Search results for: vehicle location

Authors: Akhmad F. K. Khitam, Yi Tai, Hsin-Yun Lee

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In the modern research of construction management, the goals of scheduling are not only to finish the project within the limited duration, but also to improve the impact of people and environment. Especially for the impact to the pedestrian and vehicles, the considerable social cost should be estimated in the total performance of a construction project. However, the site environment has many differences between projects. These interactions affect the requirement and goal of scheduling. It is difficult for schedule planners to quantify these interactions. Therefore, this study use 3D dynamic simulation technology to plan the schedule of the construction engineering projects that affect the current space users (i.e., the pedestrians and vehicles). The proposed model can help the project manager find out the optimal schedule to minimize the inconvenience brought to the space users. Besides, a roadwork project and a building renovation project were analyzed for the practical situation of engineering and operations. Then this study integrates the proper optimization algorithms and computer technology to establish a decision support model. The proposed model can generate a near-optimal schedule solution for project planners.

Keywords: scheduling, simulation, optimization, pedestrian and vehicle behavior

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Authors: Imran Badshah

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This paper study the impact of Un-signalized pedestrian on traffic flow at Stationary Bottleneck. The Highway Capacity Manual (HCM) analyze the methodology of level of service for Urban street segment but it does not include the impact of un-signalized pedestrian crossing at stationary bottleneck. The un-signalized pedestrian crossing in urban road segment causes conflict between vehicles and pedestrians. As a result, the average time taken by vehicle to travel along a road segment increased. The speed of vehicle and the level of service decreases as the running time of a segment increased. To analyze the delay, we need to determine the pedestrian speed while crossing the road at a stationary bottleneck. The objective of this research is to determine the speed of pedestrian and its impact on traffic flow at stationary bottleneck. In addition, the result of this study should be incorporated in the Urban Street Analysis Chapter of HCM.

Keywords: stationary bottleneck, traffic flow, pedestrian speed, HCM

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Authors: Ssekamanya, Mastura Badzis, Khamsiah Ismail, Dayang Shuzaidah Bt Abduludin

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With rising incidents of school violence worldwide, educators and researchers are trying to understand and find ways to enhance the safety of children at school. The purpose of this study was to investigate the extent to which the demographic variables of gender, age, length of service, position, academic qualification, and school location predicted teachers’ awareness about school safety practices in Malaysian primary schools. A stratified random sample of 380 teachers was selected in the central Malaysian states of Kuala Lumpur and Selangor. Multiple regression analysis revealed that none of the factors was a good predictor of awareness about school safety training, delivery methods of school safety information, and available school safety programs. Awareness about school safety activities was significantly predicted by school location (whether the school was located in a rural or urban area). While these results may reflect a general lack of awareness about school safety among primary school teachers in the selected locations, a national study needs to be conducted for the whole country.

Keywords: school safety awareness, predictors of school safety, multiple regression analysis, malaysian primary schools

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Authors: Seo Soo-Yeon, Kim Sang-Ku, Noh Sang-Hyun, Lee Ji-Eun, Kim Seol-Ki, Lim Jong-Wook

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This paper presents a test result to find the structural capacity of Hollow-Precast Concrete (HPC) column with Head-Splice Sleeve (HSS) for the connection of bars under horizontal cyclic load. Two Half-scaled HPC column specimens were made with the consideration of construction process in site. The difference between the HPC specimens is the location of HSS for bar connection. The location of the first one is on the bottom slab or foundation while the other is above the bottom slab or foundation. Reinforced concrete (RC) column was also made for the comparison. In order to evaluate the hysteretic behavior of the specimens, horizontal cyclic load was applied to the top of specimen under constant axial load. From the test, it is confirmed that the HPC columns with HSS have enough structural capacity that can be emulated to RC column. This means that the HPC column with HSS can be used in the moment resisting frame system.

