Rare but Severe Neural Machine Translation Errors Induced by Minimal Deletion: An Empirical Study on Chinese and English

We examine the inducement of rare but severe errors in English-Chinese and Chinese-English in-domain neural machine translation by minimal deletion of the source text with character-based models. By deleting a single character, we can induce severe translation errors. We categorize these errors and compare the results of deleting single characters and single words. We also examine the effect of training data size on the number and types of pathological cases induced by these minimal perturbations, finding significant variation. We find that deleting a word hurts overall translation score more than deleting a character, but certain errors are more likely to occur when deleting characters, with language direction also influencing the effect.Comment: COLING 2022 Camera Read

Crowd-Sourced Mobility Mapping for Location Tracking Using Unlabeled Wi-Fi Simultaneous Localization and Mapping

Due to the increasing requirements of the seamless and round-the-clock Location-based services (LBSs), a growing interest in Wi-Fi network aided location tracking is witnessed in the past decade. One of the significant problems of the conventional Wi-Fi location tracking approaches based on received signal strength (RSS) fingerprinting is the time-consuming and labor intensive work involved in location fingerprint calibration. To solve this problem, a novel unlabeled Wi-Fi simultaneous localization and mapping (SLAM) approach is developed to avoid the location fingerprinting and additional inertial or vision sensors. In this approach, an unlabeled mobility map of the coverage area is first constructed by using the crowd-sourcing from a batch of sporadically recorded Wi-Fi RSS sequences based on the spectral cluster assembling. Then, the sequence alignment algorithm is applied to conduct location tracking and mobility map updating. Finally, the effectiveness of this approach is verified by the extensive experiments carried out in a campus-wide area

The primary controlling factors of the occurrence state of deep high-rank coalbed methane in eastern Ordos Basin

Introduction: This study investigates the key controlling factors of the occurrence state of deep coalbed methane (CBM). CBM is an abundant energy resource in China, particularly in deep coal seams. However, the exploration and development of deep CBM face numerous challenges, and the understanding of the controlling factors of its occurrence state is still limited.Methods: The study reveals that deep CBM primarily exists in the form of adsorbed gas and free gas within the pore-fracture system of coal. Factors such as formation temperature, formation pressure, pore structure, and water saturation collectively influence the occurrence state of deep CBM. By employing the Simplified Local Density (SLD) model and molecular simulation methods.Results and discussion: This study examines the impact of two external geological control factors (formation temperature, formation pressure) and three internal geological control factors (pore size, water saturation, Specific surface area) on deep CBM and establishes a theoretical model for gas content. Finally, the relationship between the adsorbed gas, free gas, total gas content, and burial depth is calculated using the model, uncovering the primary factors controlling the occurrence state of deep CBM. This research is of significant importance in providing key parameters for gas content in deep coal and optimizing deep CBM exploration

Personal Mobility Map Construction for Crowd-Sourced Wi-Fi Based Indoor Mapping

This letter addresses the problem of wireless indoor positioning and proposes the concept of personal mobility map (PMM). As a graph describing an individual's typical mobility pattern over a physical or abstract space, PMM can be used as the building block for crowd-sourcing based simultaneous localization and mapping (SLAM). PMM can also enable new kinds of location-based services (LBSs). To construct a PMM, we conduct intra-sequence clustering on the sequences of Wi-Fi received signal strength (RSS) measurements to cluster the measurements into different location points (LPs), followed by personal intersequence LP assembling, which aligns these LPs with the concept of the Smith-Waterman algorithm originally used for protein sequencing. Experiments with Wi-Fi RSS measurements collected in the university campus prove that the PMM performs well in indoor mapping and path estimation

Monitoring hypoxia induced changes in cochlear blood flow and hemoglobin concentration using a combined dual-wavelength laser speckle contrast imaging and Doppler optical microangiography system.

A synchronized dual-wavelength laser speckle contrast imaging (DWLSCI) system and a Doppler optical microangiography (DOMAG) system was developed to determine several ischemic parameters in the cochlea due to a systemic hypoxic challenge. DWLSCI can obtain two-dimensional data, and was used to determine the relative changes in cochlear blood flow, and change in the concentrations of oxyhemoglobin (HbO), deoxyhemoglobin (Hb) and total hemoglobin (HbT) in mice. DOMAG can obtain three-dimensional data, and was used to determine the changes in cochlear blood flow with single vessel resolution. It was demonstrated that during a hypoxic challenge there was an increase in the concentrations of Hb, a decrease in the concentrations of HbO and cochlear blood flow, and a slight decrease in the concentration of HbT. Also, the rate of change in the concentrations of Hb and HbO was quantified during and after the hypoxic challenge. The ability to simultaneously measure these ischemic parameters with high spatio-temporal resolution will allow the detailed quantitative analysis of several hearing disorders, and will be useful for diagnosing and developing treatments