Switching Problem Research Articles

Preface

From 16 to 18 September 2020, in the city of Voronezh, on the basis of the Voronezh State Technical University, The II International Theoretical and Practical Conference on Alternative and Smart Energy (TPCASE-2020) was held online aie.cchgeu.ru. The co-organizer of this scientific event was the Academy of Engineering Sciences named after A.M. Prokhorov.Energy today is the most important driving force of world economic progress, and the well-being of billions of the world’s inhabitants directly depends on its state. The steady increase in the number of people leads to an increase in energy consumption. Every day more and more reserves of natural resources (coal, gas, oil) necessary for the operation of traditional energy are being depleted, so the problem of switching from traditional sources of energy is becoming more and more urgent. In addition to the prospect of depletion of traditional sources, there is also an environmental problem, since the combustion of hydrocarbon fuels leads to harmful emissions into the atmosphere, worsening the human habitat, creating environmental problems. Therefore, it is important to find new energy sources that are safer from an environmental point of view.The world has already seen significant progress in the use of alternative, renewable energy sources.

Modified Optical Burst Switching (OBS) Based Edge Node Architecture Using Real-Time Scheduling Techniques

Contention is the main problem in optical burst switching (OBS) systems that lead to loss more burst by dropping the contended burst. To deal with this problem, we propose a new proactive method which is based on the integration of Real-Time Scheduling Techniques: Earliest-deadline-first (EDF) and round-robin (RR). Based on this consideration, this paper proposes a series of novel coherent interdependence methods to propose a novel OBS edge node Architecture: (i) An adaptive priority system to obtain QoS guarantees, (ii) Admission control and bandwidth distribution to maximize the link throughput. The proposed technique classifies the incoming data packets into two categories: granted service (GS) for high priority and best effort (BE) for low priority. The RR technique is used for scheduling different BE and GS packets when they have the same deadlines while the EDF is used to manage GS packets with different deadlines. In addition, the admission and bandwidth assignment policies vary in function of traffic characteristics. For GS traffic, only the bandwidth used is needed, while the remaining bandwidth is assigned to best effort traffic. With the EDF and RR scheduling algorithms, the proposed edge node design obtains a brand new architecture. The proposed OBS architecture has been tested for dynamic traffic in which both BE and GS traffic arrives according to a Poisson distribution for different scenarios based on traffic distribution and switch resources reservation. In scenario#1, 90% GS traffic and 10% BE traffic and reserve 7% of the switch resources for BE traffic are considered. Therefore, the proposed architecture provides a higher grade of service to the end-users with the guaranteed service level of agreements than the existing architecture that does not implement resource reservation protocols. In addition, the modified OBS-edge node is designed and implemented on FPGA Virtex-11C2V40. The hardware performance analysis shows that the network dimension is a key factor in latency measurement. A 2×2 network dimension can serve approximately 230 Mbps throughput and approximately 400 Mbps in the case when the number of flits (segment of burst) is twice.

A computationally efficient authentication and key agreement scheme for multi-server switching in WBAN

In the wireless body area network (WBAN), the wearable device can monitor the patient's physiological information and send information to a server so that doctors can remotely diagnose the patient. As the patient's physiological information is sensitive, transmitting the data in the WBAN may reveal patient's privacy. In addition, in a multi-server environment, each server is usually independent of each other. However, most existing authentication schemes for WBAN either use a single-server model or do not consider multi-server switching issues. Therefore, we propose a computationally efficient mutual authentication and key agreement scheme for multi-server switching in WBAN. Our scheme ensures that patients can implement secure switching servers at any time in a multi-server environment. Our scheme proves to be secure under the Real-Or-Random model and ProVerif. In addition, compared with related schemes, our scheme solves the server switching problem while reducing the computational cost.

