Estimation of Sensitive Attributes Using a Stratified Kuk Randomization Device

통상적으로 표준적인 최적배분은 층별 조사비용을 고려하여 표본을 배분한다. 만일 조사단위당 비용이 서로 다를 경우 보다 현실적인 배분방법을 고려할 필요가 있다. 즉, 개별 조사단위의 특성에 따라 이익비용비를 최대로 하는 단위를 먼저 표본으로 고려하는 동적배분을 고려하였다. 이러한 관점에서 층별 표본수를 배분하고, 배분된 표본규모에 따라 임의로 표본을 선정하는 방식인 표준적인 최적배분과는 차이가 있다. 이 논문은 약물오용, 낙태, 알콜중독 등과 같은 민감한 특성을 조사하는 층화확률화 응답기법에 대해 각 층별로 표본을 배분할 경우 최적 동적배분을 고려하여 보다 현실적인 문제를 해결하고자 하였으며, 수치적 예제를 통해 동적배분 방법의 효과성을 증명하였다. Typically the standard optimal allocation method distributes the sample for each stratum considering survey cost. In case of varying survey cost for each survey unit, we need to consider more practical allocation method. In other words, according to characteristics of an individual unit, we consider the optimal dynamic allocation method which first selects the survey unit having maximum value of benefit cost ratio. In terms of this, the proposed allocation method is different from standard optimal allocation method which allocate samples for each stratum and selects the random sample according to each size of sample. This paper is considered the dynamic optimal allocation method for the stratified randomized response technique which surveys for sensitive characteristic of survey units such as drug abuse, abortion, alcoholic. We prove the practical usefulness of proposed method using the numerical example.

Optimal effort allocation in stratified, large area trawl surveys, with application to shrimp surveys in the Barents Sea

The grooming node has the capability of grooming multicast traffic with the small granularity into established light at high cost of complexity and node architecture. In the paper, a grooming nodes optimal allocation (GNOA) method is proposed to optimize the allocation of the grooming nodes constraint by the blocking probability for multicast traffic in sparse WDM networks. In the proposed GNOA method, the location of each grooming node is determined by the SCLD strategy. The improved smallest cost largest degree (SCLD) strategy is designed to select the nongrooming nodes in the proposed GNOA method. The simulation results show that the proposed GNOA method can reduce the required number of grooming nodes and decrease the cost of constructing a network to guarantee a certain request blocking probability when the wavelengths per fiber and transmitter/receiver ports per node are sufficient for the optical multicast in WDM networks.

With the increasing complexity of contemporary supply chains and the diversity of products in warehouses, product allocation strategies are crucial for warehouse operational efficiency. This paper addresses the operational planning challenge related to product allocation in a warehouse with heterogeneous products and storage racks. While the literature offers solutions to theoretical problems, applications to practical cases are less suited for complex environments. The objective is to present a novel approach to the storage location assignment problem, designed for an environment involving heterogeneous products. Using real data and practical insights for product subclassification from a case study in the automobile industry, the proposed allocation method is compared with two other scenarios: an optimal allocation method and a random one. A heuristic approach is then developed. The results show a 54% increase in bin availability and a 29% reduction in total distance traveled compared to the random solution

In this paper, we consider the estimation of a sensitive character when the population is consisted of several strata; this is undertaken by applying Niharika et al.’s model which is using geometric distribution as a randomization device. A sensitive parameter is estimated for the case in which stratum size is known, and proportional and optimum allocation methods are taken into account. We extended the Niharika et al.’s model to the case of an unknown stratum size; a sensitive parameter is estimated by applying stratified double sampling to the Niharika et al.’s model. Finally, the efficiency of the proposed model is compared with that of Niharika et al. in terms of the estimator variance.

According to the maximum hollow circle strategy of the Voronoi diagram, Starting from the basic principles for equipment allocation of the chemical reconnaissance system, the capability range of the three kinds of chemical reconnaissance nodes is determined by the ideal model of chemical reconnaissance actions, and a optimization method for equipment allocation is established in the plane area which under the reconnaissance protection.The simulation experiment about the algorithm is carried out by taking a certain chemical reconnaissance protection as an example.Finally, the deficiencies of this method in theoretical significance and reality are analyzed, which provides a method and modeling foundation for the research on equipment application of chemical reconnaissance.

Many research works have been developed for stereo image compression purpose where most of them aim at encoding a reference image, a residual one and a disparity map. While the disparity field is often losslessly encoded, we are mainly interested in this paper in the bit allocation problem between the reference and residual images. Generally, the bit allocation is expressed as an optimization problem which involves the computation of the operational rate-distortion (RD) functions for all the wavelet subbands and for different quantization steps. However, this strategy is computationally intensive. To solve this problem, we consider the uniform scalar quantization of the wavelet subbands of both images modeled by a Generalized Gaussian distribution. Thanks to recent approximations of the entropy and distortion functions, we develop an optimal and fast bit allocation method. The obtained results confirm the efficiency of the proposed bit allocation method in the context of stereo image coding.

To solve the question of guaranteeing the safety of a system with a complex structure and tight couplings, a new method of optimal allocation exploiting the dynamical planning theory is presented. Two key factors that can affect system safety, i.e., accident loss and accident rate are analyzed. Then, to measure comprehensively requirements of system safety, accident safety level is defined based on these two factors. Subsequently, optimal allocation for complex systems’ safety resource is implemented according to the network properties of the inherent structures of the systems and constraint conditions for safe investments. Finally, a case study shows that the method using dynamical planning for optimal allocation of system safety can ensure preferential allocations of the parts with high safety requirements. Besides, this optimal allocation method is feasible and valid.

