bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Railway Mixed Goods Loading Layout considering Stability
Authors: Wang Juan , Yao Yinghua , Zhang Yinggui , Wang Ximing
Published: August 2022

It is well known that stability, center-of-gravity balance, and concentrated-weight are key factors of the transportation safety. The reasonable formulation of the loading layout scheme ensures the safety of shipment based on fully utilizing the effective volume and load capacity of freight vehicles. This paper takes the railway mixed goods loading layout as the research object, considering the constraints such as goods loading center-of-gravity balance, the allowable moment of concentrated-weight, supporting and goods placement mode, and taking the maximum comprehensive utilization rates for both effective volume and load capacity of freight vehicle as the optimization objective, an optimization model of railway mixed goods balanced and anticoncentrated-weight loading layout considering stability is built. Additionally, this paper designs mixed goods classified and simple/general goods block composition methods. We improve the representation and selection of layout space, construct goods block selection algorithm based on the greedy d-step lookahead tree search and goods block evaluation function and propose a goods block placement strategy and update rules of layout space after goods block placement. An optimization algorithm of railway mixed goods balanced and anticoncentrated-weight load layout considering stability is designed. The results show that the formulated scheme not only ensures that the goods meet the full support constraints, but also the comprehensive utilization rate of the effective volume and load capacity of the vehicle is not less than 89%, and the probability of meeting the loading center-of-gravity balance and allowable moment of concentrated-weight are as high as 99% and 99.47%, respectively. The proposed method realizes the balanced and anticoncentrated-weight loading of railway mixed goods, ensures the safe, stable, and efficient goods loading, and provides decision support for the safe loading layout of railway goods.
A Novel Energy Planning Scheme Based on PGA Algorithm and Its Application
Authors: Lv Xian-Long , Tang Shikai , Su Jia
Published: August 2022

In order to actively respond to the “14th Five-Year Plan,” the PGA algorithm is used to develop a new energy planning strategy in this paper. The project can make full use of my country’s abundant renewable energy resources, encourage energy conservation and reduction of emissions, improve the energy structure’s low-carbon level, support the development of smart green energy, and achieve ecological civilization construction. This solution can show users how much greenhouse gas emissions can be reduced through some environmental changes, as well as the basic issues of meeting the future energy needs. It can display the benefits, costs, and emissions data under different scenarios in the future and use the scenario demonstration method to show energy planning to make energy data more vivid. It allows people, technicians, and decision makers to understand what will happen to China’s carbon emissions over time in the next 15 years. This paper innovatively combines a particle swarm optimization algorithm with a genetic algorithm and designs a PGA algorithm for path optimization. In terms of carbon emission reduction, comparative trials demonstrate that the PGA algorithm’s path optimization is 58.06 percent greater than the genetic algorithm; In terms of cost, the PGA algorithm’s path optimization is 15.72% less expensive than the genetic algorithm’s. This article provides a reference path for selecting the best results for future energy planning schemes and provides a new strategy for the “14th Five-Year” energy plan.
[Retracted] The Black‐Box Deconstruction of Dynamic Sustainable Development Ability Driving Environmental Performance of Manufacturing Enterprises
Authors: Liu Qiang , Zhang Wanqian , Gao Ziwei , Yang Wei
Published: August 2022

Based on the conceptual model of the black‐box deconstruction of dynamic sustainable development ability driving environmental performance of manufacturing enterprises, the nonparametric percentile bootstrap method based on deviation correction is used to demonstrate the theoretical hypothesis and empirically deconstruct the black‐box of dynamic sustainable development driving environmental performance. Empirical results show that (1) dynamic sustainable development ability has a positive influence on environmental performance; (2) green resource integration ability, green duality, low‐carbon manufacturing practice, and green intelligence capital play mediating roles in the influence of dynamic sustainable development ability on environmental performance; and (3) environmental regulation positively moderates the mediating mechanism of green resource integration ability, green duality, low‐carbon manufacturing practice, and green intelligence capital of the relationships between dynamic sustainable development ability and environmental performance.
Effect of Dwell Time on Fracture Load of Friction Stir Spot Welded Dissimilar Metal Joints
Authors: Sathyaseelan P. , Manickavasagam V. M. , Ravichandran P. , Prasad D. V. S. S. S. V. , Ramana Murty Naidu S. C. V. , Pradeep Kumar S. , Ahmad Khan Ateeb , Karthik R. , Kerga Gizachew Assefa
Published: August 2022

