Boundary query solution using convex hull algorithm

An important issue in database (DB) systems is responding to different users’ queries in an acceptable time. To do this, we should define different queries based on users’ real needs and we should consider suitable solutions. In this article, we express a new query called ‘boundary query’ which is used for achieving an overall view of a subject in the DB. This query does not return all query answers but it returns boundary values that cover all answers for the related query. In this article, we map a DB environment to a vector space based on necessary attributes. Then we implement the proposed method, and based on the results, we observe that the proposed method's run time is acceptable for huge DBs.     

Development of an indoor navigation system for a monocular-vision-based autonomous mobile robot

We have developed a technology for a robot that uses an indoor navigation system based on visual methods to provide the required autonomy. For robots to run autonomously, it is extremely important that they are able to recognize the surrounding environment and their current location. Because it was not necessary to use plural external world sensors, we built a navigation system in our test environment that reduced the burden of information processing mainly by using sight information from a monocular camera. In addition, we used only natural landmarks such as walls, because we assumed that the environment was a human one. In this article we discuss and explain two modules: a self-position recognition system and an obstacle recognition system. In both systems, the recognition is based on image processing of the sight information provided by the robot’s camera. In addition, in order to provide autonomy for the robot, we use an encoder and information from a two-dimensional space map given beforehand. Here, we explain the navigation system that integrates these two modules. We applied this system to a robot in an indoor environment and evaluated its performance, and in a discussion of our experimental results we consider the resulting problems.     

Greedy algorithms for a class of knapsack problems with binary weights

In this article we identify a class of two-dimensional knapsack problems with binary weights and related three-criteria unconstrained combinatorial optimization problems that can be solved in polynomial time by greedy algorithms. Starting from the knapsack problem with two equality constraints we show that this problem can be solved efficiently by using an appropriate partitioning of the items with respect to their binary weights. Based on the results for this problem we derive an algorithm for the three-criteria unconstrained combinatorial optimization problem with two binary objectives that explores the connectedness of the set of efficient knapsacks with respect to a combinatorial definition of adjacency. Furthermore, we prove that our approach is asymptotically optimal and provide extensive computational experiments that shows that we can solve the three-criteria problem with up to one million items in less than half an hour. Finally, we derive an efficient algorithm for the two-dimensional knapsack problems with binary constraints that only takes into account the results we obtained for the unconstrained three-criteria problem with binary weights.     

Increasing the Level of Automation in the Forestry Logging Process with Crane Trajectory Planning and Control

Working with forestry machines requires a great deal of training to be sufficiently skilled to operate forestry cranes. In view of this, it would be desirable within the forestry industry to introduce automated motions, such as those seen in robotic arms, to shorten the training time and make the work of the operator easier. Motivated by this fact, we have developed two experimental platforms for testing control systems and motion‐planning algorithms in real time. They correspond to a laboratory setup and a commercial version of a hydraulic manipulator used in forwarder machines. The aim of this article is to present the results of this development by providing an overview of our trajectory‐planning algorithm and motion‐control method, with a subsequent view of the experimental results. For motion control, we design feedback controllers that are able to track reference trajectories based on sensor measurements. Likewise, we provide arguments to design controllers in an open‐loop for machines that lack sensing devices. Relying on the tracking efficiency of these controllers, we design time‐efficient reference trajectories of motions that correspond to logging tasks. To demonstrate performance, we provide an overview of extensive testing done on these machines.     

A vibrotactile approach to tactile rendering

While moving our fingertip over a fine surface we experience a sensation that gives us an idea of its properties. A satisfactory simulation of this feeling is still an unsolved problem. In this paper, we describe a rendering strategy based on vibrations that play an important role in the tactile exploration of fine surfaces. To produce appropriate excitation patterns we use an array of vibrating contactor pins. Similar to the colour model in computer graphics, we simulate arbitrary vibrations as a superposition of only two sinewaves. Each sinewave is intended for the excitation of a specific population of mechanoreceptors. We carried out first tests of our rendering strategy on Brownian surfaces of different fractal dimensions.     

Integration and Test Sequencing for Complex Systems

The integration and test phase of complex manufacturing machines, like an ASML lithographic manufacturing system, is expensive and time consuming. The tests that can be performed at a certain point in time during the integration phase depend on the modules that are integrated and, therefore, on the preceding integration sequence. In this paper, we introduce a mathematical model to describe an overall integration and test sequencing problem, and we propose an algorithm to solve this problem. The method is a combination of integration sequencing and test sequencing. Furthermore, we introduce several strategies that determine when test phases should start. With a case study within the development of a software release that is used to control an ASML lithographic machine, we show that the described method and strategies can be used to solve real-life problems.      

