Computer Network Security Defense Model

With the rapid development of the Internet industry, hundreds of millions of online resources are also booming. In the information space with huge and complex resources, it is necessary to quickly help users find the resources they are interested in and save users time. At this stage, the content industry’s application of the recommendation model in the content distribution process has become the mainstream. The content recommendation model provides users with a highly efficient and highly satisfying reading experience, and solves the problem of information redundancy to a certain extent. Knowledge tag personalized dynamic recommendation technology is currently widely used in the field of e-commerce. The purpose of this article is to study the optimization of the knowledge tag personalized dynamic recommendation system based on artificial intelligence algorithms. This article first proposes a hybrid recommendation algorithm based on the comparison between content-based filtering and collaborative filtering algorithms. It mainly introduces user browsing behavior analysis and design, KNN-based item similarity algorithm design, and hybrid recommendation algorithm implementation. Finally, through algorithm simulation experiments, the effectiveness of the algorithm in this paper is verified, and the accuracy of the recommendation has been improved.

influence of product quality and promotion on the purchase decision of NPK retail non subsidy fertilizer at PT. Pupuk Sriwidjaja Palembang in the South Sumatra Region

This study aims to determine the effect of product quality and promotion on purchasing decisions of retail non-subsidized NPK fertilizers at PT Pupuk Sriwidjaja Palembang in the South Sumatra region. The population in this study is the end-user, namely household food crops agricultural buyers of non-subsidized retail NPK fertilizers, both Pusri and other brands divided based on the harvest area in 2019 in South Sumatera Province many as 100 respondents using two-stage cluster random sampling technique as a sample determination. The multiple linear regression analysis results show that product quality positively and significantly affects purchasing decisions. The promotion has a positive and significant effect on purchasing decisions. Product quality is better to improve quality control of the production process and product quality, evaluate the standard of fertilizer bags used, evaluate the fertilizer distribution process, evaluate the implementation of fertilizer storage at GPP, and conduct socialization and education to kiosk. Promotions, giving direct gifts to farmers, conducting outreach activities, and meeting customers, Pusri officers in the field must be more proactive in visiting kiosk, providing scheduled soft skills training to Pusri officers.

EU ANTI-COVID POLICY IN THE WESTERN BALKANS

The pandemic generated by COVID-19 has brought new challenges for global politics. For this reason, the EU has been changing its policy towards the Western Balkans. The entire region is known to be engaged in the European integration process, which has received new issues associated with the COVID-19 pandemic. Therefore, the «Team Europe» package was launched on April 2020 to support EU partner countries in response to coronavirus and its consequences. This programme includes the most vulnerable countries of the European Neighborhood Policy, Africa and the Western Balkans. The core task was to back the health system and the socio-economic recovery of the partner states. In addition, the distribution of vaccines against COVID-19, called as «vaccine diplomacy», has become a peculiar policy area. The EU is vigorously involved in this process, especially allocating funds to the COVAX program and its internal distribution mechanisms. Consequently, the purpose of this study is to analyze the effectiveness of the EU anti-crisis policy in the Western Balkans. The article deals with the initial measures implemented by the EU to aid the countries of the region. Moreover, the author touches upon the issue of the launching of the EU’s vaccine distribution process.

USE OF PROPOSALITY MEASURES IN THE PROBLEM OF DISTRIBUTING THE PRODUCTION PROGRAM BY THE SCHEDULED PERIOD ON THE BASIS OF THE SIMILARITY OF THE SIMILARITY OF DAKE, JACKARD, MAXFEDOR, OTIA, RAO, TANIMOTO

The distribution of the production program of many production options for planned periods of various durations is relevant for modern production. The specificity of this production is that from the same parts, assemblies (assembly units), many modifications and sizes of products can be assembled to satisfy more consumers. The complexes of work on individual products is neither a repetition of each other, nor completely different, but have some similarities and individual differences, and the production time is less than the planned period. In the work, the authors expressed the opinion that if the duration of the production cycle is less than the planned period, then the structural and technological features of individual products cannot be ignored in the tasks of distributing the production program (volume-calendar planning tasks). This statement is erroneous. Using such specifics, it is possible to improve the economic indicators of such production, and we have shown in this paper. The combination of similar structural and technological products in separate planning periods increases the specialization of production in separate periods, reduces losses from equipment downtime, increases labor productivity and reduces the load on the operating manager by reducing the number of planning and accounting units in each period. In the work, proximity measures are proposed based on the known similarity coefficients, since it is more convenient to algorithmize the distribution process of the production program. The authors proved that the proposed measures correspond to the Frechet axiomatics.

EOQ Development Model in Optimize Raw Material Inventory

The purpose of this study was to determine the amount of safety inventory, order frequency, minimum inventory, maximum inventory limit, total Melon product inventory costs needed by PT. Rajawali Asia Bali uses the EOQ method. Data analyzed using the EOQ method shows that PT. Rajawali Asia Bali safety stock, it is very necessary to support the smooth distribution process that takes place. In accordance with the calculations with the formula, there is a safety stock that must be provided by PT. Rajawali Asia Bali is equal to 7,201 boxes. Planning for Sweet Corn products at PT. Rajawali Asia Bali using the EOQ method has 48.069 boxes.

