Trade-offs between headway, fare, and real-time bus information under different weather conditions

2018 ◽  
Vol 10 (2) ◽  
pp. 217-240
Author(s):  
Md Matiur Rahman ◽  
Lina Kattan ◽  
S. C. Wirasinghe
2018 ◽  
Vol 1 (3) ◽  
Author(s):  
IJE Manager

In the past century, fossil fuels have dominated energy supply in Indonesia. However, concerns over emissions are likely to change the future energy supply. As people become more conscious of environmental issues, alternatives for energy are sought to reduce the environmental impacts. These include renewable energy (RE) sources such as solar photovoltaic (PV) systems. However, most RE sources like solar PV are not available continuously since they depend on weather conditions, in addition to geographical location. Bali has a stable and long sunny day with 12 hours of daylight throughout the year and an average insolation of 5.3 kWh/m2 per day. This study looks at the potential for on-grid solar PV to decarbonize energy in Bali. A site selection methodology using GIS is applied to measure solar PV potential. Firstly, the study investigates the boundaries related to environmental acceptability and economic objectives for land use in Bali. Secondly, the potential of solar energy is estimated by defining the suitable areas, given the technical assumptions of solar PV. Finally, the study extends the analysis to calculate the reduction in emissions when the calculated potential is installed. Some technical factors, such as tilting solar, and intermittency throughout the day, are outside the scope of this study. Based on this model, Bali has an annual electricity potential for 32-53 TWh from solar PV using amorphous thin-film silicon as the cheapest option. This potential amount to three times the electricity supply for the island in 2024 which is estimated at 10 TWh. Bali has an excessive potential to support its own electricity demand with renewables, however, some limitations exist with some trade-offs to realize the idea. These results aim to build a developmental vision of solar PV systems in Bali based on available land and the region’s irradiation.


Author(s):  
V. Нolovan ◽  
V. Gerasimov ◽  
А. Нolovan ◽  
N. Maslich

Fighting in the Donbas, which has been going on for more than five years, shows that a skillful counter-battery fight is an important factor in achieving success in wars of this kind. Especially in conditions where for the known reasons the use of combat aviation is minimized. With the development of technical warfare, the task of servicing the counter-battery fight began to rely on radar stations (radar) to reconnaissance the positions of artillery, which in modern terms are called counter-battery radar. The principle of counter-battery radar is based on the detection of a target (artillery shell, mortar mine or rocket) in flight at an earlier stage and making several measurements of the coordinates of the current position of the ammunition. According to these data, the trajectory of the projectile's flight is calculated and, on the basis of its prolongation and extrapolation of measurements, the probable coordinates of the artillery, as well as the places of ammunition falling, are determined. In addition, the technical capabilities of radars of this class allow you to recognize the types and caliber of artillery systems, as well as to adjust the fire of your artillery. The main advantages of these radars are:  mobility (transportability);  inspection of large tracts of terrain over long distances;  the ability to obtain target's data in near real-time;  independence from time of day and weather conditions;  relatively high fighting efficiency. The purpose of the article is to determine the leading role and place of the counter-battery radar among other artillery instrumental reconnaissance tools, to compare the combat capabilities of modern counter-battery radars, armed with Ukrainian troops and some leading countries (USA, China, Russia), and are being developed and tested in Ukraine. The method of achieving this goal is a comparative analysis of the features of construction and combat capabilities of modern models of counter-battery radar in Ukraine and in other countries. As a result of the conducted analysis, the directions of further improvement of the radar armament, increasing the capabilities of existing and promising counter-battery radar samples were determined.


