Showing papers by "Amazon.com published in 2014"

Improved allometric models to estimate the aboveground biomass of tropical trees

Abstract: Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development.

Unmanned aerial vehicle delivery system

Abstract: This disclosure describes an unmanned aerial vehicle ("UAV") configured to autonomously deliver items of inventory to various destinations. The UAV may receive inventory information and a destination location and autonomously retrieve the inventory from a location within a materials handling facility, compute a route from the materials handling facility to a destination and travel to the destination to deliver the inventory.

Unsupervised feature learning for 3D scene labeling

Abstract: This paper presents an approach for labeling objects in 3D scenes. We introduce HMP3D, a hierarchical sparse coding technique for learning features from 3D point cloud data. HMP3D classifiers are trained using a synthetic dataset of virtual scenes generated using CAD models from an online database. Our scene labeling system combines features learned from raw RGB-D images and 3D point clouds directly, without any hand-designed features, to assign an object label to every 3D point in the scene. Experiments on the RGB-D Scenes Dataset v.2 demonstrate that the proposed approach can be used to label indoor scenes containing both small tabletop objects and large furniture pieces.

Mining of user event data to identify users with common interests

Abstract: A computer-implemented matching service matches users to other users, and/or to user communities, based at least in part on a computer analysis of event data reflective of user behaviors. The event data may, for example, evidence user affinities for particular items represented in an electronic catalog, such as book titles, music titles, movie titles, and/or other types of items that tend to reflect the traits of users. Event data reflective of other types of user actions, such as item-detail-page viewing events, browse node visits, search query submissions, and/or web browsing patterns may additionally or alternatively be considered. By taking such event data into consideration, the matching service reduces the burden on users to explicitly supply personal profile information, and reduces poor results caused by exaggerations and other inaccuracies in such profile information.

Detecting item interaction and movement

Abstract: This disclosure describes a system for tracking removal or placement of items at inventory locations with a materials handling facility. In some instances, a user may remove an item from an inventory location and the inventory management system may detect that removal and update a user item list associated with the user to include an item identifier representative of the removed item. Likewise, if the user places an item at an inventory location, the inventory management system may detect that placement and update the user item list to remove an item identifier representative of the placed item.

Log-based predictive maintenance

Abstract: Success of manufacturing companies largely depends on reliability of their products. Scheduled maintenance is widely used to ensure that equipment is operating correctly so as to avoid unexpected breakdowns. Such maintenance is often carried out separately for every component, based on its usage or simply on some fixed schedule. However, scheduled maintenance is labor-intensive and ineffective in identifying problems that develop between technician's visits. Unforeseen failures still frequently occur. In contrast, predictive maintenance techniques help determine the condition of in-service equipment in order to predict when and what repairs should be performed. The main goal of predictive maintenance is to enable pro-active scheduling of corrective work, and thus prevent unexpected equipment failures.

Session management in distributed storage systems

Abstract: A request for a session identifier for a particular client is transmitted from an access subsystem of a storage service to a metadata subsystem of the service. A session identifier based on a persistent session storage location at which metadata of the client session are stored is received at the access subsystem. The session identifier is cached at the access subsystem prior to its transmission to the client. A lock state indicator generated by the metadata subsystem in response to a particular request from the client during the client session may also be cached at the access subsystem. Subsequent storage requests from the client during the session may be handled by the access subsystem using the cached session identifier and lock state indicator.

Multi-use UAV docking station systems and methods

Abstract: Systems and methods for providing a series of multiuse UAV docking stations are disclosed. The docking stations can be networked with a central control and a plurality of UAVs. The docking stations can include a number of services to facilitate both UAV guidance and maintenance and community acceptance and benefits. The docking stations can include package handling facilities and can act as a final destination or as a delivery hub. The docking stations can extend the range of UAVs by providing recharging/refueling stations for the UAVs. The docking stations can also include navigational aid to guide the UAVs to the docking stations and to provide routing information from the central control. The docking stations can be incorporated into existing structures such as cell towers, light and power poles, and buildings. The docking stations can also comprise standalone structures to provide additional services to underserved areas.

Online Clustering of Bandits

Abstract: We introduce a novel algorithmic approach to content recommendation based on adaptive clustering of exploration-exploitation ("bandit") strategies. We provide a sharp regret analysis of this algorithm in a standard stochastic noise setting, demonstrate its scalability properties, and prove its effectiveness on a number of artificial and real-world datasets. Our experiments show a significant increase in prediction performance over state-of-the-art methods for bandit problems.

