A secure encryption method of communication channel based on cloud computing technology

The traditional channel encryption method is interfered by noise signal, which leads to long encryption time and poor security. This paper proposes a communication channel security encryption method based on cloud computing technology. In order to obtain the minimum benefits of the same channel and orthogonal channel in the frequency conversion receiver, the dual input and dual output model is constructed; the influence of time domain and frequency domain on the transmission signal is analyzed, and the nonlinear transmission characteristics of the channel signal are obtained. Through cloud computing technology, the channel transmission characteristics are divided into dynamic parameters and static parameters to realize the key distribution of communication channel under cloud computing technology; the balance factor is used to provide the key for the sorted generators to realize the secure encryption of communication channel. The results show that the average error probability of the proposed method is about 0.275, and the signal-to-noise ratio is between 115 and 118 SNR.

Scene Text Detection Based On Fusion Network

Due to the robustness resulted from scale transformation and unbalanced distribution of training samples in scene text detection task, a new fusion framework TSFnet is proposed in this paper. This framework is composed of Detection Stream, Judge Stream and Fusion Stream. In the Detection Stream, loss balance factor (LBF) is raised to improve the region proposal network (RPN). To predict the global text segmentation map, the algorithm combines regression strategy and case segmentation method. In the Judge Stream, a classification of the samples is proposed based on the Judge Map and the corresponding tags to calculate the overlap rate. As a support of Detection Stream, feature pyramid network is utilized in the algorithm to extract Judge Map and calculate LBF. In the Fusion Stream, a new fusion algorithm is raised. By fusing the output of the two streams, we can position the text area in the natural scene accurately. Finally, the algorithm is experimented on the standard data sets ICDAR 2015 and ICDAR2017-MLT. The test results show that the [Formula: see text] values are 87.8% and 67.57%, respectively, superior to the state-of-the art models. This proves that the algorithm can solve the robustness issues under the unbalance between scale transformation and training data.

Balanced Distribution Adaptation for Metal Oxide Semiconductor Gas Sensor Array Drift Compensation

Drift compensation is an important issue for metal oxide semiconductor (MOS) gas sensor arrays. General machine learning methods require constant calibration and a large amount of label gas data. At the same time, recalibration will cause a lot of costs, and label gas is difficult to obtain in practice. In this paper, a novel drift compensation method based on balanced distribution adaptation (BDA) is proposed. First, the BDA drift compensation method can adjust the conditional distribution and marginal distribution between the two domains through the weight balance factor, thereby more effectively reducing the mismatch between the two domains. When the BDA method performs classification tasks through machine learning, no labeled data is required in the target domain. Then, the particle swarm optimization algorithm is used to improve the accuracy of drift compensation. Individuals in the population are initialized randomly, and their fitness values are calculated. Iterative optimization of the population individuals is conducted until the optimal weight balance factor parameters are calculated. Finally, the BDA method is experimentally verified on the public gas sensor drift data set. Experimental results showed that the BDA method was significantly better than the existing joint distribution adaptation (JDA) method and other standard drift compensation methods such as K-Nearest Neighbor (KNN). In the two setting groups, the recognition accuracy was 4.54% and 1.62% ahead of the JDA method, and 12.23% and 15.83% ahead of the KNN method.

Dynamic balance between demand-and-supply of urban taxis over trajectories

<abstract> <p>Urban taxi serves as an irreplaceable tool in public transportation systems. The balancing of demand-and-supply can be of significant social benefit, for which the equilibrium method for urban taxis, especially with dynamic trip demands, is not well studied yet. In this paper, we formally define the equilibrium problem and propose a coarse-grained dynamic balancing algorithm. It efficiently evaluates the trip demand distribution pattern and schedules supplies to more unbalanced regions. We first propose a density-based blocking algorithm to detect regions that are with more travel demands. A trip demand merging strategy is then proposed, which checks the correlation of trip demands to merge the trips into ones. To reduce the computation load, a lazy trip correlation strategy is devised to speed up the merging process. By calculating the defined balance factor, a scheduling algorithm is proposed to realize the trip merge and supply translocation based balancing approach. We evaluated our approach using a month of global positioning system (GPS) trajectories generated by 13,000 taxis of Shanghai. By learning the spatiotemporal distribution of historical taxi demand-and-supplies, we simulated an inflated trip demand platform. Tested on this platform with extensive experiments, the proposed approach demonstrates its effectiveness and scalability.</p> </abstract>