The dissimilar materials joining in heavy structural fabrication industries is tedious work for welding and design engineers, since the weld region’s criticality is encountered by hot cracking and its associated problems. Moreover, dissimilar materials are joined by mechanical locking such as rivets, bolt and nuts, and screws. Nowadays, the fasteners are eliminated by friction stir welding (FSW). The friction stir spot welding (FSSW) is a variant of FSW; it can be avoided by seam welding. Hence, in this investigation, FSSW is used for joining AA6061 aluminum alloy with mild steel using tool rotation speed, plunge depth and rate, and shoulder to pin diameter ratio. The experimental method observed that the joint fabricated with a rotational speed of 1000 rpm, plunge rate of 5 mm/min, plunge depth of 6 mm/min, and shoulder diameter to pin diameter ration of 3.0 yielded highest fracture load The optimum heat input could obtain the improvement in FSSW joint strength. Recrystallized grains and favorable intermetallic compound formation are the primary factors for sound welding.
Performance Evaluation of Laboratory Management System Based on BP Neural Network
Authors: Su Anjie , Wu Zhigang , Yin Yifeng
Published: August 2022

Due to the lack of scientific performance evaluation methods and effective performance management, many tax authorities’ performance evaluation and performance management are not perfect. The BP neural network has strong nonlinear mapping, self‐learning, and self‐adaptive abilities. It has been widely used in the field of numerical prediction and pattern recognition. Based on the exploration of neural network, this paper combines BP neural network with performance evaluation and applies BP neural network to the performance evaluation of university laboratories. Data envelopment analysis (DEA) is mainly used to evaluate the performance of other fields. This paper selects key laboratories as the research object. The performance evaluation of university laboratories based on BP neural network is studied. The existing laboratory evaluation system is scientifically and reasonably revised, reasonable scientific methods are introduced, and a complete and scientific evaluation scheme suitable for the current evaluation requirements is explored. This paper perfects the evaluation method system, so as to scientifically and reasonably allocate research resources, which can maximize the enthusiasm of research departments.
Dynamic Evaluation of Intensive Land Use Based on Objective Empowerment by Entropy Method and Neural Network Algorithm
Authors: Yang Ting , Cheng Hanlie , Zhao Hailian , Cadasse David
Published: August 2022

In the past, the extreme value standardization of indicators, the traditional weighting method, and the multifactor comprehensive model of land intensive use inevitably linearly correlate the evaluation indicators with the evaluation objects, ignoring the direction differences of different indicators in different intervals. At the same time, these methods are also difficult to meet the change of evaluation index weight value with land use type, and cannot adapt to the actual situation of land use environment level and dynamic change. Considering the objectivity of nonlinear correlation moderate index and weight assignment, based on the standardization of quadratic function index and entropy assignment, this paper studies the intensive and dynamic use of land in development zones by different regions to improve the realistic fit of the evaluation model. The results show that the overall level of land intensive use in Chongqing center district and western Chongqing is better than that in northeast Chongqing and southeast Chongqing, roughly showing the state of “high in west and low in east.”
Real‐Time Evaluation of Cerebral Autoregulation Based on Near‐Infrared Spectroscopy to Predict Clinical Outcome after Bypass Surgery in Moyamoya Disease
Authors: Kim Junmo , Ha Eun-Jin , Kim Hee-Soo , Park Eun-Young , Lee Hyung-Chul , Choo Yoon-Hee , Shim Youngbo , Kim Kwangsoo , Kim Keewon , Lee Seung-Bo
Published: August 2022

Impaired cerebral autoregulation (CA) can cause negative outcomes in neurological conditions. Real‐time CA monitoring can predict and thereby help prevent postoperative complications for neurosurgery patients, especially those suffering from moyamoya disease (MMD). We applied the concept of moving average to the correlation between mean arterial blood pressure (MBP) and cerebral oxygen saturation (SCO2) to monitor CA in real time, revealing optimal window size for the moving average. The experiment was conducted with 68 surgical vital‐sign records containing MBP and SCO2. To evaluate CA, the cerebral oximetry index (COx) and coherence obtained from transfer function analysis (TFA) were calculated and compared between patients with postoperative infarction and those who without. For real‐time monitoring, the moving average was applied to COx and coherence to determine the differences between groups, and the optimal moving‐average window size was identified. The average COx and coherence within the very‐low‐frequency (VLF) range (0.02‐0.07 Hz) during the entire surgery were significantly different between the groups (COx: AUROC = 0.78, p = 0.003; coherence: AUROC = 0.69, p = 0.029). For the case of real‐time monitoring, COx showed a reasonable performance (AUROC > 0.74) with moving‐average window sizes larger than 30 minutes. Coherence showed an AUROC > 0.7 for time windows of up to 60 minutes; however, for windows larger than this threshold, the performance became unstable. With an appropriate window size, COx showed stable performance as a predictor of postoperative infarction in MMD patients.
Green Supply Chain Management Model of e-Commerce Enterprises Based on SCOR Model
Authors: Zhou Zhimin
Published: August 2022

