Voluntary Disclosure and Earnings Management

Discretion pervades the accounting rules. Proponents argue that allowing discretion enables managers to incorporate more information in their disclosures, while opponents believe that managers can abuse discretion and engage in earnings management at the expense of shareholders. We explicitly model accounting discretion and earnings management in a disclosure setting motivated by Shin (1994). We use this setting to study the interaction between management’s voluntary disclosure and the subsequent mandatory disclosure of value-relevant information. We show that, in equilibrium, allowing the manager to have some discretion over the mandatory financial reports may enhance the informativeness of the more-timely voluntary disclosure. However, allowing too much discretion for earnings management may result in less informative voluntary disclosure. Thus there may be a hidden benefit of granting some (but not too much) discretion in firms’ mandatory financial statements

Method of Reservoir Optimal Operation Based on Improved Simulated Annealing Genetic Algorithm

According to the specific circumstances of Wanjiazhai Reservoir, establish a reservoir optimal scheduling nonlinear mathematical model with a maximum generation capacity target, this paper uses an improved simulated annealing genetic algorithm to solve the model. The algorithm is in view of the defects of the traditional simulated annealing genetic algorithm to improve the algorithm from three aspects: introducing the niche technology, using adaptive crossover and mutation strategy, using the elitist strategy during the selection. Through examples are calculated and compared with the traditional simulated annealing genetic algorithm, the improved algorithm effectively overcomes the stagnation phenomenon, to enhance the global search ability. Its optimization performance is better than that of the traditional simulated annealing genetic algorithm

M3PT: A Multi-Modal Model for POI Tagging

POI tagging aims to annotate a point of interest (POI) with some informative tags, which facilitates many services related to POIs, including search, recommendation, and so on. Most of the existing solutions neglect the significance of POI images and seldom fuse the textual and visual features of POIs, resulting in suboptimal tagging performance. In this paper, we propose a novel Multi-Modal Model for POI Tagging, namely M3PT, which achieves enhanced POI tagging through fusing the target POI's textual and visual features, and the precise matching between the multi-modal representations. Specifically, we first devise a domain-adaptive image encoder (DIE) to obtain the image embeddings aligned to their gold tags' semantics. Then, in M3PT's text-image fusion module (TIF), the textual and visual representations are fully fused into the POIs' content embeddings for the subsequent matching. In addition, we adopt a contrastive learning strategy to further bridge the gap between the representations of different modalities. To evaluate the tagging models' performance, we have constructed two high-quality POI tagging datasets from the real-world business scenario of Ali Fliggy. Upon the datasets, we conducted the extensive experiments to demonstrate our model's advantage over the baselines of uni-modality and multi-modality, and verify the effectiveness of important components in M3PT, including DIE, TIF and the contrastive learning strategy.Comment: Accepted by KDD 202

A Large-Scale Particle Image Velocimetry System Based on Dual-camera Field of View Stitching

Large-Scale Particle Image Velocimetry (LSPIV) is an effective method for the measurement of the river surface flow velocity. For the wide cross-section river, in the near-field area of river surface image there are small and clear targets. But the flow tracers are almost invisible in the far-field area because of the resolution limit of one single video camera, which makes it difficult to complete the velocimetry task. So a dual-camera based LSPIV system has been developed for monitoring the wide cross-section river. This system is based on two digital Internet Protocol (IP) video cameras either of which captures more than half of the river surface with high resolution. And then the developed system stitches the two images into one covering the entire wide cross-section rivers. In the far field of river, the accuracy of the vector increases from 20.4 % to 80.4 %

Packet Classification Algorithms: From Theory to Practice

Abstract—During the past decade, the packet classification problem has been widely studied to accelerate network applications such as access control, traffic engineering and intrusion detection. In our research, we found that although a great number of packet classification algorithms have been proposed in recent years, unfortunately most of them stagnate in mathematical analysis or software simulation stages and few of them have been implemented in commercial products as a generic solution. To fill the gap between theory and practice, in this paper, we propose a novel packet classification algorithm named HyperSplit. Compared to the well-known HiCuts and HSM algorithms, HyperSplit achieves superior performance in terms of classification speed, memory usage and preprocessing time. The practicability of the proposed algorithm is manifested by two facts in our test: HyperSplit is the only algorithm that can successfully handle all the rule sets; HyperSplit is also the only algorithm that reaches more than 6Gbps throughput on the Octeon3860 multi-core platform when tested with 64-byte Ethernet packets against 10K ACL rules. Keywords-algorithm; classification; multi-core; performance I

Method of Optimal Scheduling of Cascade Reservoirs based on Improved Chaotic Ant Colony Algorithm

On the basis of the analysis of the basic information of the river basin reservoirs and application of chaotic ant swarm algorithm, the medium-and long-term optimization operation model is established, which regards the maximum annual generation capacity of the cascade hydropower stations as the main purpose. The simulation result shows the algorithm improves the total annual power generation of the cascade reservoirs, and is better than the basic chaotic ant colony solving method of reservoir operation model, finally provides an effective solution to solve the cascade reservoirs optimization operation problem

Method of Optimal Scheduling of Cascade Reservoirs based on Improved Chaotic Ant Colony Algorithm

Abstract: On the basis of the analysis of the basic information of the river basin reservoirs and application of chaotic ant swarm algorithm, the medium-and long-term optimization operation model is established, which regards the maximum annual generation capacity of the cascade hydropower stations as the main purpose. The simulation result shows the algorithm improves the total annual power generation of the cascade reservoirs, and is better than the basic chaotic ant colony solving method of reservoir operation model, finally provides an effective solution to solve the cascade reservoirs optimization operation problem

N 2

Using static chambers and gas chromatography, nitrous oxide (N2O) fluxes from an apple orchard soil in the Bohai Bay region of China were measured from February 2010 to February 2011. In this study, two nitrogen (N) fertilizer treatments were designed—without (CK) or with (SN) synthetic N fertilizers (800 kg N ha−1). The annual cumulative N2O emissions from CK and SN were 34.6 ± 3.0 (mean ± standard error) and 44.3 ± 6.0 kg N2O–N ha−1, respectively. Such high emissions resulted from the intensive N fertilization in the experimental and previous years. The direct emission factor (EFd) of N2O induced by the applied synthetic N fertilizers was 1.2%. The EFd is within the range of previous studies carried out in other croplands, which suggests that it is reasonable to estimate regional N2O emissions from apple orchards using the EFd obtained in other croplands. In addition, significant positive correlations existed between N2O fluxes and soil temperatures or soil dissolved organic carbon contents