Node.js employs an event-driven architecture and a non-blocking I/O model, and it provides some blindingly fast performance to some types of data-intensive Web apps. It is about JavaScript on the server side. LinkedIn, Yahoo and eBay are among ardent Node.js users, and none other than Microsoft has discussed end-to-end JavaScript coverage on its Azure cloud. Read the rest...

Robots operating in household environments must find objects on shelves, under tables, and in cupboards. Previous work often formulate the object search problem as a POMDP (Partially Observable Markov Decision Process), yet constrain the search space in 2D. We propose a new approach that enables the robot to efficiently search for objects in 3D, taking occlusions into account. We model the problem as an object-oriented POMDP, where the robot receives a volumetric observation from a viewing frustum and must produce a policy to efficiently search for objects. To address the challenge of large state and observation spaces, we first propose a per-voxel observation model which drastically reduces the observation size necessary for planning. Then, we present a novel octree-based belief representation which captures beliefs at different resolutions and supports efficient exact belief update. Finally, we design an online multi-resolution planning algorithm that leverages the resolution layers in the octree structure as levels of abstractions to the original POMDP problem. Our evaluation in a simulated 3D domain shows that, as the problem scales, our approach significantly outperforms baselines without resolution hierarchy by 25%-35% in cumulative reward. We demonstrate the practicality of our approach on a torso-actuated mobile robot searching for objects in areas of a cluttered lab environment where objects appear on surfaces at different heights.

For Convolutional Neural Network-based object detection, there is a typical dilemma: the spatial information is well kept in the shallow layers which unfortunately do not have enough semantic information, while the deep layers have a high semantic concept but lost a lot of spatial information, resulting in serious information imbalance. To acquire enough semantic information for shallow layers, Feature Pyramid Networks (FPN) is used to build a top-down propagated path. In this paper, except for top-down combining of information for shallow layers, we propose a novel network called Image Pyramid Guidance Network (IPG-Net) to make sure both the spatial information and semantic information are abundant for each layer. Our IPG-Net has two main parts: the image pyramid guidance transformation module and the image pyramid guidance fusion module. Our main idea is to introduce the image pyramid guidance into the backbone stream to solve the information imbalance problem, which alleviates the vanishment of the small object features. This IPG transformation module promises even in the deepest stage of the backbone, there is enough spatial information for bounding box regression and classification. Furthermore, we designed an effective fusion module to fuse the features from the image pyramid and features from the backbone stream. We have tried to apply this novel network to both one-stage and two-stage detection models, state of the art results are obtained on the most popular benchmark data sets, i.e. MS COCO and Pascal VOC.

Autonomous robot manipulation involves estimating the translation and orientation of the object to be manipulated as a 6-degree-of-freedom (6D) pose. Methods using RGB-D data have shown great success in solving this problem. However, there are situations where cost constraints or the working environment may limit the use of RGB-D sensors. When limited to monocular camera data only, the problem of object pose estimation is very challenging. In this work, we introduce a novel method called SilhoNet that predicts 6D object pose from monocular images. We use a Convolutional Neural Network (CNN) pipeline that takes in Region of Interest (ROI) proposals to simultaneously predict an intermediate silhouette representation for objects with an associated occlusion mask and a 3D translation vector. The 3D orientation is then regressed from the predicted silhouettes. We show that our method achieves better overall performance on the YCB-Video dataset than two state-of-the art networks for 6D pose estimation from monocular image input.