Techniques for user authentication

Abstract: Techniques for user authentication are disclosed. In some situations, the techniques include receiving, from a client device, an authentication request to access a network resource, the request including a user identifier, obtaining a security credential associated with the user identifier contained in the received request, generating an authorization code based on the obtained security credential, providing to the client device instructions to obtain first information corresponding to the generated authorization code, receiving, from the client device, the first information provided in response to the provided instructions, and, when the first information received from the client device corresponds to at least a portion of the generated authorization code, authorizing the client device to access the network resource.

Synchronizing the playing and displaying of digital content

Abstract: The techniques disclosed herein allow a user to synchronize the playing and displaying of digital content on an electronic device. The device may render a first portion of digital content so it may be displayed. The device may also play a segment of the digital content as audio using text to speech software. The device may also render a second portion of digital content for display depending on whether the position of the last word read is greater than the last position in the first portion of digital content.

The distribution and amount of carbon in the largest peatland complex in Amazonia

Abstract: Peatlands in Amazonian Peru are known to store large quantities of carbon, but there is high uncertainty in the spatial extent and total carbon stocks of these ecosystems. Here, we use a multi-sensor (Landsat, ALOS PALSAR and SRTM) remote sensing approach, together with field data including 24 forest census plots and 218 peat thickness measurements, to map the distribution of peatland vegetation types and calculate the combined above- and below-ground carbon stock of peatland ecosystems in the Pastaza-Maranon foreland basin in Peru. We find that peatlands cover 35 600±2133 km 2 and contain 3.14 (0.44–8.15) Pg C. Variation in peat thickness and bulk density are the most important sources of uncertainty in these values. One particular ecosystem type, peatland pole forest, is found to be the most carbon-dense ecosystem yet identified in Amazonia (1391±710 Mg C ha �1 ). The novel approach of combining optical and radar remote sensing with above- and below-ground carbon inventories is recommended for developing regional carbon estimates for tropical peatlands globally. Finally, we suggest that Amazonian peatlands should be a priority for research and conservation before the developing regional infrastructure causes an acceleration in the exploitation and degradation of these ecosystems. S Online supplementary data available from stacks.iop.org/ERL/9/124017/mmedia

IVT-seq reveals extreme bias in RNA sequencing

Abstract: Background: RNA-seq is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value. Results: We present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of over 1,000 in vitro transcribed RNAs from a full-length human cDNA library and sequenced them with polyA and total RNA-seq, the most common protocols. Because each cDNA is full length, and we show in vitro transcription is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find 50% of transcripts have more than two-fold and 10% have more than 10-fold differences in within-transcript sequence coverage. We also find greater than 6% of transcripts have regions of dramatically unpredictable sequencing coverage between samples, confounding accurate determination of their expression. We use a combination of experimental and computational approaches to show rRNA depletion is responsible for the most significant variability in coverage, and several sequence determinants also strongly influence representation. Conclusions: These results show the utility of IVT-seq for promoting better understanding of bias introduced by RNA-seq. We find rRNA depletion is responsible for substantial, unappreciated biases in coverage introduced during library preparation. These biases suggest exon-level expression analysis may be inadvisable, and we recommend caution when interpreting RNA-seq results.

Efficient duplicate detection for machine learning data sets

Abstract: At a machine learning service, a determination is made that an analysis to detect whether at least a portion of contents of one or more observation records of a first data set are duplicated in a second set of observation records is to be performed. A duplication metric is obtained, indicative of a non-zero probability that one or more observation records of the second set are duplicates of respective observation records of the first set. In response to determining that the duplication metric meets a threshold criterion, one or more responsive actions are initiated, such as the transmission of a notification to a client of the service.

Local collaborative ranking

Abstract: Personalized recommendation systems are used in a wide variety of applications such as electronic commerce, social networks, web search, and more. Collaborative filtering approaches to recommendation systems typically assume that the rating matrix (e.g., movie ratings by viewers) is low-rank. In this paper, we examine an alternative approach in which the rating matrix is locally low-rank. Concretely, we assume that the rating matrix is low-rank within certain neighborhoods of the metric space defined by (user, item) pairs. We combine a recent approach for local low-rank approximation based on the Frobenius norm with a general empirical risk minimization for ranking losses. Our experiments indicate that the combination of a mixture of local low-rank matrices each of which was trained to minimize a ranking loss outperforms many of the currently used state-of-the-art recommendation systems. Moreover, our method is easy to parallelize, making it a viable approach for large scale real-world rank-based recommendation systems.