With the rapid development of e-commerce technology, e-commerce enterprises, especially B2C enterprises, have sprung up. This competition based on e-commerce technology has changed the traditional supply chain model and improved the operation efficiency of the supply chain. However, with the use of e-commerce technology, the supply and demand relationship between e-commerce enterprises has become extremely complicated. The original risk management system in the past has long been unable to adapt to the development needs of e-commerce enterprises in the new era. In view of this, it has far-reaching practical significance to actively carry out research on supply chain risk management for e-commerce enterprises, especially for B2C enterprises. In this research, on the premise of some previous theoretical and practical results, a B2C enterprise supply chain risk identification model is established by means of the research on SCOR, namely, the supply chain operation mode, combined with the characteristics of the B2C enterprise supply chain. The comprehensive evaluation method is used to evaluate the supply chain risk. Finally, an empirical study is carried out with J Company, which represents the B2C enterprise, as an example, which proves the applicability and reliability of this model. The results of this study have a certain reference value for the identification and control of B2C enterprise supply chain risks and also an inspiration for future research.
Research on Literature Clustering Algorithm for Massive Scientific and Technical Literature Query Service
Authors: Zhang Chen
Published: August 2022

Traditional science and technology literature search mainly provides users with reliable and detailed information materials and services through technical means, data resources, and service strategies. With the development of network technology, computer technology, and information technology, digital information resources are increasing day by day, which continuously impact the traditional knowledge service mode. Some traditional technical methods and service means can no longer meet the information needs of users under large data sets. This paper proposes a model of large-scale literature search service in the context of big data by studying the technical means and service modes used for scientific and technical literature search in universities in the era of big data. Specifically, this paper proposes a method for fast literature retrieval by combining R-tree indexing for the characteristics of diverse data types and large data volume of science and technology literature. The method uses an improved k-mean clustering algorithm to construct an R-tree clustering model and improve the retrieval efficiency of the system by retrieving scientific and technical literature data through R-tree indexing. Experiments on university science and technology literature datasets show that the method in this paper improves both efficiency and precision when searching literature.
Performance of Ferroelectric Materials in the Construction of Smart Manufacturing for the New Infrastructure of Smart Cities
Authors: Zhou Minggui , Yan Gongxing
Published: August 2022

Smart city construction is the inevitable product of scientific development and transformation of life by building digital cities, building the Internet of Things, and making city management systems simple and intelligent through cloud computing. Smart city is a new generation information technology. Make full use of the advanced form of urban informatization based on the next generation innovation of knowledge society in all walks of life in the city. Cloud computing is a new network application concept. The core concept of cloud computing is to take the Internet as the center, and provide fast and secure cloud computing services and data storage on the website, so that everyone who uses the Internet can use the huge computing resources and data center on the network. The role of smart city engineering infrastructure is to build the infrastructure of this platform, so that smart cities can operate effectively, such as deformation test of ferroelectric materials, particle suitability analysis of ferroelectric materials, etc., This research is oriented to the intelligent manufacturing of new infrastructures in smart cities and analyzes the performance of ferroelectric materials in construction, aiming to better grasp the performance of ferroelectric materials and provide constructive suggestions for smart manufacturing in smart cities. The article first understands and states the related concepts, related construction requirements, development status and problems that need to be solved for smart city smart manufacturing by consulting relevant materials; then, it discusses the ferroelectric materials involved in the construction, analyzes the data of piezoelectric properties, etc., which will help to give more clear guidance on the process of tooling design; finally, the application link of ferroelectric materials is tested, and the deformation of ferroelectric materials and this premise are discussed on the problem of intelligent manufacturing efficiency and intelligent manufacturing efficiency. The experimental results show that the maximum value in the group of smart manufacturing benefits is 559.37; the maximum value between groups is 172.35. For efficiency of smart manufacturing, the maximum value between groups reaches 187.07; the maximum value in groups is 286.35. Whether it is a significant analysis of smart manufacturing benefits or smart manufacturing efficiency, the experimental results are quite impressive.
Movie Box Office Prediction Based on IFOA‐GRNN
Authors: Lu Wei , Zhang Xiaoqiao , Zhan Xinchen
Published: August 2022

Predicting movie box office has received extensive attention from academia and industry. At present, the main method of forecasting movie box office is subjective prediction, which is not widely accepted due to its accuracy and applicability. This study improves the fruit fly algorithm to optimize the generalized regression neural network (IFOA‐GRNN) model to predict whether a movie can become a high‐grossing movie. By using the actual box office data and performing virtual simulation calculations, the root means square error of the IFOA‐GRNN model predicting the movie box office is 0.3412, and the classification accuracy is about 90%. By comparing this model with FOA‐GRNN, KNN, GRNN, Random Forest, Naive Bayes, Ensembles for Boosting, Discriminant Analysis Classifier, and SVM, it is found that the prediction effect of the IFOA‐GRNN model is significantly better than the above eight models. The contribution of this article is to propose a generalized regression neural network model based on an improved fruit fly optimization algorithm, which can greatly improve the accuracy of movie box office prediction.
Analysis of Multimodal Teaching of College English under the Background of Artificial Intelligence
Authors: Niu Lu
Published: August 2022

