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Summary: This article describes a generalized single‐phase multiwinding step‐up transformer‐based multilevel converter with optimized device count. The proposed topology comprises of a single dc source, eight switches (four unidirectional and four bidirectional) and a single high‐frequency multiwinding transformer. Phase disposition pulse width modulation (PDPWM) is used for the level creation. The proposed converter is examined qualitatively and quantitatively using the total number of transformers, PWM control method, switch count, voltage stress, and the number of gate drivers, all of which are favorable. All elements of transformer selection, winding requirements, and comparative study have been thoroughly examined. A thorough Lagrange multiplier method has been applied to minimize the copper losses and optimize the multiwinding transformer (MWT) winding. The proposed converter simulations are performed using the MATLAB/SIMULINK environment. Further, the validation of the result is confirmed by a hardware setup of 0.9 kW. [ABSTRACT FROM AUTHOR]

The broiler industry is crucial in Malaysia's agricultural sector, contributing significantly to meat production and the economy. However, the industry faces significant challenges, primarily stemming from high production costs, with feed costs constituting a substantial portion. Therefore, there is a need to improve domestic farm performance and competitiveness by optimizing resources and minimizing expenses to enhance overall productivity. This study aims to estimate the extent of cost efficiency in broiler farming in Peninsular Malaysia and identify key determinants influencing the inefficiency cost. A comprehensive survey involving 241 broiler farms in Peninsular Malaysia was conducted using structured questionnaires and a stratified random sampling technique. Employing the Stochastic Cost Frontier model revealed an operational inefficiency of approximately 5.7% above optimal costs among the surveyed farms, indicating substantial potential for a 5.7% reduction in production costs through enhanced management strategies. Factors such as feed prices, day-old chick prices, price of miscellaneous inputs, production output levels, and capital investment prices emerged as prominent influencers in the broiler cost function. Furthermore, the study indicated that socio-economic factors such as housing system, extension visits, credit access and contract farming are associated with lower inefficiencies, thereby enhancing cost efficiency in broiler farming operations. Conversely, higher bird mortality rates are associated with the increased inefficiency. Gaining insights into these factors is crucial for stakeholders to allocate resources wisely, plan strategically, and enhance competitiveness in broiler farming. [ABSTRACT FROM AUTHOR]

Explaining material traces of movement as proxies for past movement is fundamental for understanding the processes behind why people in the past traversed the landscape in the way that they did. For this, least-cost path analysis and the use of slope-based cost functions for estimating the cost of movement when walking have become commonplace. Despite their prevalence, current approaches misrepresent what these cost functions are, their relationship to the hypotheses that they aim to represent, and their role in explanation. As a result, least-cost paths calculated using single cost functions are liable to spurious results with limited power for explaining known past routes, and by extension the decision-making processes of past people. Using the ideas of multiple model idealisation and robustness analysis, and applied via a tactical simulation, this study demonstrates that similar least-cost paths can be produced from slope-based cost functions representing both the same hypothesis and different hypotheses, suggesting that least-cost path results are robust but underdetermined under the tested environmental settings. The results from this tactical simulation are applied for the explanation of a Roman road in Sardinia. Using probabilistic least-cost paths as an approach for incorporating multiple cost functions representing the same hypothesis and error in the digital elevation model, it is shown that both model outcomes representing the minimisation of time and energy are unable to explain the placement of the Roman road. Rather, it is suggested that the Roman road was influenced by pre-existing routes and settlements. [ABSTRACT FROM AUTHOR]

A new multi gain SC inverter topology with fewer switching components and lower voltage stress is presented in this paper. It comprises eight switches and two capacitors, which raise the output voltage by three times the supply voltage. The capacitors voltages are automatically balanced to ensure proper operation. The circuit constructional, operation, and parameter optimisation techniques are discussed in details. A simple logic-based multicarrier Level Shift Pulse Width Modulation (LS-PWM) is employed to control the switching operation that reduces the complexity of the control circuit. Furthermore, a comparative analysis with other recent topologies has been presented to demonstrate the virtues of this approach. Finally, the proposed topology (PT) verification, feasibility, and effectiveness have been demonstrated both in simulation and experimentation. [ABSTRACT FROM AUTHOR]

This letter introduces the design of an estimator for parameters of Middleton Class A noise using its canonical formula and classical numerical methods. The main focus is to acquire parameters to characterize communication channels in intelligent systems or those based on cognitive paradigms. A comprehensive analysis of the first-order characteristics of the Middleton Class A noise model is conducted to establish the foundational understanding necessary for developing the presented estimator model, named impulsive noise estimator with minimization methods (INEMM). Subsequently, the method is introduced, substantiated, and compared to various established estimators concerning precision and complexity. Results show a distinct advantage in terms of overall performance. [ABSTRACT FROM AUTHOR]

In this letter, the problem of optimization of multirate filterbanks is addressed. The factors that define the efficiency of these multirate systems are investigated and the implementations of structures in stages are analyzed. The latter, together with the polyphase implementations of the filters, allows obtaining optimal filterbanks in the use of resources for the FPGAs. [ABSTRACT FROM AUTHOR]

