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1

Rideout, Douglas, und John Hof. „Allocating Joint Costs in Applied Forestry“. Western Journal of Applied Forestry 2, Nr. 2 (01.04.1987): 45–48. http://dx.doi.org/10.1093/wjaf/2.2.45.

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Abstract Two cost allocation techniques, "separable costs-remaining benefits" and the "simple Shapley value," are discussed and evaluated. The evaluation is performed relative to basic principles of cost allocation: that separable costs should be covered and that allocations should not exceed respective benefits. Two examples demonstrate that neither allocation technique is always consistent with the principles. The paper also discusses conditions under which each technique conforms to the principles, in part and in full. West. J. Appl. For. 2(2):45-48, April 1987.
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2

Khumawala, Saleha B., Linda M. Parsons und Teresa P. Gordon. „TRACKS: Assessing the Quality of Not-For-Profit Efficiency Ratios: Do Donors Use Joint Cost Allocation Disclosures?“ Journal of Accounting, Auditing & Finance 20, Nr. 3 (Juli 2005): 287–309. http://dx.doi.org/10.1177/0148558x0502000305.

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We examine whether required disclosures regarding joint cost allocations raise concerns about the validity of efficiency ratios reported by not-for-profit organizations. An experimental design is used to hold constant the geographic location, size, and mission of competing charitable organizations. Participants include financial officers of not-for-profit organizations (preparers), foundation executives (expert donors), and students (novice donors). We find that preparers base contribution decisions almost entirely on the reported fund-raising cost and accept the validity of reported program ratios. Foundation executives, representing experienced users of not-for-profit financial statements, also appear to accept the joint cost allocations as reported. By contrast, novice users are the most attentive to the allocation disclosures and consider them more often when deciding on the amount of a hypothetical gift. Overall, there is little evidence that joint cost allocation disclosures are used to adjust reported expenditures for fund-raising costs. Based on our results, donors appear to ignore the effects of allocating joint costs. Although current accounting standards limit the availability of an accounting method commonly used to manage financial results, it appears that the opportunity for not-for-profit managers to use joint cost allocations to manage ratios and influence donors remains.
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3

Shastitko, Andrey, Anna Meleshkina und Anastasiya Shastitko. „Cost Allocation, Regulation and Incentives in Joint Production of Goods“. Moscow University Economics Bulletin 2015, Nr. 1 (28.02.2015): 18–40. http://dx.doi.org/10.38050/01300105201512.

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This article addresses the joint cost allocation problem in context of firm’s price policy, market structure, enforcement of tax, environmental and antitrust legislation and the correlating problem of incentives’ design. The paper presents the theoretical foundations to distinguish such concepts as joint and by-product, their correlation with the category of waste. Moreover, the authors provide a comparative analysis of different methods of joint cost allocations and their areas of applicability. The practical part of this work involves the overview of actual practices of cost allocation in chemical industry. It confirms the need for an adjusted approach assessment of the efficiency and legitimacy of joint production in each particular case.
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4

ALMEIDA, VINICIO DE SOUZA E., und RICARDO PEREIRA CÂMARA LEAL. „A JOINT EXPERIMENTAL ANALYSIS OF INVESTOR BEHAVIOR IN IPO PRICING METHODS“. Revista de Administração de Empresas 55, Nr. 1 (Februar 2015): 14–25. http://dx.doi.org/10.1590/s0034-759020150103.

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This article jointly examines the differences of laboratory versions of the Dutch clock open auction, a sealed-bid auction to represent book building, and a two-stage sealed bid auction to proxy for the “competitive IPO”, a recent innovation used in a few European equity initial public offerings. We investigate pricing, seller allocation, and buyer welfare allocation efficiency and conclude that the book building emulation seems to be as price efficient as the Dutch auction, even after investor learning, whereas the competitive IPO is not price efficient, regardless of learning. The competitive IPO is the most seller allocative efficient method because it maximizes offer proceeds. The Dutch auction emerges as the most buyer welfare allocative efficient method. Underwriters are probably seeking pricing efficiency rather than seller or buyer welfare allocative efficiency and their discretionary pricing and allocation must be important since book building is prominent worldwide.
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5

Wang, Heng, Aijun Liu und Xiaofei Pan. „Optimization of Joint Power and Bandwidth Allocation in Multi-Spot-Beam Satellite Communication Systems“. Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/683604.

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Multi-spot-beam technique has been widely applied in modern satellite communication systems. However, the satellite power and bandwidth resources in a multi-spot-beam satellite communication system are scarce and expensive; it is urgent to utilize the resources efficiently. To this end, dynamically allocating the power and bandwidth is an available way. This paper initially formulates the problem of resource joint allocation as a convex optimization problem, taking into account a compromise between the maximum total system capacity and the fairness among the spot beams. A joint bandwidth and power allocation iterative algorithm based on duality theory is then proposed to obtain the optimal solution of this optimization problem. Compared with the existing separate bandwidth or power optimal allocation algorithms, it is shown that the joint allocation algorithm improves both the total system capacity and the fairness among spot beams. Moreover, it is easy to be implemented in practice, as the computational complexity of the proposed algorithm is linear with the number of spot beams.
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6

Thabet, Saqr Khalil Saeed, Emmanuel Osei-Mensah, Omar Ahmed, Abegaz Mohammed Seid und Olusola Bamisile. „Resource Optimization for 3D Video SoftCast with Joint Texture/Depth Power Allocation“. Applied Sciences 12, Nr. 10 (17.05.2022): 5047. http://dx.doi.org/10.3390/app12105047.

