Research on teaching reform of Police Law course

In the investigation of the internship situation of public security graduates, it is found that there is a big gap between the ability of public security theory and practice and the demand of employers. Therefore, professional courses should further enhance the scientific nature in supporting professional personnel training. As the core course of public security major, Police Regulations have found some pain points and difficulties in curriculum design and teaching implementation in the process of teaching results investigation and discipline reflection. Based on this, this course carries out a more scientific and targeted learning goal setting under the guidance of OBE concept to support the training of professional talents. On the basis of the constructivism teaching concept, the teaching reform of this course is explored, so that the spark of teaching activities and students' thinking can collide in the classroom, and under the guidance of teachers, it gradually constructs its own ideas and veins, roots theoretical knowledge in the fertile soil of public security practice, and truly achieves the goal of training applied police talents. Keywords: OBE concept; Teaching reform; Joint police examination DOI: 10.7176/NMMC/106-0

SAMSON: Spectral Absorption-fluorescence Microscopy System for ON-site-imaging of algae

This paper presents SAMSON, a Spectral Absorption-fluorescence Microscopy System for ON-site-imaging of algae within a water sample. Designed to be portable and low-cost for on-site use, the optical sub-system of SAMSON consists of a mixture of low-cost optics and electronics, designed specifically to capture both fluorescent and absorption responses from a water sample. The graphical user interface (GUI) sub-system of SAMSON was designed to enable flexible visualisation of algae in the water sample in real-time, with the ability to perform fine-grained exposure control and illumination wavelength selection. We demonstrate SAMSON's capabilities by equipping the system with two fluorescent illumination sources and seven absorption illumination sources to enable the capture of multispectral data from six different algae species (three from the Cyanophyta phylum (blue-green algae) and three from the Chlorophyta phylum (green algae)). The key benefit of SAMSON is the ability to perform rapid acquisition of fluorescence and absorption data at different wavelengths and magnification levels, thus opening the door for machine learning methods to automatically identify and enumerate different algae in water samples using this rich wealth of data

Analysis and Forecasting for Traffic Flow Data

In this thesis, a number of techniques related to Principal Component Analysis (PCA) are used to derive core traffic patterns from streams of traffic data on a large number of road segments. Using a few number of k hidden variables, we show that the traffic information on the road segments can be captured by k traffic patterns. The dimensionality of the correlated road segments is successfully reduced from n to a much smaller number k by applying techniques related to Principal Component Analysis (PCA), where n is the number of road segments and k is the number of hidden variables. We use the k nearest neighbor(KNN) method to predict the values of the hidden variables over small time windows. As a result, we are able to forecast the speeds for n road segments very quickly. Our results are aimed at network-level and real-time prediction. In general, the computation of PCA is computationally demanding when n is large. A more efficient online version of PCA, called PASTd algorithm is used to reduce the data dimension. As a result, our forecasting method is efficient, flexible, and robust

Optimal use of Charge Information for the HL-LHC Pixel Detector Readout

The pixel detectors for the High Luminosity upgrades of the ATLAS and CMS detectors will preserve digitized charge information in spite of extremely high hit rates. Both circuit physical size and output bandwidth will limit the number of bits to which charge can be digitized and stored. We therefore study the effect of the number of bits used for digitization and storage on single and multi-particle cluster resolution, efficiency, classification, and particle identification. We show how performance degrades as fewer bits are used to digitize and to store charge. We find that with limited charge information (4 bits), one can achieve near optimal performance on a variety of tasks.Comment: 27 pages, 20 figure

Gender Bias in Large Language Models across Multiple Languages

With the growing deployment of large language models (LLMs) across various applications, assessing the influence of gender biases embedded in LLMs becomes crucial. The topic of gender bias within the realm of natural language processing (NLP) has gained considerable focus, particularly in the context of English. Nonetheless, the investigation of gender bias in languages other than English is still relatively under-explored and insufficiently analyzed. In this work, We examine gender bias in LLMs-generated outputs for different languages. We use three measurements: 1) gender bias in selecting descriptive words given the gender-related context. 2) gender bias in selecting gender-related pronouns (she/he) given the descriptive words. 3) gender bias in the topics of LLM-generated dialogues. We investigate the outputs of the GPT series of LLMs in various languages using our three measurement methods. Our findings revealed significant gender biases across all the languages we examined.Comment: 20 pages, 27 tables, 7 figures, submitted to ACL202