Miracle-dz/UniFAR-FTUs huggingface dataset:
Leveraging Sub-class Discimination for Compositional Zero-Shot Learning

Compositional Zero-Shot Learning (CZSL) aims at identifying unseen compositions composed of previously seen attributes and objects during the test phase. In real images, the visual appearances of attributes and objects (primitive concepts) generally interact with each other. Namely, the visual appearances of an attribute may change when composed with different objects, and vice versa. But previous works overlook this important property. In this paper, we introduce a simple yet effective approach with leveraging sub-class discrimination. Specifically, we define the primitive concepts in different compositions as sub-classes, and then maintain the sub-class discrimination to address the above challenge. More specifically, inspired by the observation that the composed recognition models could account for the differences across sub-classes, we first propose to impose the embedding alignment between the composed and disentangled recognition to incorporate sub-class discrimination at the feature level. Then we develop the prototype modulator networks to adjust the class prototypes w.r. t. the composition information, which can enhance sub-class discrimination at the classifier level. We conduct extensive experiments on the challenging benchmark datasets, and the considerable performance improvement over state-of-the-art approaches is achieved, which indicates the effectiveness of our method. Our code is available at https://github.com/hxm97/SCD-CZSL.
Postharvest Preservation of Flammulina velutipes with Isoamyl Isothiocyanate

Flammulina velutipes was treated with 10, 50, and 250 μL L−1 isoamyl isothiocyanate (IAITC), and effects on quality preservation were assessed. IAITC displayed positive effects during the storage of F. velutipes: (i) maintained tissue integrity, reduced weight loss rates; (ii) reduced browning degree by inhibiting the activities of browning-related enzymes; (iii) enhanced activities of two antioxidant enzymes (superoxide dismutase and catalase) and increased ascorbic acid content; (iv) ameliorated microbial spoilage by inhibiting bacterial growth, especially Serratia, a major bacterial community on the surface of F. velutipes; (v) enhanced chitin content and thereby maintained structural integrity; and (vi) maintained levels of Asp, Glu, linoleic acid, and polyunsaturated fatty acids. In conclusion, IAITC reduced catalase activity and total phenolic content in F. velutipes during storage. The most suitable concentration of IAITC in the preservation of F. velutipes was 50 µL L−1.
Directly Connected Linear Antenna Array With Band-Notch Characteristics for UWB Applications

This letter proposes a directly connected linear antenna array for ultrawideband applications. First, a wideband antenna element based on multimode resonances is proposed. To facilitate direct connection for small array sizes, the mutual coupling between adjacent elements is reduced. Additionally, an extra slot mode is introduced to achieve both band notch property and antenna miniaturization simultaneously. To combat the edge effect of this antenna array, only slight geometry adjustments of periphery elements are required. Finally, to verify the proposed concept, a 1 × 4 array prototype is fabricated and measured. The experimental results are consistent with the simulation ones, obtaining a wide bandwidth of 117% and gain over 10 dBi. Additionally, a band notch at 3.5 GHz with a gain drop to −3.7 dBi is realized.
On a Fuzzy Completely Closed Filter with Respect of Element in a BH-algebra

In this paper, we introduce a new notion that we call a fuzzy completely closed filter with respect of an element in a BH-algebra, and we link this notion with notions filter and ideal of BH- algebra, We give some properties of fuzzy completely closed filter with respect of an element and we study properties of it.
Study on the Effect of the Impact Location and the Type of Hammer Tip on the Frequency Response Function (FRF) in Experimental Modal Analysis of Rectangular Plates

In this work effect of the impact location and the type of hammer tip on the frequency response function (FRF) is studied. Experimental modal analysis of rectangular plates is carried out for this purpose by using impact hammer, accelerometer and fast Fourier transform (FFT) analyzer. It is observed that the impulse hammer hit location has, no effect on the eigenfrequency, yet a difference in amplitude of the eigenfrequencies is obtained. The effect of the hammer tip on the pulse and the force spectrum is studied for three types of tips metal, plastic and rubber. A solid rectangular plate was excited by using these tips one by one in three different tests. It is observed that for present experimental set up plastic tip excites the useful frequency range.
Physiological Signal Analysis and Stress Classification from VR Simulations Using Decision Tree Methods

