Wave-packet treatment of neutrino oscillations and its implications on determining the neutrino mass hierarchy

We derive the neutrino flavor transition probabilities with the neutrino treated as a wave packet. The decoherence and dispersion effects from the wave-packet treatment show up as damping and phase-shifting of the plane-wave neutrino oscillation patterns. If the energy uncertainty in the initial neutrino wave packet is larger than around 0.01 of the neutrino energy, the decoherence and dispersion effects would degrade the sensitivity of reactor neutrino experiments to mass hierarchy measurement to lower than 3 $\sigma$ confidence level

Multichannel filters for speech recognition using a particle swarm optimization

Speech recognition has been used in various real-world applications such as automotive control, electronic toys, electronic appliances etc. In many applications involved speech control functions, a commercial speech recognizer is used to identify the speech commands voiced out by the users and the recognized command is used to perform appropriate operations. However, users’ commands are often corrupted by surrounding ambient noise. It decreases the effectiveness of speech recognition in order to implement the commands accurately. This paper proposes a multichannel filter to enhance noisy speech commands, in order to improve accuracy of commercial speech recognizers which work under noisy environment. An innovative particle swarm optimization (PSO) is proposed to optimize the parameters of the multichannel filter which intends to improve accuracy of the commercial speech recognizer working under noisy environment. The effectiveness of the multichannel filter was evaluated by interacting with a commercial speech recognizer, which was worked in a warehouse

TOM: Why Isn’t Price Enough?

In an efficient market, differences in quality should be fully reflected in differences in price. This paper examines a highly active residential property market and verifies whether housing attributes can explain time on the market (TOM) in addition to prices. In contrast to the previous literature, only the price ratio and inflation factor are found to be critical in affecting TOM. An interpretation of the results is suggested, along with some directions for future research.TOM, price ratio, inflation factor, physical attribute, time aggregation

Is Nostalgia Still the Key to Nostalgic Consumption in the Market of Young Consumers? Explore the roles of nostalgia in the case of Lomography cameras.

Abstract Research Purpose: Recently, the increasing awareness in nostalgia has produced an empirical foundation towards the understanding of nostalgia in human lives and its potential implication towards marketing strategies. However, such studies were neglected on the area of young consumers with qualitative research, where nostalgia does no merely happen on older generation. In fact, contemporary nostalgic consumption involved a variety of factors other than just demographic; for instance, past experience, word of mouth and identity. The purpose of this present research is to explore and clarify the roles of nostalgia and the motivations of nostalgic consumption by young consumers in a greater depth, in particular on the case of Lomography cameras. Also, the research offers useful insights for potential directions of marketing implications and future research. Methodology: In order to answer the research questions in-depth, qualitative method was employed. In addition, purposive and snowball sampling were applied to identify participants with similar characteristics, consumption experiences and age. As a result, 11 semi-structured interviews were conducted. Main Findings: The findings demonstrated that within the younger buyers, nostalgia has little impact on their decisions of nostalgic consumption due to their limited knowledge and experiences of the past. Besides, participants seem to have different motivations and symbolic meanings when carrying out this consumption. Consequently, this research discovered 8 recurring themes that may have influenced the nostalgic consumptions: impression of nostalgic products and brands, brand images, product designs, product functions, gift giving, the influences of visual media, self-identity and social identity. Specifically, the high consistency of product designs and identities are regarded as the most important factors for young consumers, where word of mouth reinforced their purchase intentions

Spot Focusing Coma Correction by Linearly Polarized Dual-Transmitarray Antenna in the Terahertz Region

