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Dragomir
Dragomir Davidovic, Atlanta, GA US
| Patent application number | Description | Published |
|---|---|---|
| 20110108806 | Method to Modify the Conductivity of Graphene - A gated electrical device includes a non-conductive substrate and a graphene structure disposed on the non-conductive substrate. A metal gate is disposed directly on a portion of the graphene structure. The metal gate includes a first metal that has a high contact resistance with graphene. Two electrical contacts are each placed on the graphene structure so that the metal gate is disposed between the two electrical contacts. In a method of making a gated electrical device, a graphene structure is placed onto a non-conductive substrate. A metal gate is deposited directly on a portion of the graphene structure. Two electrical contacts are deposited on the graphene structure so that the metal gate is disposed between the two electrical contacts. | 05-12-2011 |
Dragomir Ivicevic, New York, NY US
| Patent application number | Description | Published |
|---|---|---|
| 20100244515 | Reclining Chair - In the specification and drawings a chair is described and shown with a resiliently flexible frame having a front seat support; a seat slidably engaged to the front seat support; and a back rotatably engaged to the frame, the back being rotatably engaged to the seat. | 09-30-2010 |
Dragomir Krdzalic, Pretoria ZA
| Patent application number | Description | Published |
|---|---|---|
| 20090216219 | PHOTON THERAPY DEVICE - The invention provides a controller unit for controlling the emission of at least on photon emitted source, the controller unit includes a central processing unit pre-programmed with selectable pre-programmed photonic emission protocols. The photonic emission protocols include parameters for regulating photonic emission from photon emitting sources, with the protocols having a pulsed emission mode for about 30% of the duration of each protocol, and a continuous emission mode for about 70% of the duration of each protocol, with a pulse rate selected from a range of frequencies of between 120 Hz and 20,000 Hz when in the pulsed emission mode. | 08-27-2009 |
Dragomir Ljubojevic, St. Gallen CH
| Patent application number | Description | Published |
|---|---|---|
| 20120112689 | MOBILE ELECTRIC APPLIANCE WITH CHARGE STATUS INDICATOR AND BATTERY FOR IT - A mobile electric appliance is disclosed. The mobile electric appliance includes at least one battery bay for accommodating a battery with at least one voltage-generating cell and a battery-side charge status indicator, an electrical consumer, a power connector, as well as a charging device for charging the at least one battery. In addition, the mobile electric appliance includes means for detecting the charge status of the at least one battery and a device-side charge status indicator arranged on the mobile electric appliance. The battery may also include an interface, which is prepared to relay the charge status determined to an external processing unit. | 05-10-2012 |
| 20120112699 | METHOD AND CHARGING DEVICE FOR CHARGING AT LEAST TWO BATTERIES - A method for charging at least two batteries each having at least one cell is disclosed. During a first charging phase, batteries are charged sequentially to a first charge status and afterwards batteries are charged during a second charging phase sequentially to a second, higher charge status. The first charging phase is begun with the battery having the lowest charge status. In addition, a charging device for carrying out the method according to the invention and a mobile electric appliance including such a charging device are disclosed. | 05-10-2012 |
Dragomir Yankov, Sunnyvale, CA US
| Patent application number | Description | Published |
|---|---|---|
| 20100082400 | SCORING CLICKS FOR CLICK FRAUD PREVENTION - Machine learning techniques are employed to build and evolve classifiers (e.g., decision trees or other rule-based classifiers) which generate scores representing confidence values associated with particular paths through a classifier (rather than discrete class labels), and then compare those scores to tunable thresholds to effect classification. | 04-01-2010 |
| 20100082800 | CLASSIFICATION AND CLUSTER ANALYSIS SPAM DETECTION AND REDUCTION - Multiple features of email traffic are analyzed and extracted. Feature vectors comprising the multiple features are created and cluster analysis is utilized to track spam generation even from dynamically changing or aliased IP addresses. | 04-01-2010 |
| 20110184817 | Sensitivity Categorization of Web Pages - Methods, systems, and computer programs for categorizing the sensitivity of web pages are presented. In one method, a space of sensitive pages is identified based on the sensitivity categorization of a first plurality of web pages and a second plurality of web pages. The first plurality of web pages is obtained by performing search queries using known sensitive words, and the second plurality of web pages includes randomly selected web pages. Additionally, the method identifies a third plurality of web pages that includes web pages on or near the boundary between the space of sensitive pages and the space of non-sensitive pages. The space of sensitive pages is then redefined based on the sensitivity categorization of the first, second, and third pluralities of web pages. Once the space of sensitive pages is defined, the method is used to determine that a given web page is sensitive when the given web page is in the space of sensitive pages. Web pages are included in a marketing operation when the web pages are not sensitive. | 07-28-2011 |
| 20120095943 | SYSTEM FOR TRAINING CLASSIFIERS IN MULTIPLE CATEGORIES THROUGH ACTIVE LEARNING - A system for training classifiers in multiple categories through an active learning system, including a computer having a memory and a processor, the processor programmed to: train an initial set of m binary one-versus-all classifiers, one for each category in a taxonomy, on a labeled dataset of examples stored in a database coupled with the computer; uniformly sample up to a predetermined large number of examples from a second, larger dataset of unlabeled examples stored in a database coupled with the computer; order the sampled unlabeled examples in order of informativeness for each classifier; determine a minimum subset of the unlabeled examples that are most informative for a maximum number of the classifiers to form an active set for learning; and use editorially-labeled versions of the examples of the active set to re-train the classifiers, thereby improving the accuracy of at least some of the classifiers. | 04-19-2012 |