Conceptual design: issues and challenges
Decisions made during conceptual design have signi®cant in ̄uence on the cost, performance, reliability, safety and environmental impact of a product. It has been estimated that design decisions account for more than 75% of ®nal product costs. It is, therefore, vital that designers have access to the right tools to support such design activities. In the early 1980s, researchers began to realize the impact of design decisions on downstream activities. As a result, different methodologies such as design for assembly, design for manufacturing and concurrent engineering, have been proposed. Software tools that implement these methodologies have also been developed. However, most of these tools are only applicable in the detailed design phase. Yet, even the highest standard of detailed design cannot compensate for a poor design concept formulated at the conceptual design phase. In spite of this, few CAD tools have been developed to support conceptual design activities. This is because knowledge of the design requirements and constraints during this early phase of a product's life cycle is usually imprecise and incomplete, making it dif®cult to utilize computer-based systems or prototypes. However, recent advances in ®elds such as fuzzy logic, computational geometry, constraints programming and so on have now made it possible for researchers to tackle some of the challenging issues in dealing with conceptual design activities. In this special issue, we have gathered together discussions on various aspects of conceptual design phase: from the capturing of the designer's intent, to modelling design constraints and solving them in an ef®cient manner, to verifying the correctness of the design.  Qin et al. begin this issue with the article aFrom online sketching to 2D and 3D geometry: a fuzzy knowledge based systemo in which they look at the interesting research problem of capturing the user's sketching intentions and automatically generating the corresponding geometric primitives. The motivation of this work comes from the fact that most designers still prefer to express their creative design ideas through 2D sketches. It is therefore important for a computer-aided conceptual design system to allow sketched input. Qin et al. built a prototype system that allows 2D sketched input, interprets the input sketch into more geometrically exact 2D vision objects and, when needed, projects the 2D objects into 3D models. The system receives the sketched input data through a sequence of mouse button presses, mouse motions and mouse button release events. After that, the system attempts to identify each curve segments and generate a precise 2D primitive for the identi®ed segment. For each pair of 2D primitives identi®ed, a 2D relationship (connectivity, parallelism or perpendicularity) is inferred by the system. As the 2D geometry (primitives 1 relationships) slowly accumulates, the system continually checks to see whether it can recognize a 3D object or feature. Upon recognition, the 3D object/ feature will be placed in 3D space and new features can be built upon previous ones. Latif Al Hakim et al. approach the problem from the concurrent engineering perspective. Traditionally, design is a serial activity whereby reliability, manufacturability, maintainability, safety and other requirements are considered sequentially. In recent years, in an effort to increase competitiveness and reduce design life cycle, the concept of concurrent engineering is introduced. Instead of performing design-related activities in series, they are performed simultaneously. This approach greatly increases the complexity of the design process due to the highly interactive nature of the various design tasks. To support design activities adequately in such an environment, Latif Al Hakim et al. propose the incorporation of reliability with functional perspectives at the conceptual design stage. They use graph theory to represent a product and the relationships between its components. A product's components are represented as the vertices of a graph, while the edges of the graph represent the ̄ow of energy between components. With this representation, it is easy to visualize energy ̄ow between components and thus trace any loss of functionality. In addition, this representation allows one easily to take into consideration various constraints such as cost for further design re®nement. The third paper in this special issue points out the need for a suitable conceptual design representation scheme for smooth integration with downstream applications of the product development process. Brunnetti and Golob propose a feature-based representation scheme for capturing product semantics handled in the conceptual design phase. They believe that any computer-aided design system should accomplish two major goals. The ®rst is to support the ̄ow of information without loss along the product development process, and the second is to assist designers in Computer-Aided Design 32 (2000) 849±850 COMPUTER-AIDED DESIGN

title: Dealing with different distributions in learning from
abstract: In the problem of learning with positive and unlabeled examples, existing research all assumes that positive examples P and the hidden positive examples in the unlabeled set U are generated from the same distribution. This assumption may be violated in practice. In such cases, existing methods perform poorly. This paper proposes a novel technique A-EM to deal with the problem. Experimental results with product page classification demonstrate the effectiveness of the proposed technique.

title: Opinion Mining
abstract: Описанл процедуру формування інтегрального показника об’єкта згідно з відгуками користувачів під час застосування методів оцінювання опінії текстової інформації у web-документах. Запропоновано використання лінгвістичних змінних та застосування вагових коефіцієнтів для достовірнішого результату оцінювання емоційного забарвлення текстової інформації. Ключові слова: опінія, емоційне забарвлення, об’єкт, інтегральний показник, лінгвістична змінна, ваговий коефіцієнт.

title: Speed-up iterative frequent itemset mining with constraint changes
abstract: Mining of frequent itemsets is a fundamental data mining task. Past research has proposed many efficient algorithms for this purpose. Recent work also highlighted the importance of using constraints to focus the mining process to mine only those relevant itemsets. In practice, data mining is often an interactive and iterative process. The user typically changes constraints and runs the mining algorithm many times before being satisfied with the final results. This interactive process is very time consuming. Existing mining algorithms are unable to take advantage of this iterative process to use previous mining results to speed up the current mining process. This results in an enormous waste of time and computation. In this paper, we propose an efficient technique to utilize previous mining results to improve the efficiency of current mining when constraints are changed. We first introduce the concept of tree boundary to summarize useful information available from previous mining. We then show that the tree boundary provides an effective and efficient framework for the new mining. The proposed technique has been implemented in the context of two existing frequent itemset mining algorithms, FP-tree and tree projection. Experiment results on both synthetic and real-life datasets show that the proposed approach achieves a dramatic saving of computation.

