Abstract
Laser diagnostics and treatment procedures are commonly performed for visible and near-IR wavelengths. The knowledge of the wavelength dependences for the optical properties of various biological tissues in this spectral range is useful for clinical applications. Since the optical properties of human liver have been previously known only for near-IR wavelengths, the aim is to estimate their wavelength dependences between 400 and 1000 nm. Using spectral measurements from liver samples in this range, we determine their optical properties with the inverse adding-doubling method. The obtained results indicate the presence of bile, oxyhaemoglobin and deoxyhaemoglobin in human liver. The combination of these biological components results in strong absorption for wavelengths between 400 and 600 nm, with peaks at unusual wavelengths. For wavelengths above 600 nm, the wavelength dependences for all optical properties present the typical behavior, but strong and shifted absorption observed for wavelengths below 600 nm has been previously unknown and can be useful for clinical procedures with lasers working in this range.

Abstract
In IEEE 802.11 based wireless networks interference increases as more access points are added. A metric helping to quantize this interference seems to be of high interest. In this paper we study the relationship between the improved attacking case metric, which captures interference, and throughput for IEEE 802.11 based network using directional antenna. The y(1/3) = a + b (ln x)(3) model was found to best represent the relationship between the interference metric and the network throughput. We use this model to predict the performance of similar networks and decide the best configuration a network operator could use for planning his network.

Abstract
Modern search is heavily powered by knowledge bases, but users still query using keywords or natural language. As search becomes increasingly dependent on the integration of text and knowledge, novel approaches for a unified representation of combined data present the opportunity to unlock new ranking strategies. We have previously proposed the graph-of-entity as a purely graph-based representation and retrieval model, however this model would scale poorly. We tackle the scalability issue by adapting the model so that it can be represented as a hypergraph. This enables a significant reduction of the number of (hyper)edges, in regard to the number of nodes, while nearly capturing the same amount of information. Moreover, such a higher-order data structure, presents the ability to capture richer types of relations, including nary connections such as synonymy, or subsumption. We present the hypergraph-of-entity as the next step in the graph-of-entity model, where we explore a ranking approach based on biased random walks. We evaluate the approaches using a subset of the INEX 2009 Wikipedia Collection. While performance is still below the state of the art, we were, in part, able to achieve a MAP score similar to TF-IDF and greatly improve indexing efficiency over the graph-of-entity.

Abstract
Particle swarm optimization (PSO) is a search algorithm inspired by the collective behavior of flocking birds and fishes. This algorithm is widely adopted for solving optimization problems involving one objective. The evaluation of the PSO progress is usually measured by the fitness of the best particle and the average fitness of the particles. When several objectives are considered, the PSO may incorporate distinct strategies to preserve nondominated solutions along the iterations. The performance of the multiobjective PSO (MOPSO) is usually evaluated by considering the resulting swarm at the end of the algorithm. In this paper, two indices based on the Shannon entropy are presented, to study the swarm dynamic evolution during the MOPSO execution. The results show that both indices are useful for analyzing the diversity and convergence of multiobjective algorithms.

Abstract
[No abstract available]

Abstract
Line-following robots can recognize and follow a line drawn on a surface. Their operating principles have elements that could be used in the development of numerous autonomous technologies, with applications in education and industry. This class of robots usually represent the first contact students have with educational robotics, being used to develop students' logic thinking and programming skills. The cost of robotic platforms is still prohibitive in low-budget schools and universities, which makes almost impossible having a platform for each small group of students in a classroom, harming the learning process. This work proposes a 3D web-based open-source simulator for Pololu's 3Pi line-following robots, making such technology more accessible and available even for distance learning courses. The developed software simulates the robot's physical structure, behavior, and operations-as being able to read surfaces-, enabling the user to observe the robot following the line as the code commands. The simulator was validated based on experiments that included motion analysis and time measurements of pre-stablished tasks so that its execution could be more coherently based on what happens in reality.