DGG: A Novel Framework for Crowd Gathering Detection

Crowd gathering detection plays an important role in security supervision of public areas. Existing image-processing-based methods are not robust for complex scenes, and deep-learning-based methods for gathering detection mainly focus on the design of the network, which ignores the inner feature of the crowd gathering action. To alleviate such problems, this work proposes a novel framework Detection of Group Gathering (DGG) based on the crowd counting method using deep learning approaches and statistics to detect crowd gathering. The DGG mainly contains three parts, i.e., Detecting Candidate Frame of Gathering (DCFG), Gathering Area Detection (GAD), and Gathering Judgement (GJ). The DCFG is proposed to find the frame index in a video that has the maximum people number based on the crowd counting method. This frame means that the crowd has gathered and the specific gathering area will be detected next. The GAD detects the local area that has the maximum crowd density in a frame with a slide search box. The local area contains the inner feature of the gathering action and represents that the crowd gathering in this local area, which is denoted by grid coordinates in a video frame. Based on the detected results of the DCFG and the GAD, the GJ is proposed to analyze the statistical relationship between the local area and the global area to find the stable pattern for the crowd gathering action. Experiments based on benchmarks show that the proposed DGG has a robust representation of the gathering feature and a high detection accuracy. There is the potential that the DGG can be used in social security and smart city domains.

Effects of different shrimp extracts on Vibrio parahaemolyticus growth and virulence

Vibrio parahaemolyticus is the main causative agent of acute hepatopancreatic necrosis disease (AHPND) in shrimp. This study aimed to investigate how shrimp extracts affect the growth and virulence of an AHPND-causative strain known as V. parahaemolyticus XN9. To this end, the bacteria was cultured in media containing 3% extract of each of five shrimp types and their growth kinetics were compared against that from bacteria grown in brain-heart infusion (BHI) media. Eight-hour growth curves were constructed using the plate-counting method. The activity of five extracellular enzymes that contribute to bacterial virulence was examined using the agar-based method. The results showed that V. parahaemolyticus XN9’s growth was strongly enhanced in all five shrimp extract media with the highest increase (25% greater than the BHI medium) found in the giant tiger prawn extract. Additionally, all the shrimp extracts boosted the extracellular enzymatic activity of V. parahaemolyticus XN9, although to different extents. In summary, the shrimp extracts, particularly that from the prawns, not only promoted the viability and growth of V. parahaemolyticus XN9 but also its extracellular enzymatic activities.

Olfactory receptor subgenome and expression in a highly olfactory procellariiform seabird

Procellariiform seabirds rely on their sense of smell for foraging and homing. Both genomes and transcriptomes yield important clues about how olfactory receptor (OR) subgenomes are shaped by natural and sexual selection, yet no transcriptomes have been made of any olfactory epithelium of any bird species thus far. Here we assembled a high-quality genome and nasal epithelium transcriptome of the Leach’s storm-petrel (Oceanodroma leucorhoa) to extensively characterize their OR repertoire. Using a depth-of-coverage-assisted counting method, we estimated over 160 intact OR genes (∼500 including OR fragments). This method reveals the highest number of intact OR genes and the lowest proportion of pseudogenes compared to other waterbirds studied, and suggests that rates of OR gene duplication vary between major clades of birds, with particularly high rates in passerines. OR expression patterns reveal two OR genes (OR6-6 and OR5-11) highly expressed in adults, and four OR genes (OR14-14, OR14-12, OR10-2, and OR14-9) differentially expressed between age classes of storm-petrels. All four genes differentially expressed between age classes were more highly expressed in chicks compared to adults, suggesting that ORs genes may exhibit ontogenetic specializations. Three highly differentially expressed OR genes also had high copy number ratios, suggesting that expression variation may be linked to copy number in the genome. We provide better estimates of OR gene number by using a copy number-assisted counting method, and document ontogenetic changes in OR gene expression that may be linked to olfactory specialization. These results provide valuable insight into the expression, development, and macroevolution of olfaction in seabirds.

Improved Image Analysis Method to Evaluate Tracking Property under Successive Flashover Based on Fractal Theory

Successive flashover would result in carbonized tracking on insulator surface and cause deterioration to the insulation. Thus, investigation of the tracking can be beneficial in understanding flashover characteristics during long-term operation. In this paper, DC flashover was operated on the insulator, and the image of tracking after successive discharge were captured. Improved differential box-counting method (IDBM) was applied to analyze these images based on fractal theory. Weighted item was suggested during the counting procedure for rectangle image with margin covered by cut-size box. Fractal dimension of the tracking was calculated according to the suggested method. It is claimed that the suggested method could estimate the discharge propagation property and deterioration characteristics on the insulator surface. Moreover, IDBM showed advantages in image pre-processing and deterioration property revealed compared to traditional box-counting method attributing to the consideration of color depth. This image analysis method shows universality in dealing with tracking image and could provide additional information to flashover voltage. This paper suggested a potential approach for the investigation of discharge mechanism and corresponding deterioration in future research.

