{"title":"Data Mining Using Multi-Valued Logic Minimization","authors":"Tsutomu Sasao","doi":"10.1109/ISMVL57333.2023.00030","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00030","url":null,"abstract":"In a partially defined classification function, each input combination represents features of an example, while the output represents the class of the example. Each variable may have different radix. In this paper, we show a method to minimize the number of variables. Combined with a multiplevalued logic minimizer, data sets of examples are represented by a compact set of rules. Experimental results using University of California Irvine (UCI) benchmark functions show the effectiveness of the approach, especially for imbalanced data sets. The results are compared with J48 and JRIP. This approach produces explainable 100% correct rules, which are promising for bio-medical applications.","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121927367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Predicting the Development of Chronic Lung Disease in Neonataes from Chest X-ray Images Using Deep Learning","authors":"Ryunosuke Maeda, Daisuke Fujita, Kosuke Tanaka, Jyunichi Ozawa, Mitsuhiro Haga, Naoyuki Miyahara, Fumihiko Nanba, Syoji Kobashi","doi":"10.1109/ISMVL57333.2023.00020","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00020","url":null,"abstract":"Neonatal chronic lung disease (CLD) is the most common and serious lung disease in premature infants. No previous studies have used chest X-ray images. In this study, we propose to predict and classify patients with and without CLD from neonatal chest X-ray images using a convolutional neural network (CNN). We conducted a 5-segment cross-validation experiment using chest X-ray images of 115 subjects at 7 days of age. Accuracy and AUC values of 0.6 and 0.642 were obtained, respectively. Future work includes the development of an algorithm suitable for neonatal data and the estimation of other age groups.","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121019753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using S Gates and Relative Phase Toffoli Gates to Improve T-Count in Quantum Boolean Circuits","authors":"David Clarino, Shohei Kuroda, S. Yamashita","doi":"10.1109/ISMVL57333.2023.00037","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00037","url":null,"abstract":"Toffoli gates are an important primitive in reversible Boolean logic. In quantum computation, these Toffoli gates are composed using other elementary gates, most notably the Clifford+T basis. However, in fault-tolerant implementations of quantum circuits, a non-transversal gate like the T gate incurs extra cost relative to transversal gates like the S and CNOT gates. Relative-phase Toffoli Gates (RTOF) have been proposed as a way to minimize this \"T-depth\" at the cost of incurring a relative phase that could skew the final quantum states. While previous research has proposed a way to use transversal S gates to eliminate this relative phase, this paper proposes a novel form of the RTOF that incorporates S gates in order to simplify generation of the logic to return the phase","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128794733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Delta-Sigma Domain Signal Processing: A Review with Relevant Topics in Stochastic Computing","authors":"T. Waho, Akihisa Koyama, Hitoshi Hayashi","doi":"10.1109/ISMVL57333.2023.00027","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00027","url":null,"abstract":"The progress over the last 30 years on ΔΣ-domain signal processing (ΔΣ-SP) is reviewed, focusing on basic circuits such as adders, multipliers, and filters. Based on bitstream operations, ΔΣ-SP shares many advantages with stochastic computing (SC). Moreover, the noise-shaping properties inherent to the ΔΣ modulation play a crucial role in overcoming the challenges in SC. Neural network applications, a promising field in the future, are also described.","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116952705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Some Consistency Criteria for Many-Valued Judgment Aggregation","authors":"C. Fermüller","doi":"10.1109/ISMVL57333.2023.00048","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00048","url":null,"abstract":"Classical judgment aggregation has produced several well-known impossibility results that extend to a variety of logics, including many-valued logics. In this paper, we aim to complement these negative results by providing some positive ones, which we develop in response to an analysis of the discursive dilemma. Specifically, we investigate the use of the averaging operator, which is arguably the most natural operator in a many-valued setting, to generate consistent aggregated judgments in either Kleene-Zadeh or Łukasiewicz logic. Our results show that under certain conditions, the averaging operator can yield consistent aggregated judgments for specific