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Este artículo estudia el desempeño comercial de los 12 principales países exportadores de bienes industriales en el periodo 2004-2013, analizando tanto la pretendida asociación existente entre la productividad laboral y la competitividad externa, como el rol de las industrias altamente tecnológicas en el éxito exportador. La aplicación de la metodología de Wang, Wei, y Zhu (2018), a partir del uso de matrices insumo-producto globales, para el caso del comercio de E.U y China, muestra el mejor posicionamiento de E.U en CGV y ejemplifica la relevancia de las nuevas dinámicas productiva globales para la evaluación del comercio internacional a nivel sectorial.

This article addresses the issue of input–output finite-time stability (IO-FTS) for nonlinear systems by employing sliding-mode control (SMC) methodology. Many practical systems subject to complex factors, such as the single-link robot arm model (SLRAM), can be characterized as nonlinear systems. Our attention is focused on designing a fuzzy-model-based finite-time SMC law to attenuate the influences of uncertainty, nonlinear term, and external disturbance during the finite-time region. First, a novel integral sliding-mode surface is proposed based on the Takagi–Sugeno fuzzy rule. Then, by using the key point of Lyapunov function theory, an appropriate fuzzy SMC law is designed to make sure that the signal variables can arrive at a domain within the assigned fixed-time level. Moreover, some new IO-FTS criteria are constructed for the resulting sliding dynamics over the whole finite-time level, including reaching phase and sliding motion phase. Via the SLRAM, we demonstrate the effectiveness of the proposed SMC approach.

Several new statistical tools and analytical frameworks have been recently developed to measure countries’ and sectors’ involvement in global value chains. Such a wealth of methodologies reflects the fact that different empirical questions call for distinct accounting methods and different levels of aggregation of trade flows. In this article, we describe icio, a new command for the computation of the most appropriate measures of trade in value added as well as participation in global value chains. icio follows the conceptual framework proposed by Borin and Mancini (2019, Policy Research Working Paper WPS 8804; WDR 2020 Background Paper, World Bank Group), which in turn extends, refines, and reconciles the other main contributions in this strand of the literature. icio is flexible enough to work with any intercountry input–output table and with any level of aggregation of trade flows.

An extracellular electric field (EF) induces transmembrane polarizations on extremely inhomogeneous spaces Evidence shows that EF-induced somatic polarization in pyramidal cells can modulate the neuronal input-output (I/O) function. However, it remains unclear whether and how dendritic polarization participates in the dendritic integration and contributes to the neuronal I/O function. To this end, we built a computational model of a simplified pyramidal cell with multi-dendritic tufts, one dendritic trunk, and one soma to describe the interactions among EF, dendritic integration, and somatic output, in which the EFs were modeled by inserting inhomogeneous extracellular potentials. We aimed to establish the underlying relationship between dendritic polarization and dendritic integration by analyzing the dynamics of subthreshold membrane potentials in response to AMPA synapses in the presence of constant EFs. The model-based singular perturbation analysis showed that the equilibrium mapping of a fast subsystem can serve as the asymptotic subthreshold I/O relationship for sublinear dendritic integration. This allows us to predict the tendency of EF-mediated dendritic integration by showing how EF changes modify equilibrium mapping. EF-induced hyperpolarization of distal dendrites receiving synapses inputs was found to play a key role in facilitating the AMPA receptor-evoked excitatory postsynaptic potential (EPSP) by enhancing the driving force of synaptic inputs. A significantly higher efficacy of EF modulation effect on global AMPA-type dendritic integration was found compared with local AMPA-type dendritic integration. During the generation of an action potential (AP), the relative contribution of EF-modulated dendritic integration and EF-induced somatic polarization was determined to show their collaboration in promoting or inhibiting the somatic excitability, depending on the EF polarity. These findings are crucial for understanding the EF modulation effect on neuronal computation, which provides insight into the modulation mechanism of noninvasive brain modulation.