ANALISIS FAKTOR-FAKTOR WORK-LIFE BALANCE PADA PEGAWAI PT. INDUSTRI TELEKOMUNIKASI INDONESIA (PERSERO) BANDUNG

Companies that manage their human resources professionally will create a balance of work life and personal lives of its employees. This happened at PT. INTI Bandung where the employees already feel a balance between work life and personal life. Thus, the authors conducted this study to determine the work-life balance factor and what was the most dominant factor in the employees of PT. INTI Bandung. The method used in this study is quantitative with descriptive analysis and factor analysis as well as the sampling method that is simple random sampling. The results showed the condition of work-life balance in PT. INTI Bandung has been balanced by proven by the results of the analysis of the questionnaire data that produced a value that reached 77.2%. While the results of the factor analysts indicate that there are four new factors formed, namely the first factor Management of the Work Environment with a contribution value of 32.70%, the second factor Time Management and Role with a contribution value of 13.01%, the third factor Work Time Flexibility and Stress Level with a contribution value of 10.02%, and a fourth factor, Corporate Support with a contribution value of 7.60%. Thus the most dominant work-life balance factor in PT. INTI Bandung is a factor in the Management of Work Environment with a contribution value of 32.70%

Theoretical developments in balance model and models with virtual weight restrictions

The balance model (BM) is a unit invariant model in which takes into account the imposed strategies for DMUs through adding some balance constraints to the basic DEA models in general and the CCR model in particular. Also, balance factor is calculated along with efficiency, effectiveness and similar concepts. The mentioned balance constraints belong to the virtual weight restrictions (VWRs) category. However, to date, the consequences of incorporating weight restrictions (e.g. absolute weight restrictions, assurance regions type I (ARI), assurance regions type II (ARII)) within the classical DEA models have been explored by scholars, but are not considered for virtual weight restrictions. This paper analyses properties of the balance model and subsequently the models with VWRs by an illustrative example. The results show that models with such restrictions correctly maximize the relative efficiency (RE) of the assessed DMU despite the fact that none of the DMUs might be fully efficient (i.e. with efficiency score of 1). In addition, feasibility conditions are discussed. Finally, the proposed method will be applied to assess the branches of a specialized bank of Iran as a real application.

Relevance of Work-Life Balance in India – A Skeptical Analysis among Teaching Professionals

A person has to balance the work and life in all walks of his life. Due to social change in the society, the type of households is changing from the joint family to nuclear family. The family, work, and society demand equal attention and obligation. The person has to balance the work to family interference and family to work interference. The work-life balance has been adopted by various corporate and organization. This paper reviews how various professionals manage work and life. Some factors influence the work-life balance in the day to day life. It is the greatest task for retaining the manpower in an institution. It is important to facilitate the employee to maintain a work-life balance. There are different kinds of professionals who face challenges in managing work-life balance. It is assumed that the teacher with more children finds difficulty in balancing work-life balance than the childless teacher. She may perceive a better work-life balance. The male teachers may experience a higher degree of burnt out than female teachers. These views helped the author to explore the factors involved in balancing work-life balance and to provide suggestions to manage the work-life. The author has taken up empirical study, this paper focuses on understanding the situation of teachers &amp; faculties in terms of Work-life balance, Factor involved in work-life balance, and to provide suggestions to manage the work-life balance in the teaching profession.

Improved cuckoo search algorithm and its application to permutation flow shop scheduling problem

Aiming at the problem that the standard cuckoo search algorithm relies on Levy flights, which leads to the step-size randomness of the search process, a self-adaptive step cuckoo search algorithm based on dynamic balance factor is proposed in our paper. First, two parameters are introduced in our paper, which were iteration number ratio parameter and adaptability ratio parameter. Then, a dynamic balance factor parameter is introduced to adjust the weight number of iteration number ratio parameter and adaptability ratio parameter. Finally, parameter skewness value calculation method and self-adaptive step strategy were proposed combined with the dynamic balance factor. Six typical test functions are used to test the performance of the proposed algorithm, the standard cuckoo search algorithm and the self-adaptive step cuckoo search algorithm which relies only on the iterative times. The test results show that the proposed algorithm had good convergence speed and accuracy. Meanwhile, taking the permutation flow shop scheduling problem as an example, eight operators of Car benchmark class are used as the test data to compare the performance of three algorithms, the effectiveness and superiority of the algorithm in solving the permutation flow shop scheduling problem are verified.