scholarly journals Evidential Data Fusion for Characterization of Pavement Surface Conditions during Winter Using a Multi-Sensor Approach

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8218
Author(s):  
Issiaka Diaby ◽  
Mickaël Germain ◽  
Kalifa Goïta
Keyword(s):  
Deep Learning ◽  
Data Fusion ◽  
Low Cost ◽  
Winter Period ◽  
The Road ◽  
Traffic Conditions ◽  
Evidential Theory ◽  
Learning Architectures

The role of a service that is dedicated to road weather analysis is to issue forecasts and warnings to users regarding roadway conditions, thereby making it possible to anticipate dangerous traffic conditions, especially during the winter period. It is important to define pavement conditions at all times. In this paper, a new data acquisition approach is proposed that is based upon the analysis and combination of two sensors in real time by nanocomputer. The first sensor is a camera that records images and videos of the road network. The second sensor is a microphone that records the tire–pavement interaction, to characterize each surface’s condition. The two low-cost sensors were fed to different deep learning architectures that are specialized in surface state analysis; the results were combined using an evidential theory-based data fusion approach. This study is a proof of concept, to test an evidential approach for improving classification with deep learning, applied to only two sensors; however, one could very well add more sensors and make the nanocomputers communicate together, to analyze a larger urban environment.

Low-Cost Smart Heads-Up Display Assist System for Automobiles

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Gautham G ◽  
Deepika Venkatesh ◽  
A. Kalaiselvi
Keyword(s):  
Fuel Economy ◽  
Low Cost ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Raspberry Pi ◽  
Worst Case ◽  
The Road ◽  
Traffic Conditions ◽  
Metropolitan Cities ◽  
Ingenious Method

In recent years, due to the increasing density of traffic every year, it is been a hassle for drivers in metropolitan cities to maintain lane and speeds on road. The drivers usually waste time and effort in idling their cars to maintain in traffic conditions. The drivers get easily frustrated when they tried to maintain the path because of the havoc created. Transportation Institute found that the odds of a crash(or near crash) more than doubled when the driver took his or her eyes off the road formore than two seconds. This tends to cause about 23% of accidents when not following their lane paths. In worst case the fuel economy often drops and tends to cause increase in pollution about 28% to 36% per vehicle annually. This corresponds to the wastage of fuel. Owing to this problem, we proposed an ingenious method by which the lane detection can be made affordable and applicable to existing automobiles. The proposed prototype of lane detection is carried over with a temporary autonomous bot which is interfaced with Raspberry pi processor, loaded with the lane detection algorithm. This prototype bot is made to get live video which is then processed by the algorithm. Also, the preliminary setups are carried over in such a way that it is easily implemented and accessible at low cost with better efficiency, providing a better impact on future automobiles.

scholarly journals Formulation of probability-based pervasive information set features and Hanman transform classifier for the categorization of mammograms

2021 ◽  
Vol 3 (6) ◽  
Author(s):  
Jyoti Dabass ◽  
M. Hanmandlu ◽  
Rekha Vig
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Statistical Analysis ◽  
Fuzzy Set ◽  
State Of The Art ◽  
Entropy Function ◽  
Information Set ◽  
Learning Architectures

AbstractWith aim of detecting breast cancer at the early stages using mammograms, this study presents the formulation of five feature types by extending the information set to encompass the concept of an intuitionist fuzzy set. The resulting pervasive information set gives not only the certainty of the pixel intensities of mammograms to a class but also the deficiency in the fuzzy modeling referred to as the hesitancy. The generalized adaptive Hanman Anirban fuzzy entropy function is shown to be equivalent to the hesitancy entropy function. The probability-based fuzzy Hanman transform and the pervasive Information with probability taking the role of hesitancy degree help derive the above five feature types termed as probability-based pervasive Information set features. The effectiveness of each feature type is demonstrated on the mini-MIAS and DDSM databases for the multi-class categorization of mammograms using the Hanman transform classifier. The statistical analysis by ANOVA test proves that the features are statistically significant and the experimental results are shown to be clinically relevant by the expert radiologists. The performance of the five feature types is either superior to or equal to that of some deep learning architectures on comparison but they outperform the state-of-the-art literature methods in the classification of breast cancer using mammograms.

Benefits from Constructing a Dam Across the Vistula in Siarzewo in Terms of Transport and Environmental Protection

2017 ◽  
Author(s):  
Jan Kempa ◽  
Jacek Chmielewski ◽  
Grzegorz Bebyn
Keyword(s):  
Environmental Impact ◽  
Road Network ◽  
Transport Model ◽  
Investment Project ◽  
Dam Construction ◽  
Transport Activity ◽  
The Road ◽  
Traffic Conditions ◽  
On The Road

This paper presents the results of analyses that concern the benefits from the planned construction of a dam across the Vistula in Siarzewo. The simulated transport model developed in the VISUM environment has been used to determine the forecast traffic intensity, the value of traffic volume indices, transport activity, travel times of drivers and passengers as well as the costs of environmental impact. The above-mentioned characteristics have enabled to determine savings both in terms of traffic costs and environmental impacts resulting from the dam construction. The paper indicates that the implementation of the investment project improves traffic conditions on the road network and reduces the transport environmental impact in Kujawsko-Pomorskie Province. Moreover, it has been found that the revealed effects concern in particular the first years after the launch of the project. The development of the road network diminishes the role of the analysed investment project significantly.