As the Internet drives the spread of digitalization and the further improvement of computing power, the traditional college English teaching mode can no longer adapt to the needs of teaching in the age of artificial intelligence. Single or lesser modality is gradually replaced by multimodality, an emerging teaching mode. The study of multimodal discourse is a new hot spot in language research and a key issue of concern for English classroom teaching reform. Based on the analysis of the practical application dilemmas of multimodality in college English teaching culture, context, content (meaning + form), and expression, this article proposes a path to innovate multimodal discourse teaching in college English classroom in the era of artificial intelligence. It includes familiarizing with multimode integrated platform for teaching tools and developing intercultural communication abilities. Multimode situational lectures with the help of modern information technology are developed. At the content level, we should adhere to the unity and coordination of the meaning and form of multimodal teaching. Use language and nonlanguage in a way that will enhance learning at the multimode media level. Additionally, AI enriches English teaching methods, changes the intelligence of English teachers, and improves the efficiency of English teaching. AI helps to create a more relevant and interactive English learning environment, improve many aspects of English teaching, including teaching evaluation, and effectively improve the face of college English teaching.
Human Behavior Recognition Method Based on Edge Intelligence
Authors: Sun Yongxia , Jiang Weijin
Published: August 2022

The increasingly intelligent video surveillance system is the certain result of the gradual maturity of information technology. Human behavior recognition is one of the important tasks in the area of intelligent security monitoring. This paper proposes a human behavior recognition mechanism that uses edge‐cloud collaborative computing. Firstly, at the edge node N0, the video is preprocessed to remove similar frames and the extracted skeleton sequence is expressed in multiple levels. Then the cloud trains the spatial‐temporal graph ConvNet model and deploys it to the edge nodes N1 ~ Nm. The edge uses the trained model to complete behavior recognition tasks and uploads the results to the cloud for fusion to obtain the final behavior category. The experimental results prove that the advantages of edge‐cloud collaboration have made the model recognition accuracy rate steadily increase by more than 2.2%.
Legal Path of Rural Revitalization for Decision-Making Risk Prevention of Internet of Things Algorithm
Authors: He Wenqiang , Ding Haolun
Published: August 2022

The implementation of the rural revitalization strategy is an important strategic plan to solve the social “three rural” problems on the new road of building a socialist modernized country in an all-round way. It is also the current society to promote the comprehensive rule of law and to create and improve a modern rural social governance system under the leadership of the party committee, the government is responsible, the society is coordinated, and the country is governed by law. However, due to the wide distribution of rural areas and the large population base of farmers, there are many risks in the implementation of the rural revitalization strategy. In the comprehensive use of economic, administrative, and legal means, legal means has become the key. For this reason, this article conducted in-depth research on the legal path of rural revitalization under the risk prevention of Internet of Things algorithm decision-making. The research results showed that the risk prevention of Internet of Things algorithm decision-making was introduced into the research on the legal path of rural revitalization, and a sound rural governance system that combined autonomy, rule of law, and morality is an important part of the revitalization of seven villages. It can improve the 2.67% effectiveness of risk prevention in decision-making and can also play a key role in ruling the country according to law, showing the correct direction of agricultural legal system construction and at the same time high-level rural construction and development under the framework of the rule of law. It will vigorously promote the comprehensive modernization of agriculture, the comprehensive progress of rural areas, and the revitalization and development of rural areas.
Experimental Investigation and Optimization of Material Removal Rate and Tool Wear in the Machining of Aluminum-Boron Carbide (Al-B4C) Nanocomposite Using EDM Process
Authors: Arunnath A. , Madhu S. , Tufa Mebratu
Published: August 2022

Electrical discharge machining (EDM) is a cost-effective unconventional machining method used for machining any composites materials. EDM is based on the thermoelectric energy between the electrode and workpiece. In this work, boron carbide particles of 50 nm (6 wt.%) are reinforced with aluminum 7075 (94 wt.%) prepared using stir casting method. The stir casting process is carried out at speed of 700–800 rev/min. The fabricated aluminum-boron carbide nanometal matrix composites are used as workpiece (anode); copper electrode is used as tool (cathode). This work investigates the influence of EDM process parameters such as current (I), pulse on-time (ton), and tool diameter (d) during machining of Al-B4C composite on metal removal rate (MRR) and tool wear rate (TWR). The design of experimental plan is executed by Taguchi approach, and the responses of each parameter are influenced by analysis of variances (ANOVA). Response table for average value of MRR and TWR shows that the current is the significant parameter affecting MRR and TWR. From this work, it was observed that material removal rate increased with increasing the current, and the tool wear rate decreases.
A Resource Scheduling Method for Enterprise Management Based on Artificial Intelligence Deep Learning
Authors: Zhu Lujie , Huang Li
Published: August 2022

