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The interface is a crucial element in component-based software, enabling the linkage of distinct components to facilitate interaction. Defects within the interface can significantly impact the overall trustworthiness of the system. Therefore, it is essential to assess the interface trustworthiness based on a defect-centric approach. This paper introduces a novel model for evaluating interface trustworthiness, anchored in defect analysis. First, the defect types are formalized based on interface specifications. Then, the comprehensive weight allocation method is established to characterize the importance degree of each interface defect type by combining the G1 and CRITIC methods. Subsequently, the attributes of the interface are evaluated by defect value analysis, and the trustworthiness measurement model of the interface is proposed based on these attributes. Furthermore, to evaluate the trustworthiness of the whole system, the trustworthiness measure models under different combination structure of components are established. Finally, the model’s’ applicability is demonstrated through an illustrative example. This trustworthiness evaluation from the interface view can guide interface designers to obtain high-quality interfaces and improve the trustworthiness of the entire software.

Traditional human–computer interaction devices such as the keyboard and mouse become ineffective for an effective interaction with the virtual environment applications because the 3D applications need a new interaction device. An efficient human interaction with the modern virtual environments requires more natural devices. Among them the "Hand Gesture" human–computer interaction modality has recently become of major interest. The main objective of gesture recognition research is to build a system which can recognize human gestures and utilize them to control an application. One of the drawbacks of present gesture recognition systems is being application-dependent which makes it difficult to transfer one gesture control interface into multiple applications. This paper focuses on designing a hand gesture recognition system which is vocabulary independent as well as adaptable to multiple applications. This makes the proposed system vocabulary independent and application independent. The designed system is comprised of the different processing steps like detection, segmentation, tracking, recognition, etc. Vocabulary independence has been incorporated in the proposed system with the help of a robust gesture mapping module that allows the user for cognitive mapping of different gestures to the same command and vice versa. For performance analysis of the proposed system accuracy, recognition rate and command response time have been compared. These parameters have been considered because they analyze the vital impact on the performance of the proposed vocabulary and application-independent hand gesture recognition system.

Although verbal and numerical scales are commonly used in the Analytic Hierarchy Process for pairwise comparisons, new experiments with computer-based visual tools confirm that ratio preferences can be effectively and efficiently elicited using adjustable visual tools and simultaneous comparisons, as well. Such an improved approach shows promise in the design of a new class of multi-criteria decision support system both for individual and group decisions.

With the increasing role of computing devices, facilitating natural human computer interaction (HCI) will have a positive impact on their usage and acceptance as a whole. For long time, research on HCI has been restricted to techniques based on the use of keyboard, mouse, etc. Recently, this paradigm has changed. Techniques such as vision, sound, speech recognition allow for much richer form of interaction between the user and machine. The emphasis is to provide a natural form of interface for interaction. Gestures are one of the natural forms of interaction between humans. As gesture commands are found to be natural for humans, the development of gesture control systems for controlling devices have become a popular research topic in recent years. Researchers have proposed different gesture recognition systems which act as an interface for controlling the applications. One of the drawbacks of present gesture recognition systems is application dependence which makes it difficult to transfer one gesture control interface into different applications. This paper focuses on designing a vision-based hand gesture recognition system which is adaptive to different applications thus making the gesture recognition systems to be application adaptive. The designed system comprises different processing steps like detection, segmentation, tracking, recognition, etc. For making the system as application-adaptive, different quantitative and qualitative parameters have been taken into consideration. The quantitative parameters include gesture recognition rate, features extracted and root mean square error of the system while the qualitative parameters include intuitiveness, accuracy, stress/comfort, computational efficiency, user's tolerance, and real-time performance related to the proposed system. These parameters have a vital impact on the performance of the proposed application adaptive hand gesture recognition system.

The increasing amount of available Protein-Protein Interaction (PPI) data enables scalable methods for the protein complex prediction. A protein complex is a group of two or more proteins formed by interactions that are stable over time, and it generally corresponds to a dense sub-graph in PPI Network (PPIN). However, dense sub-graphs correspond not only to stable protein complexes but also to sets of proteins including dynamic interactions. As a result, conventional simple PPIN based graph-theoretic clustering methods have high false positive rates in protein complex prediction. In this paper, we propose an approach to predict protein complexes based on the integration of PPI data and mutually exclusive interaction information drawn from structural interface data of protein domains. The extraction of Simultaneous Protein Interaction Cluster (SPIC) is the essence of our approach, which excludes interaction conflicts in network clusters by achieving mutually exclusion among interactions. The concept of SPIC was applied to conventional graph-theoretic clustering algorithms, MCODE and LCMA, to evaluate the density of clusters for protein complex prediction. The comparison with original graph-theoretic clustering algorithms verified the effectiveness of our approach; SPIC based methods refined false positives of original methods to be true positive complexes, without any loss of true positive predictions yielded by original methods.

We propose an interactive approach to data mining meant as the derivation of linguistic summaries of databases. For interactively formulating the linguistic summaries, and then for searching the database, we employ Kacprzyk and Zadrożny's [6-11]) fuzzy querying add-on, FQUERY for Access. We present an implementation for the derivation of linguistic summaries of sales data at a computer retailer.

There is obvious contradiction between the discrete spectrum resource and the high bandwidth requirement. As the key technology of LTE, OFDM (Orthogonal Frequency Division Multiplexing) technology can effectively avoid the frequency selective fading and inter symbol interface by using the orthogonal carrier [1], which improves the transmission accuracy of shortwave data. However the number of orthogonal carriers is limited in OFDM system. Spectrum aggregation technology is an useful technology by extending discrete bands or multiple continuous bands into a wider band to get more resources[2].It's possible to take advantage of these technologies to improve the system capacity. My work is responsible for researching the hardware and software design of interface between DSP and FPGA in the system based on spectrum aggregation technology and OFDM technology. Theoretical study based on MATLAB shows that the test system can improve the information transmission rate. This experimental system is feasible and effective.

In various of teaching activities and propagating activities, it is inevitable that some listeners in certain locations cannot see or cannot see clearly the details of the actual object which are explained so that it impacts understanding effectiveness deeply. In this paper, an portable round display device is introduced. Just with placing the mobile phone in the phone clip, images of actual object could be obtained using the phone's camera. Wireless transmission equipment HDMI transmitter sends the audio and video signals from phone's camera to projector screen. Images of detailed instruction activities are projected clear onto a screen. The main part of the display device is composed of linkages structures, in which main shaft is droved by motor that is fixed on transmission case. Multi-angle observation position of actual object is realized. The all-round display device is simple and practical, as well as it is easy to carry and operate.

Based on the concepts of system safety engineering, life-cycle and interface that comes from American system safety standard MIL-STD-882E, and apply them to the process of risk analysis and management of large-scale activities. Identify the involved personnel, departments, funds and other contents throughout the life cycle of large-scale activities. Recognize and classify the ultimate risk sources of people, objects and environment of large-scale activities from the perspective of interface. Put forward the accident cause analysis model according to the previous large-scale activities' accidents and combine with the analysis of the risk source interface. Analyze the risks of each interface and summary various types of risks the large-scale activities faced. Come up with the risk management consciousness, policies and regulations, risk control and supervision departments improvement ideas.