New Generation Operational Support System

The paper introduces the present status and development objec- tives of the operational support systems of the three telecommuni- cation operators in China and briefly describes the features of the new generation telecommunication operational support system (NGOSS),such as adopting the TMN/TOM structure,supporting the unified and multiple access processing,conducting effective and centralized management of data.

Current status of medical support in military operations other than war in domestic and overseas

Objective: To investigate the current status of medical support in military operations other than war (MOOTW) in domestic and overseas. Methods: This paper mainly adopts the descriptive, comparative and induction research methods. The current status of medical support in MOOTW in China, America, Russia, Israel, Canada, had been studied through some official papers, and series of professional books by analysis the precise date in various kinds of emergency event. Results: The contrast shows that there is still a quite huge development in medical support in MOOTW, no matter in China, or in other countries. Conclusion: In order to strengthen the forces, besides building professional rescue teams, it is necessary to take a regular revise of plans, according to missions` needs.

SE-DEA-SVM evaluation method of ECM operational disposition scheme

Operational disposition of electronic countermeasures(ECM)is a hot topic in modern warfare research.Through fully analyzing the characteristics and shortcomings of the traditional operational disposition scheme,a super-efficient data envelopment analysis support vector machine(SE-DEA-SVM)method for evaluating the operational configuration scheme of ECM is proposed.Firstly,considering the subjective and objective factors affecting the operational disposition of ECM,the index system of operational disposition scheme is established,and we explain the solution method of terminal indexs.Secondly,the evaluation and algorithm process of SE-DEA-SVM evaluation method are introduced.In this method,the super-efficient data envelopment analysis(SE-DEA)model is used to calculate the weight of index system,and the support vector machine(SVM)method combined with the training samples of evaluation index is used to obtain the input-output model of evaluation value of combat configuration.Finally,by an example(obtaining five schemes),we verify the SE-DEA-SVM evaluation method and analyze the results.The efficiency analysis,comparison analysis,and error analysis of this method are carried out.The results show that this method is more suitable for military evaluation with small samples,and it has high efficiency,applicability,and popularization value.

Intelligent decision support system of operation-optimization in copper smelting converter

An artificial intelligence technique was applied to the optimization of flux adding systems and air blasting systems, the display of on line parameters, forecasting of mass and compositions of slag in the slagging period, optimization of cold material adding systems and air blasting systems, the display of on line parameters, and the forecasting of copper mass in the copper blow period in copper smelting converters. They were integrated to build the Intelligent Decision Support System of the Operation Optimization of Copper Smelting Converter(IDSSOOCSC), which is self learning and self adaptating. Development steps, monoblock structure and basic functions of the IDSSOOCSC were introduced. After it was applied in a copper smelting converter, every production quota was clearly improved after IDSSOOCSC had been run for 4 months. Blister copper productivity is increased by 6%, processing load of cold input is increased by 8% and average converter life span is improved from 213 to 235 furnace times.

A Multi-case Study of Community Supported Agriculture (CSA) Operation Model in Beijing

As one of the ways to localize foods,community supported agriculture can strengthen food safety and should be reasonably guided and developed.Based on the analysis of the spatial layout of the community supported agriculture organizations in Beijing,this paper described the development framework and course of community supported agriculture in Beijing.Combining 3 differentiated cases with the consumer's participation in community supported agriculture and the trust mechanism,it was found that the drive type has a very significant impact on the characteristics of these organizations.

Information Monitoring Technology for Support Structure of Railway Tunnel During Operation

In the process of railway construction, because of the inconvenience ofgeological condition, water bursting and mud surging happen frequently, and the laterdeformation of support structure on the happening geology section would threaten thenormal running of railway. The limit difference of deformation control value of thesupport structure section where geological accidents frequently happen, is small, andartificial half-automatic supervisory technology cannot get the health condition of tunnelin time, resulting many cars speed-down accidents due to deformation of supportstructure. Through design innovation, we introduce TGMIS in the later period ofYanzishan railway construction to quickly capture the deformation of support structure,the strain of lining concrete, the strain of steel frame, stress of surrounding soil, stress ofsurrounding water, strain of second lining steel bar and other situ data. Also we setobservation prism and measuring robot device in specific position inside tunnel, androbot laser locator laser spot is projected onto reflection target surface, by graphicprocessing algorithm, the receiver calculates the measured value and standard value ofthe 3D coordinates of the laser spot. Then the information is transmitted throughtransmitting device, transducer and USB-485 to computer to predict and evaluate thehealth condition of the support structure of the tunnel so as to provide safety warninginformation. Provide timely and reliable data for the operation company to avoid theoccurrence of vicious accidents.