Bumpless Transfer Control for Gas Turbine

This paper mainly studies a bumpless transfer controller which can be applied to a certain gas turbine. Due to the requirements of low exhaust emission and high combustion efficiency, the gas supply system of the gas turbine is composed of duty fuel, master fuel, and secondary fuel, which inevitably lead to the switching problem in the control system. In order to solve this problem, we have built a three-branch natural gas supply system in the Amesim software and established a gas turbine model in the Simulink software according to its mechanism. In addition, the gas turbine model and the natural gas system model are jointly simulated through the interface. Finally, in accordance with the traditional PID gas turbine controller, an active disturbance rejection controller (ADRC) is designed, which is combined with a bumpless transfer controller including differentiator and integrator to suppress the interference caused by fuel switching. The effectiveness and superiority of this strategy are verified by the complete joint simulations.

A case of optimal switching with signed switching costs

In this work we show that one can solve a set of multi-modes optimal switching problems with a particular, very natural form of signed costs. The problems are a special type of impulse control problems where the control set is discrete and the system is operated continuously over a finite horizon.

ANALISIS ALIH KODE DAN CAMPUR KODE PADA TUTURAN ACARA INI TALK SHOW DI YOUTUBE

This research discusses the problems of Code Switching and Code Mixing that occur in the speech title speech in Ini Talk Show . The purpose of this research was to describe the form of Code Switching and Code Mixing performed by speakers at the event. The method used by Researchers in this research is a descriptive qualitative method. In this Research, The role of The researcher is an instrument and data collector. The data collection technique is done by observing, listening, and taking notes. The results of the research found that code-switching and code-mixing were carried out by speakers at the event. Researchers found the Switching of Codes Internal from Indonesian into Sundanese. Switching of Codes External from Indonesian into English, English into Indonesian, Indonesian into Arabic, and from English into Javanese. Whereas Mix code researchers found in the form of words, phrases, baster, and clause. Factors that cause Code Switching are motivated by speakers, interlocutors, the presence of a third person, and to generate a sense of humor. Meanwhile, code-mixing is motivated by the language of the speaker and interlocutor, and tries to interpret or explain.

An Online Policy for Energy-Efficient State Control of Manufacturing Equipment

Machine state control is one of the most promising energy-efficient measures for machining processes. A proper control reduces the energy consumed during idle periods by switching off/on the machines. A critical barrier for practical implementation is related to the knowledge of part arrival process that is affected by uncertainty. The stochastic processes involved in the system are usually assumed to be known. However, real production environments are subject to several sources of randomness that are difficult to model a priori. This work provides an online time-based algorithm that is able to control the machine state. Through a method for the estimation of the stochastic process, the algorithm provides the optimal control parameters based on a collected set of observations. A new policy is formulated to manage the control over time such that changes in the control parameters are applied only under certain conditions. Potential benefits are discussed using realistic numerical cases. Note to Practitioners-This article analyzes the control problem of switching off/on a machine tool for energy saving during machine idle periods. A control policy based on time information is investigated when the machine requires a startup time to resume the service after being switched off. The proposed policy works online while acquiring information from the real system. An algorithm is described for identifying and applying the optimal control parameters. The results of this research will be useful for a practical implementation of a switching policy for energy saving. This implementation requires the estimation of the power adsorbed by the machine in four different states and, therefore, it reduces the implementation effort for practitioners.

Considering the Impact of Changing Alphabet on Education

The article is an experience of understanding the impact of changing alphabet on the educational process. Scientific interest in this issue is due, first of all, to long discussions about the transition of the Republic of Kazakhstan from Cyrillic to Latin script, which have been particularly relevant since 2015. The issues of changing the alphabet were the focus of both scientific study and discussion by various segments of society, both in the country and abroad. This year, 2020, has put on the agenda one of the main issues for the entire modern world - the fight against the global pandemic and pushed to the background the problem of switching to a new schedule. This allows us to confirm the opinion of some researchers about the change of script as a political project than another one. However, a number of issues are still being discussed. What will be the consequences of switching to an another script? Will the changing improve the countrys intellectual potential? Will it increase the countrys competitiveness? And this is only part of the question. There are no clear answers to the question about the impact of changing script on the educational process.