The amygdala, one of the most studied brain structures, integrates brain-wide heterogeneous inputs and governs multidimensional outputs to control diverse behaviors central to survival, yet how amygdalar input-output neuronal circuits are organized remains unclear. Using a simplified cell-type- and projection-specific retrograde transsynaptic tracing technique, we scrutinized brain-wide afferent inputs of four major output neuronal groups in the amygdalar basolateral complex (BLA) that project to the bed nucleus of the stria terminals (BNST), ventral hippocampus (vHPC), medial prefrontal cortex (mPFC) and nucleus accumbens (NAc), respectively. Brain-wide input-output quantitative analysis unveils that BLA efferent neurons receive a diverse array of afferents with varied input weights and predominant contextual representation. Notably, the afferents received by BNST-, vHPC-, mPFC- and NAc-projecting BLA neurons exhibit virtually identical origins and input weights. These results indicate that the organization of amygdalar BLA input-output neuronal circuits follows the input-dependent and output-independent principles, ideal for integrating brain-wide diverse afferent stimuli to control parallel efferent actions. The data provide the objective basis for improving the virtual reality exposure therapy for anxiety disorders and validate the simplified cell-type- and projection-specific retrograde transsynaptic tracing method.

Global climate change is an alarming problem nowadays. Weather temperatures have been uncertain because of what many scientists claim is the effect of greenhouse gases, contributed mainly by the energy industry. In Malaysia, the energy industry provides a significant contribution to it economy making up about 20 percent of the GDP. Malaysia is the third largest natural gas exporter in the Asia-Pacific region in 2011 and eleventh in the world (British Petroleum Statistical Review of World Energy, 2014). Malaysia's CO2 emission recorded at 185 million tonnes in 2010 (International Energy Agency, 2012). Mohd Safaai et al. (2011) projected that without any mitigation measures 285.73 million tonnes of CO2 will be released in 2020. In the Copenhagen forum 2009, Malaysia has pledged to reduce 40% of carbon emissions by 2020 compared to the 2005 levels. Motivated by the government efforts, this study will construct environmentally extended input-output framework for Malaysia to obtain the energy-related CO2 emission intensities by sectors. The study is responded to the inadequate of reliable data on Malaysia’s sectoral CO2 emissions and to the growing awareness of the effectiveness of Malaysia climate change policies. This study expanding the current understanding of interactions among economic activities, energy intensities, and CO2 emissions. Results of this study found that Transportation recorded the second highest contributor to CO2 emission, and these findings were different to many other existing studies that found transportation sector as a main contributor to CO2 emission. In addition, results suggest that it is necessary to control environmental problems and encourage the energy use efficiency in the production process, particularly in the Building and construction sector, Transportation, Electricity, gas and water and Agriculture sector in Malaysia The findings will help the policy-makers particularly in Malaysia to develop a strategic plan and tools to manage CO2 emission with respect to climate change in these four sectors.

When economic shocks occur, whether at home or abroad, economic agents are expected to react to reduce the negative impact or amplify the positive effects. The ability of a country to contain econo...

Regional industrialisation and integration form part of the economic policy priorities of a number of countries in Southern Africa and of the Southern African Development Community (SADC). Manufact...

The production process in the system of economic cycle of the national economy, as well as the relevant tools for the study of production processes, is considered. The production infrastructure of the national economy is studied as an important part of critical infrastructure, reproduction processes. Production is considered in the context of the formation of added value by large groups of types of economic activity, at the institutional and regional levels, in the context of making management decisions at the macro- and microeconomic levels. The inter-industry balance sheet tools are defined as the basic one for assessing production processes and their criticality. To this end, aggregated three-sector input-output tables in producer’s prices for a number of countries have been prepared. Within their framework, the sectoral structure of the economy is considered, direct costs and full costs (Leontief matrix) are determined, indicators of criticality of the production infrastructure are determined. It is proposed to assess the criticality of production infrastructure using such parameters as the share of gross added value in output, the cost of sectors and the economy as a whole, the coefficients of impact and recall, the classification of industries into key, with direct and inverse impact, etc. Comparative studies of criticality indicators for a number of countries were carried out, in particular, direct costs and derivative indicators of criticality of the production system (Frobenius number, Frobenius vector, etc.) were determined. The proposed approaches to improving the parameters of criticality of the production infrastructure of the Ukrainian economy were worked out.

By incorporating a logic-based switching mechanism into high-gain linear controllers, global output-feedback adaptive stabilization is achieved for a class of nonlinear systems with unknown input–output-dependent lower-triangular growth rate and uncertain control coefficient. When a controller candidate, associated with a Lyapunov candidate, is connected into the closed-loop, the logic unit constantly supervises the change rate of the Lyapunov candidate. If it does not decrease as rapidly as predicted, another controller candidate will be switched in to replace the former one. It is theoretically proved that there is only a finite number of switching times, and asymptotic stability of the closed-loop system is guaranteed. Compared with existing results, the logic-based switching adaptive control approach can tolerate strong input–output-dependent nonlinearities, as well as large uncertainties from the system dynamics including the control coefficient. Finally, a numerical example is provided to illustrate the feasibility and the effectiveness of the proposed approaches.