Operations Support Systems Standards:Status Quo and Trends

The emerging of diversified new telecommunications technologies leads to a continuous change of telecom networks. Consequently, the operations support systems of telecommunications operators are facing structure adjustments as well as new systems construction. In this situation, new generation operations support systems standards are urgently required. Several standardization organizations have made substantial progress in the study of the new generation standards, such as ITU' s study on Next Generation Network (NGN) management, TMF's on New Generation Operations Systems and Software (NGOSS) and CCSA's on network management standards. However, the existing operations support systems face the challenges of architecture improvement, change of the focus of operations support, orientation of customers' demands and technology evolution.

3G-oriented Business and Operations Support System

The diversity of services of Third-Generation (3G) wireless systems, the rapid development of new services and the big number of entities on the value chain would be the new challenges when building and operating 3G networks. A solution to these challenges is to build a new Business and Operations Support System (BOSS). Considering the numerous varieties of 3G services as well as the QoS requirements, it is suggested that operators should integrate the existing Business Support Systems (BSS) and Operations Support Systems (OSS), perfect the Customer Relationship Management (CRM), make the systems adapt to the life cycle of data, information and services, and make steady progress in standardization work.

NGN-oriented Business and Operations Support System

The Next Generation Network (NGN) is based on packet switching and open network architecture. Therefore, the NGN business and operations support focuses on customers, totally different from that of the conventional telecommunications network, which concentrates on network operation and maintenance. An NGN operations and maintenance support system should be customer-focused, market-oriented and profit-targeted. Based on its unified NGN operations and maintenance support system, ZTE has implemented an integrated network management system that covers every functional level of the NGN. Accordingly, technical updates can be implemented flexibly on the network to meet the requirements of technology revolution, and new customer-oriented services can be offered to operators.

Research and Design of IPv6 Network Management and Operations Support System

IPv6 is the foundation of the development of Next Generation Internet (NGI). An IPv6 network management and operations support system is necessary for real operable NGI. Presently there are no approved standards yet and relevant equipment interfaces are not perfect. A Network Management System (NMS) at the network layer helps implement the integrated management of a network with equipment from multiple vendors, including the network resources and topology, end-to-end network performance, network failures and customer Service Level Agreement (SLA) management. Though the NMS will finally realize pure IPv6 network management, it must be accommodated to the management of relevant IPv4 equipment. Therefore, modularized and layered structure is adopted for the NMS in order to implement its smooth transition.

ZTE Showcases Operations and Business Support Solutions at the 8th Annual Asia- Pacific Billing & Revenue Assurance Show

ZTE Corporation (ZTE) announced that its participation in the 8th Annual Asia-Pacific Billing & Revenue Assurance Conference in Singapore from May 12th till 15th 2008 delivered a keynote on its latest ZSmart operations and business support solutions and shared the latest BSS/OSS technology with key industry players.

