Denoising Diffusion Autoencoders are Unified Self-supervised Learners

Inspired by recent advances in diffusion models, which are reminiscent of denoising autoencoders, we investigate whether they can acquire discriminative representations for classification via generative pre-training. This paper shows that the networks in diffusion models, namely denoising diffusion autoencoders (DDAE), are unified self-supervised learners: by pre-training on unconditional image generation, DDAE has already learned strongly linear-separable representations within its intermediate layers without auxiliary encoders, thus making diffusion pre-training emerge as a general approach for generative-and-discriminative dual learning. To validate this, we conduct linear probe and fine-tuning evaluations. Our diffusion-based approach achieves 95.9% and 50.0% linear evaluation accuracies on CIFAR-10 and Tiny-ImageNet, respectively, and is comparable to contrastive learning and masked autoencoders for the first time. Transfer learning from ImageNet also confirms the suitability of DDAE for Vision Transformers, suggesting the potential to scale DDAEs as unified foundation models. Code is available at github.com/FutureXiang/ddae.Comment: ICCV 2023 Ora

Solving a Fully Fuzzy Linear Programming Problem through Compromise Programming

In the current literatures, there are several models of fully fuzzy linear programming (FFLP) problems where all the parameters and variables were fuzzy numbers but the constraints were crisp equality or inequality. In this paper, an FFLP problem with fuzzy equality constraints is discussed, and a method for solving this FFLP problem is also proposed. We first transform the fuzzy equality constraints into the crisp inequality ones using the measure of the similarity, which is interpreted as the feasibility degree of constrains, and then transform the fuzzy objective into two crisp objectives by considering expected value and uncertainty of fuzzy objective. Since the feasibility degree of constrains is in conflict with the optimal value of objective function, we finally construct an auxiliary three-objective linear programming problem, which is solved through a compromise programming approach, to solve the initial FFLP problem. To illustrate the proposed method, two numerical examples are solved

A Multiobjective Programming Method for Ranking All Units Based on Compensatory DEA Model

In order to rank all decision making units (DMUs) on the same basis, this paper proposes a multiobjective programming (MOP) model based on a compensatory data envelopment analysis (DEA) model to derive a common set of weights that can be used for the full ranking of all DMUs. We first revisit a compensatory DEA model for ranking all units, point out the existing problem for solving the model, and present an improved algorithm for which an approximate global optimal solution of the model can be obtained by solving a sequence of linear programming. Then, we applied the key idea of the compensatory DEA model to develop the MOP model in which the objectives are to simultaneously maximize all common weights under constraints that the sum of efficiency values of all DMUs is equal to unity and the sum of all common weights is also equal to unity. In order to solve the MOP model, we transform it into a single objective programming (SOP) model using a fuzzy programming method and solve the SOP model using the proposed approximation algorithm. To illustrate the ranking method using the proposed method, two numerical examples are solved

Organic matter provenance and depositional environment of marine-to-continental mudstones and coals in eastern Ordos Basin, China—Evidence from molecular geochemistry and petrology

Cyclothems, composed of interbedded mudstone, coal and sandstone layers, make up the Taiyuan and Shanxi Formations in the Late Carboniferous to Early Permian in North China under a marine-to-continental depositional environment. The cyclothems act as important fossil energy hosts, such as coalbeds, hydrocarbon source rocks and unconventional natural gas reservoirs. Organic geochemistry and petrology of mudstones and coals in the Taiyuan and Shanxi Formations in the eastern Ordos Basin were studied to reveal the organic matter sources and paleoenvironments. Total organic carbon (TOC) contents vary from 1.1 wt% (mudstone) to 72.6 wt% (coal). The samples are mainly within the oil window, with the Tmax values ranging from 433 to 469 °C. Organic petrology and source biomarkers indicate that the mudstones were sourced from a mixed organic matter input, and terrigenous organic matter predominates over aquatic organic matter. The coals are mostly sourced by terrigenous organic matter inputs. High concentrations of hopanes argue for a strong bacterial input. Some m/z 217 mass chromatograms have peaks at the hopanes' retention times as a result of high hopane to sterane ratios. These hopane-derived peaks do not interfere the identification of the steranes because the hopanes and the steranes have different retention times. Maturity-dependent biomarkers demonstrate that the samples have been thermally mature, which agree with the Tmax values. Anomalously low C29 20S/(20S + 20R) and C29 ββ/(ββ + αα) sterane ratios are present in all the samples, and are interpreted as due to the terrigenous organic matter input or the coal-related depositional environment. In addition, biomarkers and iron sulfide morphology indicate that the organic matter of the mudstones deposited in a proximal setting with shallow, brackish/fresh water bodies. With consideration of preservation of organic matter, the redox conditions are dysoxic. Redox oscillations resulted in the records of oxic conditions in some samples. Finally, the coals and the mudstones mainly generate gas and have poor oil generative potential

