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In recent years, substantial attention has been given to the optimal placement and planning of sampling or monitoring based on the Value of Information (VoI). The drawback of the VoI approach is it...

The concise and reliable representation of a given source dataset is available for data based learning and decision-making, which can be obtained through a controllable data fusion process within a formatted space. Based on the density matrix representation of a given source weather dataset, this paper first calculates the Hellinger distances and affinities between different density matrices, and then takes them to construct a two-dimensional metric space using the longest Hellinger metric and affinity paths. Within this space, the given source data units are converted into the corresponding rectangle nodes which are determined by the minimum horizontal and vertical distances between different data units. According to a predefined detection size in this space, the basic blocks centred by different rectangle nodes are classified into different subset blocks for fusion. Each subset block is jointed by the basic blocks with overlapped areas. During the detection process, the detection size keeps increasing until a predefined reference variable, such as the relative density for all subset blocks, reaches a predefined turning point. The fusion of the rectangle nodes in a subset block depends on the distances between the included rectangle nodes’ positions and this subset block’s centre position which is calculated according to the included rectangle nodes’ weights and positions. The experimental analysis shows that the proposed weather data fusion method is controllable and stable and can obtain concise and reliable fusion results for learning inputs and decision-making.

This study investigated the localization ability of an impulse vibration source outside the body in two-dimensional space. We tested whether humans can recognize the direction or distance of an impulse vibration source when using their hand to detect spatiotemporal vibrotactile information provided by the propagated vibrational wave from the source. Specifically, we had users put their hands on a silicone rubber sheet in several postures. We asked users to indicate the position of the vibration source when a location on the sheet was indented. Experimental results suggested that the direction of the impact vibration source can be recognized to some extent, although recognition accuracy depends on hand posture and the position of the vibration source. The best results were achieved when the fingers and palm were grounded and a vibration source was presented around the middle fingertip, and the directional recognition error in this case was 6 degree. In contrast, results suggest it is difficult to accurately recognize the distance of the vibration. The results of this study suggest a new possibility for directional display where vibrotactile actuators are embedded at a distance from the user's hand.

During the design of transducers configuration for an active noise control system, current optimization methods need to predetermine the error sensors configuration, which significantly increases the workload of later optimization of the secondary sources configuration. In this study, a new method free from specific error sensors configuration information is presented that higher order microphones are used to capture the sound field so as to formulate the cost function in wave domain. In addition, according to sparsity characteristics of the primary sound field, sparsity-inducing regularization is introduced to optimize the secondary sources configuration, including the number and positions, by calculating a sparse approximate solution to underdetermined equations. Effects of the number of candidate secondary sources are discussed, and the comparison with the uniform configuration and the optimized configuration using the genetic algorithm is performed. Results show that the proposed method can optimize the secondary sources configuration effectively independent of the error sensors configuration information. The noise reduction of the proposed method is close to that by the genetic algorithm, while other evaluation metrics for the system are much better, which would benefit the stability of active noise control system.

The paper presents mesh-connected computer (MCC) algorithms to solve the visibility problem for a set of disjoint simple objects such as line segments, circles, and simple polygons in the plane. Given a set of n such objects, the algorithms compute, on a √n x √n MCC, a view of these objects in O(√n) time. Both parallel and perspective views are considered. Earlier published algorithms for computing the views are sequential and have O(n log n) time complexity. Consider the solutions to solve problems of size n on MCCs with p processors, where p < n. An analysis is presented of the time performance and the limitations imposed by the computational and communication requirements, and the trade-offs between the size of the MCC and the time complexity that can be achieved.

