AVERAGE-VALUE MODELING OF HYSTERESIS CURRENT CONTROL IN POWER ELECTRONICS

Hysteresis current control has been widely used in power electronics with the advantages of fast dynamic response under parameter, line and load variation and ensured stability. However, a main disadvantage of hysteresis current control is the uncertain and varying switching frequency which makes it difficult to form an average-value model. The changing switching frequency and unspecified switching duty cycle make conventional average-value models based on PWM control difficult to apply directly to converters that are controlled by hysteresis current control. In this work, a new method for average-value modeling of hysteresis current control in boost converters, three-phase inverters, and brushless dc motor drives is proposed. It incorporates a slew-rate limitation on the inductor current that occurs naturally in the circuit during large system transients. This new method is compared with existing methods in terms of simulation run time and rms error. The performance is evaluated based on a variety of scenarios, and the simulation results are compared with the results of detailed models. The simulation results show that the proposed model represents the detailed model well and is faster and more accurate than existing methods. The slew-rate limitation model of hysteresis current control accurately captures the salient detail of converter performance while maintaining the computational efficiency of average-value models. Validations in hardware are also presented

Groups With Two Generators Having Unsolvable Word Problem And Presentations of Mihailova Subgroups

A presentation of a group with two generators having unsolvable word problem and an explicit countable presentation of Mihailova subgroup of F_2×F_2 with finite number of generators are given. Where Mihailova subgroup of F_2×F_2 enjoys the unsolvable subgroup membership problem.One then can use the presentation to create entities\u27 private key in a public key cryptsystem

Double shielded Public Key Cryptosystems

By introducing extra shields on Shpilrain and Ushakov\u27s Ko-Lee-like protocol based on the decomposition problem of group elements we propose two new key exchange schemes and then a number of public key cryptographic protocols. We show that these protocols are free of known attacks. Particularly,if the entities taking part in our protocols create their private keys composed by the generators of the Mihailova subgroups of Bn, we show that the safety of our protocols are very highly guarantied by the insolvability of subgroup membership problem of the Mihailova subgroups

A Practical Illustration of Methods to Deal with Potential Outliers: A Multiverse Outlier Analysis of Study 3 from Brummelman, Thomaes, Orobio de Castro, Overbeek, and Bushman (2014)

Recently, Brummelman, Thomaes, Orobio de Castro, Overbeek, and Bushman (2014: Study 3) demonstrated that inflated praise benefits challenge seeking of children with high self-esteem, but harms challenge seeking of children with low self-esteem. In the present paper, we examined the original data set on model-fit and prediction outliers according to various reasonable criteria and norms. Subsequently, we carried out a multiverse outlier re-analysis on the data of Brummelman and colleagues’ Study 3, employing the same analytical approach as the original authors did but excluding outliers. Out of the twelve re-analyses in the multiverse, six demonstrated that removing only a small number of outliers rendered the originally reported crucial interaction effect between self-esteem and type of praise non-significant and produced a sizeable reduction of the effect size. The present paper illustrates the use of reporting outlier analyses, which lies in allowing a critical evaluation of the empirical evidence and offering a more complete picture that enhances future studies in the field

VaBUS: Edge-Cloud Real-Time Video Analytics via Background Understanding and Subtraction

Edge-cloud collaborative video analytics is transforming the way data is being handled, processed, and transmitted from the ever-growing number of surveillance cameras around the world. To avoid wasting limited bandwidth on unrelated content transmission, existing video analytics solutions usually perform temporal or spatial filtering to realize aggressive compression of irrelevant pixels. However, most of them work in a context-agnostic way while being oblivious to the circumstances where the video content is happening and the context-dependent characteristics under the hood. In this work, we propose VaBUS, a real-time video analytics system that leverages the rich contextual information of surveillance cameras to reduce bandwidth consumption for semantic compression. As a task-oriented communication system, VaBUS dynamically maintains the background image of the video on the edge with minimal system overhead and sends only highly confident Region of Interests (RoIs) to the cloud through adaptive weighting and encoding. With a lightweight experience-driven learning module, VaBUS is able to achieve high offline inference accuracy even when network congestion occurs. Experimental results show that VaBUS reduces bandwidth consumption by 25.0%-76.9% while achieving 90.7% accuracy for both the object detection and human keypoint detection tasks

Transcutaneous electrical nerve stimulation (TENS) for phantom pain and stump pain following amputation in adults.