Deep learning-based object detection and instance segmentation have achieved unprecedented progress. In this paper, we propose Complete-IoU (CIoU) loss and Cluster-NMS for enhancing geometric factors in both bounding box regression and Non-Maximum Suppression (NMS), leading to notable gains of average precision (AP) and average recall (AR), without the sacrifice of inference efficiency. In particular, we consider three geometric factors, i.e., overlap area, normalized central point distance and aspect ratio, which are crucial for measuring bounding box regression in object detection and instance segmentation. The three geometric factors are then incorporated into CIoU loss for better distinguishing difficult regression cases. The training of deep models using CIoU loss results in consistent AP and AR improvements in comparison to widely adopted $ell_n$-norm loss and IoU-based loss. Furthermore, we propose Cluster-NMS, where NMS during inference is done by implicitly clustering detected boxes and usually requires less iterations. Cluster-NMS is very efficient due to its pure GPU implementation, , and geometric factors can be incorporated to improve both AP and AR. In the experiments, CIoU loss and Cluster-NMS have been applied to state-of-the-art instance segmentation (e.g., YOLACT), and object detection (e.g., YOLO v3, SSD and Faster R-CNN) models. Taking YOLACT on MS COCO as an example, our method achieves performance gains as +1.7 AP and +6.2 AR$_{100}$ for object detection, and +0.9 AP and +3.5 AR$_{100}$ for instance segmentation, with 27.1 FPS on one NVIDIA GTX 1080Ti GPU. All the source code and trained models are available at https://github.com/Zzh-tju/CIoU

During VR demos we have performed over last few years, many participants (in the absence of any haptic feedback) have commented on their perceived ability to 'feel' differences between simulated molecular objects. The mechanisms for such 'feeling' are not entirely clear: observing from outside VR, one can see that there is nothing physical for participants to 'feel'. Here we outline exploratory user studies designed to evaluate the extent to which participants can distinguish quantitative differences in the flexibility of VR-simulated molecular objects. The results suggest that an individual's capacity to detect differences in molecular flexibility is enhanced when they can interact with and manipulate the molecules, as opposed to merely observing the same interaction. Building on these results, we intend to carry out further studies investigating humans' ability to sense quantitative properties of VR simulations without haptic technology.

Data analytics in the cloud has become an integral part of enterprise businesses. Big data analytics systems, however, still lack the ability to take user performance goals and budgetary constraints for a task, collectively referred to as task objectives, and automatically configure an analytic job to achieve these objectives. This paper presents a data analytics optimizer that can automatically determine a cluster configuration with a suitable number of cores as well as other system parameters that best meet the task objectives. At a core of our work is a principled multi-objective optimization (MOO) approach that computes a Pareto optimal set of job configurations to reveal tradeoffs between different user objectives, recommends a new job configuration that best explores such tradeoffs, and employs novel optimizations to enable such recommendations within a few seconds. We present efficient incremental algorithms based on the notion of a Progressive Frontier for realizing our MOO approach and implement them into a Spark-based prototype. Detailed experiments using benchmark workloads show that our MOO techniques provide a 2-50x speedup over existing MOO methods, while offering good coverage of the Pareto frontier. When compared to Ottertune, a state-of-the-art performance tuning system, our approach recommends configurations that yield 26\%-49\% reduction of running time of the TPCx-BB benchmark while adapting to different application preferences on multiple objectives.

Software development has been changing rapidly. This development process can be influenced through changing developer friendly approaches. We can save time consumption and accelerate the development process if we can automatically guide programmer during software development. There are some approaches that recommended relevant code snippets and APIitems to the developer. Some approaches apply general code, searching techniques and some approaches use an online based repository mining strategies. But it gets quite difficult to help programmers when they need particular type conversion problems. More specifically when they want to adapt existing interfaces according to their expectation. One of the familiar triumph to guide developers in such situation is adapting collections and arrays through automated adaptation of object ensembles. But how does it help to a novice developer in real time software development that is not explicitly specified? In this paper, we have developed a system that works as a plugin-tool integrated with a particular Data Mining Integrated environment (DMIE) to recommend relevant interface while they seek for a type conversion situation. We have a mined repository of respective adapter classes and related APIs from where developer, search their query and get their result using the relevant transformer classes. The system that recommends developers titled automated objective ensembles (AOE plugin).From the investigation as we have ever made, we can see that our approach much better than some of the existing approaches.

This paper investigates the convergence of the randomized Kaczmarz algorithm for the problem of phase retrieval of complex-valued objects. While this algorithm has been studied for the real-valued case}, its generalization to the complex-valued case is nontrivial and has been left as a conjecture. This paper establishes the connection between the convergence of the algorithm and the convexity of an objective function. Based on the connection, it demonstrates that when the sensing vectors are sampled uniformly from a unit sphere and the number of sensing vectors $m$ satisfies $m>O(nlog n)$ as $n, m ightarrowinfty$, then this algorithm with a good initialization achieves linear convergence to the solution with high probability.

