Factorization in Formal Languages

We consider several novel aspects of unique factorization in formal languages. We reprove the familiar fact that the set uf(L) of words having unique factorization into elements of L is regular if L is regular, and from this deduce an quadratic upper and lower bound on the length of the shortest word not in uf(L). We observe that uf(L) need not be context-free if L is context-free. Next, we consider variations on unique factorization. We define a notion of "semi-unique" factorization, where every factorization has the same number of terms, and show that, if L is regular or even finite, the set of words having such a factorization need not be context-free. Finally, we consider additional variations, such as unique factorization "up to permutation" and "up to subset"

Optimal Reachability in Divergent Weighted Timed Games

Weighted timed games are played by two players on a timed automaton equipped with weights: one player wants to minimise the accumulated weight while reaching a target, while the other has an opposite objective. Used in a reactive synthesis perspective, this quantitative extension of timed games allows one to measure the quality of controllers. Weighted timed games are notoriously difficult and quickly undecidable, even when restricted to non-negative weights. Decidability results exist for subclasses of one-clock games, and for a subclass with non-negative weights defined by a semantical restriction on the weights of cycles. In this work, we introduce the class of divergent weighted timed games as a generalisation of this semantical restriction to arbitrary weights. We show how to compute their optimal value, yielding the first decidable class of weighted timed games with negative weights and an arbitrary number of clocks. In addition, we prove that divergence can be decided in polynomial space. Last, we prove that for untimed games, this restriction yields a class of games for which the value can be computed in polynomial time

Credimus

We believe that economic design and computational complexity---while already important to each other---should become even more important to each other with each passing year. But for that to happen, experts in on the one hand such areas as social choice, economics, and political science and on the other hand computational complexity will have to better understand each other's worldviews. This article, written by two complexity theorists who also work in computational social choice theory, focuses on one direction of that process by presenting a brief overview of how most computational complexity theorists view the world. Although our immediate motivation is to make the lens through which complexity theorists see the world be better understood by those in the social sciences, we also feel that even within computer science it is very important for nontheoreticians to understand how theoreticians think, just as it is equally important within computer science for theoreticians to understand how nontheoreticians think

The accuracy of breast volume measurement methods: a systematic review

Breast volume is a key metric in breast surgery and there are a number of different methods which measure it. However, a lack of knowledge regarding a method’s accuracy and comparability has made it difficult to establish a clinical standard. We have performed a systematic review of the literature to examine the various techniques for measurement of breast volume and to assess their accuracy and usefulness in clinical practice. Each of the fifteen studies we identified had more than ten live participants and assessed volume measurement accuracy using a gold-standard based on the volume, or mass, of a mastectomy specimen. Many of the studies from this review report large (> 200 ml) uncertainty in breast volume and many fail to assess measurement accuracy using appropriate statistical tools. Of the methods assessed, MRI scanning consistently demonstrated the highest accuracy with three studies reporting errors lower than 10% for small (250 ml), medium (500 ml) and large (1,000 ml) breasts. However, as a high-cost, non-routine assessment other methods may be more appropriate

Computing with cells: membrane systems - some complexity issues.

Membrane computing is a branch of natural computing which abstracts computing models from the structure and the functioning of the living cell. The main ingredients of membrane systems, called P systems, are (i) the membrane structure, which consists of a hierarchical arrangements of membranes which delimit compartments where (ii) multisets of symbols, called objects, evolve according to (iii) sets of rules which are localised and associated with compartments. By using the rules in a nondeterministic/deterministic maximally parallel manner, transitions between the system configurations can be obtained. A sequence of transitions is a computation of how the system is evolving. Various ways of controlling the transfer of objects from one membrane to another and applying the rules, as well as possibilities to dissolve, divide or create membranes have been studied. Membrane systems have a great potential for implementing massively concurrent systems in an efficient way that would allow us to solve currently intractable problems once future biotechnology gives way to a practical bio-realization. In this paper we survey some interesting and fundamental complexity issues such as universality vs. nonuniversality, determinism vs. nondeterminism, membrane and alphabet size hierarchies, characterizations of context-sensitive languages and other language classes and various notions of parallelism

Space Complexity of the Directed Reachability Problem over Surface-Embedded Graphs

The graph reachability problem, the computational task of deciding whether there is a path between two given nodes in a graph is the canonical problem for studying space bounded computations. Three central open questions regarding the space complexity of the reachabil-ity problem over directed graphs are: (1) improving Savitch’s O(log2 n) space bound, (2) designing a polynomial-time algorithm with O(n1−) space bound, and (3) designing an unambiguous non-deterministic log-space (UL) algorithm. These are well-known open questions in complex-ity theory, and solving any one of them will be a major breakthrough. We will discuss some of the recent progress reported on these questions for certain subclasses of surface-embedded directed graphs

bk-complete problems and greediness

Kintala and Fischer [7] defined the limited nondeterminism hierarchy within NP, the so called b  hierarchy. bk is the class of languages recognized by polynomial time bounded Turing machines that make at most O(logk n) nondeterministic moves, where n is the length of the input. It has been conjectured that "by restricting the amount of nondeterminism in NP-complete problems, we do not seem to obtain complete problems for bk [4]". We demonstrate that this statement is incorrect under what seems to us to be  the natural interpretation of the term "restricting the amount of nondeterminism". We develop the concept of limited nondeterminism-preserving reductions, and obtain complete problems for bk by restricting the amount of nondeterminism in NP-complete problems. We also discuss the connections between b hierarchy completeness and greedy algorithms; we show that using greediness we can define many complete problems for b