Earticle

온실가스 배출권의 할당에 관한 기존의 연구들을 보면 경매나 무상할당방식의 장단점 또는 형평성 및 경제성 측면에서 국내 가능성 여부 등을 조사한 연구들은 많았으나, 온실가스 배출특성을 고려한 할당방식에 대한 연구사례는 많지 않았다. 이에 따 라 본 연구에서는 특정 배출시설에 대하여 배출권 할당방법을 마련하고 실제 배출권 할당을 설계하는 과정에서 적용 가능성이 있는지 살펴보고자 하였다. 본 연구에서는 온실가스 배출량이 많은 발전시설에 대하여 연료별로 구분하여 할당계수와 할당량 을 산정하고, 이를 통해 배출시설의 특성을 고려한 2가지 방법의 할당기준을 적용하여 할당량을 산정하였으며 주요 결과는 다 음과 같다. 첫째, 발전시설을 연료별로 구분하여 배출시설의 특성을 고려하여 할당계수를 마련하고 이를 이용해 배출권을 할 당한 결과 배출권의 과다 할당문제가 발생하지 않았다. 특히, 연구에서 사용된 2011년도의 배출량과 비교할 경우에는 배출권 할당량이 2011년도 배출량에 비해 22% 정도 적음에 따라 배출시설들은 배출권 거래와 시설 개선 등을 통해 온실가스를 감축 하여야 한다. 둘째, 동일 종류의 배출시설이며 동일 연료를 사용함에도 시설의 효율과 관리 노하우 정도에 따라 온실가스 배 출량이 서로 상이한 특성을 고려하여 할당계수를 산정하여 배출권을 할당한 결과 배출권의 구매 또는 판매가 가능한 배출권이 생산됨을 알 수 있다. 이는 배출권 거래가 가능해지기 위해 기본적으로 필요한 배출권 거래 가능량이 발생하는 것으로서 배출 권에 대한 수요와 공급의 토대를 제공한다. 또한, 해당 사업장으로 하여금 배출권 매매를 통해서만 할당량을 준수하게 하지 않 고 연료 전환이나 자체 시설에 대한 효율개선 노력을 통해 온실가스 배출량을 감축하도록 유도할 수 있다. 셋째, 비용을 투자 하여 다른 시설에 비해 단위 연료 사용량 당 온실가스 배출량이 적은 시설의 경우 조기 행동(early action)에 대한 보상을 요구 할 수 있는데, 본 연구에서 제시한 할당계수 산정방법을 이용하는 경우에는 조기행동에 대한 보상도 가능한 것을 알 수 있다. 이는 배출권을 할당함에 있어 논란이 될 수 있는 형평성 해결 과정에 논리적 근거를 제공할 수 있을 것으로 보인다.

This study analyzes the allocation method of the Emission Trading Scheme around the world and suggests an allocation method which may be applied to our country especially for power plants. In this study, the allocation of tradable permits was calculated by multiplying the allocation factor and activities of the emission facilities. The allocation factor is the sum of the carbon dioxide emissions per maximum activities during the baseline year (the recent 3 years). As a result, firstly, the over-allocation problem which other countries encountered at the primary stage when they started the Emission Trading Scheme may not happen. Secondly, this method may pave the way for the emission trading because it provides supply and demand of the tradable permits. Thirdly, this method can induce the stakeholders into making other efforts such as fuel change, efficiency improvement etc. excluding emission trading because the amount of allocation is about 22% less than the most recent emission. Lastly, this method may give compensation to the facilities which made actions to cut back on carbon dioxide earlier than other facilities. Their emission factor is less than the allocation factor, so their allocation amount is more than their recent emissions.

