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1. 发明授权

US08166460B2 System and method for analyzing HTTP sessions 有权
标题翻译：用于分析HTTP会话的系统和方法
公开(公告)号：US08166460B2
公开(公告)日：2012-04-24
申请号：US11860113
申请日：2007-09-24
申请人： Rahul Jindal , Rohit Aggarwal , Mike Sauer
发明人： Rahul Jindal , Rohit Aggarwal , Mike Sauer
IPC分类号： G06F9/44 , G06F15/16
CPC分类号： H04L67/02 , H04L67/38
摘要： Software intended to operate in a clustered environment can be tested for appropriate failover behavior through the use of an automated tool which allows failover to be simulated without requiring that the application be deployed in a cluster environment and observing the effects of actual failover. Such an automated tool can measure the characteristics of one or more session objects created by the application and provide appropriate messages for a developer when those characteristics indicate improper coding for failover.
摘要翻译：旨在在群集环境中运行的软件可以通过使用自动化工具进行适当的故障转移行为测试，从而允许在不需要将应用程序部署在群集环境中并观察实际故障转移的影响的情况下进行故障切换。这种自动化工具可以测量由应用程序创建的一个或多个会话对象的特征，并且当这些特征指示对故障转移进行不正确的编码时，为开发者提供适当的消息。

2. 发明申请

US20080098119A1 System and Method for Analyzing HTTP Sessions 有权
标题翻译：用于分析HTTP会话的系统和方法
公开(公告)号：US20080098119A1
公开(公告)日：2008-04-24
申请号：US11860113
申请日：2007-09-24
申请人： Rahul Jindal , Rohit Aggarwal , Mike Sauer
发明人： Rahul Jindal , Rohit Aggarwal , Mike Sauer
IPC分类号： G06F15/16 , G06F11/00
CPC分类号： H04L67/02 , H04L67/38
摘要： Software intended to operate in a clustered environment can be tested for appropriate failover behavior through the use of an automated tool which allows failover to be simulated without requiring that the application be deployed in a cluster environment and observing the effects of actual failover. Such an automated tool can measure the characteristics of one or more session objects created by the application and provide appropriate messages for a developer when those characteristics indicate improper coding for failover.
摘要翻译：旨在在群集环境中运行的软件可以通过使用自动化工具进行适当的故障转移行为测试，从而允许在不需要将应用程序部署在群集环境中并观察实际故障转移的影响的情况下进行故障切换。这种自动化工具可以测量由应用程序创建的一个或多个会话对象的特征，并且当这些特征指示对故障转移进行不正确的编码时，为开发者提供适当的消息。

3. 发明申请

US20140122382A1 BAYESIAN MODELING OF PRE-TRANSPLANT VARIABLES ACCURATELY PREDICTS KIDNEY GRAFT SURVIVAL 审中-公开
标题翻译：预先准确预测的贝叶斯模型准确预测KIDNEY GRAFT SURVIVAL
公开(公告)号：US20140122382A1
公开(公告)日：2014-05-01
申请号：US13662456
申请日：2012-10-27
申请人： Eric A. Elster , Doug Tadaki , Trevor S. Brown , Rahul Jindal
发明人： Eric A. Elster , Doug Tadaki , Trevor S. Brown , Rahul Jindal
IPC分类号： A61B5/00
CPC分类号： A61B5/7267 , A61B5/201 , A61B5/4848 , A61B5/7275 , G06F19/00 , G16H10/60 , G16H50/20 , G16H50/50
摘要： An embodiment of the invention provides a method for determining a patient-specific probability of renal transplant survival. The method collects clinical parameters from a plurality of renal transplant donor and patient to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient/donor; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative organ matching. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant survival.
摘要翻译：本发明的一个实施例提供了一种用于确定患者特异性肾移植存活概率的方法。该方法从多个肾移植供体和患者收集临床参数以创建训练数据库。使用培训数据库中的数据创建完全无监督的贝叶斯信念网络模型; 并且，完全无监督的贝叶斯信仰网络得到验证。从个体患者/供体收集临床参数; 并且通过图形用户界面将这样的临床参数输入到完全无监督的贝叶斯信仰网络模型中。患者特异性疾病概率是从完全无监督的贝叶斯信念网络模型输出的，并发送到图形用户界面，供临床医生在术前器官匹配中使用。使用来自个体患者的临床参数和患者特异性移植生存概率来更新完全无监督的贝叶斯信念网络模型。

