Haul Truck Tires Recycling

The disposal of large Off-the-Road (OTR) tires is an increasingly important concern. These tires can weigh up to 8,450 pounds with an overall diameter and width of approximately 140.7 inches and 45.1 inches respectively. OTR tires are used for mining vehicles such as haul trucks, wheel loaders, backhoes, graders, and trenchers.[1] These new tires cost between $38,000 and$50,000 each, depending on multiple factors including oil prices and the cyclical nature of the industry. Haul trucks contain six tires per vehicle, and mines replace these tires around every 9-12 months.[2] Statistics regarding discarded OTR tires are not provided by the industry as they are for other types of tires. Thus, it is difficult to approximate the number and location of waste OTR tires not only in individual states, but in the U.S. in general.[3] Currently, Minnesota and Arizona are the only states that place regulations and fees on OTR tires. However, Minnesota is the only state that actually tracks them.[3] The Rubber Manufacturers Association (RMA) roughly estimates that OTR tires account for 1% of scrap tires by number and 15% by weight. When the tires are replaced, the old tires can be discarded with the waste rock in stockpiles at the mining site but more often are landfilled without documentation by an appropriate agency due to lack of federal regulations. Their low density and hollow centers cause them to float to the top of landfills, disrupting the compactness.[4] Also, tires have a heat content 20-40% greater than that of coal which can be very dangerous on the rare occasions that tires catch fire in stockpiles.[5] Furthermore, burning tires release hazardous substances including pyrolytic oil, ash, and smoke, which contain carcinogens, heavy metals, and other toxic compounds.[6] Due to the large size of OTR tires, there are few facilities that can accommodate their recycling.[3] This leads to increased costs in transporting them to such sites. Transportation costs for a tire taken out of service can be up to $1000. In addition to the freight costs, recycling an OTR tire can cost up to$1500 because of their rugged construction compared to passenger tires which cost around 1 to recycle.[3] In response to the waste OTR tire problem, the Ball Hogs from the University of Arkansas have designed a solution that recycles OTR tires by using old tires as liners in ball mills for hard rock mines. Ball mills are large cylindrical vessels consisting of an outer shell, an inside liner and a load of metal balls. A motor turns the ball mill using a transmission system causing the metal balls to move in a cascading motion to grind the material fed into the ball mill. Ball mills require liners that are constructed from materials such as steel or rubber. For a 30 ft long ball mill with a Task #2 5 University of Arkansas 20 ft diameter, a hard rubber liner reinforced with steel can cost 150,000. These liners are replaced at least once a year, creating a substantial upkeep cost for these ball mills. Metal mines in Bolivia are already using tractor tires to line many ball mills. This technique has been effective for over twenty years. The high import costs of new liners and the low cost of labor has led many Bolivian metal processors to use truck and tractor tires as liners in their ball mills. This construction normally occurs on site using tools like handsaws, drills, torches and knives to cut up tires and manpower to mount these tire-made liners onto mills. However, this is not always the case in the U.S. where labor costs are much higher and the mills are generally larger. Many mines in the U.S. do not have the means to fabricate and install these liners on site; therefore, a third-party solution is proposed that will take a mine’s discarded tires and make ball mill liners out of them. The Ball Hogs’ solution provides an environmentally and economically feasible process of increasing the life of OTR tires beyond their typical use. This alternative would utilize the engineering and technology that makes these tires strong enough to hold a 400 ton truck. Mining companies would save yearly an average of $70,000 per ball mill liner replacement, and over 780,000 kg of CO2 per liner. Furthermore, mining companies would earn positive PR, goodwill, and tax breaks. We recommend all mining companies use their OTR tire treads as ball mill liners

Real-Time Data Processing With Lambda Architecture

Data has evolved immensely in recent years, in type, volume and velocity. There are several frameworks to handle the big data applications. The project focuses on the Lambda Architecture proposed by Marz and its application to obtain real-time data processing. The architecture is a solution that unites the benefits of the batch and stream processing techniques. Data can be historically processed with high precision and involved algorithms without loss of short-term information, alerts and insights. Lambda Architecture has an ability to serve a wide range of use cases and workloads that withstands hardware and human mistakes. The layered architecture enhances loose coupling and flexibility in the system. This a huge benefit that allows understanding the trade-offs and application of various tools and technologies across the layers. There has been an advancement in the approach of building the LA due to improvements in the underlying tools. The project demonstrates a simplified architecture for the LA that is maintainable

An empirical Bayes mixture method for effect size and false discovery rate estimation

