Full Use Of Limited Resources Research Articles

Macroeconomic regulators of functioning of agro-industrial complex of the Republic of Kazakhstan: key directions

The goal is to develop effective tools for macroeconomic policy for the innovative development of AIC of the republic. Methods – abstract-logical, economic-statistical, system approach, comparative analysis. Results - the article shows the role of agro-industrial complex in achieving strategic goals: ensuring food security, increasing export potential, increasing the competitiveness of market entities on domestic and foreign markets. The evolution of agricultural industry in economically developed countries is considered: inter-sectoral cooperation, effectiveness of specialization, cooperation, production and economic ties during integration. The features of agro-industrial production and the key problems of its development are presented. The main factors constraining the strengthening of innovation and investment orientation of enterprises in the system of measures aimed to achieve full use of limited resources have been identified. Ways to form macroeconomic environment are proposed - necessary condition for stimulating entrepreneurial activity. The place and importance of total expenditures in solving the assigned tasks, the state budget deficit and methods of financing, methods of regulating banking, new monetary policy, tax and insurance systems and directions for their improvement, main components of transformation of agricultural sector into national innovation system are outlined. Conclusions - the strategic course towards innovative processes in agriculture is determined by global and domestic trends, the use of the latest resource-saving technologies and their rational use, contributes to stable increase in the level of domestic consumption, reduction in import volumes due to substitution of domestic food products. The article was written based on the research results on the project: AR19678876 “Effective system of macroeconomic instruments for state regulation of innovative development of AIC of the RK.”

Replacement of plant communities altered soil bacterial diversity and structure rather than the function in similar habitats of the Yellow River Delta, China

Convergent evolution in plants has important roles in understanding the coexistence of species and the construction of communities in the same habitat. However, evidence that determines whether this phenomenon also occurs in soil bacteria is lacking. In this study, the communities of Suaeda salsa, Phragmites australis, and Tamarix chinensis on the same succession sequence in the supratidal habitat of the Yellow River Delta are taken as research objects. 16S rRNA high-throughput sequencing technology was used to test the diversity, structure, and function of rhizosphere soil bacteria. Result shows that the diversity of bacteria increases in the order of S. salsa < P. australis < T. chinensis. This finding may be related to the improvements of litter inputs, root exudates, and the change of soil physicochemical properties with the replacement of plant communities. At the phylum level, four out of eight bacterial phyla, mainly explained by pH (58.6 %), organic matter (57.7 %), moisture content (57.6 %), total carbon (40.8 %), and available potassium (39.5 %) of soils, changed significantly with the replacement of plant communities (p < 0.05). At the genus level, the dominant bacteria in different communities were clearly distinguished, but their metabolic function remains unchanged, indicating that convergent evolution also exists in the bacterial world. In summary, bacteria tend to make full use of limited resources by increasing niches rather than increasing the intensity of metabolic activities in similar habitats.

Smart and automation technologies for ensuring the long-term operation of a factory amid the COVID-19 pandemic: an evolving fuzzy assessment approach.

The COVID-19 pandemic has severely impacted factories all over the world, which have been closed to avoid the spread of COVID-19. As a result, ensuring the long-term operation of a factory amid the COVID-19 pandemic becomes a critical but challenging task. To fulfill this task, the applications of smart and automation technologies have been regarded as an effective means. However, such applications are time-consuming and budget-intensive with varying effects and are not necessarily acceptable to workers. In order to make full use of limited resources and time, it is necessary to establish a systematic procedure for comparing various applications of smart and automation technologies. For this reason, an evolving fuzzy assessment approach is proposed. A case study has been conducted to demonstrate the effectiveness of the evolving fuzzy assessment approach in ensuring the long-term operation of a factory amid the COVID-19 pandemic.

IoT Microservice Deployment in Edge-Cloud Hybrid Environment Using Reinforcement Learning

The edge-cloud hybrid environment requires complex deployment strategies to enable the smart Internet-of-Things (IoT) system. However, current service deployment strategies use simple, generalized heuristics and ignore the heterogeneous characteristics in the edge-cloud hybrid environment. In this article, we devise a method to find a microservice-based service deployment strategy that can reduce the average waiting time of IoT devices in the hybrid environment. For this purpose, we first propose a microservice-based deployment problem (MSDP) based on the heterogeneous and dynamic characteristics in the edge-cloud hybrid environment, including heterogeneity of edge server capacities, dynamic geographical information of IoT devices, and changing device preference for applications and complex application structures. We then propose a multiple buffer deep deterministic policy gradient (MB_DDPG) to provide more preferable service deployment solutions. Our algorithm leverages reinforcement learning and neural network to learn a deployment strategy without any human instruction. Therefore, the service provider can make full use of limited resources to improve the Quality of Service (QoS). Finally, we implement MB_DDPG based on real-world data sets and some synthetic data, and we also implement another two algorithms, genetic algorithm and random algorithm, as a contrast. The experimental results demonstrate that MB_DDPG is able to learn a preferable strategy which, in terms of average waiting time, outperforms genetic algorithm and the random algorithm by 32% and 44%, respectively.