This paper presents the results of a limited investigation which brings into focus the difficulties encountered in developing exact distribution-free methods for stratified simple random sampling. It is shown that exact distribution-free confidence intervals for a population median can be obtained from a stratified sample under very special circumstances. The principal result concerns the order statistics of the combined separate strata samples, where proportional allocation is employed. It is proved that a pair of symmetric order statistics provides a confidence interval for the population median whose confidence coefficient is not less than the confidence coefficient obtained from the corresponding order statistics of a random sample of the same total size drawn from the entire population. Furthermore, it is shown by means of a numerical example that this result necessarily holds only when proportional allocation is employed.

This study investigates energy allocation strategies for Internet of Things (IoT) clusters powered by energy harvesting, addressing the challenge of equitable and efficient energy distribution among nodes. Employing a game-theoretic framework, we compare cooperative (Shapley value-based), non-cooperative (penalty-driven), proportional, and priority-based allocation methods across 30 variations of penalty (20–60%), top allocation percentage (30–70%), and allocation strictness (Strict vs. Permissive). A simulation with 10 nodes over 24 time steps evaluates fairness (Gini coefficient), efficiency, wastage, and unmet demand. Results indicate that cooperative, proportional, and priority methods achieve 0% unmet demand and 100% efficiency, with Gini coefficients ranging from 0.094 to 0.350. Non-cooperative Strict allocations exhibit higher unmet demand (0–50.1%) and lower efficiency (0.499–1.0), improving with higher top percentages and Permissive settings. The optimal variation (Penalty=30%, Top=70%, Permissive) balances fairness (Gini=0.125) and efficiency (1.0). Cooperative strategies are recommended for IoT deployments, with tuned non-cooperative methods as viable alternatives. Future work includes dynamic penalty adjustments, heterogeneous node models, and real-world validation. This research contributes to sustainable IoT systems by providing a robust framework for energy management. Keywords: Iot, Energy Harvesting, Game Theory, Energy Allocation, Fairness, Efficiency

Optimal stochastic scenario-based allocation of smart grids’ renewable and non-renewable distributed generation units and protective devices

In this paper, we consider the saturation problem in the 3GPP LTE cellular system caused by the expected huge number of machine‐type communication (MTC) devices, leading to a significant impact on both machine‐to‐machine (M2M) and human‐to‐machine H2H traffic. M2M communications are expected to dominate traffic in LTE and beyond cellular networks. In order to address this problem, we proposed an advanced architecture designed for 5G LTE networks to enable the coexistence of H2H/M2M traffic, supported by different priority strategies to meet QoS for each traffic. The queuing strategy is implemented with an M2M gateway that manages four queues allocated to different types of MTC traffic. The optimal radio resource allocation method in LTE and beyond cellular networks was developed. This method is based on adaptive selection of channel bandwidth depending on the QoS requirements and priority traffic aggregation in the M2M gateway. Additionally, a new simulation model is proposed which can help in studying and analyzing the mutual impact between M2M and H2H traffic coexistence in 5G networks while considering high and low priority traffics for both M2M and H2H devices. This simulator automates the proposed method of optimal radio resource allocation between the M2M and H2H traffic to ensure the required QoS. Our simulation results proved that the proposed method improved the efficiency of radio resource utilization to 13% by optimizing the LTE frame formation process.

The authors propose an optimal structure decision method which can determine cell type, arrangement, degree of freedom, and link length. It can be used for fixed-base and mobile-base manipulators, so that universal/modular manipulators can be made. Simulation results show the differences in evaluation for different candidates and tasks and also demonstrate that the structure decision method works efficiently. With respect to the software structure, optimal knowledge allocation is one of the most important issues for CEBOT. The authors propose a method of optimal knowledge allocation based on the amount of communication among cells. Communication among cells for the control proposed is described. >

Multiuser orthogonal frequency division multiplexing (MU-OFDM) is a promising technique for achieving high downlink capacities in future cellular systems. A key issue in MU-OFDM is the allocation of the OFDM subcarriers and power among users sharing the channel. Previous allocation algorithms cannot ensure fairness in advance. In this paper, a proportional rate adaptive resource allocation method for MU-OFDM is proposed. Subcarrier and power allocation are carried out sequentially to reduce the complexity, and an optimal power allocation procedure is derived, through which proportional fairness is achieved. Simulation results show that this low-complexity MU-OFDM system achieves double the capacity of a fixed time division approach to OFDM multiple access, and also has higher capacity than previously derived suboptimal power distribution schemes.

For many European postal operators the growth in parcel and express segment does not outweigh letter revenue decline. Postal operators should find new growth drivers. They are actively pursuing growth opportunities in new business areas, mainly in logistics and freight, financial services, digital services and telecommunications, which are the largest sources of global postal revenues after traditional letter post and parcels and express delivery services. Postal operators also invest other markets such as local services or silver economy.When diversifying or entering new markets postal operators should firstly cover incremental costs. Determining incremental costs implies to establish adequate methods to allocate fixed and common costs in the case of multi-product firms. Allocating indirect costs such as overheads and network costs is not an easy task. While some costs can be easily identified and traced to individual product or line of business, there are common costs between historical and new activities that need to be allocated between the different products sold by postal operators.Knowledge of the costs can ensure the compliance with competition law and is a key to success and efficiency in new markets. Postal operators should therefore develop proper allocation cost methodologies. There exist several cost allocation methodologies. This presents the advantages and disadvantages of three different types of cost allocation methods: proportional cost allocation methods; methods based on game theoretical concepts and methods based on the value of the activity.