High energy-storage performance of lead-free AgNbO3 antiferroelectric ceramics fabricated via a facile approach

AgNbO₃ lead free AFE ceramics are considered as one of the promising alternatives to energy storage applications. In the majority of studies concerning the preparation of AgNbO₃ AFE ceramics, an oxygen atmosphere is required to achieve high performance, increasing the complexity of the fabrication process. Herein, a facile approach to preparing AgNbO₃ ceramics in the ambient air was reported, in which the AgNbO₃ ultrafine powder with stable perovskite structure was synthesized by hydrothermal method instead of the conventional ball milling process, leading to a lower temperature of phase formation and thus smaller grain size. The resulting ceramics sintered at 940 °C displayed high breakdown strength (216 kV/cm) and a recoverable energy density of 3.26 J/cm³ with efficiency of 53.5 %. Also, the high thermal stability of recoverable energy density (with minimal variation of ≤20 %) and efficiency (≤ 10 %) over 30–150℃, enables AgNbO₃ ceramics achieved to be a promising candidate for energy storage applications.     

Polynomial filtering for nonlinear stochastic systems with state‐ and disturbance‐dependent noises

This article is concerned with the polynomial filtering problem for a class of nonlinear stochastic systems governed by the Itô differential equation. The system under investigation involves polynomial nonlinearities, unknown‐but‐bounded disturbances, and state‐ and disturbance‐dependent noises ((x,d)‐dependent noises for short). By expanding the polynomial nonlinear functions in Taylor series around the state estimate, a new polynomial filter design method is developed with hope to reduce the conservatism of the existing results. In virtue of stochastic analysis and inequality technique, sufficient conditions in terms of parameter‐dependent linear matrix inequalities (PDLMIs) are derived to guarantee that the estimation error system is input‐to‐state stable in probability. Moreover, the desired polynomial matrix can be obtained by solving the PDLMIs via the sum‐of‐squares approach. The effectiveness and applicability of the proposed method are illustrated by two numerical examples with one concerning the permanent magnet synchronous motor.     

Incomplete analytic hierarchy process with minimum weighted ordinal violations

ABSTRACT

Incomplete pairwise comparison matrices offer a natural way of expressing preferences in decision-making processes. Although ordinal information is crucial, there is a bias in the literature: cardinal models dominate. Ordinal models usually yield nonunique solutions; therefore, an approach blending ordinal and cardinal information is needed. In this work, we consider two cascading problems: first, we compute ordinal preferences, maximizing an index that combines ordinal and cardinal information; then, we obtain a cardinal ranking by enforcing ordinal constraints. Notably, we provide a sufficient condition (that is likely to be satisfied in practical cases) for the first problem to admit a unique solution and we develop a provably polynomial-time algorithm to compute it. The effectiveness of the proposed method is analyzed and compared with respect to other approaches and criteria at the state of the art.     

The impact of the ICT4D project on sustainable rural development using a capability approach: Evidence from Bangladesh

Information and Communication Technology for Development (ICT4D) projects have shown a great promises in recent years. However, simply materializing of ICT4D projects is not enough for minimizing the prevalent digital divide in rural areas in developing countries. For the success of an Information and Communication Technology (ICT) intervention, it is important to consider the capabilities of users, who are responsible for converting ICT resources into outcome. While most of the ICT-related studies are focused on the adoption of actual technologies and influences of different internal and external factors on intervention outcomes, very few studies are focused on evaluating intervention outcomes and redesigning intervention strategies. In this study, I opted for using a conceptual framework following the Capability Approach that simultaneously identifies the influence factors for intervention outcome as well as evaluates the outcome based on Noble Laureate Amartya Sen’s five freedoms concept. A qualitative technique has been chosen to conduct the study. As part of the impact evaluation of an ICT4D intervention, a project known as Union Digital Centres (UDCs) in Bangladesh was selected. A total of ten themes are identified indicating that the outcome of the intervention is contributing to socio-economic and human development. However, the study has revealed that lack of capabilities of users (e.g. prior knowledge and financial inability) bar the UDC programs to fulfill their goals at highest level. This study would practically help the UDC policy makers to adjust the UDC intervention design by addressing the shortcomings of the users to yield higher UDC program outcome. Additionally, this study theoretically contributes in ICT adoption literature by showing that there is a mutual influence between users’ capabilities and ICT-related project outcomes. Finally, using specific case study (ICT4D project in Bangladesh), this study contextualizes Amartya Sen’s five freedoms concept in the ICT-specific context.     

