A security framework for cloud-based video surveillance system

Multimedia Tools and Applications - Utilizing cloud services in running large-scale video surveillance systems is not uncommon. However, special attention should be given to data security and...     

A real time cloud-based framework for glaucoma screening using EfficientNet

These days one of the major causes of partial or complete blindness that has affected a majority of people all around the world is glaucoma. Glaucoma is caused as a result of increased fluid pressure inside the optic nerves called intra ocular pressure. A real time cloud-based framework for screening the glaucoma suspect’s retinal fundus images as received by the people on the public cloud, is proposed in this paper. In the proposed framework the existence of glaucoma and analysis of the retinal fundus images is achieved by deep learning technique and convolutional neural network respectively. EfficientNet and UNet++ models are used to identify the presence of glaucoma. On comparing our framework to various state-of-the-art models and quantitative assessment are performing on various benchmark datasets like RIM-ONE and DRISHTI-GS1, it was found that the proposed framework is scalable, location independent, and easily accessible to one and all due to the cloud platform.

     

A system framework for OKP product planning in a cloud-based design environment

Nowadays, one-of-a-kind (OKP) companies, which generally operate in an 'engineer-to-order' business mode, strive to deliver individualized products with quality to achieve customer satisfaction. Thus, an accurate and prompt analysis of customer requirements (CRs) in the early design stage is critical to its success. However, most OKP companies are small or medium-sized enterprises (SMEs). Due to the limited resources and low product planning budget, they often cannot obtain abundant CR information nor can they afford the expense of complicated planning process. To address these issues, a system framework is proposed in support of OKP product planning process in a cloud-based design (CBD) environment. The challenges and future market niches of OKP companies are presented. The comparison of typical distributed systems shows that CBD, which utilizes advanced information technologies and business model, has advantages in providing sufficient resources, decreasing product development time span for OKP companies in a cost-efficient way. This article describes the proposed system architecture, the business interaction process and the information communication among customers, designers and marketing analysts at the product planning stage. To validate the proposed framework, a prototype system module MyProduct is under development in the CBD environment with an illustrative example.     

COWB: A cloud-based framework supporting collaborative knowledge management within biomedical communities

Despite the large acceptance of Semantic Web technologies and their key role in bioinformatics, some concerns begin to emerge about their suitability for supporting the requirements of collaborative environments where a research community shares and creates new knowledge. The paper discusses these concerns and proposes COWB (COllaborative Workspaces in Biomedicine), a framework which supports collaborative knowledge management in the context of biomedical communities. COWB is grounded on a multi-layer ontology-centric model. It harnesses both the semantic knowledge captured from ontologies and the functional knowledge about resources which extend the domain knowledge and support its management. Public and private workspaces provide an accessible representation of the collective knowledge that is incrementally created and allow the knowledge to cross the boundaries of closed local information. The paper presents the deployment of COWB in a cloud platform which severely curtails issues associated with scalability and performance. The paper shows the suitability of the proposed approach and aims to suggest how exploiting the potential of the Semantic Web technologies in the context of emergent technologies including Web 2.0, NoSQL databases and the cloud paradigm.     

面向Lustre集群存储的应用日志分析及系统自动优化框架

在科学计算、大数据处理和人工智能等领域,对相关应用负载进行研究,分析负载I/O模式,揭示应用负载变迁规律等,对指导集群存储系统性能优化十分重要。当前应用种类繁多并且应用快速迭代更新,复杂的环境使得对应用负载的特性挖掘充满挑战。针对以上问题,在生产环境中收集了5个Lustre集群存储共计326天的应用日志信息,对应用负载的访问、负载特性进行了深入的探究与分析,并对已有观察进行了验证和补充。通过对应用日志信息横向、纵向和多维度对比分析与信息挖掘,总结了4个发现,并研究相关发现与以往工作的关联性,结合实际生产环境,给出了相应的系统优化策略与切实可行的实施方案,为用户、维护人员、上层应用开发者和多层存储系统设计等人员提供了相关参考与建议。同时,针对实际应用环境复杂、系统优化工作耗时费力等问题,设计并实现了一种系统自动优化框架(SAOF),SAOF可为指定应用负载提供资源预留、带宽限定等功能,初步测试表明,SAOF能根据系统资源与任务负载需求为不同任务提供自动化的QoS保障。     