Phase-only modulation of light.

We disclose the method to obtain polarization insensitive phase-only modulation that preserves both the state and the degree of polarization of light modulated using a medium with controlled birefringence. We find that, in the double-pass configuration involving reflection from the Faraday rotator mirror, such a medium acts as the phase-only modulator. The experimental data measured in the Michelson-interferometer-based setup for deformed-helix ferroelectric liquid crystal cells are found to be in good agreement with the theoretical results. For such cells, we experimentally demonstrate high-frequency (4 kHz modulation rate) 2π phase-only light modulation governed by the average phase shift and solve the problem of optical axes switching.

A simple and effective hybrid genetic search for the job sequencing and tool switching problem

The job Sequencing and tool Switching Problem (SSP) has been extensively studied in the field of operations research, due to its practical relevance and methodological interest. Given a machine that can load a limited amount of tools simultaneously and a number of jobs that require a subset of the available tools, the SSP seeks a job sequence that minimizes the number of tool switches in the machine. To solve this problem, we propose a simple and efficient hybrid genetic search based on a generic solution representation, a tailored decoding operator, efficient local searches and diversity management techniques. To guide the search, we introduce a secondary objective designed to break ties. These techniques allow to explore structurally different solutions and escape local optima. As shown in our computational experiments on classical benchmark instances, our algorithm significantly outperforms all previous approaches while remaining simple to apprehend and easy to implement. We finally report results on a new set of larger instances to stimulate future research and comparative analyses.

Approximate Bayesian computation for finite mixture models

Finite mixture models are used in statistics and other disciplines, but inference for mixture models is challenging due, in part, to the multimodality of the likelihood function and the so-called label switching problem. We propose extensions of the Approximate Bayesian Computation–Population Monte Carlo (ABC–PMC) algorithm as an alternative framework for inference on finite mixture models. There are several decisions to make when implementing an ABC–PMC algorithm for finite mixture models, including the selection of the kernels used for moving the particles through the iterations, how to address the label switching problem and the choice of informative summary statistics. Examples are presented to demonstrate the performance of the proposed ABC–PMC algorithm for mixture modelling. The performance of the proposed method is evaluated in a simulation study and for the popular recessional velocity galaxy data.

Distinct performance profiles on the Brixton test in frontotemporal dementia

The Brixton Spatial Anticipation Test is a well-established test of executive function that evaluates the capacity to abstract, follow, and switch rules. There has been remarkably little systematic analysis of Brixton test performance in the prototypical neurodegenerative disorder of the frontal lobes: behavioural variant frontotemporal dementia (bvFTD) or evaluation of the test's ability to distinguish frontal from temporal lobe degenerative disease. We carried out a quantitative and qualitative analysis of Brixton performance in 76 patients with bvFTD and 34 with semantic dementia (SD) associated with temporal lobe degeneration. The groups were matched for demographic variables and illness duration. The bvFTD group performed significantly more poorly (U=348, p<.0001, r=.58), 53% of patients scoring in the poor-impaired range compared with 6% of SD patients. Whereas bvFTD patients showed problems in rule acquisition and switching, SD patients did not, despite their impaired conceptual knowledge. Error analysis revealed more frequent perseverative errors in bvFTD, particularly responses unconnected to the stimulus, as well as random responses. Stimulus-bound errors were rare. Within the bvFTD group, there was variation in performance profile, which could not be explained by demographic, neurological, or genetic factors. The findings demonstrate sensitivity and specificity of the Brixton test in identifying frontal lobe degenerative disease and highlight the clinical value of qualitative analysis of test performance. From a theoretical perspective, the findings provide evidence that semantic knowledge and the capacity to acquire rules are dissociable. Moreover, they exemplify the separable functional contributions to executive performance.

