Adaptive–interpolative binarization with stroke preservation for restoration of faint characters in degraded documents

A novel technique for binarization with stroke preservation of faint characters in degraded documents is proposed. It works in a multi-scale framework with an adaptive–interpolative thresholding technique. Instead of computing a global threshold value, it computes the local threshold values for a small set of grid points by observing the intensity pattern of the pixels lying in the concerned grid cells. Estimated thresholds are used, in turn, to compute the threshold values of all the remaining pixels using a fast-yet-efficient interpolation procedure. To handle noises in degraded images, this grid-based adaptive thresholding is applied in successively reducing scales to obtain the near-optimal binarization as a set of connected components. After a post-processing meant for stroke preservation with these connected components, we get the final output. Exhaustive experimentation and comparison with other existing methods have been successfully carried out with benchmark datasets and also with our own datasets.     

无可信第三方的数据匿名化收集协议

针对半诚信的数据收集者对包含敏感属性(SA)数据收集和使用过程中可能造成隐私泄露问题,该文在传统模型中增加实时的数据领导者,并基于改进模型提出一个隐私保护的数据收集协议,确保无可信第三方假设前提下,数据收集者最大化数据效用只能建立在K匿名处理过的数据基础上。数据拥有者分布协作的方式参与协议流程,实现了准标识(QI)匿名化后SA的传输,降低了数据收集者通过QI关联准确SA值的概率,减弱内部标识揭露造成隐私泄露风险;通过树形编码结构将SA的编码值分为随机锚点和补偿距离两份份额,由K匿名形成的等价类成员选举获取两个数据领导者,分别对两份份额进行聚集和转发,解除唯一性的网络标识和SA值的关联,有效防止外部标识揭露造成的隐私泄露;建立符合该协议特性的形式化规则并对协议进行安全分析,证明了协议满足隐私保护需求。     

基于雾计算的智能电表用户虚拟环隐私保护方案

作为智能电网的基础组件,智能电表(SMS)可以定期向电力公司报告用户的详细用电量数据。但是智能电表也带来了一些安全问题,比如用户隐私泄露。该文提出了一种基于虚拟环的隐私保护方案,可以提供用电数据和用户身份的隐私,使攻击者无法知道匹配电力数据与用户身份的关系。在所提方案中,智能电表可以利用其虚拟环成员身份对其真实身份进行匿名化,并利用非对称加密和Paillier同态系统对其获得的用电量数据生成密文数据;然后智能电表将密文数据发送给其连接的雾节点,雾节点定期采集其管理的智能电表的密文数据。同时,雾节点对这些智能电表的虚拟环身份进行验证,然后将收集到的密文数据聚合并发送给控制中心;最后控制中心对聚合后的密文进行解密,得到用电量数据。实验结果表明所提方案在计算和通信成本上具有一定的优势。     

Users’ Preferences for Smart Home Automation – Investigating Aspects of Privacy and Trust

Smart home automation provides residents with relief and convenience in everyday life and allows for self-determined aging in place. Yet, market penetration is offset by user concerns related to privacy and trust issues: With increasing system complexity, users may perceive a loss of control and fear technical unreliability. While barriers to acceptance in terms of privacy and trust are well understood when considered separately, they are hardly investigated in conjunction so far. We conducted a quantitative study using Adaptive Choice-Based Conjoint Analysis via an online questionnaire. We explored how aspects of privacy and trust determine the willingness to use smart homes from the perspective of (future) users (n = 137, 18 to 64 years of age), and also with respect to the level of automation and application field. Results show that semi-automated systems are rather preferred than fully automated smart home technology. The perceived reliability of automation is the most important acceptance determinant, followed by the location of data storage. Whereas the awareness to use (e.g., recommendations), the type of data, and application field are less important factors for the overall willingness to use smart homes. Findings inform scientists in the field of human-automation interaction and technical developers of smart home automation for technology innovation adapted to user needs.     

OW‐SVM: Ontology and whale optimization‐based support vector machine for privacy‐preserved medical data classification in cloud

Cloud is a multitenant architecture that allows the cloud users to share the resources via servers and is used in various applications, including data classification. Data classification is a widely used data mining technique for big data analysis. It helps the learners to discover hidden data patterns by training massive data collected from the real world. Because this trained model is the private asset of an entity, it should be protected from all other noncollaborative entities. Therefore, it is essential to take effective measures to preserve the confidential data. The objective of this paper is to preserve the privacy of the confidential data in the cloud environment by introducing the medical data classification method. In view of that, this paper presents a method for medical data classification using a novel ontology and whale optimization‐based support vector machine (OW‐SVM) approach. Initially, privacy‐preserved data are developed adopting Kronecker product bat approach, and then, ontology is built for the feature selection process. Ontology and whale optimization‐based support vector machine is then proposed by integrating ontology and whale optimization algorithm into SVM, in which ontology and whale optimization algorithm is used for the feasible selection of kernel parameters. The experiment is done using 3 heart disease datasets, such as Cleveland, Switzerland, and Hungarian. In a comparative analysis, the performance of the OW‐SVM approach is compared with that of K‐nearest neighbor, Naive Bayes, decision tree, SVM, and OW‐SVM, using accuracy, sensitivity, specificity, and fitness, as the evaluation metrics. The OW‐SVM approach could achieve maximum performance with accuracy of 83.21%, the sensitivity of 91.49%, specificity of 73%, and fitness of 81.955, outperforming existing comparative techniques.     

