Measuring higher education performance in Brazil: government indicators of performance vs ideal solution efficiency measures

PurposeThis study extends the educational institutions' performance and efficiency literature by examining Brazil's Federal Institute of Education, Science and Technology (FIEST), which consists of educational units throughout the country that span several levels of education.Design/methodology/approachThe authors build and analyze a covariance matrix consisting of both a group of efficiency measures and a group of performance indicators used by Brazil's Ministry of Education (BME). The values in the covariance matrix are maximized through application of the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS), in which the weights of each variable are optimized in order to capture the direction of the relationship between the two sets of efficiency measures.FindingsAlthough the authors find that the collective efficiency of the educational units analyzed did not change during the period of study, the analysis reveals that government indicators of performance do not exhibit a strong relationship to the ideal solution efficiency measures used in this study.Originality/valueThis study extends the educational institution efficiency literature by examining Brazil's FIEST, which consists of 40 educational units throughout the country that spans several levels of education, from upper high school vocational courses to higher degrees.

An Universal Adversarial Attack Method Based on Spherical Projection

Adversarial attack on neural networks has become an important problem restricting its security applications, and among adversarial attacks oriented towards the sample set, the universal perturbation design causing most sample output errors is critical to the study. This paper takes the neural network for image classification as the research object, summarizes the existing universal perturbation generation algorithm, proposes a universal perturbation generation algorithm combining batch stochastic gradient rise and spherical projection search, achieves loss function reduction through the iterative training of stochastic gradient rise in batch samples, and limits the universal perturbation search to a high-dimensional sphere with radius [Formula: see text] to reduce the search space of universal perturbation. Moreover, the regularized technology is introduced to improve the generation quality of universal perturbations. The experimental results show that compared with the baseline algorithm, the attack success rate increases by more than 10%, the solution efficiency of universal perturbation is improved by one order of magnitude, and the quality controllability of universal perturbation is better.

Feeder Scheduling and Container Transportation with the Factors of Draught and Bridge in the Yangtze River, China

Inland shipping in the Yangtze River in China has become very prosperous, making feeder scheduling and container transportation increasingly difficult for feeder operators. This research analyzed the decision-making of container transportation businesses in feeder companies operating between Shanghai Port and inland ports along the Yangtze River in China. The research considered the complexity of the natural conditions and water channels, including the draught limitations and the height of the bridges over the river. To analyze ways to increase the effectiveness of shipping containers from Shanghai Port into inland river ports along the Yangtze River, we built a mixed integer nonlinear programming (MINLP) model to minimize the total operating cost and determine the most effective departure time of each feeder. After linearizing the model, we designed a particle swarm optimization (PSO) algorithm to increase solution efficiency and introduced a taboo list and aspiration criterion of a Taboo Search (TS) algorithm to improve the PSO algorithm. Finally, we verified the accuracy of the model and the efficiency of the algorithms using numerical experiments. The research provides theoretical guidance for feeder operators and inland river shipping companies.

Noise-Immune Labels of Residual Codes for Improving Solution Efficiency to Packet Overflow in an Optical Label-Switched Buffer

In this paper, an optical buffering solution based on label switching is proposed, where packets are buffered by identifying and renewing the light labels of pseudo-orthogonal codes. The buffer overflow occurs when label switching fails to perform on the queued packets due to the insufficient labels. Assigning an increased code number to the buffer could reduce the overflow effect, but the decoder noise mitigates its efficiency. Therefore, we study a noise-immune labeling method of residual function by advancing the correlation properties of the existing codes. The proposed label-switching scheme improves the solution efficiency to buffer overflow as a lower code-error probability can be reached. Moreover, multiple label codes can be simultaneously generated from a shared light source to achieve a power-efficient buffer structure.