Keywords: structural capacity, hollow-precast concrete column, head-splice sleeve, horizontal cyclic load

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, FFT, principal component analysis, eigenvector, octave-notes, DSP

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Authors: Rana Gill, Chandandeep Kaur

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Segmentation of images can be implemented using different fundamental algorithms like edge detection (discontinuity based segmentation), region growing (similarity based segmentation), iterative thresholding method. A comprehensive literature review relevant to the study gives description of different techniques for vehicle number plate detection and edge detection techniques widely used on different types of images. This research work is based on edge detection techniques and calculating threshold on the basis of five edge operators. Five operators used are Prewitt, Roberts, Sobel, LoG and Canny. Segmentation of characters present in different type of images like vehicle number plate, name plate of house and characters on different sign boards are selected as a case study in this work. The proposed methodology has seven stages. The proposed system has been implemented using MATLAB R2010a. Comparison of all the five operators has been done on the basis of their performance. From the results it is found that Canny operators produce best results among the used operators and performance of different edge operators in decreasing order is: Canny>Log>Sobel>Prewitt>Roberts.

Keywords: segmentation, edge detection, text, extracting characters

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Authors: Chun Pao Kuo, Chi Tong Lin

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The study explored atomization characteristics of tire pyrolysis fuel and its impacts on using three types of fuel: diesel oil mixed with 10% of tire pyrolysis fuel (called T10), diesel oil mixed with 20% tire pyrolysis (called T20), and consumer-grade diesel oil (D100). The investigators used the fuel for simulation and tests at various fuel injection timing, engine speed, and fuel injection speed to inspect impacts from fuel type on oil droplet atomization speed and output power. Actual vehicle tests were conducted using a 5-ton sedan (Hino) with 3660 cc displacement and a front-end inline four-cylinder diesel engine, and this type of vehicle is easily available from the market. A dynamometer was used to set up three engine speeds for the dynamometer testing at different injection timing and pressure. Next, an exhaust analyzer was used to measure exhaust pollution at different conditions to explore the effect of fuel types and injection speeds on output power in order to establish the best operation conditions for tire pyrolysis fuel.

Keywords: diesel engine, exhaust pollution, fuel injection timing, tire pyrolysis oil

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Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

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This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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Authors: Giuseppe Spampinato, Salvatore Curti, Ivana Guarneri, Arcangelo Bruna

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This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.

Keywords: clustering, cross traffic alert, optical flow, real time, vanishing point

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Authors: Pragya Bhawsar, Utpal Chattopadhyay

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Small and Medium Enterprises play crucial role in contributing to economic objectives of an emerging nation. To support SMEs, the idea of creation of clusters has been prevalent since past two decades. In this paper, an attempt has been done to explore the impact of being in the cluster on the competitiveness of SMEs. To meet the objective, Nasik Cluster (India) has been selected. The information was collected by means of two focus group discussions and survey of thirty SMEs. The finding generates interest revealing the fact that under the concept ‘Cluster’ a lot of ambiguity flourish. Besides the problems and opportunities of the firms in the cluster the results bring to notice that the benefits of clusterization can only reach to SMEs when the whole location can be considered/understood as a cluster, rather than many subsets (various forms of clusters) prevailing under it. Fostering such an understanding calls for harmony among the various stakeholders of the clusters. The dynamics of interaction among government, local industry associations, relevant institutions, large firms and finally SMEs which makes the most of the location based cluster, are significant in shaping the host cluster’s competitiveness and vice versa.

Keywords: SMEs, industry clusters, common facility centres, co-creation, policy

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Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

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Authors: Mohadese Sukhtesaraii, Mohammad Esmail Esmaili Jelodar, Kosar Sookhtesaraii

