A Study of Management Problems and Countermeasures of Home Appliance Manufacturing Enterprises Based on a Green Supply Chain during COVID-19

Jian Li,Yong-Seo Seob,Xin Yin 한국무역연구원 2021 무역연구 Vol.17 No.1

Purpose There was a significant impact on the global economy in 2020 during COVID-19. Home appliance manufacturing enterprises are important to promote the rapid development of economies in Korea and China;but with rapid development;waste has caused enormous damage to the environment. Consumers take green factors into account when purchasing products. At the same time;governments promulgate environmental laws and regulations. Therefore;it is necessary and urgent for home appliance manufacturing enterprises to implement green supply chain management. Design/Methodology/Approach Based on the development of green supply chain management theory;this paper analyzes the present situation of home appliance manufacturing industry in Yancheng and the existing problems of green supply chain management. Based on a questionnaire on the restrictive factors of green supply chain management of the home appliance manufacturing industry in Yancheng using SPSS21.0;this paper studied the restraining factors and corresponding secondary factors of the green supply chain management in Yancheng home appliance manufacturing enterprises (government;enterprise;supply chain upstream;and downstream). Findings The study found that government policy was most influential;among which environmental laws and regulations had a low impact;but imperfect environmental laws and regulations and loose enforcement have a greater impact. Second was the influence of the companies themselves;among which the number and quality of green supply chain management personnel to be improved have a greater impact. Supply chain upstream and downstream were the least impact factors;among which conveying the concept of green supply chain management to suppliers had a greater impact. Research Implications Strategies and solutions are put forward to the government;enterprises;and the upstream and downstream of the supply chain to promote the improvement of green supply chain management of home appliance manufacturing enterprises in Yancheng. These findings could be applied equally to Korea.

Geophysical methods for the investigation of a closed dumping ground

Xin, Ling,Chu, Jian,Wang, Jing-Yuan,Yin, Ke,Tong, Huan-Huan,Chia, Charles Y.H.,Mohamed Noh, Omar A. Techno-Press 2015 Geomechanics & engineering Vol.8 No.5

Reclamation of closed dumping grounds is a potential solution to solve land scarce problems. Traditional geotechnical investigations of closed dumping grounds face some problems, such as the emission of hazardous liquids and gases, and the lack of ground information due to the discontinuity between two boreholes. Thus, noninvasive and continuous investigation methods are needed to supplement traditional geotechnical investigations. In this paper, two types of geophysical investigation methods, Seismic Analysis of Surface Waves (SASW) and 2D Resistivity, were carried out to study noninvasive and continuous site investigations for dumping grounds. The two geophysical methods are able to profile the distribution of physical properties of the fill and original materials, by which the extent of the dumping ground can be found and some anomalies in the subsurface can be located. Boreholes were used to assist in locating the dumping material-ground interfaces. The results show that dumping material-ground interfaces obtained from the two geophysical methods are roughly consistent. Moreover, attempt is made in the paper to use the geophysical methods to classify the types of dumping materials. The results show that the classification of dumping materials using the geophysical methods follows the results of the manual sorting of the dumping materials from a borehole.

A DoS Detection Method Based on Composition Self-Similarity

( Zhu Jian-qi ),( Fu Feng ),( Chong-kwon Kim ),( Yin Ke-xin ),( Liu Yan-heng ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.5

Based on the theory of local-world network, the composition self-similarity (CSS) of network traffic is presented for the first time in this paper for the study of DoS detection. We propose the concept of composition distribution graph and design the relative operations. The (R/S)d algorithm is designed for calculating the Hurst parameter. Based on composition distribution graph and Kullback Leibler (KL) divergence, we propose the composition self-similarity anomaly detection (CSSD) method for the detection of DoS attacks. We evaluate the effectiveness of the proposed method. Compared to other entropy based anomaly detection methods, our method is more accurate and with higher sensitivity in the detection of DoS attacks.

Lifetime data modelling and reliability analysis based on modified weibull extension distribution and Bayesian approach

Yuan-Jian Yang,Wenhe Wang,Xin-Yin Zhang,Ya-Lan Xiong,Gui-Hua Wang 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.11

Satellite reliability has long been a critical issue in space industry. In-orbit lifetime data modelling and the corresponding reliability analysis are indispensable aspects for satellite reliability. However, limited by available in-orbit lifetime data, these two aspects have not been well studied. Aiming to mitigate this limitation, we conduct a coherent research on satellite reliability analysis based on an in-orbit database of 1584 satellites. A nonparametric reliability analysis is firstly implemented on the data set to identify the characteristics of failure rate. Then, the modified Weibull extension distribution is used to model the satellite reliability. Point estimation and interval estimation are carried out by utilizing a Bayesian method. Posterior distributions of model parameters are obtained and reserved for further reliability analysis of newly launched satellites. The results presented in this paper can provide helpful information to the space industry for design improvement and test planning of new satellites.

