TULSA, Okla. – Hongjin Tan, a 35 year old Chinese national and U.S. legal permanent resident, pleaded guilty Tuesday in federal court to committing theft of trade secrets from his employer, a U.S. petroleum company.

The head of a Houston-based company that was the subsidiary of a Chinese company that developed stolen trade secrets was sentenced to 16 months in prison and ordered to forfeit more than $330,000 by U.S. District Judge Christopher R. Cooper of the District of Columbia.

A superseding indictment was returned yesterday in federal court in Brooklyn, New York, charging Huawei Technologies Co. Ltd. (Huawei), the world’s largest telecommunications equipment manufacturer, and two U.S. subsidiaries with conspiracy to violate the Racketeer Influenced and Corrupt Organizations Act (RICO).

TULSA, Okla. –A former associate scientist was sentenced Thursday in federal court for stealing proprietary information worth more than $1 billion from his employer, a U.S. petroleum company.

Are you one of those people who have given their camera a name? If the answer is yes, .. this might be one of the most normal things in the world. Today i’d like to explore the emotional relationship between us and our photographic machines. Special guest: Monika Andrae. Photo by William Daigneault Links: Photo … Continue reading "883 The Man Machine Connection"

The post 883 The Man Machine Connection appeared first on PHOTOGRAPHY TIPS FROM THE TOP FLOOR.

David Rohde points us to this new seminar series that has the following description: Machine learning is changing the world we live in at a break neck pace. From image recognition and generation, to the deployment of recommender systems, it seems to be breaking new ground constantly and influencing almost every aspect of our lives. […]

Steven Quinn was fined a total of £360 and ordered to pay £62 compensation after walking out without settling-up at Lau's restaurant, in Newcastle City Centre

Newcastle United goalkeeper Rob Elliot has opened up about team-mate Isaac Hayden and what makes him such an important player

Here's a video segment on the fog machine Kit that we use. A transcription of the video is available after the jump.

At the turn of the 20th century, a vaccine had been developed for smallpox, a virus that killed millions in the 1800s. Those who survived the disease were often left badly scarred or blind. The...

DES MOINES — More than 20 days after Iowa signed a $26 million contract with a Utah company to expand testing in the state, the machines the firm supplied to run the samples still have not...

At the turn of the 20th century, a vaccine had been developed for smallpox, a virus that killed millions in the 1800s. Those who survived the disease were often left badly scarred or blind.

The vaccine’s protection, though, lasted only five years and had to be renewed. And people forgot to do that, leading to occasional epidemics, including a serious outbreak on the Meskwaki Settlement near Tama.

In February 1901, three dozen Iowa communities reported smallpox outbreaks. When Des Moines reported 200 smallpox cases in late February, the mayor closed the schools and prohibited public gatherings. Still, no one died. That would not be the case at the Meskwaki Settlement.

On Oct. 22, 1901, an area resident told Dr. Benjamin Thompson of Tama, “I believe the Indians have the smallpox.”

Thompson went to the nearby Meskwaki Settlement, home to 309 people, to investigate.

He learned that an Indian from the Winnebago tribe had visited the settlement Sept. 23. He had become ill, but no doctor was called and he continued meeting with tribe members.

Two weeks later, the Meskwaki were becoming ill.

Thompson went back to the settlement with Dr. George Carpenter of Toledo. The first wickiup they visited had four active smallpox cases and three people recovering from the virus. Two Meskwaki who’d lived there had died.

The doctors found another five cases and were told of two other deaths.

The doctors that night reported to a joint meeting of the boards of health in Tama, Toledo and Montour.

William Malin, the Interior Department’s Indian agent for the settlement, insisted there was no problem. But after another medical visit to the settlement, the three cities quarantined themselves.

By Nov. 2, 70 Meskwaki had smallpox, and nine members of the tribe had died. Two weeks later, the totals had risen to 90 Meskwaki with smallpox and 35 deaths.

