New approximations for minimum-weighted dominating sets and minimum-weighted connected dominating sets on unit disk graphs

Given a node-weighted graph, the minimum-weighted dominating set (MWDS) problem is to find a minimum-weighted vertex subset such that, for any vertex, it is contained in this subset or it has a neighbor contained in this set. And the minimum-weighted connected dominating set (MWCDS) problem is to find a MWDS such that the graph induced by this subset is connected. In this paper, we study these two problems on a unit disk graph. A (4 +ε)-approximation algorithm for an MWDS based on a dynamic programming algorithm for a Min-Weight Chromatic Disk Cover is presented. Meanwhile, we also propose a (1 +ε)-approximation algorithm for the connecting part by showing a polynomial-time approximation scheme for a Node-Weighted Steiner Tree problem when the given terminal set is c-local and thus obtain a (5 +ε)-approximation algorithm for an MWCDS.     

Performance evaluation for a transportation system in stochastic case

In a single-commodity multistate flow network, the arc capacity is stochastic and thus the system capacity (i.e. the maximum flow from the source to the sink) is not a fixed number. This paper constructs a multicommodity multistate flow network with weighted capacity allocation to model a transportation system. Each arc with cost attribute has several possible capacities. The capacity weight, the consumed amount of arc capacity by per commodity, varies with the arcs and types of commodity. We define the system capacity as a demand vector d if the system fulfills at most d. The addressed problem in this work is to measure the service quality of a transportation system. We propose a performance index, the probability that the upper bound of the system capacity equals a demand vector d subject to the budget constraint. A simple algorithm based on minimal cuts is presented to generate all (d,B)-MC that are the maximal capacity vectors meeting exactly the demand d under the budget B. The proposed performance index can be subsequently evaluated in terms of such (d,B)-MC.     

Connected sum of digital closed surfaces

During the past 20 years the research of digital surfaces has proceeded to find their properties in the digital space Zⁿ, such as a topological number, a simple k-point, the 3D-Jordan theorem, a k-separating set, a boundary detecting algorithm and so on. Actually, unlike surfaces in a continuous space, the features of digital surfaces have different characteristics. The aim of this paper is to introduce the notion of a digital closed k-surface in Zⁿ, n ? 3, with the general k-adjacency relations as a generalization of Malgouyres’ and Morgenthaler’s k-surfaces in Z³, to establish some minimal simple closed k-surfaces in Z³ and to find their digital topological properties in relation with the k-fundamental group and k-contractibility. Moreover, a connected sum of two digital closed surfaces is introduced and its digital topological properties are investigated.     

Supporting early pruning in top-k query processing on massive data

This paper analyzes the execution behavior of “No Random Accesses” (NRA) and determines the depths to which each sorted file is scanned in growing phase and shrinking phase of NRA respectively. The analysis shows that NRA needs to maintain a large quantity of candidate tuples in growing phase on massive data. Based on the analysis, this paper proposes a novel top-k algorithm Top-K with Early Pruning (TKEP) which performs early pruning in growing phase. General rule and mathematical analysis for early pruning are presented in this paper. The theoretical analysis shows that early pruning can prune most of the candidate tuples. Although TKEP is an approximate method to obtain the top-k result, the probability for correctness is extremely high. Extensive experiments show that TKEP has a significant advantage over NRA.     

An adaptive overlay network inspired by social behaviour

Nature is a great source of inspiration for scientists, because natural systems seem to be able to find the best way to solve a given problem by using simple and robust mechanisms. Studying complex natural systems, scientists usually find that simple local dynamics lead to sophisticated macroscopic structures and behaviour. It seems that some kind of local interaction rules naturally allow the system to auto-organize itself as an efficient and robust structure, which can easily solve different tasks. Examples of such complex systems are social networks, where a small set of basic interaction rules leads to a relatively robust and efficient communication structure. In this paper, we present PROSA, a semantic peer-to-peer (P2P) overlay network inspired by social dynamics. The way queries are forwarded and links among peers are established in PROSA resemble the way people ask other people for collaboration, help or information. Behaving as a social network of peers, PROSA naturally evolves to a small world, where all peers can be reached in a fast and efficient way. The underlying algorithm used for query forwarding, based only on local choices, is both reliable and effective: peers sharing similar resources are eventually connected with each other, allowing queries to be successfully answered in a really small amount of time. The resulting emergent structure can guarantee fast responses and good query recall.     

