
坦佩雷理工大学 (Tampere University of Technology, TUT) 是芬兰最著名的理工大学,世界一流大学。TUT在QS 2016/2017世界大学排名中位居319,在芬兰大学中位居第四 。TUT的科研与众多知名的跨国公司保持着密切的关系,也是芬兰培养创新和科技人才的主要中心之一。毗邻大学校园的是Hermia科技园,其中主要包括诺基亚、微软、因特尔等的研发中心。世界上第一个GSM电话就在TUT所在的Hervanta打出。华为也于2016年在TUT的校园成立了研发中心,依托TUT的技术和人才优势进行成像技术、计算机视觉和语音领域的研发 。TUT是两个按照基金会形式运作的芬兰的大学之一,接近其预算的50%是外来资金,这个指标使TUT在世界排名第十一位,在欧洲第四位 。
This paper studies the problem of computing the stochastic probability (shortest code length) of the encoded vectors containing cluster structure using Normalized Maximum Likelihood (NML) model. This is of great theoretical and practical importance in data clustering based on Minimum Description Length (MDL) principle, such as for estimating the best number of clusters and best cluster structure for the data. Straightforward computation of the shortest code length of the vector containing cluster structure based on the NML model requires polynomial time with respect to the size of the vector and number of clusters. We show that this is a tractable problem by introducing a recursion formula for the efficient computation of normalizing constant from the NML model. The time complexity of the new formula is linear opposed to previous polynomial time with respect to the size of the vector and number of clusters.
PurposeThis study aims to understand the shared use of academic workspaces from the staff's perspective. The paper first examines the factors and readiness for shared use of academic workspaces. Second, it illustrates nine possible work modes and users' preferences. Thereby, the paper discusses the access-based consumption of academic workspaces.Design/methodology/approachThe study focuses on a Finnish case university, where both qualitative and quantitative data were collected in 2022 during the campus development process. The qualitative findings use an inductive analysis of 18 semi-structured and 10 focus group interviews. The interviewees represent two faculties and all levels of academia. The quantitative results use descriptive statistical analyses of university-wide workplace preference survey data (n = 1,507 respondents).FindingsThe findings illustrate that the shared use of academic workspaces depends on: the sharing partner level, the time and length of use and the access options and spaces. The respondents were more ready to share workspaces with a closer community. The nine work modes present possible shared use options for workspaces. Half of the respondents chose the typical non-sharing mode and the other half chose less typical solutions. The results indicate a move towards preferences for more varied work modes.Originality/valueTo the best of the authors' knowledge, this study is one of the first to examine the spectrum of shared use of academic workspaces on campus, which typically are not viewed as shared and are also under-researched. It systematically maps the factors to benefit the user-oriented campus development processes.
Despite the growing use of biopolymers in automotive, packaging and structural applications, predictive modelling of their elastic–viscoplastic deformation remains limited. In this work, a micromechanically based constitutive model is proposed to describe the micro‑ to macroscopic behaviour of a semi‑crystalline PLA matrix reinforced with short hemp fibers. The formulation relies on a multiplicative split of the deformation gradient into elastic and viscoelastic–plastic parts, with elasticity governed by fiber and crystalline phases and time‑dependent deformation localized in the amorphous phase. High fiber content and strong fiber–matrix bonding enable the suppression of lattice crystalline anisotropy, leading to a compact model with a reduced number of internal variables. The model is calibrated and validated using uniaxial tensile tests on pellet‑extrusion 3D‑printed specimens with controlled porosity and plasticiser content, and reproduces nonlinear loading, unloading, creep and stress relaxation. In a second step, synthetic data generated by the constitutive model are used to train surrogate machine‑learning models, which are discussed as a perspective for accelerating long‑term simulations and parametric studies in forming applications.
The increasing penetration of inverter-based resources has led to a significant reduction in system inertia, resulting in faster and more pronounced frequency deviations in modern low-inertia power systems. In such environments, the dynamic behavior of electrical loads becomes increasingly important in shaping overall system frequency response. This paper presents an enhanced load model that incorporates load-side dynamics in addition to conventional static behavior, thereby augmenting the representation of load-frequency control (LFC) models. This improved formulation increases the accuracy of frequency response studies in power systems. A comparison between the proposed augmented model and the conventional LFC representation demonstrates that relying solely on static load modeling can lead to inaccurate results and potentially misleading conclusions. Therefore, accurate modeling of load-side dynamics is essential for reliable frequency stability assessment in modern power systems.
Metastable beta titanium alloys combine excellent mechanical properties with low density, and are therefore very attractive in many mechanically demanding applications. The high strength and hardness, however, cause several challenges in the machining of these materials, and the machining costs of titanium components can be significant compared to the overall costs of the component. The cutting conditions can be optimized using finite element simulations, leading to reduced machining costs and improved machining quality. However, the simulations of the rather complex machining processes need reliable material models. The models can only be generated when the mechanical behavior of the material is well understood. In this work, the mechanical response of Ti-15-3-3-3 alloy has been characterized in a wide range of strain rates and temperatures. The Johnson-Cook material model was fit to the measurement data, and the model was used to simulate orthogonal cutting of the material. The simulation results were further compared to cutting experiments at high cutting speeds. The current model is able to simulate the serrated chip formation frequently observed in machining of titanium alloys at high cutting speeds. Also, the simulated cutting forces match well with the experimentally obtained forces. However, the model needs to be further developed to match also the fine details of the chip, such as the chip curl and thickness of the individual serrations.