Towards Using Unlabeled Data in a Sparse-coding Framework for Human Activity Recognition

We propose a sparse-coding framework for activity recognition in ubiquitous and mobile computing that alleviates two fundamental problems of current supervised learning approaches. (i) It automatically derives a compact, sparse and meaningful feature representation of sensor data that does not rely on prior expert knowledge and generalizes extremely well across domain boundaries. (ii) It exploits unlabeled sample data for bootstrapping effective activity recognizers, i.e., substantially reduces the amount of ground truth annotation required for model estimation. Such unlabeled data is trivial to obtain, e.g., through contemporary smartphones carried by users as they go about their everyday activities. Based on the self-taught learning paradigm we automatically derive an over-complete set of basis vectors from unlabeled data that captures inherent patterns present within activity data. Through projecting raw sensor data onto the feature space defined by such over-complete sets of basis vectors effective feature extraction is pursued. Given these learned feature representations, classification backends are then trained using small amounts of labeled training data. We study the new approach in detail using two datasets which differ in terms of the recognition tasks and sensor modalities. Primarily we focus on transportation mode analysis task, a popular task in mobile-phone based sensing. The sparse-coding framework significantly outperforms the state-of-the-art in supervised learning approaches. Furthermore, we demonstrate the great practical potential of the new approach by successfully evaluating its generalization capabilities across both domain and sensor modalities by considering the popular Opportunity dataset. Our feature learning approach outperforms state-of-the-art approaches to analyzing activities in daily living.Comment: 18 pages, 12 figures, Pervasive and Mobile Computing, 201

Chromosome 7 genetic aberrations of extranodal gastric diffuse large B-cell lymphoma

In vorangegangenen Studien an extranodalen diffus großzelligen B-Zell-Lymphomen des Magens, im Englischen als „gastric diffuse large B-cell lymphoma“ bezeichnet (DLBCL), hat unsere Studiengruppe einige genomische Aberrationen entdeckt. Eine dieser Aberrationen - „loss of heterozygosity“ (LOH) - befand sich auf dem langen Arm des Chromosoms 7. Um diese auffällige Region und das gesamte Chromosom 7 noch näher auf Aberrationen zu untersuchen, wurde eine Analyse mit 29 Mikrosatellitenmarker durchgeführt und eine genaue Chromosomenkarte der genetischen Aberrationen auf Chromosom 7 erstellt. In dieser Studie fanden sich 5 sogenannte Hot-Spots von Aberrationen. Insgesamt fanden wir bei 42% der 31 untersuchten DLBCL eine solche Aberration. Die häufigste genetische Aberration auf Chromosom 7 (20,7% der informativen Fälle) war der Verlust einer Region in der zytogenetischen Bande 7p21.1. Ein weiterer LOH-Hot-Spot auf 7p wurde in 3 Lymphomen (10%) bei 7p12.1-13 identifiziert. In diesem Hot-Spot liegt der Gen-Lokus für das Ikaros-Gen. Der lange Arm von Chromosom 7 wies mehrere Aberrationen auf: erstens in der Bande 7q31.1-32.2, zweitens bei 7q34-36.3. Zusätzlich identifizierten wir einen Amplifikations-Hot-Spot auf dem langen Arm; er war in der Bande 7q22.3-31.1 lokalisiert und kam bei 4 Tumoren vor (12,9%). Das Vorkommen genetischer Aberrationen auf Chromosom 7 bei DLBCL ist deutlich höher als anfänglich erwartet. Solch häufige genetische Auffälligkeiten sprechen dafür, dass mögliche neue Tumorsuppressorgene und Onkogene in den oben näher bezeichneten Regionen lokalisiert sind.In a previous study on extranodal gastric high-grade large B-cell lymphoma (DLBCL), we found several common aberrations, one of them being LOH on the long arm of chromosome 7. To more closely characterize the deleted region and survey chromosome 7 for additional abnormalities, we expanded the number of microsatellite markers this chromosome was analyzed with to 29 and generated a detailed chromosomal map of genetic aberrations. Altogether, 5 aberration hot spots were identified; 42% of the assayed 31 DLBCLs showed an allelic imbalance. The highest frequency of LOH was found in the 7p21.1 band showing aberrations in 6 cases (20.7% of informative cases). An additional 7p LOH hot spot was detected in 7p12.1-13 (encompassing the Ikaros gene locus) present in three (10%) lymphomas. The long arm of the chromosome displayed the most extensive aberrations: the first one in bands 7q31.2-32.3, the second one on 7q34-36.3. Additionally, we identified a new hot spot of amplifications on the long arm, in bands 7q22.3-31.1 displayed by four (12.9%) tumors. The prevalence of chromosome 7 aberrations in DLBCL is thus more frequent than initially expected. Such recurrent abnormalities suggest that novel tumor suppressor genes and oncogenes are located in the above-specified regions