scholarly journals A Novel Approach for the Detection of Road Speed Bumps using Accelerometer Sensor

TEM Journal ◽  
2020 ◽  
pp. 469-476
Author(s):  
Bassam Al-Shargabi ◽  
Majid Hassan ◽  
Thamer Al-Rousan
Keyword(s):  
Surface Condition ◽  
Proof Of Concept ◽  
Android Application ◽  
Accelerometer Sensor ◽  
Optimal Method ◽  
The Road ◽  
Novel Approach ◽  
Road Speed ◽  
Moving Vehicles ◽  
Proposed Model

Smart phones and tablets have turned into an indispensable piece in our society. Accordingly, these devices are equipped with many sensors that can be exploited in many applications such as monitoring road surface condition. It becomes important to find an optimal method for detecting road speed bumps and potholes in order to monitor the road conditions and to alert other moving vehicles in order to slow their speed and avoid any damage and experience safe and comfortable driving. Moreover, data collected by smartphones about road conditions can help city authorities to repair and maintain the roads. The aim of this paper is to introduce a model for detecting road speed bumps and potholes using an Android application based on accelerometer sensor. This application uses data gathered by accelerometer sensor that was collected from various roads in order to determine the accuracy of this proposed approach. The proposed model was implemented as an Android application as a proof of concept and it was tested to check its accuracy.

scholarly journals Research on Road Adhesion Condition Identification Based on an Improved ALexNet Model

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
QiMing Wang ◽  
JinMing Xu ◽  
Tao Sun ◽  
ZhiChao Lv ◽  
GaoQiang Zong
Keyword(s):  
Machine Learning ◽  
Surface Condition ◽  
Image Features ◽  
Road Surface ◽  
Driving Safety ◽  
Error Performance ◽  
Training Time ◽  
The Road ◽  
Network Training ◽  
Proposed Model

Automotive intelligence has become a revolutionary trend in automotive technology. Complex road driving conditions directly affect driving safety and comfort. Therefore, by improving the recognition accuracy of road type or road adhesion coefficient, the ability of vehicles to perceive the surrounding environment will be enhanced. This will further contribute to vehicle intelligence. In this paper, considering that the process of manually extracting image features is complicated and that the extraction method is random for everyone, road surface condition identification method based on an improved ALexNet model, namely, the road surface recognition model (RSRM), is proposed. First, the ALexNet network model is pretrained on the ImageNet dataset offline. Second, the weights of the shallow network structure after training, including the convolutional layer, are saved and migrated to the proposed model. In addition, the fully connected layer fixed to the shallow network is replaced by 2 to 3, which improves the training accuracy and shortens the training time. Finally, the traditional machine learning and improved ALexNet model are compared, focusing on adaptability, prediction output, and error performance, among others. The results show that the accuracy of the proposed model is better than that of the traditional machine learning method by 10% and the ALexNet model by 3%, and it is 0.3 h faster than ALexNet in training speed. It is verified that RSRM effectively improves the network training speed and accuracy of road image recognition.

scholarly journals Optimization Model for the Pavement Pothole Repair Problem Considering Consumable Resources

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 364
Author(s):  
Shu-Shun Liu ◽  
Agung Budiwirawan ◽  
Muhammad Faizal Ardhiansyah Arifin ◽  
Wei Tong Chen ◽  
Ying-Hua Huang
Keyword(s):  
Heavy Rain ◽  
Return Time ◽  
Road Maintenance ◽  
Resource Assignment ◽  
Routing Problem ◽  
Pavement Maintenance ◽  
The Road ◽  
Road Pavement ◽  
Novel Approach ◽  
Proposed Model

When heavy rain strikes Taiwan, it always results in cracks in road pavement, and damages arising from potholes. Tremendously compromising road safety, road users may have fatal accidents caused by untimely repair actions. The road maintenance department needs to take the responsibilities for road sections in the form of inspections and faces the decision about how to properly allocate available resources to repair pavement damages immediately. When performing pavement repair works, we need to consider the resource consumption behavior and explore the mechanism of replenishing resources and calculating the return time. Therefore, in order to help maintenance units to deal with consumable resource issues, this study proposes a novel approach to offer the mechanism of consumable resource calculation, which is difficult to solve through the traditional vehicle routing problem (VRP) approach. This proposed model treats the pothole repair problem as a resource-constrained project scheduling problem (RCPSP), which is capable of resolving such consumable resource considerations. The proposed model was developed by adopting constraint programming (CP) techniques. Research results showed that the proposed model is capable of providing the optimal decisions of pavement pothole repair tasks and also meets practical requirements to make appropriate adjustment, and helps the maintenance unit to shorten total repair duration and optimize resource assignment decisions of pavement maintenance objectives.