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During wireless video transmission, channel conditions can vary drastically. When the channel fails to support the transmission bit rate, the video quality degrades sharply. A pseudo-analog transmission system such as SoftCast relies on linear operations to achieve a linear quality transition over a wide range of channel conditions. When transmitting 3D videos over SoftCast, the following issues arise: (1) assigning the transmission power to texture and depth maps to obtain the optimal overall quality and (2) handling 3D video data traffic by dropping and re-allocating resources. This paper solves the pseudo-analog transmission resource allocation problem and improves the results by applying the optimal joint power allocation. First, the minimum and the target distortion optimization problems are formulated in terms of a power–bandwidth pair versus distortion. Then, a minimum distortion optimization algorithm iteratively computes all the possible resource allocations to find the optimal allocation based on the minimum distortion. Next, the three-dimensional target distortion problem is divided into two subproblems. In the power-distortion problem, to obtain a target distortion, the algorithm exhaustively solves the closed form of the power resource under a predefined upper-bound bandwidth. For the bandwidth-distortion problem, reaching a target distortion requires solving iteratively for the bandwidth resource closed form, given a predefined power. The proposed resource control scheme shows an improvement in transmission efficiency and resource utilization. At low power usage, the proposed method could achieve a PSNR gain of up to 1.5 dB over SoftCast and even a 1.789 dB gain over a distortion-resource algorithm, using less than 1.4% of the bandwidth.
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Yao Song, Yao Song, Limin Xiao Yao Song, Liang Wang Limin Xiao, Wei Wei Liang Wang und Jinquan Wang Wei Wei. „Joint Online Optimization of Task Rescheduling and Data Redistribution“. 網際網路技術學刊 24, Nr. 1 (Januar 2023): 011–22. http://dx.doi.org/10.53106/160792642023012401002.

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<p>Wide-area distributed computing environment is the main platform for storing large amounts of data and conducting wide-area computing. Tasks and data are jointly scheduled among multiple computing platforms to improve system efficiency. However, large network latency and limited bandwidth in wide-area networks may cause a large delay in scheduling information and data migration, which brings low task execution efficiency and a long time waiting for data. Traditional works mainly focus on allocating tasks based on data locality or distributing data replications, but optimizing task allocation or data placement alone is insufficient from a global perspective. To mitigate the impact of large network latency and limited bandwidth on system performance, joint online optimization of task rescheduling and data redistribution is proposed in this study. The task allocation and data placement can be adjusted collaboratively during the system running process through the task stealing and backfilling mechanism and the data replication placement mechanism. The experimental results indicate that compared with the state-of-the-art method, the proposed method improves the system throughput and computing resource utilization by 20.67% and 20.26% respectively, and can significantly reduce the global data migration costs.</p> <p>&nbsp;</p>
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8

Zhang, Jiawei. „Cost Allocation for Joint Replenishment Models“. Operations Research 57, Nr. 1 (Februar 2009): 146–56. http://dx.doi.org/10.1287/opre.1070.0491.

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9

Balachandran, Bala V., und Ram T. S. Ramakrishnan. „Joint Cost Allocation for Multiple Lots“. Management Science 42, Nr. 2 (Februar 1996): 247–58. http://dx.doi.org/10.1287/mnsc.42.2.247.

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10

Barrymore, S. J. „RISK ALLOCATION IN PETROLEUM JOINT VENTURES“. APPEA Journal 36, Nr. 1 (1996): 580. http://dx.doi.org/10.1071/aj95036.

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This paper will consider aspects of contractual risk allocation in the energy industry.The industry is a mature one, with sophisticated and experienced contractors and operators. Hydrocarbons have uniquely hazardous characteristics making all parties, the State and the community acutely aware of the need to control the means of its discovery, appraisal, production and transportation.The Exxon Valdez and Piper Alpha disasters are paradigm examples of the drastic consequences and the magnitude of the risk, that can flow from what might otherwise be considered 'a minor act or omission'.Risk management is based on the premise that it is in the interest of any project that certain risks be borne by certain parties, normally the person in the best position to control the risk concerned. A realistic approach to allocation of risk will reduce costs and claims and prevent over or under insurance. Where a risk which can be efficiently absorbed or covered by one party is passed to another, the short-term gain may be more than offset by the other party's increased charges or defensive practices for absorbing the risk or its inability to perform following a liability arising from that risk.As noted above, the risk allocation and management technique dealt with in this paper is contractual. Parties seek to distribute and allocate risks by the use of clauses of indemnity, limitation, exclusion, insurance and force majeure. Each of these contracts allocate risk to one party or the other for matters such as personal injury, property loss and damage, public liability, pollution, negligent workmanship and indirect loss or damage.This paper will examine the structure of these clauses (other than insurance) in the context of offshore development projects, centring around the joint operating agreement made between an operator and the licence holders, and a consideration of contracts entered into between the operator and its participants and the project contractors and project insurers. It will also address the issue of conduct in breach of statute and the effect of such conduct on indemnity and insurance agreements.
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11