Singularities in five-axis machining are a series of deadly positions, which may cause unstable axis movements and deteriorate the performance of machine tools. This paper presents an optimization strategy to locally deform the tool path so that singularities of five-axis machine tools can be avoided. To achieve this purpose, a new concept of “forbidden circle”, which is the projection of the three dimensional “singular cone” associated with tool orientations in a two dimensional space named P-plane, is established for the first time to transform the complicated three dimensional problem into a two dimensional problem. Based on this idea, the projected points in P-plane are interpolated as B-spline first, and then, the B-spline control points are locally optimized by taking the “forbidden circle” as the geometrical constraint to keep the B-spline from crossing it. Especially, in the optimization procedure, the constraints are linearized with the changes of B-spline control points to change the whole optimization problem as a typical positive definite quadratic programming problem, which can achieve one and only global optimal solution. By doing so, singularity is avoided, and at the same time, the machining errors caused by tool path deformation can be minimized. Simulation and experimental results verify the effectiveness of the singularity avoidance method.

The mathematical model for the rectifier circuit using semiconductor diodes is setup in this paper. The properties of the rectifier circuit presented by the ordinary differential equation containing a control parameter K. When K is large enough, the studied equation gives a trajectory approximating to a trajectory of the rectifier circuit above. The theorem about the approximation of these solutions with arbitrary small error (this error can be controlled by increasing K). The usefulness of this model is illustrated via concrete example. This study can to get more profound results in further and investigate an optimal process for an assembly line of rectifiers in electrical engineering.

A flexible crane system with vibrating and varying cable is investigated in two-dimensional space. Two partial differential equations and four ordinary differential equations derived by the Hamilton's principle are used to describe the dynamics of the flexible crane system. The dynamic model of the crane system considers the variation of the tension of the cable. Boundary control design is given to suppress vibrations of the flexible crane system. The Lyapunov's direct method is employed to prove the uniform ultimate boundedness of the states of the cable system. The effectiveness and performance of the proposed control schemes are depicted via numerical simulations.

In order to deploy multi-robot into a 2-D desired formation during the seeking process, this paper proposes a hybrid seeking algorithm with the formation deployment. Firstly, this paper expands the 1-D deployment algorithm to 2-D, and then combines with the extreme seeking algorithm to obtain the hybrid seeking algorithm. With the algorithm, multi-robot can deploy into a desired 2-D formation during seeking process. Simulation results are provided to illustrate the effectiveness of the algorithm.

A new class of double nearest-neighbor errorcorrecting codes on hexagonal constellation in the two dimensional space is presented. The proposed code is a linear [n,n−3] code over GF(p) where p = 6n+1 is a prime. We show that the proposed code corrects any generalized Lee error with at most weight 2.

The coverage control problem for robotic networks focuses on distributively coordinating the positioning of multiple dynamic agents to provide sensor coverage across a bounded region in two dimensional space. The associated optimal coverage problem seeks to position these agents so as to minimize an associated coverage cost. This coverage cost is typically defined with respect to a density function that is used to bias the network towards desired configurations. Previous approaches to this optimal coverage problem have addressed both static and dynamic environments through the choice of density function; however, stability guarantees for time-varying densities are restricted by significant technical assumptions that simplify the underlying proofs at the expense of limited applicability. In this paper, a generalized algorithm is presented that guarantees practical stability under relaxed technical assumptions. The algorithm, and its convergence, is illustrated via simulation examples.

With the increase of Internet of Things (IoT) applications, indoor positioning systems have begun to gain importance. Since there is no widespread technique in this area like Global Positioning System (GPS) at outdoors, a vast variety of techniques and technologies are being used in indoor positioning. Triangulation is one of the most frequently used techniques which can be categorized into two techniques: lateration and angulation. Lateration technique uses distance information in the estimation of location while the angulation technique uses angles besides distances. The lateration technique is called as trilateration when it is applied in two dimensional space. In this paper, trilateration technique is analyzed where one of the reference points resides of an uncertain location. The location of an object is estimated as an area by using two certain reference points. The proposed method determines an added value which represents how much the area is reduced. Experiments are performed to calculate an approximate added value without applying the proposed method because of the costly calculation requirements. The results of the experiments and the obtained added values are also reported as final evaluation of the study.

