Periodic replacement with minimal repair at failure and general random repair cost for a multi-unit system

A policy of periodic replacement with minimal repair at failure is considered for the multi-unit system which have the specific multivariate distribution. Under such a policy an operating system is completely replaced whenever it reaches age T (T > 0) at a cost c₀ while minimal repair is performed at any intervening component failures. The cost of the j-th minimal repair to the component which fails at age y is g(C(y),c_j(y)), where C(y) is the age-dependent random part, c_j(y) is the deterministic part which depends on the age and the number of the minimal repair to the component, and g is an positive nondecreasing continuous function. A simple expression is derived for the expected minimal repair cost in an interval in terms of the cost function and the failure rate of the component. Necessary and sufficient conditions for the existence of an optimal replacement interval are exhibited.     

Low-operation voltage of InGaN/GaN light-emitting diodes by using aMg-doped Al0.15Ga0.85N/GaN superlattice

Low-resistivity Mg-doped Al_0.15Ga_0.85N/GaN strained-layer superlattices were grown. In these superlattices, the maximum hole concentration is 3×10¹⁸/cm³ at room temperature. Hall-effect measurements indicate high conductivity of this structure in which the high activation efficiency is attributed to the strain-induced piezoelectric fields. This work also fabricated InGaN/GaN blue LEDs that consist of a Mg-doped Al_0.15Ga_0.85N/GaN SLs. Experimental results indicate that the LEDs can achieve a lower operation voltage of around 3 V, i.e., smaller than conventional devices which have an operation voltage of about 3.8 V     

A general replacement of a system subject to shocks

A system is subject to shocks that arrive according to a nonhomogeneous Poisson process. The system is replaced at age T at a fixed cost c₀. If the k-th shock arrives at time S_k<T, it is either a fatal shock with probability p(S_k) or a nonfatal shock with probability 1−p(S_k). The fatal shock causes the system total breakdown, and the system is replacd at a cost c_∞. The nonfatal shock weakens the system and makes it more expensive to run. The aim of the paper is to find the optimal T which minimizes the long run expected cost per unit time of the policy. Various special cases are considered.     

The associate impact of individual internal experiences and reference groups on buying behavior: A case study of animations,comics, and games consumers

Among the entertainment and media market, it can be observed that animations, comics, and video games (hereinafter abbreviated as ACG) have the highest output value and most market influence. Moreover, ACG also incorporates various industries and creates many derivative products. As the ACG industry emphasizes acousto-optics, imagery, and storylines, personal impressions derived from consumer experiences will influence consumer decisions. In addition, the ACG industry is mainly marketed towards younger age groups, with younger people being the main consumers; as such, these consumers’ decisions are more easily affected by peer behavior.This study aims to analyze the effects of internal cognitions and external influences on buying behavior of ACG consumers by applying the uncomplicated decision tree data mining algorithm. We analyze and develop the target attributes on measures of customer loyalty for ACG industry to set up the decision trees from the collected questionnaire data. The decision tree data mining method is applied to analyze the hidden association rules between the target attributes (i.e., consumer loyalty) and the critical influencing factors of consumer’s internal impressions and external influences for ACG consumers. The results and suggestions of this paper can be used as a reference for enterprises in the ACG industry to help with business policies concerning products’ extensional design, marketing, and CRM, and to further strengthen customer satisfaction and loyalty, thus increasing company profits.     

Mining association rules between positive word-of-mouth on social network sites and consumer acceptance: A study for derivative product of animations,comics, and games

In recent years, we can easily observe that animations, comics, and games (ACG) have great output value and market influence on the entertainment and digit media market. The ACG industry is not an industry of a single country or region but a global industry. In addition to its own revenue, the derivative products (or licensed merchandise) of ACG can extend the ACG industry to win more business opportunities. The ACG industry is mainly marketed towards younger people, who are the major users of social network sites. Hence, the electronic word-of-mouth (eWOM) on social network sites often becomes a reference basis of the young people’s attitudinal acceptance and purchase intention in purchasing ACG-related derivative product.In this paper, we analyze the influential factors of positive eWOM’s communication motivations that affect consumer acceptance on social network sites, and apply the uncomplicated decision tree data mining algorithm to compute the association rules between these influential factors and consumer acceptance, expecting to understand the relationship between eWOM on social network sites and consumer acceptance. The results of this study can help the business decision-making in CRM and marketing of the industry of ACG-related derivative product. This study found that the degree of perception of ACG product and the degree of taking pleasure in sharing ACG-related information with others have a significant correlation with consumer acceptance.     

