One of the main goals of machine learning methods is to build a model or hypothesis from a set of data (also called evidence). After this learning process, the quality of the hypothesis must be evaluated as precisely as possible. For instance, if prediction errors have negative consequences in a certain application domain of a model (for example, detection of carcinogenic cells), it is important to know the exact ABStrAct

/pdf/calibration-of-machine-learning-models-38rlb7qssq.pdf

Calibration of Machine Learning Models

Real-Time Process Algebra RTPA is a denotational mathematics for the algebraic modeling and manipulations of software system architectures and behaviors by the Unified Data Models UDMs and Unified Process Models UPMs. On the basis of the RTPA specification and refinement methodologies, automatic software code generation is enabled toward improving software development productivity. This paper examines designing and developing the RTPA-based software code generator RTPA-CG that transfers system models in RTPA architectures and behaviors into C++ or Java. A two-phrase strategy has been employed in the design of the code generator. The first phrase analyzes the lexical, syntactical, and type specifications of a software system modeled in RTPA, which results in a set of abstract syntax trees ASTs. The second phrase translates the ASTs into C++ or Java based on predesigned mapping strategies and code generation rules. The toolkit of RTPA code generator encompasses an RTPA lexer, parser, type-checker, and a code builder. Experimental results show that system models in RTPA can be rigorously processed and corresponding C++/Java code can be automatically generated using the toolkit. The code generated is executable and effective under the support of an RTPA run-time library.

Design and Implementation of an Autonomic Code Generator Based on RTPA

A real-time operating system RTOS provides a platform for the design and implementation of a wide range of applications in real-time systems, embedded systems, and mission-critical systems. This paper presents a formal design model for a general RTOS known as RTOS+ that enables a specific target RTOS to be rigorously and efficiently derived in real-world applications. The methodology of a denotational mathematics, Real-Time Process Algebra RTPA, is described for formally modeling and refining architectures, static behaviors, and dynamic behaviors of RTOS+. The conceptual model of the RTOS+ system is introduced as the initial requirements for the system. The architectural model of RTOS+ is created using RTPA architectural modeling methodologies and refined by a set of Unified Data Models UDMs. The static behaviors of RTOS+ are specified and refined by a set of Unified Process Models UPMs. The dynamic behaviors of the RTOS+ system are specified and refined by the real-time process scheduler and system dispatcher. This work is presented in two papers in serial due to its excessive length. The static and dynamic behavioral models of RTOS+ is described in this paper; while the conceptual and architectural models of RTOS+ has been published in IJSSCI 22.

The Formal Design Model of a Real-Time Operating System RTOS+: Static and Dynamic Behaviors

A strategy of automatic answer retrieval for repeated or similar questions in user-interactive systems by employing semantic question patterns is proposed in this paper. The used semantic question pattern is a generalized representation of a group of questions with both similar structure and relevant semantics. Specifically, it consists of semantic annotations or constraints for the variable components in the pattern and hence enhances the semantic representation and greatly reduces the ambiguity of a question instance when asked by a user using such pattern. The proposed method consists of four major steps: structure processing, similar pattern matching and filtering, automatic pattern generation, question similarity evaluation and answer retrieval. Preliminary experiments in a real question answering system show a precision of more than 90% of the method.

Toward Automatic Answers in User-Interactive Question Answering Systems

Composition of software applications from component parts in response to high-level goals is a long-standing and highly challenging goal. We target the problem of composition in flow-based information processing systems and demonstrate how application composition and component development can be facilitated by the use of semantically described application metadata. The semantic metadata describe both the data flowing through each application and the processing performed in the associated application code. In this paper, we explore some of the key features of the semantic model, including the matching of outputs to input requirements, and the transformation and the propagation of semantic properties by components.

Semantic Matching, Propagation and Transformation for Composition in Component-Based Systems

Generic cabling is a key component for multiplex cable wiring. It is one of the basic foundations of intelligent buildings. Using operation flow in generic cabling, the index constraints affecting generic cabling have been evolved in this paper. A mathematical model is built based on the ant colony algorithm with multiple constraints, and improvements were made on the original basis to extend the ant colony algorithm from the regular simple ant colony and structure to a multi-ant colony and structure. The equilibrium settlement of multiplex wiring is realized according to the introduction of the multi-ant colony model. The ant cycle model is combined to extend the optimization target from the local wiring path to the entire wiring path, and to solve the drawbacks existing in the regular ant colony algorithm and other search algorithms that take the local wiring path as the optimization target. The introduced retrospective algorithm make the ants avoid the path marked "invalid" in the subsequent search process and improves the search performance and convergence speed of the ant colony algorithm.

Generic Cabling of Intelligent Buildings Based on Ant Colony Algorithm

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Generic Cabling of Intelligent Buildings Based on Ant Colony Algorithm