Active group route guidance based on DODE: A novel modeling framework integrating dynamic driver behavior

2020 ◽  
Author(s):  
Tiandong Xu ◽  
Yuan Hao
Keyword(s):  
Traffic Management ◽  
Driver Behavior ◽  
Information Provision ◽  
Pilot Project ◽  
Route Guidance ◽  
Modeling Framework ◽  
Proposed Model ◽  
Route Diversion ◽  
System Sustainability ◽  
Guidance Model

This work aims to provide effective and reliable traffic guidance strategies for improving the system performance and travel reliability, wherein the drivers’ route diversion behavior is the key determinant in these strategies. This study presents a novel modeling framework that can incorporate the dynamic driver behavior into a real-time group route guidance model based on dynamic origin–destination demand estimation and prediction (DODE) for information-based active traffic management. Experiments are conducted to test the effectiveness of the proposed model on the basis of the traffic dataset of the Route Guidance Pilot Project. Experimental results show that the effect of route diversion on DODE under information provision, which can improve the accuracy of DODE, must be considered. Compared with the traditional guidance model, the proposed model considers the system objective and the actual route diversion behavior and can provide better performance and ensure system sustainability.

Determinan Kejadian Stunting Pada Balita Di Kabupaten Gianyar Bali

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Hesteria Friska Armynia Subratha ◽  
Ni Made Indra Peratiwi
Keyword(s):  
Data Collection ◽  
Service Providers ◽  
Information Provision ◽  
Pilot Project ◽  
Z Score ◽  
Enabling Factors ◽  
Analysis Process ◽  
Health Service Providers ◽  
Reinforcing Factors ◽  
Qualitative Descriptive

ABSTRAKPenurunan prevalensi stunting balita merupakan tujuan yang pertama dari enam tujuan dalam Target Nutrisi Global untuk tahun 2025. Program pemerintah dalam penanggulangan masalah gizi pada balita sudah cukup banyak dan terstruktur. Namun, pada kenyataannya kasus kejadian balita stunting masih banyak dijumpai. Pada Kabupaten Gianyar terdapat 22,2% balita stunting, dan merupakan salah satu kabupaten yang menjadi pilot project penanganan stunting di Indonesia.Penelitian ini bertujuan untuk mengetahui secara mendalam determinan kejadian stunting pada balita di Kabupaten Gianyar, Bali  ditinjau dari faktor presdiposisi, faktor pemungkin dan faktor penguat. Penelitian deskriptif kualitatif ini menggunakan metode pengumpulan data observasi dan wawancara mendalam. Pengumpulan data dilaksanakan pada Bulan Mei-Juni 2020. Subyek penelitian ini adalah 8 pengasuh balita (usia 6-60 bulan) dan balita (usia 6-60 bulan) yang memiliki z-score TB/U di bawah -2SD di Kabupaten Gianyar. Proses analisis data menggunakan analisis data tematik.Hasil penelitian menunjukkan bahwa faktor yang berhubungan dengan kejadian stunting adalah adalah faktor pendorong (pengetahuan ibu, pemberian ASI Eksklusif), faktor pemungkin (ketersediaan dana, ketersediaan pangan keluarga), faktor penguat (dukungan keluarga).Semua petugas kesehatan agar memberikan informasi yang memadai mengenai pentingnya gizi pada balita sedini mungkin. Pemberian informasi dapat diberikan melalui penyuluhan kepada remaja, ibu-ibu selama hamil, nifas dan saat menyusui sewaktu ibu kunjungan ANC, mengikuti kelas ibu hamil, datang ke pusling, dan pada waktu ibu berkunjung ke posyandu. Kata Kunci       : Determinan, Stunting, Gianyar  ABSTRACTDecreasing the children stunting prevelence is the first of the sixth 2005 Global Nutrition Target goals. There were a lot and structured government prevention program regarding to the infants nutritional problems. However, in fact,  there were still found 22,2% infants stunting problems in Gianyar Regency. It was one of regencies that become a pilot project of stunting  countermeasures in Indonesia.This study aimed to determine the Gianyar Regency inftants stunting determinants in terms of precipitating factors, enabling factors and reinforcing factors. This was qualitative descriptive research with observation and in-depth interviews applied as and the data collection methods. Data collection was carried out over May-June 2020. The subjects of this research were 8 infant’s caregivers (6-60 months old) and infants (6-60 months old) who had a TB / U z-score below -2SD in Gianyar Regency. The data analysis process applied thematic data analysis.The results found that the factors associated with stunting occurrence were predisposing factors (knowledge, exclusive breastfeeding), enabling factors (funds availability, family food availability) and reinforcing factors (family support).All health service providers should provide adequate information as early as possible about the nutrition importance for infants. Information provision could be given by counseling to adolescents, mothers during pregnancy, childbirth and while breastfeeding on ANC mothers visit, attend pregnancy classes, visitting clinic and when mothers visit the Integrated Healthcare Center. Keywords         : Determinants, Stunting, Gianyar

