Time Parameter Based Low-Energy Data Encryption Method for Mobile Applications

Various mobile devices and applications are now used in daily life.These devices require high-speed data processing,low energy consumption,low communication latency,and secure data transmission,especially in 5G and 6G mobile networks.High-security cryptography guarantees that essential data can be transmitted securely;however,it increases energy consumption and reduces data processing speed.Therefore,this study proposes a low-energy data encryption(LEDE)algorithm based on the Advanced Encryption Standard(AES)for improving data transmission security and reducing the energy consumption of encryption in Internet-of-Things(IoT)devices.In the proposed LEDE algorithm,the system time parameter is employed to create a dynamic S-Box to replace the static S-Box of AES.Tests indicated that six-round LEDE encryption achieves the same security level as 10-round conventional AES encryption.This reduction in encryption time results in the LEDE algorithm having a 67.4%lower energy consumption and 43.9%shorter encryption time than conventional AES;thus,the proposed LEDE algorithm can improve the performance and the energy consumption of IoT edge devices.

River width and depth as key factors of diurnal activity energy expenditure allocation for wintering Spot-billed Ducks in the Xin'an River Basin

Rivers are important habitats for wintering waterbirds.However,they are easily influenced by natural and human activities.An important approach for waterbirds to adapt to habitats is adjusting the activity time and energy expenditure allocation of diurnal behavior.The compensatory foraging hypothesis predicts that increased energy expenditure leads to longer foraging time,which in turn increases food intake and helps maintain a constant energy balance.However,it is unclear whether human-disturbed habitats result in increased energy expenditure related to safety or foraging.In this study,the scan sample method was used to observe the diurnal behavior of the wintering Spot-billed Duck(Anas poecilorhyncha) in two rivers in the Xin’an River Basin from October 2021 to March 2022.The allocation of time and energy expenditure for activity in both normal and disturbed environments was calculated.The results showed that foraging accounted for the highest percentage of time and energy expenditure.Additionally,foraging decreased in the disturbed environment than that in the normal environment.Resting behavior showed the opposite trend,while other behaviors were similar in both environments.The total diurnal energy expenditure of ducks in the disturbed environment was greater than that in the normal environment,with decreased foraging and resting time percentage and increased behaviors related to immediate safety(swimming and alert) and comfort.These results oppose the compensatory foraging hypothesis in favor of increased security.The optimal diurnal energy expenditure model included river width and water depth,which had a positive relationship;an increase in either of these two factors resulted in an increase in energy expenditure.This study provides a better understanding of energy allocation strategies underlying the superficial time allocation of wintering waterbirds according to environmental conditions.Exploring these changes can help understand the maximum fitness of wintering waterbirds in response to nature and human influences.

基于TimeSVD++与DPC的推荐算法研究

针对使用奇异值分解(SVD)方法时需要填充矩阵的内容较多以及K-means算法受到K值的影响且数据集形状限制等问题,提出一种将TimeSVD++与改进的密度峰值聚类结合的方法。首先在SVD++的基础上引入参数时间因子,构建TimeSVD++模型;其次,采用将相似系数引入高斯核函数的方法,对密度峰聚类算法中的局部密度公式进行修正;引入信息熵确定最优截断距离,最后在数据集MovieLens-1M和MovieLens-100k上验证,并将实验结果与其它算法进行对比。结果表明:所提出的方法在MAE,RMSE,Recall和F1值指标上均优于其它的算法。

Cubic Root Extractors of Gaussian Integers and Their Application in Fast Encryption for Time-Constrained Secure Communication

There are settings where encryption must be performed by a sender under a time constraint. This paper de-scribes an encryption/decryption algorithm based on modular arithmetic of complex integers called Gaus-sians. It is shown how cubic extractors operate and how to find all cubic roots of the Gaussian. All validations (proofs) are provided in the Appendix. Detailed numeric illustrations explain how to use the method of digital isotopes to avoid ambiguity in recovery of the original plaintext by the receiver.