The emergence of Industry 4.0 has resulted in a rapid increase in the demand for bandwidth due to the proliferation of the industrial Internet of Things (IIoT). Increased utilization of the network also gives rise to undesirable consequences such as high latency and increased likelihood of data loss through packet drops. Encoding inputs using event-based sampling is a potential solution for decreasing network traffic generated when continuous input variables are sampled. The problem addressed by this article is the fact that currently there is no effective method for comparing different encoders. The resulting contribution is the use of mutual information to compare the input and encoded output in terms of accuracy for the currently most efficient encoders that use either memory based event triggering (MBET) or deadband error modulation (DEM). This allows a practitioner to select a suitable encoder for a given input specification.

Multi-regional input–output (MRIO) data are a powerful tool to analyze complex interdependencies in the international trade and supply network. Their field of application is however limited by the ...

As many other developing countries, the statistical office of Turkey displays an input-output table at the national level only and it is not regularly updated. Yet, the need for regional-level information is growing because numerous publicly-funded development projects and private investments have taken place at the sub-national level over the recent years. In this paper we create an input-output table for one region, TR33, for the year 2014 by regionalizing and updating the national table through a location quotient approach. It allows us to calculate the regional employment and output multipliers across 35 sectors and to verify if their ranking varies across location quotient techniques. We expect our conclusions will help policy-makers and private investors take an informed decision when investing in TR33.

This paper will focus on optimizing parameters of sliding mode controllers (SMC) for hybrid stepper motor models simulated in Matlab/Simulink. The main objective is to achieve a smooth transient and robust, steady-state to track reference rotor position when the stepper motor is subjected to load disturbances. Two different structures of SMC controllers will be studied, which are based on the flat system concept that is applicable to the stepper motor model. The hassle to determine controller parameters will be optimized using the Simulink Response Optimizer application. The performance of the controllers will be evaluated by considering load torque and variation in the model parameters. Although the results showed that an open-loop controller could move the rotor to the desired position, however, the transient response had undesired oscillations before the output settled at the steady state. The response was improved by optimizing SMC controllers’ parameters to meet the desire step response requirement. Despite both SMC methods have successfully tracked the reference, there are some challenges to deal with each method in regard to the state measurements, the number of optimized controllers’ parameters, and the scattering of control inputs.

In this paper, we develop a metric of reshoring at the macroeconomic level, at the level of industries or countries. Our dynamic measure computes the change in the domestic–foreign input ratio and therewith captures the idea of moving production back to the home country. Additional conditions ensure that the measure is confined to actual reshoring and does not pick up, for example, mere changes in the scale and composition of production. We show that reshoring is only weakly approximated by reduced offshoring. We compute the reshoring intensity from the World Input Output Database and illustrate the use of the data with several applications. Specifically, we compute trends in reshoring for examples of countries and industry sectors, we investigate reshoring from China, and examine the impact of an increasing degree of automation for reshoring in emerging and developing economies.

The main problems of constructing multiregional input-output (IO) models used for the development of spatial and sectoral long-term national economy forecasts are caused by the absence of proper statistics. Therefore, it is necessary to make up the input-output tables (IOTs) based on a limited set of direct and indirect indicators that measure spatial patterns of production, consumption, capital formation, etc., sufficiently accurate for filling up multiregional IO models. The paper discusses Russian IOT spatial mapping problems and proposes an approach to partial automation of the procedures necessary for regional IOT construction (by federal districts). The regionalization was carried out using a static IO model with the bounding sum control. As a result, a set of consistent regional tables for 2015 was developed, with the eight IOT sum equalling Russia’s IOT. Based on the estimated regional IOTs, a static multiregional input-output model (OMIOM) across federal districts for 2015 was made up. The model allows us to proceed to the follow-up phase, i. e., developing a semi-dynamic model for long-term national economic projection computations