应用软件运行日志的收集与服务处理框架

随着现代计算机系统的规模和复杂性不断增大,其运行日志的数量也不断增多,但是由于日志数据的规模巨大、内容杂乱,用户查看日志数据具有一定的困难,因此对应用软件运行日志进行有效收集与处理具有重要意义。提出了一种应用软件运行日志的收集与服务处理框架,利用分布式收集策略对日志数据收集,定义了一种多层次数据存储结构对日志数据进行存储,并向用户提供日志数据查询服务。通过对某综合减灾系统的日志数据分析验证了提出的日志数据收集与服务处理框架的实用性,并与传统的日志收集分析软件ELK和Chukwa进行了对比。     

A Framework for Command Recovery in User Interface

In this paper,a framework is presented for adding a general command recovery facility to user interface.A simple model of interactive system is discussed and four meta commands.UNDO,REDO.SKIPBACK,and SKIPFORWARD,are defined.The double-linked list is used to organize the recovery information in a natural way for easy implementation.Applications of the framework to various demands of command recoveries show that the use of the framework is veryeasy and convenient.     

A transaction log analysis of a digital library

As experimental digital library testbeds gain wider acceptance and develop significant user bases, it becomes important to investigate the ways in which users interact with the systems in practice. Transaction logs are one source of usage information, and the information on user behavior can be culled from them both automatically (through calculation of summary statistics) and manually (by examining query strings for semantic clues on search motivations and searching strategy). We have conducted a transaction log analysis on user activity in the Computer Science Technical Reports Collection of the New Zealand Digital Library, and report insights gained and identify resulting search interface design issues. Specifically, we present the user demographics available with our library, discuss the use of operators and search options in queries, and examine patterns in query construction and refinement. We also describe common mistakes in searching, and examine the distribution of query terms appearing in the logs. Received: 17 December 1998/Revised: 25 May 1999     

Optimized cloud-based scheduling for protein secondary structure analysis

The Journal of Supercomputing - In the domain of proteomics, an in-depth analysis of the 3D structure of a protein is of paramount importance for many biological studies and applications. At the...     

A prototype cloud-based reproducible data analysis and visualization platform for outputs of agent-based models

Agent-based models typically have stochastic elements and many potential parameter combinations. This requires that we conduct multiple model runs to sweep the parameter space, creating large quantities of computationally generated, hyper-dimensional, “big data”. Understanding the models’ implications requires structured exploration of these complex output data. In response to this need, the MIRACLE team has developed a prototype web application that enables researchers who archive their model output data and analysis methods to perform online output data exploration and reproducible, re-parameterizable data analysis. We plan to build on this prototype, integrating with broader reproducibility initiatives in scientific computation and big data, to facilitate improved communication within research groups, and increase access and transparency for external research community and the general public. This paper provides contextual background and a case study of the prototype MIRACLE data storage and analysis web tool.     

基于日志的数据恢复及其在Oracle中的实现

在信息系统的工程实践中,数据库出现故障后的数据恢复是一项复杂的技术问题。从事务处理和事务日志的角度阐述了数据恢复的基本方法,并特别指出了实现完全数据恢复的技术途径和实施策略,同时结合Oracle数据库系统解剖了一个典型的数据恢复范例。研究结果表明,利用事务日志可以实现无数据丢失的完全恢复。     

A cloud-based intelligent TV program recommendation system

In recent years, cloud computing technology has matured significantly, as has the development of digital TV services. This, therefore, has led to an increased demand for improved quality TV services. In this paper, cloud computing technology is used to build a program recommendation system for digital TV programs, and the Hadoop Fair Scheduler is utilized to improve processing performance. Historical data of watched TV programs are collected through an electronic program guide, and then processed using K-means clustering, term frequency/inverse document frequency and k-nearest neighbor algorithms, to obtain clusters of audience groups and to find popular TV programs for each cluster. The proposed system can process massive amounts of user data in real-time, and can easily be scaled up.     

