基于中心对称局部相似数量模型的均值漂移目标跟踪

为实现对运动目标的实时跟踪,提出中心对称局部相似数量(center symmetric-local similarity number,CSLSN)这一新的局部显著度纹理描述算子,并将其引入到目标表征模型。该算子通过分析中心像素及其8邻域像素之间的大小关系,在局部相似数量(local similarity number,LSN)纹理算子的基础上,针对其无法区分同一局部显著度下的不同纹理结构的问题,增加以中心像素为对称点的局部梯度信息,提取出候选目标区域中具有CS-LSN主要模式的真实目标像素,有效地抑制了背景像素的影响并减少了后续目标表征模型的计算量;利用真实目标像素的CS-LSN纹理特征和色度特征构建直方图,完成目标表征;进而将其嵌入到均值漂移(mean shift,MS)框架完成跟踪。实验结果表明,该方法在目标与背景相似、部分遮挡、光照变化及物体形变等情况下均能完成鲁棒跟踪,目标大小为29像素×25像素时,处理速度约为25帧/s,可满足实时应用的需求。

Mg-Al-O复合氧化物催化剂的表面酸碱性质(I):强度与数量研究

分别在６７３、８７３和１０７３Ｋ分解Ｍｇ／Ａｌ摩尔比为３的水滑石生成３Ｍｇ－Ａｌ－Ｏ复合氧化物。ＸＲＤ测定均显示ＭｇＯ物相，８７３Ｋ以上焙烧的样品同时存在ＭｇＡｌ２Ｏ４类晶石物相。微量吸附量热测定其表面酸碱强度与数量，发现碱强度与数量顺序为：８７３Ｋ＞１０７３Ｋ＞６７３Ｋ，而酸强度与数量顺序是：６７３Ｋ＞１０７３Ｋ＞８７３Ｋ。

青藏高压系统对川渝春夏臭氧污染的影响机制

为研究青藏高压系统对川渝地区春夏季臭氧(O3)污染的影响机制,对2015~2018年每年4~9月的中国气象局高空全要素填图数据(Micaps PLOT High)、川渝14个城市的国控环境监测站点O3监测数据及气象台站数据进行了研究分析.结果表明:O3浓度的高低与青藏高压中心位置分布的状况和数量密切相关,中心分布越密集、出现的极值区域越多和中心个数越多时,同期地表温度越高,O3浓度越高(尤其是中心位置出现在100°E和28°N的频数越多,地表温度越高,导致较多O3极值的出现).对比分析同年逐月与逐年同月高压脊线南北偏移情况对O3浓度的影响,发现高压脊线越往北跳,对应日照时数越长,O3浓度越高.综合分析高压中心和高压脊线对川渝地区O3影响的共同作用,发现高压中心和高压脊线分别主要通过控制地表温度和日照时数来影响O3浓度,且同一时段,二者对O3浓度影响的效果和程度也存在差异,有时对O3浓度的增加表现为协同作用,有时为拮抗作用.

Decreasing Trend in Summer Precipitation over the Western Sichuan Basin since the 1950s

Changing precipitation in the densely populated Sichuan basin may have a great impact on human life. This study analyzes the change in summer precipitation since 1951 over the western Sichuan basin, one of the regions of the heaviest rainfall in China, by using two datasets provided by the Chinese Meteorological Data Center. The results indicate that summer (from June to September) precipitation over the western Sichuan basin shows a significantly decreasing trend. The summer precipitation over this region has decreased by about 20% since the 1950s, with a rate of decrease of about 40 mm per decade.

A Spatio-temporal Data Model for Road Network in Data Center Based on Incremental Updating in Vehicle Navigation System

The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation system is in charge of storing incremental data,and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal.According to the analysis on the shortcomings of several typical spatio-temporal data models used in the data center and based on the base map with overlay model,the reverse map with overlay model (RMOM) was put forward for the data center to make rapid response to incremental data request.RMOM supports the data center to store not only the current complete road network data,but also the overlays of incremental data from the time when each road network changed to the current moment.Moreover,the storage mechanism and index structure of the incremental data were designed,and the implementation algorithm of RMOM was developed.Taking navigational road network in Guangzhou City as an example,the simulation test was conducted to validate the efficiency of RMOM.Results show that the navigation database in the data center can response to the requirements of incremental data by only one query with RMOM,and costs less time.Compared with the base map with overlay model,the data center does not need to temporarily overlay incremental data with RMOM,so time-consuming of response is significantly reduced.RMOM greatly improves the efficiency of response and provides strong support for the real-time situation of navigational road network.