Cross-domain Recommendation by Combining Feature Tags with Transfer Learning

Yuyu Yin,Xin Wang,Jilin zhang,Jian Wan 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.10

Most recommender systems based on collaborative filtering aim to provide recommendations for a user in one domain. But data sparsity is a major problem for collaborative filtering techniques. Recently, many scholars have proposed recommendation models to alleviate the sparsity problem by transferring rating matrix in other domains. But different domains have different rating scales (e.g., rating scale may be 1-5 or 1-10). Simple process for the rating scale does not reflect the real situation. The diversity of rating scales may cause the opposite effect, making the recommendation results more imprecise. In this paper, we propose a transfer model which learning the common feature tags from other domain. This model ignores the difference of rating scales between two domains, and focus on studying the feature tags. Using its own rating values to fill the missing value. We first get the different types of users (items) based on non-negative matrix tri-factorization from auxiliary domain. The process we call the user (item) clustering. Than we can get a BP neural network which can judge the type of user according to user's feature tags by studying the features of different types of users (items). And we classify the user (items) which from target domain by exploiting the trained neural network and the users’ feature tags of target domain. Use the average rating values of the same type of users (items) to fill the missing value of target domain. We perform extensive experiments to show that our proposed model outperforms the state-of-the-art CF methods for the cross-domain recommendation task.

Relation between Ki-67, ER, PR, Her2/neu, p21, EGFR, and TOP II-α Expression in Invasive Ductal Breast Cancer Patients and Correlations with Prognosis

Yan, Jian,Liu, Xiao-Long,Han, Lu-Zhe,Xiao, Gang,Li, Ning-Lei,Deng, Yi-Nan,Yin, Liang-Chun,Ling, Li-Juan,Yu, Xiao-Yuan,Tan, Can-Liang,Huang, Xiao-Ping,Liu, Li-Xin Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.2

The aim of the present study was to investigate the expression of the transcription factor Ki-67, ER, PR, Her2/neu, p21, EGFR, and TOP II-${\alpha}$ in the tumor tissue of patients with invasive ductal carcinoma(IDC); in addition, we examined correlations between these markers. Two hundred and sixteen IDC patients, who were not previously been treated with chemo- or radiotherapy, were included in the study. All tumors were grade I-III. Expression of molecular markers was determined by immunohistochemical analysis on paraffin-embedded tissue sections. Follow-up data were collected for 3 months to 10 years and analyzed for tumor recurrence, survival time, and prognostic risk factors. We determined Ki-67 expression correlates with the expression of ER, PR, HER-2, EGFR, and TOP-${\alpha}$, as well as lymph node involvement, high tumor grade, lymphovascular invasion, high tumor stage, and high TNM stage in IDC. Positive Ki-67 expression was a risk factor for rapid tumor recurrence and may help tumor progression, leading to poor prognosis in IDC. Ki-67 was directly correlated with EGFR, TOP II-${\alpha}$, lymph node involvement, high tumor grade, lymphovascular invasion, high tumor stage, and high TNM stage in the hormone receptor subtypes of breast cancer. In triple negative breast cancer, Ki-67 correlated with TOP II-${\alpha}$. Expression of Ki-67 correlated with that of ER, PR, HER-2, EGFR, TOP II-${\alpha}$, and p21. In addition, the biomarker Ki-67 has a role as a prognostic factor and indicates a poor prognosis in IDC.

Immune Reconstitution of CD4⁺T Cells after Allogeneic Hematopoietic Stem Cell Transplantation and its Correlation with Invasive Fungal Infection in Patients with Hematological Malignancies

Peng, Xin-Guo,Dong, Yan,Zhang, Ting-Ting,Wang, Kai,Ma, Yin-Jian Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.8

Objective: To explore the immune reconstitution of $CD4^+T$ cells after allogeneic hematopoietic stem cell transplantation (Allo-HSCT) and its relationship with invasive fungal infection (IFI) in patients with hematological malignancies. Materials and Methods: Forty-seven patients with hematological malignancies undergoing Allo-HSCT in Binzhou Medical University Hospital from February, 2010 to October, 2014 were selected. At 1, 2 and 3 months after transplantation, the immune subpopulations and concentration of cytokines were assessed respectively using flow cytometry (FCM) and enzyme linked immunosorbent assay (ELISA). The incidence of IFI after transplantation and its correlation with immune reconstitution of $CD4^+T$ cells were investigated. Results: The number of $CD4^+T$ cells and immune subpopulations increased progressively after transplantation as time went on, but the subpopulation cell count 3 months after transplantation was still significantly lower than in the control group (p<0.01). In comparison to the control group, the levels of interleukin-6 (IL-6) and IL-10 after transplantation rose evidently (p<0.01), while that of transforming growth factor-${beta}$ (TGF-${beta}$) was decreased (p<0.01). There was no statistically significant difference level of interferon-${\gamma}$ (IFN-${\gamma}$) (p>0.05). The incidence of IFI was 19.2% (9/47), and multivariate logistic regression revealed that IFI might be related to Th17 cell count (p<0.05), instead of Th1, Th2 and Treg cell counts as well as IL-6, IL-10, TGF-${beta}$ and IFN-${\gamma}$ levels (p>0.05). Conclusions: After Allo-HSCT, the immune reconstitution of $CD4^+T$ cells is delayed and Th17 cell count decreases obviously, which may be related to occurrence of IFI.

