Hierarchical learning using deep optimum-path forest

Bag-of-Visual Words (BoVW) and deep learning techniques have been widely used in several domains, which include computer-assisted medical diagnoses. In this work, we are interested in developing tools for the automatic identification of Parkinson’s disease using machine learning and the concept of BoVW. The proposed approach concerns a hierarchical-based learning technique to design visual dictionaries through the Deep Optimum-Path Forest classifier. The proposed method was evaluated in six datasets derived from data collected from individuals when performing handwriting exams. Experimental results showed the potential of the technique, with robust achievements.     

Application of fuzzy image restoration in criminal investigation

The advancement of science and technology has a positive effect on the development of law disciplines. The development of algorithms and artificial intelligence also has a certain impact on judicial practice. Image restoration is a significant technique in image processing. It aims to objectively restore the content or quality of the original image from the degraded image. Image degradation is always generated in image transmission, such as distortion, blur. In modern video surveillance system, image restoration is significant for criminal investigation. However, image restoration based on conventional filter algorithms cannot achieve satisfactory performance. Thus, we first introduce the image restoration algorithms based on different degradation model. Then, we propose some applications of fuzzy image restoration in criminal investigation. We conduct experiments on both degraded images and videos and experimental results have shown the effectiveness of fuzzy image restoration applying to the criminal investigation.     

Clustering adaptive canonical correlations for high-dimensional multi-modal data

Multi-modal canonical correlation analysis (MCCA) is an important joint dimension reduction method and has been widely applied to clustering tasks of multi-modal data. MCCA-based clustering is usually dimension reduction of high-dimensional data followed by clustering of low-dimensional data. However, the two-stage clustering is difficult to ensure the adaptability of dimension reduction and clustering, which will affect the final clustering performance. To solve the issue, we propose a novel clustering adaptive multi-modal canonical correlations (CAMCCs) method, which constructs a unified optimization model of multi-modal correlation learning and clustering. The method not only realizes discriminant learning of correlation projection directions under unsupervised cases, but also is able to directly obtain class labels of multi-modal data. Additionally, the method also realizes out-of-sample extension in class labels. Solutions of CAMCCs are optimized by an iterative way, and we analyze its convergence. Extensive experimental results on various datasets have demonstrated the effectiveness of the method.     

Putting yourself in someone else's shoes: The impact of a location-based,collaborative role-playing game on behaviour

The goal of this study was to probe the effectiveness of a mobile game-based learning approach in modifying behavioural outcomes and competence. The experiment was set against the background of low rates of laymen providing CPR during sudden cardiac arrests. A post-test control group design was used to contrast and evaluate the effects of the two different types of learning. Two hundred two students were randomly assigned to two conditions, a game-based variant simulating an emergency situation (experimental group), and an instruction-based approach (control group). After the intervention participants completed a questionnaire assessing self-prediction, self-efficacy, attitude, subjective norm, empathy and competence. The largest arguably significant difference between the two groups showed in self-prediction and capacity beliefs. Results further revealed a positive relationship between self-prediction and the variables attitude and self-efficacy. The type of scenario did not translate into the other concepts we assessed, though, and results were inconclusive regarding the effectiveness of the type of learning scenario and CPR knowledge. We explain the small effect size partly by the experimental procedure and the design of the game intervention, which is discussed in the course of this article.     

Morphological and molecular identification of Liposcelis corrodens (Heymons, 1909) (Psocodea: Liposcelididae) as the first record from China

Liposcelis corrodens (Psocodea: Liposcelididae) is recognized as one species of common stored product pests, however, it has not been reported in China. In this study, we identified Liposcelis specimens collected from a maize reserve depot in China as Liposcelis corrodens based on morphological and molecular methods. The identification of L. corrodens and keys to the stored Liposcelis species of Group IID were reported. The mitochondrial gene cytochrome c oxidase I (mtDNA COI) of the specimens was sequenced and used as a DNA barcode to conduct molecular identification and phylogenetic analyses with other Liposcelis species of Group IID from different geographical populations. This is the first record of L. corrodens in China and it will be useful for the further studies of taxonomy and management of stored booklice.     

The relationship between cell phone use,academic performance,anxiety, and Satisfaction with Life in college students

While functional differences between today’s cell phones and traditional computers are becoming less clear, one difference remains plain – cell phones are almost always on-hand and allow users to connect with an array of services and networks at almost any time and any place. The Pew Center’s Internet and American Life Project suggests that college students are the most rapid adopters of cell phone technology and research is emerging which suggests high frequency cell phone use may be influencing their health and behavior. Thus, we investigated the relationships between total cell phone use (N = 496) and texting (N = 490) on Satisfaction with Life (SWL) in a large sample of college students. It was hypothesized that the relationship would be mediated by Academic Performance (GPA) and anxiety. Two separate path models indicated that the cell phone use and texting models had good overall fit. Cell phone use/texting was negatively related to GPA and positively related to anxiety; in turn, GPA was positively related to SWL while anxiety was negatively related to SWL. These findings add to the debate about student cell phone use, and how increased use may negatively impact academic performance, mental health, and subjective well-being or happiness.     

双重信息编码遗传算法在选址模型中的应用

在分析了一类配送中心选址问题的基础上,建立了该配送中心选址问题的数学模型。提出一种具有双重信息的遗传算法编码方案,并结合相应的遗传操作进行求寻优求解,最后通过实验证明了该方法的可行性和有效性。