A Multi-pipe Path Planning by Modified Ant Colony Optimization

Path planning in 3D geometry space is used to find an optimal path in the restricted environment, according to a certain evaluation criteria. To solve the problem of long searching time and slow solving speed in 3D path planning, a modified ant colony optimization is proposed in this paper. Firstly, the grid method for environment modeling is adopted. Heuristic information is connected with the planning space. A semi-iterative global pheromone update mechanism is proposed. Secondly, the optimal ants mutate the paths to improve the diversity of the algorithm after a defined iterative number. Thirdly, co-evolutionary algorithm is used. Finally, the simulation result shows the effectiveness of the proposed algorithm in solving the problem of 3D pipe path planning.

MARIE:One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

Security and safety remain paramount concerns for both governments and individuals worldwide.In today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to society.Consequently,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent incidents.Recent advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying firearms.This paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection applications.The SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction capabilities.The experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy trade-off.Through these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.

Mathematical models of steady-state temperature fields produced by multi-piped freezing

The multi-piped freezing method is usually applied in artificial ground freezing （AGF） projects to fulfill special construction requirements, such as two-, three-, or four-piped freezing. Based on potential superposition theory, this paper gives analytical solutions to steady-state frozen temperature for two, three, and four freezing pipes with different temperatures and arranged at random. Specific solutions are derived for some particular arrangements, such as three freezing pipes in a linear arrangement with equal or unequal spacing, right and isosceles triangle arrangements, four freezing pipes in a linear arrangement with equal spacing, and rhombus and rectangle arrangements. A comparison between the analytical solutions and numerical thermal analysis shows that the analytical solutions are sufficiently precise. As a part of the theory of AGF, the analytical solutions of temperature fields for multi-piped freezing with arbitrary layouts and different temperatures of freezing pipes are approached for the first time.

Modeling Study of Seasonal Variation of the Pelagic-Benthic Ecosystem Characteristics of the Bohai Sea

Based on experiment data of the Sino-German comprehensive investigations in the Bohai Sea in 1998 and 1999, a simple coupled pelagic-benthic ecosystem multi-box model is used to simulate the ecosystem seasonal variation. The pelagic sub-model consists of seven state variables： phytoplankton, zooplankton, TIN, TIP, DOC, POC and dissolved oxygen （DO）. The benthic sub-model includes macro-benthos, meiobenthos, bacteria, detritus, TIN and TIP in the sediment. Besides the effects of solar radiation, water temperature and the nutrient from sea bottom exudation, land-based inputs are considered. The impact of the advection terms between the boxes is also considered. Meanwhile, the effects of the micro- bial-loop are introduced with a simple parameterization. The seasonal variations and the horizontal distributions of the ecosystem state variables of the Bohai Sea are simulated. Compared with the observations, the results of the multi-box model are reasonable. The modeled results show that about 13% of the photosynthesis primary production goes to the main food loop, 20% transfers to the benthic domain, 44% is consumed by the respiration of phytoplankton, and the rest goes to DOC. Model results also show the importance of the microbial food loop in the ecosystem of the Bohai Sea, and its contribution to the annual zooplankton production can be 60%-64%.

Deep Learning Based Face Detection and Identification of Criminal Suspects

Occurrence of crimes has been on the constant rise despite the emerging discoveries and advancements in the technological field in the past decade.One of the most tedious tasks is to track a suspect once a crime is committed.As most of the crimes are committed by individuals who have a history of felonies,it is essential for a monitoring system that does not just detect the person’s face who has committed the crime,but also their identity.Hence,a smart criminal detection and identification system that makes use of the OpenCV Deep Neural Network(DNN)model which employs a Single Shot Multibox Detector for detection of face and an auto-encoder model in which the encoder part is used for matching the captured facial images with the criminals has been proposed.After detection and extraction of the face in the image by face cropping,the captured face is then compared with the images in the CriminalDatabase.The comparison is performed by calculating the similarity value between each pair of images that are obtained by using the Cosine Similarity metric.After plotting the values in a graph to find the threshold value,we conclude that the confidence rate of the encoder model is 0.75 and above.

R&S整装待发,迎接TD-LTE测试挑战

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