Most optimization-based community detection approaches formulate the problem in a single or bi-objective framework. In this paper, we propose two variants of a three-objective formulation using a customized non-dominated sorting genetic algorithm III (NSGA-III) to find community structures in a network. In the first variant, named NSGA-III-KRM, we considered Kernel k means, Ratio cut, and Modularity, as the three objectives, whereas the second variant, named NSGA-III-CCM, considers Community score, Community fitness and Modularity, as three objective functions. Experiments are conducted on four benchmark network datasets. Comparison with state-of-the-art approaches along with decomposition-based multi-objective evolutionary algorithm variants (MOEA/D-KRM and MOEA/D-CCM) indicates that the proposed variants yield comparable or better results. This is particularly significant because the addition of the third objective does not worsen the results of the other two objectives. We also propose a simple method to rank the Pareto solutions so obtained by proposing a new measure, namely the ratio of the hyper-volume and inverted generational distance (IGD). The higher the ratio, the better is the Pareto set. This strategy is particularly useful in the absence of empirical attainment function in the multi-objective framework, where the number of objectives is more than two.

Feature pyramid has been an efficient method to extract features at different scales. Development over this method mainly focuses on aggregating contextual information at different levels while seldom touching the inter-level correlation in the feature pyramid. Early computer vision methods extracted scale-invariant features by locating the feature extrema in both spatial and scale dimension. Inspired by this, a convolution across the pyramid level is proposed in this study, which is termed pyramid convolution and is a modified 3-D convolution. Stacked pyramid convolutions directly extract 3-D (scale and spatial) features and outperforms other meticulously designed feature fusion modules. Based on the viewpoint of 3-D convolution, an integrated batch normalization that collects statistics from the whole feature pyramid is naturally inserted after the pyramid convolution. Furthermore, we also show that the naive pyramid convolution, together with the design of RetinaNet head, actually best applies for extracting features from a Gaussian pyramid, whose properties can hardly be satisfied by a feature pyramid. In order to alleviate this discrepancy, we build a scale-equalizing pyramid convolution (SEPC) that aligns the shared pyramid convolution kernel only at high-level feature maps. Being computationally efficient and compatible with the head design of most single-stage object detectors, the SEPC module brings significant performance improvement ($>4$AP increase on MS-COCO2017 dataset) in state-of-the-art one-stage object detectors, and a light version of SEPC also has $sim3.5$AP gain with only around 7% inference time increase. The pyramid convolution also functions well as a stand-alone module in two-stage object detectors and is able to improve the performance by $sim2$AP. The source code can be found at https://github.com/jshilong/SEPC.

With the growing reliance on the ubiquitous availability of IT systems and services, these systems become more global, scaled, and complex to operate. To maintain business viability, IT service providers must put in place reliable and cost efficient operations support. Artificial Intelligence for IT Operations (AIOps) is a promising technology for alleviating operational complexity of IT systems and services. AIOps platforms utilize big data, machine learning and other advanced analytics technologies to enhance IT operations with proactive actionable dynamic insight.

In this paper we share our experience applying the AIOps approach to a production cloud object storage service to get actionable insights into system's behavior and health. We describe a real-life production cloud scale service and its operational data, present the AIOps platform we have created, and show how it has helped us resolving operational pain points.

In one embodiment, a plurality of objects associated with a dataset and a specified number of nearest objects to be identified are received. The received objects are sorted in a structured format. Further, a key object and a number of adjacent objects corresponding to the key object are selected from the sorted plurality of objects, wherein the number of adjacent objects is selected based on the specified number of nearest objects to be identified. Furthermore, distances between the key object and the number of adjacent objects are determined to identify the specified number of nearest objects, wherein the distances are determined until the specified number of nearest objects is identified. Based on the determined distances, the specified number of nearest objects in the dataset is identified for data analysis.