LEÓN, JESÚS ALBERTO, und JOSÉ RENATO DE NÓBREGA. „Comparative Statics of Joint Reproductive Allocation“. Journal of Theoretical Biology 205, Nr. 4 (August 2000): 563–79. http://dx.doi.org/10.1006/jtbi.2000.2086.

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12

Liu, Wei, und Jing Min Tang. „Dynamic Subcarrier and Power Allocation Based on Nash Bargaining Solution in Symmetric Cooperative OFDMA Networks“. Advanced Materials Research 187 (Februar 2011): 510–15. http://dx.doi.org/10.4028/www.scientific.net/amr.187.510.

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In this paper, subcarrier and power allocation are jointly considered in a three-node symmetric cooperation orthogonal frequency-division multiple access uplink system. With the help of Nash bargaining solution, the dynamic subcarrier allocation scheme and the adaptive power allocation scheme are proposed for joint optimization. The joint resource allocation is decomposed and solved by dynamic subcarrier allocation algorithm and adaptive power allocation algorithm. Simulation results show the effectiveness of the proposed cooperative scheme.
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13

Jiang, Weiheng, und Wenjiang Feng. „Joint Power Allocation at the Base Station and the Relay for Untrusted Relay Cooperation OFDMA Network“. International Journal of Antennas and Propagation 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/530632.

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The secure communication that multiple OFDMA-based cell-edge mobile stations (MS) can only transmit confidential messages to base station (BS) through an untrusted intermediate relay (UR) is discussed. Specifically, with the destination-based jamming (DBJ) scheme and fixed MS transmission power assumption, our focus is on the joint BS and US power allocation to maximize system sum secrecy rate. We first analyze the challenges in solving this problem. The result indicates that our nonconvex joint power allocation is equivalent to a joint MS access control and power allocation. Then, by problem relaxation and the alternating optimization approach, two suboptimal joint MS access control and power allocation algorithms are proposed. These algorithms alternatively solve the subproblem of joint BS and UR power allocation and the subproblem of MS selection until system sum secrecy rate is nonincreasing. In addition, the convergence and computational complexity of the proposed algorithms are analyzed. Finally, simulations results are presented to demonstrate the performance of our proposed algorithms.
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14

Guo, Xi, Zening Wu, Xinling Wang, Cuimei Lv, Changkuan Gu, Yang Li und Meiyan Gao. „The Joint Optimal Allocation Study of Regional Total Water Consumption and Pollutant Carrying Capacity of Water Function Areas Based on Emergy Theory“. Water 12, Nr. 4 (13.04.2020): 1101. http://dx.doi.org/10.3390/w12041101.

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How to allocate the limited water consumption and pollutant carrying capacity of water function areas to sub-areas and water sectors is key for the practice of the most stringent water resource management decision-making. In response to the joint optimal allocation mechanism of water consumption and pollutant-carrying capacity, joint optimal allocation and the unified quantification problem of multiform benefits, the whole process of joint optimal distribution is refined into the links “water supply—water use and consumption—drainage—pollutant carrying” and the unified quantification method based on the emergy theory to achieve various economic, social, and ecological benefits in different links is proposed. Then the joint optimal allocation joint optimal allocation model of regional water consumption and pollutant carrying capacity is constructed, which realizes the reverse constraint relationship between water quantity and pollution carrying capacity in the water quality and quantity conversion processes. Using Zhengzhou city as an example, the models and methods were applied and researched. Countermeasures and suggestions for the rational allocation of available water resources and water pollution capacity were put forward accordingly.
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15

Rahmadani, Rahmadani, und Putri Aini. „Analisis Alokasi Biaya Bersama ddengan Menggunakan Metode Nilai Jual Relatif Pada Usaha Martabak Manis“. Jurnal Akuntansi, Manajemen, Bisnis dan Teknologi (AMBITEK) 3, Nr. 2 (01.08.2023): 200–205. http://dx.doi.org/10.56870/ambitek.v3i2.95.