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Throughout history, humans have always wanted to have a shelter to live in, and this need and desire became the beginning of building and architecture. It was necessary to build a shelter and a building, dealing with the surrounding nature. The design and construction of architectural spaces are always influenced by nature, climate, and geographical location, and It is believed clearly see this influence even in the use of materials used in the construction of architectural buildings. The historical port of Siraf is located on the northern coast of the Persian Gulf in Bushehr province and 38 km from Kangan port. Geographically and climatically, Siraf is considered one of the hot and humid areas. The Zagros mountains, which continue from the Iranian plateau to the sea, end at Bandar Siraf; As a result, it creates a strip one kilometer wide by the sea. The location of Siraf in the restrictive conditions of the mountains and the sea has made it impossible to expand the city. The main goal of the current research is to investigate the climate of Siraf and the influence of the region's climate on the architecture and design of residential buildings in Siraf, known as noble houses, in the early Islamic centuries. In this research, it is looking for an answer to the question of how the climatic and geographical conditions have affected the architecture of Siraf buildings. The theoretical framework of this research can be expressed based on the influence of climate on the historical architecture of Bandar Seraf and the spatial analysis of archeology. Also, the research method will be analytical-descriptive and using field and library studies. The authors of the article believe that the architectural spaces of the early Islamic centuries of Siraf city were affected by the climate and geographical location, and the architects started building buildings by considering factors such as the sun's radiation, wind direction, and the position of the mountains and the sea. To use the regional and environmental potential for buildings.

Keywords: hose N, noble hose, islamic era, siraf, climate

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Authors: Isyaku Labaran Fagge

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This study investigated on appraisal of civil servants level of participation in recreational activities in North Western States of Nigeria. To achieve this purpose, a descriptive survey was employed for the designed questionnaire which were administered on 300 respondents, who served as subject for this study, in North Western States of Nigeria. Descriptive statistics of simple frequency count, percentage and Chi square (x2) statistical techniques at 0.05 alpha level were used for all statistical tests of significance. The findings of the study revealed that senior civil servants by (gender, status and location) do participate in recreational activities. On the knowledgeable personnels, all the recreational centres (by gender, status and location) had no knowledgeable personnels to handle the centres across North Western States. Many recreational centers should be create. Government should train and employ more knowledgeable personnel to handle the centres. Civil servants in urban areas do participate more than the civil servants in rural areas.

Keywords: recreation, civil servants, participation, recreational activities

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Authors: Nermine A. Harraz, Aliaa Abouali

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The retail stores put up for sale multiple items while the spaces in the backroom and display areas constitute a scarce resource. Availability, volume, and location of the product displayed in the showroom influence the customer’s demand. Managing these operations individually will result in sub-optimal overall retail store’s profit; therefore, a non-linear integer programming model (NLIP) is developed to determine the inventory replenishment and shelf space allocation decisions that together maximize the retailer’s profit under shelf space and backroom storage constraints taking into consideration that the demand rate is positively dependent on the amount and location of items displayed in the showroom. The developed model is solved using LINGO® software. The NLIP model is implemented in a real world case study in a large retail outlet providing a large variety of products. The proposed model is validated and shows logical results when using the experimental data collected from the market.

Keywords: retailing management, inventory replenishment, shelf space allocation, showroom, backroom

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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Authors: Ehsan Saghehei, Mahdi Eghbali

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The maximal covering location problem (MCLP) was originally developed to determine a set of facility locations which would maximize the total customers' demand serviced by the facilities within a predetermined critical service criterion. However, on some problems that differences between the demand nodes are covered or the number of nodes each node is large, the method of solving MCLP may ignore these differences. In this paper, Heuristic solution based on the ranking of demands in each node and the number of nodes covered by each node according to a predetermined critical value is proposed. The output of this method is to maximize total demands of nodes and number of covered nodes, simultaneously. Furthermore, by providing an example, the solution algorithm is described and its results are compared with Greedy and Lagrange algorithms. Also, the results of the algorithm to solve the larger problem sizes that compared with other methods are provided. A summary and future works conclude the paper.

