Data-Driven Method for the Prediction of Estimated Time of Arrival

Predicting the estimated time of arrival (ETA) plays an essential role in decision support (conflict detection, arrival sequencing, or trajectory optimization) for air traffic controllers. In this paper, a new multiple stages strategy for ETA prediction is proposed based on radar trajectories, including arrival pattern identification, arrival pattern classification, and flight time estimation. First, an intention-oriented trajectory clustering method is developed based on a new trajectory representation technique. Such a proposed trajectory clustering method can group trajectories into different arrival patterns in an efficient way. Second, an arrival pattern classification model is constructed based on random forest and XGBoost algorithms. Then, a flight time regression model is trained for each arrival pattern by using the XGBoost algorithm. Information on current states, historical states, and traffic situations is considered to build the feature set during these processes. Finally, the arrival operation toward Guangzhou International Airport is chosen as a case study. The results illustrate that the proposed method and feature engineering approach could improve the performance of ETA prediction. The proposed multiple stages strategy is superior to the single-model-based ETA prediction.

A study on Non-Markovian Bulk Arrival And Bulk Service with Multiple Vacations

A queue or a waiting line, involves arriving customers who is waiting to be served at one or more service stations, by one or more servers. The term ‘customer’ may refer, for example, to a machine arriving at an inspection center or to a person arriving at a booking counter in a railway station. Customers are selected for service by certain rule known as queue discipline. The basic characteristics of a queuing system follows systematically (1) The arrival pattern of customer (2) The service pattern of servers (3) The queue discipline (4) The system capacity (5) Number of servers. If more than one arrival enters the system simultaneously, the input is said to Bulk Arrival. Customer may be served individually or in batches, in case of batch service the service system is called bulk service system.

Process arrival pattern aware algorithms for acceleration of scatter and gather operations

Imbalanced process arrival patterns (PAPs) are ubiquitous in many parallel and distributed systems, especially in HPC ones. The collective operations, e.g. in MPI, are designed for equal process arrival times, and are not optimized for deviations in their appearance. We propose eight new PAP-aware algorithms for the scatter and gather operations. They are binomial or linear tree adaptations introducing additional process ordering and (in some cases) additional activities in a special background thread. The solution was implemented using one of the most popular open source MPI compliant library (OpenMPI), and evaluated in a typical HPC environment using a specially developed benchmark as well as a real application: FFT. The experimental results show a significant advantage of the proposed approach over the default OpenMPI implementation, showing good scalability and high performance with the FFT acceleration for the communication run time: 16.7% and for the total application execution time: 3.3%.

Study on the Performance of Adjustable Platform Screen Door in Subway Stations

In the last decades, the construction of subway systems has been in rapid progress in metropolis. Former studies have pointed out that substantial amount of energy is consumed by subway stations. Thus, the adjustable platform screen door (APSD) system is widely adopted, which is characterized by the energy-saving in both the cooling season and the transitional season. However, the installation of APSD system might result in thermal discomfort for passengers, which lacks investigation. This study aims to study the performance on the thermal comfort of subway station with APSD system. In this process, Computational Fluid Dynamics (CFD) Simulation was conducted using PHOENICS to obtain the velocity and temperature distribution under 3 kinds of train arrival patterns. Furthermore, Relative Warmth Index (RWI) was used to assess thermal comfort. The results show that the velocities of the platform and station hall are below 2.5m/s and 3.7m/s respectively, which is closely related to the train arrival pattern. With regard to the platform occupied zone, the RWI is between 0.04 to 0.19, which is almost within the thermal comfort zone according to the ASHRAE comfort classification. Nevertheless, for the occupied zone of the hall, the RWI is between 0.15 to 0.52, indicating relatively warm.

Capacity and patient flow planning in post-term pregnancy outpatient clinics: a computer simulation modelling study

Background The demand for a large Norwegian hospital’s post-term pregnancy outpatient clinic has increased substantially over the last 10 years due to changes in the hospital’s catchment area and to clinical guidelines. Planning the clinic is further complicated due to the high did not attend rates as a result of women giving birth. The aim of this study is to determine the maximum number of women specified clinic configurations, combination of specified clinic resources, can feasibly serve within clinic opening times. Methods A hybrid agent based discrete event simulation model of the clinic was used to evaluate alternative configurations to gain insight into clinic planning and to support decision making. Clinic configurations consisted of six factors: X0: Arrivals. X1: Arrival pattern. X2: Order of midwife and doctor consultations. X3: Number of midwives. X4: Number of doctors. X5: Number of cardiotocography (CTGs) machines. A full factorial experimental design of the six factors generated 608 configurations.Results Each configuration was evaluated using the following measures: Y1: Arrivals. Y2: Time last woman checks out. Y3: Women’s length of stay (LoS). Y4: Clinic overrun time. Y5: Midwife waiting time (WT). Y6: Doctor WT. Y7: CTG connection WT. Optimisation was used to maximise X0 with respect to the 32 combinations of X1-X5. Configuration 0a, the base case Y1 = 7 women and Y3 = 102.97 [0.21] mins. Changing the arrival pattern (X1) and the order of the midwife and doctor consultations (X2) configuration 0d, where X3, X4, X5 = 0a, Y1 = 8 woman and Y3 86.06 [0.10] mins.Conclusions The simulation model identified the availability of CTG machines as a bottleneck in the clinic, indicated by the WT for CTG connection effect on LoS. One additional CTG machine improved clinic performance to the same degree as an extra midwife and an extra doctor. The simulation model demonstrated significant reductions to LoS can be achieved without additional resources, by changing the clinic pathway and scheduling of appointments. A more general finding is that a simulation model can be used to identify bottlenecks, and efficient ways of restructuring an outpatient clinic.

Pola Kedatangan Serangga pada Jasad Hewan Sebagai Indikator dalam Kegiatan Forensik (INSECT ARRIVAL PATTERN ON CARRION AS AN INDICATOR OF FORENSIC ACTIVITIES)

Decomposition stage of carrion will attract various species of insects to come. Some species of insect will attract on carrion in the early stage of decomposition, but some of them in the late stage of death. The purpose of this research were to observe and analyze the distinctive features of insect succession on carrion that could predict the time of death. Two carrions were placed in indoor and outdoor. Insect collection and observation was done three times a day i.e, morning, afternoon and evening. Adult flying insects were collected by sweeping net, whereareas immature insect with manual. The result showed that decomposition of the carrion indoor were faster than the corrion outdoor. In outdoor there were found orders of Diptera (i.e Muscidae, Calliphoridae, Sarcophagidae,Tachinidae), Coleoptera (Chrysomelidae, Staphylinidae, Scarabeidae, Silphidae), Hymenoptera (Formicidae), Hemiptera, Blataria and Orthoptera (Grillidae). However, in indoors there were found the order of Diptera (Muscidae, Calliphoridae, Sarcophagidae, Tachinidae), Coleoptera (Chrysomelidae, Staphylinidae, Scarabeidae, Silphidae), Hymenoptera (Formicidae), Hemiptera, Aranea, and Lepidoptera. Decomposition stage of carrion indoor faster than outdoor. In the early stage to the decay stage, insects that came on carrion outdoor and indoor were Diptera (Calliphoridae, Tachinidae, Muscidae, and Sarcophagidae. On the post decay and skeletonization stage the insect that come were Coleoptera (Staphylinidae, Chrysomelidae, Scarabeidae, and Silphidae ). Hymenoptera (Formicidae) came from early stage to skeletal stage.