A data warehouse is constructed using the relational mapping of a transactional database without reconstructing the data relationships of the transactional database. First, an application programmer analyzes an object model in order to describe facts and dimensions using the objects, attributes, and paths of the object model. Each of the dimensions has an identifier that correlates an item in the transactional database to a dimension record in the data warehouse. The fact and dimension descriptions are saved to a description file. Second, a Data Warehouse Engine (DWE) then access the description file and uses the object model, fact and dimension descriptions, and object-relational mapping to map transactional data to the data warehouse.

Generally, compositions and methods of producing dimensionally stable three dimensional objects using an additive build up process. Specifically, materials combinable in an additive build up process using a materials printer for the production of stable three dimensional molds useful in the production of molded or formed parts.

A method and apparatus for the stabilization and safe removal of buried waste that is tested and classified as being transuranic or not transuranic waste and disposed accordingly. The buried waste (usually in vertical pipe units) is enclosed in a casing and ground and mixed with the surrounding soil. This process allows for chemical reactions to occur that stabilizes the mixture. The entire process is contained within the casing to avoid contamination. In situ or external testing is done for radio isotopes to classify the waste. If it is classified as transuranic the waste is removed in a controlled way into a retrieval enclosure and disposed off in drums. If the waste is not transuranic then grout is introduced into the mixture, allowed to set and the resulting monolith is removed and buried in trenches.

A method and apparatus for distributing objects. In one embodiment, the method comprises computing a modulus operand based on a number of objects to be distributed and a number of objects pertaining to a first category; computing a modulus operation based on a number of distributed objects and the modulus operand; and distributing a first object or a second object based on a result of computing the modulus operation.

An automated process uses a local positioning system to acquire location (i.e., position and orientation) data for one or more movable target objects. In cases where the target objects have the capability to move under computer control, this automated process can use the measured location data to control the position and orientation of such target objects. The system leverages the measurement and image capture capability of the local positioning system, and integrates controllable marker lights, image processing, and coordinate transformation computation to provide tracking information for vehicle location control. The resulting system enables position and orientation tracking of objects in a reference coordinate system.

A system for translating user motion into multiple object responses of an on-screen object based on user interaction of an application executing on a computing device is provided. User motion data is received from a capture device from one or more users. The user motion data corresponds to user interaction with an on-screen object presented in the application. The on-screen object corresponds to an object other than an on-screen representation of a user that is displayed by the computing device. The user motion data is automatically translated into multiple object responses of the on-screen object. The multiple object responses of the on-screen object are simultaneously displayed to the users.

Provided are a three-dimensional (3D) ultrasound system and a method for operating the 3D ultrasound system, which are capable of intuitively displaying the abnormality of an object by determining a grade by comparing measurement data obtained by measuring ultrasound data relating to the object and displaying the measurement data in a different way based on the determined grade.

Systems for spacing and transferring objects between operative stations are provided. Such systems can be used with ovens for preforms for plastic material, in blowing or stretch-blowing machines and for other applications in the packaging field. Such systems provide spacing and transferring of objects advancing in procession on transport elements, from a minimum pitch to a preset pitch larger than said minimum pitch, and for transferring said spaced objects to handling elements.

A carrying strap for supporting an object is described. According to an exemplary embodiment of the present invention, the carrying strap comprises a neck pad for distributing the object's weight over the user's neck, the neck pad having inner or first, and outer or second sides affixed to each other along perimeter, wherein the first side is configured to contact backside of the user's neck and the first side comprises two partially overlapped layers in a mirror-image orientation to form an open slot, located substantially near center portion of the neck pad, which is configured for housing a removable cushion that provides extra cushion to the backside of the user's neck; at least one hook for securing the object; and an extension portion connecting the neck pad and the at least one hook.

In a case where a communication device belongs to a first wireless network for the communication device to execute a wireless communication, the communication device may execute using a wireless communication with a mobile device via the first wireless network after sending to the mobile device a first wireless setting. The first wireless setting may be for the mobile device to belong to the first wireless network and include a password. In a case where the communication device belongs to a second wireless network for the communication device to execute a wireless communication, the communication device may execute a wireless communication with the mobile device via the second wireless network after sending to the mobile device a second wireless setting. The second wireless setting may be for the mobile device to belong to the second wireless network and not including the password.