Author(s):  
Gaurav Chaurasia ◽  
Arthur Nieuwoudt ◽  
Alexandru-Eugen Ichim ◽  
Richard Szeliski ◽  
Alexander Sorkine-Hornung

We present an end-to-end system for real-time environment capture, 3D reconstruction, and stereoscopic view synthesis on a mobile VR headset. Our solution allows the user to use the cameras on their VR headset as their eyes to see and interact with the real world while still wearing their headset, a feature often referred to as Passthrough. The central challenge when building such a system is the choice and implementation of algorithms under the strict compute, power, and performance constraints imposed by the target user experience and mobile platform. A key contribution of this paper is a complete description of a corresponding system that performs temporally stable passthrough rendering at 72 Hz with only 200 mW power consumption on a mobile Snapdragon 835 platform. Our algorithmic contributions for enabling this performance include the computation of a coarse 3D scene proxy on the embedded video encoding hardware, followed by a depth densification and filtering step, and finally stereoscopic texturing and spatio-temporal up-sampling. We provide a detailed discussion and evaluation of the challenges we encountered, as well as algorithm and performance trade-offs in terms of compute and resulting passthrough quality.;AB@The described system is available to users as the Passthrough+ feature on Oculus Quest. We believe that by publishing the underlying system and methods, we provide valuable insights to the community on how to design and implement real-time environment sensing and rendering on heavily resource constrained hardware.


2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.


Computers ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 127
Author(s):  
Besmir Sejdiu ◽  
Florije Ismaili ◽  
Lule Ahmedi

Sensors and other Internet of Things (IoT) technologies are increasingly finding application in various fields, such as air quality monitoring, weather alerts monitoring, water quality monitoring, healthcare monitoring, etc. IoT sensors continuously generate large volumes of observed stream data; therefore, processing requires a special approach. Extracting the contextual information essential for situational knowledge from sensor stream data is very difficult, especially when processing and interpretation of these data are required in real time. This paper focuses on processing and interpreting sensor stream data in real time by integrating different semantic annotations. In this context, a system named IoT Semantic Annotations System (IoTSAS) is developed. Furthermore, the performance of the IoTSAS System is presented by testing air quality and weather alerts monitoring IoT domains by extending the Open Geospatial Consortium (OGC) standards and the Sensor Observations Service (SOS) standards, respectively. The developed system provides information in real time to citizens about the health implications from air pollution and weather conditions, e.g., blizzard, flurry, etc.


Author(s):  
L.P.S.S.K. Dayananda ◽  
A. Narmilan ◽  
P. Pirapuraj

Background: Weather monitoring is an important aspect of crop cultivation for reducing economic loss while increasing productivity. Weather is the combination of current meteorological components, such as temperature, wind direction and speed, amount and kind of precipitation, sunshine hours and so on. The weather defines a time span ranging from a few hours to several days. The periodic or continuous surveillance or the analysis of the status of the atmosphere and the climate, including parameters such as temperature, moisture, wind velocity and barometric pressure, is known as weather monitoring. Because of the increased usage of the internet, weather monitoring has been upgraded to smart weather monitoring. The Internet of Things (IoT) is one of the new technology that can help with many precision farming operations. Smart weather monitoring is one of the precision agriculture technologies that use sensors to monitor correct weather. The main objective of the research is to design a smart weather monitoring and real-time alert system to overcome the issue of monitoring weather conditions in agricultural farms in order for farmers to make better decisions. Methods: Different sensors were used in this study to detect temperature and humidity, pressure, rain, light intensity, CO2 level, wind speed and direction in an agricultural farm and real time clock sensor was used to measured real time weather data. The major component of this system was an Arduino Uno microcontroller and the system ran according to a program written in the Arduino Uno software. Result: This is a low-cost smart weather monitoring system. This system’s output unit were a liquid crystal display and a GSM900A module. The weather data was displayed on a liquid crystal display and the GSM900A module was used to send the data to a mobile phone. This smart weather station was used to monitor real-time weather conditions while sending weather information to the farmer’s mobile phone, allowing him to make better decisions to increase yield.