15세기 국가주도로 편찬된 관찬지리지는 편찬 시기에 따라 산물들이 편제된 항목과 내용이 차이가 있다. 磁器의 경우도 예외는 아니어서 각 군현의 토산(토산공물)항, 혹은 각 도의 궐공항에 다른 산물과 함께 기재되어 있거나, 각 군현 항목 말미에 魚梁·鹽 場·鐵場 등의 예와 같이 생산처인 磁器所로 기재되어 있다. 그리고 이와 같은 기재방식의 추이는 조선 개국 후 지속적으로 정비되었던 공납제와 그 맥락을 같이하고 있다. 본 글에서는 지리지마다 자기와 관련한 내용이 다르게 편제된 이유, 그리고 이를 기초로 『세종실록』 지리지의 각 도의 궐공항에 있는 ‘자기’가 의미하는 바가 무엇인지 검토해보았다. 자기가 기재된 산물항의 변동은 공납으로 수취되었던 자기의 성격과 그 흐름을 같이하고있다. 그 원인은 각 군현에서 공납으로 납부되었던 자기의 생산과 수요의 변화가 지리지에반영되었기 때문이다. 『세종실록』 지리지의 수찬자들은 각 도의 궐공항에 산물을 기재함에있어 ‘每邑所産’의 서술규식 이외에 산물의 특성과 지역성 등을 고려하여 ‘道단위의 分定’ 을 원칙으로 하였다. 특히 각 도 궐공항에 기재된 내용을 바탕으로 평안도와 함길도는 진상자기가 분정되지 않았던 반면, 경기도와 충청도, 황해도와 강원도, 전라도와 경상도는진상자기가 분정되어 있었다. 이를 규명한 것은 이 논문의 주요 성과라 하겠다. 이상의 내용을 토대로 기존 연구에서 한결같이 주목해왔던 ‘進上用 白磁와 貢納用 粉靑 沙器’라는 이원적 해석에 의문을 가지고, 선행연구자들이 제시한 진상백자에 대한 성격과실례들을 살펴보았다. 그 결과 선행연구자들이 언급한 진상백자의 성격은 국왕을 비롯한왕실구성원이 사용한 자기라는 한정된 범위 내에 포함되어 있었으며, 본 글에서 규명한 각道에 분정된 진상자기의 성격과는 부합되지 않고 있음을 확인하였다. 따라서 추후 각 道단위로 분정된 진상자기의 실제에 접근하기 위해서는 지금까지 일관되게 주목되었던 ‘進上用 白磁와 貢納用 粉靑沙器’라는 이원적 해석은 재고되어야 한다. 그리고 이를 살펴보기 위한 과정에서 진상과 공납제를 이원화하는 시각보다는, 공납제 아래에서 수취된 진상과 공물이라는 시각으로 접근하고자 하여야 한다.

Gwanchan geography books (geography books written or commissioned by the state) of the fifteenth century show differences in the table of contents and products depending on the period of compilation. Porcelain is no exception, and it is listed together with other products among the local product items (for tributes) of each county, among the items for missed tributes of each province, or at the end of an item for each county. Porcelain is listed in terms of the location where it is produced, as in the cases of weirs, salt pans, and iron foundries. The changing trend of such a system is in line with the tribute system, which was continuously improved since the founding of the Joseon Dynasty. In this paper, we examined the reason that the contents related to porcelain were organized differently in each geography book, and, based on this, the meaning of “porcelain” among the items for missed tributes in each province in The Veritable Records of King Sejong was reviewed. Changes in the product item where porcelain is listed are in line with the characteristics of porcelain given as a tribute. The reason for this is that changes in the production and demand for porcelain, which was given as a tribute in each county, were reflected in geography books. In addition to the descriptive rule of “produced in each village,” the writers of The Veritable Records followed the principle of “allocation by province” in consideration of the characteristics and locality of the products when listing the products among the missed tribute items for each province. In particular, the contents of the missed tribute items of each province show that Pyeongan and Hamgil provinces were not assigned porcelain dedicated to the king, while Gyeonggi, Chungcheong, Hwanghae, Gangwon, Jeolla, and Gyeongsang provinces were. Identifying this was the main achievement of this paper. We examine the characteristics and examples of white porcelain dedicated to the king as suggested by previous studies, with questions about the dubious interpretation of “white porcelain as a gift and Buncheong porcelain (bluish-green stoneware) as a tribute,” which has been consistently remarked upon in previous studies. We found that the characteristics of white porcelain dedicated to the king mentioned by previous studies were included within the limited scope of porcelain used by the king and other members of the royal family, and did not match the characteristics of the porcelain dedicated to the king assigned to each province as identified in this paper. Therefore, for an accurate understanding of the porcelain dedicated to the king assigned to each province later, the vague interpretation of “white porcelain as a gift and Buncheong porcelain as a tribute,” which has been consistently noted so far, needs to be reexamined. In this process, it is necessary to approach it from the perspective of the received gift and as an offering under the tribute system, rather than the dualistic view of dedication to the king and the tribute system.