Keyword determinations from voice data

Abstract: Topics of potential interest to a user, useful for purposes such as targeted advertising and product recommendations, can be extracted from voice content produced by a user. A computing device can capture voice content, such as when a user speaks into or near the device. One or more sniffer algorithms or processes can attempt to identify trigger words in the voice content, which can indicate a level of interest of the user. For each identified potential trigger word, the device can capture adjacent audio that can be analyzed, on the device or remotely, to attempt to determine one or more keywords associated with that trigger word. The identified keywords can be stored and/or transmitted to an appropriate location accessible to entities such as advertisers or content providers who can use the keywords to attempt to select or customize content that is likely relevant to the user.

Countermeasures for threats to an uncrewed autonomous vehicle

Abstract: Uncrewed autonomous vehicles (“UAVs”) may navigate from one location to another location. Described herein are systems, devices, and methods providing countermeasures for threats that may compromise the UAVs. A plurality of UAVs may establish a mesh network to distribute information to one another. A first UAV may receive external data from a second UAV using the mesh network. The external data may be used to confirm or cross-check data such as location, heading, altitude, and so forth. Disagreement between data generated by the first UAV with external data from the second UAV may result in the determination that the first UAV is compromised. Remedial actions may be taken, such as the first UAV may be directed to a safe location to land or park, may receive commands from another UAV, and so forth.

Joint Learning for Attribute-Consistent Person Re-Identification

Abstract: Person re-identification has recently attracted a lot of attention in the computer vision community. This is in part due to the challenging nature of matching people across cameras with different viewpoints and lighting conditions, as well as across human pose variations. The literature has since devised several approaches to tackle these challenges, but the vast majority of the work has been concerned with appearance-based methods. We propose an approach that goes beyond appearance by integrating a semantic aspect into the model. We jointly learn a discriminative projection to a joint appearance-attribute subspace, effectively leveraging the interaction between attributes and appearance for matching. Our experimental results support our model and demonstrate the performance gain yielded by coupling both tasks. Our results outperform several state-of-the-art methods on VIPeR, a standard re-identification dataset. Finally, we report similar results on a new large-scale dataset we collected and labeled for our task.

Managing resources using resource expiration data

Abstract: Resource management techniques, such as cache optimization, are employed to organize resources within caches such that the most requested content (e.g., the most popular content) is more readily available. A service provider utilizes content expiration data as indicative of resource popularity. As resources are requested, the resources propagate through a cache server hierarchy associated with the service provider. More frequently requested resources are maintained at edge cache servers based on shorter expiration data that is reset with each repeated request. Less frequently requested resources are maintained at higher levels of a cache server hierarchy based on longer expiration data associated with cache servers higher on the hierarchy.

Mobile device interfaces

Abstract: Electronic devices, interfaces for electronic devices, and techniques for interacting with such interfaces and electronic devices are described. For instance, this disclosure describes an example electronic device that includes sensors, such as multiple front-facing cameras to detect orientation and/or location of the electronic device relative to an object and one or more inertial sensors. Users of the device may perform gestures on the device by moving the device in-air and/or by moving their head, face, or eyes relative to the device. In response to these gestures, the device may perform operations.

A new species of river dolphin from Brazil or: how little do we know our biodiversity.

Abstract: True river dolphins are some of the rarest and most endangered of all vertebrates. They comprise relict evolutionary lineages of high taxonomic distinctness and conservation value, but are afforded little protection. We report the discovery of a new species of a river dolphin from the Araguaia River basin of Brazil, the first such discovery in nearly 100 years. The species is diagnosable by a series of molecular and morphological characters and diverged from its Amazonian sister taxon 2.08 million years ago. The estimated time of divergence corresponds to the separation of the Araguaia-Tocantins basin from the Amazon basin. This discovery highlights the immensity of the deficit in our knowledge of Neotropical biodiversity, as well as vulnerability of biodiversity to anthropogenic actions in an increasingly threatened landscape. We anticipate that this study will provide an impetus for the taxonomic and conservation reanalysis of other taxa shared between the Araguaia and Amazon aquatic ecosystems, as well as stimulate historical biogeographical analyses of the two basins.