To complicate matters, the Meskwaki declined offers to go to the hospital, they refused smallpox vaccinations and they refused to stay on the settlement. If they became sick, they would hide from the doctors.

The Tama Herald reported, “It looks as though the disease must run its course through the tribe, carrying off the aged and the infirm and weakening the constitution of those who may survive.”

The Iowa governor appealed to Interior Secretary Ethan Hitchcock for authority to enforce the quarantine among the Meskwaki. Hitchcock complied, giving the state the authority to “take any necessary action.”

National Guard hospital tents and cots were shipped to the settlement. The Meskwaki were vaccinated, and they acquiesced to the quarantine.

The local towns began raising money for medicines and provisions not covered by the federal government.

Meanwhile, Congress appropriated $50,000 — more than $1 million in today’s dollars — to eradicate smallpox on the settlement. The bill gave the Interior Department the authority to quarantine the village and, if necessary, burn Meskwaki wickiups and clothing to halt the contagion.

The state of Iowa chipped in another $7,000 to burn the clothing, blankets, wickiups and other property belonging to the Tama tribe and to provide replacements for the Meskwaki.

The money paid for disinfectants — formaldehyde gas and corrosive sublimate fluid — to bathe tribal members and their dogs. Members of the tribe were forced to move to a camping ground while their village was decontaminated.

Malin, the Indian agent, reported to the Interior Department it took seven days to clean and renovate “the Indian camp.”

“During this process, a large number of the wickiups, where the disease had been prevalent, also large quantities of clothing, bedding and other infected property, were committed to the flames and new goods of similar character supplied,” he reported.

“Twenty-four new board houses, built of good lumber, and some 2,700 square yards of very heavy duck for tents, to those who preferred tents to houses, were given in lien of the wickiups destroyed. ... The Indians emerged from the trying ordeal through which they had passed and came out into the world again, after having been confined to the limited area of their camping grounds ... with a higher and better conception of the white man’s civilization.”

That assessment aside, the Meskwaki Settlement survived and grew. It now covers 8,000 acres and is home to 800 of the tribe’s 1,300 members.

It wasn’t until 1980 that smallpox was declared eradicated worldwide.

l Comments: d.fannonlangton@gmail.com

DES MOINES — More than 20 days after Iowa signed a $26 million contract with a Utah company to expand testing in the state, the machines the firm supplied to run the samples still have not passed muster.

A time frame for completing the validation process for the Test Iowa lab machines is unknown, as the process can vary by machine, University of Iowa officials said Friday.

The validation process is undertaken to determine if the machines are processing tests accurately. To this point, the lab has processed the Test Iowa results using machines the State Hygienic Lab already had, officials told The Gazette.

Running side-by-side testing is part of the validation process. The lab then compares whether the machines yield the same results when the sample is run, officials said Friday. The side-by-side testing means the Test Iowa samples are being run at least twice to compare results.

The state does not break out how many of the 331,186 Iowans who by Friday have completed the coronavirus assessment at TestIowa.com have actually been tested. Test Iowa was initiated last month to ramp up testing of essential workers and Iowans showing COVID-19 symptoms. The state’s fourth drive-though location where people with appointments can be tested opened Thursday at the Kirkwood Continuing Education Training Center in Cedar Rapids.

On Friday, Iowa posted a fourth straight day of double-digit deaths from coronavirus, with the latest 12 deaths reported by the state Department of Public Health bringing the statewide toll to 243 since COVID-19 was first confirmed March 8 in Iowa.

State health officials reported another 398 Iowans tested positive for the respiratory ailment, bringing that count to 11,457 of the 70,261 residents who have been tested — a positive rate of more than 16 percent.

One in 44 Iowans has been tested for COVID-19, with 58,804 posting negative results, according to state data. A total of 4,685 people have recovered from the disease.

During a Thursday media briefing, Gov. Kim Reynolds told reporters a backlog of test results that occurred due to validation of Test Iowa equipment had been “caught up,” but some Iowans who participated in drive-through sites set up around the state indicated they still were awaiting results.

