Deep Neural Networks - A Brief History

Introduction to deep neural networks and their history.Comment: 14 pages, 14 figure

The Potential and Challenges of CAD with Equational Constraints for SC-Square

Cylindrical algebraic decomposition (CAD) is a core algorithm within Symbolic Computation, particularly for quantifier elimination over the reals and polynomial systems solving more generally. It is now finding increased application as a decision procedure for Satisfiability Modulo Theories (SMT) solvers when working with non-linear real arithmetic. We discuss the potentials from increased focus on the logical structure of the input brought by the SMT applications and SC-Square project, particularly the presence of equational constraints. We also highlight the challenges for exploiting these: primitivity restrictions, well-orientedness questions, and the prospect of incrementality.Comment: Accepted into proceedings of MACIS 201

Characterization of the disturbed zone in a large rock excavation for the Three Gorges Project

Excavation in a rock mass leads to the perturbation of the stress regime, often creating a stress-relieved, locally weakened zone known as the disturbed zone. This paper presents the results of in situ studies that were carried out both in the central rock barrier (or separation block) between the shiplift and the temporary shiplock and in the northern slope of the permanent shiplock of the Three Gorges Project. The vertical extent of the disturbed zone was determined jointly by cross-hole seismic wave penetration testing and borehole elastic modulus testing, and the horizontal extent was assessed by monitoring and evaluating the deformation characteristics. Compared with the undisturbed rock mass, the P-wave velocity of the disturbed zone was reduced by 34-38% and the borehole elastic modulus by 12-31%. The reductions were caused by the opening of primary structural planes or the extension of apertures due to local sliding along the structural planes. In the disturbed zone, no newly formed fractured planes were found. The observed disturbed zone was compared with the tensile stress zones and the shear-damaged zones calculated by the finite element method. A rock reinforcement scheme was recommended and implemented.published_or_final_versio

Beneficiation of recycled process water at DRDGOLD's ERGO plant, and its effect on gold recovery

To conserve fresh water resources and comply with environmental regulations, DRDGOLD, a South African gold producer re-treating surface tailings, has transitioned to a fully closed water circulation system. Consequently, the accumulation of contaminants, as well as addition of reagents, has led to changes in water composition that have compromised leach performance and overall gold recovery. A two-sample t-test confirmed a significant difference in gold recoveries between the use of Rand Water, which was used as a benchmark, and untreated process water. Atomic absorption analysis of ERGO’s process water, confirmed the presence of iron, nickel, zinc, and manganese. A study of the effect of the identified contaminants on gold recovery showed that iron, nickel, and zinc have the largest negative effect on gold recovery, with iron and nickel being more detrimental than zinc. Sulphates were shown to have a possible passivation effect, which also influenced gold recoveries, although to a lesser extent than the heavy metals. Calcium, when present in excess, had a positive influence on gold recovery indicating the possible formation of a calcium aurocyanide complex. Lime softening successfully reduced the heavy metal and sulphate concentrations, and the gold recoveries obtained with the treated process water were similar to those as achieved with Rand Water

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors

"Case files from the University of Florida: When an Earache is more than an Earache": A case report

Brain abscess is not a common diagnosis as there are only approximately 2000 cases reported each year in the United States. There are three main routes of access to the brain including contiguous infection from the oropharynx, direct implantation and hematogenously. We present a case of brain abscess in a child who had multiple visits for ear pain to various physicians including pediatricians and to emergency departments. Additionally, the microbiology of brain abscesses is briefly discussed, as is treatment