Prediction Model of End Mill Cutting Edge Based on Material Properties and Cutting Conditions

In machining, the cutting performance of the tool depends on the tool material, tool structure, tool geometry, properties of workpiece materials, and cutting conditions. If the user chooses an inappropriate cutting tool for the machining of the workpiece material, this will cause energy loss and severe tool wear. This study aims to investigate the influence of mechanical properties of workpiece material and cutting conditions on the tool geometry and to establish a polynomial network for the prediction of a reasonable normal relief angle and a normal wedge angle based on experimental data. Experimental results indicate that the cutting of high hardness and high strength workpiece materials requires a larger normal wedge angle to increase the cutting edge strength. In addition, the design of the normal relief angle is related to Young\u27s modulus and the toughness of the workpiece material, mainly to avoid material elastic recovery during the cutting process. In terms of cutting parameters, as the radial depth of cut increases, the contact area between the tool and the chip increases, which causes the heat to concentrate at the tip of the tool; hence, it is necessary to increase the normal wedge angle. In addition, the feed per tooth had a negligible effect on the normal wedge angle. Finally, the prediction model was verified by five untested workpiece materials. The results of the cutting tests showed that the flatness of the cutting edge was less than 15 μm, which indicates that a normal cutting phenomenon occurred on the flank

THE EFFECT OF TENNIS RACKET STRING VIBRATION ABSORBER PLACEMENT ON TENNIS RACKET VIBRATIONS

The purpose of this research was to analyze the vibration effect of tennis racket caused by impact on different locative vibration absorber and locations. In this experiment, The tennis racket was fixed and kept the face horizontalized to the ground with 50 Ib on strings. A tennis ball was dropped from one meter height to impact three locations of the racket. The different locative vibration absorber was fixed on the racket. It was installed an accelerometer to capture the vibration signal of the handle of the racket. After the experiment, the data was used logarithmic decrement to calculate damping ratio. It was illustrated when the vibration absorber in Back and Tip to have obvious effect. But in Side, it could not effectively decrease the vibration compared with the racket without absorber

Enhancing the Insulation of Wide-Range Spectrum in the PVA/N Thin Film by Doping ZnO Nanowires

In this study, polyvinyl alcohol/nitrogen (PVA/N) hybrid thin films doped with sharp-sword ZnO nanowires with insulating effect and wide-range spectrum are demonstrated for the first time. PVA/N doped ZnO nanocomposites were developed by blending PVA and N-doped ZnO nanowires in water at room temperature. Measurements from the field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), Raman, and photoluminescence emission (PL) spectra of the products show that nitrogen is successfully doped into the ZnO wurtzite crystal lattice. In addition, the refractive index of PVA/N doped ZnO hybrid thin films can be controlled by varying the doped ZnO nanowires under different NH3 concentrations. It is believed that PVA/N doped ZnO hybrid thin films are a suitable candidate for emerging applications like heat-shielding coatings on smart windows

How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval

Various techniques have been developed in recent years to improve dense retrieval (DR), such as unsupervised contrastive learning and pseudo-query generation. Existing DRs, however, often suffer from effectiveness tradeoffs between supervised and zero-shot retrieval, which some argue was due to the limited model capacity. We contradict this hypothesis and show that a generalizable DR can be trained to achieve high accuracy in both supervised and zero-shot retrieval without increasing model size. In particular, we systematically examine the contrastive learning of DRs, under the framework of Data Augmentation (DA). Our study shows that common DA practices such as query augmentation with generative models and pseudo-relevance label creation using a cross-encoder, are often inefficient and sub-optimal. We hence propose a new DA approach with diverse queries and sources of supervision to progressively train a generalizable DR. As a result, DRAGON, our dense retriever trained with diverse augmentation, is the first BERT-base-sized DR to achieve state-of-the-art effectiveness in both supervised and zero-shot evaluations and even competes with models using more complex late interaction (ColBERTv2 and SPLADE++)