Identification of the priority conservation areas of national park: A case study of Lishui City, Zhejiang Province, China

It is the goal of protected area management to make full use of limited resources to better protect biodiversity. Currently, the main tasks of developing national park system in China are to combine conservation features, optimize the spatial network of protected areas, and identify the prio-rity conservation areas of national parks effectively. In this study, we assessed the spatial distribution of key ecosystem services (carbon sequestration, oxygen release, hydrological regulation, water resources, and soil retention) using ecological model, and simulated the distribution of suitable habitats for 37 endangered species by MaxEnt in Lishui City, Zhejiang Province. The irreplaceability index of each planning unit in Lishui was calculated on the 0.4 km×0.4 km grid using the systema-tic conservation planning model (MARXAN), setting key ecosystem services and endangered species as the conservation objects. Combined with the local management needs, the priority protection areas of national parks were identified comprehensively. The results showed that during 2005 to 2015, the annual carbon storage, oxygen release, hydrological regulation, water resource, and soil retention in the study area was 0.05 kg C·m-2·a-1, 0.13 kg O2·m-2·a-1, 83.25×108 m3·a-1, 803 mm·a-1, and 95.53 t·hm-2·a-1, respectively. The irreplaceability index of different land use types was significantly different. The irreplaceability index of forest, river and reservoir, garden, cultivated land, residential land was 50-100, 60-100, 30-50, 15-35, 0-25, respectively. The priority conservation areas accounted for 11.8% of the study area. This study put forward a systematic conservation planning idea combining biodiversity and ecosystem services, which could provide a useful framework and technical support for optimizing the network layout of protected areas and priority conservation areas of national parks, and help to enhance the overall effectiveness of the establishment of the protected areas system with national parks as its main type in China.

Implementation of Project Management System Based on Project Management

With the rapid development of information technology and the gradual expansion of education, the construction of campus information is accelerating. The use of information technology to promote teaching reform is an important idea for the current school education reform, it is to improve the quality of teaching specifi c measures, especially new requirements is needed for colleges and universities as they continue to expand enrollment and teaching resources. Way to make full use of limited resources, use more scientifi c management methods and teaching methods, improve work effi ciency, ensure the quality of teaching, improve the eff ectiveness of running a school, has become an important subject of university research. The application of computer in teaching management is the key to realize the scientifi c and modern teaching management. To improve the quality of teaching, we must grasp the various teaching links. The examination is an important part for the students to test the eff ect of learning. Objective evaluation of the students as a means of curriculum construction is also an important part. In the school teaching work, the traditional test questions management is usually in the form of questions or test paper set, and design manually by teachers, which is large, and complex. The automatically generation system for test paper integrated the traditional manual volume, which solves a lot of problems, such as avoid unnecessary duplication of eff ort, saving the human resources and time; the use of scientifi c measures to evaluate and evaluate the diffi culty of harmonizing papers, the eff ective quality of test papers; and a signifi cant reduction in the probability of missing errors in the test paper, reduce unnecessary trouble

JCCA resource allocation for video transmission in relay-enhanced OFDMA system

Resulting from the rapid growth of wireless video services in the recent years, radio resource is often inadequate in the high data rate communication environment. Under the circumstance, it is important to make full use of limited resource for efficient video transmission. Hence, we propose a joint content and channel aware (JCCA) resource allocation algorithm in relay-enhanced OFDMA system. It can maximize accumulation of allocated subcarriers' contribution for transmitting video data so as to improve overall quality of users' received video under resource constrained conditions. As it is described in this work, the algorithm is implemented by packet scheduling, path selection and subcarrier allocation, in which time-varying data content and channel state are jointly considered at the same time. And the two implementation schemes, JCCAG and JCCAL, are designed for JCCA resource allocation algorithm. JCCAG is executed for allocating subcarriers through global search among all subcarriers' contribution. For reducing complexity of JCCAG, subcarriers are allocated according to the corresponding contribution towards each user on the basis of local search in JCCAL. In the simulation, we make comparison between the JCCA resource allocation algorithm and others for video transmission in relay-enhanced OFDMA system. And the comparison results are evaluated through objective and subjective criterion, respectively. It is demonstrated that the proposed algorithm can perform better in improving overall quality of users' received video.