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The adoption and integration of e-commerce strategies into existing business models have allowed many companies to broaden their customer base and boost profits. However, the lack of a cost-efficient logistics planning model often results in the unsatisfactory performance of complex multi-echelon supply chain networks. As transportation planning and scheduling are typically managed via independent entities within the supply network, one key challenge is achieving maximum asset utilization rates considering production flow, logistics cost, and delivery time constraints. This study leverages digital twin capabilities to propose a 4PL-oriented heuristics search model for omnichannel logistics planning and scheduling. The approach aims to enhance transportation flow and resource utilization while shortening waiting times within multi-echelon networks. An industrial case study is featured to validate its cost-effectiveness.

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The biometric technologies have long been used for identification and authentication purposes; and fingerprint is one of the most widely used biometric technologies. In medicine and healthcare applications, biometric systems are used to identify patients and retrieve crucial medical records. In this paper, we propose a fingerprint singularity detection algorithm based on a very well-known pattern recognition technique. The successfully developed algorithm was tested for different fingerprint image resolutions, noise levels, and it was directly compared to the traditional technique, Poincare index which is the scalar values representing the geometrical behavior of basic patterns. The test of the proposed algorithm shows the outperformed results in both the high noise and low resolution images. Especially, the descriptors can be extracted directly from the suspect original and sample fingerprint images. The proposed method is therefore robust and can be adopted to any special descriptors rather than the pure core and delta points. With the recent advancement in data science, the successfully developed algorithm is potential for development of innovative biometric and medical applications, especially for telehealth and e-health systems.