4. 发明申请

US20220372335A1 TAPE WITH MULTIPLE SIDED ADHESIVE MATERIAL 有权
公开(公告)号：US20220372335A1
公开(公告)日：2022-11-24
申请号：US17767178
申请日：2020-10-16
申请人： Rahul Jindal , Rajan Gupta
发明人： Rahul Jindal , Rajan Gupta
IPC分类号： C09J7/20
摘要： An adhesive tape is disclosed that can simplify the process of pasting a torn, cut off, additional piece of material into its position. The adhesive tape comprising a strip that comprises of flaps made up of flexible material extending radially from a common axis along the length of the strip. The surfaces of the flap are either both adhesive surfaces or one adhesive surface and another is non-adhesive surface. The invention provides a removable layer which protects an adhesive quality of the adhesive surface on which corresponding removable layer is pasted. The invention also provides a method of easily tracing the removable layer which is pasted onto the tape which relates to the method to know the approximate/exact amount of tape left in a roll.

5. 发明授权

US09561006B2 Bayesian modeling of pre-transplant variables accurately predicts kidney graft survival 有权
标题翻译：移植前变量的贝叶斯模型准确预测肾移植物存活
公开(公告)号：US09561006B2
公开(公告)日：2017-02-07
申请号：US13662456
申请日：2012-10-27
申请人： Eric A. Elster , Doug Tadaki , Trevor S. Brown , Rahul Jindal
发明人： Eric A. Elster , Doug Tadaki , Trevor S. Brown , Rahul Jindal
IPC分类号： G06F15/18 , A61B5/00 , A61B5/20 , G06F19/00
CPC分类号： A61B5/7267 , A61B5/201 , A61B5/4848 , A61B5/7275 , G06F19/00 , G16H10/60 , G16H50/20 , G16H50/50
摘要： An embodiment of the invention provides a method for determining a patient-specific probability of renal transplant survival. The method collects clinical parameters from a plurality of renal transplant donor and patient to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient/donor; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative organ matching. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant survival.
摘要翻译：本发明的一个实施例提供了一种用于确定患者特异性肾移植存活概率的方法。该方法从多个肾移植供体和患者收集临床参数以创建训练数据库。使用培训数据库中的数据创建完全无监督的贝叶斯信念网络模型; 并且，完全无监督的贝叶斯信仰网络得到验证。从个体患者/供体收集临床参数; 并且通过图形用户界面将这样的临床参数输入到完全无监督的贝叶斯信仰网络模型中。患者特异性疾病概率是从完全无监督的贝叶斯信念网络模型输出的，并发送到图形用户界面，供临床医生在术前器官匹配中使用。使用来自个体患者的临床参数和患者特异性移植生存概率来更新完全无监督的贝叶斯信念网络模型。

6. 发明申请

US20220363272A1 METHOD AND SYSTEM TO PREDICT VARIATION IN MILEAGE OF A VEHICLE AS PER FUEL IN FUEL TANK, FUEL DENSITY, TIRE AIR PRESSURE AND TO OPTIMIZE IT 有权
公开(公告)号：US20220363272A1
公开(公告)日：2022-11-17
申请号：US17767155
申请日：2020-11-10
申请人： Rahul Jindal , Rohan Garg
发明人： Rahul Jindal , Rohan Garg
IPC分类号： B60W50/00 , B60W50/14 , B60W40/105 , H04W4/40
摘要： A mileage prediction and optimization system (FIG. 1) is disclosed for optimizing the mileage of a vehicle. The mileage prediction and optimization system comprises a prediction and optimization module (300) adapted to determine variation in mileage of the vehicle at least based on the current fuel volume, current speed, current fuel density, the current tire air pressure, the current tire air temperature, current fetched values from an ECU module (700) and the pre-defined mileage data of the vehicle. Further, the prediction and optimization module (300) is adapted to optimize the mileage of the vehicle by reducing variation of fuel density, reducing variation of tire air pressure and informing optimal gear-speed combinations to a user regardless of whether the vehicle is stationary or in motion.

