BACKGROUND.The American Joint Committee on Cancer (AJCC) 2002 staging system (AJCC 2002) suggested that squamous cell carcinoma of the oral cavity (OSCC) with T4b is unresectable. The current retrospective results show that selected T4b patients were resectable with favorable outcomes.METHODS.From January 1996 to December 2000, 103 consecutive untreated T4 OSCC patients (reclassified by AJCC 2002) without carotid artery encasement and skull base extension were eligible for radical treatment. All received head‐and‐neck magnetic resonance imaging (MRI) and/or computed tomography (CT) scans before operation. The surgical principles were safety margins of ≥1 cm for primary tumors, modified/radical neck dissections for clinical lymph node‐positive disease, and supraomohyoid neck dissection for lymph node‐negative disease. In all, 95.1% of patients (98 of 103 patients) underwent free‐flap reconstructions. Adjuvant radiotherapy or concomitant chemoradiotherapy was administed to those with pathological T4 (AJCC 1997), cervical lymph node metastasis, or close margins (≤4 mm). Survivals were calculated according to the method of Kaplan and Meier.RESULTS.In all, 58 patients were classified as having T4a disease and 45 were classified as having T4b disease. No statistical difference was observed in the 5‐year local control, neck control, disease‐free survival, and overall survival rates between the T4a and T4b groups. In multivariate analyses, pathologic lymph node status (pN0‐1 vs. pN2) was found to be the sole independent predictor for T4b for local control (P = .012), disease‐free survival (P = .005), and overall survival (P = .008).CONCLUSIONS.Selected T4b OSCC patients were found to be resectable with outcomes that were comparable to those of T4a OSCC patients and may benefit from radical surgery, free‐flap reconstruction, and adjuvant therapy. A pathologic lymph node status of ≥2 was found to be the sole independent predictor for T4b disease in local control and survival. Cancer 2006. © 2006 American Cancer Society.

This paper introduces a novel algorithm that increases the efficiency of the current cloud-based smart-parking system and develops a network architecture based on the Internet-of-Things technology. This paper proposed a system that helps users automatically find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance and the total number of free places in each car park. This cost will be used to offer a solution of finding an available parking space upon a request by the user and a solution of suggesting a new car park if the current car park is full. The simulation results show that the algorithm helps improve the probability of successful parking and minimizes the user waiting time. We also successfully implemented the proposed system in the real world.INDEX TERMS Smart-parking system, performance metrics.

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