Under the current trend of economic globalization and international competition, more and more production enterprises are introducing the project management model, that is, customer or order projection, and using the concept of project management to manage operations. In an enterprise, there are multiple customers at the same time, and the production line can also generate multiple orders from different customers at the same time. That is to say, multiple projects are running at the same time, resulting in continuous changes in management processes, heavy project coordination tasks, and a serious waste of corporate resources. The resources that can be used are limited. In the production business using project management, how to rationally utilize the limited business scheduling resources has become the focus of research. Aiming at the method of business management resource scheduling, this paper investigates the application of enhanced particle swarm algorithm on the cloud deep learning platform, and the mapping problem between virtual machines and physical machines. As a heuristic algorithm, particle swarm optimization is suitable for solving combinatorial optimization problems. By improving the diversity of particle hosts and setting parameters, it improves the integration speed and accuracy of the algorithm. Through the analysis of the current situation of multi-project business management, it examines the allocation of resources. In terms of business management, it has established a resource allocation model for multiple projects. The results show that the method improves the efficiency of the enterprise by 35% compared to the traditional method with a 20% reduction in personnel. A better configuration scheme is simulated by MATLAB, which verifies the scientificity and effectiveness of the method studied in this paper.
Neural Network Model of Dynamic Prediction of Cross-Border E-Commerce Sales for Virtual Community Knowledge Sharing
Authors: Guan Hui
Published: August 2022

The current popular one with forecasting method simply studies for prediction, and insufficient consideration is given to the prediction of the evolution of product sales applied to Internet platforms. To improve the forecast effect and to realize the usage of the forecasting in line with “Internet+” surroundings, the product sales controllable correlation mining, personalized forecasting ways of counting, improve counting, and other corresponding algorithms, a “Internet + foreign trade” concept based on the controllable correlation comes up with the model of mobile prediction. The result can show that the sample has the opening features and dynamics of “Internet+” to prerealize the dynamic, intelligent, and quantitative qualitative prediction of export product sales based on the controllable correlation big data of cross-border e-commerce in the “Internet + foreign trade” environment. The comprehensive prediction effect of this model is obviously better than that of traditional models and has strong evolution and high practical value. This thesis has the benefits for promoting the technological development of cross-border e-commerce and making us cross the cross-border e-commerce industry.
Prediction and Influencing Factors of Big Data on College Students’ Positive Psychological Quality under Mobile Wireless Network
Authors: Jiang Li , Zhang Yizhe
Published: August 2022

Psychological big data is observed based on behavior or habitual features of people for determining the influencing factors. The influencing factor information is used for analysis in treatment, recommendation, and diagnosis of psychological disorders, depression, etc. Identifying the influencing factors is challenging due to irregular behaviors and responses from young people. However, for organizing the quality of observation, this article introduces a behavioral pattern recognition method (BPRM) with associating quality (AQ) identification. This method observes the different day-to-day behaviors of young people and recurrently associates them. The observations are aided through conventional wireless networks for swift interconnection and information sharing. The association is organized based on the transfer learning state processing model. Based on the state processing, the behavior-based psychological data are classified as abnormal and normal. If the association throughout the state changes remains the same, then it is organized or else the new data are identified as an influencing factor. The state changes are validated using random observation intervals that result in series data associations. Based on the actual data extraction, the proposed method improves the prediction accuracy and reduces false rate and processing time, whereas it improves the organization precision.
Qizhi Kebitong Formula Ameliorates Streptozocin‐Induced Diabetic Osteoporosis through Regulating the PI3K/Akt/NF‐κB Pathway
Authors: Tian Lulu , Ding Lu , Wang Guoqiang , Guo Yu , Zhao Yunyun , Wei Yuchi , Li Xingquan , Zhang Wei , Mi Jia , Li Xiangyan , Wang Zeyu , Wang Xiuge
Published: August 2022

Background. Diabetic osteoporosis (DOP) is a progressive osteoblast dysfunction induced by high glucose, which has negative impacts on bone homeostasis. Qizhi Kebitong formula (QKF) is a traditional Chinese medicine (TCM) formula for treating DOP. However, its role in the protection of DOP has not been clarified yet. Here, we aimed to explore the potential mechanisms of QKF on DOP development via in vivo experiment. Methods. Network pharmacology was used to detect the key targets and signaling pathways of QKF on DOP. The effects of QKF on DOP were examined by the phenotypic characteristics, micro‐CT, and hematoxylin‐eosin (H&E) staining. The predicted targets and pathways were validated by a streptozocin‐ (STZ‐) induced mouse model. Subsequently, the levels of the selected genes and proteins were analyzed using qRT‐PCR and Western blot. Finally, AutoDock and PyMOL were used for molecular docking. Results. In this study, 90 active compounds and 2970 related disease targets have been found through network pharmacology. And QKF could improve the microstructures of femur bone mass, reduce inflammatory cell infiltration, and downregulate the levels of TNF‐α, IKBKB, IL‐6, and IL‐1β. Moreover, the underlying effect of PI3K/Akt/NF‐κB pathways was also recommended in the treatment. Conclusion. Altogether, our findings suggested that QKF could markedly alleviate osteoblast dysfunction by modulating the key targets and PI3K/Akt/NF‐κB signaling pathway.
Color Enhancement Algorithm for Visual Communication Posters Based on Homomorphic Filtering
Authors: Xu Jing , yuqing Hu
Published: August 2022