A time domain induced polarization relaxation time spectrum inversion method based on a damping factor and residual correction

Relaxation time spectra （RTS） derived from time domain induced polarization data （TDIP） are helpful to assess oil reservoir pore structures. However, due to the sensitivity to the signal-to-noise ratio （SNR）, the inversion accuracy of the traditional singular value decomposition （SVD） inversion method reduces with a decrease of SNR. In order to enhance the inversion accuracy and improve robustness of the inversion method to the SNR, an improved inversion method, based on damping factor and spectrum component residual correction, is proposed in this study. The numerical inversion results show that the oscillation of the RTS derived from the SVD method increased with a decrease of SNR, which makes it impossible to get accurate inversion components. However, the SNR has little influence on inversion components of the improved method, and the RTS has high inversion accuracy and robustness. Moreover, RTS derived from core sample data is basically in accord with the pore-size distribution curve, and the RTS derived from the actual induced polarization logging data is smooth and continuous, which indicates that the improved method is practicable.

Predictive factors of endoscopic submucosal dissection procedure time for gastric superficial neoplasia

AIM:To identify the determinants of endoscopic submucosal dissection(ESD) operation time.METHODS:This investigation was conducted as a single-center,prospective study in which ESD was performed by the same endoscopist at the Chinese PLA General Hospital.A total of 173 patients underwent ESD operations performed by Dr.Lu from July 2007 to December 2011,and 183 lesions were enrolled.Patient gender,age,tumor location,gross type,tumor size,pathological type and adhesions were recorded prospectively.The order of treatment represented the experience of the operator.Univariate analysis and multivariate analysis were performed to evaluate the relationships between these factors and ESD procedure time.RESULTS:Univariate analysis showed the ESD time was closely related to the gender(P = 0.0210),tumor size(P < 0.0001),location(P < 0.0001),gross type(P < 0.0001) and adhesion(P = 0.0010).The surgical proficiency level was associated with ESD time in unit area(P < 0.0001).Multivariate analysis revealed that the ESD time was positively correlated with tumor size(P < 0.0001),adhesion(P < 0.0001) and location(P < 0.0001),but negatively correlated with surgical proficiency level(P = 0.0046).CONCLUSION:Large tumor size,adjacency to the cardia,and adhesion are predictors of a long ESD time,whereas high surgical proficiency level predicts a short ESD time.

Factors Influencing the Emergency Medical Service Response Time for Cardiovascular Disease in Guangzhou, China

While emergency medical service (EMS) response time (ERT) is a major factor associated with the survival of patients with cardiovascular disease (CVD), relatively few studies have explored the factors associated with ERT. This study aimed to assess the current status of ERT and to identify the factors affecting ERT in patients with CVD in China. Between January 1, 2011 and December 31, 2015, EMS responses to CVD incidents in Guangzhou, China, were examined. The primary outcome was ERT, defined as the time from receipt of an emergency call to the arrival of paramedics on the scene. Factors associated with ERT were evaluated by multivariable logistic regression. A total of 44 383 CVD incidents were analysed. The median ERT was 12.58 min (interquartile range=9.98-15.67). Among the risk factors, distance (OR=13.73, 95% CI=11.76- 16.04), level of hospital (OR=1.57, 95% CI=1.40-1.75), and site of the incident (OR=1.53, 95% CI=1.38-1.69) were the top three significant factors affecting the ERT. Our results suggest that greater attention should be given to factors affecting the ERT. It is essential to make continuous efforts to promote the development of effective interventions to reduce the response time.

Coupling effects of influence factors on probability of corrosion initiation time of reinforced concrete

The coupling model of major influence factors such state affecting the chloride diffusion process in concrete is as environmental relative humidity, load-induced crack and stress discussed. The probability distributions of the critical chloride concentration Cc, the chloride diffusion coefficient D, and the surface chloride concentration Cs were determined based on the collected natural exposure data. And the estimation of probability of corrosion initiation considering the coupling effects of influence factors is presented. It is found that the relative humidity and curing time are the most effective factors affecting the probability of corrosion initiation before and after 10 years of exposure time. At the same exposure time, the influence of load-induced crack and stress state on the probability of corrosion initiation is obvious, in which the effect of crack is the most one

A NEW PUBLIC-KEY ENCRYPTION SCHEME BASED ON LUCAS SEQUENCE

Investigated the properties of LUCas sequence(LUC), the paper proposed a new variant of (probabilistic) public-key encryption scheme. Security analysis of the proposed encryption schemes shows that its one-wayness is equivalent to partial LUC discrete logarithm problem in ZN, and for the proposed probabilistic encryption scheme, its semantic security is equivalent to decisional LUC Diffie-Hellman problem in ZN. At last, the efficiency of the proposed schemes is briefly analyzed.