Stress is induced in response to any mental, physical or emotional change associated with our daily experiences. While short term stress can be quite beneficial, prolonged stress is detrimental to the heart, muscle tissues and immune system. In order to be proactive against these symptoms, it is important to assess the impact of stress due to various activities, which is initially determined through the change in the sympathetic (SNS) and parasympathetic (PNS) nervous systems. After acquiring physiological data wirelessly through captive electrocardiogram (ECG), galvanic skin response (GSR) and respiration (RESP) sensors, 21 time, frequency, nonlinear, GSR and respiration features were manually extracted from 15 subjects ensuing a baseline phase, virtual reality (VR) roller coaster simulation, color Stroop task and VR Bubble Bloom game. This paper presents a comprehensive physiological analysis of stress from an experiment involving a VR video game Bubble Bloom to manage stress levels. A personalized classification and regression tree (CART) model was developed using a novel Gini index algorithm in order to effectively classify binary classes of stress. A novel K-means feature was derived from 11 other features and used as an input in the Decision Tree (DT) algorithm, strong learners Ensemble Gradient Boosting (EGB) and Extreme Gradient Boosting (XGBoost (XGB)) embedded in a pipeline to classify 5 classes of stress. Results obtained indicate that heart rate (HR), approximate entropy (ApEN), low frequency and high frequency ratio (LF/HF), low frequency (LF), standard deviation (SD1), GSR and RESP all reduced and high frequency (HF) increased following the VR Bubble Bloom game phase. The personalized CART model was able to classify binary stress with 87.75% accuracy. It proved to be more effective than other related studies. EGB was able to classify binary stress with 100% accuracy, which outperformed every other related study. XGBoost and DT were able to classify five classes of stress with 72.22% using the novel K-means feature. This feature produced less error and better model performance in comparison to using all the features. Results substantiate that our proposed methods were more effective for stress classification than most related studies.
OBTENÇÃO E APLICAÇÃO DE CURVAS DE CARGA REPRESENTATIVAS UTILIZANDO CLUSTERIZAÇÃO OU CADEIA DE MARKOV

E de grande importância que as concessionarias de energia eletrica tenham conhecimento do comportamento de seus consumidores com relacao ao consumo de energia para a realizacao de diversos estudos. Tal comportamento pode ser representado por curvas de carga. Baseado nisso, neste trabalho sao apresentadas duas formas para se obter curvas representativas, uma atraves do metodo de clusterizacao Modified Follow the Leader porem considerando as curvas divididas em patamares e outro atraves da geracao de curvas sinteticas aplicando cadeia de Markov. Ambos os metodos sao aplicados a partir de um conjunto de medicoes relativas a um processo de revisao tarifaria de uma concessionaria brasileira. Os resultados obtidos demonstram que nto os clusters quanto as curvas sinteticas podem ser utilizadas como curvas de carga representativas para reproduzir o comportamento de diferentes tipos de consumidores.
Single-Channel Speech Dereverberation in Noisy Environment for Non-Orthogonal Signals

∗ c ©2018 S. Hirzel Verlag/European Acoustics Association. Published in Acta Acustica united with Acustica, Volume 104, Number 6. This is authors’ post-print version, the definitive publisher-authenticated version is available online at http://www.ingentaconnect. com/content/dav/aaua. The readers must contact the publisher for reprint or permission to use the material in any form. DOI: https://doi.org/10.3813/AAA.919270 phenomenon of reverberation reduces speech intel37 ligibility and degrades the performance of hearing 38 aids and automatic speech recognition (ASR) sys39 tems [1, 2]. The resulted speech distortion can be 40 contributed by two distinct components of reverber41 ation the early reflections which cause coloration of 42 speech, and the late reflections that contribute to echo 43 and other significant distortions. While both types of 44 reverberation components cause speech deformation, 45 it is the latter one that is found to be more detri46 mental in practice [3, 4]. In real environments, rever47 beration is often accompanied with background noise. 48 Thus it is important to perform speech dereverbera49 tion and noise suppression at the same time. In our 50 current work, we design a combined speech derever51 beration and noise suppression system using a modi52 fied spectral subtraction (SS) method to address the 53 non-orthogonality between the signal components and 54 evaluated and compared the performance with other 55 conventional and contemporary methods. 56
COVID-19 and the adoption of digital marketing by micro and small enterprises in Nigeria