A device for depositing a mixture of powders to form an object with composition gradients, including: a plurality of tanks respectively configured to contain different powders; a powder mixer placed under the tanks and including a rotatably mounted mixing member; a plurality of powder dispensing mechanisms respectively cooperating with the tanks, and each configured to regulate mass flow rate of the powder escaping from a respective of the tanks towards the mixer; a powder mixture collector placed under the mixer; and a powder mixture dispenser placed under the collector.

The present invention provides: a method of polishing an object to be polished for processing a surface of the object to be polished into a concave or convex state with a high degree of accuracy; and a polishing pad. An object to be polished is placed on a polishing pad over the boundary between the first polishing region and the second polishing region, the first polishing region has grooves and the second polishing region has grooves different from those of the first polishing region, and either one of the two regions being formed on a region on the center side, and the other on the outer side in a radial direction on the surface of the polishing pad; and the object to be polished is polished by rotating the polishing pad and the object to be polished.

A system, that includes a hybrid sensor that comprises: a monochromatic portion that is arranged to obtain a monochromatic image of a first area of an object; a multiple-color portion that is arranged to obtain a multi-colored image of a second area of the object; wherein the monochromatic portion comprises monochromatic sensing elements that sense radiation of a same frequency band; wherein the multiple-color portion comprises color sensing elements of different types, wherein different types of color sensing elements are associated with different frequency bands.

Within machine vision, object movement is often estimated by applying image evaluation techniques to visible light images, utilizing techniques such as perspective and parallax. However, the precision of such techniques may be limited due to visual distortions in the images, such as glare and shadows. Instead, lidar data may be available (e.g., for object avoidance in automated navigation), and may serve as a high-precision data source for such determinations. Respective lidar points of a lidar point cloud may be mapped to voxels of a three-dimensional voxel space, and voxel clusters may be identified as objects. The movement of the lidar points may be classified over time, and the respective objects may be classified as moving or stationary based on the classification of the lidar points associated with the object. This classification may yield precise results, because voxels in three-dimensional voxel space present clearly differentiable statuses when evaluated over time.

The invention relates to a fixing element (33) extending as a flat, particularly lamellar element along a preferred direction (34) and comprising a corrugated sheet metal core (18) as a central component, said core providing the fixing element (33) with the characteristic of being integrally rigid and permanently deformable by hand, and said core being covered by a cover (36, 37). For such a fixing element, a large range of use is achieved in that the corrugations of the corrugated core sheet (18) are oriented substantially parallel to the preferred direction (34), and that means (38, 39) for releasably attaching the fixing element (33) are disposed on the fixing element (33).

A system and method in a television system for presenting information associated with a user-selected object in a television program is provided. An identity of a user-selected object in a television program being presented to a user is determined. Based at least in part on the identity of the user-selected object in the television program, information to present to the user is determined. The determined information is presented to the user on a television display.

Provided is an object lens driving device that includes a wire holder coupled to a support portion and on which an end of a plurality of suspension wires are fixed. The wire holder includes a first area supported on the support portion and a second area extending from the first area and on which the end of each of the plurality of suspension wires is fixed. In this example, a thickness of the second area is thinner than a thickness of the first area.

Provided is an objective lens driving unit that prevents an electrical short circuit between very closely spaced second terminals in the objective lens driving unit. The objective lens driving unit is capable of being used in a slim-type optical disc drive.

A method serves to produce a three-dimensional object by additive construction in direct construction sequence from solidifiable material, which is either present in the starting state in a fluid phase or can be liquefied, where multiple material components are discharged alternately in a programmable manner by means of multiple discharge units and configure different parts of the object joined to one another as a result of the discharge, where the geometric proportions obtained during discharge already correspond to the object, and because the material components form between them either edge regions merging into one another without boundaries or boundary regions of the different material components abutting one another without joining, a method and an object produced therewith can be provided, in which boundary and edge regions are formed “as if from one piece” between different material components even in the case of complex geometries.

