On P Systems with Promoters/Inhibitors

This article shows how the computational universality can be reached by using P systems with object rewriting context-free rules, promot- ers/inhibitors and one catalyst. Both generative and accepting cases are stud- ied. Some examples that illustrate the theoretical issues are also presented

Several Applications of Spiking Neural P Systems

In this paper we investigate some applications of Spiking Neural P Systems regarding their capability to solve some classical computer science problems. In this respect it is studied the versatility of such systems to simulate a well known parallel computational model, namely the Boolean circuits. In addition, another notorious application - the sorting - is considered within this framework

P Systems with Adjoining Controlled Communication Rules

This paper proposes a new model of P systems where the rules are activated by objects present in the neighboring regions. We obtain the computational completeness considering only two membranes, external inhibitors and carriers. Leaving the carriers apart we obtain equality with ET0L systems in terms of number sets

SSD Admission Control for Content Delivery Networks

Content delivery networks (CDNs) are utilized to deliver content with low latency. Solid State Drive (SSD) devices are a cost-effective option for intermediate tier caches in servers used in CDNs. However, excessive writes of content to SSD devices can degrade useful life of such devices. This disclosure describes admission control techniques to manage content in an SSD cache. In particular, a popularity metric for content items is determined based on an inter-arrival time. The popularity metric takes into account past admission history and is dynamically to account for variations in content popularity over different time periods. These techniques balance the SSD cache write rates to optimize the device life and cache performance

FINANCIAL CONTAGION AND INVESTORS BEHAVIOR

International capital markets, in general, seem to be volatile markets, influenced bymany factors, a phenomenon that affects both developed markets, as well as least developed, withemerging market economies suffering most because of this. It is clear, however, that volatility willremain for as long as it is delayed the adoption of specific measures at national and internationalfinancial architecture level, measures that may be necessary to reduce these risks, to limit theirimpact, and that the question financial market can relapse in a manner as efficiently as possible.investor behaviour, financial crisis, rational investor, irational investor, financial contagion

ASSESING THE IMPLEMENTATION OF REAL CONVERGENCE IN ROMANIA

The convergence is an essential objective of the integration process of Romania in the European Union. Minimizing gaps in the level of development that arise between Romania and the average European Union can not be achieved solely through the use of marconvergence, European Union, real convergence

Periaortic venous necklace and renal right double arteries; Case report

The case was found on an organic sample consisting of the two kidneys with the renal pedicles and the corresponding segments of the abdominal aorta and inferior vena cava. From the inferior face of the left renal vein, on the lower side of the aorta, a venous branch with an upward path of 8.02 mm was detached, passing on the anterior face of the aorta, passing before its right side, in order to end on the left side of the inferior vena cava, 13.9 mm above the end of the left renal vein in the inferior vena cava, this branch thus describing a periaortic ring (necklace), in which on the left side of the aorta the inferior adrenal vein ends. The periaortic ring (necklace) had a cross-sectional dimension of 3.2 mm and a vertical one of 1.7 cm. On the right side of the aorta, a 2.9 mm venous branch came out of the renal vein, ending on the left side of the inferior vena cava, 1.2 mm above the end of the left renal vein. At the level of the right kidney there were two renal arteries, superior and inferior. Between the two arteries there was an interval of 5.1 cm

A Parameter-free approach for solving combinatorial optimization problems through biased randomization of efficient heuristics

This paper discusses the use of probabilistic or randomized algorithms for solving combinatorial optimization problems. Our approach employs non-uniform probability distributions to add a biased random behavior to classical heuristics so a large set of alternative good solutions can be quickly obtained in a natural way and without complex conguration processes. This procedure is especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods, both of exact and approximate nature, may fail to reach their full potential. The results obtained are promising enough to suggest that randomizing classical heuristics is a powerful method that can be successfully applied in a variety of casesPeer ReviewedPreprin

A simulation-based approach for solving the flowshop problem

A simulation-based algorithm for the Permutation Flowshop Sequencing Problem (PFSP) is presented. The algorithm uses Monte Carlo Simulation and a discrete version of the triangular distribution to incorporate a randomness criterion in the classical Nawaz, Enscore, and Ham (NEH) heuristic and starts an iterative process in order to obtain a set of alternative solutions to the PFSP. Thus, a random but biased lo We can then consider several properties per solution other than the makespan, such as balanced idle times among machines, number of completed jobs at a given target time, etc. This allows the decision-maker to consider multiple solution characteristics apart from those defined by the aprioristic objective function. Therefore, our methodology provides flexibility during the sequence selection process, which may help to improve the scheduling process. Several tests have been performed to discuss the effectiveness of this approach. The results obtained so far are promising enough to encourage further developments and improvements on the algorithm and its applications in real-life scenarios. In particular, Multi-Agent Simulation is proposed as a promising technique to be explored in future works.Postprint (published version

A parameter-free approach for solving combinatorial optimization problems through biased randomization of efficient heuristics

This paper discusses the use of probabilistic or randomized algorithms for solving combinatorial optimization problems. Our approach employs non-uniform probability distributions to add a biased random behavior to classical heuristics so a large set of alternative good solutions can be quickly obtained in a natural way and without complex con guration processes. This procedure is especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods, both of exact and approximate nature, may fail to reach their full potential. The results obtained are promising enough to suggest that randomizing classical heuristics is a powerful method that can be successfully applied in a variety of cases