Reynolds spokesman Pat Garrett confirmed Thursday that “a very small percentage” of coronavirus test samples collected under the Test Iowa program could not be processed because they were “potentially damaged,” resulting in incomplete results.

There were 407 Iowans who were hospitalized (with 34 admitted in the past 24 hours) for coronavirus-related illnesses and symptoms with 164 being treated in intensive care units and 109 requiring ventilators to assist their breathing.

Health officials said the 12 deaths reported Friday were: three in Woodbury County, two in Linn County and one each in Black Hawk, Dallas, Dubuque, Jasper, Louisa, Muscatine and Scott counties. No other information about the COVID-19 victims was available from state data.

According to officials, 51 percent of the Iowans who have died from coronavirus have been male — the same percentage that tested positive.

Iowans over the age of 80 represent 46 percent of the COVID-19 victims, followed by 41 percent between 61 and 80.

Of those who have tested positive, state data indicates about 42 percent are age 18 to 40; 37 percent are 41 to 60; 14 percent are 61 to 80 and 5 percent are 81 or older.

Counties with the highest number of positive test results are Polk (2,150), Woodbury (1,532), Black Hawk (1,463) and Linn (813).

Earlier this week, state officials revamped the data available to the public at coronavirus.iowa.gov, with the new format no longer listing the age range of Iowans who died from coronavirus and providing information using a different timeline than before.

The governor did not hold a daily media briefing Friday due to scheduling conflicts created by Vice President Mike Pence’s trip to Iowa. Garrett said Reynolds would resume her COVID-19 briefings next week.

John McGlothlen and Zack Kucharski of The Gazette contributed to this report.

Have you chosen Mac for its reliable system? They really have a lot of advantages and are of the best quality. Mac users don’t face serious problems with hard drives often. But the reality is such...

Facebook Software Engineer and HipHop for PHP team member Jason Evans provides details on Facebook’s move to a new high-performance PHP virtual machine. Described by Evans is ”a new PHP execution engine based on the HipHop language runtime that we call the HipHop Virtual Machine (hhvm).” He sees it as replacement for the HipHop PHP Read the rest...

This work has been motivated by recent papers that quantify the density of values of generic quadratic forms and other polynomials at integer points, in particular ones that use Rogers' second moment estimates. In this paper we establish such results in a very general framework. Namely, given any subhomogeneous function (a notion to be defined) $f: mathbb{R}^n o mathbb{R}$, we derive a necessary and sufficient condition on the approximating function $psi$ for guaranteeing that a generic element $fcirc g$ in the $G$-orbit of $f$ is $psi$-approximable; that is, $|fcirc g(mathbf{v})| le psi(|mathbf{v}|)$ for infinitely many $mathbf{v} in mathbb{Z}^n$. We also deduce a sufficient condition in the case of uniform approximation. Here, $G$ can be any closed subgroup of $operatorname{ASL}_n(mathbb{R})$ satisfying certain axioms that allow for the use of Rogers-type estimates.

Differential machine learning (ML) extends supervised learning, with models trained on examples of not only inputs and labels, but also differentials of labels to inputs.

Differential ML is applicable in all situations where high quality first order derivatives wrt training inputs are available. In the context of financial Derivatives risk management, pathwise differentials are efficiently computed with automatic adjoint differentiation (AAD). Differential ML, combined with AAD, provides extremely effective pricing and risk approximations. We can produce fast pricing analytics in models too complex for closed form solutions, extract the risk factors of complex transactions and trading books, and effectively compute risk management metrics like reports across a large number of scenarios, backtesting and simulation of hedge strategies, or capital regulations.

The article focuses on differential deep learning (DL), arguably the strongest application. Standard DL trains neural networks (NN) on punctual examples, whereas differential DL teaches them the shape of the target function, resulting in vastly improved performance, illustrated with a number of numerical examples, both idealized and real world. In the online appendices, we apply differential learning to other ML models, like classic regression or principal component analysis (PCA), with equally remarkable results.