Disclosed is an object detection device capable of improving object detection accuracy by preventing erroneous combination detection. In this device, a detection object region correction unit (103) corrects a detection object region set by a detection object region set unit (102) on the basis of moving speed map information associated with a coordinate group in a reference image plane and the detected moving speed on each coordinate, which is detected by a radar. Thus, the detection object region can be amended by the use of the moving speed map information even when the detection object region is obtained as a result of erroneous combination. As a result, the object detection accuracy can be improved.

A radar sensor and a method of detecting an object by using the same are provided. The method includes: receiving at least one radar signal reflected from the object; converting the received at least one radar signal to at least one signal in a frequency domain; accumulating the converted at least one signal for a predetermined time and extracting at least one feature from the accumulated at least one signal; and identifying the object by comparing the extracted at least one feature with at least one reference value stored in a database.

An RF beam is used to probe the presence or absence of a rotating blade in a known field of view. Timing of appearance or disappearance or “zero-crossing” of a reflected signal is correlated with timing of the blade movement. Blades which are leading or lagging versus other blades will produce different timing signatures representative of alignment of the blades.

A non-contact support platform system is provided for supporting a substantially flat object. The system includes a platform with a first plurality of pressure ports and a first plurality of vacuum ports for inducing a fluid cushion to support the object at a distance from the platform. The system further includes a second plurality of pressure ports located at a predetermined zone of the platform for increasing the distance of the object from the platform at the predetermined zone.

Methods and systems for a complete vehicle ecosystem are provided. Specifically, systems that when taken alone, or together, provide an individual or group of individuals with an intuitive and comfortable vehicular environment. The present disclosure builds on integrating existing technology with new devices, methods, and systems to provide a complete vehicle ecosystem.

The system described in this disclosure may be configured to read information stored on toy objects that indicates whether the toy objects have been used and/or are being used with other toy objects, gaming systems, and/or other devices. The system described in this disclosure may be configured to facilitate an association of the information stored on the toy objects with virtual entities in a virtual space, update virtual content associated with the virtual entities, determine relationships between users, and/or other perform other functions based on the information stored on the toy objects. The information stored on the toy objects may be updated responsive to the toy objects being used by users with other toy objects, gaming systems, and/or other devices. The use of the toy objects by users may include two or more users playing together with toy objects and/or playing with gaming systems associated with the toy objects.

A fastener for attaching objects to channeled members wherein the objects have a hole extending therethrough and the channeled members have a longitudinal slot formed between projecting longitudinal walls. The fastener includes a button and a retainer. The button includes an abutment wall, an abutment surface and an axially extending slot. The retainer includes an engagement boss and a head at opposite ends of shaft. The retainer extends through the button slot. For attaching the object, the button extends through the object hole with the abutment wall adjacent the object and the abutment surface adjacent the channeled member. The retainer boss and part of the shaft extend through the longitudinal slot. The retainer is rotated for engaging the longitudinal walls with the boss. The longitudinal walls are sandwiched between the boss and the button abutment surface and the object is sandwiched between the channeled member and the button abutment wall.

A resonator element includes a substrate including a first principal surface and a second principal surface respectively forming an obverse surface and a reverse surface of the substrate, and vibrating in a thickness-shear vibration mode, a first excitation electrode disposed on the first principal surface, and a second excitation electrode disposed on the second principal surface, and being larger than the first excitation electrode in a plan view, the first excitation electrode is disposed so as to fit into an outer edge of the second excitation electrode in the plan view, and the energy trap confficient M fulfills 15.5≦M≦36.7.

A resonator element includes a substrate vibrating in a thickness-shear vibration mode, a first excitation electrode disposed on one principal surface of the substrate, and has a shape obtained by cutting out four corners of a quadrangle, and a second excitation electrode disposed on the other principal surface of the substrate, and a ratio (S2/S1) between the area S1 of the quadrangle and the area S2 of the first excitation electrode fulfills 87.7%≦(S2/S1)

An atomic oscillator includes: a gas cell which includes two window portions having a light transmissive property and in which metal atoms are sealed; a light emitting portion that emits excitation light to excite the metal atoms in the gas cell; a light detecting portion that detects the excitation light transmitted through the gas cell; a heater that generates heat; and a connection member that thermally connects the heater and each window portion of the gas cell to each other.