A Novel Approach of Plasma Nitrocarburizing Using a Solid Carbon Active Screen – a Proof of Concept

2017 ◽  
Vol 72 (5) ◽  
pp. 254-259 ◽  
Author(s):  
I. Burlacov ◽  
S. Hamann ◽  
H.-J. Spies ◽  
A. Dalke ◽  
J. Röpcke ◽  
...  
Keyword(s):  
Solid Carbon ◽  
Proof Of Concept ◽  
Novel Approach ◽  
Plasma Nitrocarburizing ◽  
Active Screen

scholarly journals Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tinggui Chen ◽  
Shiwen Wu ◽  
Jianjun Yang ◽  
Guodong Cong ◽  
Gongfa Li
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Sudden Onset ◽  
The Road ◽  
Bee Colony ◽  
Proposed Model ◽  
Effectiveness And Efficiency ◽  
In Transit ◽  
Emergency Supply

It is common that many roads in disaster areas are damaged and obstructed after sudden-onset disasters. The phenomenon often comes with escalated traffic deterioration that raises the time and cost of emergency supply scheduling. Fortunately, repairing road network will shorten the time of in-transit distribution. In this paper, according to the characteristics of emergency supplies distribution, an emergency supply scheduling model based on multiple warehouses and stricken locations is constructed to deal with the failure of part of road networks in the early postdisaster phase. The detailed process is as follows. When part of the road networks fail, we firstly determine whether to repair the damaged road networks, and then a model of reliable emergency supply scheduling based on bi-level programming is proposed. Subsequently, an improved artificial bee colony algorithm is presented to solve the problem mentioned above. Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.

scholarly journals Use of Oxidative Stress Responses to Determine the Efficacy of Inactivation Treatments on Cryptosporidium Oocysts

2021 ◽  
Vol 9 (7) ◽  
pp. 1463
Author(s):  
Tamirat Tefera Temesgen ◽  
Kristoffer Relling Tysnes ◽  
Lucy Jane Robertson
Keyword(s):  
Oxidative Stress ◽  
Stress Responses ◽  
Target Genes ◽  
Cryptosporidium Oocyst ◽  
Drinking Water Treatment ◽  
Proof Of Concept ◽  
Environmental Matrices ◽  
Oocyst Wall ◽  
Novel Approach ◽  
Cryptosporidium Oocysts

Cryptosporidium oocysts are known for being very robust, and their prolonged survival in the environment has resulted in outbreaks of cryptosporidiosis associated with the consumption of contaminated water or food. Although inactivation methods used for drinking water treatment, such as UV irradiation, can inactivate Cryptosporidium oocysts, they are not necessarily suitable for use with other environmental matrices, such as food. In order to identify alternative ways to inactivate Cryptosporidium oocysts, improved methods for viability assessment are needed. Here we describe a proof of concept for a novel approach for determining how effective inactivation treatments are at killing pathogens, such as the parasite Cryptosporidium. RNA sequencing was used to identify potential up-regulated target genes induced by oxidative stress, and a reverse transcription quantitative PCR (RT-qPCR) protocol was developed to assess their up-regulation following exposure to different induction treatments. Accordingly, RT-qPCR protocols targeting thioredoxin and Cryptosporidium oocyst wall protein 7 (COWP7) genes were evaluated on mixtures of viable and inactivated oocysts, and on oocysts subjected to various potential inactivation treatments such as freezing and chlorination. The results from the present proof-of-concept experiments indicate that this could be a useful tool in efforts towards assessing potential technologies for inactivating Cryptosporidium in different environmental matrices. Furthermore, this approach could also be used for similar investigations with other pathogens.

W-MMP2Vec: Topic-driven network embedding model for link prediction in content-based heterogeneous information network

2021 ◽  
Vol 25 (3) ◽  
pp. 711-738
Author(s):  
Phu Pham ◽  
Phuc Do
Keyword(s):  
Link Prediction ◽  
Representation Learning ◽  
Information Network ◽  
Network Embedding ◽  
Heterogeneous Information Network ◽  
Heterogeneous Information ◽  
Learning Framework ◽  
Novel Approach ◽  
Proposed Model ◽  
Meta Path

Link prediction on heterogeneous information network (HIN) is considered as a challenge problem due to the complexity and diversity in types of nodes and links. Currently, there are remained challenges of meta-path-based link prediction in HIN. Previous works of link prediction in HIN via network embedding approach are mainly focused on exploiting features of node rather than existing relations in forms of meta-paths between nodes. In fact, predicting the existence of new links between non-linked nodes is absolutely inconvincible. Moreover, recent HIN-based embedding models also lack of thorough evaluations on the topic similarity between text-based nodes along given meta-paths. To tackle these challenges, in this paper, we proposed a novel approach of topic-driven multiple meta-path-based HIN representation learning framework, namely W-MMP2Vec. Our model leverages the quality of node representations by combining multiple meta-paths as well as calculating the topic similarity weight for each meta-path during the processes of network embedding learning in content-based HINs. To validate our approach, we apply W-TMP2Vec model in solving several link prediction tasks in both content-based and non-content-based HINs (DBLP, IMDB and BlogCatalog). The experimental outputs demonstrate the effectiveness of proposed model which outperforms recent state-of-the-art HIN representation learning models.

scholarly journals A Theoretical Model with Which to Safely Optimize the Configuration of Hydraulic Suspension of Modular Trailers in Special Road Transport