This paper is meant to be read in conjunction with its companion GitHub repo https://github.com/differential-machine-learning, where we posted a TensorFlow implementation, tested on Google Colab, along with examples from the article and additional ones. We also posted appendices covering many practical implementation details not covered in the paper, mathematical proofs, application to ML models besides neural networks and extensions necessary for a reliable implementation in production.

We develop a supervised machine learning algorithm that is able to learn topological phases for finite condensed matter systems from bulk data in real lattice space. The algorithm employs diagonalization in real space together with any supervised learning algorithm to learn topological phases through an eigenvector ensembling procedure. We combine our algorithm with decision trees and random forests to successfully recover topological phase diagrams of Su-Schrieffer-Heeger (SSH) models from bulk lattice data in real space and show how the Shannon information entropy of ensembles of lattice eigenvectors can be used to retrieve a signal detailing how topological information is distributed in the bulk. The discovery of Shannon information entropy signals associated with topological phase transitions from the analysis of data from several thousand SSH systems illustrates how model explainability in machine learning can advance the research of exotic quantum materials with properties that may power future technological applications such as qubit engineering for quantum computing.

The standard training algorithm in neural machine translation (NMT) suffers from exposure bias, and alternative algorithms have been proposed to mitigate this. However, the practical impact of exposure bias is under debate. In this paper, we link exposure bias to another well-known problem in NMT, namely the tendency to generate hallucinations under domain shift. In experiments on three datasets with multiple test domains, we show that exposure bias is partially to blame for hallucinations, and that training with Minimum Risk Training, which avoids exposure bias, can mitigate this. Our analysis explains why exposure bias is more problematic under domain shift, and also links exposure bias to the beam search problem, i.e. performance deterioration with increasing beam size. Our results provide a new justification for methods that reduce exposure bias: even if they do not increase performance on in-domain test sets, they can increase model robustness to domain shift.

This paper is the first to consider online algorithms to schedule a proportionate flexible flow shop of batching machines (PFFB). The scheduling model is motivated by manufacturing processes of individualized medicaments, which are used in modern medicine to treat some serious illnesses. We provide two different online algorithms, proving also lower bounds for the offline problem to compute their competitive ratios. The first algorithm is an easy-to-implement, general local scheduling heuristic. It is 2-competitive for PFFBs with an arbitrary number of stages and for several natural scheduling objectives. We also show that for total/average flow time, no deterministic algorithm with better competitive ratio exists. For the special case with two stages and the makespan or total completion time objective, we describe an improved algorithm that achieves the best possible competitive ratio $varphi=frac{1+sqrt{5}}{2}$, the golden ratio. All our results also hold for proportionate (non-flexible) flow shops of batching machines (PFB) for which this is also the first paper to study online algorithms.

Sentence level quality estimation (QE) for machine translation (MT) attempts to predict the translation edit rate (TER) cost of post-editing work required to correct MT output. We describe our view on sentence-level QE as dictated by several practical setups encountered in the industry. We find consumers of MT output---whether human or algorithmic ones---to be primarily interested in a binary quality metric: is the translated sentence adequate as-is or does it need post-editing? Motivated by this we propose a quality classification (QC) view on sentence-level QE whereby we focus on maximizing recall at precision above a given threshold. We demonstrate that, while classical QE regression models fare poorly on this task, they can be re-purposed by replacing the output regression layer with a binary classification one, achieving 50-60\% recall at 90\% precision. For a high-quality MT system producing 75-80\% correct translations, this promises a significant reduction in post-editing work indeed.

In encoder-decoder neural models, multiple encoders are in general used to represent the contextual information in addition to the individual sentence. In this paper, we investigate multi-encoder approaches in documentlevel neural machine translation (NMT). Surprisingly, we find that the context encoder does not only encode the surrounding sentences but also behaves as a noise generator. This makes us rethink the real benefits of multi-encoder in context-aware translation - some of the improvements come from robust training. We compare several methods that introduce noise and/or well-tuned dropout setup into the training of these encoders. Experimental results show that noisy training plays an important role in multi-encoder-based NMT, especially when the training data is small. Also, we establish a new state-of-the-art on IWSLT Fr-En task by careful use of noise generation and dropout methods.