Anomaly IoT Node Detection Based on Local Outlier Factor and Time Series

The heterogeneous nodes in the Internet of Things(IoT)are relatively weak in the computing power and storage capacity.Therefore,traditional algorithms of network security are not suitable for the IoT.Once these nodes alternate between normal behavior and anomaly behavior,it is difficult to identify and isolate them by the network system in a short time,thus the data transmission accuracy and the integrity of the network function will be affected negatively.Based on the characteristics of IoT,a lightweight local outlier factor detection method is used for node detection.In order to further determine whether the nodes are an anomaly or not,the varying behavior of those nodes in terms of time is considered in this research,and a time series method is used to make the system respond to the randomness and selectiveness of anomaly behavior nodes effectively in a short period of time.Simulation results show that the proposed method can improve the accuracy of the data transmitted by the network and achieve better performance.

A New Encryption-Then-Compression Scheme on Gray Images Using the Markov Random Field

Compressing encrypted images remains a challenge.As illustrated in our previous work on compression of encrypted binary images,it is preferable to exploit statistical characteristics at the receiver.Through this line,we characterize statistical correlations between adjacent bitplanes of a gray image with the Markov random field(MRF),represent it with a factor graph,and integrate the constructed MRF factor graph in that for binary image reconstruction,which gives rise to a joint factor graph for gray images reconstruction(JFGIR).By exploiting the JFGIR at the receiver to facilitate the reconstruction of the original bitplanes and deriving theoretically the sum-product algorithm(SPA)adapted to the JFGIR,a novel MRF-based encryption-then-compression(ETC)scheme is thus proposed.After preferable universal parameters of the MRF between adjacent bitplanes are sought via a numerical manner,extensive experimental simulations are then carried out to show that the proposed scheme successfully compresses the first 3 and 4 most significant bitplanes(MSBs)for most test gray images and the others with a large portion of smooth area,respectively.Thus,the proposed scheme achieves significant improvement against the state-of-the-art leveraging the 2-D Markov source model at the receiver and is comparable or somewhat inferior to that using the resolution-progressive strategy in recovery.

Computer Programs for Prediction of Mining Area Deformation with Time Factor Taken into Consideration

This paper discussed the current of works on computerisation of all problems related to mining subsidence, including the time factor,carried out in the Division of Mining Geodesy of Technical University of Silesia, Poland. First, the formulas implemented in the programs were presented. These formulas considerably increase the description accuracy of final deformations by taking into uncaved strip along extraction rib (extraction margin). They also improve the deformation description of areas located far from the extraction place. Then, the research results aiming to improving the description of deformation with time were introduced. Finally, the Windows based version of the program for the creation of mining geological opinions were presented in the form accepted by Mining Offices of Poland.

Identification of normalization factors for quantitative realtime RT-PCR analysis of gene expression in Pacific abalone Haliotis discus hannai

Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is widely used in studies of gene expression. In most of these studies, housekeeping genes are used as internal references without validation. To identify appropriate reference genes for qRT-PCR in Pacific abalone Haliotis discus hannai, we examined the transcription stability of six housekeeping genes in abalone tissues in the presence and absence of bacterial infection. For this purpose, abalone were infected with the bacterial pathogen Fibrio anguillarum for 12 h and 48 h. The mRNA levels of the housekeeping genes in five tissues （digestive glands, foot muscle, gill, hemocyte, and mantle） were determined by qRT-PCR. The PCR data was subsequently analyzed with the geNorm and NormFinder algorithms. The results show that in the absence of bacterial infection, elongation factor-l-alpha and beta-actin were the most stably expressed genes in all tissues, and thus are suitable as cross-tissue type normalization factors. However, we did not identify any universal reference genes post infection because the most stable genes varied between tissue types. Furthermore, for most tissues, the optimal reference genes identified by both algorithms at 12 h and 48 h post-infection differed. These results indicate that bacterial infection induced significant changes in the expression of abalone housekeeping genes in a manner that is dependent on tissue type and duration of infection. As a result, different normalization factors must be used for different tissues at different infection points.

