Abstract: A robot arm assembly includes a first robot arm, a second robot arm, a third robot arm, a connecting base, a first driving assembly, a second driving assembly, a third driving assembly, and a cable receiving tube. The connecting base includes a housing and a protection cover. A sidewall of the housing defines an opening. The protection cover covers the opening and is mounted on the housing. An end of the housing defines a cable inlet. The first driving assembly rotates the first robot arm. The second driving assembly rotates the second robot arm. The third driving assembly rotates the third robot arm. The cable receiving tube is received in the first robot arm, the second robot arm, and the third robot arm.

Abstract: Method, apparatus, and programs for customizing a web site are provided. In one example, a method for customizing a web site is provided. One or more representations corresponding to one or more customizable components of a web site are provided. The one or more representations are to be displayed on a display screen to a user. An input entered by the user and directed to a specific customizable component of the web site is received. How to customize the specific customizable component of the web site is determined based on the input. An instruction is generated with respect to the customizable component. The instruction is used to implement customization of the specific customizable component of the web site in accordance with the input from the user.

Abstract: Techniques for predicting a user response to content are provided. In example embodiments, one or more feature vectors are assembled into an assembled feature vector. A particular one of the feature vectors not being available is determined. In response to determining that the particular one of the feature vectors is not available, the particular feature vector is ignored based on an importance value associated with the particular feature vector. A substitute value associated with the particular feature vector is inserted into a portion of the assembled feature vector associated with the particular feature vector. A prediction modeling process based on the assembled feature vector and a prediction model is performed to predict a likelihood of a particular member performing a particular user action on a particular content item.

Abstract: A robot arm assembly with tubes or pipes carrying fluids or electrical cables which do not get bent and are relatively straight, and are not disrupted by, the moving parts of the robot arm includes a first robot arm, a second robot arm, a third robot arm, and a flexible carrying tube. The second robot arm includes a first axle base, a first input shaft, a first bevel gear, and a second bevel gear. The flexible tube is inserted into the first bevel gear and the second bevel gear along a first axis, and fixed to the output shaft.

Abstract: Systems and methods for reducing a churn rate associated with subscribers of social network services are described. In some example embodiments, the systems and methods may access activity information associated with a former subscriber of a social network service, compare the accessed activity information to activity information associated with subscribers of the social network service, identify one or more differences between the activity information associated with the former subscriber of the social network service and the activity information associated with the subscribers of the social network service, and perform an action based on the identified one or more differences.

Abstract: A robot arm assembly includes a first robot arm, a second robot arm, and a third robot arm. The first robot arm includes a first body and a backlash adjusting assembly received in the first body. The backlash adjusting assembly includes a base plate, a protruding shaft perpendicularly coupled to the base plate, and an adjusting member. The base plate defines a slotted hole. The adjusting member is detachably inserted into the slotted hole and is detachably coupled to first body. The second robot arm includes a second body and a first transmission assembly rotatably coupled to the second body. The first transmission assembly includes a first adjusting gear, a first intermediate gear, and a second adjusting gear. The first intermediate gear meshes the first and second adjusting gear. The second adjusting gear is coupled to the second body. The first intermediate gear is sleeved on the protruding shaft.

Abstract: Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such as Web mining, search marketing, bioinformatics, citation analysis, and epidemiology. A probabilistic model is presented for relational clustering, which also provides a principal framework to unify various important clustering tasks including traditional attributes-based clustering, semi-supervised clustering, co-clustering and graph clustering. The model seeks to identify cluster structures for each type of data objects and interaction patterns between different types of objects. Under this model, parametric hard and soft relational clustering algorithms are provided under a large number of exponential family distributions.

Abstract: An elliptical exercise apparatus includes a main device, a guider frame rotatably connected to the main device via an axis, the guider frame being rotatable relative to the ground and the main device, two crank units respectively rotatably connected to a right side and a left side of the main device, two supporting sets both interconnected between the two crank units and the guider frame, two swing links respectively pivotally connected to two sides of the main device, and two control links both interconnected between the two supporting sets and the two swing links. Under this arrangement, when the elliptical exercise apparatus is folded, one supporting set abuts against the guider frame and one corresponding control link simultaneously, so that when the user moves the elliptical exercise apparatus which is folded, the structure of the elliptical exercise apparatus prevents unwanted motion of the cranks and the supporting sets.

Abstract: A system to generate a targeted churn reduction campaign in an on-line social networking system may be implemented as a churn reduction campaign generator. In one embodiment, a churn reduction campaign generator utilizes a subscriber retention model and a churn probability model. When there is an indication, within an on-line social networking system, that a member, who is a subscriber to a paid service in the on-line social networking system, is likely to fail to renew their subscription (or “churn”), the churn reduction campaign generator executes the subscriber retention model to trigger a targeted subscriber retention campaign.

Abstract: A robot arm assembly includes a first output shaft, a first driving mechanism, a second output shaft and a second driving mechanism. The first driving mechanism includes a first driving motor for driving the first output shaft to rotate, a first driving belt pulley non-rotatably connected to the first output shaft, and a first belt winding on the first driving motor and the first driving belt pulley. The second output shaft is rotatably sleeved in the first output shaft. The second driving mechanism includes a second driving motor for driving the second output shaft to rotate, a second driving belt pulley non-rotatably connected to the second output shaft, and a second belt winding on the second driving motor and the second driving belt pulley.