Infinite-Horizon Optimal Switching Regions for a Pair-Trading Strategy with Quadratic Risk Aversion Considering Simultaneous Multiple Switchings: A Viscosity Solution Approach

Very few studies have explored the structure of optimal switching regimes. We extend the existing research on the infinite-horizon multiple-regime switching problem with an arbitrary number of switch options by replacing the linear running reward function with a quadratic function in the objective function. To make our analysis more rigorous, we establish the theoretical basis for the application of the simultaneous multiple-regime switches to the problem with the extended objective function, and provide the sufficient condition under which each certain separated region in the space includes, at most, one single connected optimal switching region, which determines the structure of the optimal switching regions, and we identify the structure of the optimal switching regions for the particular problem.

Analysis and Implementation of Inverter Wide-Range Soft Switching in WPT System Based on Class E Inverter

This article addresses the problem of hard switching caused by the change of equivalent load in a wireless power transfer (WPT) system based on a class E inverter. Based on the load-sensitive characteristics of the class E inverter, the coil structure is improved, and the self/mutual inductance compensation method of the transmitting coil is proposed to realize a wide range of soft switching. On the basis of fully considering the coupling relationship between the source and load coils, a coil structure with multiple coils in series on the primary side is proposed, and the cross-coupling relationship between the coils is analyzed in detail and simplified. The inverter parameters and coupling mechanism were adjusted by means of coil series reverse connection. Combined with the parameter influence law and the load equivalent principle of the class E inverter, the margin of soft switching at the inverter side was increased and the load offset correction was carried out. The soft-switching effect of the equivalent load from 0 to 3.3 times of ideal load was obtained, and the purpose of improving system reliability and efficiency was achieved. Finally, the feasibility and effectiveness of the proposed method were verified by simulation and experiment.

Fully Soft-Switched High Step-Up Nonisolated Three-Port DC–DC Converter Using GaN HEMTs

In this article, a soft-switched nonisolated high step-up multi-input dc–dc converter is proposed. The proposed converter has overcome the hard switching problem of the conventional boost three port converter (boost-TPC) by providing zero-voltage-switching condition for all switches at various operating modes. The proposed converter uses coupled inductors technique to enhance the voltage gain and utilizes the leakage inductance energy and the energy storage device power path to provide soft switching condition. In addition, the voltage stress of the main switch is reduced which has led to utilizing low R ds(ON) switches. Various converter operating modes are presented and design considerations are discussed. To evaluate the proposed converter performance, two prototypes of the proposed converter are implemented utilizing the latest generation gallium nitride high electron mobility transistors and the mature Si MOSFETs technology. The results show that the proposed converter efficiency is enhanced in comparison with the conventional boost-TPC converter.

Problems of business processes transformation in the context of building digital economy

The article explores the main problems and features of one of the most relevant phenomena today - digital transformation, which implies fundamental changes in the activities of organizations based on the use of digital technologies. The paper reviews sources on the problems of building a digital economy and moving a business to the digital level. The purpose of this study is to identify the main difficulties for the restructuring of organizations' processes on a digital format, as well as the formation of the theoretical and conceptual foundations of digital business transformation in the face of uncertainty and variability of the modern business environment. Using the methods of analysis, generalization, comparison, synthesis, deduction, induction, the essence of digital transformation is studied, Russia's positions among other countries in terms of readiness for the digital economy are analyzed, problems and barriers that impede the process of digital transformation for Russian and foreign companies are formulated. Based on the use of a systematic approach, methods of scientific abstraction, economic modelling, the work identifies the main functional areas of change, presents a loop of digital business transformation that reflects its main stages, necessary components and changes, and describes key segments of new digital business models of companies. The results can be used to conduct further theoretical and methodological and practice-oriented research in the field of digital business transformation, and can also be used by design teams of organizations to analyze the problems of switching to a digital format, develop a digital transformation strategy and rebuild a business model.