BACKGROUND: This is the first update of a Cochrane review published in Issue 5, 2010 on transcutaneous electrical nerve stimulation (TENS) for phantom pain and stump pain following amputation in adults. Pain may present in a body part that has been amputated (phantom pain) or at the site of amputation (stump pain), or both. Phantom pain and stump pain are complex and multidimensional and the underlying pathophysiology remains unclear. The condition remains a severe burden for those who are affected by it. The mainstay treatments are predominately pharmacological, with increasing acknowledgement of the need for non-drug interventions. TENS has been recommended as a treatment option but there has been no systematic review of available evidence. Hence, the effectiveness of TENS for phantom pain and stump pain is currently unknown. OBJECTIVES: To assess the analgesic effectiveness of TENS for the treatment of phantom pain and stump pain following amputation in adults. SEARCH METHODS: For the original version of the review we searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, AMED, CINAHL, PEDRO and SPORTDiscus (February 2010). For this update, we searched the same databases for relevant randomised controlled trials (RCTs) from 2010 to 25 March 2015. SELECTION CRITERIA: We only included RCTs investigating the use of TENS for the management of phantom pain and stump pain following an amputation in adults. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed trial quality and extracted data. We planned that where available and appropriate, data from outcome measures were to be pooled and presented as an overall estimate of the effectiveness of TENS. MAIN RESULTS: In the original review there were no RCTs that examined the effectiveness of TENS for the treatment of phantom pain and stump pain in adults. For this update, we did not identify any additional RCTs for inclusion. AUTHORS' CONCLUSIONS: There were no RCTs to judge the effectiveness of TENS for the management of phantom pain and stump pain. The published literature on TENS for phantom pain and stump pain lacks the methodological rigour and robust reporting needed to confidently assess its effectiveness. Further RCT evidence is required before an assessment can be made. Since publication of the original version of this review, we have found no new studies and our conclusions remain unchanged

Electrochemical oxidation mechanisms for selective products due to C-O and C-C cleavages of beta-O-4 linkages in lignin model compounds

Electrochemical oxidation is a promising and effective method for lignin depolymerization owing to its selective oxidation capacity and environmental friendliness. Herein, the electrooxidation of non-phenolic alkyl aryl ether monomers and beta-O-4 dimers was experimentally (by cyclic voltammetry, in situ spectroelectrochemistry, and gas chromatography-mass spectroscopy) and theoretically (by DFT calculations) explored in detail. Compared to the reported literature (T. Shiraishi, T. Takano, H. Kamitakahara and F. Nakatsubo, Holzforschung, 2012, 66(3), 303-309), 1-(4-ethoxyphenyl)ethanol showed a distinguishable oxidation pathway, where the resulting carbonyl product surprisingly underwent a bond cleavage on alkyl-aryl ether to ultimately produce a quinoid like compound. In contrast, beta-O-4 dimers, like 2-phenoxy-1-phenethanol and 2-phenoxyacetophenone also demonstrated electrochemical oxidation induced by C-beta-O and C-alpha-C-beta bond cleavages. For the oxidation products, the presence of the C-alpha-hydroxyl group in dimers was the key to selectively generate aldehyde-containing species under mild electrochemical conditions, otherwise it produces alcohol-containing products following a different mechanism compared to the C-alpha & xe001;O containing dimers

Adaptive Multi-Channel Residual Shrinkage Networks for the Diagnosis of Multi-Fault Gearbox

Intelligent fault diagnosis is a hot research topic in machinery and equipment health monitoring. However, most intelligent fault diagnosis models have good performance in single fault mode, but poor performance in multiple fault modes. In real industrial scenarios, the interference of noise also makes it difficult for intelligent diagnostic models to extract fault features. To solve these problems, an adaptive multi-channel residual shrinkage network (AMC-RSN) is proposed in this paper. First, a channel attention mechanism module is constructed in the residual block and a soft thresholding function is introduced for noise reduction. Then, an adaptive multi-channel network is constructed to fuse the feature information of each channel in order to extract as many features as possible. Finally, the Meta-ACON activation function is used before the fully connected layer to decide whether to activate the neurons by the model outputs. The method was implemented in gearbox fault diagnosis, and the experimental results show that AMC-RSN has better diagnostic results than other networks under various faults and strong noises