There are many methods that can be used to compute the geographic similarity between regions represented through areas in a two dimensional space. However, it is the rough set based membership function that allows an estimate of the similarity between a subzone formed by the data. The major objective behind this paper is to measure the similarity of GIS subzones on a discrete dataset. This has a varied number of applications not only in GIS and epidemiology but also in clusters analysis and artificial intelligence.

The paper describes a hybrid algorithm of position-trajectory control of a moving object, based on the integration of the wave and ant algorithms. The process of tracing the trajectory is carried out step by step. At each step relative to the current position of the moving object, a zone is formed within which all the obstacles are localized with the help of the radar, after which a separate trajectory section is constructed which is a continuation of the previously constructed section. And the entire trajectory is a collection of individual sections. The time complexity of this algorithm depends on the ant colony lifetime l (the number of iterations), the number of vertices of the graph n, and the number of ants m, and is defined as O(l∙n2∙m).

Euclidean geometry employs Cartesian coordinate system in which reference axes are perpendicular to each other. In this system every point is represented with a unique tuple which is non-ambiguous. In contrast to classical geometry, the fuzzy geometry deals with the objects with hazy boundary and thus can be viewed as a collection of fuzzy points. In fuzzy set theory it is considered that universe is non-fuzzy, the way we perceive any object is fuzzy or imprecise. This hypothesis guided us to establish fuzzy plane geometry in two dimensional space. This chapter starts with the discussion on reference frame considered for developing fuzzy geometry, which act as a yardstick to measure. The concept of fuzzy point and fuzzy line segment are also introduced here.

Conventional identification algorithms of space- frequency block codes (SFBC) only utilize the space- domain redundancy between any two receive antennas. In this paper, a novel two-dimensional space-frequency domain redundancy based SFBC identification algorithm for frequency selective fading is proposed in which the detection probability varies with the number of subcarriers. In particular, space-domain redundancy is utilized to construct the cross-correlation function of the estimator while frequency-domain redundancy is incorporated in the hypothesis test statistic. Simulation results verify the viability of the proposed algorithm and its superior performance for short observation periods with comparable computational complexity to the conventional algorithms.

Address-Event Representation is a flowering technology that can change the visual perception of the computer vision world. This paper proposes a methodology to associate the input data from this kind of sensors. A new descriptor computed using an extended LBP operator seeks to characterize the connectivity of the asynchronous incoming events in a two dimensional space. Those features can be organized on histograms and combined with others descriptors, as histograms of oriented events. They can be the input of traditional classifiers to detect or recognize objects from the scene.

Many disciplines are faced with the problem of handling time-series data. This study introduces an innovative visual representation for time series, namely the continuous triangular model. In the continuous triangular model, all subintervals of a time series can be represented in a two-dimensional continuous field, where every point represents a subinterval of the time series, and the value at the point is derived through a certain function (e.g. average or summation) of the time series within the subinterval. The continuous triangular model thus provides an explicit overview of time series at all different scales. In addition to time series, the continuous triangular model can be applied to a broader sense of linear data, such as traffic along a road. This study shows how the continuous triangular model can facilitate the visual analysis of different types of linear data. We also show how the coordinate interval space in the continuous triangular model can support the analysis of multiple time series through spatial analysis methods, including map algebra and cartographic modelling. Real-world datasets and scenarios are employed to demonstrate the usefulness of this approach.

The present work offers the solution for a target speed estimation in two dimensional space by the distributed radar systems. The proposed method supposes initial separated estimation of speeds in all channels (as it is done in conventional systems) and further refined estimation of the target speed by the joined least squares optimization. It was shown that the refined estimation allows obtaining of more precise speed estimate.

