As Bitcoin Falters, Crypto Miners Brace for a Crash …

Texas, a cryptocurrency mining hot spot, has been grappling with an intense heat wave that caused the price of energy to jump by 70 percent —from 10.6 cents to 18.4 cents per kilowatt hour—over...

Analysis of Motorcycle Accident Injury Severity and …

Motorcycle road traffic accidents represent a big concern, as vulnerable road users account for more than half of all road deaths worldwide. The estimation of the influential factors associated with the increase of injury severity of motorcyclists involved in a road accident is of extreme importance as it provides a necessary basis for the development of an appropriate …

Why Does My Mining Rig Keep Turning Off?

Why does my mining rig keep turning off? Some of the leading causes of rig crashes are things like overclocking, faulty risers, and heat. However, to know for sure what's causing the …

Factors influencing the patterns of wrong-way driving crashes …

Past studies on WWD crashes used either descriptive statistics or logistic regression to identify the impact of key contributing factors on frequency and/or severity of crashes. Machine learning and data mining approaches are resourceful in determining interesting and non-trivial patterns from complex datasets.

Analyzing Factors Associated with Fatal Road Crashes: A Machine …

machine learning model to investigate the relationship of fatal road crashes with a set of input feature variables. Using the proposed model, the ranking of the input feature variables was ...

Injury severity on traffic crashes: A text mining with an …

Injury severity on traffic crashes: A text mining with an interpretable machine-learning approach. ... Thus, this study combines machine learning-based text mining with GCV-LIME to identify likely causality factors for injury severities while providing interpretability as required by traffic safety analysts. Data for heavy vehicle crashes ...

Collision Avoidance Systems in the Mining …

Collision avoidance in and around mining operations is an important concern for mines: collisions between workers and vehicles or machinery are one of the leading causes of serious accidents in the US mining industry.

Estimating occupation-related crashes in light and medium …

A two-fold process was developed that included: 1) a machine learning approach for mining crash narratives and 2) a deterministic data linkage effort with crash state data and workers compensation (WC) claims records and emergency medical service (EMS) data, independently. Overall, the combined process identified 5,302 OMV crashes in light and ...

Driving risk assessment using near-crash database through data mining

DOI: 10.1016/j.aap.2015.07.007 Corpus ID: 5751386; Driving risk assessment using near-crash database through data mining of tree-based model. @article{Wang2015DrivingRA, title={Driving risk assessment using near-crash database through data mining of tree-based model.}, author={g Wang and Yang Zheng and Xiaofei Li and Chenfei Yu and Kenji Kodaka …

The 7 Best Cryptocurrency Mining Hardware for …

Bitcoin hash rate December 2022-2024: TradingView 5. WhatsMiner M30S++ WhatsMiner M30S++: Whatsminer Power draw: 3.472 kW Hash rate power: 112 TH/s Price tag: $9,900 – $14,000 Another model from …

Injury severity on traffic crashes: A text mining with an …

Thus, this study combines machine learning-based text mining with GCV-LIME to identify likely causality factors for injury severities while providing interpretability as required by traffic safety analysts. Data for heavy vehicle crashes collected from 2007 to 2017 in Queensland, Australia, were used to evaluate the proposed approach ...

Analyse vehicle–pedestrian crash severity at intersection …

A comprehensive vehicle-by-vehicle crash data set is developed by integrating 5 years of data from California crash, vehicles involved, and road databases that is used to model the severity of rear-end crashes for comparing three analytic techniques: multinomial logit, mixedMultinomiallogit, and support vector machine (SVM).

Exploring Traffic Crash Narratives in Jordan Using Text …

modeling [9]. Chen and Tao (2022) used text mining to examine expressway traffic crash duration and discovered that it can help explain traffic crash causes [10] Other work described a novel way of assessing road-curve collision severity using text mining, highlighting the potential of text mining to improve risk and crash severity information ...

Injury severity on traffic crashes: A text mining with an …

DOI: 10.1016/J.SSCI.2020.104988 Corpus ID: 225020866; Injury severity on traffic crashes: A text mining with an interpretable machine-learning approach @article{Arteaga2020InjurySO, title={Injury severity on traffic crashes: A text mining with an interpretable machine-learning approach}, author={Cristian Arteaga and Alexander Paz and JeeWoong Park}, journal={Safety …

Bitcoin miners' worst days may have passed, but a few

While the hash rate of Bitcoin's network has improved, miners are still under a lot of stress due to low profitability. The earnings of Bitcoin miners have shrunk to one-third of their value from the peak. Before the May 2022 price collapse, miners made more than $0.22 daily per TH/s, a figure which …

Applying machine learning, text mining, and spatial analysis …

Text mining. The crash reports collect valuable information about the reason behind crashes. Rather than only using the crash frequency on crossings, the narrative reports were read to find any potential reasons for crashes. ... This study explored the feasibility of applying cutting-edge machine learning and text mining techniques to develop a ...

Advances, challenges, and future research needs in machine …

Comparatively, the application of machine learning for crash modelling has gained traction over the past two decades, mainly due to its superior performance for predictions. ... feature subset selection algorithms based on association rule mining can also be used, leveraging their structure freedom and global search capability (Hu et al., 2022).

Using Data-Mining Techniques for the Prediction of the

Objective: Analyze the road crashes in Cartagena (Colombia) and the factors associated with the collision and severity.The aim is to establish a set of rules for defining countermeasures to improve road safety. Methods: Data mining and machine learning techniques were used in 7894 traffic accidents from 2016 to 2017.The severity was determined between …

Best Bitcoin Mining Rigs in December 2024

List of the Top Bitcoin Mining Machines in 2024. Bitmain Antminer S21 200T – Ultra-Efficient, 200 TH/s Miner; Bitmain Antminer S19 XP Hydro – Water-cooled, 255 TH/s Miner; MicroBT WhatsMiner M56S – 212 TH/s Water …

Why So Many Bitcoin Mining Companies Are Pivoting to AI

A worker installs a new row of Bitcoin mining machines at the Whinstone U.S. Bitcoin mining facility in Rockdale, Texas, on October 9, 2021. ... Mining companies who survived the crash reaped ...