Feature Extraction and Recognition for Rolling Element Bearing Fault Utilizing Short-Time Fourier Transform and Non-negative Matrix Factorization

Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, thc time-frequency analysis is often applied to describe the local information of these unstable signals smartly. However, it is difficult to classitythe high dimensional feature matrix directly because of too large dimensions for many classifiers. This paper combines the concepts of time-frequency distribution（TFD） with non-negative matrix factorization（NMF）, and proposes a novel TFD matrix factorization method to enhance representation and identification of bearing fault. Throughout this method, the TFD of a vibration signal is firstly accomplished to describe the localized faults with short-time Fourier transform（STFT）. Then, the supervised NMF mapping is adopted to extract the fault features from TFD. Meanwhile, the fault samples can be clustered and recognized automatically by using the clustering property of NMF. The proposed method takes advantages of the NMF in the parts-based representation and the adaptive clustering. The localized fault features of interest can be extracted as well. To evaluate the performance of the proposed method, the 9 kinds of the bearing fault on a test bench is performed. The proposed method can effectively identify the fault severity and different fault types. Moreover, in comparison with the artificial neural network（ANN）, NMF yields 99.3% mean accuracy which is much superior to ANN. This research presents a simple and practical resolution for the fault diagnosis problem of rolling element bearing in high dimensional feature space.

Analysis of the Main Factors Influencing Food Production in China Based on Time Series Trend Chart

Based on the annual sample data on food production in China since the reform and opening up,we select 8 main factors influencing the total food production( growing area,application rate of chemical fertilizer,effective irrigation area,the affected area,total machinery power,food production cost index,food production price index,financial funds for supporting agriculture,farmers and countryside),and put them into categories of material input,resources and environment,and policy factors. Using the factor analysis,we carry out the multi-angle analysis of these typical influencing factors one by one through the time series trend chart. It is found that application rate of chemical fertilizer,the growing area of food crops and drought-affected area become the key factors affecting food production. On this basis,we set forth the corresponding recommendations for improving the comprehensive food production capacity.

Phylogenetic diversity of eastern Asia-eastern North America disjunct plants is mainly associated with divergence time

The underlying causes of biodiversity disparities among geographic regions have long been a fundamental theme in ecology and evolution.However,the patterns of phylogenetic diversity(PD) and phylogenetic beta diversity(PBD) of congeners that are disjunctly distributed between eastern Asia-eastern North America(EA-ENA disjuncts) and their associated factors remain unknown.Here we investigated the standardized effect size of PD(SES-PD),PBD,and potentially associated factors in 11natural mixed forest sites(five in EA and six in ENA) where abundant EA-ENA disjuncts occur.We found that the disjuncts in ENA possessed higher SES-PD than those in EA at the continental scale(1.96vs-1.12),even though the number of disjunct species in ENA is much lower than in EA(128 vs 263).SESPD of the EA-ENA disjuncts tended to decrease with increasing latitude in 11 sites.The latitudinal diversity gradient of SES-PD was stronger in EA sites than in ENA sites.Based on the unweighted unique fraction metric(UniFrac) distance and the phylogenetic community dissimilarity,PBD showed that the two northern sites in EA were more similar to the six-site ENA group than to the remaining southern EA sites.Based on the standardized effect size of mean pairwise distances(SES-MPD),nine of eleven studied sites showed a neutral community structure(-1.96 ≤SES-MPD ≤1.96).Both Pearson’s r and structural equation modeling suggested that SES-PD of the EA-ENA disjuncts was mostly associated with mean divergence time.Moreover,SES-PD of the EA-ENA disjuncts was positively correlated with temperaturerelated climatic factors,although negatively correlated with mean diversification rate and community structure.By applying approaches from phylogenetics and community ecology,our work sheds light on historical patterns of the EA-ENA disjunction and paves the way for further research.

