An Efficient Encrypted Speech Retrieval Based on Unsupervised Hashing and B+ Tree Dynamic Index

Existing speech retrieval systems are frequently confronted with expanding volumes of speech data.The dynamic updating strategy applied to construct the index can timely process to add or remove unnecessary speech data to meet users’real-time retrieval requirements.This study proposes an efficient method for retrieving encryption speech,using unsupervised deep hashing and B+ tree dynamic index,which avoid privacy leak-age of speech data and enhance the accuracy and efficiency of retrieval.The cloud’s encryption speech library is constructed by using the multi-threaded Dijk-Gentry-Halevi-Vaikuntanathan(DGHV)Fully Homomorphic Encryption(FHE)technique,which encrypts the original speech.In addition,this research employs Residual Neural Network18-Gated Recurrent Unit(ResNet18-GRU),which is used to learn the compact binary hash codes,store binary hash codes in the designed B+tree index table,and create a mapping relation of one to one between the binary hash codes and the corresponding encrypted speech.External B+tree index technology is applied to achieve dynamic index updating of the B+tree index table,thereby satisfying users’needs for real-time retrieval.The experimental results on THCHS-30 and TIMIT showed that the retrieval accuracy of the proposed method is more than 95.84%compared to the existing unsupervised hashing methods.The retrieval efficiency is greatly improved.Compared to the method of using hash index tables,and the speech data’s security is effectively guaranteed.

Tree Species Composition and Diversity in the Riparian Forest of Lake Barombi Kotto, Cameroon

Tree species composition and diversity were investigated in the riparian forest around Lake Barombi Kotto, Cameroon. This study aimed at determining the tree species composition, population structure, and providing evidence of anthropogenic disturbances in the riparian forest of Lake Barombi Kotto. The objectives were to determine the tree species composition and diversity in the riparian forest around Lake Barombi Kotto, to elucidate the forest structure and to document the anthropogenic disturbances in this forest. Five plots were laid within which the tree enumeration and measurement of dbh were carried out. Trees were identified using scientific identification keys in the Flora of West Africa. Disturbance scores were given to each site by qualitatively assessing various disturbances. A total of 340 trees belonging to 70 plant species, 63 genera and 28 plant families were enumerated. Shannon-Wiener diversity varied across sites, with the highest value (H = 3.45) recorded in Tung and the lowest (H = 2.21) in Malenda. Population structure differed across sites, the largest stand basal area of 43.78 m2/ha was recorded in Bondokombo while the smallest (2.15 m2/ha) was recorded in the Sacred Island. Cecropia peltata L., Pseudospondias macrocarpa Oliv. Pierre and Ceiba pentandra (L.) Gaertn had the largest basal areas across the different sites. Species rich families were Malvaceae (9 species), Fabaceae (9 species), Annonaceae (4 species), and Anacardiaceae (4). This study shows that, there is a high tree species diversity in the protected forest (Tung) but the other unprotected sites are highly disturbed by anthropogenic activities. There is need to develop and enhance existing management policies for this riparian forest, especially by replanting the cut trees and creating a protected riparian buffer to conserve its floristic diversity and ecological functions.

Reliability Analysis of Electrical System of CNC Machine Tool Based on Dynamic Fault Tree Analysis Method

The electrical system of CNC machine tool is very complex which involves many uncertain factors and dynamic stochastic characteristics when failure occurs.Therefore,the traditional system reliability analysis method,fault tree analysis(FTA)method,based on static logic and static failure mechanism is no longer applicable for dynamic systems reliability analysis.Dynamic fault tree(DFT)analysis method can solve this problem effectively.In this method,DFT first should be pretreated to get a simplified fault tree(FT);then the FT was modularized to get the independent static subtrees and dynamic subtrees.Binary decision diagram(BDD)analysis method was used to analyze static subtrees,while an approximation algorithm was used to deal with dynamic subtrees.When the scale of each subtree is smaller than the system scale,the analysis efficiency can be improved significantly.At last,the usefulness of this DFT analysis method was proved by applying it to analyzing the reliability of electrical system.

Study on System Failure Probability Model Based on Dynamic Fault Tree

Aiming at the characteristics of complex logic relation and multiple dynamic gates in system,its failure probability model is established based on dynamic fault tree. For the multi-state dynamic fault tree,it can be transferred into Markov chain with continuous parameters. The state transfer diagram can be decomposed into several state transfer chains,and the failure probability models can be derived according to the lengths of the chains. Then,the failure probability of the dynamic fault tree analysis(DFTA) can be obtained by adding each chain's probability. The failure probability calculation of DFTA based on the continuous parameter Markov chain is proposed and proved. Given an example,the analytic method is compared with the conventional methods which have to solve the differential equation. It is known from the results that the analytic method can be applied to engineering easily.

