… Then they designed efficient algorithms and data structures for gap detection and gap
updates when the disks were changed. Their method works well both in Euclidean space and on …

… Each point along the two-dimensional space in the first sequence represents a student.
In the second sequence, students A, B and C are assigned to a group that has the greatest …

… ) is the probability density of a particle when it is vibrating in a “cage” made up of surrounding
nearest neighbors [49]. This is similar in spirit to finding … 5) of the simulated two dimensional …

… Their probability of detection was 97.1% and the false alarm rate was 20.3%. Nevertheless,
… feature space to two-dimensional (retaining ~80% of the total variance) phase space for …

… linear nature of localization error due to small inaccuracy in cross-ratio measurements.
Properties of the localization error due to two dimensional … to a linear light source in 3-D space is …

… in our system is to extract local features of the detected body part(orientation,centroid. . . etc),
… In short, our system can detect the human body parts and classify the posture of human at …

… Experiment results show that the approaches proposed in this thesis can increase the … Soil
Moisture Contents detection, the soil or the structure of soil layer’s study, the detection of the …

… the clustering algorithm is critical in this application. In chapter 2, we proposed an algorithm
… Let hx = nx/N be the probability for gray level x occurred in a PCB image, nx be the number …

… π π π π for two-dimensional input variables. Therefore, M is … , since one cluster in the input
space corresponds to one … σ represent the mean and variance of that cluster, respectively…

… , a wideband two dimensional (2-D) elliptical GBSM for massive MIMO was proposed in [55,56],
where clusters were assumed to … A VR is a region in space corresponding to a cluster. A …