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This study aims to prove how the process of allocating shared costs in the sweet martabak business on Jalan Pintu Air IV, Kwala Bekala, Medan Johor District, Medan. Data collection techniques used observation and interview methods. Researchers made direct observations of financial recording methods at the Sweet Martabak Business on Jalan Pintu Air IV Kwala Bekala. The result of this study is that sweet martabak businesses do not calculate in detail and do not use special methods to calculate joint cost allocation for sweet martabak. Through joint costs using the relative selling price method, the business has an allocation of joint costs of IDR 5,004,500 with a gross profit of IDR 2,273,500. The selling price method is the most appropriate method because this method has the advantage that the selling price can reflect the amount of costs absorbed by each type of product produced.
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16

Guo, Shaoyong, Xing Hu, Gangsong Dong, Wencui Li und Xuesong Qiu. „Mobile edge computing resource allocation: A joint Stackelberg game and matching strategy“. International Journal of Distributed Sensor Networks 15, Nr. 7 (Juli 2019): 155014771986155. http://dx.doi.org/10.1177/1550147719861556.

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Mobile edge computing has attracted great interests in the popularity of fifth-generation (5G) networks and Internet of Things. It aims to supply low-latency and high-interaction services for delay-sensitive applications. Utilizing mobile edge computing with Smart Home, which is one of the most important fields of Internet of Things, is a method to satisfy users’ demand for higher computing power and storage capacity. However, due to limited computing resource, how to improve efficiency of resource allocation is a challenge. In this article, we propose a hierarchical architecture in Smart Home with mobile edge computing, providing low-latency services and promoting edge process for smart devices. Based on that, a Stackelberg Game is designed in order to allocate computing resource to devices efficiently. Then, one-to-many matching is established to handle resource allocation problems. It is proved that the allocation strategy can optimize the utility of mobile edge computing server and improve allocating efficiency. Simulation results show the effectiveness of the proposed strategy compared with schemes based on auction game, and present performance with different changing system parameters.
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Wang, Susheng, und Tian Zhu. „CONTROL ALLOCATION, REVENUE SHARING, AND JOINT OWNERSHIP*“. International Economic Review 46, Nr. 3 (August 2005): 895–915. http://dx.doi.org/10.1111/j.1468-2354.2005.00350.x.

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18

Yao, Jiangchao, Yanfeng Wang, Ya Zhang, Jun Sun und Jun Zhou. „Joint Latent Dirichlet Allocation for Social Tags“. IEEE Transactions on Multimedia 20, Nr. 1 (Januar 2018): 224–37. http://dx.doi.org/10.1109/tmm.2017.2716829.

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19

Xie, Changxia, Dong Ma, Yun Gao, Jie Sheng und Canyan Zhu. „Joint Resource Allocation for Multicasting in HetNets“. IOP Conference Series: Materials Science and Engineering 490 (10.04.2019): 062006. http://dx.doi.org/10.1088/1757-899x/490/6/062006.

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20

Dror, Moshe, Bruce C. Hartman und Wei Chang. „The cost allocation issue in joint replenishment“. International Journal of Production Economics 135, Nr. 1 (Januar 2012): 242–54. http://dx.doi.org/10.1016/j.ijpe.2011.07.015.

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21

Windsperger, J. „Allocation of decision rights in joint ventures“. Managerial and Decision Economics 30, Nr. 8 (Dezember 2009): 491–501. http://dx.doi.org/10.1002/mde.1464.

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22

Rong, Yu, Tianci Dou und Xingchao Zhang. „Optimal resource allocation method and fault-tolerant control for redundant robots“. Mechanical Sciences 14, Nr. 2 (06.10.2023): 399–412. http://dx.doi.org/10.5194/ms-14-399-2023.

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Abstract. Resource coordination and allocation strategies are proposed to reduce the probability of failure by aiming at the problem that the robot cannot continue to work after joint failure. Firstly, the principal component analysis method under unsupervised branches in machine learning is used to analyze the reliability function and various indexes of the robot to obtain the comprehensive evaluation function. Then, based on the fault-tolerant-control inverse-kinematics optimal algorithm, each joint can be scheduled by weighted processing. Finally, the comprehensive evaluation function is used as an index to evaluate the probability of fault occurrence, and the weight is defined to realize the coordinated resource allocation of redundant robots. Taking the planar four revolute joints (4R) redundant robot as an example, the algorithm control is compared. Based on reasonable modeling and physical verification, the results show that the method of optimal resource coordination and allocation is effective.
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23

Arya, Anil, Jonathan C. Glover und Brian Mittendorf. „The Effects of Joint Cost Allocation on Intra-Firm Trade: A Comparison of Insulating and Non-Insulating Approaches“. Journal of Management Accounting Research 29, Nr. 2 (01.09.2016): 1–10. http://dx.doi.org/10.2308/jmar-51578.

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ABSTRACT While it is generally believed that insulating cost allocations help managers focus their attention on their own actions and shield them from the actions of others, non-insulating schemes can have appeal by encouraging teamwork and/or mutual monitoring among divisions. In this paper, we demonstrate that non-insulating allocations can induce fruitful cooperation among parties even when teamwork and mutual monitoring are nonissues. In particular, we show that in the case of intra-firm trade governed by transfer pricing, non-insulating allocations can permit one division to internalize benefits of private information borne by another and thereby alleviate information-induced trade barriers. Unlike in the traditional case of fostering teamwork, however, the cooperative nature of non-insulating allocation introduced by information differences is distinctly more circumstance-specific. In line with this view, the paper also identifies conditions under which the use of non-insulating allocation shifts divisional incentives in a manner that only adds further tension to trade.
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Tsuchiya, Takahiro, und Ryosuke Masuda. „Allocation of Proximity Sensors for Obstacle Detection of a Robot Manipulator“. Journal of Robotics and Mechatronics 9, Nr. 6 (20.12.1997): 482–89. http://dx.doi.org/10.20965/jrm.1997.p0482.