Imposing biological constraints onto an abstract neocortical attractor network model

In this letter, we study an abstract model of neocortex based on its modularization into mini- and hypercolumns. We discuss a full-scale instance of this model and connect its network properties to the underlying biological properties of neurons in cortex. In particular, we discuss how the biological constraints put on the network determine the network's performance in terms of storage capacity. We show that a network instantiating the model scales well given the biologically constrained parameters on activity and connectivity, which makes this network interesting also as an engineered system. In this model, the minicolumns are grouped into hypercolumns that can be active or quiescent, and the model predicts that only a few percent of the hypercolumns should be active at any one time. With this model, we show that at least 20 to 30 pyramidal neurons should be aggregated into a minicolumn and at least 50 to 60 minicolumns should be grouped into a hypercolumn in order to achieve high storage capacity.     

Mobile cloud-based depression diagnosis using an ontology and a Bayesian network

Recently, depression has becomes a widespread disease throughout the world. However, most people are not aware of the possibility of becoming depressed during their daily lives. Therefore, obtaining an accurate diagnosis of depression is an important issue in healthcare. In this study, we built an inference model based on an ontology and a Bayesian network to infer the possibility of becoming depressed, and we implemented a prototype using a mobile agent platform as a proof-of-concept in the mobile cloud. We developed an ontology model based on the terminology used to describe depression and we utilized a Bayesian network to infer the probability of becoming depressed. We also implemented the system using multi-agents to run on the Android platform, thereby demonstrating the feasibility of this method, and we addressed various implementation issues. The results showed that our method may be useful for inferring a diagnosis of depression.     

Designing an overload control strategy for secure e-commerce applications

Uncontrolled overload can lead e-commerce applications to considerable revenue losses. For this reason, overload prevention in these applications is a critical issue. In this paper we present a complete characterization of secure e-commerce applications scalability to determine which are the bottlenecks in their performance that must be considered for an overload control strategy. With this information, we design an adaptive session-based overload control strategy based on SSL (Secure Socket Layer) connection differentiation and admission control. The SSL connection differentiation is a key factor because the cost of establishing a new SSL connection is much greater than establishing a resumed SSL connection (it reuses an existing SSL session on the server). Considering this big difference, we have implemented an admission control algorithm that prioritizes resumed SSL connections to maximize the performance in session-based environments and dynamically limits the number of new SSL connections accepted, according to the available resources and the current number of connections in the system, in order to avoid server overload. Our evaluation on a Tomcat server demonstrates the benefit of our proposal for preventing server overload.     

The ramification problem in temporal databases: an approach with conflicting constraints

In this paper we study the ramification problem in the setting of temporal databases. Standard solutions from the literature on reasoning about action are inadequate because they rely on the assumption that fluents persist, and because actions have effects on the next situation only. In this paper we provide a solution to the ramification problem based on an extension of the situation calculus and the work of McCain and Turner. More specifically, we study the case where there are conflicting effects of an action, a particularly complex problem. Also we present a tool which implements the proposed solution.     

Effective Fitness as an Alternative Paradigm for Evolutionary Computation II: Examples and Applications

In paper I of this series we reviewed the recent development of an alternative paradigm for evolution on a fitness landscape–effective fitness–which offers an intuitive way to understand population dynamics as flows on an effective fitness landscape when genetic operators other than reproductive selection play an important role. In this article we demonstrate the utility of the concept using several simple analytical models and some more complex models that we simulate numerically. In particular, we show that effective fitness offers a qualitative and quantitative framework within which the phenomenon of induced symmetry breaking of the genotype-phenotype map may be understood. As explicit examples we consider: the violation of the building block hypothesis in non-epistatic landscapes; self-adaptation of genetic algorithms in time-dependent fitness landscapes and the appearance of evolutionary robustness as an emergent property in the evolution of language. In all cases we demonstrate that effective fitness offers a framework within which these diverse phenomena can be understood and in principle quantitatively studied.     

基于元胞自动机的应急疏散系统仿真研究

分析了紧急情况下人员疏散的难点,提出了应急系统人员疏散策略,设计了一种基于CA的人员疏散模型.通过模型仿真,分析模型中相关参数对疏散效果的影响,在此基础上对人员疏散模型中地场方法进行改进,模拟结果表明,基于CA的应急疏散仿真能够很好的模拟建筑内人员应急疏散行为及紧急事件的发展情况.同时该仿真方法具有直观性、灵活性和可扩展性,为应急管理研究提供了一个很好的研究思路.     