In order to increase the image quality of visual communication posters and to solve the problems of uneven pixel distribution, distortion, and poor visual effect caused by the lighting environment, an image filtering method, with features based on wavelet and block homomorphic, is proposed on the basis of homomorphic filtering. According to the component change defect of red, green, and blue (RGB) color space, the image color space that needs to be processed is converted into HSV form and then processed in blocks. At that moment, the wavelet transform method is applied to replace the traditional Fourier transform in the block homomorphic filtering to decompose the luminance component. Furthermore, subimages that are decomposed by the wavelet are divided into blocks and then subjected to high-pass filtering so as to obtain a clear image. The investigational outcomes express that the proposed algorithm has an obvious enhancement effect on the visual communication poster image under the variable illumination situation. Furthermore, the suggested technique effectively rectifies the overall brightness of the image and significantly advances the detail contrast of the visual communication poster image. The signal-to-noise (SNR) ratio of our algorithm at different bit rates is higher than that of the LICE and CIE methods. Similarly, the enhancement impact demonstrates that the image statistical parameters of our algorithm are substantially better than those of the LICIE and CIE methods.
Pharmaceutical Effluent Treatment Using Multi-effect Evaporator Process
Authors: Periyannan R. , Arun Prasad J. , Arulmozhi S. , Balaji M. , Gopalan A. , Banu Priya N. R. , Shanthi P. , Shanmugavadivel G. , Anukarthika B. , Santino David Ladu Nyagong
Published: August 2022

The disposal practices of pharmaceutical-generated pollutants have become a serious threat to mankind’s health, safety, and environmental concerns. Pharmaceutically polluted effluents have been demonstrated as endocrine disruptors which mimic growth hormones when consumed at nG/L to mG/L concentrations. The production stages utilize both organic and inorganic compounds, which contribute to chemical oxygen demand (COD) and total dissolved solids (TDS) heavily. Conventional technologies have failed to accomplish zero liquid minimization. To achieve zero minimization, it is necessary to develop modernization techniques in effluent treatment streams. A novel technique to recover solids and organic matter removals as well as zero-liquid discharge (ZLD) flash mixer, stripping, and multi-effect evaporator (MEE) processes is employed. Flash mixing is a pre-treatment stage, and stripping enables solvent reclamation. The multi-effect evaporators involve heat transfer equipment mainly used for volume reduction and cutting down on waste handling costs. The multi-effect evaporator not only is able to eliminate pharmaceutical xenobiotics but also requires pre-treatments such as flash mixture and stripping column sections. Thus, this research emphasizes efficiently removing high total dissolved solids (HTDS) and high chemical oxygen demand (HCOD) from pharmaceutical effluent. The removal efficiency was found to be 85% for TDS and TSS, 93% for BOD, and 81% for COD, which is more than the conventional mode of treatment.
Factors Affecting Chinese Short‐Term International Students’ Cross‐Cultural Adaptation in Psychology, Learning, and Life
Authors: Zhang Haiyan , Li Mingsheng
Published: August 2022

Although Chinese international students’ cross‐cultural adaptation has achieved intense research, factors in developing Chinese SISs’ cross‐cultural adaptation remain underresearched. This study examined the factors through a survey of Chinese SISs’ transitional adaptation in psychology, life, and learning. Mixed‐method research was conducted: a survey of 155 SISs from a top Chinese university undertaking study across 16 countries and in‐depth interviews with 15 SISs. Results indicate that knowledge of the host country and university, language proficiency, sense of participation, and engagement are the crucial factors in developing Chinese SISs’ cross‐cultural adaptation. These factors reveal significant correlations with the students’ adaptive performances in psychology, life, and learning. However, the factor of duration indicates no significant correlation with students’ cross‐cultural adaptation, which demonstrates an inconsistency with the previous studies. The findings of this study highlight the need for developing Chinese SISs’ sense of engagement, enhancing the language training, and building up the knowledge of the host cultures previous to the study abroad.
An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health
Authors: Wahab Fazal , Zhao Yuhai , Javeed Danish , Al-Adhaileh Mosleh Hmoud , Almaaytah Shahab Ahmad , Khan Wasiat , Saeed Muhammad Shahid , Kumar Shah Rajeev
Published: August 2022