This study aims to analyze digital marketing adoption among micro and small enterprises (MSEs) operating in Lagos State, Nigeria. This state was chosen because it was the worst hit by the COVID-19 pandemic regarding the reported number of infections and it has a large concentration of MSEs. There is no doubt that the COVID-19 pandemic brought changes to how businesses operate. It succeeded in pushing business owners into adopting new business strategies, all in the bid to adapt to the reality of the pandemic and the associated changes. The cross-sectional survey design was adopted; data were collected through an online survey of 240 MSEs operating in Lagos State. The results show no substantial increase in digital marketing adoption during the pandemic relative to the pre-pandemic era. The findings, however, reveal that digital marketing use differed significantly according to sector and size before and during the pandemic. No changes were found in digital marketing adoption in the information technology and finance sectors, while a decline in digital marketing adoption was reported in the hospitality sector. On the other hand, there was a rise in the use of digital marketing during the pandemic in the agriculture and manufacturing sectors. These findings provide an empirical managerial perspective establishing the link between reality and theoretical business underpinnings.
On the solution of the fuzzy c-means model

In this paper, we study the properties of the solution of the standard fuzzy c-means (FCM) algorithm, and show that a fuzzy partition including a W-universium is not a solution of FCM. Hence, this paper gives a new explanation that some cluster invalidity index can work for FCM, and provides evidence that the definition of fuzzy partition proposed in is reasonable. Moreover, one conjecture on the solution of FCM is proposed.
A Continual Pre-training Approach to Tele-Triaging Pregnant Women in Kenya

Access to high-quality maternal health care services is limited in Kenya, which resulted in ∼36,000 maternal and neonatal deaths in 2018. To tackle this challenge, Jacaranda Health (a non-profit organization working on maternal health in Kenya) developed PROMPTS, an SMS based tele-triage system for pregnant and puerperal women, which has more than 350,000 active users in Kenya. PROMPTS empowers pregnant women living far away from doctors and hospitals to send SMS messages to get quick answers (through human helpdesk agents) to questions about their medical symptoms and pregnancy status. Unfortunately, ∼1.1 million SMS messages are received by PROMPTS every month, which makes it challenging for helpdesk agents to ensure that these messages can be interpreted correctly and evaluated by their level of emergency to ensure timely responses and/or treatments for women in need. This paper reports on a collaborative effort with Jacaranda Health to develop a state-of-the-art natural language processing (NLP) framework, TRIM-AI (TRIage for Mothers using AI), which can automatically predict the emergency level (or severity of medical condition) of a pregnant mother based on the content of their SMS messages. TRIM-AI leverages recent advances in multi-lingual pre-training and continual pre-training to tackle code-mixed SMS messages (between English and Swahili), and achieves a weighted F1 score of 0.774 on real-world datasets. TRIM-AI has been successfully deployed in the field since June 2022, and is being used by Jacaranda Health to prioritize the provision of services and care to pregnant women with the most critical medical conditions. Our preliminary A/B tests in the field show that TRIM-AI is ∼17% more accurate at predicting high-risk medical conditions from SMS messages sent by pregnant Kenyan mothers, which reduces the helpdesk’s workload by ∼12%.
Kajibuntan: A House Chore Division App

