Listen to Minority: Encrypted Traffic Classification for Class Imbalance with Contrastive Pre-Training

Mobile Internet has profoundly reshaped modern lifestyles in various aspects. Encrypted Traffic Classification (ETC) naturally plays a crucial role in managing mobile Internet, especially with the explosive growth of mobile apps using encrypted communication. Despite some existing learning-based ETC methods showing promising results, three-fold limitations still remain in real-world network environments, 1) label bias caused by traffic class imbalance, 2) traffic homogeneity caused by component sharing, and 3) training with reliance on sufficient labeled traffic. None of the existing ETC methods can address all these limitations. In this paper, we propose a novel Pre-trAining Semi-Supervised ETC framework, dubbed PASS. Our key insight is to resample the original train dataset and perform contrastive pre-training without using individual app labels directly to avoid label bias issues caused by class imbalance, while obtaining a robust feature representation to differentiate overlapping homogeneous traffic by pulling positive traffic pairs closer and pushing negative pairs away. Meanwhile, PASS designs a semi-supervised optimization strategy based on pseudo-label iteration and dynamic loss weighting algorithms in order to effectively utilize massive unlabeled traffic data and alleviate manual train dataset annotation workload. PASS outperforms state-of-the-art ETC methods and generic sampling approaches on four public datasets with significant class imbalance and traffic homogeneity, remarkably pushing the F1 of Cross-Platform215 with 1.31%, ISCX-17 with 9.12%. Furthermore, we validate the generality of the contrastive pre-training and pseudo-label iteration components of PASS, which can adaptively benefit ETC methods with diverse feature extractors.Comment: Accepted by 2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking, 9 pages, 6 figure

Geographical Distribution Characteristics of Ethnic-Minority Villages in Fujian and Their Relationship with Topographic Factors

The geographical distribution characteristics of villages characterised by ethnic minorities are determined by the selection of the site when the village was initially established. The location of inherited and well-preserved minority villages must be exceptionally compatible with the natural terrain, with a logical relationship. Nonetheless, the issue of village location, which is directly related to the development of the features of the geographical distribution, has received little attention from scholars. The average nearest proximity index, Voronoi, kernel density analysis, proximity analysis, and the Geographical Detector (GeoDetector) were used to analyse the geographic distribution characteristics of villages and their correlation with terrain, as well as the difference between the influence of each terrain factor. The findings indicated the following. (1) The geographical distribution of minority villages in Fujian Province is of the agglomeration type, with a significant “mononuclear” feature, and the topography has a facilitating effect on the clustering distribution of villages. (2) The geographical distribution of minority villages in each city of Fujian Province coexisted with the agglomeration type and the dispersion type, and the role of topography in promoting the agglomeration-type distribution of villages was not affected by the distribution density of villages. (3) The site selection of Fujian-minority villages is characterised by medium altitude, moderate slope, sun exposure, and no obvious hydrophilicity. Minority villages are mainly located in areas with an elevation of 202–647 m; a slope of 6–15°; a flat land aspect with a south slope, southeast slope, or southwest slope; and distance of 500–1500 m from 5–20 m wide rivers of level 2. (4) The site selection of Fujian minority villages is influenced by various topographic factors, such as elevation, slope, aspect, river buffer, river width, and river level, among which river width has the most substantial effect. (5) All topographic factors have a two-factor enhancing relationship with each other, aspect and slope have the most substantial effect and play a dominant role in site selection. The research findings illuminate the internal logic of the geographical distribution differentiation of villages characterised by ethnic minorities, which is critical for promoting the protection of modern ethnic-minority villages

PENGARUH DEWAN KOMISARIS ASING, DEWAN KOMISARIS INDEPENDEN DAN KEPEMILIKAN SAHAM ASING TERHADAP NILAI PERUSAHAAN (STUDI EMPIRIS PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BEI TAHUN 2009-2011)

Penelitian ini bertujuan untuk menguji pengaruh dewan komisaris asing, dewan komisaris independen dan kepemilikan saham asing terhadap nilai perusahaan manufaktur yang terdaftar di BEI (Bursa Efek Indonesia) selama periode pengamatan (2009-2011).Penelitian ini merupakan penelitian empiris dengan pendekatan kuantitatif yang melibatkan penggunaan analisa statistik. Penelitian ini menggunakan data sekunder. Alat analisisnyang digunakan dalam penelitian ini adalah regresi linier berganda dengan bantuan sofware SPSS (Statistical Package for Social Scienc) Hasil penelitian menunjukkan bahwa dewan komisaris asing dan kepemilikan saham asing berpengaruh positif dan signifikan terhadap nilai perusahaan, sedangkan variabel dewan komisaris independen tidak mempunyai pengaruh yang signifikan terhadap nilai perusahaan

A High-Performance Mid-infrared Optical Switch Enabled by Bulk Dirac Fermions in Cd3As2

Pulsed lasers operating in the 2-5 {\mu}m band are important for a wide range of applications in sensing, spectroscopy, imaging and communications. Despite recent advances with mid-infrared gain media, the lack of a capable pulse generation mechanism, i.e. a passive optical switch, remains a significant technological challenge. Here we show that mid-infrared optical response of Dirac states in crystalline Cd3As2, a three-dimensional topological Dirac semimetal (TDS), constitutes an ideal ultrafast optical switching mechanism for the 2-5 {\mu}m range. Significantly, fundamental aspects of the photocarrier processes, such as relaxation time scales, are found to be flexibly controlled through element doping, a feature crucial for the development of convenient mid-infrared ultrafast sources. Although various exotic physical phenomena have been uncovered in three-dimensional TDS systems, our findings show for the first time that this emerging class of quantum materials can be harnessed to fill a long known gap in the field of photonics.Comment: 17 pages, 3 figure

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

An Image Edge Detection Algorithm Based on an Artificial Plant Community

Image edge detection is a difficult task, because it requires the accurate removal of irrelevant pixels, while retaining important pixels that describe the image’s structural properties. Here, an artificial plant community algorithm is proposed to aid in the solving of the image edge detection problem. First, the image edge detection problem is modeled as an objective function of an artificial plant community searching for water sources and nutrients. After many iterations, the artificial plant community is concentrated in habitable areas that are rich in water sources and nutrients, that is, the image edges, and the nonhabitable zones that are not suitable for living are deserted, that is, the nonedges. Second, an artificial plant community algorithm is designed to solve the objective function by simulating the growth process of a true plant community. The living behavior of the artificial plant community includes three operations: seeding, growing, and fruiting. The individuals in the plant community also correspond to three forms, namely seeds, individuals, and fruit. There are three fitness comparisons in each iteration. The first fitness comparison of each iteration is carried out during the seeding operation. Only the fruit with higher fitness levels in the last iteration can become seeds, while the fruit with low fitness levels die, and some new seeds are randomly generated. The second fitness comparison is implemented in the growing operation. Only the seeds with higher fitness levels can become individuals, but the seeds with lower fitness levels will die; thus, the community size will decrease. The third fitness comparison is in the fruiting operation, where the individual with the greatest fitness can produce an identical fruit through parthenogenesis, and the individuals with higher fitness levels can learn from each other and produce more fruit, so the population size can be restored. Through the continuous cycle of these three operations, the artificial plant community will finally determine the edge pixels and delete the nonedge pixels. Third, the experiment results reveal how the proposed algorithm generates the edge image, and the comparative results demonstrate that the proposed artificial plant community algorithm can effectively solve the image edge detection problems. Finally, this study and some limitations are summarized, and future directions are suggested. The proposed algorithm is expected to act as a new research tool for solving various complex problems