Keywords: heuristic solution, maximal covering location problem, ranking, set covering

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Authors: Susana Aragoneses Garrido

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Every day, the roads are scenery of numerous accidents involving vehicles, producing thousands of deaths and serious injuries all over the world. Investigations have revealed that Human Factors (HF) are one of the main causes of road accidents in modern societies. Distracted driving (including external or internal aspects of the vehicle), which is considered as a human factor, is a serious and emergent risk to road safety. Consequently, a further analysis regarding this issue is essential due to its transcendence on today’s society. The objectives of this investigation are the detection and assessment of the HF in order to provide solutions (including a better vehicle design), which might mitigate road accidents. The methodology of the project is divided in different phases. First, a statistical analysis of public databases is provided between Spain and The UK. Second, data is classified in order to analyse the major causes involved in road accidents. Third, a simulation between different paths and vehicles is presented. The causes related to the HF are assessed by Failure Mode and Effects Analysis (FMEA). Fourth, different car models are evaluated using the Rapid Upper Body Assessment (RULA). Additionally, the JACK SIEMENS PLM tool is used with the intention of evaluating the Human Factor causes and providing the redesign of the vehicles. Finally, improvements in the car design are proposed with the intention of reducing the implication of HF in traffic accidents. The results from the statistical analysis, the simulations and the evaluations confirm that accidents are an important issue in today’s society, especially the accidents caused by HF resembling distractions. The results explore the reduction of external and internal HF through the global analysis risk of vehicle accidents. Moreover, the evaluation of the different car models using RULA method and the JACK SIEMENS PLM prove the importance of having a good regulation of the driver’s seat in order to avoid harmful postures and therefore distractions. For this reason, a car redesign is proposed for the driver to acquire the optimum position and consequently reducing the human factors in road accidents.

Keywords: analysis vehicles, asssesment, ergonomics, car redesign

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Authors: Mohkammad Nur Cahyadi, Imam Wahyu Farid, Ronny Mardianto, Agung Budi Cahyono, Eko Yuli Handoko, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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Unmanned aerial vehicle (UAV) technology has cost efficiency and data retrieval time advantages. Using technologies such as UAV, GNSS, and LiDAR will later be combined into one of the newest technologies to cover each other's deficiencies. This integration system aims to increase the accuracy of calculating the volume of the land stockpile of PT. Garam (Salt Company). The use of UAV applications to obtain geometric data and capture textures that characterize the structure of objects. This study uses the Taror 650 Iron Man drone with four propellers, which can fly for 15 minutes. LiDAR can classify based on the number of image acquisitions processed in the software, utilizing photogrammetry and structural science principles from Motion point cloud technology. LiDAR can perform data acquisition that enables the creation of point clouds, three-dimensional models, Digital Surface Models, Contours, and orthomosaics with high accuracy. LiDAR has a drawback in the form of coordinate data positions that have local references. Therefore, researchers use GNSS, LiDAR, and drone multi-sensor technology to map the stockpile of salt on open land and warehouses every year, carried out by PT. Garam twice, where the previous process used terrestrial methods and manual calculations with sacks. Research with LiDAR needs to be combined with UAV to overcome data acquisition limitations because it only passes through the right and left sides of the object, mainly when applied to a salt stockpile. The UAV is flown to assist data acquisition with a wide coverage with the help of integration of the 200-gram LiDAR system so that the flying angle taken can be optimal during the flight process. Using LiDAR for low-cost mapping surveys will make it easier for surveyors and academics to obtain pretty accurate data at a more economical price. As a survey tool, LiDAR is included in a tool with a low price, around 999 USD; this device can produce detailed data. Therefore, to minimize the operational costs of using LiDAR, surveyors can use Low-Cost LiDAR, GNSS, and UAV at a price of around 638 USD. The data generated by this sensor is in the form of a visualization of an object shape made in three dimensions. This study aims to combine Low-Cost GPS measurements with Low-Cost LiDAR, which are processed using free user software. GPS Low Cost generates data in the form of position-determining latitude and longitude coordinates. The data generates X, Y, and Z values to help georeferencing process the detected object. This research will also produce LiDAR, which can detect objects, including the height of the entire environment in that location. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours. This study conducted an experimental process on the roof of a building with a radius of approximately 30 meters.