Comparative Analysis of Government Subsidy Policies in a Dynamic Green Supply Chain Considering Consumers Preference

Governments formulate different subsidy policies to incentivize manufacturers to produce green products, and these policies may have different subsidy effects. The purpose of this study is to compare and analyze the dynamic effects of different subsidy policies to the manufacturer in a green supply chain composed of a manufacturer and a retailer. Three differential game models, considering the consumers preference, are established under three subsidy policies, and the corresponding optimal equilibrium strategies of the supply chain members are analyzed. An example is used to compare the effects of the three policies under the equal government subsidy expenditure. The study finds that the rankings of indexes to evaluate steady-state subsidy effects under the different subsidy policies are time invariant, and the government can preliminarily evaluate these policies according to different subsidy goals. The rankings of indexes to evaluate phased subsidy effects under these policies are time varying. If both subsidy effects and subsidy efficiencies in steady state are taken into account, the optimal selection paths of subsidy policies in the whole period can be obtained. The subsidy effects of the same policy are amplified under the condition of equal steady-state subsidy expenditure, but the rankings of effect indexes under the different subsidy policies are not affected

Identifying critical success factors in emergency management using a fuzzy DEMATEL method

Since unexpected natural disasters have been causing enormous losses all over the world, emergency management is receiving more and more attention recently. However, most existing studies generally focus on optimization models of specific activities instead of studying the system as a whole. Moreover, the performance of emergency management may be affected by various different factors and it is always difficult for the practitioners to improve all aspects at the same time. In view of the constraint of resources, this paper brings forward an imperative issue on how to enhance emergency management by segmenting complex influencing factors into groups to improve them in a stepwise way. To address this concern involving the vagueness of human judgments, an effective method that combines fuzzy logic and decision-making trial and evaluation laboratory (DEMATEL) is used. Considering the interdependence among factors, this fuzzy DEMATEL method forms a structural model and then visualizes the causal relationships among factors through a cause-effect relationship diagram. Then according to the results of proposed method, critical success factor (CSF) of emergency management is figured out. Finally, 5 CSFs are identified out of 20 influencing factors, and all factors can be achieved in a stepwise way for better promoting the effectiveness and efficiency of emergency management

An effective genetic algorithm for the fleet size and mix vehicle routing problems

This paper studies the fleet size and mix vehicle routing problem (FSMVRP), in which the fleet is heterogeneous and its composition to be determined. We design and implement a genetic algorithm (GA) based heuristic. On a set of twenty benchmark problems it reaches the best-known solution 14 times and finds one new best solution. It also provides a competitive performance in terms of average solution.Genetic algorithm Single parent crossover Local search Fleet size and mix vehicle routing problem

Two-stage DEA for Bank Efficiency Evaluation Considering Shared Input and Unexpected Output Factors

With the increasingly fierce market competition, only by relying on high-quality products and high customer satisfaction can enterprises survive in the fierce competition. Among many evaluation methods, Data Envelopment Analysis (DEA), as a non-parametric statistical method to effectively deal with multi-input and multi-output problems, has received more and more attention in evaluating the relative efficiency of decision-making units. In the process of bank efficiency evaluation based on DEA method, there will be a situation that banks have both dual role factors and unexpected output factors. The Two-stage DEA model provides an effective analysis method to solve the problem of bank efficiency evaluation of complex organizational structure. In order to evaluate the efficiency of unexpected output with uncertain information, a stochastic DEA model of unexpected output is established