Simplified Chinese to Traditional Chinese character conversion is a common preprocessing step in Chinese NLP. Despite this, current approaches have poor performance because they do not take into account that a simplified Chinese character can correspond to multiple traditional characters. Here, we propose a model that can disambiguate between mappings and convert between the two scripts. The model is based on subword segmentation, two language models, as well as a method for mapping between subword sequences. We further construct benchmark datasets for topic classification and script conversion. Our proposed method outperforms previous Chinese Character conversion approaches by 6 points in accuracy. These results are further confirmed in a downstream application, where 2kenize is used to convert pretraining dataset for topic classification. An error analysis reveals that our method's particular strengths are in dealing with code-mixing and named entities.

Neural machine translation (NMT) needs large parallel corpora for state-of-the-art translation quality. Low-resource NMT is typically addressed by transfer learning which leverages large monolingual or parallel corpora for pre-training. Monolingual pre-training approaches such as MASS (MAsked Sequence to Sequence) are extremely effective in boosting NMT quality for languages with small parallel corpora. However, they do not account for linguistic information obtained using syntactic analyzers which is known to be invaluable for several Natural Language Processing (NLP) tasks. To this end, we propose JASS, Japanese-specific Sequence to Sequence, as a novel pre-training alternative to MASS for NMT involving Japanese as the source or target language. JASS is joint BMASS (Bunsetsu MASS) and BRSS (Bunsetsu Reordering Sequence to Sequence) pre-training which focuses on Japanese linguistic units called bunsetsus. In our experiments on ASPEC Japanese--English and News Commentary Japanese--Russian translation we show that JASS can give results that are competitive with if not better than those given by MASS. Furthermore, we show for the first time that joint MASS and JASS pre-training gives results that significantly surpass the individual methods indicating their complementary nature. We will release our code, pre-trained models and bunsetsu annotated data as resources for researchers to use in their own NLP tasks.

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the Blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; however, cuff-based BP measurements are discrete and uncomfortable to the user. To address this need, a cuff-less, continuous and a non-invasive BP measurement system is proposed using Photoplethysmogram (PPG) signal and demographic features using machine learning (ML) algorithms. PPG signals were acquired from 219 subjects, which undergo pre-processing and feature extraction steps. Time, frequency and time-frequency domain features were extracted from the PPG and their derivative signals. Feature selection techniques were used to reduce the computational complexity and to decrease the chance of over-fitting the ML algorithms. The features were then used to train and evaluate ML algorithms. The best regression models were selected for Systolic BP (SBP) and Diastolic BP (DBP) estimation individually. Gaussian Process Regression (GPR) along with ReliefF feature selection algorithm outperforms other algorithms in estimating SBP and DBP with a root-mean-square error (RMSE) of 6.74 and 3.59 respectively. This ML model can be implemented in hardware systems to continuously monitor BP and avoid any critical health conditions due to sudden changes.

Unsupervised machine translation (MT) has recently achieved impressive results with monolingual corpora only. However, it is still challenging to associate source-target sentences in the latent space. As people speak different languages biologically share similar visual systems, the potential of achieving better alignment through visual content is promising yet under-explored in unsupervised multimodal MT (MMT). In this paper, we investigate how to utilize visual content for disambiguation and promoting latent space alignment in unsupervised MMT. Our model employs multimodal back-translation and features pseudo visual pivoting in which we learn a shared multilingual visual-semantic embedding space and incorporate visually-pivoted captioning as additional weak supervision. The experimental results on the widely used Multi30K dataset show that the proposed model significantly improves over the state-of-the-art methods and generalizes well when the images are not available at the testing time.

