Traffic Flow Management Using Aggregate Flow Models and the Development of Disaggregation Methods

A linear time-varying aggregate traffic flow model can be used to develop Traffic Flow Management (tfm) strategies based on optimization algorithms. However, there are no methods available in the literature to translate these aggregate solutions into actions involving individual aircraft. This paper describes and implements a computationally efficient disaggregation algorithm, which converts an aggregate (flow-based) solution to a flight-specific control action. Numerical results generated by the optimization method and the disaggregation algorithm are presented and illustrated by applying them to generate TFM schedules for a typical day in the U.S. National Airspace System. The results show that the disaggregation algorithm generates control actions for individual flights while keeping the air traffic behavior very close to the optimal solution

Ancillary Service Capacity Optimization for Both Electric Power Suppliers and Independent System Operator

Ancillary Services (AS) in electric power industry are critical to support the transmission of energy from generators to load demands while maintaining reliable operation of transmission systems in accordance with good utility practice. The ancillary services are procured by the independent system operator (ISO) through a process called the market clearing process which can be modeled by the partial equilibrium from the ends of ISO. There are two capacity optimization problems for both Market participants (MP) and Independent System Operator (ISO). For a market participant, the firm needs to determine the capacity allocation plan for various AS to pursue operating revenue under various uncertainties which can never be accurately estimated. We thereby employ a heuristic named “resource reservation” to suggest two types of bids, the regular and the must-win for a market participant to pursue higher expected revenue and satisfactory performance in terms of revenue under the worst case scenario. Meanwhile, the ISO, needs to determine the total amount of capacity required to guarantee the overall reliability of the transmission system. Our numerical experiment is based on our industrial partner’s operational data and the simulation result suggests that our proposed methods would greatly outperform the deterministic methods in terms of the profitability for a market participant and the ISO’s entire system’s reliability

Heuristics for Synthesizing Robust Networks with a Diameter Constraint

Robustness of a network in the presence of node or link failures plays an important role in the design of the network. A key factor that quantifies this robustness is the algebraic connectivity of the network. In this paper, the authors address the problem of finding a network that maximizes the algebraic connectivity of the network while ensuring that the length of the shortest path joining any two nodes in the network is within a given bound. This paper presents k-opt and tabu search heuristics for finding feasible solutions for this network synthesis problem. Computational results are also presented to corroborate the performance of the proposed algorithms

An Approximate Dynamic Programming Approach to Vehicle Platooning Coordination in Networks

Platooning connected and autonomous vehicles (CAVs) provide significant benefits in terms of traffic efficiency and fuel economy. However, most existing platooning systems assume the availability of pre-determined plans, which is not feasible in real-time scenarios. In this paper, we address this issue in time-dependent networks by formulating a Markov decision process at each junction, aiming to minimize travel time and fuel consumption. Initially, we analyze coordinated platooning without routing to explore the cooperation among controllers on an identical path. We propose two novel approaches based on approximate dynamic programming, offering suboptimal control in the context of a stochastic finite horizon problem. The results demonstrate the superiority of the approximation in the policy space. Furthermore, we investigate platooning in a network setting, where speed profiles and routes are determined simultaneously. To simplify the problem, we decouple the action space by prioritizing routing decisions based on travel time estimation. We subsequently employ the aforementioned policy approximation to determine speed profiles, considering essential parameters such as travel times. Our simulation results in SUMO indicate that our method yields better performance than conventional approaches, leading to potential travel cost savings of up to 40%. Additionally, we evaluate the resilience of our approach in dynamically changing networks, affirming its ability to maintain efficient platooning operations