In banking system the evaluation of productivity and performance is the key factor among the fundamental concepts in management. For identify the potential performance of a bank efficiency is the parameter to evaluate effective banking system. To measure the efficiency of a bank selection of appropriate input-output variables is one of the most vital issues. The suitable identification of input-output variables helps to create and identify model in order to evaluate the efficiency and analysis. The Data Envelopment Analysis (DEA) is a mathematical approach used to measure the efficiency of identified Decision Making Units (DMUs). The DEA is a methodology for evaluating the relative efficiency of peer decision making units of identified input/output variables for the financial year 2018-19. In this study the basic DEA CCR, BCC models used for measure the efficiency of DMUs. In addition to these models for minimize the input excess and output shortfall Slack Based Measure (SBM) efficiency used. The SBM is a scalar measure which directly deals with slacks of input, output variables which help in obtain improved efficiency score compare with previous model. The result from the analysis is

Multiplier effects play a major role in determining importance of a sector of interest to the national economy. In order to determine the significance of Croatian transport sectors, in this paper input-output analysis was applied. A comparative analysis of type I and type II output, gross value added and employment multipliers based on input-output tables for Croatian economy for the year 2010 and 2015 was performed. Type I multipliers were calculated based on the open IO model. Closed IO model was used in type II multipliers determination. Results indicate that sector code H49—Land transport services and transport services via pipelines and sector code H50— water transport services in the year 2015 recorded lower type I and type II output, gross value added and employment multipliers compared to the year 2010. For sector code H51—Air transport services, significant growth in terms of all three economic indicators was detected, especially when interest is focused on type I and type II employment multipliers. Results presented in this paper could be valuable for academia and general public because they reflect multipliers estimation of transport sectors in Republic of Croatia for the first time based on sound macroeconomic analysis tool.

The purpose of the study was to determine the problem of control of a dynamic system of higher dimension. Relying on Leontev input-output balance, we formalized the dynamic system and synthesized its control. Within the research, we developed a mathematical model that combines different working objects that consume and release various resources. The value of the penalty for all nodes and objects is introduced into the matrix representation of the problem, taking into account various options for their interaction, i.e., the observation problem. A matrix representation of the planning task at each working object is formed. For the formed system, a control loop is created; the influencing parameters of the external environment are indicated. We calculated the system operational mode, taking into account the interaction of the nodes of objects with each other when the parameters of the external environment influence them. Findings of research show that in achieving a complex result, the system is inefficient without optimal planning and accounting for the matrix of penalties for the interaction of nodes and objects of the dynamic system with each other. In a specific example, for a dynamic system with a dimension of 4.8 million parameters, we estimated the control taking into account the penalty matrix, which made it possible to increase the inflow of additional resources from the outside by 2.4 times from 130 billion conv. units up to 310 conv. units in 5 years. Taking into account the maximum optimization of control in the nodes, an increase of 3.66 times in the inflow of additional resources was ensured --- from 200.46 to 726.62 billion rubles

The plastic industry is an economic sector that plays an important role in promoting a circular economy in Vietnam. This study used the updated 2018 input-output (IO) table to identify and analyse the production and consumption of seven different plastics including: HDPE, PS, PE, PET, PVC, PP, and others. The study also integrated the IO model to unveil the environmental burden of these plastics through the plastic demand of 40 economic sectors and households. As a result, in 2018, the amount of direct solid waste from the plastic industry was 58,147 tons and the amount of indirect solid waste from the plastic industry to other economic sectors and the household sector were 214,258 tons and 6,262 tons, respectively. Agriculture and its services, food processing, fashion manufacturing, basic chemical production, electrical and electronic equipment production, and transport production embodied the highest indirect burdens due to their use of plastic products. This study contributes to MFA research and developing strategies for sustainable production and consumption of plastics and the management of plastic waste in Vietnam.

The main problems of constructing models used to develop of spatial and sectoral long-term economic forecasts are due to the lack of direct statistical data in full, i.e. regional tables of distribution of goods and services. Their calculation has to be carried out on the basis of a limited set of direct and indirect indicators that make it possible to determine the spatial structures of production, consumption, accumulation of fixed capital, etc. with an accuracy sufficient for further use in the information content of interregional intersectoral models. The report examines the problems of spatial allocation of the all-Russian table “input-output” and proposes the author's approach to the partial automation of the procedures necessary to construct a set of regional tables (by federal district). Regionalization was carried out using a static interregional intersectoral model with control of bordering outcomes. The result is a set of consistent regional tables as of 2015 - the sum of eight input-output tables exactly matches the all-Russian table. The constructed static multiregional input-output model (OMIOM) across federal districts is necessary for the next stage of work - the development of a semi-dynamic model used to calculate options for long-term national economic forecasts.

