1∶2000成图比例尺数字航空摄影测量质量控制与保障

通过《太原市1∶2 000成图比例尺数字航空摄影测量》项目实践,以该项目中1∶2 000数字线划图制作为例,结合数据分层详细介绍了数字摄影测量中的质量控制与保障的措施,以供类似测量工作借鉴。     

Optimizing the parallel adaptive indexing algorithm on multi-core CPUs

An improved parallel adaptive indexing algorithm on multi-core CPUs is proposed to solve the problems that the parallel adaptive indexing algorithms cannot take full advantage of the CMP's parallel execution resource, and properly process the sequential query pattern. Based on the optimization of the Refined Partition Merge algorithm, our improved parallel adaptive indexing algorithm combines the Parallel Database Cracking method with the Refined Partition Merge algorithm. In our algorithm, when fewer data chunks are in the index, we use the optimized Refined Partition Merge algorithm so as to reduce the probability of conflict between threads, decrease the waiting time, and increase the utilization of the threads, and when more data chunks are in the index, we use the Parallel Database Cracking method so as to take full advantage of the CMP's parallel execution resources. Besides, we propose an optimization for the robustness, which makes our algorithm suitable for two common query patterns. Experiments show that our method can reduce the query time by 25.7％～33.2％, and suit with common query patterns.     

OPTIMIZATION OF REDUNDANCY IN WATER DISTRIBUTION NETWORKS USING GRAPH THEORETIC PRINCIPLES

An integer goal programming based approach to maximize reliability in water distribution networks is developed. Previous work has shown that graphs which are inherently the most invulnerable to failure have the same number of links incident at each node, i.e. they are regular in degree. The converse of this statement is not true. Regular graphs can contain weaknesses such as bridges, articulation nodes, and even total disconnections. The integer goal programming formulation in this paper is combined with a procedure which recognizes both explicit and implicit articulation points within the water distribution network to ensure that such weaknesses are excluded from the final solution. The integer program component of the approach attempts to maximize regularity within the network. In the goal programming context this is achieved by minimizing the sum of the deviations, at each node, in terms of the number of links incident upon it, from the average number of links incident on a node over the whole network. The integer requirement is imposed to prevent non-integer numbers of links being selected by the model.     

Weak signal identification with semantic web mining

We investigate an automated identification of weak signals according to Ansoff to improve strategic planning and technological forecasting. Literature shows that weak signals can be found in the organization’s environment and that they appear in different contexts. We use internet information to represent organization’s environment and we select these websites that are related to a given hypothesis. In contrast to related research, a methodology is provided that uses latent semantic indexing (LSI) for the identification of weak signals. This improves existing knowledge based approaches because LSI considers the aspects of meaning and thus, it is able to identify similar textual patterns in different contexts. A new weak signal maximization approach is introduced that replaces the commonly used prediction modeling approach in LSI. It enables to calculate the largest number of relevant weak signals represented by singular value decomposition (SVD) dimensions. A case study identifies and analyses weak signals to predict trends in the field of on-site medical oxygen production. This supports the planning of research and development (R&D) for a medical oxygen supplier. As a result, it is shown that the proposed methodology enables organizations to identify weak signals from the internet for a given hypothesis. This helps strategic planners to react ahead of time.     

Modeling sleep mode gains in energy-aware networks

Nowadays two main approaches are being pursued to reduce energy consumption of networks: the use of sleep modes in which devices enter a low-power state during inactivity periods, and the adoption of energy proportional mechanisms where the device architecture is designed to make energy consumption proportional to the actual load. Common to all the proposals is the evaluation of energy saving performance by means of simulation or experimental evidence, which typically consider a limited set of benchmarking scenarios.     

A novel intelligent verification platform based on a structured analysis model

An intelligent verification platform based on a structured analysis model is presented.Using an abstract model mechanism with specific signal interfaces for user callback,the unified structured analysis data,shared by the electronic system level design,functional verification,and performance evaluation,enables efficient management review,auto-generation of code,and modeling in the transaction level.We introduce the class tree,flow parameter diagram,structured flow chart,and event-driven finite state machine as structured analysis models.As a sand table to carry maps from different perspectives and levels via an engine,this highly reusable platform provides the mapping topology to search for unintended consequences and the graph theory for comprehensive coverage and smart test cases.Experimental results show that the engine generates efficient test sequences,with a sharp increase in coverage for the same vector count compared with a random test.     

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper,we present a non-transferable utility coalition graph game(NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing(OFDMA) based cognitive radio networks to maximize both system throughput and system fairness.In this algorithm,with the assistance of others SUs,SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs.So this scheme can effectively exploit both space and frequency diversity of the system.Performance results show that,NTU-CGG significantly improves system fairness level while not reducing the throughput comparing with other existing algorithms.     

Star graph automorphisms and disjoint Hamilton cycles

The search for edge-disjoint Hamilton cycles in star graphs is important for the design of interconnection network topologies. We define automorphisms for star graphs St _n of degree n?1, for every positive odd integer n, which yield permutations of labels for the edges of St _n taken from the set of integers between 1 and ? n/2 ?. By decomposing these permutations into permutation cycles, we are able to identify edge-disjoint Hamilton cycles that are automorphic images of a known Hamilton cycle in St _n . Our method produces a better than two-fold improvement from ? ? (n)/10 ? to ? 2? (n)/9 ?, where ? is the Euler function, for the known number of edge-disjoint Hamilton cycles in St _n for all odd integers n. For prime n, the improvement is from ? n/8 ? to ? n/5 ?, and we can extend this result to the case when n is the power of a prime greater than 7.     

Orderly algorithms for graph generation

The existence of orderly analogues of graph generators proposed by Heap and Farrell is established. The modifications to these algorithms supply practical methods enabling one to generate exhaustive lists of graphs and locally restricted graphs; moreover, the difficulty involved in ensuring that no duplications occur in the list is greatly reduced.     

Towards a sales assistant using a product knowledge graph

The phenomenal growth in the consumer electronics industry over the last decade is mainly due to rapid advances in integration technologies. The market is ever evolving with new products made available on a frequent basis. However, typically, the average consumer tends to have insufficient knowledge of the features and functions of an electronic device. Although most manufacturers provide product specifications, they are often difficult for consumers to understand and it is hard for customers to grasp the details of a product. This study introduces the concept of a product knowledge graph, which is constructed by transforming a set of data from a product management system and external data. This study overcomes the technical barriers for customers with the use of knowledge graph technologies. To construct large-scale product knowledge, an ontology model is designed and a platform for knowledge extraction and transformation is also developed. Then, a sales assistant called God of Sales is demonstrated. This study provides a novel approach to explaining product features and functions in a comprehensive manner with semantic recommendations.