纤维肌痛综合征生物标记物的筛选及免疫细胞浸润分析

背景:纤维肌痛综合征作为常见风湿病,其发病与中枢敏化及免疫异常有关,但具体过程尚未阐明,缺乏特异性诊断标志物,不断探索该病的发病机制具有重要的临床意义。目的:基于加权基因共表达网络分析(WGCNA)等生物信息学方法和机器学习算法筛选纤维肌痛综合征潜在的诊断相关标志基因,并分析其免疫细胞浸润特征。方法:对来自基因表达综合数据库(GEO)的纤维肌痛综合征数据集转录谱进行差异分析和WGCNA分析,整合筛选出差异共表达基因,进一步采用机器学习套索回归(LASSO)算法、支持向量机递归特征消除(SVM-RFE)机器学习算法来识别核心生物标志物,并绘制受试者工作特征(ROC)曲线以评估诊断价值。最后,采用单样本基因集富集分析(ssGSEA)和基因集富集分析(GSEA)评估纤维肌痛综合征的免疫细胞浸润情况及通路富集。结果与结论:①对GSE67311数据集按照log2|(FC)|>0,P<0.05的条件进行差异分析后获得8个下调的差异表达基因;进行WGCNA分析后获得正相关性最高(r=0.22,P=0.04)的模块(MEdarkviolet)内含基因497个,负相关性最高(r=-0.41,P=6×10-5)的模块(MEsalmon2)内含基因19个;将差异表达基因与WGCNA的2个高相关性模块基因取交集,获得7个基因。②对上述7个基因进行LASSO回归算法筛选出4个基因,进行SVM-RFE机器学习算法筛选出5个基因,两者取交集后确定了3个核心基因,分别为重组1号染色体开放阅读框150蛋白(germinal center associated signaling and motility like,GCSAML)、整合素β8(Integrin beta-8,ITGB8)和羧肽酶A3(carboxypeptidase A3,CPA3);绘制3个核心基因的ROC曲线下面积分别为0.744,0.739,0.734,提示均具有很好的诊断价值,可作为纤维肌痛综合征的生物标志物。③免疫浸润分析结果显示,与对照组相比纤维肌痛综合征患者记忆B细胞、CD56 bright NK细胞和肥大细胞显著下调(P<0.05),且与上述3个生物标志物显著正相关(P<0.05)。④富集分析结果提示,纤维肌痛综合征的富集途径包括9条,主要与嗅觉传导、神经活性配体-受体相互作用及感染等通路密切相关。⑤上述结果显示,纤维肌痛综合征的发生发展与多基因参与、免疫调节异常及多个通路失调有关,但这些基因与免疫细胞之间的相互作用,以及它们与各通路之间的关系尚需进一步研究。

Support vector machine for prediction of siRNA silencing efficacy

In order to assist the design of short interfering ribonucleic acids （siRNA）, 573 non-redundant siRNAs were collected from published literatures and the relationship between siRNAs sequences and RNA interference （RNAi） effect is analyzed by a support vector machine （SVM） based algorithm relied on a basebase correlation （BBC） feature. The results show that the proposed algorithm has the highest area under curve （AUC） value （0. 73） of the receive operating characteristic （ROC） curve and the greatest r value （0. 43） of the Pearson＇s correlation coefficient. This indicates that the proposed algorithm is better than the published algorithms on the collected datasets and that more attention should be paid to the base-base correlation information in future siRNA design.

Research and Application of Maize Precision Intelligence Spatial Decision Support System

In order to solve the problem of the maze precision fertilizer,soil fertility evaluation,soil fertility classify and yield projections,the geographic information system with spatial information processing functions,spatial data mining techniques with spatial information analysis capabilities,expert system technology in the field of artificial intelligence,traditional information management systems and decision support system were effectively integrated in this study,and the statistical analysis method of GIS and data visualization were combined to design and implement the maize precise intelligent space decision-making system.This system had greatly improved the decision-making ability in agricultural production carried out by agricultural management.

Multi-mode process monitoring based on a novel weighted local standardization strategy and support vector data description

There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.

TWIN SUPPORT TENSOR MACHINES FOR MCS DETECTION

Tensor representation is useful to reduce the overfitting problem in vector-based learning algorithm in pattern recognition.This is mainly because the structure information of objects in pattern analysis is a reasonable constraint to reduce the number of unknown parameters used to model a classifier.In this paper, we generalize the vector-based learning algorithm TWin Support Vector Machine(TWSVM) to the tensor-based method TWin Support Tensor Machines(TWSTM), which accepts general tensors as input.To examine the effectiveness of TWSTM, we implement the TWSTM method for Microcalcification Clusters(MCs) detection.In the tensor subspace domain, the MCs detection procedure is formulated as a supervised learning and classification problem, and TWSTM is used as a classifier to make decision for the presence of MCs or not.A large number of experiments were carried out to evaluate and compare the performance of the proposed MCs detection algorithm.By comparison with TWSVM, the tensor version reduces the overfitting problem.