In-call virtual assistants

Abstract: Techniques for providing virtual assistants to assist users during a voice communication between the users. For instance, a first user operating a device may establish a voice communication with respective devices of one or more additional users, such as with a device of a second user. For instance, the first user may utilize her device to place a telephone call to the device of the second user. A virtual assistant may also join the call and, upon invocation by a user on the call, may identify voice commands from the call and may perform corresponding tasks for the users in response.

Transitioning items from a materials handling facility

Abstract: This disclosure describes a system for automatically transitioning items from a materials handling facility without delaying a user as they exit the materials handling facility. For example, while a user is located in a materials handling facility, the user may pick one or more items. The items are identified and automatically associated with the user at or near the time of the item pick. When the users enters and/or passes through a transition area, the picked items are automatically transitioned to the user without affirmative input from or delay to the user.

Network resource identification

Abstract: A system, method and computer-readable medium for client-side processing of resource identifiers. A client request for content is returned that includes information for generating a request for translation information and a number of embedded resource identifiers. Based on the information for generating a request for translation information, the client generates and obtains translation information and processes the embedded resource identifiers to obtain resources from a service provider.

On Averaging Multiview Relations for 3D Scan Registration

Abstract: In this paper, we present an extension of the iterative closest point (ICP) algorithm that simultaneously registers multiple 3D scans. While ICP fails to utilize the multiview constraints available, our method exploits the information redundancy in a set of 3D scans by using the averaging of relative motions. This averaging method utilizes the Lie group structure of motions, resulting in a 3D registration method that is both efficient and accurate. In addition, we present two variants of our approach, i.e., a method that solves for multiview 3D registration while obeying causality and a transitive correspondence variant that efficiently solves the correspondence problem across multiple scans. We present experimental results to characterize our method and explain its behavior as well as those of some other multiview registration methods in the literature. We establish the superior accuracy of our method in comparison to these multiview methods with registration results on a set of well-known real datasets of 3D scans.

Distributed load balancer

Abstract: A distributed load balancer in which a router receives packets from at least one client and routes packet flows to multiple load balancer (LB) nodes according to a per-flow hashed multipath routing technique. For a given packet flow, the LB nodes randomly select a server node as a target for the packet flow from among multiple server nodes and send a connection request to the server node. A load balancer module on the server node makes the decision on whether to accept or reject the connection based on one or more metrics indicating a respective server's current load. If the module accepts the connection request, a connection is established between the server and the client. Otherwise, the load balancer nodes may select another server node and try again. The connections established between clients and servers pass through the load balancer nodes, but are not terminated at the load balancer nodes.

Detecting fraudulent activity by analysis of information requests

Abstract: Techniques are described for use in inhibiting attempts to fraudulently obtain access to confidential information about users. In some situations, the techniques involve automatically analyzing at least some requests for information that are received by a Web site or other electronic information service, such as to determine whether they likely reflect fraudulent activities by the request senders or other parties that initiate the requests. For example, if a request is being made to a Web site based on a user's interaction with a third-party information source (e.g., another unaffiliated Web site) that is not authorized to initiate the request, the third-party information source may be a fraudulent phishing site or engaging in other types of fraudulent activity. If fraudulent activity is suspected based on analysis of one or more information requests, one or more actions may be taken to inhibit the fraudulent activity.

Context interpretation in natural language processing using previous dialog acts

Abstract: Features are disclosed for processing and interpreting natural language, such as interpretations of user utterances, in multi-turn dialog interactions. Context information regarding interpretations of user utterances and system responses to the user utterances can be maintained. Subsequent user utterances can be interpreted using the context information, rather than being interpreted without context. In some cases, interpretations of subsequent user utterances can be merged with interpretations of prior user utterances using a rule-based framework. Rules may be defined to determine which interpretations may be merged and under what circumstances they may be merged.

Visual overlay for augmenting reality

Abstract: Augmented reality may be provided to one or more users in a real-world environment. For instance, information related to a recognized object may be displayed as a visual overlay appearing to be in the vicinity of the object in the real-world environment that the user is currently viewing. The information displayed may be determined based on at least one of captured images and transmissions from other devices. In one example, a portable apparatus receives a transmitted user identifier (ID) and may submit the user ID to a remote computing device that compares a profile of a user corresponding to the user ID with a profile associated with the portable apparatus for determining, at least in part, information to be displayed as the visual overlay. As another example, the portable apparatus may include a camera to capture images that are analyzed for recognizing objects and identifying other users.