Following events such as fatigue or stroke, individuals often move their trunks forward during reaching, leveraging a broader muscle group even when only arm movement would suffice. In previous work, we showed the existence of a "force reserve": a phenomenon where individuals, when challenged with a heavy weight, adjusted their motor coordination to preserve approximately 40% of their shoulder's force. Here, we investigated if such reserve can predict hip, shoulder, and elbow movements and torques resulting from an induced shoulder strength deficit. We engaged 20 healthy participants in a reaching task with incrementally heavier dumbbells, analyzing arm and trunk movements via motion capture and joint torques through inverse dynamics. We simulated these movements using an optimal control model of a 3-degree-of-freedom upper body, contrasting three cost functions: traditional sum of squared torques, a force reserve function incorporating a nonlinear penalty, and a normalized torque function. Our results demonstrate a clear increase in trunk movement correlated with heavier dumbbell weights, with participants employing compensatory movements to maintain a shoulder force reserve of approximately 40% of maximum torque. Simulations showed that while traditional and reserve functions accurately predicted trunk compensation, only the reserve function effectively predicted joint torques under heavier weights. These findings suggest that compensatory movements are strategically employed to minimize shoulder effort and distribute load across multiple joints in response to weakness. We discuss the implications of the force reserve cost function in the context of optimal control of human movements and its relevance for understanding compensatory movements poststroke. NEW & NOTEWORTHY: Our study reveals key findings on compensatory movements during upper limb reaching tasks under shoulder strength deficits, as observed poststroke. Using heavy dumbbells with healthy volunteers, we demonstrate how forward trunk displacement conserves around 40% of shoulder strength reserve during reaching. We show that an optimal controller employing a cost function combining squared motor torque and a nonlinear penalty for excessive muscle activation outperforms traditional controllers in predicting torques and compensatory movements in these scenarios. [ABSTRACT FROM AUTHOR]

In many research studies, multiple objectives need to be considered simultaneously to ensure an effective and efficient investigation. A compound optimal design provides a viable solution to this problem, allowing for the maximization of overall benefits through the integration of several factors. The paper addresses the application of compound optimal designs in the context of progressive first‐failure censoring, with a particular focus on the Generalized Exponential distribution with two parameters. The paper provides an illustrative example of compound designs by considering the cost function along with trace, variance, and determinant of inverse Fisher information. The best design is determined using a graphical solution technique that is both comprehensible and precise. Using a simple example, we demonstrate the advantage of compound optimal designs over constraint optimal designs. Furthermore, the paper examines real‐world data collection to demonstrate the practical utility of compound optimal designs. [ABSTRACT FROM AUTHOR]

Introduction: HIV self‐testing (HIVST) is a promising strategy to improve diagnosis coverage among key populations (KP). The ATLAS (Auto Test VIH, Libre d'Accéder à la connaissance de son Statut) programme implemented HIVST in three West African countries, distributing over 380,000 kits up between 2019 and 2021, focussing on community‐led distribution by KP to their peers and subsequent secondary distribution to their partners and clients. We aim to evaluate the cost‐effectiveness of community‐led HIVST in Côte d'Ivoire, Mali and Senegal. Methods: An HIV transmission dynamics model was adapted and calibrated to country‐specific epidemiological data and used to predict the impact of HIVST. We considered the distribution of HIVST among two KP—female sex workers (FSW), and men who have sex with men (MSM)—and their sexual partners and clients. We compared the cost‐effectiveness of two scenarios against a counterfactual without HIVST over a 20‐year horizon (2019–2039). The ATLAS‐only scenario mimicked the 2‐year implemented ATLAS programme, whereas the ATLAS‐scale‐up scenario achieved 95% coverage of HIVST distribution among FSW and MSM by 2025 onwards. The primary outcome is the number of disability‐adjusted life‐years (DALY) averted. Scenarios were compared using incremental cost‐effectiveness ratios (ICERs). Costing was performed using a healthcare provider's perspective. Costs were discounted at 4%, converted to $USD 2022 and estimated using a cost‐function to accommodate economies of scale. Results: The ATLAS‐only scenario was highly cost‐effective over 20 years, even at low willingness‐to‐pay thresholds. The median ICERs were $126 ($88–$210) per DALY averted in Côte d'Ivoire, $92 ($88–$210) in Mali and 27$ ($88–$210) in Senegal. Scaling‐up the ATLAS programme would also be cost‐effective, and substantial epidemiological impacts would be achieved. The ICERs for the scale‐up scenario were $199 ($122–$338) per DALY averted in Côte d'Ivoire, $224 ($118–$415) in Mali and $61 ($18–$128) in Senegal. Conclusions: Both the implemented and the potential scale‐up of community‐led HIVST programmes in West Africa, where KP are important to overall transmission dynamics, have the potential to be highly cost‐effective, as compared to a scenario without HIVST. These findings support the scale‐up of community‐led HIVST to reach populations that otherwise may not access conventional testing services. [ABSTRACT FROM AUTHOR]