scholarly journals Adaptive Real-Time Routing Protocol for (m,k)-Firm in Industrial Wireless Multimedia Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1633 ◽  
Author(s):  
Beom-Su Kim ◽  
Sangdae Kim ◽  
Kyong Hoon Kim ◽  
Tae-Eung Sung ◽  
Babar Shah ◽  
...  
Keyword(s):  
Real Time ◽  
Routing Protocol ◽  
Traffic Management ◽  
Research Area ◽  
Multimedia Data ◽  
Wireless Multimedia ◽  
Multimedia Sensor Networks ◽  
Proposed Model ◽  
Event Information ◽  
Firm Model

Many applications are able to obtain enriched information by employing a wireless multimedia sensor network (WMSN) in industrial environments, which consists of nodes that are capable of processing multimedia data. However, as many aspects of WMSNs still need to be refined, this remains a potential research area. An efficient application needs the ability to capture and store the latest information about an object or event, which requires real-time multimedia data to be delivered to the sink timely. Motivated to achieve this goal, we developed a new adaptive QoS routing protocol based on the (m,k)-firm model. The proposed model processes captured information by employing a multimedia stream in the (m,k)-firm format. In addition, the model includes a new adaptive real-time protocol and traffic handling scheme to transmit event information by selecting the next hop according to the flow status as well as the requirement of the (m,k)-firm model. Different from the previous approach, two level adjustment in routing protocol and traffic management are able to increase the number of successful packets within the deadline as well as path setup schemes along the previous route is able to reduce the packet loss until a new path is established. Our simulation results demonstrate that the proposed schemes are able to improve the stream dynamic success ratio and network lifetime compared to previous work by meeting the requirement of the (m,k)-firm model regardless of the amount of traffic.

Hierarchical Concept-Driven Language Model

2021 ◽  
Vol 15 (6) ◽  
pp. 1-22
Author(s):  
Yashen Wang ◽  
Huanhuan Zhang ◽  
Zhirun Liu ◽  
Qiang Zhou
Keyword(s):  
Language Model ◽  
Generation Process ◽  
Data Generation ◽  
Modeling Framework ◽  
Long Distance ◽  
Short Text ◽  
Proposed Model ◽  
Scalable Inference ◽  
End To End ◽  
Hidden Layer

For guiding natural language generation, many semantic-driven methods have been proposed. While clearly improving the performance of the end-to-end training task, these existing semantic-driven methods still have clear limitations: for example, (i) they only utilize shallow semantic signals (e.g., from topic models) with only a single stochastic hidden layer in their data generation process, which suffer easily from noise (especially adapted for short-text etc.) and lack of interpretation; (ii) they ignore the sentence order and document context, as they treat each document as a bag of sentences, and fail to capture the long-distance dependencies and global semantic meaning of a document. To overcome these problems, we propose a novel semantic-driven language modeling framework, which is a method to learn a Hierarchical Language Model and a Recurrent Conceptualization-enhanced Gamma Belief Network, simultaneously. For scalable inference, we develop the auto-encoding Variational Recurrent Inference, allowing efficient end-to-end training and simultaneously capturing global semantics from a text corpus. Especially, this article introduces concept information derived from high-quality lexical knowledge graph Probase, which leverages strong interpretability and anti-nose capability for the proposed model. Moreover, the proposed model captures not only intra-sentence word dependencies, but also temporal transitions between sentences and inter-sentence concept dependence. Experiments conducted on several NLP tasks validate the superiority of the proposed approach, which could effectively infer meaningful hierarchical concept structure of document and hierarchical multi-scale structures of sequences, even compared with latest state-of-the-art Transformer-based models.