EFFICIENCY OF DEVELOPMENT AND IMPLEMENTATION MANAGEMENT SOLUTIONS

In conditions of intensive economic variability, the decision-maker needs a quick adaptation to the external environment. The main goal of the article is the development, implementation and control of an effective management solution. Efficiency is understood as such a management decision that contributes to the continuation of the economic structure's activity. External interaction of the economic structure with state authorities allows making such management decisions that are able to solve the problems that have arisen, as well as move to a new level of innovative development, for example, by modernizing production; subsidizing innovative industries and technologies; infrastructure and road development; implementation of tax preferences, benefits, etc. The article contains a list of services provided by the Ministry of Economic Development of the Republic of Bashkortostan to stimulate a favorable investment climate. Despite the expanded package of services provided by public authorities, small and medium-sized businesses do not show active cooperation, including in the form of participation in grants or competitions aimed at developing the region. To develop and implement an effective management solution, the internal policy of the organization should be based on objective interaction and mutual understanding between employees, departments, departments, sectors, etc. The key to the success of an economic structure is based on the timely receipt of reliable information, which is an effective basis for the continuation of its life. The information archive bank is a reliable assistant to the person making management decisions. In-depth analysis of archival information allows us to evaluate the decisions made in past years, develop scenarios and choose the most optimal option aimed at ensuring the life of the economic structure in the market in the future. As a scenario progresses, adjusting it is integral to achieving the best possible effect. In turn, the clear position of all participants in the process, starting with the implementation of a managerial decision and timely control, guarantees the achievement of the set goal.

Efficient Planning and Solving Algorithm of S -Shape Acceleration and Deceleration

S -shape acceleration and deceleration are the most widely used flexible acceleration and deceleration method in the current CNC system, but its velocity solution equation contains irrational terms, which create a more complicated solution process. When analyzing the solution process of the S -shape acceleration and deceleration directly, using a traditional numerical solution method, the phenomenon of “solving the interval jump” arises, which is the main reason for low efficiency and poor stability of the solution. According to the S -curve profile and solution, the concept of separating the curve profile recognition from the velocity solution was proposed, and a method of quickly identifying the interval of the solution location was introduced. Through the method mentioned above, the complete acceleration and deceleration curve parameters can be obtained through a one-time plan and a one-time solution, and the solution efficiency and stability are guaranteed; solving the Newton problem depends too much on the initial value of Newton velocity, which not only retains the speed advantage of the Newton method but also uses the downhill factor to ensure its convergence. Through the simulation comparison and analysis, the efficiency, stability, and universality of the method are verified.

A Proposed Extended Version of the Hadi-Vencheh Model to Improve Multiple-Criteria ABC Inventory Classification

The ABC classification problem is approached as a ranking problem by the most current classification models; that is, a group of inventory items is expressed according to its overall weighted score of criteria in descending order. In this paper, we present an extended version of the Hadi-Vencheh model for multiple-criteria ABC inventory classification. The proposed model is one based on the nonlinear weighted product method (WPM), which determines a common set of weights for all items. Our proposed nonlinear WPM incorporates multiple criteria with different measured units without converting the performance of each inventory item, in terms of converting each criterion into a normalized attribute value, thereby providing an improvement over the model proposed by Hadi-Vencheh. Our study mainly includes various criteria for ABC classification and demonstrates an efficient algorithm for solving nonlinear programming problems, in which the feasible solution set does not have to be convex. The algorithm presented in this study substantially improves the solution efficiency of the canonical coordinates method (CCM) algorithm when applied to large-scale, nonlinear programming problems. The modified algorithm was tested to compare our proposed model results to the results derived using the Hadi-Vencheh model and demonstrate the algorithm’s efficacy. The practical objectives of the study were to develop an efficient nonlinear optimization solver by optimizing the quality of existing solutions, thus improving time and space efficiency.

A Proposed Extended Version of the Hadi-Vencheh Model to Improve Multiple Criteria ABC Inventory Classification

In this paper, we present an extended version of the Hadi-Vencheh model for multiple criteria ABC inventory classification. The proposed model is a nonlinear weighted product model (WPM) which determines a common set of weights for all the items. Our proposed nonlinear WPM incorporates multiple criteria with different measure units, without converting the performance of each inventory item in terms of each criterion into a normalized attribute value, thereby providing an improvement over the model proposed by Hadi-Vencheh. Our study mainly includes various criteria for ABC classification, and demonstrates an efficient algorithm for solving nonlinear programming problems in which the feasible solution set does not have to be convex. The algorithm presented in this study improves the solution efficiency of the Canonical Coordinates Method (CCM) algorithm substantially when applied to large scale, nonlinear programming problems. The modified algorithm was tested to compare our proposed model results to the results derived using the Hadi-Vencheh model and demonstrate the algorithm's efficacy. The practical implications of the study are to develop an efficient nonlinear optimization solver by optimizing the quality of existing solutions, thus improving time and space efficiency.