This article presents a novel reduced component multilevel inverter with 3 DC sources and 9 switches which is suitable for renewable energy and electric vehicle applications. The proposed topology can operate with symmetrical and asymmetrical DC sources and produces seven levels and a maximum of 15 levels, respectively. Additional benefits of the suggested topology include modularity, lower total standing voltage, and fewer on-state switches. Effective comparison with existing topologies is provided to demonstrate the novelty of the suggested topology. Generalized horizontal, vertical, and two-way Extendable topologies are discussed. Discrete modulation approaches are used to investigate the influence of modulation index variation on the proposed inverter's output voltage, THD, power, and efficiency while considering static and dynamic load changes. The performance of MLI with proposed optimized nearest level control method using particle swarm optimization technique surpasses conventional nearest level control and multi-carrier level shift modulation methods. Extensive simulation tests are carried out in MATLAB/Simulink and validated the results with experimental tests. 5.6% THD and efficiency in the range of 93% to 95% are achieved with the proposed15-level inverter. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Technology Economics is the property of Chinese Society of Technology Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study presents a novel approach for solving the economic dispatch (ED) problem in groups of generating units communicating through a communication network. The suggested strategy is a consensus-based dynamic event-triggered (ET) distributed optimization method. Our methodology considers the sharing of the local information between generators and their convex cost functions to address the total cost function and offers a decentralized optimization solution over a network. The proposed distributed method addresses the ED problem by considering the criterion of optimal cost and by offering efficient communication. Generating units are grouped according to their generation operational limits, that is, total capacity and dynamic ET distributed protocols are developed to ensure the consensus of cost variables among generating units, operating under normal capacity conditions. The remaining generating agents work on their operating limits, which are segregated through the sharing of flag information through a switching mechanism. Consequently, in contrast to the existing methods, the recommended protocol allows nodes to function in groups, based on the power supply, for ED with geographical clustering and capacity restrictions, in addition to handling the system constraints. Furthermore, the proposed technique employs a dynamic triggering method to manage bandwidth and guarantee the elimination of Zeno behavior. The simulation results validate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper proposes an improved biogeography-based optimization (BBO) algorithm to effectively solve the economic and environmental dispatch (EED) problem in power systems. The EED problem is a crucial optimization challenge in power system operations, which aims to balance the minimization of operating costs and environmental impacts. Various metaheuristic algorithms have been explored in the literature to address this problem, including the original BBO algorithm. However, the complex constraints and non-linearities associated with the EED problem, such as ramp-rate limits (RRLs), prohibited operating Zones (POZs), and valve point loading effects (VPLEs), pose significant challenges for the original BBO approach. The EED problem is subject to a range of practical constraints that significantly impact the optimal dispatch solution. Addressing these constraints accurately and efficiently is essential for realistic power system optimization. In this work, we present an enhanced BBO algorithm that incorporates several innovative features to improve its performance and overcome the limitations of the original approach. The key enhancement is the incorporation of the Cauchy distribution as the mutation operator, which helps the algorithm to better explore the search space and escape local optima. Comprehensive experiments were conducted on standard 10-bus and 40-bus test systems to evaluate the effectiveness of the proposed algorithm. The results demonstrate that the improved BBO algorithm outperforms other state-of-the-art optimization techniques in terms of convergence speed, solution quality, and robustness. Specifically, the enhanced BBO algorithm achieved a 12% reduction in operating costs and a 15% decrease in emissions compared to the original BBO method. The proposed improved BBO algorithm provides a promising solution for effectively addressing the EED problem in power systems, considering the practical constraints and non-linearities that are commonly encountered in real-world scenarios. [ABSTRACT FROM AUTHOR]

In the realm of smart communication systems, where the ubiquity of 5G/6G networks and IoT applications demands robust data confidentiality, the cryptographic integrity of block and stream cipher mechanisms plays a pivotal role. This paper focuses on the enhancement of cryptographic strength in these systems through an innovative approach to generating substitution boxes (S-boxes), which are integral in achieving confusion and diffusion properties in substitution–permutation networks. These properties are critical in thwarting statistical, differential, linear, and other forms of cryptanalysis, and are equally vital in pseudorandom number generation and cryptographic hashing algorithms. The paper addresses the challenge of rapidly producing random S-boxes with desired cryptographic attributes, a task notably arduous given the complexity of existing generation algorithms. We delve into the hill climbing algorithm, exploring various cost functions and their impact on computational complexity for generating S-boxes with a target nonlinearity of 104. Our contribution lies in proposing a new cost function that markedly reduces the generation complexity, bringing down the iteration count to under 50,000 for achieving the desired S-box. This advancement is particularly significant in the context of smart communication environments, where the balance between security and performance is paramount. [ABSTRACT FROM AUTHOR]

In this study, in order to do a life testing experiment, sampled units are divided into a prefixed number of groups with equal number of units. Units in all the groups are tested simultaneously and independently and, in each group the experiment is terminated as soon as a prefixed time elapses or a prefixed number of failures occurs. We provide the meta-analysis of an exponential lifetime data from Type-I hybrid censored samples. The main goal of this study is to obtain optimal schemes based on some optimality criteria by minimizing certain cost function that is based on a maximum likelihood estimator of mean lifetime. We provide the maximum likelihood estimator of mean lifetime and its probability density function under this set-up. Various optimal schemes have been provided by minimizing expected total cost incurred during the experiment as the raw moments can be obtained explicitly. Numerical results on bias and mean squared error of the maximum likelihood estimator have been reported. We also provide confidence intervals of the unknown parameter. For illustration, meta-analysis for a real data set of three groups is presented. [ABSTRACT FROM AUTHOR]

The paper is devoted to the study of duality in the linear Kantorovich problem with a fixed barycenter. It is proved that Kantorovich duality holds for general lower semicontinuous cost functions on completely regular spaces. In the course of considering this subject, the question of representation of a continuous linear functional by a Radon measure is raised and solved, provided that the barycenter of the functional is given by a Radon measure. In addition, we consider two new barycentric optimization problems and prove duality results for them. [ABSTRACT FROM AUTHOR]