In this paper, we propose a closed-form solution for time-difference-of-arrival (TDOA) based joint source and sensor localization in two-dimensional space (2D). This closed-form solution is a combination of two closed-form solutions for time-of-arrival information recovery and time-of-arrival (TOA)-based joint source and sensor localization in 2D. In our previous works, we derived closed-form solutions for TOA-based joint source and sensor localization and near-closed-form solutions for TOA information recovery in three-dimensional space (3D). Since the localization in 2D is simpler than that in 3D, closed-form solutions for both problems in 2D are derived in this paper. The root-mean-square errors (RMSEs) achieved by the proposed closed-form solution are compared with the Cramer-Rao lower bound (CRLB) in synthetic experiments. The results show that the proposed solution works well in both low-noise and noisy cases and with both small and large numbers of sources and sensors.

Geometric form perception and its role in reorienting process have been studied extensively in children, but little is known about its early origin in infancy. Here, we present findings of three experiments that used looking-time paradigm to test infants’ sensitivity to geometric and feature information in two-dimensional visual display. One-year-old infants participated in spatial search tasks, which were manipulated regarding the display movement (static, visible rotation and invisible rotation) as a degree of disorientation. The results showed that infants were able to create expectation about a hiding location based on the geometry of a rectangle only in the directionally stable search space, whereas they were capable to use feature cues (color) for reorienting even in that condition when the spatial display was rotated and they were allowed to track the display motion. However, infants did not use either geometry or feature properties of 2-D space in an orientation invariant manner. The findings are discussed within the theory of reorientation with respect to the 2-dimensional space.

Time intervals are conventionally represented as linear segments in a one-dimensional space. An alternative representation of time intervals is the triangular model (TM), which represents time intervals as points in a two-dimensional space. In this paper, the use of TM in visualising and analysing time intervals is investigated. Not only does this model offer a compact visualisation of the distribution of intervals, it also supports an innovative temporal query mechanism that relies on geometries in the two-dimensional space. This query mechanism has the potential to simplify queries that are difficult to specify using traditional linear temporal query devices. Moreover, a software prototype that implements TM in a geographical information system (GIS) is introduced. This prototype has been applied in a real scenario to analyse time intervals that were detected by a Bluetooth tracking system. This application shows that TM has the potential to support a traditional GIS to analyse interval-based geographical data.

This paper introduces a methodology that permits presentation of the results of data envelopment analysis (DEA) graphically. A specialized form of multi-dimensional scaling, Co-Plot, enables presentation of the DEA results in a two-dimensional space, hence in a clear, understandable manner. When plotting ratios rather than original data, DEA efficient units can be visualized clearly, as well as their connections to specific variables and/or ratios. Furthermore, Co-Plot can be used in an exploratory data analysis to identify outliers, whose data require additional scrutiny, and potentially inconsequential variables that could be aggregated or removed from the analysis with little effect on the subsequent DEA results. The Co-Plot diagram of ratios presents super-efficient observations on an outer ring or sector of the plot and all reasonably efficient units on a slightly inner ring/sector, surrounding the remaining inefficient decision-making units. First, the well-known 35 Chinese Cities dataset is provided as an illustration. Second, a simulation study tests the applicability of Co-Plot to present the results of DEA.

The objective of this paper is to depict the knowledge array of standards. This is done by identifying and analyzing external effects, specifically spillover effects. The database used is Perinorm. We use a cluster analysis in order to create groups of technology fields for German standards according to the fields of the International Classification of Standards. Methodologically, the distances between these objects or clusters are defined by the chosen distance measure, which in turn is determined by the sum of their cross references. The applied joining clustering method uses these distances between the objects and allows the data to be mapped within a two dimensional space. The results of this mapping show the existence of structures within the standards data fitting to the well-known structure of patent spillovers.

In this paper, a new algorithm for visualization of high-multidimensional data is described. The algorithm follows several steps. At first, centers representing several categories are selected, and Euclidean distances between these centers are calculated in a high-dimensional space. Then these centers are placed in a 2-dimensional space in such a way that distances in this 2-dimensional space are similar to distances in the high-dimensional space. Next individual patterns are placed one-by-one in the 2-dimensional space trying to keep the similar distances in a high-dimensional and 2-dimensional space. With this algorithm, it was possible to visualize many high-dimensional data sets. The algorithm was successfully verified in several real life problems. It turned out that in some cases, which were until now considered as not linearly separable, became easily separable once patterns were transformed in the 2-dimensional space using the proposed algorithm.

