This paper presents the concept of Simultaneous Localization and Multi-Mapping (SLAMM). It is a system that ensures continuous mapping and information preservation despite failures in tracking due to corrupted frames or sensor's malfunction; making it suitable for real-world applications. It works with single or multiple robots. In a single robot scenario the algorithm generates a new map at the time of tracking failure, and later it merges maps at the event of loop closure. Similarly, maps generated from multiple robots are merged without prior knowledge of their relative poses; which makes this algorithm flexible. The system works in real time at frame-rate speed. The proposed approach was tested on the KITTI and TUM RGB-D public datasets and it showed superior results compared to the state-of-the-arts in calibrated visual monocular keyframe-based SLAM. The mean tracking time is around 22 milliseconds. The initialization is twice as fast as it is in ORB-SLAM, and the retrieved map can reach up to 90 percent more in terms of information preservation depending on tracking loss and loop closure events. For the benefit of the community, the source code along with a framework to be run with Bebop drone are made available at https://github.com/hdaoud/ORBSLAMM.
The present paper deals with the novel approach for clustering using the image feature of stabilization diagram for automated operational modal analysis in parametric model which is stochastic subspace identification (SSI)-COV. The evolution of automated operational modal analysis (OMA) is not an easy task, since traditional methods of modal analysis require a large amount of intervention by an expert user. The stabilization diagram and clustering tools are introduced to autonomously distinguish physical poles from noise (spurious) poles which can neglect any user interaction. However, the existing clustering algorithms require at least one user-defined parameter, the maximum within-cluster distance between representations of the same physical mode from different system orders and the supplementary adaptive approaches have to be employed to optimize the selection of cluster validation criteria which will lead to high demanding computational effort. The developed image clustering process is based on the input image of the stabilization diagram that has been generated and displayed separately into a certain interval frequency. and standardized image features in MATLAB was applied to extract the image features of each generated image of stabilisation diagrams. Then, the generated image feature extraction of stabilization diagrams was used to plot image clustering diagram and fixed defined threshold was set for the physical modes classification. The application of image clustering has proven to provide a reliable output results which can effectively identify physical modes in stabilization diagrams using image feature extraction even for closely spaced modes without the need of any calibration or user-defined parameter at start up and any supplementary adaptive approach for cluster validation criteria.
The lack of information on ground truth gas dispersion and experiment verification information has impeded the development of mobile olfaction systems, especially for real-world conditions. In this paper, an integrated testbed for mobile gas sensing experiments is presented. The integrated 3 m × 6 m testbed was built to provide real-time ground truth information for mobile olfaction system development. The testbed consists of a 72-gas-sensor array, namely Large Gas Sensor Array (LGSA), a localization system based on cameras and a wireless communication backbone for robot communication and integration into the testbed system. Furthermore, the data collected from the testbed may be streamed into a simulation environment to expedite development. Calibration results using ethanol have shown that using a large number of gas sensor in the LGSA is feasible and can produce coherent signals when exposed to the same concentrations. The results have shown that the testbed was able to capture the time varying characteristics and the variability of gas plume in a 2 h experiment thus providing time dependent ground truth concentration maps. The authors have demonstrated the ability of the mobile olfaction testbed to monitor, verify and thus, provide insight to gas distribution mapping experiment.
Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.
Microdialysis is a sampling technique first introduced in the late 1950s. Although this technique was originally designed to study endogenous compounds in animal brain, it is later modified to be used in other organs. Additionally, microdialysis is not only able to collect unbound concentration of compounds from tissue sites; this technique can also be used to deliver exogenous compounds to a designated area. Due to its versatility, microdialysis technique is widely employed in a number of areas, including biomedical research. However, for most in vivo studies, the concentration of substance obtained directly from the microdialysis technique does not accurately describe the concentration of the substance on-site. In order to relate the results collected from microdialysis to the actual in vivo condition, a calibration method is required. To date, various microdialysis calibration methods have been reported, with each method being capable to provide valuable insights of the technique itself and its applications. This paper aims to provide a critical review on various calibration methods used in microdialysis applications, inclusive of a detailed description of the microdialysis technique itself to start with. It is expected that this article shall review in detail, the various calibration methods employed, present examples of work related to each calibration method including clinical efforts, plus the advantages and disadvantages of each of the methods.