Narrowband internet-of-things (NB-IoT) is a competitive 5G technology for massive machine-type communication scenarios, but meanwhile introduces narrowband interference (NBI) to existing broadband transmission such as the long term evolution (LTE) systems in enhanced mobile broadband (eMBB) scenarios. In order to facilitate the harmonic and fair coexistence in wireless heterogeneous networks, it is important to eliminate NB-IoT interference to LTE systems. In this paper, a novel sparse machine learning based framework and a sparse combinatorial optimization problem is formulated for accurate NBI recovery, which can be efficiently solved using the proposed iterative sparse learning algorithm called sparse cross-entropy minimization (SCEM). To further improve the recovery accuracy and convergence rate, regularization is introduced to the loss function in the enhanced algorithm called regularized SCEM. Moreover, exploiting the spatial correlation of NBI, the framework is extended to multiple-input multiple-output systems. Simulation results demonstrate that the proposed methods are effective in eliminating NB-IoT interference to LTE systems, and significantly outperform the state-of-the-art methods.

Recently, the Edge Computing paradigm has gained significant popularity both in industry and academia. Researchers now increasingly target to improve performance and reduce energy consumption of such devices. Some recent efforts focus on using emerging RRAM technologies for improving energy efficiency, thanks to their no leakage property and high integration density. As the complexity and dynamism of applications supported by such devices escalate, it has become difficult to maintain ideal performance by static RRAM controllers. Machine Learning provides a promising solution for this, and hence, this work focuses on extending such controllers to allow dynamic parameter updates. In this work we propose an Adaptive RRAM Variability-Aware Controller, AVAC, which periodically updates Wait Buffer and batch sizes using on-the-fly learning models and gradient ascent. AVAC allows Edge devices to adapt to different applications and their stages, to improve computation performance and reduce energy consumption. Simulations demonstrate that the proposed model can provide up to 29% increase in performance and 19% decrease in energy, compared to static controllers, using traces of real-life healthcare applications on a Raspberry-Pi based Edge deployment.

A system and method that facilitates urban traffic state detection based on support vector machine (SVM) and multilayer perceptron (MLP) classifiers is provided. Moreover, the SVM and MLP classifiers are fused into a cascaded two-tier classifier that improves the accuracy of the traffic state classification. To further improve the accuracy, the cascaded two-tier classifier (e.g., MLP-SVM), a single SVM classifier and a single MLP classifier are fused to determine a final decision for a traffic state. In addition, fusion strategies are employed during training and implementation phases to compensate for data acquisition and classification errors caused by noise and/or outliers.

A cloud system may create physical resource tags to store relationships between cloud computing offerings, such as computing service offerings, storage offerings, and network offerings, and the specific physical resources in the cloud computing environment. Cloud computing offerings may be presented to cloud customers, the offerings corresponding to various combinations of computing services, storage, networking, and other hardware or software resources. After a customer selects one or more cloud computing offerings, a cloud resource manager or other component within the cloud infrastructure may retrieve a set of tags and determine a set of physical hardware resources associated with the selected offerings. The physical hardware resources associated with the selected offerings may be subsequently used to provision and create the new virtual machine and its operating environment.

A system, method and computer program product for allocating shared resources. Upon receiving requests for resources, the cost of bundling software in a virtual machine (VM) image is automatically generated. Software is selected by the cost for each bundle according to the time required to install it where required, offset by the time to uninstall it where not required. A number of VM images having the highest software bundle value (i.e., highest cost bundled) is selected and stored, e.g., in a machine image store. With subsequent requests for resources, VMs may be instantiated from one or more stored VM images and, further, stored images may be updated selectively updated with new images.

A server computer system determines that configuring a first virtual machine in a cloud depends on a configuration result of configuring a second virtual machine. The server computer system configures the second virtual machine in the cloud and configures the first virtual machine in the cloud using the configuration result of the second virtual machine.

