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Industrial Software Effort Estimation Development and Correction Effort

A., AS S., A-WF A., NS

The increase in software size and complexity in automotive and industrial domains not only leads to the improvement of new functionality but also to an increase in the defect rate. Defect rate is a...

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Machine learning approach to predict 1-year mortality after heart transplantation: a single-centre study

Allehyani, B Savo, MT Khwaji, A Al Kholaif, N Galzerano, D Al Buraiki, J Alamro, B Al Sergani, H Di Salvo, G Cozac, DA Pergola, V Khaliel, F

Aims Heart transplantation is a critical life-saving procedure for patients with end-stage heart failure. However, predicting postoperative mortality remains challenging. The aim of this study is t...

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The Model of Consciousness: An Analysis of Causation, Self, Gödel’s Incompleteness, and Buddhist Philosophy

Samarawickrama, M

This paper examines the limitations of analytical and computational methods in understanding reality, highlighting the secondary role of language and mathematics, which often leads to paradoxes. G ...

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Consciousness and Mathematics: A Number Theoretic Approach to Modelling Reality

Samarawickrama, M

This research analyses the fundamentals of numbers for interpreting consciousness and reality. Complementing G del s incompleteness theorems, we adopted number theory to explore non-referential and...

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The Mind, Experience, Observation, and Reality: A Framework and Technique for Fundamental Experience of Rūparealm1

Samarawickrama, M

This paper introduces a novel framework for understanding the fundamental experience of r parealm1 through the individual mind2 governing causation. We present a sensor-based model that captures th...

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Hamiltonian characterization of multi-time processes with classical memory

Goswami, K Roy, AK Srivastava, V Perez, B Giarmatzi, C Gilchrist, A Costa, F

A central problem in open quantum systems is the characterization of non-Markovian processes, where an environment retains the memory of its interaction with the system. A key distinction is whethe...

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Cyclist Near-Miss Detection Using Lightweight Deep Temporal Neural Networks

Saleh, K Grigorev, A Mihaita, A-S

Near-miss incidents, where cyclists narrowly avoid collisions, are critical for understanding and improving urban cycling safety but are often underreported in official statistics. This paper intro...

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A Novel Mixed-Integer Linear Programming Model for the Capacitated Arc Routing Problem Adapted to Roadside Management Operations

Castañeda-Rodríguez, I Mihaita, A-S Marche, B Dávila-Gálvez, S Camargo, M

Roadside management is an issue in many territories worldwide. Decision-makers face multiple challenges in finding the right combination in scheduling roadside maintenance activities while meeting ...

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Machine learning-based prediction model construction for type 2 diabetes mellitus: A comparison of algorithms and multi-level risk factor analysis

Xu, Q Ball, J Sun, J

BACKGROUND: Against the backdrop of the global high incidence of Type 2 diabetes mellitus (T2DM), existing prediction models are largely confined to single-dimensional risk factors, suffering from ...

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Challenging history taking encounters: a systematic review, meta-analysis and phenomenological framework.

Hossain, S Murray, K Zhang, L Jassem, AM Clarke, J Somers, J Dias, R Uridge, A Sharma, S Teodorczuk, A Keijzers, G McConnell, H Sun, J Amey, L Broadley, SA

OBJECTIVES: All physicians will experience challenging history taking encounters, where communication is impaired and negatively impacts the diagnostic process. The aims of this systematic review w...

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