scholarly journals A support vector machine with the tabu search algorithm for freeway incident detection

2014 ◽  
Vol 24 (2) ◽  
pp. 397-404 ◽  
Author(s):  
Baozhen Yao ◽  
Ping Hu ◽  
Mingheng Zhang ◽  
Maoqing Jin
Keyword(s):  
Support Vector Machine ◽  
Tabu Search ◽  
Traffic Management ◽  
Search Algorithm ◽  
Detection System ◽  
Support Vector ◽  
Incident Detection ◽  
Tabu Search Algorithm ◽  
Proposed Model ◽  
Parameter Values

Abstract Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems (ATMISs). An automated incident detection system can effectively provide information on an incident, which can help initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident detection.

Comparison of Three Traffic Management Plans Showing Shadow and Police Vehicle Effects on Driver Behavior at Highway Single Lane Closures

2020 ◽  
Vol 2674 (9) ◽  
pp. 15-25
Author(s):  
Ross Blackman ◽  
Matthew Legge ◽  
Ashim Kumar Debnath
Keyword(s):  
Traffic Management ◽  
Injury Risk ◽  
Driver Behavior ◽  
Night Time ◽  
Buffer Area ◽  
Driver Response ◽  
Management Plans ◽  
Efficiency And Effectiveness ◽  
Positive Effect ◽  
Lane Closures

Lane closures on multi-lane roads require drivers to transition safely to an open lane before passing the worksite. To reduce worker and driver injury risk, truck-mounted attenuators (TMAs) are often used to prevent vehicle work zone intrusions and reduce the severity of collisions. To maximize the efficiency and effectiveness of TMA use, it is necessary to determine how and when they should be deployed as well as the best supporting measures. The current research focuses on the effects of different traffic management plans (TMPs) on driver behavior. Three TMPs at night time highway work zones were examined: ( 1 ) two tail vehicles in the advance warning area, ( 2 ) three tail vehicles in the advance warning area, and ( 3 ) addition of a marked police car with flashing lights in the buffer area downstream of the TMA. Driver response to the different TMPs was assessed by measuring vehicle speeds at three points in the traffic management area and observing lane change and merging behaviors on the approach to the TMA. Analysis showed a positive effect of police presence in the buffer area on driver behavior: TMP3 produced a reduction of 8.4%–12.9% in proportions of vehicles exceeding the speed limit by at least 5 km/h when passing the TMA. TMP3 also appeared to produce a positive effect on merging behavior compared with the other layouts. Use of a third tail vehicle in the advance warning area was not found to produce any additional safety benefit and may have a detrimental effect.

scholarly journals REUTIVAR: Model for Precision Fertigation Scheduling for Olive Orchards Using Reclaimed Water

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2632 ◽  
Author(s):  
Carmen Alcaide Zaragoza ◽  
Irene Fernández García ◽  
Rafael González Perea ◽  
Emilio Camacho Poyato ◽  
Juan Antonio Rodríguez Díaz
Keyword(s):  
Reclaimed Water ◽  
Nutrient Status ◽  
Environmental Benefits ◽  
Treated Wastewater ◽  
Economic Activities ◽  
Olive Orchard ◽  
Weather Information ◽  
Proposed Model ◽  
Irrigation Time ◽  
System Sustainability

