Inverse scattering on the line for a generalized nonlinear Schroedinger equation

A one-dimensional generalized nonlinear Schroedinger equation is considered, and the corresponding inverse scattering problem is analyzed when the potential is compactly supported and depends on the wave function. The unique recovery of the potential is established from an appropriate set of scattering data.Comment: 20 page

Data-driven Methods for Identifying Travel Conditions Based on Traffic and Weather Characteristics

Accurate and reliable traffic state estimation is essential for the identification of congested areas and bottleneck locations. It enables the quantification of congestion characteristics, such as intensity, duration, reliability, and spreading which are indispensable for the deployment of appropriate traffic management plans that can efficiently ameliorate congestion problems. Similarly, it is important to categorize known congestion patterns throughout a long period of time, so that corresponding traffic simulation models can be built for the investigation of the performance of different traffic management plans. This study conducts cluster analysis to identify days with similar travel conditions and congestion patterns. To this end, travel, traffic and weather data from the Smart Mobility Living Lab of Thessaloniki, Greece is used. Representative days per cluster are determined to facilitate the development of traffic simulation models that typify average traffic conditions within each cluster. Moreover, spatio-temporal matrices are developed to illustrate time-varying traffic conditions along different routes for the representative days. Results indicate that the proposed clustering technique can produce valid classification of days in groups with common characteristics, and that spatio-temporal matrices enable the development of traffic management plans which encompass routing information for competing routes in the city of Thessaloniki

Data-driven Methods for Identifying Travel Conditions Based on Traffic and Weather Characteristics

Accurate and reliable traffic state estimation is essential for the identification of congested areas and bottleneck locations. It enables the quantification of congestion characteristics, such as intensity, duration, reliability, and spreading which are indispensable for the deployment of appropriate traffic management plans that can efficiently ameliorate congestion problems. Similarly, it is important to categorize known congestion patterns throughout a long period of time, so that corresponding traffic simulation models can be built for the investigation of the performance of different traffic management plans. This study conducts cluster analysis to identify days with similar travel conditions and congestion patterns. To this end, travel, traffic and weather data from the Smart Mobility Living Lab of Thessaloniki, Greece is used. Representative days per cluster are determined to facilitate the development of traffic simulation models that typify average traffic conditions within each cluster. Moreover, spatio-temporal matrices are developed to illustrate time-varying traffic conditions along different routes for the representative days. Results indicate that the proposed clustering technique can produce valid classification of days in groups with common characteristics, and that spatio-temporal matrices enable the development of traffic management plans which encompass routing information for competing routes in the city of Thessaloniki

Data-driven Methods for Identifying Travel Conditions Based on Traffic and Weather Characteristics

Accurate and reliable traffic state estimation is essential for the identification of congested areas and bottleneck locations. It enables the quantification of congestion characteristics, such as intensity, duration, reliability, and spreading which are indispensable for the deployment of appropriate traffic management plans that can efficiently ameliorate congestion problems. Similarly, it is important to categorize known congestion patterns throughout a long period of time, so that corresponding traffic simulation models can be built for the investigation of the performance of different traffic management plans. This study conducts cluster analysis to identify days with similar travel conditions and congestion patterns. To this end, travel, traffic and weather data from the Smart Mobility Living Lab of Thessaloniki, Greece is used. Representative days per cluster are determined to facilitate the development of traffic simulation models that typify average traffic conditions within each cluster. Moreover, spatio-temporal matrices are developed to illustrate time-varying traffic conditions along different routes for the representative days. Results indicate that the proposed clustering technique can produce valid classification of days in groups with common characteristics, and that spatio-temporal matrices enable the development of traffic management plans which encompass routing information for competing routes in the city of Thessaloniki

Evaluation of acute/late toxicity and local recurrence in T1-T2 glottic carcinoma treated with accelerated hypofractionated 3D-conformal external beam radiotherapy (3D-CRT)

Background. The aim of the study was to evaluate the efficacy, as well as the acute and late toxicity of an accelerated hypofractionated 3DCRT schedule as radical treatment in patients with organ confined glottic cancer cT1-2N0. Patients and methods. Between June of 2004 and September 2010, 47 retrospectively selected patients (29 males, 18 females) diagnosed with organ confined T1 or T2 glottic cancer, were treated with external 3DCRT in an accelerated hypofractionation schedule. The median age was 70 years. A dose of 64.4 Gy in 28 daily fractions was prescribed. The primary study endpoints were to assess the acute and late effects of radiation toxicity, according to the EORTC/RTOG scale, as well as the therapeutic impact of this schedule in terms of local recurrence. Results. The median follow up was 36 months. At the end of radiotherapy, grade I, II and III acute toxicity was observed in 34, 9 and 4 patients, respectively. Late grade I and II toxicity was observed in 25 and in 8 patients respectively. Only two local recurrences were observed, 15 and 24 months post 3DCRT respectively. Conclusions. Our radiotherapy schedule achieves a high locoregional control rate with the advantage of voice preservation. The proposed hypofractionated schedule can be recommended as a standard radiotherapy treatment, since these results are comparable with those of conventional fractionation schedules