2021 ◽  
Author(s):  
Romak Kordnejad

This thesis focuses on the current state of combined sewer overflows (CSO) in the City of Toronto and the potential benefits of utilizing real-time monitoring system to explore options for optimizing current models and reducing future overflows. CSOs containing sanitary and stormwater sewage over spill during wet weather conditions, contaminating bodies of water. Antiquated sewer systems built to support population at the time, no longer have the required capacity to support exponential growth causing environmental damage. Key research findings include exploring the current CSO state in the City of Toronto, remediation plans executed by the City in hopes to reduce CSO and finally concluding the City’s progress to date. Extensive research on CSOs in North American cities has shown initiative towards reducing CSOs while using real-time monitoring systems which can be utilized in the City of Toronto. Future research is required to find effective and efficient ways of implementing such systems.


Author(s):  
William Nieman

Power generation has the goal of maximizing power output while minimizing operations and maintenance cost. The challenge for plant manager is to move closer to reliability limits while being confident the risks of any decision are understood. To attain their goals and meet this challenge they are coming to realize that they must have frequent, accurate assessment of equipment operating conditions, and a path to continued innovation-. At a typical plant, making this assessment involves the collection and effective analysis of reams of complex, interrelated production system data, including demand requirements, load, ambient temperature, as well as the dependent equipment data. Wind turbine health and performance data is available from periodic and real-time systems. To obtain the timeliest understanding of equipment health for all the key resources in a large plant or fleet, engineers increasingly turn to real-time, model-based solutions. Real-time systems are capable of creating actionable intelligence from large amounts and diverse sources of current data. They can automatically detect problems and provide the basis for diagnosis and prioritization effectively for many problems, and they can make periodic inspection methods much more efficient. Technology exists to facilitate prediction of when assets will fail, allowing engineers to target maintenance costs more effectively. But, it is critical to select the best predictive analytics for your plant. How do you make that choice correctly? Real-time condition monitoring and analysis tools need to be matched to engineering process capability. Tools are employed at the plant in lean, hectic environments; others are deployed from central monitoring centers charged with concentrating scarce resources to efficiently support plants. Applications must be flexible and simple to implement and use. Choices made in selection of new tools can be very important to future success of plant operations. So, these choices require solid understanding of the problems to be solved and the advantages and trade-offs of potential solutions. This choice of the best Predictive Analytic solution will be discussed in terms of key technology elements and key engineering elements.


2018 ◽  
Vol 15 (4) ◽  
pp. 362-370 ◽  
Author(s):  
Stefan Kroll ◽  
Alessio Fenu ◽  
Tom Wambecq ◽  
Marjoleine Weemaes ◽  
Jan Van Impe ◽  
...  

2020 ◽  
Vol 2 (4) ◽  
pp. 558-578
Author(s):  
Théo Combey ◽  
António Loison ◽  
Maxime Faucher ◽  
Hatem Hajri

Neural network classifiers (NNCs) are known to be vulnerable to malicious adversarial perturbations of inputs including those modifying a small fraction of the input features named sparse or L0 attacks. Effective and fast L0 attacks, such as the widely used Jacobian-based Saliency Map Attack (JSMA) are practical to fool NNCs but also to improve their robustness. In this paper, we show that penalising saliency maps of JSMA by the output probabilities and the input features of the NNC leads to more powerful attack algorithms that better take into account each input’s characteristics. This leads us to introduce improved versions of JSMA, named Weighted JSMA (WJSMA) and Taylor JSMA (TJSMA), and demonstrate through a variety of white-box and black-box experiments on three different datasets (MNIST, CIFAR-10 and GTSRB), that they are both significantly faster and more efficient than the original targeted and non-targeted versions of JSMA. Experiments also demonstrate, in some cases, very competitive results of our attacks in comparison with the Carlini-Wagner (CW) L0 attack, while remaining, like JSMA, significantly faster (WJSMA and TJSMA are more than 50 times faster than CW L0 on CIFAR-10). Therefore, our new attacks provide good trade-offs between JSMA and CW for L0 real-time adversarial testing on datasets such as the ones previously cited.


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