A Concept for Flexible Operations and Optimized Traffic into Metroplex Regions

A "Flexible Flight Operations" concept for airport metroplexes was studied. A flexible flight is one whose destination airport is not assigned until a threshold is reached near the arrival area at which time the runway which reduces overall delay is assigned. The concept seeks to increase throughput by exploiting flexibility. The quantification of best-case benefits from the concept was pursued to establish whether concept research is warranted. Findings indicate that indeed the concept has potential for significant reductions in delay (and cost due to delay) in the N90 (NY/NJ) and SCT (Southern California) metroplexes. Delay reductions of nearly 26% are possible in N90 when 30% of the commercial airline flights are flexible (smartly selected by their low probability of connecting passengers); nearly 40% delay reduction is found when 50% of the flights are flexible. In the SCT metroplex, delay reductions estimates are greater. Greater reductions result at SCT since it is less constrained currently than N90, providing "more room" to take advantage of flexibility. Using the flexible operations concept for on-demand/air taxi and General Aviation flights were found to be beneficial at NY/NJ, indicating the flexible operations concepts may be useful to wide variety of users.

CDSD: Chinese Dysarthria Speech Database

We present the Chinese Dysarthria Speech Database (CDSD) as a valuable resource for dysarthria research. This database comprises speech data from 24 participants with dysarthria. Among these participants, one recorded an additional 10 hours of speech data, while each recorded one hour, resulting in 34 hours of speech material. To accommodate participants with varying cognitive levels, our text pool primarily consists of content from the AISHELL-1 dataset and speeches by primary and secondary school students. When participants read these texts, they must use a mobile device or the ZOOM F8n multi-track field recorder to record their speeches. In this paper, we elucidate the data collection and annotation processes and present an approach for establishing a baseline for dysarthric speech recognition. Furthermore, we conducted a speaker-dependent dysarthric speech recognition experiment using an additional 10 hours of speech data from one of our participants. Our research findings indicate that, through extensive data-driven model training, fine-tuning limited quantities of specific individual data yields commendable results in speaker-dependent dysarthric speech recognition. However, we observe significant variations in recognition results among different dysarthric speakers. These insights provide valuable reference points for speaker-dependent dysarthric speech recognition.Comment: 9 pages, 3 figure

SATB2 shows different profiles between appendiceal adenocarcinomas ex goblet cell carcinoids and appendiceal/colorectal conventional adenocarcinomas: An immunohistochemical study with comparison to CDX2

Background: Special AT-rich sequence-binding protein 2 (SATB2) is a novel marker for colorectal adenocarcinomas but little is known about its expression in appendiceal adenocarcinomas. We aim to investigate SATB2 in these tumors and colorectal adenocarcinomas with comparison to CDX2. Methods: Immunohistochemical stains for SATB2 and CDX2 were performed in 49 appendiceal adenocarcinomas (23 conventional, 26 adenocarcinoma ex goblet cell carcinoids (AdexGCCs)) and 57 colorectal adenocarcinomas. Their expression was correlated with tumor differentiation and growth patterns. Results: SATB2 staining was positive in 26/26 (100%) appendiceal AdexGCCs and 15/23 (65%) appendiceal conventional adenocarcinomas (P = 0.001). Their mean percentage of SATB2-positive cells was 93% and 34%, respectively (P \u3c 0.0001). CDX2 staining was seen in 26/26 (100%) AdexGCCs and 22/23 (96%) appendiceal conventional adenocarcinomas (P = 0.4694). SATB2 and CDX2 showed similar staining in AdexGCCs but CDX2 labeled more tumor cells than SATB2 in conventional adenocarcinomas (mean 84% vs. 34%, P \u3c 0.0001). SATB2 and CDX2 staining was seen in 82% (47/57) and 96% (55/57) colorectal adenocarcinomas, respectively (P = 0.01). The mean percentage of cells positive for SATB2 and CDX2 was 48% and 91%, respectively (P \u3c 0.00001). Decreased SATB2 immunoreactivity was associated with non-glandular differentiation particularly signet ring cells in colorectal (P = 0.001) and appendiceal conventional adenocarcinomas (P = 0.04) but not in appendiceal AdexGCCs. Conclusions: SATB2 is a highly sensitive marker for appendiceal AdexGCCs with similar sensitivity as CDX2. In colorectal and appendiceal conventional adenocarcinomas, SATB2 is not as sensitive as CDX2 and its immunoreactivity is dependent on tumor differentiation