Copyright of China Petroleum Machinery is the property of China Petroleum Machinery Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quantum error correction codes based on continuous variables play an important role for the implementation of quantum communication systems. A natural application of such codes occurs within quantum repeater systems which are used to combat severe channel losses and local gate errors. In particular, channel loss drastically reduces the distance of communication between remote users. Here, a cavity‐quantum electrodynamics (QED) based repeater scheme is considered to address the losses in the quantum channel. This repeater scheme relies on the transmission of a specific class of rotationally invariant error‐correcting codes. Several rotation‐symmetric bosonic codes (RSBCs) are compared for encoding the initial states of two remote users connected by a quantum repeater network against the convention of the cat codes and the performance of the system is quantified by using the secret key rate. In particular, the number of stations required to exchange a secret key over a fixed distance is determined and establish the resource overhead. For higher‐loss codes, the results show that a secret key rate (SKR) value of 0.01 bit per channel use can be achieved at a distance of 10000 km, with an elementary distance of 1.3 km. [ABSTRACT FROM AUTHOR]

In near‐term quantum computers like noisy intermediate‐scale quantum (NISQ) devices, reducing the impact of errors and decoherence is critical for practical implementation. Existing studies have primarily focused on Markovian noise sources; however, understanding the relationship between quantum error mitigation (QEM) and non‐Markovian noise sources is essential, as these effects are practically unavoidable in most solid‐state devices used for quantum computing. Here, a non‐Markovian model of quantum state evolution and a QEM cost function of controlled‐NOT (CNOT) gate operation are presented for NISQ devices interacting with an environment characterized by simple harmonic oscillators as a noise source. Using the projection operator formalism and both advanced and retarded propagators in time, the reduced‐density operator is derived for output quantum states in a time‐convolutionless form by solving the quantum Liouville equation. Output quantum state fluctuations are analyzed for identity and CNOT gate operations in two‐qubit operations across various input states and compare these results with experimental data from ion‐trap and superconducting quantum computing systems to estimate the key parameters of the QEM cost functions. These findings demonstrate that the QEM cost function increases as the coupling strength between the quantum system and its environment intensifies. This study highlights the significance of non‐Markovian models for understanding quantum state evolution and the practical implications of the QEM cost function in assessing experimental results from NISQ devices. [ABSTRACT FROM AUTHOR]

The process capability index (PCI) has been developed as a useful instrument for measuring how well a product matches customer expectations while also assessing the performance of a process. We are aware that when the quality characteristics of the processes follow normal distribution, conventional PCIs produces superior results. However, these traditional indices could not yield reliable findings when assessing nonnormally distributed processes, which could make decision-making more difficult. In this paper, we take into account the C N p m k c process capacity index, which may be used for both normally distributed and nonnormally distributed processes. We have employed 10 traditional methods of estimation to estimate the PCI C N p m k c when the process has a logistic-exponential distribution, and the performances of these traditional estimates of the index C N p m k c are compared in terms of their mean squared errors through a simulation exercise. Then, we create five PCI C N p m k c bootstrap confidence intervals and contrast them based on their average widths and related coverage probabilities. In order to demonstrate the applicability of the suggested methods of estimation, two data sets pertaining to the electronic industries are re-analyzed. [ABSTRACT FROM AUTHOR]

Copyright of Frontiers of Information Technology & Electronic Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: We propose a three-dimensional path-planning method to generate optimized surgical trajectories for steering flexible needles along curved paths while avoiding critical tracts in the context of surgical glioma resection. Methods: Our approach is based on an application of the rapidly exploring random tree algorithm for multi-trajectory generation and optimization, with a cost function that evaluates different entry points and uses the information of MRI images as segmented binary maps to compute a safety trajectory. As a novelty, an avoidance module of the critical neuronal tracts defined by the neurosurgeon is included in the optimization process. The proposed strategy was simulated in real-case 3D environments to reach a glioma and bypass the tracts of the forceps minor from the corpus callosum. Results: A formalism is presented that allows for the evaluation of different entry points and trajectories and the avoidance of selected critical tracts for the definition of new neurosurgical approaches. This methodology can be used for different clinical cases, allowing the constraints to be extended to the trajectory generator. We present a clinical case of glioma at the base of the skull and access it from the upper area while avoiding the minor forceps tracts. Conclusions: This path-planning method offers alternative curved paths with which to reach targets using flexible tools. The method potentially leads to safer paths, as it permits the definition of groups of critical tracts to be avoided and the use of segmented binary maps from the MRI images to generate new surgical approaches. [ABSTRACT FROM AUTHOR]

Summary: The cubature Kalman filter (CKF) based on the maximum correntropy criterion (MCC) has been widely used in the target tracking. However, numerical problems usually occur when there are outliers in the measurement noise. In order to solve the problems of state estimation under the non‐Gaussian measurement noise, a new combined cost function is defined based on the weighted least squares (WLS) method and MCC. In addition, a new method is also used to adaptively adjust the kernel size, then the improved maximum correntropy CKF (PMCCKF) and its corresponding improved maximum correntropy cubature information filter (PMCCIF) are proposed. Compared with the existing algorithms, the new method can not only obtain similar or even better estimation performance, but also avoid numerical problems. Moreover, when the kernel size is infinite, the performance of proposed algorithms will reduce to the standard CKF and corresponding cubature information filter (CIF) respectively, but the classical maximum correntropy CIF (MCCIF) will not, and even the performance is poor in this case. The advantages of the proposed algorithms are verified by four classical nonlinear models. [ABSTRACT FROM AUTHOR]