scholarly journals Considerations on the role of modernizing the road infrastructure in the prevention of road accidents

2019 ◽  
Vol 290 ◽  
pp. 06004
Author(s):  
Cristian Deac ◽  
Lucian Tarnu
Keyword(s):  
Road Safety ◽  
Road Network ◽  
Road Traffic ◽  
Road Accidents ◽  
Road Infrastructure ◽  
The Road ◽  
Traffic Conditions ◽  
Pedestrian Crossing

The realizing and improvement of road infrastructure, of modern road networks provides normal, safe and pleasant road traffic conditions and also help prevent road accidents. The road network, with its constructive characteristics, has to offer optimal conditions for the movement of vehicles, pedestrians and other categories of participants in the road traffic. Starting from the case study of a road sector with heavy road traffic, the current paper analyzes the increase in road safety in Romanian localities along European and national roads through the implementation of specific measures such as setting up sidewalks, installing New Jersey median barriers, expanding the road sectors with 2+1 lanes, replacing normal pedestrian crossings with elevated crossings or with pedestrian crossing with mid-road waiting areas etc.

Mathematical approaches for optimization of dengue fever dynamics

2019 ◽  
Vol 10 (02) ◽  
pp. 1950006
Author(s):  
Didar Murad ◽  
Noor Badshah ◽  
Muhammad Ali Syed
Keyword(s):  
Optimal Control ◽  
Dengue Fever ◽  
Low Cost ◽  
State Variables ◽  
Control Variables ◽  
Vector Population ◽  
Existence Of Optimal Control ◽  
And Control

Background and Objective: For dengue outbreak prevention and vectors reduction, fundamental role of control parameters like vaccination against dengue virus in human population and insecticide in mosquito population have been addressed theoretically and numerically. For this purpose, an existing model was modified to optimize dengue fever. Methodology: Using Pontryagin’s maximum principle, the dynamics of infection for the optimal control problem was addressed, further, defined cost functional, established existence of optimal control, stated Hamiltonian for characterization of optimization. Results: Numerical simulations for optimal state variables and control variables were performed. Conclusion: Our findings demonstrate that with low cost of control variables, state variable such as recovered population increases gradually and decrease other state variables for host and vector population.

scholarly journals Selection and characterization of a SpaCBA pilus-secreting food-grade derivative of Lacticaseibacillus rhamnosus GG

2021 ◽  
Author(s):  
Hanne L. P. Tytgat ◽  
Pia Rasinkangas ◽  
Jarmo Ritari ◽  
Justus Reunanen ◽  
Steven Aalvink ◽  
...  
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Lactobacillus Rhamnosus ◽  
Scale Production ◽  
Therapeutic Application ◽  
Food Grade ◽  
Large Scale Production ◽  
Key Points

AbstractMany studies have established the functional properties of Lacticaseibacillus rhamnosus GG, previously known as Lactobacillus rhamnosus GG, marketed worldwide as a probiotic. The extraordinary capacity of L. rhamnosus GG to bind to human mucus and influence the immune system especially stand out. Earlier, we have shown the key role of its SpaCBA sortase-dependent pili encoded by the spaCBA-srtC1 gene cluster herein. These heterotrimeric pili consist of a shaft pilin SpaA, a basal pilin SpaB, and tip pilin SpaC that contains a mucus-binding domain. Here, we set out to characterize a food-grade non-GMO mutant of L. rhamnosus GG, strain PA11, which secretes its pilins, rather than coupling them to the cell surface, due to a defect in the housekeeping sortase A. The sortase-negative strain PA11 was extensively characterized using functional genomics and biochemical approaches and found to secrete the SpaCBA pili into the supernatant. Given the functional importance and uniqueness of the mucus-binding pili of L. rhamnosus GG, strain PA11 offers novel opportunities towards the characterization and further therapeutic application of SpaCBA pili and their low-cost, large-scale production. Key points •Creation of pilus-secreting mutant (PA11) of the key probiotic LGG. •Strain PA11 is defective in a functional housekeeping sortase SrtA. •Strain PA11 opens novel biotherapeutic application avenues. Graphical abstract

Cell (patho)physiology of magnesium

2007 ◽  
Vol 114 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Federica I. Wolf ◽  
Valentina Trapani
Keyword(s):  
Energy Metabolism ◽  
Dynamic Environment ◽  
Biological Functions ◽  
Cellular Functions ◽  
Intracellular Magnesium ◽  
The Road ◽  
Cell Functions ◽  
Growth Energy

There is an unsettled debate about the role of magnesium as a ‘chronic regulator’ of biological functions, as opposed to the well-known role for calcium as an ‘acute regulator’. New and old findings appear to delineate an increasingly complex and important role for magnesium in many cellular functions. This review summarizes the available evidence for a link between the regulation of intracellular magnesium availability and the control of cell growth, energy metabolism and death, both in healthy and diseased conditions. A comprehensive view is precluded by technical difficulties in tracing magnesium within a multicompartment and dynamic environment like the cell; nevertheless, the last few years has witnessed encouraging progress towards a better characterization of magnesium transport and its storage or mobilization inside the cell. The latest findings pave the road towards a new and deeper appreciation of magnesium homoeostasis and its role in the regulation of essential cell functions.