Keywords: LiDAR, unmanned aerial vehicle, low-cost GNSS, contour

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Authors: Soheib Fergani

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This paper concerns with the formal asymptotic stability guarantees, analysis and evaluation of a nonlinear controlled unmanned aerial vehicles (uav) for trajectory tracking purpose. As the system has been recognised as an under-actuated non linear system, the control strategy has been oriented towards a hierarchical control. The dynamics of the system and the mission purpose make it mandatory to provide an absolute proof of the vehicle stability during the maneuvers. For this sake, this work establishes the complete theoretical proof for an implementable control oriented strategy that asymptotically stabilizes (GAS and LISS) the system and has never been provided in previous works. The considered model is reorganized into two partly decoupled sub-systems. The concidered control strategy is presented into two stages: the first sub-system is controlled by a nonlinear backstepping controller that generates the desired control inputs to stabilize the second sub-system. This methodology is then applied to a harware in the loop uav simulator (SiMoDrones) that reproduces the realistic behaviour of the uav in an indoor environment has been performed to show the efficiency of the proposed strategy.

Keywords: UAV application, trajectory tracking, backstepping, sliding mode control, input to state stability, stability evaluation

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Authors: Jogi Prayogo, Dwi Qaqa Prasetyatama, Rahmad Dwi Afandi, Kunto Arief Prasetyo, Viorel Herniza Leksono

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PT. Pertamina Trans Kontinental managed a fleet of 364 ships in 2018 - 2020. In that period, there were 8 incidents of ship damage, causing breakdown maintenance on 6 ships belonging to PT Pertamina Trans Kontinental throughout Indonesia's operational areas due to ropes entangled in propellers. The company's losses that were caused by the fouled propellers amounted to 306.35 Million Rupiah. Of the 8 incidents, Mooring Boat PSC I was taken as a pilot project for further analysis considering the location of the ship which is in Surabaya and Mooring Boat PSC I has experienced 2 incidents of rope entanglement that caused the company's losses due to the largest Breakdown Maintenance amounted to 200.99 Million Rupiah. After analyzing the rope entanglement in the ship's propeller based on the data of Mooring Boat PSC I related to the location of propellers that are often fouled in the conventional propulsion system, it was found that there is a suitable location for the implementation of SI KUMAN tool that serves to cut ropes to prevent the occurrence of rope entangled in ship propellers. The determination of SI KUMAN tool is based on the strength of the ship's material to be installed and a suitable design to prevent the occurrence of ropes being entangled in propellers. After the installation of the "SI KUMAN" tool and monitoring carried out for 1 year period (August 2020 - August 2021), it was found that SI KUMAN tool can eliminate the risk of fouled propeller incidents which previously occurred twice in one year so that the company's loss amounted to 200.99 Million Rupiah can be eliminated and SI KUMAN tool can still operate optimally.

Keywords: breakdown maintenance, mooring boat, fleet, fouled propeller, rope entangled, cut

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Authors: Hamed Nafar, Sajad Rezaei, Hamid Behbahani

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Safety analysis of the roads through the accident rates which is one of the widely used tools has been resulted from the direct exposure method which is based on the ratio of the vehicle-kilometers traveled and vehicle-travel time. However, due to some fundamental flaws in its theories and difficulties in gaining access to the data required such as traffic volume, distance and duration of the trip, and various problems in determining the exposure in a specific time, place, and individual categories, there is a need for an algorithm for prioritizing the road safety so that with a new exposure method, the problems of the previous approaches would be resolved. In this way, an efficient application may lead to have more realistic comparisons and the new method would be applicable to a wider range of time, place, and individual categories. Therefore, an algorithm was introduced to prioritize the safety of roads using the quasi-induced exposure method and utilizing the analytical hierarchy process. For this research, 11 provinces of Iran were chosen as case study locations. A rural accidents database was created for these provinces, the validity of quasi-induced exposure method for Iran’s accidents database was explored, and the involvement ratio for different characteristics of the drivers and the vehicles was measured. Results showed that the quasi-induced exposure method was valid in determining the real exposure in the provinces under study. Results also showed a significant difference in the prioritization based on the new and traditional approaches. This difference mostly would stem from the perspective of the quasi-induced exposure method in determining the exposure, opinion of experts, and the quantity of accidents data. Overall, the results for this research showed that prioritization based on the new approach is more comprehensive and reliable compared to the prioritization in the traditional approach which is dependent on various parameters including the driver-vehicle characteristics.