The ozonesonde is a small balloon-borne instrument that is attached to a standard radiosonde to measure profiles of ozone from the surface to 35 km with ~100-m vertical resolution. Ozonesonde data constitute a mainstay of satellite calibration and are used for climatologies and analysis of trends, especially in the lower stratosphere where satellites are most uncertain. The electrochemical-concentration cell (ECC) ozonesonde has been deployed at ~100 stations worldwide since the 1960s, with changes over time in manufacture and procedures, including details of the cell chemical solution and data processing. As a consequence, there are biases among different stations and discontinuities in profile time-series from individual site records. For 22 years the Jülich [Germany] Ozone Sonde Intercomparison Experiment (JOSIE) has periodically tested ozonesondes in a simulation chamber designated the World Calibration Centre for Ozonesondes (WCCOS) by WMO. In October-November 2017 a JOSIE campaign evaluated the sondes and procedures used in SHADOZ (Southern Hemisphere Additional Ozonesondes), a 14-station sonde network operating in the tropics and subtropics. A distinctive feature of the 2017 JOSIE was that the tests were conducted by operators from eight SHADOZ stations. Experimental protocols for the SHADOZ sonde configurations, which represent most of those in use today, are described, along with preliminary results. SHADOZ stations that follow WMO-recommended protocols record total ozone within 3% of the JOSIE reference instrument. These results and prior JOSIEs demonstrate that regular testing is essential to maintain best practices in ozonesonde operations and to ensure high-quality data for the satellite and ozone assessment communities.
Over the years, sedimentation has posed a great danger to the storage capacity of hydropower reservoirs. Good understanding of the transport system and hydrological processes in the dam is very crucial to its sustainability. Under optimal functionality, the Shiroro dam in Northern Nigeria can generate ∼600 MW, which is ideally sufficient to power about 404,000 household. Unfortunately, there have not been reliable monitoring measures to assess yield in the upstream, where sediments are sourced into the dam. In this study, we applied the Soil and Water Assessment Tool (SWAT) to predict the hydrological processes, the sediment transport mechanism and sediment yield between 1990 and 2018 in Kaduna watershed (32,124 km2) located upstream of the dam. The model was calibrated and validated using observed flow and suspended sediment concentration (SSC) data. Performance evaluation of the model was achieved statistically using Nash-Sutcliffe (NS), coefficient of determination (r2) and percentage of observed data (p-factor). SWAT model evaluation using NS (0.71), r2 (0.80) and p-factors of 0.86 suggests that the model performed satisfactorily for streamflow and sediment yield predictions. The model identified the threshold depth of water (GWQMN.gw) and base flow (ALPHA_BF.gw) as the most sensitive parameters for streamflow and sediment yield estimation in the watershed. Our finding showed that an estimated suspended sediment yield of about 84.1 t/ha/yr was deposited within the period under study. Basins 67, 71 and 62 have erosion prone area with the highest sediment values of 79.4, 75.1 and 73.8 t/h respectively. Best management practice is highly recommended for the dam sustainability, because of the proximity of erosion-prone basins to the dam.
Fine resolution (hourly rainfall) of rainfall series for various hydrological systems is widely used. However, observed hourly rainfall records may lack in the quality of data and resulting difficulties to apply it. The utilization of Bartlett-Lewis rectangular pulse (BLRP) is proposed to overcome this limitation. The calibration of this model is regarded as a difficult task due to the existence of intensive estimation of parameters. Global optimization algorithms, named as artificial bee colony (ABC) and particle swarm optimization (PSO) were introduced to overcome this limitation. The issues and ability of each optimization in the calibration procedure were addressed. The results showed that the BLRP model with ABC was able to reproduce well for the rainfall characteristics at hourly and daily rainfall aggregation, similar to PSO. However, the fitted BLRP model with PSO was able to reproduce the rainfall extremes better as compared to ABC.
As a reference photon field, several radionuclides have been used frequently, such as 241Am,137Cs and60 Co for calibration. These nuclides provide mono-energy photons for dosemeters covering few tens of keV-MeV. The main energy around 200 keV is important for both environmental and medical fields since the former should consider scattering photons and the later should measure photons from X-ray generator. In our previous work, a backscattered layout can provide a uniform photon field spectra and dose rate with an energy of 190 keV by using an affordable intensity 137 Cs gamma source. Several other quasi-monoenergetic photon fields in the range of 100-200 keV could be obtained by using several available gamma sources. Two calibrated environmental CsI(Tl) survey meters, Horiba PA-1000 and Mr. Gamma A2700, had been measured with the developed backscattered photon field to understand energy-dependent features in order to confirm dosemeter readings. Consequently, both scintillator instruments are sensitive for measurements of the relatively low dose rates at 190 keV.
This study was designed to obtain and compare the nasalance scores produced by normal Malay
children and those with repaired palatal cleft. Data from 103 noncleft children and 27 children with repaired clefts were included. All children were of Malay origin with the Malay language (Kelantan dialect) as their first language.Two short and simple test stimuli were constructed in the Malay language;one resembled the Nasal Sentences and the other resembled the Zoo Passage (oral passage) used in nasometer testing. Nasalance scores were obtained with the Nasometer II model 6400 by Kay Elemetrics. Calibration of the nasometer and collection of data followed the recommended protocol outlined in the manual. Nasalance scores for the Oral Passage was significantly higher (p< 0.001) for the children with repaired palatal clefts when compared to scores for children without clefts. However, no differences in nasalance scores were detected between both groups for the Nasal Passage. The normative nasalance scores for Malay children with Kelantan dialect was established, which can be used as an objective reference in the management of Malay patients with resonance disorders.
