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In system development life cycle (SDLC), a system model can be developed using Data Flow Diagram (DFD). DFD is graphical diagrams for specifying, constructing and visualizing the model of a system. DFD is used in defining the requirements…

Software Engineering · Computer Science 2010-11-02 Rosziati Ibrahim , Siow Yen yen

Deep learning (DL) models have achieved paradigm-changing performance in many fields with high dimensional data, such as images, audio, and text. However, the black-box nature of deep neural networks is a barrier not just to adoption in…

Machine Learning · Computer Science 2020-02-25 Parmita Mehta , Stephen Portillo , Magdalena Balazinska , Andrew Connolly

We study a subclass of POMDPs, called Deterministic POMDPs, that is characterized by deterministic actions and observations. These models do not provide the same generality of POMDPs yet they capture a number of interesting and challenging…

Artificial Intelligence · Computer Science 2012-05-14 Blai Bonet

Medical Decision-Making (MDM) is a multi-faceted process that requires clinicians to assess complex multi-modal patient data patient, often collaboratively. Large Language Models (LLMs) promise to streamline this process by synthesizing…

Table extraction is an important but still unsolved problem. In this paper, we introduce a flexible and modular table extraction system. We develop two rule-based algorithms that perform the complete table recognition process, including…

Computer Vision and Pattern Recognition · Computer Science 2021-12-03 Marcin Namysl , Alexander M. Esser , Sven Behnke , Joachim Köhler

Deep Neural Networks (DNN) are core components for classification and regression tasks of many software systems. Companies incur in high costs for testing DNN with datasets representative of the inputs expected in operation, as these need…

Software Engineering · Computer Science 2024-03-29 Antonio Guerriero , Roberto Pietrantuono , Stefano Russo

Business process deviance refers to the phenomenon whereby a subset of the executions of a business process deviate, in a negative or positive way, with respect to its expected or desirable outcomes. Deviant executions of a business process…

Artificial Intelligence · Computer Science 2016-08-31 Hoang Nguyen , Marlon Dumas , Marcello La Rosa , Fabrizio Maria Maggi , Suriadi Suriadi

Despite the highest classification accuracy in wide varieties of application areas, artificial neural network has one disadvantage. The way this Network comes to a decision is not easily comprehensible. The lack of explanation ability…

Computer Vision and Pattern Recognition · Computer Science 2016-10-18 Tameru Hailesilassie

Deep Neural Networks (DNNs) are everywhere, frequently performing a fairly complex task that used to be unimaginable for machines to carry out. In doing so, they do a lot of decision making which, depending on the application, may be…

Machine Learning · Computer Science 2022-11-17 Avriti Chauhan , Mohammad Afzal , Hrishikesh Karmarkar , Yizhak Elboher , Kumar Madhukar , Guy Katz

Business process deviance refers to the phenomenon whereby a subset of the executions of a business process deviate, in a negative or positive way, with respect to {their} expected or desirable outcomes. Deviant executions of a business…

Artificial Intelligence · Computer Science 2021-11-25 Giacomo Bergami , Chiara Di Francescomarino , Chiara Ghidini , Fabrizio Maria Maggi , Joonas Puura

Not only are Deep Neural Networks (DNNs) black box models, but also we frequently conceptualize them as such. We lack good interpretations of the mechanisms linking inputs to outputs. Therefore, we find it difficult to analyze in…

Machine Learning · Computer Science 2020-06-29 Christopher Snyder , Sriram Vishwanath

A classical approach to designing binary image operators is Mathematical Morphology (MM). We propose the Discrete Morphological Neural Networks (DMNN) for binary image analysis to represent W-operators and estimate them via machine…

Computer Vision and Pattern Recognition · Computer Science 2024-02-12 Diego Marcondes , Junior Barrera

In sequential decision making, neural networks (NNs) are nowadays commonly used to represent and learn the agent's policy. This area of application has implied new software quality assessment challenges that traditional validation and…

Software Engineering · Computer Science 2023-12-18 Q. Mazouni , H. Spieker , A. Gotlieb , M. Acher

The rapid evolution of Large Language Models (LLMs) has markedly expanded their application across diverse domains, transforming how complex problems are approached and solved. Initially conceived to predict subsequent words in texts, these…

Artificial Intelligence · Computer Science 2024-07-11 Sumedh Rasal , E. J. Hauer

Graph mining is an important area in data mining and machine learning that involves extracting valuable information from graph-structured data. In recent years, significant progress has been made in this field through the development of…

Machine Learning · Computer Science 2024-12-30 Yuxin You , Zhen Liu , Xiangchao Wen , Yongtao Zhang , Wei Ai

While researchers increasingly use deep neural networks (DNN) to analyze individual choices, overfitting and interpretability issues remain as obstacles in theory and practice. By using statistical learning theory, this study presents a…

General Economics · Economics 2019-09-18 Shenhao Wang , Qingyi Wang , Nate Bailey , Jinhua Zhao

Planning represents a fundamental capability of intelligent agents, requiring comprehensive environmental understanding, rigorous logical reasoning, and effective sequential decision-making. While Large Language Models (LLMs) have…

Artificial Intelligence · Computer Science 2025-05-27 Pengfei Cao , Tianyi Men , Wencan Liu , Jingwen Zhang , Xuzhao Li , Xixun Lin , Dianbo Sui , Yanan Cao , Kang Liu , Jun Zhao

Table understanding is key to addressing challenging downstream tasks such as table-based question answering and fact verification. Recent works have focused on leveraging Chain-of-Thought and question decomposition to solve complex…

Computation and Language · Computer Science 2025-08-26 Thi-Nhung Nguyen , Hoang Ngo , Dinh Phung , Thuy-Trang Vu , Dat Quoc Nguyen

Currently many different modeling languages are used for workflow definitions in BPM systems. Authors of this paper analyze the two most popular graphical languages, with highest possibility of wide practical usage - UML Activity diagrams…

Software Engineering · Computer Science 2007-05-23 Audris Kalnins , Valdis Vitolins

Recent advancements in Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains. However, effective decision-making relies heavily on strong reasoning abilities. Reasoning is the foundation for…

Computation and Language · Computer Science 2025-06-30 Dana Alsagheer , Yang Lu , Abdulrahman Kamal , Omar Kamal , Mohammad Kamal , Nada Mansour , Cosmo Yang Wu , Rambiba Karanjai , Sen Li , Weidong Shi