A constrained optimization approach for an adaptive generalized subspace tracking algorithm

In this paper, we present an orthonormal version of the generalized signal subspace tracking. It is based on an interpretation of the generalized signal subspace as the solution of a constrained minimization task. This algorithm, referred to as the CGST algorithm, guarantees the C_x-orthonormality of the estimated generalized signal subspace basis at each iteration which C_x denotes the correlation matrix of the sequence x(t). An efficient implementation of the proposed algorithm enhances applicability of it in real time applications.     

Four-arc approximation to ellipses: The best in general

So far, the four-arc approximations to an ellipse E are made under the condition that the major and minor axes keep strictly unchanged. In general, however, this condition is unnecessary. Then the fitting can be further improved. Considering a representative quadrant of E, we first draw two auxiliary circular arcs tangent to E at the axes but having a gap ε at their boundary, such that the small arc S lies outside the large arc L. Meanwhile the extreme errors of S and L w.r.t. E are ε and −ε respectively. Giving the radii of S and L a decrement −ε/2 and an increment ε/2 brings them to join smoothly. Thus, reducing the overall error to minimum, an analytic solution in implicit form is derived.     

A dual K-Na selective Prussian blue nanotubes sensor

A strategy for dual sensing of Na⁺ and K⁺ ions using Prussian blue nanotubes via selective inter/deintercalation of K⁺ ion and competitive inhibition by Na⁺ ion, is reported. The analytical signal is derived from the cyclic voltammetry cathodic peak position E_pc of Prussian blue nanotubes. Na⁺ and K⁺ levels in a sample solution can be determined conveniently using one Prussian blue nanotubes sensor. In addition, this versatile method can be applied for the analysis of single type of either Na⁺ or K⁺ ions. The dual-ion sensor response towards Na⁺ and K⁺ can be described using a model based on the competitive inhibition effects of Na⁺ on K⁺ inter/deintercalation in Prussian blue nanotubes. Successful application of the Prussian blue nanotubes sensor for Na⁺ and K⁺ determination is demonstrated in artificial saliva.     

Concise: Compressed ‘n’ Composable Integer Set

Bit arrays, or bitmaps, are used to significantly speed up set operations in several areas, such as data warehousing, information retrieval, and data mining, to cite a few. However, bitmaps usually use a large storage space, thus requiring compression. Consequently, there is a space-time tradeoff among compression schemes. The Word Aligned Hybrid (WAH) bitmap compression trades some space to allow for bitwise operations without first decompressing bitmaps. WAH has been recognized as the most efficient scheme in terms of computation time. In this paper we present Concise (Compressed ‘n’ Composable Integer Set), a new scheme that enjoys significantly better performances than WAH. In particular, when compared to WAH our algorithm is able to reduce the required memory up to 50%, while having comparable computation time. Further, we show that Concise can be efficiently used to represent sets of integral numbers in lieu of well-known data structures such as arrays, lists, hashtables, and self-balancing binary search trees. Extensive experiments over synthetic data show the effectiveness of our proposal.     

FINE: A Fully Informed aNd Efficient communication-induced checkpointing protocol for distributed systems

Communication-Induced Checkpointing (CIC) protocols are classified into two categories in the literature: Index-based and Model-based. In this paper, we discuss two data structures being used in these two kinds of CIC protocols, and their different roles in helping the checkpointing algorithms to enforce Z-cycle Free (ZCF) property. Then, we present our Fully Informed aNd Efficient (FINE) communication-induced checkpointing algorithm, which not only has less checkpointing overhead than the well-known Fully Informed (FI) CIC protocol proposed by Helary et al. but also has less message overhead. Performance evaluation indicates that our protocol performs better than many of the other existing CIC protocols.     