Colossal Barocaloric Effect by Large Latent Heat Produced by First-Order Intersite-Charge-Transfer Transition

Materials which show novel thermal properties can be used to make highly efficient and environmentally friendly energy systems for thermal energy storage and refrigeration through caloric effects. An A-site-ordered quadruple perovskite-structure oxide, NdCu₃Fe₄O₁₂, is found to release significant latent heat, 25.5 kJ kg⁻¹ (157 J cc⁻¹), at the intersite-charge-transfer transition temperature near room temperature. The transition is first-order and accompanied by an unusual magnetic ordering and a large negative-thermal-expansion-like volume change, and thus, it causes a large entropy change (84.2 J K⁻¹ kg⁻¹). The observed entropy change is comparable to the largest changes reported in inorganic solid materials, and more importantly, it is utilized through a colossal barocaloric effect. The adiabatic temperature change by applying 5.1 kbar pressure is estimated to reach 13.7 K, which means efficient refrigeration can be realized through this effect.     

Learning Association Rules and Tracking the Changing Concepts on Webpages: An Effective Pornographic Websites Filtering Approach

We applied the decision tree algorithm to learn association rules between webpage’s category (pornographic or normal) and the critical features. Based on these rules, we proposed an efficient method of filtering pornographic webpages with the following major advantages: 1) a weighted window-based technique was proposed to estimate for the condition of concept drift for the keywords found recently in pornographic webpages; 2) checking only contexts of webpages without scanning pictures; 3) an incremental learning mechanism was designed to incrementally update the pornographic keyword database.     

Improved Light Extraction Efficiency in AlGaInP Light-Emitting Diodes by Applying a Periodic Texture on the Surface

In this letter, AlGaInP-GaP-based light-emitting diodes (LEDs) were fabricated with an Si substrate and an SiO₂-ITO-Ag omni-directional reflector using a metal-to-metal bonding technique. To enhance light extraction efficiency, a periodic texture was applied to the (Al_0.5Ga_0.5)_0.5In_0.5P surface layer of AlGaInP-Si LEDs by photolithography and a wet etching process. The exterior of the etched texture consists of a series of bowl-shaped recesses. With a 350-mA current injection, the typical output power of the AlGaInP-Si LEDs with and without the textured surface (LED-I and LED-II, respectively) were measured at approximately 118 and 81 mW, respectively, when the LED chips were bonded on the TO 46 without resin encapsulation. The enhancement of output power in LED-I can be attributed to a multitude of bowl-shaped notches on the surface, which resulted in a reduction of the reabsorption probability of the photons due to the fact that the photon path length in LED-I is shorter than in LED-II before the photons escape into the free space.     

An agent‐based workflow scheduling mechanism with deadline constraint on hybrid cloud environment

Summary

With the advances of cloud computing, business and scientific‐oriented jobs with certain workflows are increasingly migrated to and run on a variety of cloud environments. These jobs are often with the property of deadline constraint and have to be completed within limited time. Therefore, to schedule a job with workflow (short for workflow) with deadline constraint is increasingly becoming a crucial research issue. In this paper, we, based on previous work, propose an agent‐based workflow scheduling mechanism to schedule workflows that are with deadline constraint into federated cloud environment.

Design and Methods

We add a workflow agent into the original framework to schedule the deadline‐constraint workflow. The workflow agent can smoothly schedule workflows to the cloud system according to their required resource and automatically monitor their execution. In order to accurately predict the execution time of each task to meet deadline constraint on certain VM with given resource, we inherit the use of rough set theory to estimate execution time of task in our previous work.

Result and Discussion

A heuristic algorithm that is embedded into the workflow agent is also proposed because the problem had been shown to be NP‐complete. The mechanism also adopts dynamic job dispatching method to reduce the usage of VM and to improve the resource utilization. We also conducted experiments to evaluate the efficiency and effectiveness.

Conclusion

The experimental results show that the prediction time is very close to the real execution time and can efficiently schedule multiple scientific workflows to meet the deadline constraints simultaneously.     

A Distributed Localization Scheme for Wireless Sensor Networks with Improved Grid-Scan and Vector-Based Refinement

Localization is a fundamental and essential issue for wireless sensor networks (WSNs). Existing localization algorithms can be categorized as either range-based or range-free schemes. Range-based schemes are not suitable for WSNs because of their irregularity of radio propagation and their cost of additional devices. In contrast, range-free schemes do not need to use received signal strength to estimate distances and only need simple and cheap hardware, and are thus more suitable for WSNs. However, existing range-free schemes are too costly and not accurate enough or are not scalable. To improve previous work, we present a fully distributed range-free localization scheme for WSNs. We assume that only a few sensor nodes, called anchors, know their locations, and the remaining (normal) nodes need to estimate their own locations by gathering nearby neighboring information. We propose an improved grid-scan algorithm to find the estimated locations of the normal nodes. Furthermore, we derive a vector-based refinement scheme to improve the accuracy of the estimated locations. Analysis, simulation, and experiment results show that our scheme outperforms the other range-free schemes even when the communication radius is irregular.