Recent input–output (IO) literature offers original proposals on using linear programming (LP) to make ‘tolerable limits’ approach suitable for measuring the importance of IO coefficients to an eco...

In black-box testing, test sequences may be constructed from systems modelled as deterministic finite-state machines (DFSMs) or, more generally, observable non-deterministic finite state machines (ONFSMs). Test sequences usually contain state identification sequences, with unique input output sequences ( UIOs ) often being used with DFSMs. This paper extends the notion of UIOs to ONFSMs. One challenge is that, as a result of non-determinism, the application of an input sequence can lead to exponentially many expected output sequences. To address this scalability problem, we introduce ${\mathcal K}$ K - UIOs : UIOs that lead to at most ${\mathcal K}$ K output sequences from states of $M$ M . We show that checking ${\mathcal K}$ K - UIO existence is PSPACE-Complete if the problem is suitably bounded; otherwise it is in EXPSPACE and PSPACE-Hard. We provide a massively parallel algorithm for constructing ${\mathcal K}$ K - UIOs and the results of experiments on randomly generated and real FSM specifications. The proposed algorithm was able to construct UIOs in cases where the existing UIO generation algorithm could not and was able to construct UIOs from FSMs with 38K states and 400K transitions.

The methodology for calculating the inter-industry map of uncertainty of the Ukrainian economy and the results of the calculations are considered. A historical assessment of a fragment of fiscal risks associated with tax revenue from taxes on products and other production taxes is carried out. The sectors of Ukraine’s economy are classified through the prism of the uncertainty map. It is proposed to use the production portfolio of economic activities as a tool to mitigate fiscal risks.

Groundwater quality assessment is characterized by pollution injection rates, pollution injection locations and duration of pollution injection for identifying spatial and temporal variation. In this study, spatial variations are obtained by placing observation wells in the downstream zone. Temporal variations in contaminant concentration has been simulated during the study period. Generally, simulations are carried out using various numerical models, which are subject to the availability of all required input parameters and are necessary for the proper management of contaminated aquifers. In previous publications, artificial neural networks (ANNs) are prescribed in such situations as these modeling methods focus on available input/output datasets, thus resolving the concern of obtaining all inputs that a numerical simulator usually demands. Past studies have predicted groundwater breakthrough contaminants. But the effects of input/output variations need to be discussed. This study aims to quantify the effects of a few input/output datasets in the performance of ANN models to simulate pollutant transport in groundwater systems. The combinations of input/output scenarios have rendered these ANN models sensitive to variations, thus affecting model efficiency. These outcomes can reliably be employed for contaminant estimation and provide a paradigm in data collection that will help hydrogeologists to develop more efficient prediction models. HIGHLIGHTS A brief review on groundwater modeling using artificial neural networks.; Effects of input and output parameters in ANN modeling.; ANN modeling strengths and weakness in varying input/output parameters.; The practical implication of this methodology.

Mathematical modeling is the tool to reveal and fully understand the input output relationship in most of the dynamic systems including fuel cells. The dynamic behavior of fuel cell system is deter...

The relationship between prices and labour values has been the source of fruitful controversy since the earliest Classical Political Economists. The alleged refutation of the labour theory of value was an integral part of the marginalist attack against Classical and Marxist analysis. However, statistical analysis of price-value relationships made possible by the data available since the later 20th century suggest considerable empirical strength of the labour theory of value. We trace the intellectual history of the price-value relationship and its inseparable link to capitalist competition through Smith, Ricardo, Marx and Sraffa. Following Shaikh and Ochoa, we present an empirical model of testing their hypotheses that (1) labour values regulate prices of production and (2) serve as gravitational centres for market prices. The analysis of a large dataset of 42 countries and 15 years reveal only small and stable deviations and thus lend support to the Classical Political Economic analysis. With a sample of over 36,000 price vectors, we provide the most comprehensive empirical application of its class and generalize the results that have been established in the relevant literature.