2020 ◽  
Vol 11 (1) ◽  
pp. 305
Author(s):  
Rubén Escribano-García ◽  
Marina Corral-Bobadilla ◽  
Fátima Somovilla-Gómez ◽  
Rubén Lostado-Lorza ◽  
Ash Ahmed
Keyword(s):  
Theoretical Model ◽  
Wind Turbine ◽  
Optimization Algorithm ◽  
Hydraulic Cylinder ◽  
Road Transport ◽  
Automatic Testing ◽  
Transport Systems ◽  
The Road ◽  
Proposed Model ◽  
On The Road

The dimensions and weight of machines, structures, and components that need to be transported safely by road are growing constantly. One of the safest and most widely used transport systems on the road today due to their versatility and configuration are modular trailers. These trailers have hydraulic pendulum axles that are that are attached in pairs to the rigid platform above. In turn, these modular trailers are subject to limitations on the load that each axle carries, the tipping angle, and the oil pressure of the suspension system in order to guarantee safe transport by road. Optimizing the configuration of these modular trailers accurately and safely is a complex task. Factors to be considered include the load’s characteristics, the trailer’s mechanical properties, and road route conditions including the road’s slope and camber, precipitation and direction, and force of the wind. This paper presents a theoretical model that can be used for the optimal configuration of hydraulic cylinder suspension of special transport by road using modular trailers. It considers the previously mentioned factors and guarantees the safe stability of road transport. The proposed model was validated experimentally by placing a nacelle wind turbine at different points within a modular trailer. The weight of the wind turbine was 42,500 kg and its dimensions were 5133 × 2650 × 2975 mm. Once the proposed model was validated, an optimization algorithm was employed to find the optimal center of gravity for load, number of trailers, number of axles, oil pressures, and hydraulic configuration. The optimization algorithm was based on the iterative and automatic testing of the proposed model for different positions on the trailer and different hydraulic configurations. The optimization algorithm was tested with a cylindrical tank that weighed 108,500 kg and had dimensions of 19,500 × 3200 × 2500 mm. The results showed that the proposed model and optimization algorithm could safely optimize the configuration of the hydraulic suspension of modular trailers in special road transport, increase the accuracy and reliability of the calculation of the load configuration, save time, simplify the calculation process, and be easily implemented.

Food waste treatment option selection through spherical fuzzy AHP

2021 ◽  
pp. 1-11
Author(s):  
Aysu Melis Buyuk ◽  
Gul T. Temur
Keyword(s):  
Treatment Option ◽  
Food Waste ◽  
Waste Treatment ◽  
Fuzzy Ahp ◽  
Treatment Options ◽  
Analytic Hierarchy ◽  
Food Treatment ◽  
Novel Approach ◽  
Proposed Model ◽  
Option Selection

In line with the increase in consciousness on sustainability in today’s global world, great emphasis has been attached to food waste management. Food waste is a complex issue to manage due to uncertainties on quality, quantity, location, and time of wastes, and it involves different decisions at many stages from seed to post-consumption. These ambiguities re-quire that some decisions should be handled in a linguistic and ambiguous environment. That forces researchers to benefit from fuzzy sets mostly utilized to deal with subjectivity that causes uncertainty. In this study, as a novel approach, the spherical fuzzy analytic hierarchy process (SFAHP) was used to select the best food treatment option. In the model, four main criteria (infrastructural, governmental, economic, and environmental) and their thirteen sub-criteria are considered. A real case is conducted to show how the proposed model can be used to assess four food waste treatment options (composting, anaerobic digestion, landfilling, and incineration). Also, a sensitivity analysis is generated to check whether the evaluations on the main criteria can change the results or not. The proposed model aims to create a subsidiary tool for decision makers in relevant companies and institutions.

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

FPGA and ASIC implementation of the algorithm for traffic monitoring in urban areas

2011 ◽  
Vol 59 (2) ◽  
pp. 137-140 ◽  
Author(s):  
S. Szczepański ◽  
M. Wöjcikowski ◽  
B. Pankiewicz ◽  
M. KŁosowski ◽  
R. Żaglewski
Keyword(s):  
Urban Areas ◽  
Traffic Monitoring ◽  
Detection Algorithm ◽  
Frame Rate ◽  
Integrated Sensor ◽  
The Road ◽  
Moving Vehicles ◽  
Direction Of Movement ◽  
Account Due ◽  
Selection Of

FPGA and ASIC implementation of the algorithm for traffic monitoring in urban areas This paper describes the idea and the implementation of the image detection algorithm, that can be used in integrated sensor networks for environment and traffic monitoring in urban areas. The algorithm is dedicated to the extraction of moving vehicles from real-time camera images for the evaluation of traffic parameters, such as the number of vehicles, their direction of movement and their approximate speed. The authors, apart from the careful selection of particular steps of the algorithm towards hardware implementation, also proposed novel improvements, resulting in increasing the robustness and the efficiency. A single, stationary, monochrome camera is used, simple shadow and highlight elimination is performed. The occlusions are not taken into account, due to placing the camera at a location high above the road. The algorithm is designed and implemented in pipelined hardware, therefore high frame-rate efficiency has been achieved. The algorithm has been implemented and tested in FPGA and ASIC.

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