Some Properties for Adjustable Entropy Function Method and Its Application to Power Systems Dynamic Economic Dispatch with Wind Integrated

With the continuous development of the world economy, the development and utilization of environmentally friendly and renewable energy have become the trend in many countries. In this paper, we study the dynamic economic dispatch with wind integrated. Firstly, we take advantage of the positive and negative spinning reserve to deal with wind power output prediction errors in order to establish a dynamic economic dispatch model of wind integrated. The existence of a min function makes the dynamic economic dispatch model nondifferentiable, which results in the inability to directly use the traditional mathematical methods based on gradient information to solve the model. Inspired by the aggregate function, we can easily transform the nondifferentiable model into a smooth model when parameter p tends to infinity. However, the aggregate function will cause data overflow when p tends to infinity. Then, for solving this problem, we take advantage of the adjustable entropy function method to replace of aggregate function method. In addition, we further discuss the adjustable entropy function method and point out that the solution generated by the adjustable entropy function method can effectively approximate the solution of the original problem without parameter p tending to infinity. Finally, simulation experiments are given, and the simulation results prove the effectiveness and correctness of the adjustable entropy function method.

Repeatability and Reproducibility of Measures of Bovine Methane Emissions Recorded using a Laser Detector

Methane (CH4) emissions represent a worldwide problem due to their direct involvement in atmospheric warming and climate change. Ruminants are among the major players in the global scenario of CH4 emissions, and CH4 emissions are a problem for feed efficiency since enteric CH4 is eructed to the detriment of milk and meat production. The collection of CH4 phenotypes at the population level is still hampered by costly and time-demanding techniques. In the present study, a laser methane detector was used to assess repeatability and reproducibility of CH4 phenotypes, including mean and aggregate of CH4 records, slope of the linear equation modelling the aggregate function, and mean and number of CH4 peak records. Five repeated measurements were performed in a commercial farm on three Simmental heifers, and the same protocol was repeated over a period of three days. Methane emission phenotypes expressed as parts per million per linear meter (ppm × m) were not normally distributed and, thus, they were log-transformed to reach normality. Repeatability and reproducibility were calculated as the relative standard deviation of five measurements within the same day and 15 measurements across three days, respectively. All phenotypes showed higher repeatability and reproducibility for log-transformed data compared with data expressed as ppm × m. The linear equation modelling the aggregate function highlighted a very high coefficient of determination (≥0.99), which suggests that daily CH4 emissions might be derived using this approach. The number of CH4 peaks resulted as particularly diverse across animals and therefore it is a potential candidate to discriminate between high and low emitting animals. Results of this study suggest that laser methane detector is a promising tool to measure bovine CH4 emissions in field conditions.

A Graph and Clustering-Based Framework for Efficient XACML Policy Evaluation

EXtensible Access Control Markup Language (XACML) is one of the standardized languages for specifying access control policies. Policies described by the XACML are used to express the security requirement in the network and information system when we study authorization access control. With the aim to improve the Policy Decision Point (PDP) evaluation performance, we put forward a Graph and Clustering-Based Framework, employing the aggregate function. First, we partition the rule set into subsets. For the single value, we select the best partition quantity based on the aggregate function. As for the interval value, we handle with the start point and the finish point, respectively, in the same way as single value. Second, the policy set is split according to the partition of rule set. In this way, not only single values, but also interval values are taken into consideration. After that, we explore the searching tree to obtain the possibly matched rules. Finally, we construct the combining tree and output the policy decision on the basis of it. The experimental results show that our approach is orders of magnitude better than the Sun PDP. A comparison in evaluation performance between the redundancy detecting and eliminating engine and the Sun PDP, as well as XEngine and SBA-XACML, is made. Experimental results show that the evaluation performance of the PDP can be prominently improved by eliminating redundancies.

