Change detection based on remote sensing images plays an important role in the field of analysis, and it has been widely used many areas, such as resources monitoring, urban planning, disaster assessment, etc. In recent years, aroused widespread interest due to explosive development artificial intelligence (AI) technology, change algorithms deep learning frameworks have made possible detect more delicate changes (such alteration small buildings) with help huge amounts data, especially...

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous recognition rely excessively on sophisticated hand-crafted feature design rate not high enough for its practical application. In this paper, we proposed Dual Temporal Scale Convolutional Neural Network (DTSCNN) micro-expressions recognition. The DTSCNN two-stream network. Different stream used adapt different frame video clips. Each...

Although large language models (LLMs) has shown great performance on natural processing (NLP) in the financial domain, there are no publicly available tailtored LLMs, instruction tuning datasets, and evaluation benchmarks, which is critical for continually pushing forward open-source development of artificial intelligence (AI). This paper introduces PIXIU, a comprehensive framework including first LLM based fine-tuning LLaMA with data, data 136K samples to support fine-tuning, an benchmark 5...

Recently, lead halide perovskite nanocrystals (NCs) have attracted extensive attention due to their unique optical properties. However, the toxicity of and instability moisture obstruct further commercial development. Herein, a series lead-free CsMnX3 (X = Cl, Br, I) NCs embedded in glasses were synthesized by high temperature solid-state chemistry method. These glass can remain stable after soaking water for 90 days. It is found that increasing amount cesium carbonate synthesis process not...

In power utility service outsourcing, some time-sensitive computations (e.g., dynamic prices prediction) are outsourced to a third-party provider. This brings in new privacy threats customers. Although existing works focus on achieving privacy-preserving temporal and spatial aggregation for one center, they basically cannot be directly applied the scenario of outsourcing with multiple centers providers). We thus propose scheme, called PPSO, real-time pricing demand response smart grid fault...

As the number of aged population grows, fall detection has attracted considerable research attentions in recent years. Through data collected by wearable sensors and specific algorithms, protection can be performed before user hits ground. However, most existing researches have not considered direction falls which used for more effective protection. In this paper, to further distinguish improve accuracy, we propose a multi-sensor-based system taking as multi-class problem. To extract feature...

Developing organic molecular crystals with twisted morphology either through spontaneous formation or in response to external stimuli is compelling yet challenging.

Recently, large language models (LLMs) like ChatGPT have demonstrated remarkable performance across a variety of natural processing tasks. However, their effectiveness in the financial domain, specifically predicting stock market movements, remains to be explored. In this paper, we conduct an extensive zero-shot analysis ChatGPT's capabilities multimodal movement prediction, on three tweets and historical price datasets. Our findings indicate that is "Wall Street Neophyte" with limited...

This paper aims to establish an intelligent delivery system integrated with track logistics and explores its impact on the clinical transportation of goods. The study analyzed hospital items before after implementation combined automated in 2023. Delivery conditions prior system’s activation served as control group, while those post-implementation formed observation group. research assesses effects efficiency, resource allocation, transport safety, satisfaction among medical staff. average...

In online medical consultations, patients convey their condition through self-disclosure, and the linguistic features of this disclosure, as signals, may significantly impact doctors’ diagnostic behavior service quality. Based on signaling theory, paper collects consultation data from a large platform in China, employs text mining classification techniques to extract relevant variables, applies econometric models empirically examine effect patients’ self-disclosure quality services. The...

Temporal Knowledge graph completion (TKGC) is a crucial task that involves reasoning at known timestamps to complete the missing part of facts and has attracted more attention in recent years. Most existing methods focus on learning representations based neural networks while inaccurately extracting information from insufficiently utilizing implied relations. To address these problems, we propose novel TKGC model, namely Pre-trained Language Model with Prompts for (PPT). We convert series...

Device-to-device (D2D) communication is a promising technique to improve the spectral efficiency of cellular networks. In this paper, we investigate joint uplink and downlink resource allocation problem maximize sum data rate system while guaranting quality service (QoS) for both user equipments (CUEs) D2D (DUEs). particular, jointly consider subcarrier resources DUEs reuse formulate optimization as mixed integer nonlinear programming (MINLP) which generally NP-hard. To make tractable,...

This letter investigates the joint uplink and downlink resource allocation problem, where non-orthogonal multiple access (NOMA) technology is applied to enhance device-to-device (D2D) communications. In order maximize sum data rate of NOMA-enabled D2D groups while guaranteeing minimum requirements both cellular users (CUs) groups, we first design a subcarrier assignment algorithm assign subcarriers for then transform problem into convex optimization obtain optimal power allocation....

Both oceanic and continental HP rocks are juxtaposed in the Huwan shear zone western Dabie orogen, thus provide a window for testing buoyancy-driven exhumation of dense rocks. The metamorphic age this has not been well constrained, hence it is known if they same as In situ laser ablation (multiple collector) inductively coupled plasma mass spectrometry (LA-(MC-)ICP-MS), U–Pb, trace element Hf isotope analyses were made on zircon granitic gneiss two eclogites from zone. U–Pb analysis residual...

The industrial-scale high-temperature preheating air-blown KEDA®circulating fluidized-bed (KEDA®CFB) gasification process has been developed by KEDA(ANHUI) Clean Energy Co., Ltd. to produce industrial fuel gas. This paper presents the design and first operational results of a 15MWth demonstration KEDA®CFB plant where about 3.6 tons bituminous coal was gasified per hour. influences steam ratio (SC), equivalence (ER), oxygen concentration (OC) on gas composition, high heating value (HHV),...

Physiological information such as respiratory rate and heart in the sleep state can be used to evaluate health condition of sleeper. Traditional monitoring systems need body contact are intrusive, which limits their applicability. Thus, a comfortable biosignals detection system with both high accuracy low cost is important for care. In this paper, we design based on low-cost piezoelectric ceramic sensors. 18 sensors deployed under mattress capture pressure data. The appropriate sensor that...

Emotional and physical stress can cause various health problems. In this paper, we used tissue blood oxygen saturation (StO2), a newly proposed physiological signal, to classify the human stress. We firstly constructed public StO2 database including 42 volunteers subjected two types of During experiment, observed that facial right after be either increased or decreased comparing baseline. investigated feature combinations for classification found average values from left cheek, chin, middle...