types of agendas and judgment profiles.","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129303300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection of osteochondritis dissecans using convolutional neural networks for computer-aided diagnosis of baseball elbow","authors":"Kenta Sasaki, Daisuke Fujita, Kenta Takatsuji, Yoshihiro Kotoura, Tsuyoshi Sukenari, M. Minami, Yusuke Kobayashi, Yoshikazu Kida, Kenji Takahashi, Syoji Kobashi","doi":"10.1109/ISMVL57333.2023.00022","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00022","url":null,"abstract":"Baseball elbow is a kinetic disorder of the elbow caused by repetitive pitching in baseball. Osteochondritis dissecans (OCD), one of the most common forms of baseball elbow, is a disorder of the humeral capitellum of the elbow, and early detection of OCD is important. This study aims to create a model to detect OCD from ultrasound images of the elbow. The model is based on VGG16. The proposed method was validated by using 67 OCD subjects and 91 normal subjects. The results showed that the model achieved an accuracy of 88.5%, a precision of 87.9%, a recall of 97.0%, an F1 score of 0.910, and an AUC of 0.971.","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121630328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Natural Deduction with Explosion and Excluded Middle","authors":"N. Kamide","doi":"10.1109/ISMVL57333.2023.00016","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00016","url":null,"abstract":"In this study, new natural deduction systems for intuitionistic, classical, and Gurevich logics are introduced using the new rules of explosion and excluded middle, which correspond to the principle of explosion and the law of excluded middle, respectively. Gurevich logic is an extended three-valued logic obtained from intuitionistic logic by adding strong negation. Theorems for equivalence between these natural deduction systems and the corresponding previously proposed sequent calculi for the logics are proved. Normalization theorems for the proposed natural deduction systems for intuitionistic and Gurevich logics are proved as well.","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128348946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sefatul Wasi, S. Alam, Rashedur M. Rahman, M. A. Amin, Syoji Kobashi
{"title":"Kidney Tumor Recognition from Abdominal CT Images using Transfer Learning","authors":"Sefatul Wasi, S. Alam, Rashedur M. Rahman, M. A. Amin, Syoji Kobashi","doi":"10.1109/ISMVL57333.2023.00021","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00021","url":null,"abstract":"Kidney tumor is a health concern that affects kidney cells and may leads to mortality depending on their type. Benign tumors can be unproblematic whereas malignant tumors pose the threat of kidney cancer. Early detection and diagnosis are possible through kidney tumor recognition based on deep learning techniques. In this paper, a method based on transfer learning using deep convolutional neural network (DCNN) is proposed to recognize kidney tumor from computed tomography (CT) images. The proposed method was evaluated on 5284 images. The final accuracy, precision, recall, specificity and F1 score were 92.54%, 80.45%, 93.02%, 92.38% and 0.8628, respectively.","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123301370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Hirayama, Rin Suzuki, Katsuhisa Yamanaka, Y. Nishitani
{"title":"Quick Computation of the Lower Bound on the Gate Count of Toffoli-Based Reversible Logic Circuits","authors":"T. Hirayama, Rin Suzuki, Katsuhisa Yamanaka, Y. Nishitani","doi":"10.1109/ISMVL57333.2023.00038","DOIUrl":"https://doi.org/10.1109/ISMVL57333.2023.00038","url":null,"abstract":"We present a time-efficient lower bound $tilde sigma $ on the number of gates in Toffoli-based reversible circuits that represent a given reversible logic function. For the characteristic vector s of a reversible logic function, the value of $tilde sigma ({mathbf{s}})$ is almost the same as σ-lb (s), which is known as a relatively-efficient lower bound in terms of the evaluation time and the tightness. By slightly sacrificing the tightness of the lower bound, $tilde sigma $ achieves fast computation. We prove that $tilde sigma $ is a lower bound on σ-lb. Next, we show $tilde sigma $ can be calculated faster than σ-lb. The time complexity of $tilde sigma ({mathbf{s}})$ is О(n2), where n is the dimension of s. Experimental results to compare $tilde sigma $ and σ-lb are also given. The results demonstrate that the values of $tilde sigma ({mathbf{s}})$ are equal to those of σ-lb (s) for most reversible functions and that the computation time of $tilde sigma ({mathbf{s}})$ is much shorter than that of σ-lb(s).","PeriodicalId":419220,"journal":{"name":"2023 IEEE 53rd International Symposium on Multiple-Valued Logic (ISMVL)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133879612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}