Malaysia is a tropical country and it is subjected to flooding in both the urban and rural areas. Flood
modelling can help to reduce the impacts of flood hazard by taking extra precautions. HEC-RAS model was used to predict the flood levels at selected reach of the Langat River with a total length of 34.4 km. The Langat River is located in the state of Selangor, Malaysia and it is subjected to regular flooding. The selected reach of the Langat River has insufficient data and a methodology was proposed to overcome this particular problem. Since complete floodplain data for the area are not available, the modelling therefore assumed vertical walls at the left and right banks of the Langat River and all the predicted flood levels above the banks were based on this assumption. The HECRAS model was calibrated and the values of Manning’s coefficients of roughness for the Langat River were found to range from 0.04 to 0.10. The discharge values were calculated for 5, 10, 25, 50, and 100 year return periods and the maximum predicted flood depth ranged from 2.1m to 7.8m. Meanwhile, the model output was verified using the historical record and the error between the recorded and predicted water levels was found to range from 3% to 15%.
In recent years image acquisition in close range photogrammetry relies on digital sensors such as digital cameras, video cameras, CCD cameras etc that are not specifically designed for photogrammetry. This study is performed to evaluate the compatibility of the digital metric camera and non-metric camera for the purpose of mapping meandering flume, using close range photogrammetric technique and further, to determine the accuracy that could be achieved using such a technique. The meandering flume provides an opportunity to conduct an experimental study in a controlled environment. In this study, the digital images of the whole meandering flume were acquired using a compact digital camera - Nikon Coolpix S560, a Single Lens Reflex (SLR) Nikon D60 and also a metric digital camera Rollei D30. A series of digital images were acquired to cover the whole meandering flume. Secondary data of ground control points (GCP) and check points (CP), established using the Total Station technique, was used. The digital camera was calibrated and the recovered camera calibration parameters were then used in the processing of digital images. In processing the digital images, digital photogrammetric software was used for processes such as aerial triangulation, stereo compilation, generation of digital elevation model (DEM) and generation of orthophoto. The whole process was successfully performed and the output produced in the form of orthophoto. The research output is then evaluated for planimetry and vertical accuracy using root mean square error (RMSE). Based on the analysis, sub-meter accuracy is obtained. It can be concluded that the differences between the different types of digital camera are small . As a conclusion, this study proves that close range photogrammetry technique can be used for mapping meandering flume using both the metric digital camera and non-metric digital camera.
Gamma Spectrometry Counting System requires similar counting geometries for the calibration source, reference material and samples. The objectives of this study were to find out the effects of the sample density on 137 Cs activities measurement and propose reasonable corrections. Studies found that the activity of the samples is decreasing when the density of samples increased. Therefore, in order to have a more accurate estimation of samples activities; density corrections should be done either by performs mathematical corrections using equation or by increasing the expanded uncertainty when sample densities deviated from calibration source.
The paper relates a study on the development of an analysis procedure for measuring the gold coating thickness using EDXRF technique. Gold coating thickness was measured by relating the counts under the Au Lα peak its thickness value. In order to get a reasonably accurate result, a calibration graph was plotted using five gold-coated reference standards of different thicknesses. The calibration graph shows a straight line for thin coating measurement until 0.9μm. Beyond this the relationship was not linear and this may be resulted from the selfabsorption effect. Quantitative analysis was also performed on two different samples of goldcoated jewelry and a phone connector. Result from the phone connector analysis seems to agree with the manufacturer’s gold coating value. From the analysis of gold-coated jewelry it had been able to differentiate the two articles as gold wash and gold electroplated.
Groundwater is the main source of water in the Kingdom of Saudi Arabia (KSA). A larger part of groundwater is founded in alluvial (unconfined) aquifers. Prediction of water table elevations in
unconfined aquifers is very useful in water resources planning and management. During the last two
decades, many aquifers in different regions of the KSA experienced significant groundwater decline.
The declines in these aquifers raised concerns over the quantity and quality of groundwater, as well
as concerns over the planning and management policies used in KSA. The main objective of this study was to predict water table fluctuations and to estimate the annual change in water table at an alluvial aquifer at wadi Hada Al Sham near Makkah, KSA. The methodology was achieved using numerical groundwater model (MODFLOW). The model was calibrated and then used to predict water table elevations due to pumping for a period of 5 years. The output of the model was found to be in agreement with the previous records. Moreover, the simulation results also show reasonable declination of water table elevations in the study area during the study period.