浅谈在矿山供电课程中如何高效利用慕课mooc和混合式教学

伴随着人类社会的向前推进,信息技术已经渗透到我们生活的方方面面,深刻地改变了教育事业,慕课就是在信息时代下诞生的一种新兴教学工具。但是,如何利用好这一工具却仍然是个值得研究的课题。本文从慕课的内涵出发,分析了将混合式教学模式应用于慕课这一教学平台的重要意义。并且,就混合式教学模式在慕课平台中的应用进行了分析。希望能够给相关工作者以一定的启发。     

Analysis and optimisation of particle mixing performance in fluid phase resonance mixers based on Euler/Lagrange calculations

A novel mixing principle utilising oscillating liquid columns was analysed numerically with regard to particle dispersion characteristics. For producing fluid oscillations a pipe (diameter 100 mm) was immersed centrally into a vessel (diameter 450 mm) filled with liquid (filling height 700 mm) and periodically pressurised (frequency 1.2 Hz). The outlet geometry of the central pipe, just ending near the vessel bottom, has a strong effect on mixing and was optimised in this study. The principle of a FPR-mixer does not require rotating stirrers and in the turbulent regime it has power numbers comparable to propellers. The numerical calculations were conducted by a Euler/Lagrange approach neglecting two-way coupling as well as inter-particle collisions for clarity in order to only focus on the effect of interfacial forces on particle dispersion. The continuous phase was calculated in an unsteady way based on the Reynolds-averaged equations combined with the k-ω-SST (shear stress transport) turbulence model. Lagrangian tracking was conducted considering all relevant forces; drag, gravity/buoyancy, fluid inertia, added mass, Basset force and transverse lift forces due to shear and particle rotation. The importance of these forces was analysed with respect to the turbulent particle Stokes number (considered range 0.004 < St < 10.0) and particle/liquid density ratio (i.e. 1.05, 1.5 and 2.5). Finally, the significance of Basset force and shear-rotation lift force (i.e. Magnus effect) on the dispersion process was quantified by mixing parameters.     

A deep neural network based classifier for brain tumor diagnosis

Classification process plays a key role in diagnosing brain tumors. Earlier research works are intended for identifying brain tumors using different classification techniques. However, the False Alarm Rates (FARs) of existing classification techniques are high. To improve the early-stage brain tumor diagnosis via classification the Weighted Correlation Feature Selection Based Iterative Bayesian Multivariate Deep Neural Learning (WCFS-IBMDNL) technique is proposed in this work. The WCFS-IBMDNL algorithm considers medical dataset for classifying the brain tumor diagnosis at an early stage. At first, the WCFS-IBMDNL technique performs Weighted Correlation-Based Feature Selection (WC-FS) by selecting subsets of medical features that are relevant for classification of brain tumors. After completing the feature selection process, the WCFS-IBMDNL technique uses Iterative Bayesian Multivariate Deep Neural Network (IBMDNN) classifier for reducing the misclassification error rate of brain tumor identification. The WCFS-IBMDNL technique was evaluated in JAVA language using Disease Diagnosis Rate (DDR), Disease Diagnosis Time (DDT), and FAR parameter through the epileptic seizure recognition dataset.     

一种改进的最小二乘回归子空间分割方法

最小二乘回归(LSR)算法是一种常见的子空间分割方法，由于LSR具有解析解，因此它的聚类性能较高。然而LSR算法是应用谱聚类方法聚类数据，谱聚类方法初始化聚类中心是随机的，会影响后面的聚类效果。针对这一问题，提出一种基于聚类中心局部密度和距离这2个特点的改进的LSR算法（LSR-DC）。在Extended Yale B数据集上进行实验，结果表明，该算法有较高的聚类精度，具有一定的鲁棒性，优于现有LSR等子空间分割方法。     

Value drivers of blockchain technology: A case study of blockchain-enabled online community

There is growing recognition that blockchain technology has significant potential to alter how organizations and people work and communicate. However, theoretical guidance concerning how organizations leverage blockchain technology to enhance value creation for users is still limited. Grounded in the socio-technical perspective and leveraging the rich data obtained from case analyses of blockchain-enabled online communities, this paper develops a theoretical model to identify the core value drivers that blockchain enables for online communities. The core value drivers include: a reputation-value system, data ownership mechanisms, and verification & tracking mechanisms. Our findings suggest that these three value drivers enhance value creation of online communities by motivating participation and protecting contributions.