7. 发明申请

US20120296835A1 PATENT SCORING AND CLASSIFICATION 审中-公开
标题翻译：专利分级和分类
公开(公告)号：US20120296835A1
公开(公告)日：2012-11-22
申请号：US13575126
申请日：2010-01-25
申请人： Arif Khan K , Rahul Jindal
发明人： Arif Khan K , Rahul Jindal
IPC分类号： G06Q50/26
CPC分类号： G06Q50/18
摘要： A method, system, and apparatus for classifying intangible assets are provided. The method includes determining an objective of classification. The method further includes constructing, via a processor, a Discriminant Analysis (DA) model using one or more test sets of intangible assets. The DA model includes one or more discriminant functions operable to classify the one or more test set of intangible assets into two or more groups based on a set of attributes associated with one or more intangible assets of the test set of intangible assets to meet the objective of classification. Thereafter, the method includes classifying a target set of intangible assets via the DA model.
摘要翻译：提供了分类无形资产的方法，系统和设备。该方法包括确定分类目标。该方法还包括通过处理器，使用一个或多个无形资产测试集来构建判别分析（DA）模型。 DA模型包括一个或多个判别函数，可操作以基于与无形资产的测试集合的一个或多个无形资产相关联的一组属性来将无形资产的一个或多个测试集合分成两个或更多个组，以满足目标的分类。此后，该方法包括通过DA模型对目标无形资产集进行分类。

8. 发明申请

US20160206249A9 BAYESIAN MODELING OF PRE-TRANSPLANT VARIABLES ACCURATELY PREDICTS KIDNEY GRAFT SURVIVAL 审中-公开
标题翻译：预先准确预测的贝叶斯模型准确预测KIDNEY GRAFT SURVIVAL
公开(公告)号：US20160206249A9
公开(公告)日：2016-07-21
申请号：US13662456
申请日：2012-10-27
申请人： Eric A. Elster , Doug Tadaki , Trevor S. Brown , Rahul Jindal
发明人： Eric A. Elster , Doug Tadaki , Trevor S. Brown , Rahul Jindal
IPC分类号： A61B5/00
CPC分类号： A61B5/7267 , A61B5/201 , A61B5/4848 , A61B5/7275 , G06F19/00 , G16H10/60 , G16H50/20 , G16H50/50
摘要： An embodiment of the invention provides a method for determining a patient-specific probability of renal transplant survival. The method collects clinical parameters from a plurality of renal transplant donor and patient to create a training database. A fully unsupervised Bayesian Belief Network model is created using data from the training database; and, the fully unsupervised Bayesian Belief Network is validated. Clinical parameters are collected from an individual patient/donor; and, such clinical parameters are input into the fully unsupervised Bayesian Belief Network model via a graphical user interface. The patient-specific probability of disease is output from the fully unsupervised Bayesian Belief Network model and sent to the graphical user interface for use by a clinician in pre-operative organ matching. The fully unsupervised Bayesian Belief Network model is updated using the clinical parameters from the individual patient and the patient-specific probability of transplant survival.
摘要翻译：本发明的一个实施例提供了一种用于确定患者特异性肾移植存活概率的方法。该方法从多个肾移植供体和患者收集临床参数以创建训练数据库。使用培训数据库中的数据创建完全无监督的贝叶斯信念网络模型; 并且，完全无监督的贝叶斯信仰网络得到验证。从个体患者/供体收集临床参数; 并且通过图形用户界面将这样的临床参数输入到完全无监督的贝叶斯信仰网络模型中。患者特异性疾病概率是从完全无监督的贝叶斯信念网络模型输出的，并发送到图形用户界面，供临床医生在术前器官匹配中使用。使用来自个体患者的临床参数和患者特异性移植生存概率来更新完全无监督的贝叶斯信念网络模型。

9. 发明申请

US20130073439A1 METHODS AND SYSTEMS FOR PATENT VALUATION USING FINANCIAL RATIOS 审中-公开
标题翻译：使用财务比率进行专利估值的方法和系统
公开(公告)号：US20130073439A1
公开(公告)日：2013-03-21
申请号：US13698495
申请日：2011-05-18
申请人： Ashish Porwal , Rahul Jindal
发明人： Ashish Porwal , Rahul Jindal
IPC分类号： G06Q40/00
CPC分类号： G06Q40/06
摘要： A technique for valuation of intangible assets is provided. The technique includes determining a present value of all future earnings from an intangible asset based on a current earning and one or more financial ratios. The technique further includes determining a value of the intangible asset based on the present value of all future earnings.
摘要翻译：提供了无形资产估值技术。该技术包括根据目前的收入和一个或多个财务比率来确定来自无形资产的所有未来收益的现值。该技术还包括根据所有未来收益的现值确定无形资产的价值。

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