Abstract: This invention discloses an elliptical exercise apparatus that is characterized in having left and right tracks disposed in a guider frame which is pivotally coupled to a rear portion of the elliptical exercise apparatus. When a user uses the elliptical exercise apparatus, the guider frame is at a use position. When the user folds the elliptical exercise apparatus, the guider frame is at a storage position. A user can complete folding procedure merely by operating the guider frame without lifting some heavy components of the elliptical exercise apparatus.

Abstract: A robot arm mechanism includes a drive arm, a support arm, a transmission assembly and three tool portions. The support arm is rotatably connected to the drive arm. The three tool portions are rotatably mounted on the support arm. The transmission assembly includes a first bevel gear, a second bevel gear and a transmission belt. The first bevel gear is mounted on the drive arm, the second bevel gear is mounted on the support arm and engages with the first bevel gear. The transmission belt is driven by the second bevel gear and imparts rotary motion to the plurality of tool portions simultaneously.

Abstract: A gear transmission mechanism includes a housing, a first transmission assembly, a second transmission assembly, and a gear clearance adjustment assembly. The first transmission assembly includes an input shaft, and the second transmission assembly includes an output shaft. The gear clearance adjustment assembly includes an adjustment base mounted on the housing, fasteners, bearings, a washer, a fixing member, and a pair of freely rotatable adjusting gears for the transmission of rotative force. The adjusting gears mesh with the first and second transmission gears.

Abstract: A method for identifying facial features comprises following steps: An image tracing step is performed to receive video data of a plurality of face images and to obtain a real-time background image from the video data by a video tracing technique. A data calculating step is performed to calculate a video data difference between a current face image and the real-time background image. A process setting step is performed to set an iteration number according to the video data difference. A coordinate requesting step is performed to obtain facial feature coordinates of a previous face image, the previous one of the current face image, serving as initial facial feature coordinates. A localization step is performed to obtain current facial feature coordinates of the current image by conducting an iterative calculation according to the iteration number and based on the initial facial feature coordinates.

Abstract: Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such as Web mining, search marketing, bioinformatics, citation analysis, and epidemiology. A probabilistic model is presented for relational clustering, which also provides a principal framework to unify various important clustering tasks including traditional attributes-based clustering, semi-supervised clustering, co-clustering and graph clustering. The model seeks to identify cluster structures for each type of data objects and interaction patterns between different types of objects. Under this model, parametric hard and soft relational clustering algorithms are provided under a large number of exponential family distributions.

Abstract: Techniques for predicting a user response to content are described. According to various embodiments, a configuration file is accessed, where the configuration file includes a user-specification of raw data accessible via external data sources and raw data encoding rules. In some embodiments, the raw data includes raw member data associated with a particular member and raw content data associated with a particular content item. Thereafter, source modules encode the raw data from the external data sources into feature vectors, based on the raw data encoding rules. An assembler module assembles one or more of the feature vectors into an assembled feature vector, based on user-specified assembly rules included in the configuration file. A prediction module performs a prediction modeling process based on the assembled feature vector and a prediction model, to predict a likelihood of the particular member performing a particular user action on the particular content item.

Abstract: A balancing mechanism for a robot configured for lifting heavy weights comprises a hollow balancing body comprising an opening; an elastic assembly received in the balancing body and a pulling rod assembly received in the balancing body and hinged to a robot arm of the robot. One end of the pulling rod assembly resists the elastic assembly, and another opposite end of the pulling rod assembly extends out from the balancing body through the opening, the pulling rod assembly is movably assembled with the balancing body via the elastic assembly to make the elastic assembly capable of producing a balancing moment against the gravity moment of the robot arm.

Abstract: Techniques for predicting a user response to content are described. According to various embodiments, a configuration file is accessed, where the configuration file includes a user-specification of raw data accessible via external data sources and raw data encoding rules. In some embodiments, the raw data includes raw member data associated with a particular member and raw content data associated with a particular content item. Thereafter, source modules encode the raw data from the external data sources into feature vectors, based on the raw data encoding rules. An assembler module assembles one or more of the feature vectors into an assembled feature vector, based on user-specified assembly rules included in the configuration file. A prediction module performs a prediction modeling process based on the assembled feature vector and a prediction model, to predict a likelihood of the particular member performing a particular user action on the particular content item.

Abstract: A robot includes a base seat, a first arm fixed to the base seat, a second arm rotatably connected to the first arm, an output shaft rotatably connected to a distal end of the second arm, a first driving member, and a first transmission mechanism. The first transmission mechanism includes a first transmission belt and a reducer. The first driving member is located at one end of the first arm adjacent to the base seat, the reducer is located at the other end of the first arm away from the base seat, and connected to the second arm, the first driving member is capable of driving the reducer via the first transmission belt.

Abstract: A focusing mechanism for focusing a lens module includes a base seat, a movable platform, a positioning assembly, a support bracket and a plurality of arms. The positioning assembly is fixed to the base seat and passes through a center of the movable platform, a lens of the lens module is detachably mounted on the positioning assembly. The support bracket is fixed to the movable platform. A sensor of the lens module is detachably mounted on the support bracket. Each of the plurality of arms rotatably interconnects the movable platform and the base seat, the movable platform drives the support bracket to rotate relative to the positioning assembly to enable the lens to rotate relative to the sensor via a drive of the arms.