The selection of curve number to represent watersheds with similar land use and land cover is often subjective and ambiguous. Watershed with several soil groups further complicates curve number selection process while wrong curve number selection often produces unrealistic runoff estimates. The 1954 simplified Soil Conservation Services (SCS) runoff model over-predicted runoff with significant amount and further magnified runoff prediction error toward higher rainfall depths in this study. The model was statistically insignificant with the rejection of two null hypotheses and paved the way for regional model calibration study. This paper proposes a new direct curve number derivation technique from the given rainfall-runoff conditions under the guide of inferential statistics. The technique offers a swift and economical solution to improve the runoff prediction ability of the SCS runoff model with statistically significant results. A new rainfall-runoff model was developed with calibration according to the regional hydrological conditions. It out-performed the runoff prediction of the simplified SCS runoff model and the asymptotic runoff model. The derived curve number = 89 at alpha = 0.01 level. The technique can be adopted to predict flash flood and forecast urban runoff.
This paper presents an auto grasping algorithm of a proposed robotic gripper. The purpose is to enhance the grasping mechanism of the gripper. Earlier studies have introduced various methods to enhance the grasping mechanism, but most of the works have not looked at the weight measurement method. Thus, with this algorithm, the weight of the object is calculated based on modified Wheatstone Bridge Circuit (WBC) which is controlled by programmable interface controller (PIC) method. Having this approach introduces and improves the grasping mechanism through an auto grasping algorithm. Experimental results show that an auto grasping algorithm based on pressure sensor measurements leads to a more precise grasping measurement and consequently enhance the sensitivity measurement as well as accurate movement calibration. Furthermore, several different grasping objects based on the proposed method are examined to demonstrate the performance and robustness of our approach.
This paper presents a novel approach to predicting self-calibration in a pressure sensor using a proposed Levenberg Marquardt Back Propagation Artificial Neural Network (LMBP-ANN) model. The self-calibration algorithm should be able to fix major problems in the pressure sensor such as hysteresis, variation in gain and lack of linearity with high accuracy. The traditional calibration process for this kind of sensor is a time-consuming task because it is usually done through manual and repetitive identification. Furthermore, a traditional computational method is inadequate for solving the problem since it is extremely difficult to resolve the mathematical formula among multiple confounding pressure variables. Accordingly, this paper describes a new self-calibration methodology for nonlinear pressure sensors based on an LMBP-ANN model. The proposed method was achieved using a collected dataset from pressure sensors in real time. The load cell will be used as a reference for measuring the applied force. The proposed method was validated by comparing the output pressure of the trained network with the experimental target pressure (reference). This paper also shows that the proposed model exhibited a remarkable performance than traditional methods with a max mean square error of 0.17325 and an R-value over 0.99 for the total response of training, testing and validation. To verify the proposed model's capability to build a self-calibration algorithm, the model was tested using an untrained input data set. As a result, the proposed LMBP-ANN model for self-calibration purposes is able to successfully predict the desired pressure over time, even the uncertain behaviour of the pressure sensors due to its material creep. This means that the proposed model overcomes the problems of hysteresis, variation in gain and lack of linearity over time. In return, this can be used to enhance the durability of the grasping mechanism, leading to a more robust and secure grasp for paralyzed hands. Furthermore, the exposed analysis approach in this paper can be a useful methodology for the user to evaluate the performance of any measurement system in a real-time environment.
The data presented here are related to the research paper entitled "A below-the-present late Holocene relative sea level and the glacial isostatic adjustment during the Holocene in the Malay Peninsula" (Tam et al., 2018) . The diatoms and pollen data are collected from surface sediments of the Merang wetlands, Kuala Terengganu, Malaysia, and are presented as percentages of total diatoms or total land pollen respectively. Ground elevations of the sampling sites are levelled to the national datum and expressed as elevations above or below mean sea level. These diatom and pollen data can be used for indicative meaning calibration of sea-level index points and for the development of diatom-based or pollen-based tidal level transfer functions. These data have been used for calibrating the indicative meanings for sea-level index points in the reconstruction of Holocene sea-level history of the Peninsular Malaysia.
The rapid development of open source developmental boards incorporating microcontrollers on printed circuit boards has offered many alternatives in creating feasible, low cost indoor environment monitoring and controlling platforms. Data are collected and stored in predetermined locations throughout a series of communication activities between a network of active sensors and their processing units. However, the issue of data precision and accuracy are of real concern for generating baseline information. Therefore, with that in mind, the purpose of this paper is to accentuate an insightful trend of retrieving indoor environment data (temperature and relative humidity) for an office building in a hot and humid climate condition. The indoor parameters were monitored using a combination of a single board microcontroller with an active sensor with well calibrated thermal microclimate devices. Accordingly, it was found that proactive adjustment can be conducted in order to minimize waste.