Deep Learning Approaches for Detecting COVID-19 from Chest X-ray Images: A Survey (Preprint)

2020 ◽  
Author(s):  
Hanan Alghamdi ◽  
Ghada Amoudi ◽  
Salma Elhag ◽  
Kawther Saeedi ◽  
Jomanah Nasser
Keyword(s):  
Deep Learning ◽  
Visual Information ◽  
Low Cost ◽  
Limited Resource ◽  
Learning Approaches ◽  
X Ray ◽  
Wide Range ◽  
Control And Prevention ◽  
Chest X Ray ◽  
Learning Architectures

UNSTRUCTURED Chest X-ray (CXR) imaging is a standard and crucial examination method used for suspected cases of coronavirus disease (COVID-19). In profoundly affected or limited resource areas, CXR imaging is preferable owing to its availability, low cost, and rapid results. However, given the rapidly spreading nature of COVID-19, such tests could limit the efficiency of pandemic control and prevention. In response to this issue, artificial intelligence methods such as deep learning are promising options for automatic diagnosis because they have achieved state-of-the-art performance in the analysis of visual information and a wide range of medical images. This paper reviews and critically assesses the preprint and published reports between March and May 2020 for the diagnosis of COVID-19 via CXR images using convolutional neural networks and other deep learning architectures. Despite the encouraging results, there is an urgent need for public, comprehensive, and diverse datasets. Further investigations in terms of explainable and justifiable decisions are also required for more robust, transparent, and accurate predictions

CHARACTERIZATION OF PHOSPHORIC ACID IMPREGNATED ACTIVATED CARBON PRODUCED FROM HONEYDEW PEEL

2015 ◽  
Vol 76 (5) ◽  
Author(s):  
Zalilah Murni Yunus ◽  
Norzila Othman ◽  
R. Hamdan ◽  
N. N. Ruslan
Keyword(s):  
Activated Carbon ◽  
Phosphoric Acid ◽  
Low Cost ◽  
Total Pore Volume ◽  
Wastewater Remediation ◽  
Activation Temperature ◽  
Precursor Material ◽  
Potential Use

The role of waste materials in producing activated carbon (AC) used in adsorption has been identified as an alternative to substitute commercial expensive wooden starting materials. The present study has chosen honeydew peel as an alternative starting material in activated carbon production because of it’s low cost, availabality and incurs minimal cost for waste management. The production involved chemical impregnation using 20% diluted phosphoric acid (H3PO4) prior to activation. To optimize the activation method, the effect of different activation temperatures (470°C - 550°C) on the physicochemical properties of the AC was studied. The results showed that the AC carbonized at 490°C possessed 942 mg/g iodine number, 997 m2/g surface area SBET and 0.56 ml/g total pore volume. FESEM images showed a high pore development as the activation temperature increased. FTIR indicated the presence of –OH, C=O bond in carboxylic acids, ketones, aldehydes, lactones and ester functional groups on the AC. The experimental results presented the potential use of honeydew peel as a precursor material in the preparation of inexpensive adsorbent for wastewater remediation.

Characterization of carbides in iron Fischer-Tropsch catalysts

1995 ◽  
Vol 53 ◽  
pp. 434-435
Author(s):  
Mehul D. Shroff ◽  
Dinesh S. Kalakkad ◽  
Nancy B. Jackson ◽  
Mark S. Harrington ◽  
Allen G. Sault ◽  
...  
Keyword(s):  
Photoelectron Spectroscopy ◽  
Carbide Phase ◽  
Low Cost ◽  
High Water ◽  
X Ray Diffraction ◽  
Fischer Tropsch ◽  
X Ray ◽  
Water Gas

The Fischer - Tropsch synthesis (FTS) for the production of synthetic hydrocarbons from the indirect liquefaction of coal has tremendous potential as an alternative to petroleum - based fuels. The use of iron catalysts is desirable due to their low cost, easy availability, good FTS activity and high water - gas shift activity thus enabling use with low H2 / CO ratios. However, problems relating to attrition and deactivation need to be addressed. In addition, there has been a controversy in the literature regarding the role of the carbide phase and the identity of the active catalytic phase. The main reason for the existence of this debate has been the use of different characterization techniques. Our results with a commercial, precipitated and spray-dried, Fe2O3 - CuO - K2O Fischer-Tropsch catalyst point to the fact that conventional techniques like X - ray Diffraction (XRD), X - ray Photoelectron Spectroscopy (XPS) and Auger Electron Spectroscopy (AES) which have been traditionally used to characterize these catalysts (1,2) are not very successful in detecting the existence of the carbide phase, which generally forms as 20 - 30 nm crystallites on the surface of the micron - sized magnetite crystals.

Sign in / Sign up

Export Citation Format

Share Document