Dynamic Fault Tree Analysis for Explosive Logic Network with Two-Input-One-Output

The explosive logic network( ELN) with two-input-oneoutput was designed with three explosive logic gap null gates. The time window of the output of the ELN was given,after which the dynamic fault tree analysis was implemented. Two dynamic failure modes of the ELN were obtained,and then their own Markov transition processes were established. After that,the probability of failure was calculated from the corresponding state transition diagram. The reliability of the ELN which was in different length of time under the ambient incentive was then analyzed. Based on the above processing,the reliability of the ELN can be improved.

STUDY ON COMMUNITY STRUCTURE AND SELF-SUSTAINING MECHANISM OF BROAD-LEAVED/KOREAN PINE FORESTS IN NORTHEAST CHINA

The regeneration, tree growth, and community structure and dynamics were studied in old-growth Korean pine (Pinus koraiensis) forest.The results showed that the formation of tree form and growth character have been obviously related with the gap-phase regeneration.The ecological effects of the gap suppress the tree growth in diameter,and control that young tree stem fork in early stage.The heterogeneity of tree growth in time and space is the results of high quality in tree height and diameter.The hardwood species mixth Korean pine have different ecological effect on regeneration and tree growth of Korean pine in the early stage of gap reconstructing. Community dynamics depends on tree gaps oceurs,in which a 'cyclic sucession'between Korean pine and hard wood species may occurs.The process would take about 200 yers.

Energy equalizing routing for fast data gathering in wireless sensor networks

Energy saving and fast responding of data gathering are two crucial factors for the performance of wireless sensor networks. A dynamic tree based energy equalizing routing scheme （DTEER） was proposed to make an effort to gather data along with low energy consumption and low time delay. DTEER introduces a dynamic multi-hop route selecting scheme based on weight-value and height-value to form a dynamic tree and a mechanism similar to token passing to elect the root of the tree. DTEER can simply and rapidly organize all the nodes with low overhead and is robust enough to the topology changes. When compared with power-efficient gathering in sensor information systems （PEGASIS） and the hybrid, energy- efficient, distributed clustering approach （HEED）, the simulation results show that DTEER achieves its intention of consuming less energy, equalizing the energy consumption of all the nodes, alleviating the data gathering delay, as well as extending the network lifetime perfectly.

Numerical Simulation to Reliability Analysis of Fault-Tolerant Repairable System

In the traditional method for the reliability analysis of fault-tolerant system,the system structure is described by means of binary decision diagram (BDD) and Markov process,and then the reliability indexes are calculated.However,as the size of system augments,the size of state space will increase exponentially.Additionally,Markov approach requires that the failure and repair time of the components obey an exponential distribution.In this study,by combining dynamic fault tree (DFT) and numerical simulation based on the minimal sequence cut set (MSCS),a new method to evaluate reliability of fault-tolerant system with repairable components is proposed.The method presented does not depend on Markov model,so that it can effectively solve the problem of the state-space combination explosion.Moreover,it is suitable for systems whose failure and repair time obey an arbitrary distribution.Therefore,our method is more flexible than the traditional method.At last,an example is given to verify the method.

Reliability Analysis of Electrical System of Computer Numerical Control Machine Tool Based on Bayesian Networks

The core of computer numerical control(CNC) machine tool is the electrical system which controls and coordinates every part of CNC machine tool to complete processing tasks, so it is of great significance to strengthen the reliability of the electrical system. However, the electrical system is very complex due to many uncertain factors and dynamic stochastic characteristics when failure occurs. Therefore, the traditional fault tree analysis(FTA) method is not applicable. Bayesian network(BN) not only has a unique advantage to analyze nodes with multiply states in reliability analysis for complex systems, but also can solve the state explosion problem properly caused by Markov model when dealing with dynamic fault tree(DFT). In addition, the forward causal reasoning of BN can get the conditional probability distribution of the system under considering the uncertainty;the backward diagnosis reasoning of BN can recognize the weak links in system, so it is valuable for improving the system reliability.

Mental Calculation Drives Reliable and Weak Distant Connectivity While Music Listening Induces Dense Local Connectivity

Mathematical calculation usually requires sustained attention to manipulate numbers in the mind,while listening to light music has a relaxing effect on the brain.The differences in the corresponding brain functional network topologies underlying these behaviors remain rarely known.Here,we systematically examined the brain dynamics of four behaviors(resting with eyes closed and eyes open,tasks of music listening and mental calculation)using 64-channel electroencephalogram(EEG)recordings and graph theory analysis.We developed static and dynamic minimum spanning tree(MST)analysis method and demonstrated that the brain network topology under mental calculation is a more line-like structure with less tree hierarchy and leaf fraction;however,the hub regions,which are mainly located in the frontal,temporal and parietal regions,grow more stable over time.In contrast,music-listening drives the brain to exhibit a highly rich network of star structure,and the hub regions are mainly located in the posterior regions.We then adopted the dynamic dissimilarity of different MSTs over time based on the graph Laplacian and revealed low dissimilarity during mental calculation.These results suggest that the human brain functional connectivity of individuals has unique dynamic diversity and flexibility under various behaviors.