International audience; Using a mouse-driven visual pointer, 10 participants made repeated open-loop egocentric localizations of memorized visual, auditory, and combined visual-auditory targets projected randomly across the two-dimensional frontal field (2D). The results are reported in terms of variable error, constant error and local distortion. The results confirmed that auditory and visual maps of the egocentric space differ in their precision (variable error) and accuracy (constant error), both from one another and as a function of eccentricity and direction within a given modality. These differences were used, in turn, to make predictions about the precision and accuracy within which spatially and temporally congruent bimodal visual-auditory targets are localized. Overall, the improvement in precision for bimodal relative to the best unimodal target revealed the presence of optimal integration well-predicted by the Maximum Likelihood Estimation (MLE) model. Conversely, the hypothesis that accuracy in localizing the bimodal visual-auditory targets would represent a compromise between auditory and visual performance in favor of the most precise modality was rejected. Instead, the bimodal accuracy was found to be equivalent to or to exceed that of the best unimodal condition. Finally, we described how the different types of errors could be used to identify properties of the internal representations and coordinate transformations within the central nervous system (CNS). The results provide some insight into the structure of the underlying sensorimotor processes employed by the brain and confirm the usefulness of capitalizing on naturally occurring differences between vision and audition to better understand their interaction and their contribution to multimodal perception.

By the cooperative and competitive PSO algorithm, the goal of this study is to provide the cooperative trajectories of multiple UAVs in the three dimensional space. To effectively reduce the dimension of this problem, the optimization process is mainly divided into two substages to reduce the difficulty of selecting the weights of objectives and constraints in the considered objective function. Considering several objectives and constraints, the cooperative trajectories in the first substage are given by the cooperative and competitive PSO algorithm in the two dimensional space. In the second substage, the altitude of cooperative trajectories is adjusted according to the considered objectives and constraints. In the complicated scenarios, simulation results demonstrate the effectiveness and the robustness of the cooperative and competitive PSO algorithm, which possibly provides one guideline for optimal cooperative planning trajectories of multiple UAVs in the three-dimensional space.

In this paper, we propose a Genetic Algorithm (GA) for solving the problem of dimensional ordering in Radial Visualization (Radviz) systems. The Radviz is a non-linear projection of high-dimensional data set onto two dimensional space. The order of dimension anchors in the Radviz system is crucial for the visualization quality. We conducted experiments on five common data sets and compare the quality of solutions found by GA and those found by the other well-known methods. The experimental results show that the solutions found by GA for these tested data sets are very competitive having better cost values than almost all solutions found by other methods. This suggests that GA could be a good approach to solve the problem of dimensional ordering in Radviz.

If we use computer to simulate simple form of three-dimensional dynamic process that is virtual or very difficult to achieve in reality directly in the two-dimensional space, we will reduce the development difficulty of simulation process. This paper introduces the simulation methods and key technologies by some relevant examples in “Audio and Video Electronic Textbook of Mechanical Drawing.” The examples include the formation process of gyration curved surface, the process of an object being cut by a plane, the decomposition process of a combined object. The Flash animation software is mainly used in the simulation process, and AutoCAD software and Photoshop software are the tools used for preparing materials. The results show that simple form of three-dimensional dynamic process can be simulated very realistically in the two-dimensional space, not using the tools of three-dimensional animation.