Evaluating and Optimizing Opportunity Fast-Charging Schedules in Transit Battery Electric Bus Networks

Public transport operators (PTOs) increasingly face a challenging problem in switching from conventional diesel to more sustainable battery electric buses (BEBs). In this study, we optimize the opportunity fast-charging schedule of transit BEB networks in order to minimize the charging costs and the impact on the grid. Two mixed-integer linear programming (MILP) formulations that use different discretization approaches are developed and compared. Discrete-Time Optimization (DTO) resembles a time-expanded network that discretizes the time and decisions to equal discrete slots. Discrete-Event Optimization (DEO) discretizes the time and decisions into nonuniform slots based on arrival and departure events in the network. In addition to the DEO’s higher practicability, the comparative computational study carried out on the transit-bus network in the city of Rotterdam, Netherlands, shows that the DEO is superior to the DTO in terms of computational performance. To show the potential benefits of the optimal schedule, it is compared with two reference common-sense greedy strategies: First-in-First-Served and Lowest-Charge-Highest-Priority.

Sensor Switching Control Under Attacks Detectable by Finite Sample Dynamic Watermarking Tests

Control system security is enhanced by the ability to detect malicious attacks on sensor measurements. Dynamic watermarking can detect such attacks on linear time-invariant systems. However, existing theory focuses on attack detection and not on the use of watermarking in conjunction with attack mitigation strategies. In this article, we study the problem of switching between two sets of sensors: One set of sensors has high accuracy but is vulnerable to attack, whereas the second set of sensors has low accuracy but cannot be attacked. The problem is to design a sensor switching strategy based on attack detection by dynamic watermarking. This requires new theory because existing results are not adequate to control or bound the behavior of sensor switching strategies that use finite data. To overcome this, we develop new finite sample hypothesis tests for dynamic watermarking in the case of bounded disturbances, using the modern theory of concentration of measure for random matrices. Our resulting switching strategy is validated with a simulation analysis in an autonomous driving setting, which demonstrates the strong performance of our proposed policy.

Improved multiobjective switching gain‐scheduled controller synthesis exploiting inexact scheduling parameters

SummaryIn this article, the design problem of switching gain‐scheduled output‐feedback (SGSOF) controller with mixed performance exploiting inexact scheduling parameters for continuous‐time linear parameter‐varying (LPV) systems is tackled. The absolute and proportional uncertainties on the scheduling parameters are considered. All the system matrices of the LPV plant are supposed to have polynomial dependency of arbitrary degree on the scheduling parameters. By exploiting hysteresis switching law and utilizing two independent families of parameter‐dependent Lyapunov matrices and a family of slack variables, introducing additional degrees of freedom, performance improvement is achieved. A design approach, involving a two‐step algorithm, is proposed in terms of solutions to a set of parameter‐dependent linear matrix inequalities (LMIs) including parameter searches for two scalar values. The merit of the proposed method lies in its less conservativeness in comparison with the available approaches in the literature. Numerical studies are carried out to demonstrate the effectiveness of the presented method.

DRAG: Deep Reinforcement Learning Based Base Station Activation in Heterogeneous Networks

Heterogeneous Network (HetNet), where Small cell Base Stations (SBSs) are densely deployed to offload traffic from macro Base Stations (BSs), is identified as a key solution to meet the unprecedented mobile traffic demand. The high density of SBSs are designed for peak traffic hours and consume an unnecessarily large amount of energy during off-peak time. In this paper, we propose a deep reinforcement-learning based SBS activation strategy that activates the optimal subset of SBSs to significantly lower the energy consumption without compromising the quality of service. In particular, we formulate the SBS on/off switching problem into a Markov Decision Process that can be solved by Actor Critic (AC) reinforcement learning methods. To avoid prohibitively high computational and storage costs of conventional tabular-based approaches, we propose to use deep neural networks to approximate the policy and value functions in the AC approach. Moreover, to expedite the training process, we adopt a Deep Deterministic Policy Gradient (DDPG) approach together with a novel action refinement scheme. Through extensive numerical simulations, we show that the proposed scheme greatly outperforms the existing methods in terms of both energy efficiency and computational efficiency. We also show that the proposed scheme can scale to large system with polynomial complexities in both storage and computation.