In this study, the authors consider an M/M/1 queuing system with attached inventory under an (s, S) control policy. The server takes multiple vacations whenever the inventory is depleted. It is assumed that the lead time and the vacation time follow exponential distributions. The authors formulate the model as a quasi-birth-and-dearth (QBD) process and derive the stability condition of the system. Then, the stationary distribution in product form for the joint process of the queue length, the inventory level, and the server's status is obtained. Furthermore, the conditional distributions of the inventory level when the server is on and operational, and when it is off due to a vacation, are derived. Using the stationary distribution, the authors obtain some performance measures of the system. The authors investigate analytically the effect of the server's vacation on the performance measures. Finally, several numerical examples are presented to investigate the effects of some parameters on the performance measures, the optimal policy, and the optimal cost. [ABSTRACT FROM AUTHOR]

The broiler industry is crucial in Malaysia’s agricultural sector, contributing significantly to meat production and the economy. However, the industry faces significant challenges, primarily stemming from high production costs, with feed costs constituting a substantial portion. Therefore, there is a need to improve domestic farm performance and competitiveness by optimizing resources and minimizing expenses to enhance overall productivity. This study aims to estimate the extent of cost efficiency in broiler farming in Peninsular Malaysia and identify key determinants influencing the inefficiency cost. A comprehensive survey involving 241 broiler farms in Peninsular Malaysia was conducted using structured questionnaires and a stratified random sampling technique. Employing the Stochastic Cost Frontier model revealed an operational inefficiency of approximately 5.7% above optimal costs among the surveyed farms, indicating substantial potential for a 5.7% reduction in production costs through enhanced management strategies. Factors such as feed prices, day-old chick prices, price of miscellaneous inputs, production output levels, and capital investment prices emerged as prominent influencers in the broiler cost function. Furthermore, the study indicated that socio-economic factors such as housing system, extension visits, credit access and contract farming are associated with lower inefficiencies, thereby enhancing cost efficiency in broiler farming operations. Conversely, higher bird mortality rates are associated with the increased inefficiency. Gaining insights into these factors is crucial for stakeholders to allocate resources wisely, plan strategically, and enhance competitiveness in broiler farming.

ABSTRACT Introduction HIV self‐testing (HIVST) is a promising strategy to improve diagnosis coverage among key populations (KP). The ATLAS (Auto Test VIH, Libre d'Accéder à la connaissance de son Statut) programme implemented HIVST in three West African countries, distributing over 380,000 kits up between 2019 and 2021, focussing on community‐led distribution by KP to their peers and subsequent secondary distribution to their partners and clients. We aim to evaluate the cost‐effectiveness of community‐led HIVST in Côte d'Ivoire, Mali and Senegal. Methods An HIV transmission dynamics model was adapted and calibrated to country‐specific epidemiological data and used to predict the impact of HIVST. We considered the distribution of HIVST among two KP—female sex workers (FSW), and men who have sex with men (MSM)—and their sexual partners and clients. We compared the cost‐effectiveness of two scenarios against a counterfactual without HIVST over a 20‐year horizon (2019–2039). The ATLAS‐only scenario mimicked the 2‐year implemented ATLAS programme, whereas the ATLAS‐scale‐up scenario achieved 95% coverage of HIVST distribution among FSW and MSM by 2025 onwards. The primary outcome is the number of disability‐adjusted life‐years (DALY) averted. Scenarios were compared using incremental cost‐effectiveness ratios (ICERs). Costing was performed using a healthcare provider's perspective. Costs were discounted at 4%, converted to $USD 2022 and estimated using a cost‐function to accommodate economies of scale. Results The ATLAS‐only scenario was highly cost‐effective over 20 years, even at low willingness‐to‐pay thresholds. The median ICERs were $126 ($88–$210) per DALY averted in Côte d'Ivoire, $92 ($88–$210) in Mali and 27$ ($88–$210) in Senegal. Scaling‐up the ATLAS programme would also be cost‐effective, and substantial epidemiological impacts would be achieved. The ICERs for the scale‐up scenario were $199 ($122–$338) per DALY averted in Côte d'Ivoire, $224 ($118–$415) in Mali and $61 ($18–$128) in Senegal. Conclusions Both the implemented and the potential scale‐up of community‐led HIVST programmes in West Africa, where KP are important to overall transmission dynamics, have the potential to be highly cost‐effective, as compared to a scenario without HIVST. These findings support the scale‐up of community‐led HIVST to reach populations that otherwise may not access conventional testing services.

The security-constrained AC optimal power flow (SCACOPF) is one of the most important problems that the industry has to solve on a daily basis in several electricity markets across the globe within strict time limits. Mathematically, the SCACOPF is formulated as a mixed-integer non-convex program, which is a very challenging class of problems to be solved in practice, and even obtaining feasible solutions can be difficult. In addition, most independent system operators (ISOs) impose a deterministic n-1 security criterion and, consequently, further increase the dimensionality of the problem. In this paper, we present an algorithmic approach that obtains a feasible solution to this problem with a 1-hour time limit. Our approach combines contingency selection, decomposition, and tailored warm start to the non-convex problem, and its performance is illustrated with our results in Challenge 2 of the Grid Optimization (GO) competition created by the U.S. Advanced Research Projects Agency-Energy (ARPA-E).