Many statistical problems involve data from thousands of parallel cases. Each case has some associated effect size, and most cases will have no effect. It is often important to estimate the effect size and the local or tail-area false discovery rate for each case. Most current methods do this separately, and most are designed for normal data. This paper uses an empirical Bayes mixture model approach to estimate both quantities together for exponential family data. The proposed method yields simple, interpretable models that can still be used nonparametrically. It can also estimate an empirical null and incorporate it fully into the model. The method outperforms existing effect size and false discovery rate estimation procedures in normal data simulations; it nearly acheives the Bayes error for effect size estimation. The method is implemented in an R package (mixfdr), freely available from CRAN.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS276 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Eye in the Sky: Real-time Drone Surveillance System (DSS) for Violent Individuals Identification using ScatterNet Hybrid Deep Learning Network

Drone systems have been deployed by various law enforcement agencies to monitor hostiles, spy on foreign drug cartels, conduct border control operations, etc. This paper introduces a real-time drone surveillance system to identify violent individuals in public areas. The system first uses the Feature Pyramid Network to detect humans from aerial images. The image region with the human is used by the proposed ScatterNet Hybrid Deep Learning (SHDL) network for human pose estimation. The orientations between the limbs of the estimated pose are next used to identify the violent individuals. The proposed deep network can learn meaningful representations quickly using ScatterNet and structural priors with relatively fewer labeled examples. The system detects the violent individuals in real-time by processing the drone images in the cloud. This research also introduces the aerial violent individual dataset used for training the deep network which hopefully may encourage researchers interested in using deep learning for aerial surveillance. The pose estimation and violent individuals identification performance is compared with the state-of-the-art techniques.Comment: To Appear in the Efficient Deep Learning for Computer Vision (ECV) workshop at IEEE Computer Vision and Pattern Recognition (CVPR) 2018. Youtube demo at this: https://www.youtube.com/watch?v=zYypJPJipY

Quantum Critical Environment Assisted Quantum Magnetometer

A central qubit coupled to an Ising ring of $N$ qubits, operating close to a critical point is investigated as a potential precision quantum magnetometer for estimating an applied transverse magnetic field. We compute the Quantum Fisher information for the central, probe qubit with the Ising chain initialized in its ground state or in a thermal state. The non-unitary evolution of the central qubit due to its interaction with the surrounding Ising ring enhances the accuracy of the magnetic field measurement. Near the critical point of the ring, Heisenberg-like scaling of the precision in estimating the magnetic field is obtained when the ring is initialized in its ground state. However, for finite temperatures, the Heisenberg scaling is limited to lower ranges of $N$ values.Comment: 10 pages, 9 figure

On the interdependence of galaxy morphology, star formation, and environment in massive galaxies in the nearby Universe

Using multi-wavelength data, from UV-optical-near-mid IR, for $\sim$6000 galaxies in the local Universe, we study the dependence of star formation on the morphological T-types for massive galaxies ($\log M_*/M_\odot \geq 10$). We find that, early-type spirals (Sa-Sbc) and S0s predominate in the green valley, which is a transition zone between the star forming and quenched regions. Within the early-type spirals, as we move from Sa to Sbc spirals the fraction of green valley and quenched galaxies decreases, indicating the important role of the bulge in the quenching of galaxies. The fraction of early-type spirals decreases as we enter the green valley from the blue cloud, which coincides with the increase in the fraction of S0s. This points towards the morphological transformation of early-type spiral galaxies into S0s which can happen due to environmental effects such as ram-pressure stripping, galaxy harassment, or tidal interactions. We also find a second population of S0s which are actively star-forming and are present in all environments. Since morphological T-type, specific star formation rate (sSFR), and environmental density are all correlated with each other, we compute the partial correlation coefficient for each pair of parameters while keeping the third parameter as a control variable. We find that morphology most strongly correlates with sSFR, independent of the environment, while the other two correlations (morphology-density and sSFR-environment) are weaker. Thus, we conclude that, for massive galaxies in the local Universe, the physical processes that shape their morphology are also the ones that determine their star-forming state.Comment: 18 pages, 15 figures, and 9 tables. Accepted for publication in MNRA

Quantum Fisher and Skew information for Unruh accelerated Dirac qubit

We develop a Bloch vector representation of Unruh channel for a Dirac field mode. This is used to provide a unified, analytical treatment of quantum Fisher and Skew information for a qubit subjected to the Unruh channel, both in its pure form as well as in the presence of experimentally relevant external noise channels. The time evolution of Fisher and Skew information is studied along with the impact of external environment parameters such as temperature and squeezing. The external noises are modelled by both purely dephasing phase damping as well as the squeezed generalized amplitude damping channels. An interesting interplay between the external reservoir temperature and squeezing on the Fisher and Skew information is observed, in particular, for the action of the squeezed generalized amplitude damping channel. It is seen that for some regimes, squeezing can enhance the quantum information against the deteriorating influence of the ambient environment. Similar features are also observed for the analogous study of Skew information, highlighting the similar origin of the Fisher and Skew information.Comment: 12 pages, 10 figure