Residual coal exploitation and its impact on sustainable development of the coal industry in China

Although China owns large coal reserves, it now faces the problem of depletion of its coal resources in advance. The coal-based energy mix in China will not change in the short term, and a means of delaying the coal resources depletion is therefore urgently required. The residual coal was exploited first with a lower recovery percentage and was evaluated as commercially valuable damaged coal. This approach is in comparison to past evaluations when the residual coal was allocated as exploitation losses. Coal recovery rates, the calculation method of residual coal reserves and statistics of its mines in China were given. On this basis, a discussion concerning the impacts on the delay of China's coal depletion, development of coal exploitation and sustainable developments, as well as technologies and relevant policies, were presented. It is considered that the exploitation of residual coal can effectively delay China's coal depletion, inhibit the construction of new mines, redress the imbalance between supply and demand of coal in eastern China, improve the mining area environment and guarantee social stability. The Chinese government supports the exploitation technologies of residual coal. Hence, exploiting residual coal is of considerable importance in sustainable development of the coal industry in China.     

改进的多层感知机在客户流失预测中的应用

针对在传统的客户流失预测数据预处理中，使用one-hot编码处理离散属性导致数据维度增加及数据过于稀疏的问题，提出了两种基于多层感知机的改进后的客户流失预测模型。其主要思想是分别使用堆叠自编码器和实体嵌入两种方法对多层感知机进行改进，通过将离散属性的高维编码数据向低维空间映射，有效地减少了one-hot编码产生的稀疏数据，增加了离散属性值之间的关联度。在对两份公开的数据集进行交叉验证后的实验结果表明，改进后的模型既有效地提高了预测的准确度，又维持了传统多层感知机模型在并行化计算方面的优势。     

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.     

Delineating the dimensions of social support on social networking sites and their effects: A comparative model

Social networking sites (SNSs) allow users to connect with each other by overcoming geographical and temporal boundaries and thus empower people to search for social support from online. Social support has been considered a key social value that online users can obtain from SNSs. However, few studies have systematically investigated social support in such a context. Motivated to address this gap, we have developed an advanced and theoretical framework to delineate social support on SNSs by clearly revealing the dimensions of online social support on SNSs and examining their effects on users' commitment and SNS continuance. Further, we introduce gender as a key moderator and explain in theory how differently men and women perceive the importance of the dimensions in evaluating online social support over SNSs. Our research results indicate that the identified three dimensions (informational support, emotional support, and network management) are important components of the online social support on SNSs, which is positively associated with commitment and continuance. In addition, the weight of each dimension in the evaluation of online social support varies by gender. This study is among the very first to explore online social support in the context of SNS and its effects, and has rich theoretical and practical implications.     

Ways to open innovation: Main agents and sources in the Portuguese case

Facing increasing open innovation trends, Portuguese enterprises are considering the related processes and impacts. Thus, this work aims to identify the sectors whose enterprises most engage in open innovation (such as cooperation on this issue) and which sources/agents are most used. This is analyzed by sector and type of innovation as an interesting way of differentiation for better open innovation strategy delineation. Using the data from the Community Innovation Survey (CIS-2012), it first appraises the nature of the innovation process, either cooperative or firm-based, as the starting level of analysis. Then, it differentiates the results by sector illustrating which cooperation sources/agents are most used (scope) and relative intensity of use (scale). This is important to assess levels of openness and related factors. Results show that main innovating sectors in Portugal are of three types: research-based, knowledge-based and service-based. They reveal an increasing focus on knowledge and services, trends that have been leading to more active openness towards innovation. For instance, health and construction are increasing their openness for innovating and internationalizing processes. However, Portuguese innovation is still more firm-based (in-house) than cooperation-based, especially concerning new products' launching. This work and future analyzes around it can contribute to encourage the open innovation strategy in more sectors of the economy as an easy and effective way to cope with rapid trends and changes.     