Occurrence, ecological function and medical importance of dermestid beetle hastisetae

Hastisetae are a specific group of detachable setae characterizing the larvae of Megatominae (Coleoptera: Dermestidae), commonly known as carpet and khapra beetles. These setae are located on both thoracic and abdominal tergites and they are the primary defense of the larva against invertebrate predators. According to previous studies, the main purpose of hastisetae is to work as a mechanical obstacle, but they are also capable to block and kill a predator. Hastisetae, single or aggregate, function as an extremely efficient mechanical trap, based on an entangling mechanism of cuticular structures (spines and hairs) and body appendages (antennae, legs and mouthparts). It is believed that this defensive system evolved primarily to contrast predation by invertebrates, however it has been observed that hastisetae may affect vertebrates as well. Although information on the impacts of vertebrate predators of the beetles is lacking, hastisetae have been shown to be a possible threat for human health as an important contaminant of stored products (food and fabric), work and living environment. Review of past and recent literature on dermestid larvae has revealed that despite these structures indicated as one of the distinctive characters in species identification, very little is known about their ultrastructure, evolution and mechanism of action. In the present work, we will provide the state of knowledge on hastisetae in Dermestidae and we will present and discuss future research perspectives intended to bridge the existing knowledge gaps.

Study of Optimized Window Aggregate Function for Big Data Analytics

Background: A Window Aggregate function belongs to a class of functions, which have emerged as a very important tool for Big Data Analytics. They lend support in analysis and decisionmaking applications. A window aggregate function aggregates and returns the result by applying the function over a limited number of tuples corresponding to current tuple and hence lending support for big data analytics. We have gone through different patents related to window aggregate functions and its optimization. The cost associated with Big data analytics, especially the processing of window functions is one of the major limiting factors. However, now a number of optimizing techniques have evolved for both single as well as multiple window aggregate functions. Methods: In this paper, the authors have discussed various optimization techniques and summarized the latest techniques that have been developed over a period through intensive research in this area. The paper tried to compare various techniques based on certain parameters like the degree of parallelism, multiple window function support, execution time etc. Results: After analyzing all these techniques, segment tree data structure seems better technique as it outperforms other techniques on different grounds like efficiency, memory overhead, execution speed and degree of parallelism. Conclusion: In order to optimize the window aggregate function, segment tree data structure technique is a better technique, which can certainly improve the processing of window aggregate function specifically in big data analytics.

Domain Partitioning: Approach to Computing Average Iceberg Queries

: Data analytics and data mining systems work on data which stored in files, the files are not store relationships among the data, from such kind of data we compute aggregate values over the set of required attributes for find insights of data, find attributes values which aggregation values greater than threshold such kind of queries called iceberg queries. Computing iceberg queries with average aggregate function is default, because limited memory available. Existing method are suffers with re-computation of candidate. We proposed a Record Traction Algorithm(RTA) ,it use Domain partitioning approach, it avoid re-computation of candidate in during next scan of data set, it use bit vector and bitmap numbers for Domain Partitioning the data, our experiment reveals that our approach generate a candidate only once and input data will reduced in further candidate sets.

Monitoring and Assessment of Protected Areas’ Management Capacities in the Republic of Serbia

The necessity to measure the effectiveness of the management of protected areas has been widely recognized. This paper aims to show a realistic state of affairs in protected area management in the Republic of Serbia on the basis of the results of managers’ monitoring and their obligations stipulated by law. It will also answer questions on which form of management is optimal, by means of a proposed assessment model. The research has been performed on a sample of 30 sensu stricto protected areas, managed by 21 different managers. For the purpose of ranking and comparing the degree of protected area management effectiveness, the use of a normalized aggregate function (scoring) has been introduced. Results show that about half of the analyzed protected areas have no adequate management in terms of legally prescribed management criteria, as well as that management effectiveness is related to several external factors. The authors conclude that meeting all criteria stipulated by law, and the existence of professional staff represent fundamental factors for the effective management of protected areas.