spoken Dialog Systems音声対話システムのための自由発話に対応した照応解析による入力発話への話題補完手法.Ryota Nishimura, Raita Mori, Kengo Ohta & Norihide Kitaoka - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-F_1-13.
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  38. A Method for Network Construction Based on Communication Data on Business Chat Applicationビジネスチャットアプリ上のコミュニケーションデータに基づくネットワーク構築手法.Kenya Nonaka, Haruka Yamashita, Hajime Hotta & Masayuki Goto - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):E-L63_1-11.
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  39. Using Simulation in the Assessment of Voting Procedures: An Epistemic Instrumental Approach.Marc Jiménez Rolland, Julio César Macías-Ponce & Luis Fernando Martínez-Álvarez - 2022 - Simulation: Transactions of the Society for Modeling and Simulation International 98 (2):127-144.
    In this paper, we argue that computer simulations can provide valuable insights into the performance of voting methods on different collective decision problems. This could improve institutional design, even when there is no general theoretical result to support the optimality of a voting method. To support our claim, we first describe a decision problem that has not received much theoretical attention in the literature. We outline different voting methods to address that collective decision problem. Under certain criteria of assessment akin (...)
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  40. Estimating Time-Series Changes in Social Sensitivity for COVID-19 @ Twitter in Japan.Ryuichi Saito & Shinichiro Haruyama - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):C-L91_1-16.
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  41. Classification of Real and Fake Human Faces Using Deep Learning.Fatima Maher Salman & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):1-14.
    Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...)
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  42. Classification of Alzheimer's Disease Using Convolutional Neural Networks.Lamis F. Samhan, Amjad H. Alfarra & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):18-23.
    Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it is important (...)
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  43. Improvement of Task Allocation in TP Algorithm for MAPD Problem by Relaxation of Movement Limitation and Estimation of Pickup TimeMAPDの解法TPにおける移動範囲の制限の緩和と集荷時間の推定に基づくタスク割り当ての改善.Masanori Shimokawa & Toshihiro Matsui - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):A-L84_1-13.
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  44. Estimation of Macroeconomic Activity by Using Measured CO₂ Concentration Based on Satellite Observation Data衛星観測データに基づくCO₂濃度計測値を用いたマクロ経済活動の推計.Yoshiyuki Suimon & Hiroto Tanabe - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2).
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  45. Design Guidelines for Developing Systems for Dialogue System Competitions複数の対話システムコンペティションにおけるシステム開発の設計指針.Ryu Takeda, Kazunori Komatani, Keisuke Nakashima & Mikio Nakano - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-B_1-9.
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  46. Diverse Dialogue Generation by Deep Learning Methods Using Loss Function IncorporatingWord Statistics単語統計を損失関数に取り入れた深層学習による多様な雑談対話生成.Ayaka Ueyama & Yoshinobu Kano - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):G-L62_1-10.
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  47. Robust Slot Filling Modeling for Incomplete Annotations Using Segmentation-Based Formulation.Kei Wakabayashi, Johane Takeuchi & Mikio Nakano - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-E_1-12.
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  48. Dialogue-Filling: Response Generation Control in Retrieval-Generation Dialogue System対話穴埋め:検索・生成ベース雑談対話システムの発話制御手法.Qiang Xue, Tetsuya Takiguchi & Yasuo Ariki - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (3):IDS-C_1-9.
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  49. Scene Interpretation Method Using Transformer and Self-Supervised LearningTransformerと自己教師あり学習を用いたシーン解釈手法の提案.Kobayashi Yuya, Masahiro Suzuki & Yutaka Matsuo - 2022 - Transactions of the Japanese Society for Artificial Intelligence 37 (2):I-L75_1-17.
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  50. Papaya Maturity Classifications Using Deep Convolutional Neural Networks.Marah M. Al-Masawabe, Lamis F. Samhan, Amjad H. AlFarra, Yasmeen E. Aslem & Samy S. Abu-Naser - 2021 - International Journal of Engineering and Information Systems (IJEAIS) 5 (12):60-67.
    Papaya is a tropical fruit with a green cover, yellow pulp, and a taste between mango and cantaloupe, having commercial importance because of its high nutritive and medicinal value. The process of sorting papaya fruit based on maturely is one of the processes that greatly determine the mature of papaya fruit that will be sold to consumers. The manual grading of papaya fruit based on human visual perception is time-consuming and destructive. The objective of this paper is to the status (...)
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1 — 50 / 526