Automating the audit of electronic invoices with a soft robot

Taiwan's Chi Mei Medical Center has completed four challenges mentioned in published robotic process automation (RPA) studies including automating a dynamic process, designing feasible human-robot collaboration, incorporating other emerging technologies, and bringing positive business impacts. Its executives called a committee to implement the electronic invoicing. This implementation includes the creation of a software robot to download automatically cloud electronic invoice (E-invoice) data from Taiwan's E-invoice platform and detect the inconsistency between them and on-premise data. This bot operates when internal auditors are off their office. They satisfied this software robot since the remaining work is only verifying the resulting inconsistency. The Chi Mei Medical Center measured the time and costs before and after adopting software robots to audit E-invoice; consequently, it welcomed more bots automating other business processes. In conclusion, integrating a software robot with other emerging technologies mitigates the possible errors provided by this bot. A good human-robot collaboration relies on the consideration of human perspective in choosing RPA tasks. Free bot creators are sufficient to verify that automating a business process using a bot is a reasonable investment.Comment: 11 pages, 6 figures, 1 tabl

A 90-DAY SUBCHRONIC TOXICOLOGICAL ASSESSMENT of DEINOCOCCUS GRANDIS FERMENTED SOYMILK IN SPRAGUE-DAWLEY RATS

Objective: Despite the fact that there was no adverse effect observed in previous animal safety studies of Deinococcus grandis (D. grandis) fermented soymilk, including acute oral toxicity assay, 3 different test systems of genotoxicity test and teratogenicity study, whether D. grandis fermented soymilk is safe for long-term use remains unknown. Therefore, the study was conducted further to clarify the edible safety of D. grandis fermented soymilk for long term use.Methods: Eighty Sprague-Dawley (SD) rats were divided into four groups, each consisting of ten male and ten female rats. Rats were orally administrated with reverse osmosis water (control) or 1,000, 2,000 and 3,000 mg/kg b.w./d freeze dried D. grandis fermented soymilk powder for 90 consecutive days. Clinical observation of the rats was carried out daily. The body weight and feed intake of the rats were recorded weekly. At the end of the study, all rats were sacrificed and the blood and organs were collected for hematology, clinical biochemistry and histopathological examination.Results: During the study period, no abnormality occurred in clinical signs, body weight, and ophthalmological examination. There were no significant differences in urinalysis, hematology and clinical biochemistry parameters between the treatment and control group. Necropsy and histopathological examination showed no treatment-related change.Conclusion: According to the results, the no-observed-adverse-effect level (NOAEL) of D. grandis fermented soymilk was greater than 3,000 mg/kg b.w./d in SD rats.Keywords: Deinococcus grandis (D. grandis), 90-day subchronic toxicity, NOAEL, Safety assessment, GKB-Aid 199

Neural correlates of lateral modulation and perceptual filling-in in center-surround radial sinusoidal gratings: an fMRI study

We investigated lateral modulation effects with functional magnetic resonance imaging. We presented radial sinusoidal gratings in random sequence: a scotoma grating with two arc-shaped blank regions (scotomata) in the periphery, one in the left and one in the right visual field, a center grating containing pattern only in the scotoma regions, and a full-field grating where the pattern occupied the whole screen. On each trial, one of the three gratings flickered in counterphase for 10 s, followed by a blank period. Observers were instructed to perform a fixation task and report whether filling-in was experienced during the scotoma condition. The results showed that the blood-oxygen-level-dependent signal was reduced in areas corresponding to the scotoma regions in the full-field compared to the center condition in V1 to V3 areas, indicating a lateral inhibition effect when the surround was added to the center pattern. The univariate analysis results showed no difference between the filling-in and no-filling-in trials. However, multivariate pattern analysis results showed that classifiers trained on activation pattern in V1 to V3 could differentiate between filling-in and no-filling-in trials, suggesting that the neural activation pattern in visual cortex correlated with the subjective percept