본 논문에서는 Ku-대역에서 고정위성업무를 위한 주파수 신규 분배를 검토하는 WRC-15 의제에 대한 배경 및 연구 동향을 분석하고, 향후 국내 대응 방안을 고찰하였다. 위성 주파수는 전파규칙이 규정한 국제등록 절차에 따라 확보되는 자원이며, 주파수 자원은 한정된천연자원으로 인식되어 각 국가들의 자원 선점을 위한 경쟁이 점점 심화되고 있다. 이러한 상황에서 WRC-15에서는 고정위성업무용으로 주파수 추가 분배를 검토하게 되는데, 기존 업무의 적절한 보호 및 향후 고정위성업무의 이용 계획을 고려하여 적절히 대응할 필요가 있다.

This paper analyzed the background and status of studies for WRC-15 agenda item which considers additional frequency allocations to the fixed-satellite service in Ku-band and considered national future countermeasures. Satellite frequency can be acquired through compliance with the Radio Regulations for international registration and it has been recognized as the limited natural resource, and which leads to intensifying the competition among countries for the preoccupancy of it. Under the circumstances, WRC-15 is going to consider additional allocations to the fixed-satellite service in Ku-band and it is necessary to cope with the situation taking into account adequate protection of the existing services and future plan of frequency usage by the fixed-satellite service.

해외건설 프로젝트를 기획하고 수행하는 과정에서 현지 시장의 상황을 신속하고 정확하게 파악하는 것은 수익성 창출에 매우 큰 영향을 미친다. 뉴스기사 데이터는 정치, 경제, 사회 등 다양한 관한 정보를 담고 있기 때문에 시장의 상황을 파악하는 데 사용할 수 있는 좋은 데이터이다. 텍스트의 형태로 존재하는 대량의 뉴스기사 데이터로부터 정보를 추출하고 내용을 요약하는 과정에서 인력, 비용, 시간의 소모를 줄이기 위해 텍스트마이닝 기술이 필요하다. 본 연구에서는 뉴스기사에 다양한 주제가 공존한다는 특성으로 인해 발생하는 정보 추출의 한계를 극복하기 위해 잠재 디리클레 할당(Latent Dirichlet Allocation) 방법론을 사용하여 토픽 모델링을 수행했다. 문서 집단에 존재하는 주제의 개수가 10개라고 가정했을 때, 이용자들의 편의 증진을 위한 프로젝트(2번 주제)와 아프리카 지역의 빈곤 문제를 해결하기 위한 민간 차원의 지원(4번 주제) 등의 주제 집단이 존재하는 것을 확인했다. 이와 같이 문서 집단의 주제를 구분함으로써 더욱 의미있는 정보를 추출하고, 요약 결과의 활용성을 높일 수 있다.

Sufficient understanding of oversea construction market status is crucial to get profitability in the international construction project. Plenty of researchers have been considering the news article as a fine data source for figuring out the market condition, since the data includes market information such as political, economic, and social issue. Since the text data exists in unstructured format with huge size, various text-mining techniques were studied to reduce the unnecessary manpower, time, and cost to summarize the data. However, there are some limitations to extract the needed information from the news article because of the existence of various topics in the data. This research is aimed to overcome the problems and contribute to summarization of market status by performing topic modeling with Latent Dirichlet Allocation. With assuming that 10 topics existed in the corpus, the topics included projects for user convenience (topic-2), private supports to solve poverty problems in Africa (topic-4), and so on. By grouping the topics in the news articles, the results could improve extracting useful information and summarizing the market status.

An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.

The unbalance between system ergodic sum rate and high fairness is one of the key issues affecting the performance of non-orthogonal multiple access (NOMA) system. To solve the problem, this paper proposes a power allocation algorithm to realize the ergodic sum rate maximization of NOMA system. The scheme is mainly achieved by the construction algorithm of fair model based on α fair utility function and the optimal solution algorithm based on the interior point method of penalty function. Aiming at the construction of fair model, the fair target is added to the traditional power allocation model to set the reasonable target function. Simultaneously, the problem of ergodic sum rate and fairness in power allocation is weighed by adjusting the value of α. Aiming at the optimal solution algorithm, the interior point method of penalty function is used to transform the fair objective function with unequal constraints into the unconstrained problem in the feasible domain. Then the optimal solution of the original constrained optimization problem is gradually approximated within the feasible domain. The simulation results show that, compared with NOMA and time division multiple address (TDMA) schemes, the proposed method has larger ergodic sum rate and lower Fairness Index (FI) values.

