Fraud detection using fraud triangle risk factors

The objective of this study is to identify the financial statement fraud factors and rank the relative importance. First, this study reviews the previous studies to identify the possible fraud indicators. Expert questionnaires are distributed next. After questionnaires are collected, Lawshe’s approach is employed to eliminate these factors whose CVR (content validity ratio) values do not meet the criteria. Further, the remaining 32 factors are reviewed by experts to be the measurements suitable for the assessment of fraud detection. The Analytic Hierarchy Process (AHP) is utilized to determine the relative weights of the individual items. The result of AHP shows that the most important dimension is Pressure/Incentive and the least one is Attitude/rationalization. In addition, the top five important measurements are “Poor performance”, “The need for external financing”, “Financial distress”, “Insufficient board oversight”, and “Competition or market saturation”. The result provides a significant advantage to auditors and managers in enhancing the efficiency of fraud detection and critical evaluation.     

基于熵权-逼近理想解排序法结合体外模拟消化评价功能性水稻品质

目的 探究不同品种功能性水稻的品质差异性指标,并进行综合品质评价。方法 以来源于咸宁市农业科学院的7种功能性水稻为研究对象,对其7项基本营养成分、9种矿物质元素含量、3类淀粉含量和1种血糖预测指数共计20项营养品质指标进行对比分析,在利用正交偏最小二乘法-判别分析(orthogonal partial least-squaresdiscriminationanalysis,OPLS-DA)筛选重要差异性指标的基础上,建立熵权-逼近理想解排序法(technique for order preference by similarity to ideal solution, TOPSIS)模型对7种功能性水稻的综合品质进行评价。结果 不同品种功能性水稻的基本营养成分在较小范围内波动,但钾元素含量和淀粉含量的变化范围较大,其中水稻GN 7、GN 5、GN 6在钾元素含量方面表现较好,水稻GN 4、GN 1、GN 3抗性淀粉含量最高,预估血糖生成指数(estimated glycemic index, eGI)值更低,抗消化能力优于其他品种。OPLS-DA分析筛选出锌、钠、钾、抗性淀粉、钙、镁、...     

Hierarchical Deep Neural Network for Image Captioning

Neural Processing Letters - Automatically describing image content with natural language is a fundamental challenge for computer vision community. General methods used visual information to...     

Redox Imbalance Triggered Intratumoral Cascade Reaction for Tumor “turn on” Imaging and Synergistic Therapy

The redox homeostasis in tumors enhances their antioxidant defense ability, limiting reactive oxygen species mediated tumor therapy efficacy. The development of strategies for specific and continuous disruption of the redox homeostasis in tumor cells facilitates the improvement of the cancer therapeutic effect by promoting the apoptosis of tumor cells. Herein, a responsively biodegradable targeting multifunctional integrated nanosphere (HDMn-QDs/PEG-FA) is designed to enhance the anti-tumor efficacy by triggering intratumoral cascade reactions to effectively disrupt intracellular redox homeostasis. Once HDMn-QDs/PEG-FA enters tumor cells, manganese dioxide (MnO₂) shell on the surface of nanosphere consumes glutathione (GSH) to produce Mn²⁺, enabling enhanced chemodynamic therapy (CDT) via a Fenton-like reaction and T₁-weighted magnetic resonance imaging. Meanwhile, the degradation of MnO₂ can also cause the fluorescence recovery of quantum dots conjugated on the surface of the shell, realizing “turn-on” fluorescence imaging. In addition, the doxorubicin is released because of the cleavage of the embedded S S bond in the hybrid core framework by GSH. A superior synergistic therapeutic efficiency combined CDT and chemotherapy is shown by HDMn-QDs/PEG-FA in vivo. The tumor-inhibition rate reaches to 94.8% and does not cause normal tissue damage due to the good targeting and tumor microenvironment-specific response.     

高可靠直线位移传感器

介绍了新型的直线位移传感器的设计原理、电路设计及机械结构设计,详细分析了传感器的性能特点以及为此所采取的相应技术措施,并对传感器的应用前景进行了论述。     

View-based 3D model retrieval via supervised multi-view feature learning

With the development of the processing technologies of 3D model and the increasing of 3D model in different application flieds, 3D model retrieval is attracting more and more people’s attention. In order to handle this problem, most of approaches focus on the feature extraction form different virtual view. It is hard to guarantee the robustness and also ignore the correlation between both views. Thus, we propose an effective view-based 3D model retrieval method via supervised multi-view feature learning (SMFL). First, the subspace dimension of viusal feature is generated through Singular Value Decomposition (SVD) algorithm. This step is used to select main information from multi-view in order to reduce the final amount of calculation; Secondly, we consider the relationship of multi-view from same class and the correlation between two different classes to make the feature mapping in order to reduce the different of views from the same class and increase the different of views from the difference class; Finally, the projection mapping corresponding to the inner product of each 3D model helps to calculate the similarities between two different 3D models. The extensive experiments are conducted on popular ETH, NTU, MV-RED and PSB 3D model datasets with Zernike moments. The comparative results or The experimental results with existing 3D model retrieval methods show the superiority of the proposed method.     

Vacuum-steam pulsed blanching: An emerging method to enhance texture softening,drying behavior and physicochemical properties of Cornus officinalis

Vacuum steam pulsed blanching (VSPB) was employed as a novel blanching technology on Cornus officinalis to soften the tissue for subsequent coring and dehydration. The current work aims to explore its effect on mass transfer behavior, PPO inactivation, drying characteristics, physicochemical properties, antioxidant capacity, and microstructure of C. officinalis. Results showed that VSPB increased water loss, decreased solid gain, and increased weight reduction with increased blanching cycles. Besides, VSPB significantly changed physical properties and extensively reduced drying time which was attributed to the cell wall components dissolving and cell turgor pressure decreasing, also verified by observing microstructure alteration. PPO was completely denatured after blanching in 6 cycles, but phenolic compounds were still diffused or degraded. Notably, the content of flavonoids and antioxidant capacity significantly increased compared to fresh samples probably due to increased extractability caused by the disrupting cell structure. Besides, the carotenoids and ascorbic acid could be well preserved.     

可信网络连接的安全量化分析与协议改进

可信网络连接(TNC)被认为是可信的网络体系结构的重要部分,随着TNC研究和应用的不断深入,TNC架构自身的安全性问题变得更加至关重要.文中重点研究TNC协议架构的安全性问题,首先提出了一种针对TNC协议的基于半马尔可夫过程的安全性量化分析方法;其次针对TNC完整性验证和访问授权过程中存在的安全威胁和漏洞,提出了一套安全性增强机制,并通过安全量化分析方法进行了验证.最后利用Intel IXP2400网络处理器搭建了TNC原型系统,为文中提出的改进机制和系统框架提供了安全量化验证的实际平台.     

基于自编码器的网络游戏流量分类

加密和动态端口技术使传统的流量分类技术不能满足网络游戏识别的性能需求, 本文提出了一种基于自编码器降维的端到端流量分类模型, 实现网络游戏流量的准确识别. 首先将原始流量预处理成784 B的一维会话流向量, 利用编码器进行无监督降维, 去除无效特征; 接着探索构建卷积神经网络与LSTM网络并联算法, 对降维后的样本进行空间和时序特征的提取和融合, 最后利用融合特征进行分类. 在自建的游戏流量数据集和公开数据集上测试, 本文模型在网络游戏流量识别方面达到了97.68%的准确率; 与传统端到端的网络流量分类模型相比, 本文所设计的模型更加轻量化, 具有实用性, 并且能够在资源有限的设备中方便部署.