Least-squares reverse time migration method using the factorization of the Hessian matrix

Least-squares reverse time migration(LSRTM)can eliminate imaging artifacts in an iterative way based on the concept of inversion,and it can restore imaging amplitude step by step.LSRTM can provide a high-resolution migration section and can be applied to irregular and poor-quality seismic data and achieve good results.Steeply dipping refl ectors and complex faults are imaged by using wavefi eld extrapolation based on a two-way wave equation.However,the high computational cost limits the method’s application in practice.A fast approach to realize LSRTM in the imaging domain is provided in this paper to reduce the computational cost signifi cantly and enhance its computational effi ciency.The method uses the Kronecker decomposition algorithm to estimate the Hessian matrix.A low-rank matrix can be used to calculate the Kronecker factor,which involves the calculation of Green’s function at the source and receiver point.The approach also avoids the direct construction of the whole Hessian matrix.Factorization-based LSRTM calculates the production of low-rank matrices instead of repeatedly calculating migration and demigration.Unlike traditional LSRTM,factorization-based LSRTM can reduce calculation costs considerably while maintaining comparable imaging quality.While having the same imaging eff ect,factorization-based LSRTM consumes half the running time of conventional LSRTM.In this regard,the application of factorization-based LSRTM has a promising advantage in reducing the computational cost.Ambient noise caused by this method can be removed by applying a commonly used fi ltering method without signifi cantly degrading the imaging quality.

Study of Factors Causing Time and Cost Overrun in Pre-Construction Project (A Case Study of Malaysia)

Cost and time overrun are the key troubles of any improvement ventures. These troubles are inflicting the terrible end result in the development of kingdom monetary improvement and thriving. To overcome these problems, the?paper examines predominant impact on elements causing the mission postponement and cost. A poll review was led for the situation study embracing various information-gathering procedures. The discoveries from the contextual investigation uncovered that the most persuasive factors in Malaysia:?1) contractor’s inappropriate arranging, 2) poor site the board, 3) deficient contractual worker experience,?are the most powerful factors. This paper has likewise broken down the normal and least effective of the postpone variables causing task deferral and cost overrun in Malaysia. It likewise infers that there are various measures as per the idea of deferring components to decrease the effect on task postponement and cost overruns in the development industry.?There are significant factors in the control of time overrun that would be actual thought related to know and tackle in great impact to improvement rate which may additionally no capacity that be recovered. Thirty (30) massive development extensions in Malaysia were exceptional coping with time overrun at some stage in development. Out of 30 undertakings, 17 (56.67%) ventures had been introduced by using 1100 days’ time overrun, 5 (16.67%) extensions in the middle of a hundred and one to 200 days, 5 (16.67%) ventures?201 to 300 days while three (10%) ventures have been deferred for timeframe over 300 days.

A Novel Hybrid Encryption Method Based on Honey Encryption and Advanced DNA Encoding Scheme in Key Generation

Nowadays, increased information capacity and transmission processes make information security a difficult problem. As a result, most researchers employ encryption and decryption algorithms to enhance information security domains. As it progresses, new encryption methods are being used for information security. In this paper, a hybrid encryption algorithm that combines the honey encryption algorithm and an advanced DNA encoding scheme in key generation is presented. Deoxyribonucleic Acid (DNA) achieves maximal protection and powerful security with high capacity and low modification rate, it is currently being investigated as a potential carrier for information security. Honey Encryption (HE) is an important encryption method for security systems and can strongly prevent brute force attacks. However, the traditional honeyword encryption has a message space limitation problem in the message distribution process. Therefore, we use an improved honey encryption algorithm in our proposed system. By combining the benefits of the DNA-based encoding algorithm with the improved Honey encryption algorithm, a new hybrid method is created in the proposed system. In this paper, five different lookup tables are created in the DNA encoding scheme in key generation. The improved Honey encryption algorithm based on the DNA encoding scheme in key generation is discussed in detail. The passwords are generated as the keys by using the DNA methods based on five different lookup tables, and the disease names are the input messages that are encoded by using the honey encryption process. This hybrid method can reduce the storage overhead problem in the DNA method by applying the five different lookup tables and can reduce time complexity in the existing honey encryption process.