In this paper, we consider measurement allocation problem in a spatially correlated sensor field. Our goal is to determine the probability of each sensor's being measured based on its contribution to the estimation reliability; it is desirable that a sensor improving the estimation reliability is measured more frequently. We consider a spatial correlation model of a sensor field reflecting transmission power limit, noise in measurement and transmission channel, and channel attenuation. Then the estimation reliability is defined distortion error between event source and its estimation at sink. Motivated by the correlation nature, we model the measurement allocation problem into a cooperative game, and then quantify each sensor's contribution using Shapley value. Against the intractability in the computation of exact Shapley value, we deploy a randomized method that enables to compute the approximate Shapley value within a reasonable time. Besides, we envisage a measurement scheduling achieving the balance between network lifetime and estimation reliability.

In this paper, we considered heterogeneous spectrum sharing system where the number of subcarriers of the primary user (PU) was twice as much as that of the secondary user (SU). In this case, due to non-orthogonality and inter-carrier interference (ICI) from SU to PU, it is difficult to satisfy the interference constraint of PU. In order to mitigate ICI and satisfy the interference constraint, we proposed a new transmission scheme of the SU with power allocation scheme. The proposed scheme will only generate subcarrier-by-subcarrier interference. Therefore, it can easily satisfy the interference constraint of the PR and enhance the capacity of the SU. In addition, we derived the ergodic capacity of the SU. Based on numerical results, we confirmed that the proposed schemes could guarantee SU with a reliable capacity while satisfying the interference constraint of the PU. In addition, the derived capacity well matched the numerical results.

The lower transmission power capability of internet of things (IoT) devices in millimeter-wave (mmWave) networks necessitates the activation of beamforming techniques by employing multiple antennas. To ensure robust directional transmissions at mmWave frequencies, it is essential to accurately align narrow beams with the dominant channel direction. However, directional communications necessitate aligning the beam with the channel direction, resulting in significant transmit power consumption. We aim to reduce the transmit power required to achieve a desired beam-alignment performance, taking into account the power limitations of IoT devices.We propose an analytical framework for optimizing resource utilization in the hierarchical beam alignment algorithm, designed to progressively reduce the size of the beamformer candidate set. Based on the analytical studies, we develop a resource allocation algorithm that determines the optimal transmit power and constructs the optimal set of beamformer candidates at each beam alignment stage. Numerical simulations demonstrate that the proposed power allocation algorithm effectively reduces the transmit power to meet the performance targets for IoT networks.

By considering the limited energy of Internet of Things (IoT) devices. We take the resource allocation to guarantee the stringent Quality of Service (QoS) depending on the joint optimization of power control and finite blocklength of channel. To achieve large volumes of arrival rates, we propose Adversarial Training based Generative Adversarial Networks (AT-GANs), which utilize a significant number of extreme events to provide high reliability and adjust real data in real-time. Simulation results show that Deep-Reinforcement Learning (Deep-RL) for AT-GAN could eliminate the transient training time. As a result, the AT-GAN keeps the reliability higher than 99.9999%.

Deep reinforcement learning can effectively address resource allocation in wireless networks. However, its learning speed may be slower in more complex networks and a new policy should be learned for a newly-arrived system due to a lack of network adaptability. To address these issues, we propose a federated learning framework for resource allocation in wireless networks with multiple systems. It accelerates the learning speed by aggregating the policy at each system into a central policy and ensures network adaptability by using the central policy. Through experiments, we demonstrate that our proposed framework achieves both learning acceleration and network adaptability.

In this paper, we investigate the optimum energy allocation of dual-hop communication systems with AF protocol where we consider both coherent and differential transmission schemes. First, we demonstrate the performance of dual-hop communication systems in terms of symbol error rate (SER). Then, we carry out the optimum energy allocation which minimizes the error rate. Based on the optimized energy allocation, its effects on system performance are analyzed, and these results are compared with DF-based systems. We also compare the performance of AF-based systems depending on the transmission scheme.