Old Bitcoin mining rigs risk 'shutdown' after BTC …

New generation Bitcoin mining machines would remain profitable even if the BTC price crashes by another 50%. Older Bitcoin (BTC) mining rigs are finding it difficult to generate positive...

Crasher Machines In China | Crusher Mills, Cone Crusher, Jaw …

Latest China HS Code & tariff for crash shaped machine – Tariff & duty, regulations & restrictions, landed cost calculator, customs data for crash shaped machine in ETCN. the price of stone …

Mini Mining Machines HOT FIX update · Gold Mining …

Hello miners! We have some great news for you – we've just implemented several improvements to Gold Mining Simulator - Mini Mining Machines DLC that will greatly enhance your gold digging experience. Our team has worked hard to fix existing issues and streamline gameplay. Get ready for even more exciting gold-hunting expeditions!

The disaster at Levant

The Levant mine's man engine, a device of reciprocating ladders and stationary platforms that was installed in the mine (not to be confused with the 10m-high Cornish Mining Man Engine mechanical puppet that did a tour of Cornwall earlier this year), broke while there were over 100 miners using it - a contemporary report in the Cornishman And Cornish Telegraph …

Stake-predictor download | SourceForge

Download Stake-predictor for free. The Stake Crash Predictor is a tool designed to predict the next multi. The Stake Crash Predictor is a tool designed to predict the next multiplier number in crash game on stake. It utilizes advanced machine learning techniques to provide predictions for crash game depending on the api data.

Rope and Hose Pulley movement crash · Issue #3234

Crash achieved.... Expected Result. Expected results: I expected the ability move rope pulley's and hose pulley's for use in mining/drilling machines. The rope and hose pulley's function fine as long as they are not moved by any other block or machine. Screenshots and Videos. No response. Crash Report or Log

Taking control: collision avoidance in surface mining

Collision avoidance systems are touted as a critical pathway to safer mines. But they are now also a significant enabling technology of the wider digital, automated mine ecosystem. By Jonathan Rowland.

Texas leaders worry that Bitcoin mines threaten to …

Currently, cryptocurrency mining — mostly for Bitcoin — can draw up to 2,600 megawatts of power from the grid operated by the Electric Reliability Council of Texas, ERCOT's senior vice ...

Causal Analysis and Classification of Traffic Crash Injury …

fundamental characteristics of crash data often result in methodological limitations that are not fully understood or accounted for. More recently, studies indicated that emerging data mining techniques offer superior prediction and greater accuracy due of their ability to work with massive amounts of multidimensional, outlying, and noisy

[PDF] Real-time crash prediction on freeways using data mining …

The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data and proves to be more applicable on real-time safety management on freeways. Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses …

Bitcoin miners 'next trigger' for BTC price crash

Bitcoin (BTC) miners could form the next BTC price "trigger," research warns as withdrawals intensify. In a Quicktake post for on-chain analytics platform CryptoQuant on Nov. …

Traffic Crash Severity: Comparing the Predictive …

Crash severity analysis and prediction is a promising field in traffic safety. Various statistical methods have been used to model the severity of road crashes. However, machine learning algorithms have gained popularity in recent years. This study compares the predictive performance of various machine learning and statistical models, including prediction accuracy, …

(PDF) Road Car Accident Prediction Using a …

machine learning approach to find the best predictive method for road car traffic accident analysis. By this it is meant that road accident data patterns should be studied and

A comparative study on machine learning based algorithms …

Motorcycle crash severity is under-researched in Ghana. Thus, the probable risk factors and association between these factors and motorcycle crash severity outcomes is not known. Traditional statistical models have intrinsic assumptions and pre-defined correlations that, if flouted, can generate inaccurate results. In this study, machine learning based algorithms …

A literature review of machine learning algorithms for crash …

Data mining approach to model bus crash severity in Australia. Journal of Safety Research (2021) P.T. Savolainen et al. ... To gear these efforts, understanding state-of-the-art machine learning-based crash prediction models becomes paramount to summarise the lessons learned from past efforts, which can assist in developing robust and accurate ...

Forecasting Stock Market Crashes via Machine Learning

Chatzis et al.'s (2018) study is so far the only one that systematically addresses the problem of forecasting future stock market crashes via machine learning. 6 They also find significant predictive power of multivariate crash prediction models and conclude that machine learning techniques (including SVMs, tree-based models, and neural ...

Bitcoin miners took on billions in debt to 'pump …

After Bitcoin crashed and energy costs spiraled over the summer, mining firms that took out expensive short-term loans to buy hardware during the bull run now teeter on bankruptcy. Lenders are...

Predictive Analysis of Road Accidents Using Data Mining and Machine …

They used different supervised machine learning techniques, such as Logistic Regression, KNN, NB, DT, and Random Forest, to analyze accident data in order to understand how each factor affects the variables involved in accidents happen. Ayushi Jain et al. used data mining technique to analyse the road accidents in India. The main goal of their ...

Exploring nighttime pedestrian crash patterns at intersection …

Data: This study applied Association Rules Mining (ARM), a rule-based machine learning method, to reveal the association of nighttime pedestrian crash risk factors according to the intersection and segment locations using 2,505 nighttime pedestrian fatal and injury crashes in Louisiana (2015–2019).