The tile-based multiplayer game Mahjong is widely played in Asia and has also become increasingly popular worldwide. Face-to-face or online, each player begins with a hand of 13 tiles and players draw and discard tile...
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The tile-based multiplayer game Mahjong is widely played in Asia and has also become increasingly popular worldwide. Face-to-face or online, each player begins with a hand of 13 tiles and players draw and discard tiles in turn until they complete a winning hand. An important notion in Mahjong is the deficiency number(*** number in Japanese Mahjong) of a hand, which estimates how many tile changes are necessary to complete the hand into a winning hand. The deficiency number plays an essential role in major decision-making tasks such as selecting a tile to discard. This paper proposes a fast algorithm for computing the deficiency number of a Mahjong hand. Compared with the baseline algorithm, the new algorithm is usually 100 times faster and, more importantly,respects the agent's knowledge about available tiles. The algorithm can be used as a basic procedure in all Mahjong variants by both rule-based and machine learning-based Mahjong AI.
In our rapidly evolving technological landscape, AI tools have gained substantial power and integration across various domains. Through interviews and surveys conducted at a University in the Netherlands, we investiga...
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The forthcoming forensic sciences standard ISO/IEC 21043 is a methodological and technical standard, currently at the stage of Draft International Standard. When adopted, it will apply to all forensic disciplines, inc...
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Breast cancer is a widespread and serious condition that poses a significant threat to women's health globally, contributing significantly to mortality rates. Machine learning tools play a critical role in both th...
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Breast cancer is a widespread and serious condition that poses a significant threat to women's health globally, contributing significantly to mortality rates. Machine learning tools play a critical role in both the effective management and early detection of this disease. Feature selection (FS) methods are essential for identifying the most impactful features to improve breast cancer diagnosis. These methods reduce data dimensionality, eliminate irrelevant information, enhance learning accuracy, and improve the comprehensibility of results. However, the increasing complexity and dimensionality of cancer data pose substantial challenges to many existing FS methods, thereby reducing their efficiency and effectiveness. To overcome these challenges, numerous studies have demonstrated the success of nature-inspired optimization (NIO) algorithms across various domains. These algorithms excel in mimicking natural processes and efficiently solving complex optimization problems. Building on these advancements, we propose an innovative approach that combines powerful feature selection methods based on NIO techniques with a soft voting classifier. The NIO techniques employed include the Genetic Algorithm, Cuckoo Search, Salp Swarm, Jaya, Flower Pollination, Whale Optimization, Sine Cosine, Harris Hawks, and Grey Wolf Optimization algorithms. The Soft Voting Classifier integrates various machine learning models, including Support Vector Machines, Gaussian Naive Bayes, Logistic Regression, Decision Tree, and Gradient Boosting. These are used to improve the effectiveness and accuracy of breast cancer diagnosis. The proposed approach has been empirically evaluated using a variety of evaluation measures, such as F1 score, precision, recall, accuracy and Area Under the Curve (AUC), for performance comparison with individual machine learning techniques. The results demonstrate that the soft-voting ensemble technique, particularly when combined with feature selection based on the Jaya
The main goal behind mathematical cryptography is to keep messages and multimedia messages secret at a time when modern means of communication have spread and become very diverse. Fuzzy matrices as strong tools which ...
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In this paper, we propose two self-adaptive extragradient-like algorithms for solving pseudomonotone variational inequalities. We consider two cases: the mapping is Lipschitz continuous (with unknown modulus) and is n...
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A multiresolution chain coding scheme for contours based on Freeman chain codes in four direction is proposed. It progressively refines the grid size and encodes by the proposed R11 chain codes. Encoding and decoding ...
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We developed an information system using an object-oriented programming language and a distributed database (DDB) consisting of multiple interconnected databases across a computer network, managed by a distributed dat...
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This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models,considering the delay in converting susceptible individuals into infected *** significant delays eve...
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This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models,considering the delay in converting susceptible individuals into infected *** significant delays eventually resulted in the pandemic’s *** ensure the safety of the host population,this concept integrates quarantine and the COVID-19 *** investigate the stability of the proposed *** fundamental reproduction number influences stability *** to our findings,asymptomatic cases considerably impact the prevalence of Omicron infection in the *** real data of the Omicron variant from Chennai,Tamil Nadu,India,is used to validate the outputs.
An index is a tool for comparing a phenomenon or several phenomena dating back to different periods to know the amount of change in the phenomena or the difference between them. For example, we compare the price of a ...
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