E-health has grown into a billion-dollar industry in the last decade. Its device’s high throughput makes it an obvious target for cyberattacks, and these environments desperately need protection. In this scientific study, we presented an artificial intelligence (AI)-driven software-defined networking (SDN)-enabled intrusion detection system (IDS) to address increasing cyber threats in the E-health and internet of medical things (IoMT) environments. AI’s success in various fields, including big data and intrusion detection systems, has prompted us to develop a flexible and cost-effective approach to protect such critical environments from cyberattacks. We present a hybrid model consisting of long short-term memory (LSTM) and gated recurrent unit (GRU). The proposed model was thoroughly evaluated using the publicly available CICDDoS2019 dataset and conventional evaluation measures. Furthermore, for proper validation, the proposed framework is compared with relevant classifiers, such as cu-GRU+ DNN and cu-BLSTM. We have further compared the proposed model with existing literature to prove its efficacy. Lastly, 10-fold cross-validation is also used to verify that our results are unbiased. The proposed approach has bypassed the current literature with extraordinary performance ramifications such as 99.01% accuracy, 99.04% precision, 98.80 percent recall, and 99.12% F1-score.
Structural Behaviour of Metakaolin Geopolymer Concrete Wall-Type Abutments with Connected Wing Walls
Authors: Verma Parth , Dhurvey Priyanka , Sundramurthy Venkatesa Prabhu
Published: August 2022

This study work is related to exploring the role of connected wing walls in changing the behaviour of a metakaolin geopolymer wall type abutment when acted upon by all the forces that are generally applied on a short-span bridge. The modelling of abutment with connected wing walls is done using the STAAD Pro V8i SS6 software and all the loading applied for the analysis as per IRC: 6-2016. The modelling is done using the 4-noded plate elements for all the members, and the plate elements here are meshed using the quadrilateral meshing feature. The behaviour of the metakaolin geopolymer wall-type abutment is analyzed using various models with changing the basic parameters such as length of the wing walls, height of the walls, number of lanes on the bridge, and type of live load on the bridge. The various results are obtained in the form of bending moments from all the cases, which show us some really interesting behaviour of the abutment wall and the wing walls. As the length of the wing walls is increased, they take up more horizontal moments than the abutment wall and the deflection behaviour of the wing walls is way different than that of cantilever wall, and hence, it shows that the design aspects of the wing walls need to be checked. Also, the connected wing walls cause horizontal moments in the middle of the abutment wall, which is an interesting result; as now, it proves that after casting wing walls monolithically to the abutment wall, the design of the abutment wall cannot be done as cantilever wall, and we need to take care of this horizontal moment by providing required reinforcement. Also, as the length of the wing walls is short, the torsional moments become critical.
Effect of Microstructure on the Corrosion Fatigue Crack Growth of Low and Medium Steels
Authors: Wang Jing , Zhang Yan , Yu Chunting , Zhao Bo
Published: August 2022

This article studies the effect of microstructure on the corrosion fatigue crack growth behavior of low and medium carbon steels. 45 steel and 15CrMo were selected and five typical microstructures were obtained by different heat treatment processes. The microstructures of 45 steel and 15CrMo after annealing and normalizing are both ferrite and pearlite, but the proportions of ferrite and pearlite in the four microstructures are different. The quenching and tempering microstructure of 45 steel is tempered fine pearlite. Corrosion fatigue tests were conducted on specimens with different microstructures of the two materials. Expressions of corrosion fatigue crack growth rate and da/dN∼ΔK fitting curves of different microstructures were obtained. Comparison of da/dN∼ΔK curves of 45 steel shows that tempered fine pearlite has the best resistance to corrosion fatigue crack growth, and the content of pearlite has a great impact on the corrosion fatigue crack growth behavior for specimens with the microstructure of ferrite and pearlite. In the low ΔK region, the corrosion factor plays a dominant role in fatigue crack growth, and the corrosion resistance of pearlite is weak, which leads to a higher da/dN in the normalized state. In the high ΔK region, fatigue factor dominants, since the fatigue resistance of pearlite is strong, da/dN of the annealed state is higher. The experimental results of 15CrMo showed the same crack growth rate change regulation as that of 45 steel, which further proves the effect of pearlite on the corrosion fatigue crack propagation behavior.
Molecular Dynamics Simulation Calculation Method for Elasticity and Plasticity of Metal Nanostructures
Authors: Zeng Kunrong , Chen Kaifeng
Published: August 2022

With the rapid development of nanotechnology, surface plasmon (SP) of metal nanostructures has become one of the research hotspots in the research of information science, physics, biology, materials science, chemistry, and other interdisciplinary fields. Surface plasmon research is an emerging discipline. In this paper, based on the CPU algorithm and the GPU algorithm for the extraction of pressure and single-atom average potential energy, time tests and error analysis of different molecular scales are carried out. The analytical results show that the absolute and relative errors of pressure and single-atom average potential energy extraction increase with the molecular scale. When the molecular scale reaches 100k, the errors of pressure and single-atom average potential energy reach 0.32 and 0.052, respectively. However, compared with the pressure and single-atom average potential energy extracted by the CPU algorithm, the error of the results extracted by the GPU algorithm is only 1.55% and −1.45%.
[Retracted] Effect of Blood Homocysteine on the Outcome of Artificial Insemination in Women with Polycystic Ovary Syndrome
Authors: Cao Jing , Wang Haiyan
Published: August 2022