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In this paper, we discuss the sensor allocation problem in detecting obstacles in robot manipulators. The detection of obstacles in a work area is important for safety purposes and for the efficiency of robot control. Therefore, it is necessary to allocate the sensors properly on the links in a robot manipulator. Here, we propose two types of effective sensor allocation methods. One is based on the joint coordinates of the robot, and the other is based on the orthogonal work space. In addition, we show the allocation of additional sensors based on the quantitative conditions of the robot and its obstacles. The optical proximity sensor, which was developed by the authors, is used, and the proposed allocation methods are applied using a SCARA-type robot. It is proved, by experiments on obstacle avoidance control, that effective sensor allocations can be found.
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Ma, Kang, Heng Chang, Pengxu Chen, Zhiquan Bai und Hongwu Liu. „Joint Hovering Height, Power, and Rate Optimization for Air-to-Ground UAV-RSMA Covert Communications“. Drones 7, Nr. 7 (28.06.2023): 429. http://dx.doi.org/10.3390/drones7070429.

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In this paper, we investigate covert communications for an unmanned aerial vehicle (UAV)-aided rate-splitting multiple access (RSMA) system in which the UAV transmits to the covert and public users separately while shielding covert transmissions from a warden. Under the RSMA principles, the messages of the covert and public users are converted to common and private streams for air-to-ground transmissions. Subject to the quality of service (QoS) requirements of the public user and covertness constraint of the UAV-aid RSMA (UAV-RSMA) system, the aim of covert communication design is to maximize the covert rate by jointly optimizing the transmit power allocation, common rate allocation, and UAV hovering height, which each contribute to the uncertainty of the warden’s binary decision and attempts to enhance communication performance. To address the non-convex covert rate maximization problem in addition to the highly coupled system parameters, we decouple the original problem into three subproblems of transmit power allocation, common rate allocation, and UAV hovering height. We derive the optimal solutions for each of the subproblems of the transmit power and rate allocations and formulate a signomial programming problem to tackle UAV hovering height optimization. The simulation results indicate the superior covert rate performance achieved by the proposed AO algorithm and demonstrate that the proposed UAV-RSMA scheme achieves a higher covert rate than the benchmark schemes.
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Rideout, Doug, und John Hof. „Cost Sharing in Multiple Use Forestry: A Game Theoretic Approach“. Forest Science 33, Nr. 1 (01.03.1987): 81–88. http://dx.doi.org/10.1093/forestscience/33.1.81.

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Abstract Game theory is applied to the problem of joint cost allocation in forest management. The theory is used to define bounds (limits) to cost allocations. These traditional bounds are further defined in the context of potentially relevant benefit information to arrive at "benefit-included" bounds. These benefit-included bounds are consistent with both game theory and the early water resources principles that were based on cost separability. The traditional bounds and the benefit-included bounds are applied to a multipurpose forestry case study. The application is facilitated using the "nucleolus" cost allocation technique. The nucleolus provides a unique allocation that does not breach the bounds. The previously obscure calculation procedure of the nucleolus is clarified by example. For. Sci. 33(1):81-88.
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Rideout, Doug, und John E. Wagner. „An analysis of the separable costs – remaining benefits method of joint cost allocation“. Canadian Journal of Forest Research 16, Nr. 5 (01.10.1986): 880–84. http://dx.doi.org/10.1139/x86-157.

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The separable costs – remaining benefits (SCRB) incremental cost-allocation technique, preferred for United States Department of Agriculture Forest Service use, is critically analyzed. The paper mathematically specifies the SCRB model and demonstrates that the long-standing reasons for its wide appeal are not always valid. The analysis focuses on three fundamental reasons associated with the appeal of SCRB: (1) the ability of SCRB allocations to cover separable costs, (2) the claim that SCRB allocations will not make an efficient project purpose appear inefficient, and (3) the equity criteria often associated with SCRB. The paper shows that SCRB allocations will not always cover separable costs and suggests replacing the SCRB tests for purpose efficiency. The paper also shows that current SCRB formulations incorrectly define remaining benefits and, hence, the equity relation often associated with SCRB is defined incorrectly. The paper also suggests a general interpretation of the opportunity-cost concept that defines remaining benefits.
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Prasad, R. Murali, und P. Satish Kumar. „A Joint Routing and Bandwidth Allocation Protocol for IEEE 802.16 WiMax Mesh Networks“. International Journal of Engineering and Technology 2, Nr. 5 (2010): 442–46. http://dx.doi.org/10.7763/ijet.2010.v2.162.

