452 research outputs found
Use Classifier as Generator
Image recognition/classification is a widely studied problem, but its reverse
problem, image generation, has drawn much less attention until recently. But
the vast majority of current methods for image generation require
training/retraining a classifier and/or a generator with certain constraints,
which can be hard to achieve. In this paper, we propose a simple approach to
directly use a normally trained classifier to generate images. We evaluate our
method on MNIST and show that it produces recognizable results for human eyes
with limited quality with experiments
Frobenius height of prismatic cohomology with coefficients
We study the behavior of Frobenius operators on smooth proper pushforwards of
prismatic F-crystals. In particular we show that the i-th pushforward has its
Frobenius height increased by at most i. Our proof crucially uses the notion of
prismatic F-gauges introduced by Drinfeld and Bhatt--Lurie and its relative
version, and we give a self-contained treatment without using the stacky
formulation.Comment: 42 pages, comments welcom
N,N′-Bis(4-methylbenzylidene)benzene-1,4-diamine
The centrosymmetric title compound, C22H20N2, crystallizes with one half-molecule in the asymmetric unit. The dihedral angle between the central and outer benzene rings is 46.2 (2)°
Amazon Product Reviews Helpfulness Prediction
E-commerce business become successful by offering people convenient online experience as well as providing tens of thousands of crowd-sourced reviews that are written by customers and users about their experiences and opinions regarding the products or the services they paid for. For an online shopping website, such as Amazon.com, it is very important to recommend high-quality product reviews to the website users because customers make decisions based on what they read from the reviews. However, there are simply way too many reviews out there, and it would be a dreadful task for anyone to read them all. In this paper, we try to build a logistic regression model that can than predict helpfulness of reviews.Master of Science in Information Scienc
[1,1-(Butane-1,4-diyl)-2,3-dicyclohexylguanidinato]dimethylaluminum(III)
In the crystal structure of the title complex, [Al(CH3)2(C17H30N3)], the AlIII cation is coordinated by two methyl ligands and two N atoms from the guanidinato ligand in a distorted tetrahedral geometry. The dihedral angle between the CN2 and AlC2 planes is 85.37 (2)°. The two N atoms of the guanidinato ligand exhibit an almost uniform affinity to the metal atom
RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL
One of the recent best attempts at Text-to-SQL is the pre-trained language
model. Due to the structural property of the SQL queries, the seq2seq model
takes the responsibility of parsing both the schema items (i.e., tables and
columns) and the skeleton (i.e., SQL keywords). Such coupled targets increase
the difficulty of parsing the correct SQL queries especially when they involve
many schema items and logic operators. This paper proposes a ranking-enhanced
encoding and skeleton-aware decoding framework to decouple the schema linking
and the skeleton parsing. Specifically, for a seq2seq encoder-decode model, its
encoder is injected by the most relevant schema items instead of the whole
unordered ones, which could alleviate the schema linking effort during SQL
parsing, and its decoder first generates the skeleton and then the actual SQL
query, which could implicitly constrain the SQL parsing. We evaluate our
proposed framework on Spider and its three robustness variants: Spider-DK,
Spider-Syn, and Spider-Realistic. The experimental results show that our
framework delivers promising performance and robustness. Our code is available
at https://github.com/RUCKBReasoning/RESDSQL.Comment: Accepted to AAAI 2023 main conference (oral
EEG-EMG Analysis Method in Hybrid Brain Computer Interface for Hand Rehabilitation Training
Brain-computer interfaces (BCIs) have demonstrated immense potential in aiding stroke patients during their physical rehabilitation journey. By reshaping the neural circuits connecting the patient’s brain and limbs, these interfaces contribute to the restoration of motor functions, ultimately leading to a significant improvement in the patient’s overall quality of life. However, the current BCI primarily relies on Electroencephalogram (EEG) motor imagery (MI), which has relatively coarse recognition granularity and struggles to accurately recognize specific hand movements. To address this limitation, this paper proposes a hybrid BCI framework based on Electroencephalogram and Electromyography (EEG-EMG). The framework utilizes a combination of techniques: decoding EEG by using Graph Convolutional LSTM Networks (GCN-LSTM) to recognize the subject’s motion intention, and decoding EMG by using a convolutional neural network (CNN) to accurately identify hand movements. In EEG decoding, the correlation between channels is calculated using Standardized Permutation Mutual Information (SPMI), and the decoding process is further explained by analyzing the correlation matrix. In EMG decoding, experiments are conducted on two task paradigms, both achieving promising results. The proposed framework is validated using the publicly available WAL-EEG-GAL (Wearable interfaces for hand function recovery Electroencephalography Grasp-And-Lift) dataset, where the average classification accuracies of EEG and EMG are 0.892 and 0.954, respectively. This research aims to establish an efficient and user-friendly EEG-EMG hybrid BCI, thereby facilitating the hand rehabilitation training of stroke patients
Remodeling urban fitness trails to engaging and healthy public spaces for all
Unprecedented urban development has happened to China in the past several decades, generating countless skyscrapers and a much more compacted living environment for a majority of its people. During the same period, lifestyles changed accordingly. Physical inactivity, once an exotic term to most Chinese people, became one of the leading risk factors for mortality. To encourage more physical activities as a means to improve public health, the Chinese government proposed the National Fitness Program and put it into practice. One significant approach applied by the program is to build “fitness trails” in available public spaces for nearby residents. However, these trails, consisting a limited amount of exercise equipment, are often obsolete and abandoned places risking the health and safety of nearby residents. This leaves us a big challenge in planning and design. To what extent can we use research, knowledge, and systematic design thinking from landscape architecture to flip existing fitness trails over into engaging health enhancements for the wellbeing of all?
This thesis examined current conditions of 30 different urban fitness trails in the city of Guangzhou and conducted an in-depth analysis of two typical urban fitness trail cases in Liuyun community. By research and analysis, a set of design guidelines was created and prepared for future practices. In response to design strategies provided, a comprehensive fitness trail design in Liuyun community was made for illustration.
Through investigation, it is apparent that many of the urban fitness trails were unwisely built in locations and poorly considered in design components. By a more inclusive understanding of health, various health-promoting factors including mental health, social wellbeing, and healthy food were brought into design rather than physical activity only. In the illustrative design chapter, constructive design ideas and solutions were made and explained, with hope to set up the stage for related practitioners
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