Background. Polycystic ovary syndrome (PCOS) is the major reason for women’s low fertility and the most frequent endocrine disorder in women of childbearing age. Homocysteine is an amino acid that contains sulfur that has been negatively correlated with the reproductive outcome of polycystic women treated with IVF/ICSI. However, the impact of blood homocysteine levels on the outcome of artificial insemination in polycystic ovary syndrome women is unknown. The goal of this study is to examine the impact of serum homocysteine on the result of intrauterine insemination in females who have polycystic ovary syndrome (PCOS). Methods. 96 infertile women (129 cycles) treated with artificial insemination were collected, including 66 cases (87 cycles) in the case group (PCOS group) and 30 cases (42 cycles) in the control group (male factor infertility). The differences in general data amongst two groups, such as BMI, Hcy, and age, were compared. The case group has been classified into two groups based on serum Hcy level: LHcy group (Hcy < 15) and HHcy group (Hcy ≥ 15). The relationship among pregnancy and serum Hcy level outcome in PCOS women was compared. Results. The PCOS group had substantially increased serum homocysteine levels in comparison to the control group (P = 0.019). Among PCOS women, the clinical pregnancy rates of artificial insemination in the HHcy group and LHcy group were 14.29% and 37.88%. The difference among the two groups was substantial (P = 0.044). Artificial insemination frequency, ovulation induction, BMI, infertility years, AMH, serum testosterone, HOME IR, TSH, TPOAb, hCG, daily follicle size, intimal thickness, and other factors did not differ greatly between the two groups. Conclusion. Serum homocysteine levels are increased in women having PCOS. Their levels above the threshold will lower the clinical pregnancy rate of intrauterine insemination in PCOS women.
Monte Carlo Simulation of Static and Dynamic Properties of Linear Polymer in a Crowded Environment
Authors: Umeta Deme Tesfaye , Asfaw Solomon Negash , Didu Solomon Hailemariam , Feyisa Chimdessa Gashu , Feyisa Dereje Kenea
Published: August 2022

In this paper, we investigate the static and dynamic properties of linear polymer in the presence of obstacles. A Monte Carlo (MC) simulation method in two dimensions with a bond fluctuation model (BFM) was used to achieve this goal. To overcome the entropic barrier, we put the middle monomer of the polymer in the middle of the pore, which is placed between ordered and disordered obstacles. We probed the static properties of the polymer by calculating the mean square of the radius of gyration and the mean square end-to-end distance of the polymer, and we found that the scaling exponents of both the mean square end-to-end distance

R

2

and the mean square radius of gyration

R

g

2

as a function of the polymer length

N

vary with the area fraction of crowding agents,

ϕ

. The dynamic properties have also been studied by exploring the translocation of the polymer. Our current research shows that the escape time

τ

increases as

ϕ

increases. Moreover, in the power-law relation of escape time

τ

as a function of polymer length

N

, the scaling exponent (

α

) changes with

ϕ

. Furthermore, the study has shown that the translocation of the polymer favors the disordered barriers.
Intelligent Time Allocation for Wireless Power Transfer in Wireless-Powered Mobile Edge Computing
Authors: Dong Xiaogang , Wan Zheng , Deng Changshou , Wen Wenying , Luo Yuxuan
Published: August 2022

Wireless-powered mobile edge computing is a new network computing paradigm that combines with the advantages of wireless power transfer and mobile edge computing. When the harvest-then-offload protocol is adopted in this network, the time of wireless power transfer has a significant impact on system performance. If the time is too short, the user cannot harvest enough energy. If it is too long, the user will not have enough time to complete the task offloading. Both result in many of user tasks being discarded. To address this problem, DEWPT, a differential evolution-based optimization scheme for wireless power transfer time, is proposed in this paper. DEWPT is designed with a hybrid mutation operator and a perturbation-based binomial crossover operator. The hybrid mutation operator combines the benefits of two mutation operators with distinct characteristics, so that DEWPT not only has a strong exploration ability but also can quickly converge. Meanwhile, the perturbation-based binomial crossover operator improves DEWPT’s ability to exploit local space. These two improvements effectively enhance DEWPT’s optimization performance, which is beneficial to find the optimal time for wireless power transfer. Furthermore, to improve the optimization efficiency, micro-population is introduced into DEWPT. Finally, the computation completion ratio maximization model is used to validate the performance of DEWPT in the wireless-powered mobile edge computing network with multiple edge servers. Numerical results show that the computation offloading scheme integrating with DEWPT can achieve a higher computation completion rate than three benchmark schemes, and is competitive in complexity. This demonstrates that DEWPT is an effective time allocation scheme for wireless power transfer.