A novel virtual machine deployment algorithm with energy efficiency in cloud computing

In order to improve the energy efficiency of large-scale data centers, a virtual machine(VM) deployment algorithm called three-threshold energy saving algorithm(TESA), which is based on the linear relation between the energy consumption and(processor) resource utilization, is proposed. In TESA, according to load, hosts in data centers are divided into four classes, that is,host with light load, host with proper load, host with middle load and host with heavy load. By defining TESA, VMs on lightly loaded host or VMs on heavily loaded host are migrated to another host with proper load; VMs on properly loaded host or VMs on middling loaded host are kept constant. Then, based on the TESA, five kinds of VM selection policies(minimization of migrations policy based on TESA(MIMT), maximization of migrations policy based on TESA(MAMT), highest potential growth policy based on TESA(HPGT), lowest potential growth policy based on TESA(LPGT) and random choice policy based on TESA(RCT)) are presented, and MIMT is chosen as the representative policy through experimental comparison. Finally, five research directions are put forward on future energy management. The results of simulation indicate that, as compared with single threshold(ST) algorithm and minimization of migrations(MM) algorithm, MIMT significantly improves the energy efficiency in data centers.

Traffic-Aware VDC Embedding in Data Center： A Case Study of FatTree

Virtualization is a common technology for resource sharing in data center. To make efficient use of data center resources, the key challenge is to map customer demands （modeled as virtual data center, VDC） to the physical data center effectively. In this paper, we focus on this problem. Distinct with previous works, our study of VDC embedding problem is under the assumption that switch resource is the bottleneck of data center networks （DCNs）. To this end, we not only propose relative cost to evaluate embedding strategy, decouple embedding problem into VM placement with marginal resource assignment and virtual link mapping with decided source-destination based on the property of fat-tree, but also design the traffic aware embedding algorithm （TAE） and first fit virtual link mapping （FFLM） to map virtual data center requests to a physical data center. Simulation results show that TAE＋FFLM could increase acceptance rate and reduce network cost （about 49% in the case） at the same time. The traffie aware embedding algorithm reduces the load of core-link traffic and brings the optimization opportunity for data center network energy conservation.

Energy-Aware Scheduling Scheme Using Workload-Aware Consolidation Technique in Cloud Data Centres

To reduce energy consumption in cloud data centres,in this paper,we propose two algorithms called the Energy-aware Scheduling algorithm using Workload-aware Consolidation Technique(ESWCT) and the Energyaware Live Migration algorithm using Workload-aware Consolidation Technique(ELMWCT).As opposed to traditional energy-aware scheduling algorithms,which often focus on only one-dimensional resource,the two algorithms are based on the fact that multiple resources(such as CPU,memory and network bandwidth)are shared by users concurrently in cloud data centres and heterogeneous workloads have different resource consumption characteristics.Both algorithms investigate the problem of consolidating heterogeneous workloads.They try to execute all Virtual Machines(VMs) with the minimum amount of Physical Machines(PMs),and then power off unused physical servers to reduce power consumption.Simulation results show that both algorithms efficiently utilise the resources in cloud data centres,and the multidimensional resources have good balanced utilizations,which demonstrate their promising energy saving capability.

Service optimization in programmable cloud network

With the rapid development in cloud data centers and cloud service customers,the demand for high quality cloud service has been grown rapidly.To face this reality,this paper focuses on service optimization issues in cloud computing environment.First,a service-oriented architecture is proposed and programmable network facilities are utilized in it to optimize specific cloud services.Then various cloud services are categorized into two subcategories;static services and dynamic services.Furthermore,the concepts of cloud service quality and cloud resource idle rate are defined,and the aforementioned concepts have also been taken into consideration as parameters in the service optimization algorithm to improve the cloud service quality and optimize system workload simultaneously.Numerical simulations are conducted to verify the effectiveness of the proposed algorithm in balancing the workload of all servers.

Optimization on the Conversion of Bamboo Shoot Shell to Levulinic Acid with Environmentally Benign Acidic Ionic Liquid and Response Surface Analysis

Levulinic acid（LA） has been identified as a promising green,biomass derived platform chemical.Response surface analysis（RSA） with a four-factor-five-level central composite design（CCD） was applied to optimize the hydrolysis conditions for the conversion of bamboo（Phyllostachys Praecox f.preveynalis） shoot shell（BSS） to LA catalyzed with ionic liquid [C4mim]HSO4.The effects of four main reaction parameters including temperature,time,C[C4mim]HSO4（initial [C4mim]HSO4 concentration） and XBSS（initial BSS intake） on the hydrolysis reaction for yield of LA were analyzed.A quadratic equation model for yield of LA was established and fitted to the data with an R2 of 0.9868,and effects of main factors and their corresponding relationships were obtained with RSA.Model validation and results of CCD showed good correspondence between actual and predicted values.The analysis of variance（ANOVA） of the results indicated that the yield of LA in the range studied was significantly（P＆lt;0.05） affected by the four factors.The optimized reaction conditions were as follows：temperature of 145 ℃,time of 103.8 min,C[C4mim]HSO4 of 0.9 mol.L-1 and XBSS of 2.04%（by mass）,respectively.A high yield [（71±0.41）%（by mol）,triplicate experiment] was obtained at the optimum conditions of temperature of 145 ℃,time of 104 min,C[C4mim]HSO4 of 0.9 mol.L-1 and XBSS of 2%（by mass）,which obtained from the real experiments,concurred with the model prediction [73.8%（by mol） based on available C6 sugars in BSS or 17.9%（by mass） based on the mass of BSS],indicating that the model was adequate for the hydrolysis process.

