Abstract: A seeding machine includes a main frame, and a row unit coupled to the main frame. The row unit has a row unit frame, a gauge wheel coupled to the row unit frame, and a furrow opener coupled to the row unit frame, the furrow opener having a stationary or rotating surface that contacts and moves soil. The row unit also includes a furrow closer, the furrow closer having a stationary or rotating surface that contacts and presses soil. The seeding machine also includes a downforce adjustment system for adjusting an amount of downforce applied to the row unit, the downforce adjustment system including a moisture sensor, a controller configured to receive a signal from the moisture sensor, and an actuator configured to change the amount of downforce applied to the row unit based on the signal received by the controller.

Abstract: Message management and classification techniques are described. In one or more implementations, a message received from a sender for delivery via a user account is examined to extract one or more features of the message. A determination is then made as to whether the message corresponds to one or more categories based on the extracted features, the categories usable to enable features to be applied to the message in a user interface.

Abstract: Message management and classification techniques are described. In one or more implementations, a message received from a sender for delivery via a user account is examined to extract one or more features of the message. A determination is then made as to whether the message corresponds to one or more categories based on the extracted features, the categories usable to enable features to be applied to the message in a user interface.

Abstract: Geo-data spam filters are described. In one or more implementations, origin data and language data of a message are evaluated to establish a score for the message indicating a likelihood that the message is spam. The evaluation includes comparing the origin data and the language data to ranked lists indicating message origins and languages with which a respective message recipient interacts positively and ranked lists indicating message origins and languages with which the respective recipient interacts negatively. Interactions of the respective recipient with previously sent messages may be tracked to form these lists. Based on the score established by evaluating the origin data and the language data of the message, the message is filtered for delivery.

Abstract: Sensor information is received from a set of sensors. First and second sets of machine monitoring data are generated from the sensor information. The first set of machine monitoring data is sent to a control system with a display in an operator compartment of a mobile machine. The second set of machine monitoring data is sent to a processing system that is separate from the control system.

Abstract: Sensor information is received from a set of sensors. First and second sets of machine monitoring data are generated from the sensor information. The first set of machine monitoring data is sent to a control system with a display in an operator compartment of a mobile machine. The second set of machine monitoring data is sent to a processing system that is separate from the control system.

Abstract: Sensor information is received from a set of sensors. First and second sets of machine monitoring data are generated from the sensor information. The first set of machine monitoring data is sent to a control system with a display in an operator compartment of a mobile machine. The second set of machine monitoring data is sent to a processing system that is separate from the control system.

Abstract: The filtering of activities generated by nodes of a network while interacting with a device may be performed by evaluating the desirability of the activities (e.g., a spam or not-spam determination of email messages sent by the node) and assigning a trust rating to the node. However, nodes are often identified by network address, and an operator of a node sending undesirable activities may reassign the network address of the node in order to avoid heavy filtering. Instead, nodes may be identified as being controlled by a network entity (e.g., an autonomous system identified in a border gateway protocol routing table.) The network entity is assigned a network entity trust rating based on the trust ratings of the nodes controlled thereby, and an appropriate level of activity filtering based on the network entity trust rating may be selected for subsequent activities received from all nodes controlled by the network entity.

Abstract: Campaign detection techniques are described. In implementations, a signature is computed for each of a plurality of emails to be communicated by a service provider to respective intended recipients. A determination is made that two or more of the plurality of emails is similar based on the respective signatures. Responsive to a finding that a number of similar emails exceeds a threshold, an indication is output that the similar emails have a likelihood of being involved in a spam campaign.

Abstract: A computer implemented method for filtering unwanted bulk email in an email system and providing a positive user experience is provided. The method enables protection of email users from unsolicited bulk email using user-provided data on user interactions at both a user storage level and a global level with an email system. Metadata on user interactions with messages is collected. Messages are received by the system and evaluated using a global filter which assigns a score resulting in a message action. The action may be message delivery, message non-delivery or message routing, based on a score assigned by the global filter. When the message is delivered to user storage, the message may be examined relative to the metadata, and may alter the message action to an action different than the message action resulting from the score. Metadata for a plurality of users is returned to the global filter for use in making filtering future messages and modifies the global filter.

Abstract: A system and method of managing unsolicited email sent to an email system over a network. Email messages are received at an message at an inbound mail transfer agent. A determination is made as to whether the email message is suspected to be an unsolicited suspect message. One or more queries for additional information on one or more characteristics of the message is initiated. Determinations are made based on replies to the queries before issuing a message accepted for delivery indication to a sending server.