Focus scanning is critically important in many terahertz (THz) imaging and sensing applications. A traditional single focusing transmitarray can achieve a good focus when the source is on-axis but moving the source off-axis produces a significant aberration. This paper presents a novel approach to reducing coma in off-axis scanning in the THz region. Here, a dual transmitarray solution is proposed, in which a transmitarray with an optimized phase profile is placed behind a regular phase profile transmitarray. A linearly polarized, dual-transmitarray antenna was fabricated for validation, and the focusing performances were experimentally characterized. The measured results are in good agreement with the theoretical ones. The generated spot of the dual-transmitarray antenna remains focused on an angle up to 50deg, with a -3 dB spot size of less than 4 mm at 290 GHz. The measured near-field sidelobes are all below -10 dB within the whole scanning range.Comment: 9 pages, 14 figure

Speech Enhancement Strategy for Speech Recognition Microcontroller under Noisy Environments

Industrial automation with speech control functions is generally installed with a speech recognition sensor which is used as an interface for users to articulate speech commands. However, recognition errors are likely to be produced when background noise surrounds the command spoken into the speech recognition microcontrollers. In this paper, a speech enhancement strategy is proposed to develop noise suppression filters in order to improve the accuracy of speech recognition microcontrollers. It uses a universal estimator, namely a neural network, to enhance the recognition accuracy of microcontrollers by integrating better signals processed by various noise suppression filters, where a global optimization algorithm, namely an intelligent particle swarm optimization, is used to optimize the inbuilt parameters of the neural network in order to maximize accuracy of speech recognition microcontrollers working within noisy environments. The proposed approach overcomes the limitations of the existing noise suppression filters intended to improve recognition accuracy. The performance of the proposed approach was evaluated by a speech recognition microcontroller, which is used in electronic products with speech control functions. Results show that the accuracy of the speech recognition microcontroller can be improved using the proposed approach, when working under low signal to noise ratio conditions in the industrial environments of automobile engines and factory machines

A decision-directed adaptive gain equalizer for assistive hearing instruments

Assistive hearing instruments have a significant impact on speech enhancement when the signal-to-noise ratio is low. These instruments are usually developed using the conventional adaptive gain equalizer (AGE), which has low computational complexity and low distortion in real-time speech enhancement. The conventional AGEs are intended to boost the speech segments of speech signals but they are incapable of suppressing noise segments. The overall speech quality of the assistive hearing instruments may be reduced, as the noise segments still cannot be filtered out. In this paper, a decision-directed AGE is proposed for assistive hearing instruments. It aims to overcome the limitation of the conventional AGE, which is capable only of boosting speech segments in noisy speech but incapable of suppressing noise segments. The proposed approach simultaneously boosts the speech segments and suppresses noise segments in noisy speech. Experimental results with different types of real-world noise indicate that the proposed method achieves better speech quality than does the conventional AGE. The resulting method provides an improved functionality for assistive hearing instruments

Discontinuous Predicates as Partial Deletion in Cantonese

Providing novel evidence from discontinuous predicates in Cantonese, this paper argues that partial deletion applies to the word level. A number of disyllabic verbs in Cantonese may appear as discontinuous strings where the two syllables are separated by suffixes and/or phrasal elements. We propose that their derivation involves a conspiracy of multiple operations in Narrow Syntax and in the Phonological Form (PF): (i) verb movement in Narrow Syntax creates copies; (ii) affixes induce a PF syllable deletion rule on the higher copy; (iii) partial Copy Deletion applies to the lower copy. Consequently, partial deletion not only applies to phrasal constituents (Fanselow and Cavar 2002), but also to words/heads. We also maintain a relatively conservative understanding of Copy Deletion by scattering the deletion to a PF deletion rule and Copy Deletion, where the partial effect is due to disruption of the latter by the former

Speech recognition enhancement using beamforming and a genetic algorithm

This paper proposes a genetic algorithm (GA) based beamformer to optimize speech recognition accuracy for a pretrained speech recognizer. The proposed beamformer is designed to tackle the non-differentiable and non-linear natures of speech recognition by employing the GA algorithm to search for the optimal beamformer weights. Specifically, a population of beamformer weights is reproduced by crossover and mutation until the optimal beamformer weights are obtained. Results show that the speech recognition accuracies can be greatly improved even in noisy environments