objectives: this study sought to evaluate the accuracy and errors of linear measurements of mesiodistal dimensions of kennedy class iii edentulous space using cone beam computed tomography (cbct) in comparison with clinical measurements. materials and methods: nineteen kennedy class iii dental arches were evaluated. an impression was made of each dental arch and poured with dental stone. the di...

New network applications which involve transmission of continuous media data, such as audio and video conferencing, introduce immense challenges for the design of packet-switching intemetworks. Existing flow and congestion control mechanisms have been shown to be ineffective for supporting the real-time requirements of continuous media data transfers. We propose a novel bandwidth regulation mec...

Time-trials represent an ecologically valid approach to assessment of endurance performance. Such information is useful in the application of testing protocols and estimation of sample sizes required for research/magnitude based inference methods. The present study aimed to investigate the intra-subject variability of 5 km time-trial running performance in trained runners. Six competitive train...

[Purpose] Assessment of posture is an important goal of physical therapy interventions for preventing the progression of forward head posture (FHP). The purpose of this study was to determine the inter- and intra-rater reliabilities of the assessment of FHP. [Subjects and Methods] We recruited 45 participants (20 male subjects, 25 female subjects) from a university student population. Two physi...

One of the problems in antigen-specific cancer immunotherapy is the low density of the tumor antigen-derived peptide endogenously presented on tumor cell surface major histocompatibility complex class I molecules. To overcome this, we are engaged in research on peptide intra-tumor injection to enhance tumor cell antigenicity. In in vivo studies using immunodeficient mice, the peptide injected i...

Unknown faults may occur in practical applications, necessitating an open-set classifier that can classify known classes as well recognize unknown faults. The current deep classification methods are implicit optimizing the intra- or inter-class distances, which result performance degradation when number of far exceeds known. In this study, discriminative angle features for vibration signals inv...

We investigate object recognition and classification in a setting with a large number of classes as well as recognition and identification of individual objects of high similarity. Real-world data sets were obtained for the classification and identification tasks. The considered classification task is the discrimination of modern coins into several hundreds of different classes. Identification ...

We propose a novel approach to annotating weakly labelled data. In contrast to many existing approaches that perform annotation by seeking clusters of self-similar exemplars (minimising intra-class variance), we perform image annotation by selecting exemplars that have never occurred before in the much larger, and strongly annotated, negative training set (maximising inter-class variance). Comp...

A successful detection and classification system must have two properties: it should be general enough to compensate for intra-class variability and it should be specific enough to reject false positives. We describe a method to learn class-specific feature detectors that are robust to intra-class variability. These feature detectors enable a representation that can be used to drive a subsequen...