Research Paper : Effects of phosphorus and light intensity on the growth and competition of the two weed species Veronica persica and Chorispora tenella

( Li Chu Yin ),( Jian Xin Luo ),( Lan Fang Luo ),( Gui Xian Xie ) 한국잡초학회 2012 Weed Biology and Management Vol.12 No.1

Veronica persica Poir. (Persian speedwell) is an invasive alien weed species in the upland soils throughout China. Its dominance in weed flora could be alleviated by Chorispora tenella (Pall.) (tender chorispora) in P-poor soils and in an intense light environment. Here, three experiments in growth chambers were carried out in order to explore the effect of P and light intensity on the growth and competition of V. persica and C. tenella, the pH value in their rhizospheres, and the kinetic parameters (Km and Vmax) of the H2PO4 - uptake by the two weed species. The ANOVA results showed that the light intensity and P level in the soil obviously influenced the growth of the two weed species. However, the effect of the P level in the soil was greater for V. persica and the effect of the light intensity was greater for C. tenella. The restriction of the growth of V. persica by a low P level in the soil was much more than that of C. tenella, but it was reversed in the two species in relation to a low light intensity. In addition, the pH was lower in the rhizosphere of C. tenella after the P-deficient treatment and there was a lower Km in the uptake of H2PO4 - than for V. persica, suggesting that C. tenella could adapt to a low-P environment more easily. In conclusion, C. tenella growing together with V. persica had a competitive advantage under high-light-intensity and low-P-level conditions, but it lost its advantage with an increase in P fertilization and a decrease in light intensity.

Realgar transforming solution-induced differentiation of NB4 cell by the degradation of PML/RARa partially through the ubiquitin–proteasome pathway

Yang Hai,Xin Wang,Peng Song,Jian-yin Li,Longhe Zhao,Fei Xie,Xiang-min Tan,Qin-Jian Xie,Lan Yu,Yang Li,Zhengrong Wu,Hong Yu Li 대한약학회 2019 Archives of Pharmacal Research Vol.42 No.8

PML/retinoic acid receptor alpha (RARa), as ahallmark of acute promyeloid leukemia (APL), is directlyrelated to the outcome of clinical APL remedy. It isreported that arsenicals can effectively degrade PML/RARa, such as arsenic trioxide and realgar. However, thehigh toxicity or insolubility have hampered their clinicalapplications. Realgar transforming solution (RTS) wasproduced from realgar by bioleaching process in our lab. Previous studies demonstrated that RTS had a significantanti-cancer ability on chronic myeloid leukemia throughoncoprotein degradation. The capacity of RTS on treatingAPL is what is focused on in this study. The results showedthat RTS had a noticeable sensitivity in NB4 cell, and RTSremarkably down-regulated PML/RARa expression andinduced cell differentiation. Further, RTS could accumulatePML/RARa into the nuclear bodies and then executedegradation, which could be reversed by proteasomeinhibitor MG132. The results also exhibited that thereduction of RTS-induced PML/RARa expression accompaniedby the elevation of ubiquitin and SUMO-1 proteinexpression. Finally, PML and SUMO-1 had been demonstratedto be co-localized after RTS treatment byimmunofluorescence co-localization assay and immunoprecipitationassay. In conclusion, these results suggestedthat RTS-induced cell differentiation may attribute to thePML/RARa degradation partially through the ubiquitin–proteasome pathway.

A Method for Tree Image Segmentation Combined Adaptive Mean Shifting with Image Abstraction

( Ting-ting Yang ),( Su-yin Zhou ),( Ai-jun Xu ),( Jian-xin Yin ) 한국정보처리학회 2020 Journal of information processing systems Vol.16 No.6

Although huge progress has been made in current image segmentation work, there are still no efficient segmentation strategies for tree image which is taken from natural environment and contains complex background. To improve those problems, we propose a method for tree image segmentation combining adaptive mean shifting with image abstraction. Our approach perform better than others because it focuses mainly on the background of image and characteristics of the tree itself. First, we abstract the original tree image using bilateral filtering and image pyramid from multiple perspectives, which can reduce the influence of the background and tree canopy gaps on clustering. Spatial location and gray scale features are obtained by step detection and the insertion rule method, respectively. Bandwidths calculated by spatial location and gray scale features are then used to determine the size of the Gaussian kernel function and in the mean shift clustering. Furthermore, the flood fill method is employed to fill the results of clustering and highlight the region of interest. To prove the effectiveness of tree image abstractions on image clustering, we compared different abstraction levels and achieved the optimal clustering results. For our algorithm, the average segmentation accuracy (SA), over-segmentation rate (OR), and under-segmentation rate (UR) of the crown are 91.21%, 3.54%, and 9.85%, respectively. The average values of the trunk are 92.78%, 8.16%, and 7.93%, respectively. Comparing the results of our method experimentally with other popular tree image segmentation methods, our segmentation method get rid of human interaction and shows higher SA. Meanwhile, this work shows a promising application prospect on visual reconstruction and factors measurement of tree.