Keywords: road safety, prioritizing, Quasi-induced exposure, Analytical Hierarchy Process

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Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard Jorswieck

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The capacity of fifth-generation (5G) vehicle-to-everything (V2X) networks poses significant challenges. To ad- dress this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a heterogeneous vehicular network (HetNet). We propose a new framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles while guaranteeing the WiFi users' throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: vehicle-to-everything (V2X), resource allocation, BS assignment, new radio (NR), new radio unlicensed (NR-U), coexistence NR-U and WiFi, deep deterministic policy gradient (DDPG), deep Q-network (DQN), joint BS assignment and resource allocation (JBSRA), duty cycle mechanism

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Authors: Mindaugas Liaudanskas, Monika Tallat-Kelpsaite, Darius Kviklys, Jonas Viskelis, Pranas Viskelis, Norbertas Uselis, Juozas Lanauskas, Valdimaras Janulis

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Apples are an important source of various biologically active compounds used for human health. Phenolic compounds detected in apples are natural antioxidants and have antimicrobial, anti-inflammatory, anticarcinogenic, and cardiovascular protective activity. The quantitative composition of phenolic compounds in apples may be affected by various factors. It is important to investigate it in order to provide the consumer with high-quality well-known composition apples and products made out of it. The objective of this study was to evaluate phenolic compounds quantitative composition in apple fruits grown in a different geographical region. In this study, biological replicates of apple cv. 'Ligol', grown in Lithuania, Latvia, Poland, and Estonia, were investigated. Three biological replicates were analyzed; one of each contained 10 apples. Samples of lyophilized apple fruits were extracted with 70% ethanol (v/v) for 20 min at 40∘C temperature using the ultrasonic bath. The ethanol extracts of apple fruits were analyzed by the high-performance liquid chromatography method. The study found that the geographical location of apple-trees had an impact on the composition of phenolic compounds in apples. The number of quercetin glycosides varied from 314.78±9.47 µg/g (Poland) to 648.17±5.61 µg/g (Estonia). The same trend was also observed with flavan-3-ols (from 829.56±47.17 µg/g to 2300.85±35.49 µg/g), phloridzin (from 55.29±1.7 µg/g to 208.78±0.35 µg/g), and chlorogenic acid (from 501.39±28.84 µg/g to 1704.35±22.65 µg/g). It was observed that the amount of investigated phenolic compounds tended to increase from apples grown in the southern location (Poland) (1701.02±75.38 µg/g) to apples grown northern location (Estonia) (4862.15±56.37 µg/g). Apples (cv. 'Ligol') grown in Estonia accumulated approx. 2.86 times higher amount of phenolic compounds than apples grown in Poland. Acknowledgment: This work was supported by a grant from the Research Council of Lithuania, project No. S-MIP-17-8.

Keywords: apples, cultivar 'Ligol', geographical regions, HPLC, phenolic compounds

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

Abstract:

The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: particle swarm optimization, GIS, traffic data, outliers

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Authors: Retno A. Vinarti, Lucy M. Hederman

Abstract:

This research describes a knowledge model for a system which give personalized alert to users about infectious disease risks in the context of weather, location and time. The knowledge model is based on established epidemiological concepts augmented by information gleaned from infection-related data repositories. The existing disease risk prediction research has more focuses on utilizing raw historical data and yield seasonal patterns of infectious disease risk emergence. This research incorporates both data and epidemiological concepts gathered from Atlas of Human Infectious Disease (AHID) and Centre of Disease Control (CDC) as basic reasoning of infectious disease risk prediction. Using CommonKADS methodology, the disease risk prediction task is an assignment synthetic task, starting from knowledge identification through specification, refinement to implementation. First, knowledge is gathered from AHID primarily from the epidemiology and risk group chapters for each infectious disease. The result of this stage is five major elements (Person, Infectious Disease, Weather, Location and Time) and their properties. At the knowledge specification stage, the initial tree model of each element and detailed relationships are produced. This research also includes a validation step as part of knowledge refinement: on the basis that the best model is formed using the most common features, Frequency-based Selection (FBS) is applied. The portion of the Infectious Disease risk model relating to Person comes out strongest, with Location next, and Weather weaker. For Person attribute, Age is the strongest, Activity and Habits are moderate, and Blood type is weakest. At the Location attribute, General category (e.g. continents, region, country, and island) results much stronger than Specific category (i.e. terrain feature). For Weather attribute, Less Precise category (i.e. season) comes out stronger than Precise category (i.e. exact temperature or humidity interval). However, given that some infectious diseases are significantly more serious than others, a frequency based metric may not be appropriate. Future work will incorporate epidemiological measurements of disease seriousness (e.g. odds ratio, hazard ratio and fatality rate) into the validation metrics. This research is limited to modelling existing knowledge about epidemiology and chain of infection concepts. Further step, verification in knowledge refinement stage, might cause some minor changes on the shape of tree.

