Personalized Acoustic Modeling by Weakly Supervised Multi-Task Deep Learning using Acoustic Tokens Discovered from Unlabeled Data

It is well known that recognizers personalized to each user are much more effective than user-independent recognizers. With the popularity of smartphones today, although it is not difficult to collect a large set of audio data for each user, it is difficult to transcribe it. However, it is now possible to automatically discover acoustic tokens from unlabeled personal data in an unsupervised way. We therefore propose a multi-task deep learning framework called a phoneme-token deep neural network (PTDNN), jointly trained from unsupervised acoustic tokens discovered from unlabeled data and very limited transcribed data for personalized acoustic modeling. We term this scenario "weakly supervised". The underlying intuition is that the high degree of similarity between the HMM states of acoustic token models and phoneme models may help them learn from each other in this multi-task learning framework. Initial experiments performed over a personalized audio data set recorded from Facebook posts demonstrated that very good improvements can be achieved in both frame accuracy and word accuracy over popularly-considered baselines such as fDLR, speaker code and lightly supervised adaptation. This approach complements existing speaker adaptation approaches and can be used jointly with such techniques to yield improved results.Comment: 5 pages, 5 figures, published in IEEE ICASSP 201

Qubit Mapping Toward Quantum Advantage

Qubit Mapping is a pivotal stage in quantum compilation flow. Its goal is to convert logical circuits into physical circuits so that a quantum algorithm can be executed on real-world non-fully connected quantum devices. Qubit Mapping techniques nowadays still lack the key to quantum advantage, scalability. Several studies have proved that at least thousands of logical qubits are required to achieve quantum computational advantage. However, to our best knowledge, there is no previous research with the ability to solve the qubit mapping problem with the necessary number of qubits for quantum advantage in a reasonable time. In this work, we provide the first qubit mapping framework with the scalability to achieve quantum advantage while accomplishing a fairly good performance. The framework also boasts its flexibility for quantum circuits of different characteristics. Experimental results show that the proposed mapping method outperforms the state-of-the-art methods on quantum circuit benchmarks by improving over 5% of the cost complexity in one-tenth of the program running time. Moreover, we demonstrate the scalability of our method by accomplishing mapping of an 11,969-qubit Quantum Fourier Transform within five hours

Auto-adhesive transdermal drug delivery patches using beetle inspired micropillar structures

The patch described in this paper combines the principles of wet adhesion, which is a widely adopted biological adhesion system in nature, with transdermal drug delivery. A biologically inspired micropillar patch was fabricated that is self-adhesive, reusable, and can sustain a controlled drug release. We successfully preloaded the commercial non-steroidal anti-inflammatory generic drug unguents indomethacin, ketoprofen, diclofenac sodium and etofenamate into a polydimethylsiloxane elastomeric matrix and fabricated drug-containing micropillar patches. When examining the drug release kinetics and friction of the patches, we observed that these drug unguents can be released calculably and regularly for several days. Additionally, the drug unguents released from the patch to its attached surface are critical to increase the strength of the patch's adhesion, which is based on capillary attractive forces and is inspired by beetle feet. Here, we create a novel system combining biomimetics and drug delivery that can be modified for use across the biomedical and engineering spectra. Motivation: the objective of the present study was to characterize a micropillar PDMS patch that was inspired by a beetle's wet adhesion as a platform for conducting in vitro release studies. Commercially available non-steroid anti-inflammatory drugs (NSAIDs) were used as the model drugs for our delivery systems. An emphasis was put on quantitatively evaluating the drug release and friction manifestation of these patches

Decoding Information from noisy, redundant, and intentionally-distorted sources

Advances in information technology reduce barriers to information propagation, but at the same time they also induce the information overload problem. For the making of various decisions, mere digestion of the relevant information has become a daunting task due to the massive amount of information available. This information, such as that generated by evaluation systems developed by various web sites, is in general useful but may be noisy and may also contain biased entries. In this study, we establish a framework to systematically tackle the challenging problem of information decoding in the presence of massive and redundant data. When applied to a voting system, our method simultaneously ranks the raters and the ratees using only the evaluation data, consisting of an array of scores each of which represents the rating of a ratee by a rater. Not only is our appraoch effective in decoding information, it is also shown to be robust against various hypothetical types of noise as well as intentional abuses.Comment: 19 pages, 5 figures, accepted for publication in Physica

OPTIMAL REASSIGNMENT OF FLIGHTS TO AIRPORT BAGGAGE UNLOADING CAROUSELS IN RESPONSE TO TEMPORARY MALFUNCTIONS

Being able to efficiently reassign outbound flights to baggage unloading carousels (BUCs) following temporary malfunctions is very important for airport operators. This study proposes an optimization model with a heuristic to solve the carousel reassignment problem. The objective is to minimize the total disturbance and overlapping time caused by the reassignment of outbound flights. A heuristic is developed to efficiently solve large-sized instances. The proposed approach is then applied to solve real-world instances of the problem at a major international airport in Taiwan. The computation time is about two minutes. The objective value obtained with the heuristic is more than 15% better than that obtained by the manual approach currently used by the operator. The improvement is gained mostly from the reduction in total temporal disturbance and overlapping time. The proposed approach could assist the operator in reassigning outbound flights to BUCs in response to malfunctions

Which Should Be Used First for ALK-Positive Non-Small-Cell Lung Cancer: Chemotherapy or Targeted Therapy? A Meta-Analysis of Five Randomized Trials

Background and objectives: Targeted therapy is widely used in the era of precision medicine. Whether the sequence in which targeted therapy and chemotherapy are performed matters, is however not known. We examined the impact of the sequential treatment of targeted therapy and chemotherapy among advanced anaplastic lymphoma kinase (ALK), non-small cell lung cancer (NSCLC) patients. Materials and Methods: Randomized controlled trials comparing the use of ALK inhibitors with chemotherapy were included in this meta-analysis. We estimated the hazard ratios (HRs) and 95% confidence intervals (CI), for progression-free survival (PFS) and overall survival (OS) from a random effects model. Two-sided statistical tests were used to determine the significance of these estimates. Results: In five eligible studies (1404 patients), ALK targeted therapy, in comparison with chemotherapy, had a significantly higher PFS (HR = 0.48; 95% CI, 0.42(-)0.55), but not significantly higher OS (HR = 0.88; 95% CI, 0.72(-)1.07). Crossover from chemotherapy to ALK inhibitors was allowed after progression in all trials. The sensitivity analysis of the use of ALK inhibitors as either the first- or second-line treatment, showed improvements in PFS but not in OS. Conclusions: Our results indicate that using targeted therapy first improved PFS, but that the sequence in which the treatments were performed did not cause a significant difference in overall survival