Abstract: In embodiments of dynamic intervals for synchronizing data, the data is periodically synchronized between computing devices, such as between server devices, client devices, and/or between client and server devices. A polling optimization service can assess heuristics that are associated with the data synchronizations between the computing devices, and determine optimal dynamic intervals to periodically synchronize the data based on the heuristics. The polling optimization service can then iterate to further assess the heuristics that are associated with subsequent data synchronizations and determine updates of the optimal dynamic intervals. The polling optimization service updates the heuristics based on the subsequent and ongoing data synchronizations, and iterates to update the optimal dynamic intervals based on the updated heuristics.

Abstract: Trusted user accounts of an application provider are determined. Graphs, such as trees, are created with each node corresponding to a trusted account. Each of the nodes is associated with a vouching quota, or the nodes may share a vouching quota. Untrusted user accounts are determined. For each of these untrusted accounts, a trusted user account that has a social networking relationship is determined. If the node corresponding to the trusted user account has enough vouching quota to vouch for the untrusted user account, then the quota is debited, a node is added for the untrusted user account to the graph, and the untrusted user account is vouched for. If not, available vouching quota may be borrowed from other nodes in the graph.

Abstract: A computer implemented system and method to enable protection of email users from unsolicited bulk email using a message delivery delay based on characteristics detected in selected messages. Messages are evaluated for characteristics resembling unsolicited bulk email. A determination is made whether a message passing through the email system exhibits such characteristics and whether to delay the message. Suspect messages may be delayed for a period of time, the delay period being dependent on the characteristics giving rise to a determination to delay. Following the period, additional information received during the delay period characterizing the message is used to determine whether to dispose or deliver the message. Messages evaluated can be inbound to the email system, outbound to other email systems, or moving within the email system.

Abstract: Geo-data spam filters are described. In one or more implementations, origin data and language data of a message are evaluated to establish a score for the message indicating a likelihood that the message is spam. The evaluation includes comparing the origin data and the language data to ranked lists indicating message origins and languages with which a respective message recipient interacts positively and ranked lists indicating message origins and languages with which the respective recipient interacts negatively. Interactions of the respective recipient with previously sent messages may be tracked to form these lists. Based on the score established by evaluating the origin data and the language data of the message, the message is filtered for delivery.

Abstract: Geo-data spam filters are described. In one or more implementations, origin data and language data of a message are evaluated to establish a score for the message indicating a likelihood that the message is spam. The evaluation includes comparing the origin data and the language data to ranked lists indicating message origins and languages with which a respective message recipient interacts positively and ranked lists indicating message origins and languages with which the respective recipient interacts negatively. Interactions of the respective recipient with previously sent messages may be tracked to form these lists. Based message, the message is filtered for delivery.

Abstract: Trusted user accounts of an application provider are determined. Graphs, such as trees, are created with each node corresponding to a trusted account. Each of the nodes is associated with a vouching quota, or the nodes may share a vouching quota. Untrusted user accounts are determined. For each of these untrusted accounts, a trusted user account that has a social networking relationship is determined. If the node corresponding to the trusted user account has enough vouching quota to vouch for the untrusted user account, then the quota is debited, a node is added for the untrusted user account to the graph, and the untrusted user account is vouched for. If not, available vouching quota may be borrowed from other nodes in the graph.

Abstract: A method of displaying email messages to a user is provided. Spam classification information and meta data is associated with email messages received for a user. Email message summary information is displayed in a user interface based on whether the meta data associated with the message meets or exceeds a threshold display level for the summary information. The user provides input via the user interface which is an indication to change the threshold display level and the change is dynamically displayed.

Abstract: Detection of user accounts associated with spammer attacks may be performed by constructing a social graph of email users. Biggest connected components (BCC) of the social graph may be used to identify legitimate user accounts, as the majority of the users in the biggest connected components are legitimate users. BCC users may be used to identify more legitimate users. Using degree-based detection techniques and PageRank based detection techniques, the hijacked user accounts and spammer user accounts may be identified. The users' email sending and receiving behaviors may also be examined, and the subgraph structure may be used to detect stealthy attackers. From the social graph analysis, legitimate user accounts, malicious user accounts, and compromised user accounts can be identified.

Abstract: Message management and classification techniques are described. In one or more implementations, a message received from a sender for delivery via a user account is examined to extract one or more features of the message. A determination is then made as to whether the message corresponds to one or more categories based on the extracted features, the categories usable to enable features to be applied to the message in a user interface.