Learning complex action models with quantifiers and logical implications

Automated planning requires action models described using languages such as the Planning Domain Definition Language (PDDL) as input, but building action models from scratch is a very difficult and time-consuming task, even for experts. This is because it is difficult to formally describe all conditions and changes, reflected in the preconditions and effects of action models. In the past, there have been algorithms that can automatically learn simple action models from plan traces. However, there are many cases in the real world where we need more complicated expressions based on universal and existential quantifiers, as well as logical implications in action models to precisely describe the underlying mechanisms of the actions. Such complex action models cannot be learned using many previous algorithms. In this article, we present a novel algorithm called LAMP (Learning Action Models from Plan traces), to learn action models with quantifiers and logical implications from a set of observed plan traces with only partially observed intermediate state information. The LAMP algorithm generates candidate formulas that are passed to a Markov Logic Network (MLN) for selecting the most likely subsets of candidate formulas. The selected subset of formulas is then transformed into learned action models, which can then be tweaked by domain experts to arrive at the final models. We evaluate our approach in four planning domains to demonstrate that LAMP is effective in learning complex action models. We also analyze the human effort saved by using LAMP in helping to create action models through a user study. Finally, we apply LAMP to a real-world application domain for software requirement engineering to help the engineers acquire software requirements and show that LAMP can indeed help experts a great deal in real-world knowledge-engineering applications.     

Restricted compositions and permutations: From old to new Gray codes

Any Gray code for a set of combinatorial objects defines a total order relation on this set: x is less than y if and only if y occurs after x in the Gray code list. Let ? denote the order relation induced by the classical Gray code for the product set (the natural extension of the Binary Reflected Gray Code to k-ary tuples). The restriction of ? to the set of compositions and bounded compositions gives known Gray codes for those sets. Here we show that ? restricted to the set of bounded compositions of an interval yields still a Gray code. An n-composition of an interval is an n-tuple of integers whose sum lies between two integers; and the set of bounded n-compositions of an interval simultaneously generalizes product set and compositions of an integer, and so ? put under a single roof all these Gray codes.As a byproduct we obtain Gray codes for permutations with a number of inversions lying between two integers, and with even/odd number of inversions or cycles. Such particular classes of permutations are used to solve some computational difficult problems.     

The values of college students in business simulation game: A means-end chain approach

Business simulation games (BSGs) enable students to practice making decisions in a virtual environment, accumulate experience in application of strategies, and train themselves in modes of decision-making. This study examines the value sought by players of BSG. In this study, a means-end chain (MEC) model was adopted as the basis, and ladder method soft laddering was used to conduct in-depth interviews with students who had experience in using BSGs. The chain concept of “attribute-consequence-value” was used to understand students’ value cognition structures. Content analysis was used to analyze the attributes-consequences-values for BSGs players, then converted into a Hierarchical Value Map (HVM). The results showed that students consider teamwork and market diversity as the most important attributes, and the consequences of a cooperative approach and market diversity are emotional exchange and multi-thinking, with the ultimate value brought to users by exchanges between teams and constant thinking being interpersonal relationships and a sense of accomplishment.     

Non-contractible non-edges in 2-connected graphs

Any pair of non-adjacent vertices forms a non-edge in a graph. Contraction of a non-edge merges two non-adjacent vertices into a single vertex such that the edges incident on the non-adjacent vertices are now incident on the merged vertex. In this paper, we consider simple connected graphs, hence parallel edges are removed after contraction. The minimum number of nodes whose removal disconnects the graph is the connectivity of the graph. We say a graph is k-connected, if its connectivity is k. A non-edge in a k-connected graph is contractible if its contraction does not result in a graph of lower connectivity. Otherwise the non-edge is non-contractible. We focus our study on non-contractible non-edges in 2-connected graphs. We show that cycles are the only 2-connected graphs in which every non-edge is non-contractible.     