Capacity planning for packaging industry

This paper presents a capacity planning system (CPS) to generate a feasible production schedule, improve production efficiency, and avoid overcapacity for the packaging industry. CPS applies the concept of workload leveling and finite capacity planning to assign orders to production lines by considering several production characteristics such as drying time, quantity splitting owing to the cutting pattern of the product type, and the variability of machine capacity threshold. CPS consists of five modules, namely, order treatment module (OTM), order priority module (OPM), lot release module (LRM), workload accumulation module (WAM), and workload balance module (WBM). The experimental design is used to evaluate the effectiveness and efficiency of the proposed CPS with five factors (number of orders, order size, order size variance, order priority, and balance policy) with various levels and three response variables, namely, machine workload balance, order due date deviation, and lateness. Moreover, this result extends into finding the best settings of order priority and balance policy to generate the best favorable responses under the given three environment factors.     

Adapting the Technology Acceptance Model to evaluate the innovative potential of e-learning systems

This paper describes an experience where the Technology Acceptance Model (TAM) has been adapted for use in the evaluation of methodological and technological innovations determined by the introduction of a new e-learning system in an Italian online university. While the original TAM allows one to assess acceptance and adoption of a new technology, in this case there was also a need to consider all the phases of use of the system (course design, running and evaluation), all the users of the system (students, teachers and e-learning management), and all the system’s components (the e-learning platform, the learning resources and mostly the underlying pedagogical approach). The resulting model, which is an extension of the original TAM, is a three-dimensional one, with three aspects to be considered on each axis (phases of use, users and components). For each of the 27 combinations of these aspects, indicators of usefulness and ease-of-use have been identified. When available, data concerning actual use (derived from the tracking functions of the platform) and effectiveness (based on teachers’ adoption of new tools and students’ learning outcomes) have also been used to complement the data.     

Electric vehicle technology in China: An exploratory patent analysis

Currently, the electric vehicle (EV) technology is of great interest in China and around the world. This paper first conducts a comprehensive review of China's EV policies and the development of China's EV technology, and then analyzes the domestic performances of China's EV technology and its international competitiveness by adopting the recently developed concept of transnational patents. The results show an outstanding performance for China's EV technology in the domestic market, but a relatively poor performance in the international markets. Finally, several main factors causing the inconsistent performance of China's EV technology are proposed and discussed.     

A composite spatio-temporal modeling approach for age invariant face recognition

In this research we propose a novel method of face recognition based on texture and shape information. Age invariant face recognition enables matching of an image obtained at a given point in time against an image of the same individual obtained at an earlier point in time and thus has important applications, notably in law enforcement. We investigate various types of models built on different levels of data granularity. At the global level a model is built on training data that encompasses the entire set of available individuals, whereas at the local level, data from homogeneous sub-populations is used and finally at the individual level a personalized model is built for each individual. We narrow down the search space by dividing the whole database into subspaces for improving recognition time. We use a two-phased process for age invariant face recognition. In the first phase we identify the correct subspace by using a probabilistic method, and in the second phase we find the probe image within that subspace. Finally, we use a decision tree approach to combine models built from shape and texture features. Our empirical results show that the local and personalized models perform best when rated on both Rank-1 accuracy and recognition time.     

Another brick in the Facebook wall – How personality traits relate to the content of status updates

Status updates represent a new form of one-to-many communication which is widely used among members of social networking sites (SNS). The present study investigated the question of who in particular uses the self-presentational opportunities of this feature and which users engage in riskier self-disclosures than others. Combining questionnaire and content analysis, we related self-reports on users’ personality traits (extraversion, narcissism, self-efficacy, need to belong, need for popularity) to the actual use of Facebook status updates. Results showed that higher degrees of narcissism led to deeper self-disclosures and more self-promotional content within these messages. Users with higher need to belong disclosed more intimate information in status updates, while perceived efficacy of self-presentation was negatively related to the mass suitability of postings. Findings extend prior research on personality and SNS usage with regard to dynamic features and content differences in online self-presentation.