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29

Yan, Shuai, Xuefen Chi, Linlin Zhao und Yuhong Zhu. „A Joint Subcarrier Assignment and Power Allocation with Statistical Delay QoS Provisioning in Full-Duplex OFDMA Systems“. ITM Web of Conferences 17 (2018): 01009. http://dx.doi.org/10.1051/itmconf/20181701009.

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In this paper, we explore a joint subcarrier assignment and power allocation with statistical delay QoS guarantees for full-duplex OFDMA systems. Effective capacity theory which evaluates wireless channel capacity from a novel view of link layer provides a theory basis for modeling the system capacity under the conditions of delay QoS constrains. After modeling the aggregate effective capacity of the system, we formulate joint subcarrier assignment and power allocation problem as a mixed integer programming problem, whose target is to maximize the aggregate effective capacity. To solve this integer programming problem, we allocate initial power on each subcarrier and decompose it into two subproblems, which are subcarrier allocation problem and power allocation problem respectively. Further, we propose an alternative algorithm to achieve joint subcarrier assignment and power allocation, which can meet the “subcarrier continuity” constraint of uplink resource allocation. Simulations have shown that the performance of our proposed scheme is favorite. Additionally, we investigate the effect of the residual selfinterference, inter-node interference (INI) and statistical delay QoS exponent on the performance of systems.
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Ahmed, Ammar, Yimin D. Zhang und Aboulnasr Hassanien. „Joint Radar-Communications Exploiting Optimized OFDM Waveforms“. Remote Sensing 13, Nr. 21 (30.10.2021): 4376. http://dx.doi.org/10.3390/rs13214376.

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We propose novel Joint Radar-communication spectrum sharing strategies exploiting orthogonal frequency-division multiplexing (OFDM) waveforms that concurrently achieve the objectives of both radar and communication systems. An OFDM transmitter is considered that transmits dual-purpose OFDM subcarriers such that all the subcarriers are exploited for the primary radar function and further exclusively allocated to the secondary communication function serving multiple users. The waveform optimization is performed by employing mutual information (MI) as the optimization criterion for both radar and communication operations. For the purpose of radar performance optimization, we consider the MI between the frequency-dependent target response and the transmit OFDM waveforms. On the other hand, communication system performance is evaluated in terms of the MI between the frequency-dependent communication channels of communication users with the transmit OFDM subcarriers. These optimization objectives not only enable the transmit power allocation of the OFDM subcarriers, but also govern the subcarrier distribution among the communication users. Two resource optimization scenarios are considered, resulting in radar-centric and cooperative resource allocation strategies that exploit convex and mixed-integer linear programming optimization problems for power allocation and subcarrier distribution, respectively. We further present a chunk subcarrier allocation approach that applies to both optimization strategies to reduce the computational complexity with a trivial performance loss. Simulation results are presented to illustrate the effectiveness of the proposed strategies.
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31

Jiang, Miao, Yiqing Li, Qi Zhang und Jiayin Qin. „Joint Position and Time Allocation Optimization of UAV Enabled Time Allocation Optimization Networks“. IEEE Transactions on Communications 67, Nr. 5 (Mai 2019): 3806–16. http://dx.doi.org/10.1109/tcomm.2019.2896973.

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32

Wu, Xuanli, Zheming Ma, Xu Chen, Fabrice Labeau und Shuai Han. „Energy Efficiency-Aware Joint Resource Allocation and Power Allocation in Multi-User Beamforming“. IEEE Transactions on Vehicular Technology 68, Nr. 5 (Mai 2019): 4824–33. http://dx.doi.org/10.1109/tvt.2019.2905251.

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33

Song, Xin, Xiuwei Han, Yue Ni, Li Dong und Lei Qin. „Joint Uplink and Downlink Resource Allocation for D2D Communications System“. Future Internet 11, Nr. 1 (06.01.2019): 12. http://dx.doi.org/10.3390/fi11010012.

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In cellular networks, device-to-device communications can increase the spectrum efficiency, but some conventional schemes only consider uplink or downlink resource allocation. In this paper, we propose the joint uplink and downlink resource allocation scheme which maximizes the system capacity and guarantees the signal-to-noise-and-interference ratio of both cellular users and device-to-device pairs. The optimization problem is formulated as a mixed integer nonlinear problem that is usually NP hard. To achieve the reasonable resource allocation, the optimization problem is divided into two sub-problems including power allocation and channel assignment. It is proved that the objective function of power control is a convex function, in which the optimal transmission power can be obtained. The Hungarian algorithm is developed to achieve joint uplink and downlink channel assignment. The proposed scheme can improve the system capacity performance and increase the spectrum efficiency. Numerical results reveal that the performance of the proposed scheme of jointly uplink and downlink is better than that of the schemes for independent allocation.
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Maadi, Sondes, und Noureddine Hamdi. „Joint Power Allocation and Beamforming for Cooperative Networks“. International Journal of Communications, Network and System Sciences 04, Nr. 07 (2011): 447–51. http://dx.doi.org/10.4236/ijcns.2011.47053.