单板机在果品贮藏中的应用

介绍了个以ＴＰ８０１单板机为核心的自发式气调贮藏（ＭＡ）自动监控系统的结构、工作原理和功能。该系统投入运行三年，取得了令人满意的效果，改变了传统的人工操作方式，解决了果品高质量节能贮藏的关键技术。     

北部湾盆地流沙港组湖相烃源岩的差异

北部湾盆地是中国近海重要的富油盆地,油气发现主要集中于涠西南凹陷、乌石凹陷和福山凹陷,探明原油地质储量约为4.05×10⁸t,但各个主要凹陷的探明油气地质储量存在显著差异。北部湾盆地各凹陷的油气富集程度与其湖相烃源岩的差异密切相关,从涠西南凹陷到乌石凹陷,再到迈陈凹陷和福山凹陷,古近系流沙港组烃源岩的品质总体下降,烃源岩的有机质丰度降低,有机质类型从以腐泥型为主变成以混合型占优势,烃源岩的生烃潜力下降。分析表明,尽管北部湾盆地流沙港组烃源岩在形成期各凹陷普遍具有较高的古湖泊有机质生产力,但各凹陷的有机质来源仍然存在差异,有机质保存条件也存在差异,从涠西南凹陷到乌石凹陷,再到迈陈凹陷、福山凹陷和海中凹陷,湖相藻类来源的有机质减少,陆生高等植物来源的有机质增加,有机质保存条件具有变差的趋势。     

不同性质原油保存能力评价实验及应用

深层原油保存能力的评价制约着原油勘探的深度下限。为了评价不同性质原油保存能力,以不同性质原油与灰岩介质为对象,通过热模拟实验产物分析,参照基础理论,提出了原油保存指数概念,并以等效镜质体反射率为桥梁,对原油保存能力进行评价。原油保存能力主要受热演化程度控制,等效镜质体反射率VR_o<1.2%,VR_o=1.2%~2.0%和VR_o>2.0%的缓慢裂解、快速裂解和极限裂解阶段保存指数分别降低0.230,0.324和0.350。原油组成的差异决定不同性质原油具有不同的保存能力。轻质油早期保存能力较强,进入裂解门限后,保存能力迅速降低;重质油因较多的杂原子和侧链,致使保存能力呈现早期弱、晚期强的特点,但保存下来多是固体沥青等大分子缩聚物。根据热模拟实验结果预测了塔里木盆地满西地区深层液态烃的保存下限,满西地区奥陶系原油勘探下限深度为8 200 m。     

利用地震品质因子Q比例的分布特征预测南川页岩气藏保存条件

根据地震数据、地质资料和地震属性，开展了南川地区五峰组-龙马溪组下部页岩的地震品质因子Q平面上分布与页岩气保存条件评价研究。针对南川地区页岩气开发中的断裂破碎带，提出了一种获取稳定品质因子Q比例及界限的工作流程和相应的迭代算法。研究表明，地震品质因子Q比例的分布可以快速、直观识别出断裂破碎带的内幕特征与不同类型页岩分布区。其中，断裂破碎带页岩区的品质因子Q比例总体上偏小，大多低于0.2，局部超过0.5，平面上分布杂乱、碎斑状；页岩呈北东向展布的条带，被断裂所撕裂、破碎，保存条件较差。稳定分布的页岩区的品质因子Q比例是较高的，超过0.7，平面变化稳定，没有突变现象，保存条件好。微裂缝发育的页岩区的品质因子Q比例具有渐变的趋势性，品质因子Q比例的分布从该页岩区的边部0.7向中部有规律地减小至0.1，保存条件最佳。实践证明，高产气井大多位于稳定分布的页岩区或内部微裂隙发育的稳定页岩区，地震品质因子Q比例研究方法对页岩气保存评价与开发井优化部署是一个实用工具。     

Hydrocarbon preservation and formation water geochemistry in abnormal pressure system in the Bawu area of Lishu depression,Songliao Basin,China

The hydrocarbon production in the Bawu area of Lishu Depression is high. However, the Bawu area has undergone three main tectonic movements, the strata were strongly uplifted and eroded, and the fractures were extremely developed. The conditions of hydrocarbon preservation have become intricate. In this study, by analyzing isotopes compositions and geochemical features of formation water, and the characteristics of formation pressure, the hydrocarbon preservation can be deduced. The subnormal and lower normal pressure zones (away from Xiaokuan Fault) of Yingcheng and Shahezi Formations are relatively closed and more conducive to hydrocarbon preservation.