Interannual salinity variability of the Northern Yellow Sea Cold Water Mass

This paper discusses the interannual variability of the Northern Yellow Sea Cold Water Mass(NYSCWM) and the factors that influence it,based on survey data from the 1976–2006 national standard section and the Korea Oceanographic Data Center,monthly E-P flux data from the European Centre for Medium-Range Weather Forecasts,and meridional wind speed data from the International Comprehensive Ocean-Atmosphere Data Set. The results show that:1) the mean salinity of the NYSCWM center has a slightly decreasing trend,which is not consistent with the high salinity center; 2) both the southern salinity front and the halocline of the NYSCWM display a weakening trend,which indicates that the difference between the NYSCWM and coastal water decreases; 3) the Yellow Sea Warm Current intrusion,the E-P flux of the northern Yellow Sea,and the strength of the winter monsoon will affect the NYSCWM salinity during the following summer.

Analysis of International Migrant Workers： Case Study of Worker of Madura Origin

As international migrant workers, they should equip themselves with appropriate knowledge and skills to compete with other overseas workers in the global job market. This means that international migrant workers need to improve their quality and ability. In addition, it also requires a high work and motivation to produce a satisfactory performance. Capabilities like cognitive, affective, and psychomotor abilities are needed to support performance Information related to three abilities also motivation is important from international migrant workers from the island of Madura to be analyzed. Based on the results of qualitative research using interview technique and observation on three informants who had worked abroad as nursing, baby sitter, and housekeeper whose data validity of interview result is measured using triangulation method, it shows different ability in working on his job （though having the same motivation） resulted different performance. Low performance due to lack of ability in cognitive, affective, and psychomotor aspects resulted in workers who could not compete with other workers. The evidence came from the lack of contract extension for low-performing workers. It is therefore recommended for prospective international migrant workers to equip themselves with sufficient capacity through trainings undertaken by government training center （Balai Latihan Kerja/BLK）

A Dynamic Load Balancing Method of Cloud-Center Based on SDN

In order to balancing based on data achieve dynamic load flow level, in this paper, we apply SDN technology to the cloud data center, and propose a dynamic load balancing method of cloud center based on SDN. The approach of using the SDN technology in the current task scheduling flexibility, accomplish real-time monitoring of the service node flow and load condition by the OpenFlow protocol. When the load of system is imbalanced, the controller can allocate globally network resources. What＇s more, by using dynamic correction, the load of the system is not obvious tilt in the long run. The results of simulation show that this approach can realize and ensure that the load will not tilt over a long period of time, and improve the system throughput.

Difference of Directions Between External Driving Force and Movement Direction of Center of Mass

Driven dynamics of a two-dimensional Frenkel-Kontorova model is studied in the paper.In our numericalsimulations, it is found that the movement direction of the center of mass is not consistent with that of the externaldriving force except for some special symmetric directions at the lower driving force.Our results also indicate that themovement direction of the center of mass strongly depends on both the magnitude and the direction of the externaldriving force as well as the misfit angle between two layers.

OpenFIow Based Flow Slice Load Balancing

Today's data center networks are designed using densely interconnected hosts in the data center.There are multiple paths between source host and destination server.Therefore,how to balance traffic is key issue with the fast growth of network applications.Although lots of load balancing methods have been proposed,the traditional approaches cannot fully satisfy the requirement of load balancing in data center networks.The main reason is the lack of efficient ways to obtain network traffic statistics from each network device.As a solution,the OpenFlow protocol enables monitoring traffic statistics by a centralized controller.However,existing solutions based on OpenFlow present a difficult dilemma between load balancing and packet reordering.To achieve a balance between load balancing and packet reordering,we propose an OpenFlow based flow slice load balancing algorithm.Through introducing the idea of differentiated service,the scheme classifies Internet flows into two categories:the aggressive and the normal,and applies different splitting granularities to the two classes of flows.This scheme improves the performance of load balancing and also reduces the number of reordering packets.Using the trace-driven simulations,we show that the proposed scheme gains over 50%improvement over previous schemes under the path delay estimation errors,and is a practical and efficient algorithm.

Quantum Groups by Ore Extensions Associated withGroup Algebras

As a continuation of the work of Beattie on quantum groups constructed byOre extensions, in this paper, we characterize their centre and discuss the category ofquantum Yang-Baxter modules over them. In addition, we determine all finite dimen-sional irreducible representations over these quantum groups.

Analysis about the speckle of radar high resolution range profile

The aspect sensitivity is the main problem in radar automatic target recognition using high resolution range profile (HRRP). In the traditional viewpoint,HRRPs are assumed to be highly similar if the aspect variation is not enough to cause range migration. However,some experiments in anechoic chambers don’t agree with the assumption. Particularly,some abnormal HRRPs often occur in the measured data. Based on the scattering center model,this paper focuses on the reason of abnormal HRRP,which is named as the speckle. The theoretical model of speckle is established and the "spurious dual peaks" feature of the speckled HRRP is analyzed. Then the occurrence condition of speckle is concluded,and so is the relationship between the speckle probability in HRRP and radar carrier frequency. At last,the experiment in an anechoic chamber is used to verify all the analyses about the speckle.