Energy Evolution in Time-Dependent Harmonic Oscillator

The theory of adiabatic invariants has a long history, and very important implications and applications in many different branches of physics, classically and quantally, but is rarely founded on rigorous results. Here we treat the general time-dependent one-dimensional harmonic oscillator, whose Newton equation q + ω²(t)q = 0 cannot be solved in general. We follow the time-evolution of an initial ensemble of phase points with sharply defined energy E_o at time t = 0 and calculate rigorously the distribution of energy E₁ after time t = T, which is fully (all moments, including the variance μ²) determined by the first moment Ē₁. For example, μ² = E²_o[(Ē₁/E_o)² — (ω(T)/ω(0))²]/2, and all higher even moments are powers of μ², whilst the odd ones vanish identically. This distribution function does not depend on any further details of the function ω(t) and is in this sense universal. In ideal adiabaticity Ē₁ = ω(T)E_o/ω(0), and the variance μ,² is zero, whilst for finite T we calculate Ē₁, and μ² for the general case using exact WKB-theory to all orders. We prove that if ω(t)is of class ^m (all derivatives up to and including the order m are continuous) μ, ∝ T^{−(m + 1)}) whilst for the class °° it is known to be exponential μ ∝ exp(—aT).     

Delivery of nutrients and seston from the Muskegon River Watershed to near shore Lake Michigan

Drowned river mouth lakes are major features of coastal Great Lakes habitats and may influence nutrient and organic matter contributions from watersheds to near shore coastal zones. In May through October 2003, we measured loads of nutrients, surficial sediment, and seston to track the delivery of riverine-derived materials from the lower Muskegon River Watershed (MRW) into the near shore area of southeast Lake Michigan. Nutrient flux data indicated that seasonal loads of 1800 metric tons (MT) of particulate organic carbon, 3400 MT of dissolved organic carbon, and 24 MT of total phosphorus were discharged from the lower Muskegon River, with approximately 33% of TP load and 53% of the POC load intercepted within the drowned river mouth terminus, Muskegon Lake. Carbon: phosphorus molar ratios of seston in Muskegon River (C:P = 187) and Muskegon Lake (C:P = 176) were lower than in Lake Michigan (C:P = 334), indicating phosphorus limitation of phytoplankton in near shore Lake Michigan. Isotopic signatures of seston collected in Muskegon Lake were depleted in δ¹³C (− 30.8 ± 1.6‰) relative to the isotope signatures of seston from Lake Michigan (− 26.2 ± 1.3‰) or the mouth of the Muskegon River (− 28.1 ± 0.5‰), likely due to the presence of biogenic methane in Muskegon Lake. Seston δ¹⁵N increased on a strong east-to-west gradient within Muskegon Lake, indicating significant microbial processing of nutrients. The extent of nutrient uptake in Muskegon Lake altered the chemical and isotopic characterization of seston flowing into Lake Michigan from Muskegon River.     

A novel split-and-merge algorithm for hierarchical clustering of Gaussian mixture models

The paper presents a novel split-and-merge algorithm for hierarchical clustering of Gaussian mixture models, which tends to improve on the local optimal solution determined by the initial constellation. It is initialized by local optimal parameters obtained by using a baseline approach similar to k-means, and it tends to approach more closely to the global optimum of the target clustering function, by iteratively splitting and merging the clusters of Gaussian components obtained as the output of the baseline algorithm. The algorithm is further improved by introducing model selection in order to obtain the best possible trade-off between recognition accuracy and computational load in a Gaussian selection task applied within an actual recognition system. The proposed method is tested both on artificial data and in the framework of Gaussian selection performed within a real continuous speech recognition system, and in both cases an improvement over the baseline method has been observed.     

An improved two-party identity-based authenticated key agreement protocol using pairings

Two-party authenticated key agreement protocols using pairings have gained much attention in the cryptographic community. Several protocols of this type where proposed in the past of which many were found to be flawed. This resulted in attacks or the inability to conform to security attributes. In this paper, we propose an efficient identity-based authenticated key agreement protocol employing pairings which employs a variant of a signature scheme and conforms to security attributes. Additionally, existing competitive and the proposed protocol are compared regarding efficiency and security. The criteria for efficiency are defined in this paper, whereas the criteria for security are defined by the fulfilment of security attributes from literature.     

Tracking of moving interfaces in sedimentation processes using electrical impedance tomography

Sedimentation monitoring is widely used to control and optimize industrial processes. In this paper we propose a novel computational method for sedimentation monitoring using electrical impedance tomography (EIT). EIT measurements consist of electric current and voltage measurements that are made on the surface of the sedimentation tank and therefore they do not interfere with the sedimentation process. The proposed computational method is based on shape estimation and state estimation formulation of the EIT problem. The sedimentation is parameterized by the locations of the phase interfaces and conductivities of the phase layers. Three different evolution models for the state parameters are considered and the state estimates are computed using the extended Kalman filter algorithm. The performance of the method and the models are evaluated using simulated data from a six electrode EIT measurement configuration. From the results a promising performance of the method can be seen.     

Use of the Roughness Parameters Ssk and Sku to Control Friction—A Method for Designing Surface Texturing

The aim of this work was to show that with the use of the surface roughness parameters S_sk and S_ku we can predict tribological behavior of contact surfaces and use these parameters to plan surface texturing. This article presents a continuation of our research on virtual texturing and experimental work on surface textures in the form of channels. For this investigation, steel samples were laser surface textured in the shape of dimples with different spacings between the dimples and different dimple depths. The experimental results confirmed that the parameters S_sk and S_ku can be used to design the surface texturing, where a higher value of S_ku and more negative S_sk lead to lower friction.     

Solving partner selection problem in cyber-physical production networks using the HUMANT algorithm

The idea of non-hierarchical production networks consisting of autonomous enterprises has been present in scientific community for more than 20 years. Although some global corporations are using their own production networks across continents, they are not similar to the original idea of non-hierarchical production networks in many aspects. It seems that this idea waited for production systems to acquire proper information and communications technology (ICT) or new industrial platforms, like Industry 4.0. The result is a new type of production network called Cyber-Physical Production Network (CPPN). The CPPN is, from ICT point of view, ready to act as non-hierarchical production networks consisting of autonomous production systems with many automated processes. One of the most important processes of the CPPN is a selection of optimal partners (enterprises) to be part of a new virtual enterprise, created inside production network. An optimisation problem emerges in this process, and it is called Partner Selection Problem (PSP). It is non-polynomial-hard combinatorial problem. Since metaheuristic algorithms are well-proven in solving that kind of problem, a specially designed metaheuristic algorithm derived from ant colony optimisation and named the HUMANT (HUManoid ANT) algorithm is used in this paper. It is multi-objective optimisation algorithm that successfully solves different instances of PSP with two, three, four or more objectives.