A Soft-YoloV4 for High-Performance Head Detection and Counting

Blockage of pedestrians will cause inaccurate people counting, and people’s heads are easily blocked by each other in crowded occasions. To reduce missed detections as much as possible and improve the capability of the detection model, this paper proposes a new people counting method, named Soft-YoloV4, by attenuating the score of adjacent detection frames to prevent the occurrence of missed detection. The proposed Soft-YoloV4 improves the accuracy of people counting and reduces the incorrect elimination of the detection frames when heads are blocked by each other. Compared with the state-of-the-art YoloV4, the AP value of the proposed head detection method is increased from 88.52 to 90.54%. The Soft-YoloV4 model has much higher robustness and a lower missed detection rate for head detection, and therefore it dramatically improves the accuracy of people counting.

Estimation of Depth of Discharge of Li-ion Battery Using Neural Network

This paper deals with the estimation of depth of discharge for Li-ion batteries. Estimation is based on the knowledge of discharging curves measured for discrete values of loading currents. The estimator of the depth of discharge is a form of feedforward neural network which is trained with the measured data of discharge curves. Accuracy of estimation of the depth of discharge is shown for arbitrary generated and measured loading characteristics, where the depth of discharge is estimated by the designed neural network and measured by using the Coulomb counting method.

Penentuan Komposisi Bahan Bakar Nabati Dalam Bahan Bakar Minyak Campuran Menggunakan Metode Direct Counting C-14

ABSTRAK. Telah dilakukan penentuan komposisi bahan bakar nabati (BBN) dalam bahan bakar minyak campuran (BBMC) dengan metode direct counting C-14. Penentuan komposisi BBN dalam BBMC dilakukan dengan cara memipet 10 mL BBMC ke dalam vial gelas kemudian ditambahkan 10 mL larutan sintilator Ultima Gold F (UGF) ke dalamnya. Vial tersebut dikocok agar campuran menjadi homogen kemudian dicacah menggunakan LSC (Liquid Scintillation Counter) Elmer Perkin 2900TR selama 20 menit sebanyak 30 siklus. Hasil pencacahan ditampilkan dalam bentuk tSIE (transformed external standard spectrum) dan cpm (cacahan permenit). Hasil analisis memperlihatkan nilai cpm yang meningkat seiring kenaikan persentase BBN dalam BBMC. Nilai cpm terendah dan tertinggi untuk sampel bensin, avtur, dan solar berturut-turut adalah 14,2363 dan 62,0343, 10,664 dan 44,535, serta 9,410 dan 61,789. Terdapat korelasi kuat antara nilai tSIE dan nilai cpm pada bensin dan solar tapi tidak pada avtur. Hasil analisis terhadap sampel uji menunjukkan bahwa sampel tersebut berada di luar grafik deret sampel. Metode direct counting ini diharapkan dapat menjadi referensi dalam uji mutu BBMC.ABSTRACT. The composition of biofuel (BF) in mixed oil fuel (MOF) has been determined using the C-14 direct counting method. Determination of the composition of BF in MOF was carried out by pipetting 10 mL of BBMC into a glass vial and then adding 10 mL of Ultima Gold F (UGF) scintillator solution into it. The vial was shaken so that the mixture became homogeneous and then counted using the Elmer Perkin 2900TR LSC (Liquid Scintillation Counter) for 20 minutes for 30 cycles. The results of the counting are displayed in the form of tSIE (transformed external standard spectrum) and cpm (counts per minute). The results of the analysis show that the value of cpm increases with the increase in the percentage of BF in MOF. The lowest and highest cpm values for gasoline, avtur, and diesel samples were 14.2363 and 62.0343, 10.664 and 44.535, and 9.410 and 61.789, respectively. There is a strong correlation between tSIE and cpm values for gasoline and diesel but not for avtur. The results of the analysis of the test sample indicate that the sample is outside the sample series graph. This direct counting method is expected to be a reference in the BBMC quality test.

Multilayered Complexity Analysis in Architectural Design: Two Measurement Methods Evaluating Self-Similarity and Complexity

This article contributes to clarifying the questions of whether and how fractal geometry, i.e., some of its main properties, are suitable to characterize architectural designs. This is done in reference to complexity-related aesthetic qualities in architecture, taking advantage of the measurability of one of them; the fractal dimension. Research in this area so far, has focused on 2-dimensional elevation plans. The authors present several methods to be used on a variety of source formats, among them a recent method to analyze pictures taken from buildings, i.e., 2.5-dimensional representations, to discuss the potential that lies within their combination. Color analysis methods will provide further information on the significance of a multilayered production and observation of results in this realm. In this publication results from the box-counting method are combined with a coordinate-based method for analyzing redundancy of proportions and their interrelations as well as the potential to include further layers of comparison are discussed. It presents a new area of box-counting implementation, a methodologically redesigned gradient analysis and its new algorithm as well as the combination of both. This research shows that in future systems it will be crucial to integrate several strategies to measure balanced aesthetic complexity in architecture.