Multi-UAV Cooperative Task Assignment Based on Half Random Q-Learning

Unmanned aerial vehicle (UAV) clusters usually face problems such as complex environments, heterogeneous combat subjects, and realistic interference factors in the course of mission assignment. In order to reduce resource consumption and improve the task execution rate, it is very important to develop a reasonable allocation plan for the tasks. Therefore, this paper constructs a heterogeneous UAV multitask assignment model based on several realistic constraints and proposes an improved half-random Q-learning (HR Q-learning) algorithm. The algorithm is based on the Q-learning algorithm under reinforcement learning, and by changing the way the Q-learning algorithm selects the next action in the process of random exploration, the probability of obtaining an invalid action in the random case is reduced, and the exploration efficiency is improved, thus increasing the possibility of obtaining a better assignment scheme, this also ensures symmetry and synergy in the distribution process of the drones. Simulation experiments show that compared with Q-learning algorithm and other heuristic algorithms, HR Q-learning algorithm can improve the performance of task execution, including the ability to improve the rationality of task assignment, increasing the value of gains by 12.12%, this is equivalent to an average of one drone per mission saved, and higher success rate of task execution. This improvement provides a meaningful attempt for UAV task assignment.

Short-Term Load Forecasting Based on the Transformer Model

From the perspective of energy providers, accurate short-term load forecasting plays a significant role in the energy generation plan, efficient energy distribution process and electricity price strategy optimisation. However, it is hard to achieve a satisfactory result because the historical data is irregular, non-smooth, non-linear and noisy. To handle these challenges, in this work, we introduce a novel model based on the Transformer network to provide an accurate day-ahead load forecasting service. Our model contains a similar day selection approach involving the LightGBM and k-means algorithms. Compared to the traditional RNN-based model, our proposed model can avoid falling into the local minimum and outperforming the global search. To evaluate the performance of our proposed model, we set up a series of simulation experiments based on the energy consumption data in Australia. The performance of our model has an average MAPE (mean absolute percentage error) of 1.13, where RNN is 4.18, and LSTM is 1.93.

Influence of pallet pattern on top-to-bottom compression performance of unitized loads

Environmental scaling factors estimate a corrugated container’s ability to withstand various conditions it will encounter during the storage and distribution process. In this project, we examined the compressive resistance of unitized loads using differing pallet stacking patterns. To simulate real-world failure scenarios in our laboratory tests, we used two different nominal board grades of single-wall C-flute regular slotted containers loaded with a plywood panel and bagged salt to direct the failure location to the bottom of the stack. Our results showed that the columnar aligned pattern provided the greatest compressive resistance and the interlocked stacking arrangement yielded the lowest of the patterns evaluated. Based on the study results, we calculated box compression retention multipliers for each pattern and compared them to scaling factors published by the Fibre Box Association.

Selling Sustainability

This study aims to evaluate the qualities required for sustainable clothing brands to succeed in an industry dominated by "fast fashion," an environmentally unfriendly manufacturing and distribution process. A number of cross-industry case studies were conducted, focusing on companies with sustainability built into their business models from several verticals. Our analysis found that the main reason for these businesses’ commercial success was not the fact that they were sustainable, but that they brought an innovative and marketable product that helped consumers. Their sustainability was not a selling point; instead, their products' benefits were, and we believe that sustainable businesses fail to do so. By marketing "coolness," the health benefits, luxury appeal, and clothing quality of Whole Foods Market, Tesla, and Patagonia allowed these brands to build extremely successful businesses, with sustainability benefits tacked on as a very positive externality. Generalizing, we claim that a sustainable fashion brand must be inexpensive, marketable, innovative, and profitable to find success in the fashion industry. We concluded that fashion companies should use advanced technology such as blockchain technology and biomimicry to create sustainable products that are appealing to the masses, mirroring the case studies above by providing outsized environmental benefits.

The Impact of the COVID-19 Pandemic on Food Distribution at Emergency Food Assistance Organizations in the Southwestern United States: A Qualitative Investigation

This study aimed to identify changes in food distribution operations at emergency food assistance organizations (EFAOs) during the COVID-19 pandemic. EFAOs across the Houston metro area, TX (human service centers and food pantries) as well as the Houston Food Bank (HFB) participated in the qualitative study. Data were collected via individual semi-structured interviews and focus group (December 2020–February 2021), and coded using semi-structured thematic analysis. Categories were pre-identified based on the interview questions. Direct quotes supported subcategories. Directors from 18 EFAOs were interviewed; 8 HFB leadership staff participated in a focus group. Four major categories of change due to COVID-19 included new safety measures, changes in food distribution process, changes in volunteerism and staffing, and changes in amounts of food distributed. This study helps identify susceptibilities in EFAOs’ food distribution chain should be addressed to manage future emergency food insecurity crises more effectively. An understanding of the changes/challenges incurred by EFAOs during the COVID-19 pandemic can inform policymakers to ensure local food distribution organizations are prepared to fill the needs during future a crisis of food insecurity.