A multi-user decision support system for online city bus tour planning

Tourism is rapidly becoming a sustainable pathway toward economic prosperity for host countries and communities. Recent advances in information and communications technology, the smartphone, the Internet and Wi-Fi have given a boost to the tourism industry. The city bus tour （CBT） service is one of the most successful businesses in the tourism industry. However, there exists no smart decision support system determining the most efficient way to plan the itinerary of a CBT. In this research, we report on the ongoing development of a mobile application （app） and a website for tourists, hoteliers and travel agents to connect with city bus operators and book/purchase the best CBT both in terms of cost and time. Firstly, the CBT problem is formulated as an asymmetric sequential three-stage arc routing problem. All places of interest （PoI） and pickup/dropout points are identified with arcs of the network （instead of nodes）, each of which can be visited at least once （instead of exactly once）. Secondly, the resulting pure integer programming （IP） problem is solved using a leading optimization soft- ware known as General Algebraic Modeling System （GAMS）. The GAMS code developed for this project returns： （1） the exact optimal solution identifying the footprints of the city bus relative to all the arcs forming the minimal cost network; （2） the augmenting paths corre- sponding to the pickup stage, the PoI visiting stage and the drop-off stage. Finally, we demonstrate the applicability of the mobile app/website via a pilot study in the city of Melbourne （Australia）. All the computations relative to the initial tests show that the ability of the app to answer users＇ inquiries in a fraction of a minute.

基于K-support稀疏逻辑回归的停电敏感度预测

有效预测停电敏感度高的客户,可为电力服务部门开展精准营销和差异化服务提供数据与决策支持。本文提出一种基于k-support稀疏逻辑回归的客户停电敏感度评价算法。不同于常用的l1范数,k-support范数是对l0范数更为紧致的凸松弛,并能够同时选择多个关联性强的因子进行预测,有利于提升预测准确性。算法首先从客户基本信息、用电信息、缴费信息、95598工单、停电事件等多个维度筛选用于敏感性预测的自变量(因素),收集各用户的因素信息形成样本数据集。进一步构建停电敏感性预测的k-support稀疏逻辑回归模型,建立模型快速求解的前向后向算子分裂迭代优化算法,转化为2个子问题的快速迭代。通过优势分析法确定回归模型中对目标变量具有显著影响的自变量因素。运用某省级电网公司近百万客户数据对建立的预测模型进行校验与评估,达到良好的预测准确率,实验结果验证了本文模型的有效性。

THE ASYMPTOTIC PROPERTIES OF WEIGHTED MARKOV OPERATORS

Let (X, ∑, μ) be a σ-finite measure space, P : LI → L1 be a Markov operator, and Qt = ∑n=0 ∞ qn(t)Pn, where {qn(t)} be a sequence satisfying:i) qn(t) ≥ 0 and ∑n=0 ∞ qn(t)=1 for all t >0;ii)lim (q0(t) + ∑n=1 ∞ |qn(t) -qn-1(t)|) = 0.t→∞f ∈ L1, it is proved that Qt(f) convergent strongly to a fixed point of P as t → 0 if and only if {Qt(f)}t>0 is precompact. Qt(f) is convergent if and only if the ergodic mean operator An(f) is convergent, and they have the same limit. If P is a double stochastic operator then lim Qtf = E(f|∑0) for all f ∈ L1, where ∑0 is the invariant σ-algebra ofP. Some related results are also given.

Hypo-Calories with Micronutrients and Fat Emulsion of Pre-Operative Peripheral Parenteral Nutrition in Malnutrition Risk Rectal Cancer Patients: A Retrospective Cross-Sectional Study

Malnutrition has been recognized as a significant risk factor for the post operated patients, especially for those patients undergoing abdominal operations. This study evaluated the effect of hypo-calories with micronutrients of pre-operative peripheral parenteral nutrition support (PPPN) for rectal cancer patients. Retrospective cross sectional study method was used to investigate. We screened rectal cancer patients past year pre-operative with malnutrition risk from our cancer database and divided into 2 groups, received or not received PPPN and compared the post-operative outcomes. The results showed that the post-operative serum albumin of the 25 patients received PPPN averaged 2.5 ± 0.32 g/dl;significantly better than those of the 15 patients not received PPPN (non-PPPN), which averaged 1.92 ± 0.42 g/dl. The first ambulatory time required 3.0 ± 0.8 days for the PPPN, significantly shorter than those for the non-PPPN, which averaged 4.9 ± 2.4 days. Post-operative hospital days for the patients received PPPN were 18.2 ± 10.5 day, also significantly fewer than the non-PPPN, which averaged 33.7 ± 20.0 day. More than 25% of the non-PPPN was infected with sepsis, while none was infected in the PPPN patients. In conclusion, this study verified the benefits of micronutrients of pre-operative peripheral parenteral nutrition support for rectal cancer patients.