Augmented reality system to assist inexperienced pool players

Computational Visual Media - Pool and billiards are amongst a family of games played on a table with six pockets along the rails. This paper presents an augmented reality tool designed to assist...     

A dynamic overproduce-and-choose strategy for the selection of classifier ensembles

The overproduce-and-choose strategy, which is divided into the overproduction and selection phases, has traditionally focused on finding the most accurate subset of classifiers at the selection phase, and using it to predict the class of all the samples in the test data set. It is therefore, a static classifier ensemble selection strategy. In this paper, we propose a dynamic overproduce-and-choose strategy which combines optimization and dynamic selection in a two-level selection phase to allow the selection of the most confident subset of classifiers to label each test sample individually. The optimization level is intended to generate a population of highly accurate candidate classifier ensembles, while the dynamic selection level applies measures of confidence to reveal the candidate ensemble with the highest degree of confidence in the current decision. Experimental results conducted to compare the proposed method to a static overproduce-and-choose strategy and a classical dynamic classifier selection approach demonstrate that our method outperforms both these selection-based methods, and is also more efficient in terms of performance than combining the decisions of all classifiers in the initial pool.     

LEGClust—A Clustering Algorithm Based on Layered Entropic Subgraphs

Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity measures are distance measures. The derived proximity matrices can be used to build graphs, which provide the basic structure for some clustering methods. We present here a new proximity matrix based on an entropic measure and also a clustering algorithm (LEGCIust) that builds layers of subgraphs based on this matrix and uses them and a hierarchical agglomerative clustering technique to form the clusters. Our approach capitalizes on both a graph structure and a hierarchical construction. Moreover, by using entropy as a proximity measure, we are able, with no assumption about the cluster shapes, to capture the local structure of the data, forcing the clustering method to reflect this structure. We present several experiments on artificial and real data sets that provide evidence on the superior performance of this new algorithm when compared with competing ones.     

LEGClust- a clustering algorithm based on layered entropic subgraphs.

Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity measures are distance measures. The derived proximity matrices can be used to build graphs, which provide the basic structure for some clustering methods. We present here a new proximity matrix based on an entropic measure and also a clustering algorithm (LEGClust) that builds layers of subgraphs based on this matrix, and uses them and a hierarchical agglomerative clustering technique to form the clusters. Our approach capitalizes on both a graph structure and a hierarchical construction. Moreover, by using entropy as a proximity measure we are able, with no assumption about the cluster shapes, to capture the local structure of the data, forcing the clustering method to reflect this structure. We present several experiments on artificial and real data sets that provide evidence on the superior performance of this new algorithm when compared with competing ones.     

Improving the schedulability of soft real-time open dynamic systems: The inheritor is actually a debtor

This paper presents the Clearing Fund Protocol, a three layered protocol designed to schedule soft real-time sets of precedence related tasks with shared resources. These sets are processed in an open dynamic environment. Open because new applications may enter the system at any time and dynamic because the schedulability is tested on-line as tasks request admission. Top-down, the three layers are the Clearing Fund, the Bandwidth Inheritance and two versions of the Constant Bandwidth Server algorithms. Bandwidth Inheritance applies a priority inheritance mechanism to the Constant Bandwidth Server. However, a serious drawback is its unfairness. In fact, a task executing in a server can potentially steal the bandwidth of another server without paying any penalty. The main idea of the Clearing Fund Algorithm is to keep track of processor-time debts contracted by lower priority tasks that block higher priority ones and are executed in the higher priority servers by having inherited the higher priority. The proposed algorithm reduces the undesirable effects of those priority inversions because the blocked task can finish its execution in its own server or in the server of the blocking task, whichever has the nearest deadline. If demanded, debts are paid back in that way. Inheritors are therefore debtors. Moreover, at certain instants in time, all existing debts may be waived and the servers are reset making a clear restart of the system. The Clearing Fund Protocol showed definite better performances when evaluated by simulations against Bandwidth Inheritance, the protocol it tries to improve.     

A prototype for cartographic human body analysis

A cartographic-oriented model uses algebraic map operations to perform spatial analysis of medical data relative to the human body. A prototype system uses 3D visualization techniques to deliver analysis results. A prototype implementation suggests the model might provide the basis for a medical application tool that introduces new information insight.     

Incidence of different pork quality categories in a Portuguese slaughterhouse: A survey

This study was designed to evaluate the incidence of the PSE/DFD status in a Portuguese pig slaughterhouse, covering two seasons of the year (spring and summer) in order to find out if the proportions of those poor meat quality categories were sufficient to concern the meat industry. Meat quality classification was based on the measurements of the pH(60), pH(24), drip losses and colour (L, a, b) in the longissimus dorsi muscle (between the last third and fourth ribs) of 380 pigs randomly chosen from the line. The high global incidence of PSE and likely PSE (30%) as well as DFD (10%) carcasses and the enormous variation of the meat quality between the different days of analysis proves that the pig population presents a great variation of halothane genotype and that handling procedures have to be optimized in order to decrease stress and glycogen store depletion. The percentage of PSE carcasses during the summer season was double that found in the spring, probably due to a higher environmental temperature and relative humidity.     

Progressive ladder network topology combining interferometric and intensity fiber-optic-based sensors

Progressive ladder topology is studied by consideration of its properties of power budget and coupler tailoring. Optimization criteria are addressed for lossless and real systems, and their basic characteristics are compared with other topologies. Numerical results are presented, and an experiment is described for the case in which the network supports interferometric and intensity (with referentiation) fiber-optic-based sensors.     

Prognostic factors in resectable gastric cancer: results of EORTC study no. 40813 on FAM adjuvant chemotherapy

BACKGROUND: The high incidence of locoregional recurrences and distant metastases after curative surgery for gastric cancer calls for improved locoregional control and systemic adjuvant treatment. METHODS: In a randomized clinical trial on adjuvant FAM2 chemotherapy, quality of surgery was evaluated by comparing surgical and pathology data. Univariate and multivariate analysis was made to evaluate the effect of prognostic factors on survival and time of recurrence in relation to patients, tumor, and therapy. RESULTS: Of 314 patients randomized from 28 European institutions, 159 comprised the control and 155 the FAM2 group. After a median follow-up of 80 months, no statistically significant difference was found between survivals. However, for recurrence time, treated patients had a significant advantage over controls (p = 0.02). At univariate analysis, statistically significant differences in survival and time to progression emerged for T, N, disease stage and "adequacy" of surgery. The multivariate analysis retained preoperative Hb level, T, N, and "adequacy" of surgery for time of survival; and T, N, "adequacy" of surgery and adjuvant chemotherapy for recurrence time. CONCLUSIONS: Disease stage is the most important prognostic factor. "Adequate" surgery has an important effect. Adjuvant FAM2 delayed time of recurrence, but did not influence overall survival.