In order to solve the spectrum efficiency optimization problem of device-to-device (D2D) communication in many-to-one reusing mode, the channel allocation and power control problem in the frequency-selective channel environment is investigated. A resource allocation algorithm based on hierarchical optimization is proposed. The highly coupled resource allocation problem is decoupled by introducing the layering idea. Firstly, in the outer layer, a power control algorithm based on discrete power selection and two fast channel allocation algorithms based on priority setting are proposed. By using discrete power control for cellular users, the problem of multiple local optimal solutions is solved, which makes the power control algorithm of the whole system converge. Meanwhile, the proposed channel allocation algorithm reduces the complexity by setting priorities for D2D users, and at the same time realizes the suppression of cross-layer interference. In the inner layer, a resource allocation algorithm based on a non-cooperative game is proposed. By modeling D2D users share the same channel as a non-cooperative game model and introducing the cost function in term of same-layer interference, it achieves the suppression of same-layer interference while improving the spectrum efficiency. And the Nash equilibrium solution of the game is obtained by solving the KKT condition. Simulation experiments show that the proposed algorithm not only improves the spectrum efficiency of the system compared with the existing algorithms, but also proves the superiority of the algorithm in ultra-dense D2D communication scenarios.

This paper investigates possibilities of reducing production inefficiency using same input vector. Firms mostly suffer technical inefficiency in their production. Producers are found to operate below the frontier. Hence, empirical measures of production efficiencies are necessary to determine the inefficiency level, magnitude of inefficiency reduction, and gains that could be obtained by improving performance in the sector. The study used secondary data collected from Food and Agriculture Organization (FAO) and the National Bureau of Statistics (NBS) database. The dataset covers the period 1960-2021. Variables extracted included agricultural GDP (kg), fertiliser usage (kg), agricultural labour(man-days), and number of tractors (No). The data were subjected to a unit root test for stationarity, and a stochastic frontier production/ Cost function model were applied to determine technical inefficiency of variables in the model. The result of unit root shows that series are integrated of the first order I (1). AIC criteria indicate an optimal lag length of two years, while the Unrestricted Co-integration Trace and Maximum Eigenvalue test show strong evidence of long-run relationship amongst variables. The parameters of Stochastic Frontier Production Function estimated were positively consistent with the study’s a priori expectation for such variables as fertiliser (0.2634), labour (0.3159), land (0.1846), and tractor (0. 1587). Output-oriented technical efficiency is 0.7802 (78%) and 22% is technically inefficient. A decreasing returns to scale value of (0.9226) with a scale effect of 0.9226. The sector is 58% economically efficient with cost savings of 42% and 75% allocative efficiency. This study concludes that Nigeria’s agriculture suffers from production inefficiencies and this inefficiency can be reduced by using the same input levels.

The traditional six-step commutation control method in brushless DC motors (BLDCM) often results in significant torque ripple, which limits its application in high-precision fields. This paper proposes a scheme that combines finite control set model predictive control (FCS-MPC) to suppress commutation torque ripple. The scheme utilizes an optimal duty cycle and optimal switch compensation state. By analyzing the mathematical model of BLDC motors, the causes of commutation torque ripple were identified. To maintain the slope of the non-commutation current unchanged, a discrete model was used to predict the non-commutation current at the next moment. The predicted current was then used to calculate the optimal duty cycle. To address the shortcomings of PWM regulation performance at high speeds, a switch insertion compensation strategy was proposed. The strategy selects the optimal switch insertion compensation state based on a cost function to offset the changes in non-commutation current. Furthermore, feedback compensation was incorporated to enhance robustness in the event of parameter mismatch. The effectiveness of this method was demonstrated through experimental and simulation results.

The paper introduces a quadratic programming algorithm for real-time local path planning of autonomous vehicles. The algorithm relies on discretized sampling points and an enhanced cost function. Initially, we formulate the cost function to optimize the reference trajectory and establish the Frenet coordinate system. The drivable region undergoes discretization to generate sampling points in the Frenet coordinate system. We apply the principles of convex spatial obstacle avoidance to define the vehicle’s drivable area, taking into account the vehicle’s kinematics and establishing barrier boundary conditions. Subsequently, quadratic programming is employed to determine an optimal path within the vehicle’s drivable area. Concurrently, two cost functions are devised, the first evaluates the distance between the vehicle and obstacles, while the second assesses ride comfort, these cost functions are employed to evaluate sampling points and speed profiles, facilitating the planning of an optimal speed profile on the selected path. Finally, the algorithm undergoes validation through co-simulation using Matlab/Simulink, PreScan, and CarSim software. Various road scenarios, including straight and S-curve roads with both dynamic and static obstacles, are created to assess the method’s feasibility. The test results demonstrate the algorithm’s efficacy in avoiding moving and stationary obstacles and generating an ideal path compliant with driving conditions.