A vibration element includes a piezoelectric substrate including a vibrating section and a thick section having a thickness larger than that of the vibrating section. The thick section includes a first thick section provided along a first outer edge of the vibrating section, a second thick section provided along a second outer edge, and a third thick section provided along another first outer edge. An inclined outer edge section that intersects with each of an X axis and a Z' axis is provided in a tip section of the piezoelectric substrate.

A target and object receiving device that includes a base portion having an outer edge and a lower coupling area disposed on a top surface of the base portion. An upper portion is spaced vertically from the base portion and includes an outer edge and an upper coupling area disposed on a bottom surface of the upper portion. A separator extends vertically from the lower coupling area to the upper coupling area. Either: (a) the top surface of the base portion approaches the bottom surface of the upper portion as the top surface extends from the outer edge of the base portion toward the lower coupling area; or (b) the bottom surface of the upper portion approaches the top surface of the base portion as the bottom surface of the upper portion extends from the outer edge of the base portion toward the upper coupling area.

A board game system comprises one or more game objects, a processing device, a memory device and one or more cameras. Each of the game objects comprise a unique visual marker positioned on a top surface of the game object, wherein the unique visual marker comprises a series of concentric rings that represent data that uniquely identifies the game object. As a result, during the course of game play, the location and identification of the game objects are able to be determined by the processing device by analyzing images captured by the one or more cameras of the visual markers of the game objects on the game board. The processing device is able to compare the data of the visual markers to a table stored in the memory device that associates the data with a specific game object.

Disclosed is a system for managing multiple objects in an object zone. The system comprises multiple machine-readable object identification tags configured to be respectively attached to the multiple objects; a storage unit moving through the object zone to store the selected objects which are respectively attached with the machine-readable object identification tags; at least one machine-readable storage unit identification tag attached to the storage unit; and multiple spaced reading units capable of remotely reading the multiple machine-readable object identification tags and the at least one machine-readable storage unit identification tag, wherein the objects attached with the machine-readable object identification tags within a predefined spatial range defined based on the at least one machine-readable storage unit identification tag are associated with the storage unit. A method thereof and a storage unit are also disclosed.

A mirror for the EUV wavelength range (1) having a layer arrangement (P) applied on a substrate (S), the layer arrangement having a periodic sequence of individual layers, where the periodic sequence has at least two individual layers—forming a period—composed respectively of silicon (Si) and ruthenium (Ru). Also disclosed are a projection objective for microlithography (2) including such a mirror, and a projection exposure apparatus for microlithography having such a projection objective (2).

This specification is directed towards finding, locating, and confirming threat items and substances. The inspection system is designed to detect objects that are made from, but not limited to, special nuclear materials (“SNM”) and/or high atomic number materials. The system employs a dual energy CT scanning first stage inspection system and advanced image processing techniques to analyze images of an object under inspection (“OUI”), which includes, but is not limited to baggage, parcels, vehicles and cargo.

A cloud computing system for object location, object identification, object picking, object picking by line, object loading onto one or more transport devices, or object delivery that can include using a cloud based server comprising a cloud based processor in communication with a cloud based data storage. The cloud based server can be in communication with at least one mobile processor in communication with a mobile data storage and a display. The method can also include sending instructions to an operator from the cloud based computer to a mobile processor associated with an operator to instruct the operator to perform a logistics operation. The logistic operation can include one or more of object location, object identification, object picking, object picking by line, object loading onto one or more transport devices, and object delivery.

A method and apparatus for detecting an object. A first optical signal having a first frequency is transmitted to a location on a surface of a ground. A second optical signal having a second frequency is transmitted to the location on the surface of the ground such that the first optical signal and the second optical signal overlap each other at the location on the surface of the ground. The overlap of the first optical signal and the second optical signal at the location generates a third optical signal having a difference frequency that is a difference between the first frequency and the second frequency. The third optical signal is configured to travel into the ground. A response to the third optical signal is detected. A determination is made as to whether an object is present in the ground using the response to the third optical signal.