A system and method for reconfiguring a computing environment comprising a consumption analysis server, a placement server, an infrastructure management client and a data warehouse in communication with a set of data collection agents and a database. The consumption analysis server operates on measured resource utilization data to yield a set of resource consumptions in regularized time blocks, collects host and virtual machine configurations from the computing environment and determines available capacity for a set of target hosts. The placement server assigns a set of target virtual machines to the target set of hosts in a new placement. In one mode of operation the new placement is nearly optimal. In another mode of operation, the new placement is “good enough” to achieve a threshold score based on an objective function of resource capacity headroom. The new placement is implemented in the computing environment.

A computing machine is disclosed having a memory system for storing a collection of execution nodes, a head for reading a sequence of symbols in the execution nodes in the memory system, and writing a sequence of symbols in the memory system. The machine is configured to execute a computation with a collection of pairs of execution nodes. Each pair of execution nodes represents a machine instruction. One execution node in the pair represents input of the machine instruction represented by the execution nodes. Another execution node in the pair represents output of the machine instruction represented by the execution nodes. Each execution node has a state of the machine, a sequence of symbols and a number.

A datapath extraction tool uses machine-learning models to selectively classify clusters of cells in an integrated circuit design as either datapath logic or non-datapath logic based on cluster features. A support vector machine and a neural network can be used to build compact and run-time efficient models. A cluster is classified as datapath if both the support vector machine and the neural network indicate that it is datapath-like. The cluster features may include automorphism generators for the cell clusters, or physical information based on the cell locations from a previous (e.g., global) placement, such as a ratio of a total cell area for a given cluster to a half-perimeter of a bounding box for the given cluster.

The present disclosure relates to a superconducting rotating electrical machine and a manufacturing method for a high temperature superconducting film thereof. The superconducting rotating electrical machine includes a stator, and a rotor rotatable with respect to the stator, the rotor having a rotary shaft and a rotor winding. Here, the rotor winding includes tubes disposed on a circumference of the rotary shaft and each forming a passage for a cooling fluid therein, superconducting wires accommodated within the tubes, and a cooling fluid flowing through the inside of the tubes. This configuration may allow for direct heat exchange between the superconducting wires and a refrigerant, resulting in improvement of heat exchange efficiencies of the superconducting wires.

A visualization can include a set of swim lanes, each swim lane representing information about an event type. An event type can be specified, e.g., as those events having certain keywords and/or having specified value(s) for specified field(s). The swim lane can plot when (within a time range) events of the associated event type occurred. Specifically, each such event can be assigned to a bucket having a bucket time matching the event time. A swim lane can extend along a timeline axis in the visualization, and the buckets can be positioned at a point along the axis that represents the bucket time. Thus, the visualization may indicate whether events were clustered at a point in time. Because the visualization can include a plurality of swim lanes, the visualization can further indicate how timing of events of a first type compare to timing of events of a second type.

A tunable resonator is provided that has a high Q for each resonate frequency. The tunable resonator is a MEMs tunable resonator wherein the tuner is affected by moving a moveable mass, associated with the resonating portion of the resonator, form a first position to a second position such that the moveable mass is held in the first position or second position by a detent rather than a constant electromagnet magnetic or electrostatic force applied thereon.

A computing system includes a parent partition, child partitions, a hypervisor, shared memories each associated with one of the child partitions, and trigger pages each associated with one of the child partitions. The hypervisor receives a system event signal from one of the child partitions and, in response to receiving the system event signal, accesses the trigger page associated with that child partition. The hypervisor determines whether the trigger page indicates whether data is available to be read from the shared memory associated with the child partition. The hypervisor can send an indication to either the parent partition or the child partitions that data is available to be read from the shared memory associated with the child partition if the hypervisor determines that the trigger page indicates that data is available to be read from the shared memory associated with the child partition.

