Diplomarbeit - Chair 3 - Department of Computer Science - TU Dortmund

ll verletzt zum Beispiel das Prinzip der Autonomie von intelligenten Agenten (nach Weiß und Jakob [9] und Wooldridge und Jennings [10]). In Weiß und Jakob wird die "schwache" Charakterisierung des Age [...] Conference on Self-Adaptation and Self-Organization (SASO’08), Venice, Italy, Oct 2008. IEEE Press. [9] Gerhard Weiß and Ralf Jakob. Agentenorientierte Softwareentwicklung. Springer Verlag, 2005. [10] Michael …

TU Dortmund -- Computer Science VIII

from the use of this software. Download Download the newest version of mySVM/db: mysvmDB.0.9.1.zip (Version 0.9.1, October 16th, 2002). Installation Installation Requirements: mySVM/db was developed and …

Journal01_02.pdf

Berufsbildung nur mit einer erweiterten beruflichen Fachdidaktik erreicht werden kann (vgl. Ott, 1998, 9ff). Die Schwierigkeiten, eine den gewandelten gesellschaftlichen Ansprüchen genügende Didaktik der [...] hnik, 1992.8. Salovey P., Mayer, J.D.: Intelligence. In: Imagination, Cogniti- on and Personality, 9/1990 Schneider, P.: Selbstqualifizierung und Selbstorganisation: Zwei Leitideen einer neuen Berufsbildung …

Dynamic Data Driven Dimensioning of Balancing Power with k-Nearest Neighbors

load probability (LOLP). The current deficit probability is 0.1%, which means that in 0.1% of cases (9 hours a year) a lack of reserve is accepted. But due to the change from the former randomly caused power [...] addition the aim of prior examinations was to predict the expected demand in future energy scenarios [8], [9], whereas this approach concentrates on the prediction of control reserve today. As a model we choose [...] enlarged by 10% - the upper boundary is set at 1.1 times the 25% percentile and the upper bound at 0.9 times the 75% percentile - so that 25% of the samples were considered. The resulting levels for the …

Anticancer platinum complex

Nagata S, kumura N, Yoshikawa T, Shirakawa T, . Pharm Res 2002; 19: 323-9 m and tissues. Proc Natl Acad Sci USA 1987; 84:265-9 Fujie Y, Yamamoto H, Nagn CY, Taka Hayashi T, Suzuki R, Ezumi K, Takemasa [...] treatment, cells were harvested and lysed with CelLytic™-M (Sigma-Aldrich) and centrifuged at 10,000 rpm (9,100 g) at 4°C for 15 min. The supernatant was collected, and the total protein content was determined [...] cells from multiple forms 189 of caspase-dependent apoptosis. Proc Natl Acad Sci USA 1998; 95: 7024-9 , Ohnishi N, okoyama T. Up-regulation of MDR1 akara K, Sakaeda T, Yagami T, Kobayashi H, arm Bull 2002a; …

of internal rating transitions. The number of b ranges between 2 and 7 b 2 3 4 5 6 7 −2 log(∆) 93.9 125.9 289.3 345.8 447.3 626.2 p-value 0.009 0.535 < 0.001 < 0.001 < 0.001 < 0.001 In simulations for the [...] − ξ2,∞) ⊂ (−q0 + ξ1,∞). Proof: This is based on the openness of the parameter space see Figure 2. 9 For simplification we now restrict, for the meantime, to the case of only one change-point, namely λhj(t) [...] t1)(t) q3 hj + 2 1[t1,T ](t) (qhj + δhj)3 (8) and ∂3 log(λhj(t)) ∂δ3 hj = 2 1[t1,T ](t) (qhj + δhj)3 . (9) They are obviously continuous in qhj and δhj. The mixed second and third derivatives with respect to …

trade wheat MNB MNB with per-class normalization 0.88 0.9 0.92 0.94 0.96 0.98 1 course faculty project student MNB MNB with per-class normalization 0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1 a c c [...] trade wheat CC MNB with per-class normalization 0.88 0.9 0.92 0.94 0.96 0.98 1 course faculty project student CC MNB with per-class normalization 0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1 a c c [...] ti m e .l a w m e d ic a l. e q u ip . m e ta l. + .m in in g MNB MNB with per-class normalization 0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1 m is c .c a p it a l. g o o d s m is c .f a b .p ro d …

DeepLearning on FPGAs - Introduction to Data Mining

Java,Python,... DeepLearning on FPGAs 8 Data Mining Basics What is Data Mining? DeepLearning on FPGAs 9 Data Mining Basics “The overall goal of the data mining process is to extract information from a data [...] if d(~x∗, ~x) < min and ~x /∈ S then 5: min = d(~x∗, ~x) 6: ~xmin = ~x 7: end if 8: S = S ∪ {~xmin} 9: end for 10: end for Lookup in O(K) Computation in O(d) Worst Case runtime: O(K2Nd) for every new example [...] if d(~x∗, ~x) < min and ~x /∈ S then 5: min = d(~x∗, ~x) 6: ~xmin = ~x 7: end if 8: S = S ∪ {~xmin} 9: end for 10: end for Lookup in O(K) Computation in O(d) Worst Case runtime: O(K2Nd) for every new example …