Objective: Instead of the linear model (LM), time intervals can be represented by a two-dimensional (2D) model, which is called the triangular model (TM). Although the TM has been introduced for decades and applied in some areas, there still a lack of empirical studies on its usability. To fill this gap, this study aims to evaluate how people perform when using the TM to answer questions on time intervals, in comparison with using the traditional LM. Method: Around 250 novice participants took part in the experiment, which consisted of a video training, a pretest and posttest. The video training introduced the basic knowledge of temporal relations and the two representations. The pretest allowed participants to practice the knowledge they have learned and receive feedbacks of the answers. In the posttest, participants' accuracy and speed when answering the questions were recorded for analysis. The results of using the TM and the LM were compared in pairs. The null hypothesis is that the participants produce equal results with the two models. Result: The results showed that the participants scored better and spent less time when answering questions with the TM, which rejected the null hypothesis. Moreover, the score and speed when they used the TM did decline in the questions containing a larger number of intervals. In contrast, the score and accuracy when they used the LM declined when questions containing a large number of intervals. Conclusion: *The TM is easy to learn. After a 20-min training, novice participants can use it to solve questions and produce satisfactory result. *The TM is easy and efficient for visual queries of time intervals. *The TM is easy to use for handling a large number of intervals. Implication: *The TM can be widely applied in analysing time intervals and linear data. *Tools implementing the TM can be learned and used by novice users.

In design, problem analysis is as important as solution synthesis. Strategic knowledge is required not only for constructing a solution but also for framing a problem. While externalized representations play critical roles in design tasks, different types of representations are necessary for different stages of a design task. In early stages of a design task, design support tools need to provide hands-on representations with which a designer can easily perform trial-and-error and examine the whole as well as parts of the whole, allowing the designer to represent any levels of preciseness, as he/she likes. Sketching and drawing with paper and pencil provide an ideal representation for this process. But what about supporting design domains, such as writing or programming, where no sketching exists? In this paper, we argue that two-dimensional positioning of objects in a design support tool serves for the same purpose as sketching does for architectural design. Two-dimensional positioning allows a designer to produce hands-on representations that “talk back” to him/her without forcing the designer to formalize or verbalize what to be externalized. Two systems, ART for writing and RemBoard for component-based programming, illustrate the framework.

An isoluminant color grating usually appears to move more slowly than a luminance grating that has the same physical speed. Yet a grating defined by both color and luminance is seen as perceptually unified and moving at a single intermediate speed. In experiments measuring perceived speed and direction, it was found that color- and luminance-based motion signals are combined differently in the perception of 1-D motion than they are in the perception of 2-D motion. Adding color to a moving 1-D luminance pattern, a grating, slows its perceived speed. Adding color to a moving 2-D luminance pattern, a plaid made of orthogonal gratings, leaves its perceived speed unchanged. Analogous results occur for the perception of the direction of 2-D motion. The visual system appears to discount color when analyzing the motion of luminance-bearing 2-D patterns. This strategy has adaptive advantages, making the sensing of object motion more veridical without sacrificing the ability to see motion at isoluminance.

Recent developments in the field of simple human movement modelling provide new ways in which to view complete models for analysing and understanding complex movements. Based on a kinematic theory and a vectorial delta-lognormal model recently proposed by Plamondon, 1993a , Plamondon, 1995a , Plamondon, 1995b , Plamondon, 1995c , Plamondon, 1998 , a new method for exploring and understanding the inherent mechanisms that govern planar movement generation and predict human behaviour is presented here. This paper describes an approach for analysing simple as well as complex movements such as cursive handwriting. It highlights some difficulties encountered in the analysis of complex movements. Problems such as the development of robust approaches to solve the reverse engineering problem of automatic parameter extraction of a succession of time-overlapped nonlinear functions are discussed. The analysis of natural cursive handwriting shows many interesting properties of the model and proposes new ways to study perturbed movement phenomena.

