Enhancing unity-based AR with optimal lossless compression for digital twin assets.

The rapid development of Digital Twin (DT) technology has underlined challenges in resource-constrained mobile devices, especially in the application of extended realities (XR), which includes Augmented Reality (AR) and Virtual Reality (VR). These challenges lead to computational inefficiencies that negatively impact user experience when dealing with sizeable 3D model assets. This article applies multiple lossless compression algorithms to improve the efficiency of digital twin asset delivery in Unity's AssetBundle and Addressable asset management frameworks.

A bi-annotated Malay-English code-switching (Manglish) dataset of X posts for biological gender identification and authorship attribution.

Low-resource languages, like Malay, face the threat of extinction when linguistic resources become scarce. This paper addresses the scarcity issue by contributing to the inventory of low-resource languages, specifically focusing on Malay-English, known as Manglish. Manglish speakers are primarily located in Malaysia, Indonesia, Brunei, and Singapore.

Robustness evaluations of pathway activity inference methods on gene expression data.

Background: With the exponential growth of high-throughput technologies, multiple pathway analysis methods have been proposed to estimate pathway activities from gene expression profiles. These pathway activity inference methods can be divided into two main categories: non-Topology-Based (non-TB) and Pathway Topology-Based (PTB) methods. Although some review and survey articles discussed the topic from different aspects, there is a lack of systematic assessment and comparisons on the robustness of these approaches.

A refactoring categorization model for software quality improvement.

Refactoring, a widely adopted technique, has proven effective in facilitating and reducing maintenance activities and costs. Nonetheless, the effects of applying refactoring techniques on software quality exhibit inconsistencies and contradictions, leading to conflicting evidence on their overall benefit. Consequently, software developers face challenges in leveraging these techniques to improve software quality.

Corrigendum to "Adoption of knowledge-graph best development practices for scalable and optimized manufacturing processes" [MethodsX Volume 10(2023) 102124].

[This corrects the article DOI: 10.1016/j.mex.

Adoption of knowledge-graph best development practices for scalable and optimized manufacturing processes.

Using data analytics to properly extracting insights that are in-line to the enterprises strategic goals is crucial for the business sustainability. Developing the most fitting context as a knowledge graph that answer related businesses questions and queries at scale. Data analytics is an integral main part of smart manufacturing for monitoring the production processes and identifying the potentials for automated operations for improved manufacturing performance.

Adoption of digital twin for sustainable manufacturing and achievements of production strategic-planned goals.

To achieve the maximum return-of-investment for the adoption of Digital-Twin in manufacturing, organizations should be totally aware about the challenges that limit the widely adoption as well as opportunities that may create real-added values to their businesses at operational and strategic management. In this context, determining the most influential factors for successful adoption must be clear even at the early stages of planning towards high effective digital-transformation journey for business's sustainability. The beneficial achievements and outcome towards such successful planning and adoption of the industrial digital-twin are significant in terms of optimized processes, reduced costs and downtown of the operations, flexibility in product design and processes' adaptation to satisfy future markets demands The main purpose of this paper is to propose adoption modelling of digital-twin for optimized products and production processes.

Clone tag detection in distributed RFID systems.

Although Radio Frequency Identification (RFID) is poised to displace barcodes, security vulnerabilities pose serious challenges for global adoption of the RFID technology. Specifically, RFID tags are prone to basic cloning and counterfeiting security attacks. A successful cloning of the RFID tags in many commercial applications can lead to many serious problems such as financial losses, brand damage, safety and health of the public.

An approach for removing redundant data from RFID data streams.

Radio frequency identification (RFID) systems are emerging as the primary object identification mechanism, especially in supply chain management. However, RFID naturally generates a large amount of duplicate readings. Removing these duplicates from the RFID data stream is paramount as it does not contribute new information to the system and wastes system resources.