Olive orchard is the most representative and iconic crop in Andalusia (Southern Spain). It is also considered one of the major economic activities of this region. However, due to its extensive growing area, olive orchard is also the most water-demanding crop in the Guadalquivir River Basin. In addition, its fertilization is commonly imprecise, which causes over-fertilization, especially nitrogen. This leads to pollution problems in both soil and water, threating the environment and the system sustainability. This concern is further exacerbated by the use of reclaimed water to irrigate since water is already a nutrient carrier. In this work, a model which determines the real-time irrigation and fertilization scheduling for olive orchard, applying treated wastewater, has been developed. The precision fertigation model considers weather information, both historical and forecast data, soil characteristics, hydraulic characteristics of the system, water allocation, tree nutrient status, and irrigation water quality. As a result, daily information about irrigation time and fertilizer quantity, considering the most susceptible crop stage, is provided. The proposed model showed that by using treated wastewater, additional fertilization was not required, leading to significant environmental benefits but also benefits in the total farm financial costs.

scholarly journals Application of the AHP-BWM Model for Evaluating Driver Behavior Factors Related to Road Safety: A Case Study for Budapest

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 243 ◽  
Author(s):  
Sarbast Moslem ◽  
Danish Farooq ◽  
Omid Ghorbanzadeh ◽  
Thomas Blaschke
Keyword(s):  
Decision Making ◽  
Road Safety ◽  
Driver Behavior ◽  
Pairwise Comparison ◽  
Scientific Data ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Proposed Model ◽  
Decision Making Problem ◽  
Complex Decision Making

The use of driver behavior has been considered a complex way to solve road safety complications. Car drivers are usually involved in various risky driving factors which lead to accidents where people are fatally or seriously injured. The present study aims to dissect and rank the significant driver behavior factors related to road safety by applying an integrated multi-criteria decision-making (MCDM) model, which is structured as a hierarchy with at least one 5 × 5 (or bigger) pairwise comparison matrix (PCM). A real-world, complex decision-making problem was selected to evaluate the possible application of the proposed model (driver behavior preferences related to road safety problems). The application of the analytic hierarchy process (AHP) alone, by precluding layman participants, might cause a loss of reliable information in the case of the decision-making systems with big PCMs. Evading this tricky issue, we used the Best Worst Method (BWM) to make the layman’s evaluator task easier and timesaving. Therefore, the AHP-BWM model was found to be a suitable integration to evaluate risky driver behavior factors within a designed three-level hierarchical structure. The model results found the most significant driver behavior factors that influence road safety for each level, based on evaluator responses on the driver behavior questionnaire (DBQ). Moreover, the output vector of weights in the integrated model is more consistent, with results for 5 × 5 PCMs or bigger. The proposed AHP-BWM model can be used for PCMs with scientific data organized by traditional means.

scholarly journals Analytical Modeling for a Video-Based Vehicle Speed Measurement Framework

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 160 ◽  
Author(s):  
Mattias Dahl ◽  
Saleh Javadi
Keyword(s):  
Analytical Model ◽  
Traffic Management ◽  
Sampling Rate ◽  
Video Camera ◽  
Frame Rate ◽  
Vehicle Speed ◽  
Temporal Sampling ◽  
Measurement Framework ◽  
Speed Measurement ◽  
Proposed Model

Traffic analyses, particularly speed measurements, are highly valuable in terms of road safety and traffic management. In this paper, an analytical model is presented to measure the speed of a moving vehicle using an off-the-shelf video camera. The method utilizes the temporal sampling rate of the camera and several intrusion lines in order to estimate the probability density function (PDF) of a vehicle’s speed. The proposed model provides not only an accurate estimate of the speed, but also the possibility of being able to study the performance boundaries with respect to the camera frame rate as well as the placement and number of intrusion lines in advance. This analytical model is verified by comparing its PDF outputs with the results obtained via a simulation of the corresponding movements. In addition, as a proof-of-concept, the proposed model is implemented for a video-based vehicle speed measurement system. The experimental results demonstrate the model’s capability in terms of taking accurate measurements of the speed via a consideration of the temporal sampling rate and lowering the deviation by utilizing more intrusion lines. The analytical model is highly versatile and can be used as the core of various video-based speed measurement systems in transportation and surveillance applications.

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