System and method for conversion of virtual machine files without requiring copying of the virtual machine payload (data) from one location to another location. By eliminating this step, applicant's invention significantly enhances the efficiency of the conversion process. In one embodiment, a file system or storage system provides indirections to locations of data elements stored on a persistent storage media. A source virtual machine file includes hypervisor metadata (HM) data elements in one hypervisor file format, and virtual machine payload (VMP) data elements. The source virtual machine file is converted by transforming the HM data elements of the source file to create destination HM data elements in a destination hypervisor format different from the source hypervisor format; maintaining the locations of the VMP data elements stored on the persistent storage media constant during the conversion from source to destination file formats without reading or writing the VMP data elements; and creating indirections to reference the destination HM data elements in the destination hypervisor format and the existing stored VMP data elements.

A method and apparatus are disclosed of monitoring a number of virtual machines operating in an enterprise network. One example method of operation may include identifying a number of virtual machines currently operating in an enterprise network and determining performance metrics for each of the virtual machines. The method may also include identifying at least one candidate virtual machine from the virtual machines to optimize its active application load and modifying the candidate virtual machine to change its active application load.

A method and apparatus for estimating virtual machine energy consumption, and in particular, a method and apparatus for estimating virtual machine energy consumption in a computer system. The method includes: obtaining system energy consumption of the system hardware resources; obtaining event information of a plurality of functional units into which the system hardware resources are divided, and mapping the event information to the respective virtual machines; and calculating energy consumption of the virtual machines according to a plurality of energy consumption coefficients corresponding to the plurality of functional units and according to the event information mapped to the functional units of the respective virtual machines.

A textile for providing traditional Chinese medicine therapy to a wearer using electronic stimulation includes at least two conductive paths that are made from conductive textile material, the conductive paths are separated by nonconductive textile material, at least one pair of electrodes attach to the conductive paths corresponding to specific part of body or acupoints according to traditional Chinese medicine theory, and an electronic stimulation signal controller configured to conduct electronic stimulation signals to the electrodes via the conductive paths.

An injection molding machine includes an ejector unit configured to eject a molding product from a mold and a mold release force sensor configured to detect a force to release the molding product from the mold.

An injection molding machine includes an ejector unit configured to eject a molding product from a mold. The ejector unit includes a support provided on a platen to which the mold is attached, a slidable base configured to slide relative to the support, a transmission mechanism supported by the support and configured to convert an input into an output corresponding to the distance between the support and the slidable base and transmit the output to the slidable base, a drive source configured to cause the transmission mechanism to operate, an ejection member configured to move together with the slidable base, and an adjustment mechanism configured to adjust the position of the slidable base relative to the ejection member.

The present utility model provides a mold set used for dumpling or dumpling-like food product formation comprising a pair of jaws, the closure of which is configured to clamp a dough pad over a filling thereby forming a raw product of the dumpling or dumpling-like food product, wherein the jaws in a closed condition can be driven to simulate the human action of compressing a filling pocket of the dumpling or dumpling-like food product.

A system and method can support a flooding mechanism using a multicast group in a middleware machine environment. The middleware machine environment can comprise a gateway instance that includes an external port for receiving one or more data packets from an external network. The middleware machine environment also comprises one or more host servers, each of which is associated with one or more virtual machines that can process the data packets. Furthermore, said host servers can provide virtual interfaces that belong to a virtual hub associated with the gateway instance. At least one said packet is a flooded packet that is specified with an unknown destination address when it is received at the external port. The gateway instance operates to send the flooded packet to the multicast group that operates to forward the flooded packet to one or more said host servers in the multicast group.

A mixer system includes a mixing chamber with a drive panel, open top, discharge opening in a side of the mixing chamber, and door configured to open and close the discharge opening. A first mixing auger is disposed inside the mixing chamber, and a first auger drive is disposed on another side of the drive panel and connected to the first auger through the drive panel and connected to a driveline. A second mixing auger is disposed inside the mixing chamber on the first side of the drive panel, and another auger drive is connected to the second auger through the drive panel. A clutch is connected between the second auger drive and the driveline and configured to mechanically connect and disconnect the second auger drive from the driveline based on an input. A method of sequentially starting different augers within a mixing chamber is provided.