In modern transportation, autonomous driving technology has emerged as a significant innovation, offering improved safety, efficiency, and convenience. One of its core technologies is path planning, which creates an optimal route for vehicles in various traffic situations, ensuring they arrive safely and efficiently. However, existing path planning methods suffer from inflexible and inefficient road sampling, and limitations in path expression due to curve models. In this paper, we introduce a novel path planning framework that operates from a coarse-to-optimal approach. We first introduce an adaptive sampling method to construct a three-dimensional (3D) space-aware profiling map in the Frenet frame to quantify abstract traffic scenarios. This cost map guides the generation of waypoints by incorporating obstacle distributions in the $s$ -direction and cost values in the $l$ -direction. We then design a cost function to obtain the coarse path by considering ride comfort, anti-deviation from the center of the road, and path safety. Finally, a new path model is re-established based on the Taylor series, and a quadratic programming approach is employed to fine-tune the coarse path to attain the optimal path. Experimental results show that the proposed adaptive sampling method can dynamically adjust the sampling strategy according to the change in the number and distribution of obstacles on the road, significantly improving the sampling effectiveness rate to 100%, 99.85%, 99.68% and 99.61% for one-obstacle, two-obstacle, three-obstacle, and four-obstacle scenarios. Compared with the conventional method, the generated path length is shortened by 3.48% and 8.42%, and the maximum heading angle is reduced by 18.68% and 30.21% in the scenarios with obstacles of the same and different sizes.

Real-time stereo matching with high accuracy is a dynamic research topic; it is attractive in diverse computer vision applications. This paper presents a stereo-matching algorithm that produces high-quality disparity map while maintaining real-time performance. The proposed stereo-matching method is based on three per-pixel difference measurements with adjustment elements. The absolute differences and the gradient matching are combined with a colour-weighted extension of complete rank transform to reduce the effect of radiometric distortion. The disparity calculation is realized using improved dynamic programming that optimizes along and across all scanlines. It solves the inter-scanline inconsistency problem and increases the matching accuracy. The proposed algorithm is implemented on parallel high-performance graphic hardware using the Compute Unified Device Architecture to reach over 240 million disparity evaluations per second. The processing speed of our algorithm reaches 98 frames per second on 240 × 320-pixel images and 32 disparity levels. Our method ranks fourth in terms of accuracy and runtime for quarter-resolution images in the Middlebury stereo benchmark. [ABSTRACT FROM AUTHOR]

A novel single-phase 29-level asymmetrical switched-diode multilevel inverter (MLI) topology is presented in this paper with a reduced number of components. The developed topology can able to generate a maximum of 29-levels of output voltage using unequal DC sources. The basic 15-level MLI is developed and then further developed to 29-levels. The proposed topology reduces the circuit components, size and cost of the system. Apart from the several benefits of MLIs, reliability and accuracy plays a vital role because of the existence of more components count to reduce THD value. This can be considered as a major challenge employed to boost reliability without altering the best THD value. Various parameters are realized for both basic 15-level and the proposed 29-level switched-diode MLIs like total standing voltage (TSV), power loss, efficiency and cost function (CF). As the proposed MLI is undergone in dynamic load variations, the experimental results show the variations from R-load to L-load and L-load to R-load and it is found that the inverter is found to be stable throughout its operation. Experimental THD is represented, which is similar to the simulation THD which is under IEEE standards. TSV and cost factor of the proposed MLI is determined and is compared with several existing topologies and is observed to be cost-effective. A precise comparison is made on various parameters using graphical depiction.. The simulation for the proposed topology is done in MATLAB/Simulink and the experimental verification is done using the hardware prototype model under several conditions. [ABSTRACT FROM AUTHOR]

Most of the reduced switch multilevel inverters (MLIs), including switched capacitor MLIs (SC-MLIs), are designed with voltage sources/capacitors have obtained voltage levels with the addition of these sources only. This increases the number of voltage sources (capacitors) without full utilisation of these sources and has higher inverter total standing voltages, which leads the inverter inefficient (high conduction loss) and costly. The motivation of this work is to design a generalised reduced component MLI aiming for addition as well as subtraction of the voltage sources to obtain a voltage level, which results in the reduction of sources, enhance the voltage utilisation and lowering the inverter total standing voltage (TSV). The design parameters of the proposed MLI topology are compared with the recently developed MLIs in terms of the number of switches, capacitors and TSV to prove its superiority. The experimental prototype of the specimen 15-level and 27-level inverters is implemented using DS1103 and the corresponding results are presented. [ABSTRACT FROM AUTHOR]

Multilevel inverters (MLIs) have been widely accepted in several industrial applications. The advantages provided by MLI are achieved only through the use of several semiconductor switches and capacitors; consecutively increase the total system cost and complexity. To overcome the above limitations, this article develops a reduced device count hybrid MLI topology. The proposed MLI topology (PMLIT) can produce a 9-level voltage waveform with symmetrical sources and a 7-, 11-level output voltage waveform with asymmetrical sources using a single cell. In addition, PMLIT can be extended to produce any number of voltage levels by cascade connection of the cells with the built-in ability to produce both negative and positive voltage levels. Also, the voltage across the used capacitor is self-balanced without the use of any external components. The comparative investigation reveals the superior characteristics of the PMLIT in terms of the components and total blocking voltage over the newly and conventional topologies. Also, the calculated cost function shows that the PMLIT is more economical than the recently developed topologies. Finally, the viability of the PMLIT has been validated by conducting various tests on the simulation platform and also experimentally for 7, 9, 11 and 81 levels under diverse operating conditions. [ABSTRACT FROM AUTHOR]

The rapid development of wireless communication technology has led to an increasing number of internet of thing (IoT) devices, and the demand for spectrum for these devices and their related applications is also increasing. However, spectrum scarcity has become an increasingly serious problem. Therefore, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources so that IoT devices can access them and, meanwhile, avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of sensing the PUs signal in IoT devices, the issue of sensing time and decision cost (the cost of determining whether the signal state of the PU is correct or incorrect) arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the sensing time and cost functions for IoT devices and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal sensing time problem as a finite horizon problem and solve the threshold of the optimal decision rule by person-by-person optimization (PBPO) methodology and dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various costs of each observation taken and thresholds. [ABSTRACT FROM AUTHOR]