How to implement seismic or any other type of ray-based tomography in a new class of cellular parameterization built from any chosen distribution of nodes in two or three dimensions is shown. The complete flexibility of this novel approach allows one to introduce detail in a tomographic model only where desired, thereby reducing memory and computation time, or to impose complex a priori constraints on the inversion. Full details of powerful new algorithms are given to generate unequally sized tetrahedral or polyhedral cells and to calculate the necessary Frechet derivatives required in linearized tomography. These algorithms are efficient enough in three dimensions, to allow the parameterization to be refined during an inversion. The methods are illustrated with numerical examples. It is concluded that in linear or nonlinear inversion the computational cost of the new algorithms will not be significantly higher than that incurred by using a regular Cartesian grid.

When hoarding food within a circular arena, golden hamsters, Mesocricetus auratus W., return along a direct path from the feeding place at the centre to their nest at the periphery. The homing direction depends on dead reckoning (updated internal signals derived from locomotion) and, if available, on landmarks outside the arena. This study was aimed at defining the conditions under which a landmark panorama predominates over dead reckoning during conflict situations. In agreement with previous results, this was found to be the case only when the panorama contained at least one prominent vertical feature aligned with the apex of a two-dimensional, continuous background pattern. The minimal landscape that controlled homing was a solid cylinder presented in front of the background pattern, or its two-dimensional projection on the pattern itself. Contrary to a previous hypothesis, depth did not appear to be a critical factor in an effective landmark panorama.

The synchronization of moving agent networks with linear coupling in a two dimensional space is investigated. Base on the Lyapunov stability theory, a criterion for the synchronization is achieved via designed decentralized controllers. And, an example of typical moving agent network, having the Rössler system at each node, has been used to demonstrate and verify the design proposed. And, the numerical simulation results show the effectiveness of proposed synchronization approaches.

In the emerging area of nanonetworks, nano to micro-scale devices called nanomachines are deployed to perform various tasks for applications [1][2]. In this short paper, we consider a biosensor network that consists of nano-scale biosensors; i.e., sensors capable of sensing chemical signals (e.g., toxic chemical substances). In the biosensor network, stationary sensors are distributed over a two dimensional space, and expected to capture a chemical signal that appears in the space and that propagates via Brownian motion. We employ two different placement schemes to distribute sensors, and measure the propagation delay that is required to detect a chemical signal. Preliminary simulation results are provided to show the impact of placement schemes as well as the number of sensors on the propagation delay.

In various data mining applications performing the task of extracting information from large databases is serious problem, which occurs in many fields e.g.: bioinformatics, commercial behaviour of Internet users, social networks analysis, management and investigation of various databases in static or dynamic states. In recent years many techniques discovering hidden structures in the data set like clustering and projection of data from high-dimensional spaces have been developed. In this paper, we propose a model for multiple view unsupervised clustering based on Kohonen self-organizing-map algorithm. The results of simulations in two dimensional space using three views of training sets having different statistical properties have been presented.

A general-purpose package for the solution of problems in two space dimensions, both steady and unsteady, is described. The type of grid used is unstructured triangular. Emphasis is placed on concepts underlying the package, rather than on implementation.

The paper describes an universal constructor model realized in artificial environment called DigiHive. The environment is a two dimensional space, containing stacks of hexagonal tiles being able to moving, colliding, and making bonds between them. On the higher level of organization a structure of tiles specifies some function whose execution affects other tiles in its neighborhood. After short description of the Digi-Hive the paper describes design of an universal constructor and discusses possibilities of simulating self-replicating strategies in the environment.

When the time resolution of the signals is not so good, we can't rely on the time of arrival (TOA) information. On the other hand, if the frequency resolution of the signals is good, than frequency of arrival (FOA) informations will be more reliable. Localization of a moving, non-maneuvering target is possible by using Doppler-shift measurements in MIMO radar systems. A new method for target localization in frequency-only MIMO radar is proposed and it is compared with previous method. These methods use only received frequencies, and all of other unknown quantities can be written by using locations of the target, the receivers and the transmitters. If the received frequencies are known only, desired area can be searched grid by grid for all possible (x, y) coordinates to find the position of the target in 2D space.