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35

Kadir Hamid, Abdul, Lamia Osman Widaa, Fahd N. Al-Wesabi, Imran Khan, Anwer Mustafa Hilal, Manar Ahmed Hamza, Abu Sarwar Zaman und Mohammed Rizwanullah. „A Joint Resource Allocation Algorithm for D2D Communication“. Computers, Materials & Continua 70, Nr. 2 (2022): 3751–62. http://dx.doi.org/10.32604/cmc.2022.020136.

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36

Woerner, Stefan, Marco Laumanns und Stephan M. Wagner. „Joint optimisation of capacity and safety stock allocation“. International Journal of Production Research 56, Nr. 13 (26.09.2017): 4612–28. http://dx.doi.org/10.1080/00207543.2017.1380323.

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37

Arman, Mohammad Ali, Navid Kalantari und Abolfazl Mohammadian. „Joint Modeling of Household Vehicle and Activity Allocation“. Transportation Research Record: Journal of the Transportation Research Board 2495, Nr. 1 (Januar 2015): 121–30. http://dx.doi.org/10.3141/2495-13.

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38

Subramanian, Vijay G., Randall A. Berry und Rajeev Agrawal. „Joint Scheduling and Resource Allocation in CDMA Systems“. IEEE Transactions on Information Theory 56, Nr. 5 (Mai 2010): 2416–32. http://dx.doi.org/10.1109/tit.2010.2040860.

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39

Hjorth, Robert, Thomas Fiig, Jesper Larsen und Nicolas Bondoux. „Joint overbooking and seat allocation for fare families“. Journal of Revenue and Pricing Management 17, Nr. 6 (26.04.2018): 436–52. http://dx.doi.org/10.1057/s41272-018-0150-4.

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40

Kumaran, K., und H. Viswanathan. „Joint power and bandwidth allocation in downlink transmission“. IEEE Transactions on Wireless Communications 4, Nr. 3 (Mai 2005): 1008–16. http://dx.doi.org/10.1109/twc.2005.847026.

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41

Fu, Zhongning, Zhicai Juan und Rong Peng. „Study on interest allocation method of joint distribution“. International Journal of Services Operations and Informatics 4, Nr. 2 (2009): 97. http://dx.doi.org/10.1504/ijsoi.2009.023416.

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42

Lingling Pu, M. W. Marcellin, I. Djordjevic, B. Vasic und A. Bilgin. „Joint Source-Channel Rate Allocation in Parallel Channels“. IEEE Transactions on Image Processing 16, Nr. 8 (August 2007): 2016–22. http://dx.doi.org/10.1109/tip.2007.901810.

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43

Moon, Philip. „Paradoxes In the Cost Allocation For Joint Products“. Journal of Business Finance & Accounting 16, Nr. 3 (Juni 1989): 443–48. http://dx.doi.org/10.1111/j.1468-5957.1989.tb00029.x.

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44

Trenchard, P. M., und R. Dixon. „The clinical allocation of joint blood product costs“. Management Accounting Research 14, Nr. 2 (Juni 2003): 165–76. http://dx.doi.org/10.1016/s1044-5005(03)00021-0.

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45

Kourtis, Dimitrios, Günther Knoblich, Mateusz Woźniak und Natalie Sebanz. „Attention Allocation and Task Representation during Joint Action Planning“. Journal of Cognitive Neuroscience 26, Nr. 10 (Oktober 2014): 2275–86. http://dx.doi.org/10.1162/jocn_a_00634.

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We investigated whether people take into account an interaction partner's attentional focus and whether they represent in advance their partner's part of the task when planning to engage in a synchronous joint action. The experiment involved two participants planning and performing joint actions (i.e., synchronously lifting and clinking glasses), unimanual individual actions (i.e., lifting and moving a glass as if clinking with another person), and bimanual individual actions. EEG was recorded from one of the participants. We employed a choice reaction paradigm where a visual cue indicated the type of action to be planned, followed 1.5 sec later by a visual go stimulus, prompting the participants to act. We studied attention allocation processes by examining two lateralized EEG components, namely the anterior directing attention negativity and the late directing attention positivity. Action planning processes were examined using the late contingent negative variation and the movement-related potential. The results show that early stages of joint action planning involve dividing attention between locations in space relevant for one's own part of the joint action and locations relevant for one's partner's part of the joint action. At later stages of joint action planning, participants represented in advance their partner's upcoming action in addition to their own action, although not at an effector-specific level. Our study provides electrophysiological evidence supporting the operation of attention sharing processes and predictive self/other action representation during the planning phase of a synchronous joint task.
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Hamada, Kojun. „Incentive for innovation and the optimal allocation of patents“. Australian Journal of Management 42, Nr. 4 (04.04.2017): 692–707. http://dx.doi.org/10.1177/0312896216686152.

