Although organizational research posits various relationships between a firm’s slack resources and performance, findings to date have been ambiguous. The purpose of this study is to attempt to reconcile previous views of the relationship between slack resources and performance through employing empirical analysis based on survey data from 47 pharmaceutical and chemical firms in Henan Province of China. The results indicate that the relationship between slack resources and the performance is inverse N-shaped. Results provide evidence of a curvilinear relationship between slack resources and performance and broadly demonstrate that relationships differ based on industry circumstances and slack resources. Additionally, this study is the first to empirically identify an inverse N-shaped relationship between slack resources and performance, indicating that, in certain industry circumstances, little and much slack resources are bad for performance. Overall, results highlight the importance of additional research into intervening factors impacting the slack–performance relationship.

The proposed ubiquitous computing creates a new calculation model. Ubiquitous learning based on ubiquitous computing is the trend of current study theory. This paper introduces the concept of ubiquitous learning, analyzes and summarizes its thoughts and main characteristics, constructs the model of a ubiquitous learning environment. With the guidance of constructed ubiquitous learning environment model, we design the management system for electronic course-lattice, and use the metaphor of secretary naming the management system as electronic secretary.

A course project experiment plays a very important role in mastering a student embedded system software education. The paper gives the design and implementation solution to a Chinese character text editor for embedded system (CCTE for short), including requirement analysis, function design, task division, main process flow, Chinese character process, man-machine interface layout and test results. This course project can be used as a template for embedded system software experiment.

Activation of how and where arithmetic operations are displayed in the brain has been observed in various number-processing tasks. However, it remains poorly understood whether stabilized memory of Boolean rules are associated with background knowledge. The present study reviewed behavioral and imaging evidence demonstrating that Boolean problem-solving abilities depend on the core systems of number-processing. The core systems account for a mathematical cultural background, and serve as the foundation for sophisticated mathematical knowledge. The Ebbinghaus paradigm was used to investigate learning-induced changes by functional magnetic resonance imaging (fMRI) in a retrieval task of Boolean rules. Functional imaging data revealed a common activation pattern in the left inferior parietal lobule and left inferior frontal gyrus during all Boolean tasks, which has been used for number-processing processing in former studies. All other regional activations were tasks-specific and prominently distributed in the left thalamus, bilateral parahippocampal gyrus, bilateral occipital lobe, and other subcortices during contrasting stabilized memory retrieval of Boolean tasks and number-processing tasks. The present results largely verified previous studies suggesting that activation patterns due to number-processing appear to reflect a basic anatomical substrate of stability of Boolean rules memory, which are derived from a network originally related to the core systems of number-processing.

Autonomous learning plays an important role in raising students’ learning effect and innovation ability in university education. An effective e-learning environment is indispensable in autonomous learning. This paper studies a web based e-learning system and examines students’ autonomous learning ability and perceptions of e-learning taking students at University of Jinan in China as an example. In this paper, a web-based e-learning system for engineering graphics course is developed. The characteristics, the design idea and strategies fit for engineering graphics are introduced. The architecture and system composition are discussed. The key technologies and implementation methods of each module of system are described in detail. The students had experiences on the network learning system for two years. The practical application indicates that it can enhance students’ perceptual cognition to the teaching contents, increase their learning interests, develop their learning initiative and make them master the teaching contents more quickly.

We present a new criterion to determine the stability of polynomial with real coefficients. Combing with the existing results of the real and negative roots discrimination, we deduced the explicit conditions of stability for any real polynomial with a degree no more than four. Meanwhile, we discussed the problem of controls system stability and inertia of Bezout matrix as the applications of the criterion. A necessary and sufficient condition to determine the stability of the characteristic polynomial of the continuous time control systems was proposed. And also, we discussed a pathological case of the bilinear transformation, which can convert the stability analysis of a given discrete time system to the corresponding continuous time system, and brought forward an alternative one.

In this paper, a novel human visual sensitivity measurement approach is presented to assessment the visual quality of JPEG-coded images without reference image. The key features of human visual sensitivity (HVS) such as edge amplitude and length, background activity and luminance are extracted from sample images as input vectors. SVR-NN was used to search and approximate the functional relationship between HVS and mean opinion score (MOS). Then, the measuring of visual quality of JPEG-coded images was realized. Experimental results prove that it is easy to initialize the network structure and set parameters of SVR-NN. And the better generalization performance owned by SVR-NN can add the new features of the sample automatically. Compared with other image quality metrics, the experimental results of the proposed metric exhibit much higher correlation with perception character of HVS. And the role of HVS feature in image quality index is fully reflected.

In a network forensic system, there are huge amounts of data that should be processed, and the data contains redundant and noisy features causing slow training and testing processes, high resource consumption as well as poor detection rate. In this paper, a schema is proposed to reduce the data of the forensics using manifold learning. Manifold learning is a popular recent approach to nonlinear dimensionality reduction. Algorithms for this task are based on the idea that the dimensionality of many data sets is only artificially high. In this paper, we reduce the forensic data with manifold learning, and test the result of the reduced data.