Enhanced chemosensing of ammonia based on the novel molecular semiconductor-doped insulator (MSDI) heterojunctions

A series of new molecular semiconductor-doped insulator (MSDI) heterojunctions as conductimetric transducers to NH₃ sensing were fabricated based on a novel semiconducting molecular material, an amphiphilic tris(phthalocyaninato) rare earth triple-decker complex, Eu₂[Pc(15C5)₄]₂[Pc(OC₁₀H₂₁)₈], quasi-Langmuir-Shäfer (QLS) film, as a top-layer, and vacuum-deposited and cast film of CuPc as well as copper tetra-tert-butyl phthalocyanine (CuTTBPc) QLS film as a sub-layer, named as MSDIs 1, 2 and 3, respectively. MSDIs 1-3 and respective sub-layers prepared from three different methods were characterized by X-ray diffraction, electronic absorption spectra and current-voltage (I-V) measurements. Depending on the sub-layer film-forming method used, α-phase CuPc film structure, β-phase CuPc crystallites and H-type aggregates of CuTTBPc have been obtained, respectively. An increasing sensitivity to NH₃ at varied concentrations in the range of 15-800 ppm, follows the order MSDI 2 < MSDI 3 < MSDI 1, revealing the effect of sub-layer film structures on sensing performance of the MSDIs. In particular, the time-dependent current plot of the MSDI 1, with α-phase CuPc film as a sub-layer, clearly shows an excellent separation of the different ammonia concentration levels and nearly complete reversibility and reproducibility even at room temperature, which is unique among the phthalocyanine-based ammonia sensors thus far reported in the literature. This provides a general method to improve sensor response of organic heterojunctions by controlling and tuning the film structure of sub-layer with appropriate fabrication techniques. On the other hand, the enhanced sensitivity, stability and reproducible response of the MSDI 1 heterostructure in comparison with the respective single-layer films have also been obtained. A judicious combination of materials and molecular architectures has led to enhanced sensing properties of the MSDI 1, in which control at the molecular level can be achieved.     

Nonlinear mappings in problem solving and their PSO-based development

The study is devoted to a concept and algorithmic realization of nonlinear mappings aimed at increasing the effectiveness of the problem solving method. Given the original input space X and a certain problem solving method M, designed is a nonlinear mapping ? so that the method operating in the transformed space M(?(X)) becomes more efficient. The nonlinear mappings realize a transformation of X through contractions and expansions of selected regions of the original space. In particular, we show how a piecewise linear mapping is optimized by using particle swarm optimization (PSO) and a suitable fitness function quantifying the objective of the problem. Several families of problems are investigated and illustrated through illustrative experimental results.     

The complexity of achievement and maintenance problems in agent-based systems

We completely classify the computational complexity of the basic achievement and maintenance agent design problems in bounded environments when these problems are parameterized by the number of environment states and the number of agent actions. The different problems are P-complete, NP-complete, co-NP-complete or PSPACE-complete (when they are not trivial). We also consider alternative achievement and maintenance agent design problems by allowing longer runs in environments (that is, our environments are bounded but the bounds are more liberal than was the case previously). Again, we obtain a complete classification but so that the different problems are DEXPTIME-complete, NEXPTIME-complete, co-NEXPTIME-complete or NEXPSPACE-complete (when they are not trivial).     

Synchronizing automata with finitely many minimal synchronizing words

A synchronizing word for a given synchronizing DFA is called minimal if none of its proper factors is synchronizing. We characterize the class of synchronizing automata having only finitely many minimal synchronizing words (the class of such automata is denoted by FG). Using this characterization we prove that any such automaton possesses a synchronizing word of length at most 3n-5. We also prove that checking whether a given DFA A is in FG is co-NP-hard and provide an algorithm for this problem which is exponential in the number of states A.