How to identify the key nodes effectively in urban traffic networks to achieve the equitable resource allocation face to the complex traffic network? This issue needs to be solved in current traffic management. This study considered the urban traffic network topology and network traffic status, put forward an improved model based on the economics of the input-output method by introducing a virtual node to the selected network set up with the flow of urban traffic network, sensor nodes by Leontief inverse matrix calculation coefficient to determine node importance, according to the node importance to deliberate attack traffic network to analyze its robustness, to test the accuracy and practicability of the method. The results show that this improved method adopted to measure the importance of traffic nodes from the global scope has the advantages of fast calculation and simple process and provides a more reliable basis for rational allocation of transport resources.

The main application of input—output models is the analysis and forecasting of impact that changes in the final consumption volume and composition have on the production structure. The paper presents results of type I and II multipliers calculation for national and regional (evidence from Moscow) economies based on the input—output tables for 2016 for aggregated economic activities. The attention is devoted first of all to structural aspects of multiplicative effects and to the analysis of the variability of regional multipliers calculation results depending on the approaches. To derive regional multipliers we apply location quotient-based approaches. We show that national type II (including induced effects) and regional multipliers estimations may be highly sensitive to the estimation technique choice. Results from such calculations should be interpreted with consideration to differences of the used techniques and their tendencies to under- or overestimate effects of the final consumption structural changes.

A novel mathematical approach has been proposed for input–output range extension of Pseudo-Taylor-Exponential-Approximation (PTEA) for achieving over seven-decade exponential function, while reducing the linearity error by 1 dB and attaining simple coefficients such as to realize this technique in designing the MOSFET based circuit. This new MPTEA technique, has been successfully utilized for its current-mode (I-I) CMOS implementation involving translinear principle of MOSFETs in weak inversion (WI) region. The CMOS synthesis procedure has been detailed and relevant second-order effects consists of noise, bulk-effect etc. have been explored. For post-layout simulations of the synthesized CMOS implementation, the SPECTRE simulation tool from Cadence, with 180 nM CMOS parameters, has been utilized to justify its practical workability. The proposition, in its CMOS layout, occupies an area of 0.0126mm2 only. It consumes only ≈4.92 μW static power by utilizing ± 0.65 V power supply and produces 146.5 dB range of linear-in-dB output with ± 1 dB linearity error.

Natural disasters cause damage to regional economies. This study investigated how production activities in 35 municipalities of Shizuoka Prefecture recover when such activities stop due to a nuclear power plant disaster and tsunami that may be caused by a Nankai Megathrust Earthquake (NME). We developed a dynamic inter-regional input–output model (IRIO) featuring a production bottleneck due to a shortage of inputs and other goods. Using a simulation model, the economic damage caused by single and combined disasters was evaluated based on several recovery scenarios. The effect of depopulation in Japan on post-disaster recovery processes was also examined. This analysis provides useful disaster preparedness information for local governments and companies.

In this paper, artificial neural network is used to calibrate sensors that are commonly used in industry. Usually, such sensors have nonlinear input output characteristic that makes their calibration process rather inaccurate and unsatisfied. Artificial neural network is utilized in an inverse model learning mode to precisely calibrate such sensors. The scaled conjugate gradient (SCG) algorithm is used in the learning process. Three types of industrial sensors which are gas concentration sensor, force sensors and humidity sensors are considered in this work. It is found that the proposed calibration technique gives fast, robust and satisfactory results.

The construction sector has a special interest in the case of the Spanish economy, given its large economic dimension and environmental impact, particularly during the real estate boom prior to the last economic crisis that started in 2008. We study the CO2 emissions of construction activities in 2007, at the height of the construction boom, in the context of the productive structure of Spain. For this, we use an input–output subsystem method, which allows us to study the productive structure of the subsystem’s activities, taking into account its links with the rest of the sectors. The decomposition of total emissions in four explanatory components allows us to make a classification of the different sectors according to the type of relationships that are established between the subsystem and the rest of the economy. We derive some implications for environmental policy from the analysis of these interrelations.

This paper is concerned with the problem of input-output finite-time stability (IO-FTS) for a class of switched singular continuous-time systems. First, the concept of IO-FTS is extended to switched singular systems. Then, by using the average dwell time switching approach and constructing multiple Lyapunov functions, a sufficient condition of IO-FTS for the considered system is presented in the form of linear matrix inequalities (LMIs). Furthermore, based on the derived conditions, a suitable state feedback controller is designed to stabilize the switched singular systems. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed technique.