Towards Realistic Unsupervised Fine-tuning with CLIP

The emergence of vision-language models (VLMs), such as CLIP, has spurred a significant research effort towards their application for downstream supervised learning tasks. Although some previous studies have explored the unsupervised fine-tuning of CLIP, they often rely on prior knowledge in the form of class names associated with ground truth labels. In this paper, we delve into a realistic unsupervised fine-tuning scenario by assuming that the unlabeled data might contain out-of-distribution samples from unknown classes. Furthermore, we emphasize the importance of simultaneously enhancing out-of-distribution detection capabilities alongside the recognition of instances associated with predefined class labels. To tackle this problem, we present a simple, efficient, and effective fine-tuning approach called Universal Entropy Optimization (UEO). UEO leverages sample-level confidence to approximately minimize the conditional entropy of confident instances and maximize the marginal entropy of less confident instances. Apart from optimizing the textual prompts, UEO also incorporates optimization of channel-wise affine transformations within the visual branch of CLIP. Through extensive experiments conducted across 15 domains and 4 different types of prior knowledge, we demonstrate that UEO surpasses baseline methods in terms of both generalization and out-of-distribution detection

Improving Zero-Shot Generalization for CLIP with Synthesized Prompts

With the growing interest in pretrained vision-language models like CLIP, recent research has focused on adapting these models to downstream tasks. Despite achieving promising results, most existing methods require labeled data for all classes, which may not hold in real-world applications due to the long tail and Zipf's law. For example, some classes may lack labeled data entirely, such as emerging concepts. To address this problem, we propose a plug-and-play generative approach called \textbf{S}ynt\textbf{H}es\textbf{I}zed \textbf{P}rompts~(\textbf{SHIP}) to improve existing fine-tuning methods. Specifically, we follow variational autoencoders to introduce a generator that reconstructs the visual features by inputting the synthesized prompts and the corresponding class names to the textual encoder of CLIP. In this manner, we easily obtain the synthesized features for the remaining label-only classes. Thereafter, we fine-tune CLIP with off-the-shelf methods by combining labeled and synthesized features. Extensive experiments on base-to-new generalization, cross-dataset transfer learning, and generalized zero-shot learning demonstrate the superiority of our approach. The code is available at \url{https://github.com/mrflogs/SHIP}.Comment: Accepted by ICCV 202

Research Hotspot and Trend Analysis of China’s Elderlyoriented Smart Products

The Chinese government attaches great importance to the current situation of population aging, so it has introduced relevant aging policies. The combination of new technologies has played a positive role in the development of Elderly-oriented smart products of enterprises. Based on the research literature on Elderly-oriented smart products collected in CNKI database in recent ten years (2012-2022), this paper makes a quantitative analysis on the research results of Elderly-oriented smart products in China with the help of CiteSpace visual analysis software. Through research hotspots and evolution trends, it is found that the theme can be extended: the upgrading and construction of Elderly-oriented smart products will be a hot research topic in the academic community in the future

Population genetics of the malaria vector Anopheles aconitus in China and Southeast Asia

Anopheles aconitus is a well-known vector of malaria and is broadly distributed in the Oriental Region, yet there is no information on its population genetic characteristics. In this study, the genetic differentiation among populations was examined using 140 mtDNA COII sequences from 21 sites throughout southern China, Myanmar, Vietnam, Thailand, Laos and Sri Lanka. The population in Sri Lanka has characteristic rDNA D3 and ITS2, mtDNA COII and ND5 haplotypes, and may be considered a distinct subspecies. Clear genetic structure was observed with highly significant genetic variation present among population groups in Southeast Asia. The greatest genetic diversity exists in Yunnan and Myanmar population groups. All population groups are significantly different from one another in pairwise Fst values, except northern Thailand with central Thailand. Mismatch distributions and extremely significant F(s) values suggest that the populations passed through a recent demographic expansion. These patterns are discussed in relation to the likely biogeographic history of the region and compared to other Anopheles species

Modelling and control of an HVAC system

Heating, ventilation and air conditioning (HVAC) system is playing an important role in the design of medium to large industrial and office buildings. HVAC system is focused on regulating the temperature of the room, humidity, air flow and ensuring such elements remain within their acceptable range. Among varieties of HVAC systems, liquid desiccant dehumidification system (LDDS) has better effect on the control of the temperature and humidity with high energy efficiency.Bachelor of Engineerin

Modelling and control of the doubly-fed induction generator

Currently, mankind is faced with two pressing issues about energy and environment, therefore the use of renewable, green energy-wind energy, hydropower and solar energy as an important clean alternative energy is extensively spread which has a great significant effect over the world in recent years. Among these renewable energies, the unique advantages of wind energy draw much attention from scholars of various countries. Wind power technology has become a hot research topic. And the research about the control of wind power systems has become a hot topic. In this regard, people in the world are devoted to develop the technical innovation. Among all these technologies, wind power system of variable speed fixed frequency is most widely used, especially in the use of wound asynchronous motor as doubly-fed machine. Based on this system, the back-to-back AC frequency converter is controlled by the control system to realize the utilization of maximum wind power in the wind energy conversion system with doubly-fed induction generator. In this dissertation, the current development situation of wind power generation and dual-PWM converters is introduced. Then a brief analysis of the basic principles of wind power generation system is discussed. To control the doubly-fed induction generator, the PWM converters are analysed. And the proper control method is chosen. Finally, in the Matlab/Simulink platform for the software simulation, and simulation results verify the rotor side converter can achieve decoupling of P and Q; grid side converter can achieve unity power factor rectifier and DC side voltage stability functions.Master of Science (Power Engineering

Research Hotspot and Trend Analysis of China’s Elderlyoriented Smart Products

The Chinese government attaches great importance to the current situation of population aging, so it has introduced relevant aging policies. The combination of new technologies has played a positive role in the development of Elderly-oriented smart products of enterprises. Based on the research literature on Elderly-oriented smart products collected in CNKI database in recent ten years (2012-2022), this paper makes a quantitative analysis on the research results of Elderly-oriented smart products in China with the help of CiteSpace visual analysis software. Through research hotspots and evolution trends, it is found that the theme can be extended: the upgrading and construction of Elderly-oriented smart products will be a hot research topic in the academic community in the future

Colorimetric Sensor Array for Discrimination of Heavy Metal Ions in Aqueous Solution Based on Three Kinds of Thiols as Receptors

In the present work, we report a novel colorimetric sensor array for rapid identification of heavy metal ions. The sensing mechanism is based on the competition between thiols and urease for binding with the metal ions. Due to the different metal ion-binding abilities between the thiols and urea, different percentages of urease are free of metal ions and become catalytically active in the presence of varied metal ions. The metal ion-free urease catalyzes the decomposition of urea releasing ammonia and changing the pH of the analyte solution. Bromothymol blue, the pH indicator, changes its color in response to the metal-caused pH change. Three different thiols (l-glutathione reduced, l-cysteine, and 2-mercaptoethanol) were used in our sensor array, leading to a unique colormetric repsonse pattern for each metal. Linear discriminant analysis (LDA) was employed to analyze the patterns and generate a clustering map for identifying 11 species of metal ions (Ni²⁺, Mn²⁺, Zn²⁺, Ag⁺, Cd²⁺, Fe³⁺, Hg²⁺, Cu²⁺, Sn⁴⁺, Co²⁺, and Pb²⁺) at 10 nM level in real samples. The method realizes the simple, fast (within 30 s), sensitive, and visual discrimination of metal ions, showing the potential applications in environmental monitoring