Towards Ideal Semantics for Analyzing Stream Reasoning

The rise of smart applications has drawn interest to logical reasoning over data streams. Recently, different query languages and stream processing/reasoning engines were proposed in different communities. However, due to a lack of theoretical foundations, the expressivity and semantics of these diverse approaches are given only informally. Towards clear specifications and means for analytic study, a formal framework is needed to define their semantics in precise terms. To this end, we present a first step towards an ideal semantics that allows for exact descriptions and comparisons of stream reasoning systems.Comment: International Workshop on Reactive Concepts in Knowledge Representation (ReactKnow 2014), co-located with the 21st European Conference on Artificial Intelligence (ECAI 2014). Proceedings of the International Workshop on Reactive Concepts in Knowledge Representation (ReactKnow 2014), pages 17-22, technical report, ISSN 1430-3701, Leipzig University, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-150562 2014,

Multi-task Image Classification via Collaborative, Hierarchical Spike-and-Slab Priors

Promising results have been achieved in image classification problems by exploiting the discriminative power of sparse representations for classification (SRC). Recently, it has been shown that the use of \emph{class-specific} spike-and-slab priors in conjunction with the class-specific dictionaries from SRC is particularly effective in low training scenarios. As a logical extension, we build on this framework for multitask scenarios, wherein multiple representations of the same physical phenomena are available. We experimentally demonstrate the benefits of mining joint information from different camera views for multi-view face recognition.Comment: Accepted to International Conference in Image Processing (ICIP) 201

Impact of Farmers’ Adoption of Good Agricultural Products on Total Factor Productivity Change: The Case of Grape and Apple Production in Vietnam

Development of agricultural production with Good Agricultural Practices (GAP) standards is an objective trend of sustainable agriculture. This research employed data envelopment analysis (DEA) and ordinary least square (OLS) Regression to quantify impact of farmers’ adoption of GAP on the Total Factor Productivity Change (TFPCH) in investment in grape and apple production in Ninh Thuan of Vietnam.  The results show that farmers’ adoption of GAP positively influenced on increase on total factor productivity. Therefore, it is necessary to find-out solutions to speed up farmers’ investment in development of agriculture with GAP standards. Keywords: GAP, TFPCH, impact, farmer household, Vietna

A neurodynamic approach for a class of pseudoconvex semivectorial bilevel optimization problem

The article proposes an exact approach to find the global solution of a nonconvex semivectorial bilevel optimization problem, where the objective functions at each level are pseudoconvex, and the constraints are quasiconvex. Due to its non-convexity, this problem is challenging, but it attracts more and more interest because of its practical applications. The algorithm is developed based on monotonic optimization combined with a recent neurodynamic approach, where the solution set of the lower-level problem is inner approximated by copolyblocks in outcome space. From that, the upper-level problem is solved using the branch-and-bound method. Finding the bounds is converted to pseudoconvex programming problems, which are solved using the neurodynamic method. The algorithm's convergence is proved, and computational experiments are implemented to demonstrate the accuracy of the proposed approach

Simulation of several CNT based macrostructures using slip-link model and discrete element method

The CNT macrostructures including membranes start by forming web on which CNT fibers are oriented along the web axis, some of them are parallel and others are poorly aligned or coiled. Since the CNT web impacts on the properties of derived macrostructures, the simulation of CNT membranes attracted significant attentions. The scanning electron microscopy analysis of CNT webs showed that CNT fibers entangle together. This entanglement is a key factor for the formation of CNT macrostructures because it allows the array of parallel fibers to unfold continuously into CNT networks. The work focuses on modelling the interconnection between CNT fibers within membranes and also other macro-structures and then analyzing mechanical properties of them

Hierarchical Sparse and Collaborative Low-Rank Representation for Emotion Recognition

In this paper, we design a Collaborative-Hierarchical Sparse and Low-Rank (C-HiSLR) model that is natural for recognizing human emotion in visual data. Previous attempts require explicit expression components, which are often unavailable and difficult to recover. Instead, our model exploits the lowrank property over expressive facial frames and rescue inexact sparse representations by incorporating group sparsity. For the CK+ dataset, C-HiSLR on raw expressive faces performs as competitive as the Sparse Representation based Classification (SRC) applied on manually prepared emotions. C-HiSLR performs even better than SRC in terms of true positive rate.Comment: 5 pages, 5 figures; accepted to IEEE ICASSP 2015; programs available at https://github.com/eglxiang/icassp15_emotion

Insiders, Outsiders and Performance of Vietnamese Firms

The consensus in the finance literature is that a large proportion of inside ownership (defined as greater than 5% share ownership by non-institutional holders, managerial holdings, founding family holdings, cross-shareholdings by affiliated firms and ownership by creditors) tends to be associated with more unsatisfactory performance (as measured by ROE or ROA) when compared to firms with lower inside ownership, all else equal. However, this need not be the case if insiders act as monitors of the firm and have the same interest in returns as outsiders.  Ownership structure and firm level financial performance have not been widely studied in Vietnam.  Using data from 729 listed firms in Vietnam for 2018, we test the hypothesis that greater insider ownership has a negative impact on firm performance. We found that Vietnam's insiders play a monitoring role, exercising their relative power to ensure the firm's profitable functioning. These findings are inconsistent with research on Japanese groupings, as well as other findings. The Vietnamese stock market does not appear to be negatively affected by insider influence; indeed, insiders appear to act as positive monitors.