This paper presents an optimal structure of a frequency-reconfigurable SIW antenna, where reconfigurability is achieved using PIN diodes. The antenna is optimized using the PSO (Particle Swarm Optimization) algorithm implemented and developed in MATLAB. The antenna is based on Substrate Integrated Waveguide technology, comprising three slot resonators positioned at the bottom of the SIW antenna. PIN diodes are placed on the structure's feed line to modify the antenna's resonant frequency, making it usable on different Xband frequencies. The PSO algorithm aims to determine the optimum position of the PIN diodes and the size of each slot according to the state of the PIN diode (ON or OFF). The optimized reconfigurable SIW antenna is designed, manufactured, and measured to operate over different frequency bands depending on the diode bias state. Measured gain reaches maximum values of 8.6 dB, 9.4 dB, 9.2 dB and 8.8 dB respectively for OFF-OFF, OFF-ON, ON-OFF and ON-ON bias states. [ABSTRACT FROM AUTHOR]

This paper investigates possibilities of reducing production inefficiency using same input vector. Firms mostly suffer technical inefficiency in their production. Producers are found to operate below the frontier. Hence, empirical measures of production efficiencies are necessary to determine the inefficiency level, magnitude of inefficiency reduction, and gains that could be obtained by improving performance in the sector. The study used secondary data collected from Food and Agriculture Organization (FAO) and the National Bureau of Statistics (NBS) database. The dataset covers the period 1960-2021. Variables extracted included agricultural GDP (kg), fertiliser usage (kg), agricultural labour(man-days), and number of tractors (No). The data were subjected to a unit root test for stationarity, and a stochastic frontier production/Cost function model were applied to determine technical inefficiency of variables in the model. The result of unit root shows that series are integrated of the first order I (1). AIC criteria indicate an optimal lag length of two years, while the Unrestricted Co-integration Trace and Maximum Eigenvalue test show strong evidence of long-run relationship amongst variables. The parameters of Stochastic Frontier Production Function estimated were positively consistent with the study's a priori expectation for such variables as fertiliser (0.2634), labour (0.3159), land (0.1846), and tractor (0. 1587). Output-oriented technical efficiency is 0.7802 (78%) and 22% is technically inefficient. A decreasing returns to scale value of (0.9226) with a scale effect of 0.9226. The sector is 58% economically efficient with cost savings of 42% and 75% allocative efficiency. This study concludes that Nigeria's agriculture suffers from production inefficiencies and this inefficiency can be reduced by using the same input levels. [ABSTRACT FROM AUTHOR]

Survey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number under uncertain environment due fuzziness and indeterminacy. Therefore, this information is expressed by neutrosophic numbers rather than the classical numbers. The neutrosophic statistics, which is generalization of classical statistics, deals with the neutrosophic data that has some degree of indeterminacy and fuzziness. In this study, we investigate the compromise optimum allocation problem for estimating the population means of the neutrosophic study variables in a multi-character stratified random sampling under uncertain per unit measurement cost. We proposed the intuitionistic fuzzy cost function, modeling the fuzzy uncertainty in stratum per unit measurement cost. The compromise optimum allocation problem is formulated as a multi-objective intuitionistic fuzzy optimization problem. The solution methodology is suggested using neutrosophic fuzzy programming and intuitionistic fuzzy programming approaches. A numerical study includes the means estimation of atmospheric variables is presented to explore the real-life application, explain the mathematical formulation, and efficiency comparison with some existing methods. The results show that the suggested methods produce more precise estimates with less utilization of survey resources as compared to some existing methods. The Python is used for statistical analysis, graphical designing and numerical optimization problems are solved using GAMS.

This paper is about the effectiveness of the Cobb-Douglas (C-D) production function in industrial optimization, estimating the number of factors used in the production process of the water industry, for instance, capital and human labor. Moreover, we have modeled a nonlinear optimization problem for a local water industry using two and three factors of production. For this purpose, we have taken into account the Cobb-Douglas production function with different production factors using the Lagrange multiplier method with the ordinary least squares method. In the course of the solution, a linear function is used to calculate the cost function, and the C-D production function is used to calculate the production function. The Lagrange multiplier method with the ordinary least squares method is then used to solve the constrained optimization problem for the product of production. Furthermore, we compared the outcomes from both examples of two- and three-factor C-D production functions in order to validate the Lagrange multiplier method for the C-D production function. Moreover, the three-factor C-D production function is solved by the Lagrange multiplier method with the ordinary least squares method, which provides optimal results as compared to previous studies in literature. The validity of the proposed methodology is explained by using the products of a local production industry in Pakistan.

The paper deals with the problem of securing a guaranteed victory for our side in the course of military operations, when the dynamic power of the enemy is known. The problem of the set of weapons for a guaranteed victory is solved. A method is given for calculating the set of weapons and equipment that guarantees victory without regard to information on the set of weapons and equipment of the opposing side for any set. The method of composing and solving matrix games in game theory is used. The problem is modeled as a matrix game with mixed strategies, and the existence of its solution (saddle point) is shown in this setting. To obtain a numerical solution of the problem, the matrix game is reduced to the linear programming problem.