Couples often encounter the challenge of sharing house chores. This raises the fundamental question of how to divide chores. In this paper, we present a new application for a fair division of household chores. Our platform, called Kajibuntan, allows couples to specify the set of chores to be shared, their preferences over them, and the current allocation. Our tool visualizes the current allocation and makes proposals according to their preferences based on the theory of fair division. The goal of our tool is to provide a systematic and transparent system to divide household chores and help creating harmony in the home.
Generalised nonlinear stability of stratified shear flows: adjoint-based optimisation, Koopman modes, and reduced models

In this thesis I investigate a number of problems in the nonlinear stability of density stratified plane Couette flow. I begin by describing the history of transient growth phenomena, and in particular the recent application of adjoint based optimisation to find nonlinear optimal perturbations and associated minimal seeds for turbulence, the smallest amplitude perturbations that are able to trigger transition to turbulence. I extend the work of Rabin et al. (2012) in unstratified plane Couette flow to find minimal seeds in both vertically and horizontally sheared stratified plane Couette flow. I find that the coherent states visited by such minimal seed trajectories are significantly altered by the stratification, and so proceed to investigate these states both with generalised Koopman mode analysis and by stratifying the self-sustaining process described by Waleffe (1997). I conclude with an introductory problem I considered that investigates the linear Taylor instability of layered stratified plane Couette flow, and show that the nonlinear evolution of the primary Taylor instability is not coupled to the form of the linearly unstable mode, in contrast to the Kelvin–Helmholtz instability, for example. I also include an appendix in which I describe joint work conducted with Professor Neil Balmforth of UBC during the 2015 WHOI Geophysical Fluid Dynamics summer programme, investigating stochastic homoclinic bifurcations. This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. Chapter 3 is a modification of Eaves & Caulfield (2015), and a version of Chapter 7 is submitted to the Journal of Fluid Mechanics by the same authors. The contents of Chapter 4 will be included in a manuscript co-authored with C. Caulfield and I. Mezić. The appendix contains joint work with N. Balmforth and appears in Eaves & Balmforth (2016). No parts of this dissertation have been submitted for any other qualification. Thomas Eaves 19th April 2016 Between the successful defence of this thesis on 10th June 2016 and the submission of the final hard-bound version in July 2016, the contents of Chapter 4 are included in a manuscript submitted to Nature co-authored with C. Caulfield and I. Mezić, and the contents of Chapter 5 are included in a manuscript submitted to the Journal of Fluid Mechanics co-authored with C. Caulfield. Thomas Eaves 1st July 2016
Real-Time Wind Sensing With Massively Parallel Sample Processing

Light detection and ranging (LiDAR)-based wind monitoring has significant implications in various fields, including aviation and wind energy. Accurate and real-time wind speed measurement is crucial for the safety and the performance of these applications. This letter presents an field programmable gate arrays-based real-time wind LiDAR system. The proposed solution incorporates a massively parallel sample processing architecture that uses 16 parallel fast Fourier transform units and 256 unique spatial measurement ranges. A real-time noise suppression averaging technique is implemented to further reduce processing overhead. Field experiments highlight the superiority of the presented solution against state-of-the-art wind LiDARs, as it achieves better error floor (5%), better spatial resolution (49%), and very low processing latency (120 ms).
Korean Restaurants’ Consumer Needs Based on Marketing Mix Through the Kano Model

A proliferation of Korean restaurants in Yogyakarta can be seen over the past few years, each with its unique concept. However, a survey on Google Star Rating suggests that not all of these restaurants are sustainable. The significant discrepancy between expectations and actual satisfaction of consumers is likely a contributing factor. Moreover, intense competition exists between these restaurants. This study aims to identify which aspects of marketing—such as product, price, place, promotion, people, process, and physical evidence—influence Korean restaurants’ consumer needs. Using the Kano model, consumer satisfaction was analyzed by classifying consumer needs into attractive, must-be, one-dimensional, indifferent, reverse, or questionable categories. Purposive and snowball sampling methods were employed to select 100 respondents to complete a questionnaire. The results unveiled that four of the seven marketing mix attributes needed by Korean restaurants’ consumers fell into the one-dimensional category. The features consisted of physical evidence (clean dining room), people (clean and tidy employee appearance), product (good taste), and process (timely service). Furthermore, the attributes of unique offers (D1); fast service (F2); menu information, ingredients, how to cook it (E3); and affordable food prices (B1) contributed to greater consumer satisfaction. These attributes boosted consumer satisfaction by 80%, 79.8%, 74.5%, and 73.7%, respectively.
Human-aware Beamforming Method Based on Electromagnetic Field Strength Estimation