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This article theoretically investigates how different ownership structures of patents affect ex ante and ex post incentives for innovation by applying a property rights approach. We explore a model in which two research laboratories invest in R&D to obtain an innovative patent, and after successfully obtaining the patent they determine an ownership structure for the patent. The two parties consider how the determined patent ownership would affect their noncontractible relation-specific investments for commercialisation. We demonstrate that joint ownership of a patent between two parties is optimal. More concretely, if a selfish (altruistic) relation-specific investment is more important than an altruistic (selfish) investment, a joint ownership with no (bilateral) veto is optimal to maximise the joint value. Moreover, when both parties do not commit themselves to joint ownership in advance, they have greater incentive to invest in R&D than committing, even if they understand that joint ownership is desirable ex post.
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47

Jafari, Shahab, und Elahe Jahangard. „Dubious Allocation of Liability in the ICC Model Joint Venture Contract“. Business Law Review 43, Issue 5 (01.10.2022): 210–15. http://dx.doi.org/10.54648/bula2022031.

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Construction joint ventures are amongst the most common instances of open joint ventures. In 2018, the International Chamber of Commerce (ICC) published a model open joint ventures contract for construction projects to provide businesses with a balanced form of the agreement, enabling them to work together as joint operators. While the model contract provides a well-structured framework to regulate the relationship between the parties, the authors of this article are of the opinion that the basis for liability among joint venture members in the ICC Model Contract is dubious, if not wholly fallacious. Although much of what we say on the issue of liability of joint venture members in this article can equally be applied to all types of open joint venture agreements, or even close joint venture contracts, our main focus in this article is to scrutinize and criticize the proposed liability clause in the ICC Model Contract.
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48

Peng, Chunling, Guozhong Wang, Fangwei Li und Huaping Liu. „Joint Resource Allocation for SWIPT-Based Two-Way Relay Networks“. Energies 13, Nr. 22 (18.11.2020): 6024. http://dx.doi.org/10.3390/en13226024.

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This paper considers simultaneous wireless information and power transfer (SWIPT) in a decode-and-forward two-way relay (DF-TWR) network, where a power splitting protocol is employed at the relay for energy harvesting. The goal is to jointly optimize power allocation (PA) at the source nodes, power splitting (PS) at the relay node, and time allocation (TA) of each duration to minimize the system outage probability. In particular, we propose a static joint resource allocation (JRA) scheme and a dynamic JRA scheme with statistical channel properties and instantaneous channel characteristics, respectively. With the derived closed-form expression of the outage probability, a successive alternating optimization algorithm is proposed to tackle the static JRA problem. For the dynamic JRA scheme, a suboptimal closed-form solution is derived based on a multistep optimization and relaxation method. We present a comprehensive set of simulation results to evaluate the proposed schemes and compare their performances with those of existing resource allocation schemes.
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49

Liu, Jie, und Li Zhu. „Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing“. Complexity 2021 (29.03.2021): 1–11. http://dx.doi.org/10.1155/2021/5556651.

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Resource allocation has always been a key technology in wireless sensor networks (WSN), but most of the traditional resource allocation algorithms are based on single interface networks. The emergence and development of multi-interface and multichannel networks solve many bottleneck problems of single interface and single channel networks, it also brings new opportunities to the development of wireless sensor networks, but the multi-interface and multichannel technology not only improves the performance of wireless sensor networks but also brings great challenges to the resource allocation of wireless sensor networks. Edge computing changes the traditional centralized cloud computing processing method into a method that reduces computing storage capacity to the edge of the network and faces users and terminals. Realize the advantages of lower latency, higher bandwidth, and fast response. Therefore, this paper proposes a joint optimization algorithm of resource allocation based on edge computing. We establish a wireless sensor allocation model and then propose our algorithm model combined with the advantages of edge computing. Compared with the traditional allocation algorithm (PCOA, MCMH, and TDMA), it can further improve the resource utilization, reduce the network energy consumption, increase network capacity, and reduce the complexity of the schemes.
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Wulandari, Astri, Nachwan Mufti Adriansyah und Vinsensius Sigit Widhi Prabowo. „Greedy Based Radio Resource Allocation Algorithm with SARSA Power Control Scheme in D2D Underlaying Communication“. Journal of Measurements, Electronics, Communications, and Systems 7, Nr. 1 (30.12.2020): 6. http://dx.doi.org/10.25124/jmecs.v7i1.3472.

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Device-to-Device (D2D) underlaying communication system is a solution in reducing the workload of eNodeB and increasing the system data rate. This communication system consists of two users, namely Cellular User Equipment (CUE) and D2D pair, where CUE will share its resources with the D2D pair. This sharing resources also causes interference and should be managed using the resource allocation algorithm. In this work, the resource allocation scheme occurs in a single cell with an uplink communication direction. The resource allocation process uses greedy and joint greedy algorithms. After CUE allocates all of its resources, SARSA algorithm performs the power allocation process. The resource allocation process involves the scheduled CUE and D2D pair. After all the resource and power are allocated, parameter performance of the system is calculated. Based on the work results, joint greedy algorithm with power allocation using SARSA algorithm have performance results 1.375 × 107 bps/Watt in energy efficiency, 43.105 bps/Hz in spectral efficiency, and 0.993 in D2D fairness index.
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