Keywords: epidemiology, knowledge modelling, infectious disease, prediction, risk

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Authors: Lucian Stefanita Grigore, Damian Gorgoteanu, Cristian Molder, Amado Stefan, Daniel Constantin

Abstract:

The purpose of this article is to present an analytical-numerical study on the structural behavior of a sunken autonomous underwater vehicle (AUV) for emergency intervention. The need for such a study was generated by the key objective of the ERL-Emergency project. The project aims to develop a system of collaborative robots for emergency response. The system consists of two robots: unmanned ground vehicles (UGV) on tracks and the second is an AUV. The system of collaborative robots, AUV and UGV, will be used to perform missions of monitoring, intervention, and rescue. The main mission of the AUV is to dive into the maritime space of an industrial port to detect possible leaks in a pipeline transporting petroleum products. Another mission is to close and open the valves with which the pipes are provided. Finally, you will need to be able to lift a manikin to the surface, which you can take to land. Numerical analysis was performed by the finite element method (FEM). The conditions for immersing the AUV at 100 m depth were simulated, and the calculations for different fluid flow rates were repeated. From a structural point of view, the stiffening areas and the enclosures in which the command-and-control elements and the accumulators are located have been especially analyzed. The conclusion of this research is that the AUV meets very well the established requirements.

Keywords: analytical-numerical, emergency, FEM, robotics, underwater

Procedia PDF Downloads 151

Authors: L. Wei Sheng, M. T. Noor Syazwanee, C. J. Carolyna, M. Amiruddin, M. Pauziah

Abstract:

This paper exhibits the alternatives towards active suspension systems revised based on the classical passive suspension system to improve comfort and handling performance. An active Magneto rheological (MR) suspension system is proposed as to explore the active based suspension system to enhance performance given its freedom to independently specify the characteristics of load carrying, handling, and ride quality. Malaysian quarter car with two degrees of freedom (2DOF) system is designed and constructed to simulate the actions of an active vehicle suspension system. The structure of a conventional twin-tube shock absorber is modified both internally and externally to comprehend with the active suspension system. The shock absorber peripheral structure is altered to enable the assembling and disassembling of the damper through a non-permanent joint whereby the stress analysis of the designed joint is simulated using Finite Element Analysis. Simulation on the internal part where an electrified copper coil of 24AWG is winded is done using Finite Element Method Magnetics to measure the magnetic flux density inside the MR damper. The primary purpose of this approach is to reduce the vibration transmitted from the effects of road surface irregularities while maintaining solid manoeuvrability. The aim of this research is to develop an intelligent control system of a consecutive damping automotive suspension system. The ride quality is improved by means of the reduction of the vertical body acceleration caused by the car body when it experiences disturbances from speed bump and random road roughness. Findings from this research are expected to enhance the quality of ride which in return can prevent the deteriorating effect of vibration on the vehicle condition as well as the passengers’ well-being.

Keywords: active suspension, FEA, magneto rheological damper, Malaysian quarter car model, vibration control

Procedia PDF Downloads 210

Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

Abstract:

Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: fall detection, machine learning, deep learning, pose estimation, tracking

Procedia PDF Downloads 189