title: Finding Actionable Knowledge via Automated Comparison
abstract: The problem of finding interesting and actionable patterns is a major challenge in data mining. It has been studied by many data mining researchers. The issue is that data mining algorithms often generate too many patterns, which make it very hard for the user to find those truly useful ones. Over the years many techniques have been proposed. However, few have made it to real-life applications. At the end of 2005, we built a data mining system for Motorola (called Opportunity Map) to enable the user to explore the space of a large number of rules in order to find actionable knowledge. The approach is based on the concept of rule cubes and operations on rule cubes. A rule cube is similar to a data cube, but stores rules. Since its deployment, some issues have also been identified during the regular use of the system in Motorola. One of the key issues is that although the operations on rule cubes are flexible, each operation is primitive and has to be initiated by the user. Finding a piece of actionable knowledge typically involves many operations and intense visual inspections, which are labor-intensive and time-consuming. From interactions with our users, we identified a generic problem that is crucial for finding actionable knowledge. The problem involves extensive comparison of sub-populations and identification of the cause of their differences. This paper first defines the problem and then proposes an effective method to solve the problem automatically. To the best of our knowledge, there is no reported study of this problem. The new method has been added to the Opportunity Map system and is now in daily use in Motorola.

title: Entity discovery and assignment for opinion mining applications
abstract: Opinion mining became an important topic of study in recent years due to its wide range of applications. There are also many companies offering opinion mining services. One problem that has not been studied so far is the assignment of entities that have been talked about in each sentence. Let us use forum discussions about products as an example to make the problem concrete. In a typical discussion post, the author may give opinions on multiple products and also compare them. The issue is how to detect what products have been talked about in each sentence. If the sentence contains the product names, they need to be identified. We call this problem entity discovery. If the product names are not explicitly mentioned in the sentence but are implied due to the use of pronouns and language conventions, we need to infer the products. We call this problem entity assignment. These problems are important because without knowing what products each sentence talks about the opinion mined from the sentence is of little use. In this paper, we study these problems and propose two effective methods to solve the problems. Entity discovery is based on pattern discovery and entity assignment is based on mining of comparative sentences. Experimental results using a large number of forum posts demonstrate the effectiveness of the technique. Our system has also been successfully tested in a commercial setting.

title: Multi-resolution Meshes Deformation Based on Pyramid Coordinates
abstract: In this paper, we present a technique for multi-resolution meshes deformation based on pyramid coordinates. Pyramid coordinates are rotation invariant, and can achieve low distortion editing for large deformations. Their drawback is that the reconstruction process is nonlinear and time consuming especially for large meshes. In order to decrease the computational cost, the proposed method reduces the number of vertices involved in the deformation. We first construct a simplified mesh using a modified CPM algorithm; then edit the simplified meshes by pyramid coordinates based mesh detail presentation; finally, series of details are added to the deformed simplified mesh. Our algorithm can generate natural looking deformations more efficiently than the original pyramid coordinates method.

title: Analog circuit optimization system based on hybrid evolutionary algorithms
abstract: This paper investigates a hybrid evolutionary-based design system for automated sizing of analog integrated circuits (ICs). A new algorithm, called competitive co-evolutionary differential evolution (CODE), is proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through electrical simulation, to the optimization system in the MATLAB environment, once a circuit topology is selected. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifications are closely met, even in highly-constrained situations. Comparisons with available methods like genetic algorithms and differential evolution, which use static penalty functions to handle design constraints, have also been carried out, showing that the proposed algorithm offers important advantages in terms of optimization quality and robustness. Moreover, the algorithm is shown to be efficient.

title: The Design of the GPS-Based Surveying Robot Automatic Monitoring System for Underground Mining Safety
abstract: Earth subsidence in underground mining is an unavoidable problem in mining production, and timely and scientific observation and early warning is one of the important factors in the security of mining production. Though the surveying robot (i.e. automatic electronic total station) can automatically (or semi-automatically) monitor ground deformation for underground mining, the stability of the station location (monitor base station) has great impact on the monitor precision and when the measurement vision is covered, the surveying robot fails to monitor the corresponding deformation point. In order to tackle the above problem, the author and the research team have integrated the technology of GPS (Global Positioning System) with surveying robot and developed the GPS-based surveying robot automatic monitoring system for underground mining safety, which completely solves the foresaid problem, simplifies the monitor program and reduces the fixed investment cost of monitor. The article introduces the structure and working principle of the GPS-based surveying robot automatic monitoring system for underground mining safety, presents examples of monitor.

title: A Heuristic Greedy Optimum Algorithm for Target Coverage in Wireless Sensor Networks

title: Characterizing the dynamic connectivity between genes by variable parameter regression and Kalman filtering based on temporal gene expression data
abstract: One popular method for analyzing functional connectivity between genes is to cluster genes with similar expression profiles. The most popular metrics measuring the similarity (or dissimilarity) among genes include Pearson's correlation, linear regression coefficient and Euclidean distance. As these metrics only give some constant values, they can only depict a stationary connectivity between genes. However, the functional connectivity between genes usually changes with time. Here, we introduce a novel insight for characterizing the relationship between genes and find out a proper mathematical model, variable parameter regression and Kalman filtering to model it.



We applied our algorithm to some simulated data and two pairs of real gene expression data. The changes of connectivity in simulated data are closely identical with the truth and the results of two pairs of gene expression data show that our method has successfully demonstrated the dynamic connectivity between genes.