Practical voting rules with partial information

Voting is an essential mechanism that allows multiple agents to reach a joint decision. The joint decision, representing a function over the preferences of all agents, is the winner among all possible (candidate) decisions. To compute the winning candidate, previous work has typically assumed that voters send their complete set of preferences for computation, and in fact this has been shown to be required in the worst case. However, in practice, it may be infeasible for all agents to send a complete set of preferences due to communication limitations and willingness to keep as much information private as possible. The goal of this paper is to empirically evaluate algorithms to reduce communication on various sets of experiments. Accordingly, we propose an iterative algorithm that allows the agents to send only part of their preferences, incrementally. Experiments with simulated and real-world data show that this algorithm results in an average of 35% savings in communications, while guaranteeing that the actual winning candidate is revealed. A second algorithm applies a greedy heuristic to save up to 90% of communications. While this heuristic algorithm cannot guarantee that a true winning candidate is found, we show that in practice, close approximations are obtained.     

Minutia Cylinder-Code: a new representation and matching technique for fingerprint recognition

In this paper, we introduce the Minutia Cylinder-Code (MCC): a novel representation based on 3D data structures (called cylinders), built from minutiae distances and angles. The cylinders can be created starting from a subset of the mandatory features (minutiae position and direction) defined by standards like ISO/IEC 19794-2 (2005). Thanks to the cylinder invariance, fixed-length, and bit-oriented coding, some simple but very effective metrics can be defined to compute local similarities and to consolidate them into a global score. Extensive experiments over FVC2006 databases prove the superiority of MCC with respect to three well-known techniques and demonstrate the feasibility of obtaining a very effective (and interoperable) fingerprint recognition implementation for light architectures.     

The undirected capacitated arc routing problem with profits

A profit and a demand are associated with each edge of a set of profitable edges of a given graph. A travel time is associated with each edge of the graph. A fleet of capacitated vehicles is given to serve the profitable edges. A maximum duration of the route of each vehicle is also given. The profit of an edge can be collected by one vehicle only that also serves the demand of the edge. The objective of this problem, which is called the undirected capacitated arc routing problem with profits (UCARPP), is to find a set of routes that satisfy the constraints on the duration of the route and on the capacity of the vehicle and maximize the total collected profit. We propose a branch-and-price algorithm and several heuristics. We can solve exactly instances with up to 97 profitable edges. The best heuristics find the optimal solution on most of instances where it is available.     

Adoption of open source software in software-intensive organizations – A systematic literature review

ContextOpen source software (OSS) is changing the way organizations develop, acquire, use, and commercialize software.ObjectiveThis paper seeks to identify how organizations adopt OSS, classify the literature according to these ways of adopting OSS, and with a focus on software development evaluate the research on adoption of OSS in organizations.MethodBased on the systematic literature review method we reviewed publications from 24 journals and seven conference and workshop proceedings, published between 1998 and 2008. From a population of 24,289 papers, we identified 112 papers that provide empirical evidence on how organizations actually adopt OSS.ResultsWe show that adopting OSS involves more than simply using OSS products. We moreover provide a classification framework consisting of six distinctly different ways in which organizations adopt OSS. This framework is used to illustrate some of the opportunities and challenges organizations meet when approaching OSS, to show that OSS can be adopted successfully in different ways, and to organize and review existing research. We find that existing research on OSS adoption does not sufficiently describe the context of the organizations studied, and it fails to benefit fully from related research fields. While existing research covers a large number of topics, it contains very few closely related studies. To aid this situation, we offer directions for future research.ConclusionThe implications of our findings are twofold. On the one hand, practitioners should embrace the many opportunities OSS offers, but consciously evaluate the consequences of adopting it in their own context. They may use our framework and the success stories provided by the literature in their own evaluations. On the other hand, researchers should align their work, and perform more empirical research on topics that are important to organizations. Our framework may be used to position this research and to describe the context of the organization they are studying.     

Analysis of the maximum level policy in a production-distribution system

We consider a production-distribution system, where a facility produces one commodity which is distributed to a set of retailers by a fleet of vehicles. Each retailer defines a maximum level of the inventory. The production policy, the retailers replenishment policies and the transportation policy have to be determined so as to minimize the total system cost. The overall cost is composed by fixed and variable production costs at the facility, inventory costs at both facility and retailers and routing costs. We study two different types of replenishment policies. The well-known order-up to level (OU) policy, where the quantity shipped to each retailer is such that the level of its inventory reaches the maximum level, and the maximum level (ML) policy, where the quantity shipped to each retailer is such that the inventory is not greater than the maximum level. We first show that when the transportation is outsourced, the problem with OU policy is NP-hard, whereas there exists a class of instances where the problem with ML policy can be solved in polynomial time. We also show the worst-case performance of the OU policy with respect to the more flexible ML policy. Then, we focus on the ML policy and the design of a hybrid heuristic. We also present an exact algorithm for the solution of the problem with one vehicle. Results of computational experiments carried out on small size instances show that the heuristic can produce high quality solutions in a very short amount of time. Results obtained on a large set of randomly generated problem instances are also shown, aimed at comparing the two policies.     