A fine-grained data-flow analysis framework

 A fine-grained data-flow analysis framework (L, F) where the elements of the semilattice L are mappings from a set of items I to a semilattice of values V is introduced, and an algorithm is presented to solve this framework by considering the elements of I and V individually, rather than regarding the elements of L as atomic values. It is shown that a variety of useful data-flow problems fit into the fine-grained data-flow analysis framework, and can be solved in O(∣I∣×∣N∣) time. Received 20 August, 1991/ 3 June, 1996     

Taking back control of privacy: a novel framework for preserving cloud-based firewall policy confidentiality

As the cloud computing paradigm evolves, new types of cloud-based services have become available, including security services. Some of the most important and most commonly adopted security services are firewall services. These cannot be easily deployed in a cloud, however, because of a lack of mechanisms preserving firewall policy confidentiality. Even if they were provided, the customer traffic flowing through the Cloud Service Provider infrastructure would still be exposed to eavesdropping and information gaining by performing analysis. To bypass these issues, the following article introduces a novel framework, known as the Ladon Hybrid Cloud, for preserving cloud-based firewall policy confidentiality. It is shown that in this framework, a high level of privacy is provided thanks to leveraging an anonymized firewall approach and a hybrid cloud model. A number of optimization techniques, which help to further improve the Ladon Hybrid Cloud privacy level, are also introduced. Finally, analysis performed on the framework shows that it is possible to find a trade-off between the Ladon Hybrid Cloud privacy level, its congestion probability, and efficiency. This argument has been demonstrated through the results of conducted experiments.     

一种搜索引擎日志分析的网络舆情监测探究

近几年来,随着互联网信息技术的不断发展,电脑已得到广泛普及.而网民逐渐开始应用网络论坛、博客、微博纷纷对社会事务发表看法,由此而形成网络舆情,已成为社会舆情的重要表现形式.由于网络舆情具有传播速度快、范围广且突发的特点,加强其监测已受到政府部门的重视.本文特提出一种搜索引擎日志分析的网络舆情监测方法,以望对后期网络舆情监测工作提供参考借鉴.     

Oracle数据库非归档模式重做日志恢复方法

Linux系统是在企业中广泛使用的操作系统,企业亦多基于该操作系统安装数据库。当数据库运行在非归档模式中,且数据库处于无日志备份的情况时,一旦重做日志文件丢失将会导致数据库不可用。针对Oracle数据库重做日志文件丢失问题,提出一种非归档模式下的重做日志恢复方法。实验证明,该方法能有效实现重做日志的无备份恢复。     

Failure diagnosis and recovery based on DES framework

As many industrial systems become more complex, it becomes extremely difficult to diagnose the cause of failures. This paper presents a new failure diagnosis approach based on discrete-event systems (DES) framework. In particular, the approach is a hybrid of event-based and state-based ones leading to a simpler failure diagnoser with supervisory control capability. In our approach, we include the failure recovery events for failures in the system model in order to derive a diagnoser we refer to as a recoverable diagnoser. Further, in order to reduce the state size of the recoverable diagnoser, a procedure to construct a high-level diagnoser is presented. The design procedure for diagnoser is presented along with a pump-valve system as a illustrative example.     

A computational framework for location analysis

Location analysis decisions are interrelated and should be made within a single decision-making framework. A framework within which a number of location strategies can be placed is presented. Location-allocation models are improved in two ways: 1) the allocation rule is developed to more accurately reflect customer choice processes; and 2) the objective function is developed to incorporate future changes. Computational support for this framework is described.