本体的查询与推理机制研究

首先介绍了本体的定义并对其查询模型进行了探讨,然后在对已有的本体查询语言进行了比较和评价后认为,要充分利用本体的模式信息进行查询就必须提高查询的推理能力,重点对DQL(OWL-QL)的逻辑基础和推理机制进行分析,并提出本体查询语言的发展应该是在本体Web语言上进行语义规则的扩充。     

Integration of real-time planning and control in an unstructured manufacturing workcell

In this paper, we consider the problem of real-time planning and control of a robot manipulator in an unstructured workspace. The task we consider is to control the manipulator, such that the end-effector follows a path on an unknown surface, with the aid of a single camera assumed to be uncalibrated with respect to the robot coordinates. To accomplish a task of this kind, we propose a new control strategy based on multisensor fusion. We assume that three different sensors, i.e. encoders mounted at each joint of the robot with 6 d.o.f., a force-torque sensor mounted at the wrist of the manipulator and a visual sensor with a single camera fixed to the ceiling of the workcell, are available. Also, we assume that the contact point between the tool grasped by the end-effector and the surface is frictionless. To describe the proposed algorithm that we have implemented, first of all we decouple the vector space of control variables into two subspaces, and use one of the subspaces for controlling the magnitude of the contact force on the surface and the other subspace for controlling the constrained motion on the surface. In this way the control synthesis problem is decoupled and we are able to develop a new scheme that utilizes sensor fusion to handle uncalibrated parameters in the workcell and wherein the surface on which the task is to be performed is assumed to be visible, but has an apriori unknown position.     

Estimating the feasibility of transition paths in extended finite state machines

There has been significant interest in automating testing on the basis of an extended finite state machine (EFSM) model of the required behaviour of the implementation under test (IUT). Many test criteria require that certain parts of the EFSM are executed. For example, we may want to execute every transition of the EFSM. In order to find a test suite (set of input sequences) that achieves this we might first derive a set of paths through the EFSM that satisfy the criterion using, for example, algorithms from graph theory. We then attempt to produce input sequences that trigger these paths. Unfortunately, however, the EFSM might have infeasible paths and the problem of determining whether a path is feasible is generally undecidable. This paper describes an approach in which a fitness function is used to estimate how easy it is to find an input sequence to trigger a given path through an EFSM. Such a fitness function could be used in a search-based approach in which we search for a path with good fitness that achieves a test objective, such as executing a particular transition, and then search for an input sequence that triggers the path. If this second search fails then we search for another path with good fitness and repeat the process. We give a computationally inexpensive approach (fitness function) that estimates the feasibility of a path. In order to evaluate this fitness function we compared the fitness of a path with the ease with which an input sequence can be produced using search to trigger the path and we used random sampling in order to estimate this. The empirical evidence suggests that a reasonably good correlation (0.72 and 0.62) exists between the fitness of a path, produced using the proposed fitness function, and an estimate of the ease with which we can randomly generate an input sequence to trigger the path.     

Humanoid Posture Selection for Reaching Motion and a Cooperative Balancing Controller

Our goal in this research was to develop a motion planning algorithm for a humanoid to enable it to remove an object that is blocking its path. To remove an object in its path, a humanoid must be able to reach it. Simply stretching its arms, which in a humanoid are shorter than its body and legs, is not sufficient to reach an object located at some distance away or on the ground. Therefore, reachability has to be ensured by a combination of motions that include kneeling and orienting the pelvis. However, many posture selection options exist because of the redundancy of a humanoid. In this research, we focused on the optimization of the posture of a humanoid that is reaching toward a point. The posture selected depends on the initial posture, the location of the point, and the desired manipulability of the humanoid’s arms. A cooperative balancing controller ensures the stability of the reaching motion. In this paper, we propose an algorithm for reaching posture selection and a balancing controller for humanoids, and we present the results of several experiments that confirm the effectiveness of the proposed algorithm and controller.     

From functional specification to syntactic structures: systemic grammar and tree adjoining grammar

In this paper we provide an implementation strategy to map a functional specification of an utterance into a syntactically well-formed sentence. We do this by integrating the functional and the syntactic perspectives on language, which we take to be exemplified by systemic grammars and tree adjoining grammars (TAGs) respectively. From systemic grammars we borrow the use of networks of choices to classify the set of possible constructions. The choices expressed in an input are mapped by our generator to a syntactic structure as defined by a TAG. We argue that the TAG structures can be appropriate structural units of realization in an implementation of a generator based on systemic grammar and also that a systemic grammar provides an effective means of deciding between various syntactic possibilities expressed in a TAG grammar. We have developed a generation strategy which takes advantage of what both paradigms offer to generation, without compromising either.