This study proposes a beamforming (BF) method to maximise the received power at the receiver (Rx) in microwave wireless power transfer (MWPT) under the constraint that the human exposure power is maintained below a standard value. The proposed method first estimates the electromagnetic field strength (EMFS) of a human based on a combination of i) equivalent channel estimation between the human and transmitter and ii) human localisation using the same frequency as that of MWPT. Subsequently, a convex optimisation problem was formulated to maximise the received power of the Rx under the constraint that the estimated EMFS on the human must be maintained below the standard value. Solving this problem enables the determination of the optimum BF weight that enables null steering by considering the human area, suppression of human exposure, and high transfer efficiency. The results of full- wave simulations show that the ratio of the received power to the human exposure power of the proposed method is 5.11 dB higher than that of the conventional method, with maximum transfer efficiency that does not consider human exposure, enabling both high transfer efficiency and human avoidance. Furthermore, it is shown that if the angle between the receiver and the human is equal to or greater than 20°, it is possible to suppress human exposure below the standard value in the human body area while maintaining high transfer efficiency.
Characterizing full matrix constants of piezoelectric single crystals with strong anisotropy using two samples

Although the self-consistency of the full matrix material constants of a piezoelectric sample obtained by the resonant ultrasonic spectroscopy technique can be guaranteed because all constants come from the same sample, it is a great challenge to determine the constants of a piezoelectric sample with strong anisotropy because it might not be possible to identify enough resonance modes from the resonance spectrum. To overcome this difficulty, we developed a strategy to use two samples of similar geometries to increase the number of easy identifiable modes. Unlike the IEEE resonance methods, sample-to-sample variation here is negligible because the two samples have almost the same dimensions, cut from the same specimen and poled under the same conditions. Using this method, we have measured the full matrix constants of a [011]c poled 0.71Pb(Mg1/3Nb2/3)O3-0.29PbTiO3 single crystal, which has 17 independent constants. The self-consistency of the obtained results is checked by comparing the calculated elastic .
Rectal Bioavailability of Amoxicillin from Hollow-Type Suppositories: Effect of Chemical Form of Amoxicillin

Rectal drug administration could offer advantages in the delivery of medicines for children by avoiding swallowability issues, improving stability and enabling administration by caregivers. This study aimed to evaluate the rectal bioavailability of hollow-type suppositories (HTS) and understand the effect of two chemical forms of amoxicillin: amoxicillin sodium (AS) or amoxicillin trihydrate (AMT). HTS were prepared by incorporating a lipophilic core containing the antibiotic with a polyethylene glycol (PEG) shell. Formulations were characterised in vitro, and the absolute bioavailability was determined in a rabbit model, while drug–base interactions were evaluated using X-ray diffraction crystallography (XRD), differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy. The in vitro amoxicillin release from AMT HTS was delayed, taking 27.3 ± 4.9 h to release 50% drug compared with 1.7 h for the AS HTS, likely due to solubility differences between AMT and AS. The presence of orthorhombic AMT and anhydrous AS crystals in respective HTS was confirmed via XRD and DSC. PEG shells were able to protect the drug chemical stability when stored at 25 °C/60% RH. Despite the difference in their in vitro release rates, a similar rectal bioavailability was found in both forms of amoxicillin (absolute bioavailability 68.2 ± 6.6% vs. 72.8 ± 32.2% for AMT HTS and AS HTS, respectively; p = 0.9682). Both HTS formulations showed little or no irritation to the rectal mucosa following a single dose.