Luminescent Eu(III) hybrid sensors for in situ copper detection

In this work we used the sol-gel technique to develop luminescent Eu(III) transparent films deposited on glass slides to build for sensor devices capable of monitoring transition metal ions in aqueous solutions. The films were obtained from a bis(trialkoxysilyl) organic precursor synthesized from the amide of the 2,6-pyridinedicarboxylic acid (DPA) with aminopropyltriethoxysilane (APTES) in the presence or absence of cetyl trimethyl ammonium bromide (CTAB) surfactant as templating agent and triethylethoxysilane (TEOS) as crosslinker. These sensor devices were used to perform in situ quenching experiments by Cu(II), Fe(III), Co(II) and Ni(II) ions. The results indicate that the templated films allow the detection and quantification of these metals down to ppb levels by means of the values of the Stern-Volmer constants. In particular, it was shown that Cu(II) acts as an extremely efficient quencher (K_SV = 3.5 × 10⁵ M⁻¹) when compared with the results obtained for the other metals, opening the possibility to use these devices as potential Cu(II) sensors for actual applications in aqueous media.     

Higher Order Sliding Mode Controllers With Optimal Reaching

Higher order sliding mode (HOSM) control design is considered for systems with a known permanent relative degree. In this paper, we introduce the robust Fuller's problem that is a robust generalization of the Fuller's problem, a standard optimal control problem for a chain of integrators with bounded control. By solving the robust Fuller's problem it is possible to obtain feedback laws that are HOSM algorithms of generic order and, in addition, provide optimal finite-time reaching of the sliding manifold. A common difficulty in the use of existing HOSM algorithms is the tuning of design parameters: our methodology proves useful for the tuning of HOSM controller parameters in order to assure desired performances and prevent instabilities. The convergence and stability properties of the proposed family of controllers are theoretically analyzed. Simulation evidence demonstrates their effectiveness.     

Assisting requirements analysts to find latent concerns with <Emphasis Type="Italic">REAssistant</Emphasis>

Textual requirements are very common in software projects. However, this format of requirements often keeps relevant concerns (e.g., performance, synchronization, data access, etc.) from the analyst’s view because their semantics are implicit in the text. Thus, analysts must carefully review requirements documents in order to identify key concerns and their effects. Concern mining tools based on NLP techniques can help in this activity. Nonetheless, existing tools cannot always detect all the crosscutting effects of a given concern on different requirements sections, as this detection requires a semantic analysis of the text. In this work, we describe an automated tool called REAssistant that supports the extraction of semantic information from textual use cases in order to reveal latent crosscutting concerns. To enable the analysis of use cases, we apply a tandem of advanced NLP techniques (e.g, dependency parsing, semantic role labeling, and domain actions) built on the UIMA framework, which generates different annotations for the use cases. Then, REAssistant allows analysts to query these annotations via concern-specific rules in order to identify all the effects of a given concern. The REAssistant tool has been evaluated with several case-studies, showing good results when compared to a manual identification of concerns and a third-party tool. In particular, the tool achieved a remarkable recall regarding the detection of crosscutting concern effects.     

Adaptive inter-layer message routing in 3D networks-on-chip

Existing routing algorithms for 3D deal with regular mesh/torus 3D topologies. Today 3D NoCs are quite irregular, especially those with heterogeneous layers. In this paper, we present a routing algorithm targeting 3D networks-on-chip (NoCs) with incomplete sets of vertical links between adjacent layers. The routing algorithm tolerates multiple link and node failures, in the case of absence of NoC partitioning. In addition, it deals with congestion. The routing algorithm for 3D NoCs preserves the deadlock-free propriety of the chosen 2D routing algorithms. It is also scalable and supports a local reconfiguration that complements the reconfiguration of the 2D routing algorithms in case of failures of nodes or links. The algorithm incurs a small overhead in terms of exchanged messages for reconfiguration and does not introduce significant additional complexity in the routers. Theoretical analysis of the 3D routing algorithm is provided and validated by simulations for different traffic loads and failure rates.