Resolution enhanced light field near eye display using e‐shifting method with birefringent plate

Light field near eye displays (LFNED) can produce lightweight devices and address the accommodation–convergence conflict. However, low spatial resolution creates a poor immersive experience in LFNED. In addition, although many e‐shifting devices have been proposed to enhance resolution in projection system, yet those devices are too bulky to be applied in an LFNED to keep it lightweight. In this paper, a compact e‐shifting component is proposed to enhance image resolution in an LFNED by using a birefringent plate and twisted nematic switch cell. The proposed e‐shifting device is a flat and thin component with only 2.6 mm of thickness, which could be placed in the gap of an LFNED without increasing the thickness. The results show that the proposed components could be easily integrated in an LFNED with the result of resolution enhancement.     

What Security Questions Do Developers Ask? A Large-Scale Study of Stack Overflow Posts

Security has always been a popular and critical topic. With the rapid development of information technology, it is always attracting people’s attention. However, since security has a long history, it covers a wide range of topics which change a lot, from classic cryptography to recently popular mobile security. There is a need to investigate security-related topics and trends, which can be a guide for security researchers, security educators and security practitioners. To address the above-mentioned need, in this paper, we conduct a large-scale study on security-related questions on Stack Overflow. Stack Overflow is a popular on-line question and answer site for software developers to communicate, collaborate, and share information with one another. There are many different topics among the numerous questions posted on Stack Overflow and security-related questions occupy a large proportion and have an important and significant position. We first use two heuristics to extract from the dataset the questions that are related to security based on the tags of the posts. And then we use an advanced topic model, Latent Dirichlet Allocation (LDA) tuned using Genetic Algorithm (GA), to cluster different security-related questions based on their texts. After obtaining the different topics of security-related questions, we use their metadata to make various analyses. We summarize all the topics into five main categories, and investigate the popularity and difficulty of different topics as well. Based on the results of our study, we conclude several implications for researchers, educators and practitioners.     

Secure centralized spectrum sensing for cognitive radio networks

Spectrum utilization becomes more and more important while new communication techniques keep increasing and the spectrum bands remain finite. Cognitive radio is a revolutionary technology to make use of the spectrum more effectively. In order to avoid the interference to the primary user, spectrum sensing must be sensitive and reliable. Cooperative spectrum sensing (CSS) is one of the ways to increase the reliability of spectrum sensing. The information fusion technique is a key component of CSS. In this paper, we proposed a novel fusion scheme based on spatial correlation technique. We utilize geographical information with reputational weights to propose a two-level fusion scheme called secure centralized spectrum sensing (SCSS). The simulation results show that as the attackers present high density aggregation at some areas, the correct sensing ratio of SCSS is increasing as well even when the number of attackers is very large.     

Crime hotspot mapping using the crime related factors—a spatial data mining approach

The technique of Hotspot Mapping is widely used in analysing the spatial characteristics of crimes. The spatial distribution of crime is considered to be related with a variety of socio-economic and crime opportunity factors. But existing methods usually focus on the target crime density as input without utilizing these related factors. In this study, we introduce a new crime hotspot mapping tool—Hotspot Optimization Tool (HOT). HOT is an application of spatial data miming to the field of hotspot mapping. The key component of HOT is the Geospatial Discriminative Patterns (GDPatterns) concept, which can capture the differences between two classes in a spatial dataset. Experiments are done using a real world dataset from a northeastern city in the United States and the pros and cons of utilizing related factors in hotspot mapping are discussed. Comparison studies with the Hot Spot Analysis tool implemented by Esri ArcMap 10.1 validate that HOT is capable of accurately mapping crime hotspots.     

An ISM,DEI, and ANP based approach for product family development

Product customization has been used for many years, and with this concept, product families can be designed that are better matched to the needs of customers through the use of market segmentation and modular architecture. This study is composed of two phases: the first phase establishes the modular architecture, and taking a bicycle as the case study, applies the Interpretive Structural Model (ISM) to modularize and cluster parts, and then models the connecting relations between the parts numerically using a Disassembly Effort Index (DEI). The second step involves the development of a product family using cluster analysis to divide the experimental samples and the employment of an Analytic Network Process (ANP) to obtain the optimal weight performance of the modules after establishing the market segmentation model. Results of the case study establish four product families and address construction performance of both the common and independent modules between the product families.     

Optimal quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks

Recently, an image scrambling encryption algorithm of pixel bit based on chaos map was proposed. Considering the algorithm as a typical binary image scrambling/permutation algorithm exerting on plaintext of size M×(8N), this paper proposes a novel optimal method to break it with some known/chosen-plaintexts. The spatial complexity and computational complexity of the attack are only O(32·MN) and O(16·n₀·MN) respectively, where n₀ is the number of known/chosen-plaintexts used. The method can be easily extended to break any permutation-only encryption scheme exerting on plaintext of size M×N and with L different levels of values. The corresponding spatial complexity and computational complexity are only O(MN) and O(⌈log_L(MN)⌉·MN) respectively. In addition, some specific remarks on the performance of the image scrambling encryption algorithm are presented.     

Heat and Mass Transfer Measurements for Tray-Fermented Fungal Products

In this study, heat and mass transfer in static tray fermentation, which is widely used in solid-state fermentation (SSF) to produce fungal products, such as enzymes or koji, is investigated. Specifically, kinetic models of transport phenomena in the whole-tray chamber are emphasized. The effects of temperature, moisture, and humidity on microbial growth in large-scale static tray fermentation are essential to scale-up SSF and achieve uniform fermentation. In addition, heat and mass transfer of static tray fermentation of Trichoderma fungi with two tray setups??traditional linen coverings and stacks in a temperature?Chumidity chamber is examined. In both these setups, the following factors of fermentation were measured: air velocity, air temperature, illumination, pH, carbon dioxide (CO₂) concentration, and substrate temperature, and the effects of bed height, moisture of substrate, and relative humidity of air are studied. A thin (1 cm) bed at 28 °C and 95 % relative humidity is found to be optimum. Furthermore, mixing was essential for achieving uniform fermentation of Trichoderma fungi. This study has important applications in large-scale static tray fermentation of fungi.     

Priority setting in maintenance management: a modified multi-attribute approach using analytic hierarchy process

In the current economic climate, budgets for the maintenance of public buildings are unlikely to meet the ever-increasing maintenance needs. Although it is unlikely that this problem can be overcome completely without an injection of further resources, it is possible for government maintenance authorities to improve the situation by ensuring that the best solution in terms of ‘value for money’ is achieved in the planned maintenance programme. A maintenance plan which is based on a rational assessment of priorities and up-to-date knowledge of the condition of the property stock will help to ensure the best use of available resources. Based on the multi-attribute maintenance prioritization model developed by Alan Spedding, Roy Holmes and Qiping Shen at the University of West of England, which is simple in practice and flexible from a management point of view, this paper presents the results of some further research into this area by modifying the original model using an analytical hierarchy process in deciding the weightings of the criteria set out in the prioritization model. This modified model is more quantitative and objective than the original model. The validation of the framework is also discussed.