In this letter, we propose two power allocation strategies, named Optimal Power Allocation (OPA) and Equal Intercept Probability (EIP), for dual-hop cooperative decode-and-forward (DF) relaying networks under constraint of intercept probability (IP). Particularly, with knowledge of channel statistics of the eavesdropping links, the transmitters such as source and relays adjust their transmit power to control the value of IP by a desired level. A max?min relay selection method is applied to enhance the e2e outage probability (OP). We derive expressions of transmit power for the source and the selected relay. Then, Monte Carlo simulations were performed to verify analytical results.

Currently, most Internet of Things (IoT) resource-allocation solutions are based on centralized management, rendering it difficult to successfully establish diverse and dynamic IoT networks. Consequently, the fields of reinforcement learning and distributed computing require additional technological advancements. We propose an innovative approach for slot scheduling in IoT networks. This approach focuses on the utilization of distributed resource blocks. The purpose of this work is to demonstrate, via simulations, the influence of distributed slot assignment on the signal-to-interference ratio (SIR) and the probability of accidents occurring. The results of this research suggest that the proposed approach, in which each device in the IoT network is provided with an appropriate slot that possesses acceptable SIR levels, was successful. As the process of distributed slot allocation progresses, it is beneficial to build network convergence by utilizing the learning capabilities of each device. This was accomplished using a distributed slot-allocation process. Therefore, the existing bandwidth can be utilized more efficiently.

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

The explosive growth of data traffic and services has created cost challenges for networks. Studies have attempted to effectively apply network slicing in fifth generation networks to provide high speed, low latency, and various compatible services. However, in network slicing using mixed-integer linear programming, the operation count increases exponentially with the number of physical servers and virtual network functions (VNFs) to be allocated. Therefore, we propose an efficient slice allocation method based on cluster technology, comprising the following three steps: i) clustering physical servers; ii) selecting an appropriate cluster to allocate a VNF; iii) selecting an appropriate physical server for VNF allocation. Solver runtimes of the existing and proposed methods are compared, under similar settings, with respect to intra-slice isolation. The results show that solver runtime decreases, by approximately 30% on average, with an increase in the number of physical servers within the cluster in the presence of intra-slice isolation.

Power allocation is an important factor for cognitive radio networks to achieve higher communication capacity and faster equilibrium. This paper considers power allocation problem to each cognitive user to maximize capacity of the cognitive systems subject to the constraints on the total power of each cognitive user and the interference levels of the primary user. Since this power control problem can be formulated as a mixed-integer nonlinear programming (NP) equivalent to variational inequality (VI) problem in convex polyhedron which can be transformed into complementary problem (CP), we utilize modified projection method to solve this CP problem instead of finding NP solution and give a power control allocation algorithm with a subcarrier allocation scheme. Simulation results show that the proposed algorithm performs well and effectively reduces the system power consumption with almost maximum capacity while achieve Nash equilibrium.

New and handoff calls control mechanisms are the key point to wireless cellular networks. In this paper, we present an adaptive algorithm for dynamic channel allocation scheme with guard channels and also with handoff calls waiting queue ensuring that handoff calls take priority over new calls. Our goal is to find better tradeoff between handoffs and new calls blocking probabilities in order to achieve more efficient channel utilization. Simpy is a Python based discrete event simulation system. We use Simpy to build our simulation models to get analytical data.

This study examined changes in citation index scores and rankings of thirty-five chemistry faculty members at Seoul National University using different co-authorship credit allocation models. Using 1,436 Web of Science papers published between 2007 and 2013, we applied the inflated, fractional, harmonic, network-based allocation, and harmonic+ models to calculate faculty's h-, R-, and normalization of h- and R- index scores and rankings. The harmonic+ model, which is based on our belief that contribution of primary authors should be the same regardless of collaboration, is designed to minimize the penalty for research collaboration imposed by harmonic and NBA models by boosting the contribution of collaborating primary authors to be on the equal footing with single authors. Although citation rankings by different models are correlated with each other within the same type of citation indicator, rankings of many faculty members changed across models, suggesting the importance of an accurate and relevant authorship credit allocation model in the citation assessment of researchers. The study also found that authorship patterns in conjunction with citation counts are important factors for robust authorship models such as harmonic and NBA, and harmonic+ model may be beneficial for collaborating primary authors. Future research that reexamines the models with updated empirical data would provide further insights into the robustness of the models.