Double Threshold Research Articles

Analysis of a multi-component system with double threshold control policy

This paper investigates a multi-component repairable system with double threshold control policy. The system is composed of n identical and independent components which operate simultaneously at the beginning, and it is down when the number of operating components decreases to . When the number of failed components is less than the value L, the repairman repairs them with a low repair rate. The high repair rate is activated as soon as L failed components present, and continues until the number of failed components drops to the value N−1. Applying the matrix analytical method, the Laplace transform technique and the properties of the phase type distribution, various performance measures including the availability, the rate of occurrence of failures, and the reliability are derived in transient and stationary regimes. Further, numerical examples are reported to show the behaviour of the system.

Adaptive lane line detection and warning algorithm based on dynamic constraint

The lane line detection algorithm is highly sensitive to the environment. And the selection of parameters is greatly affected by human subjective factors. Therefore, the concept of adaptive and dynamic constraint is introduced into the lane line detection algorithm. The evaluation function is set based on the detected information. A high precision lane line detection algorithm with supervision and warning mechanism is proposed. Firstly, the Canny operator gradient calculation method is improved by using eight neighborhood models. And by setting multi-level threshold instead of double threshold detection method, the algorithm’s adaptability is improved. Secondly, the concept of dynamic region of interest is proposed. The detection region of Canny operator is constrained, the environment interference to the algorithm is reduced. Finally, lane line information is included in the supervision and correction warning mechanism. And the early warning is given to drivers. The experimental results show that the algorithm is of high accuracy, real-time and adaptability.

Savitzky-Golay Filtering and Improved Energy Entropy for Speech Endpoint Detection under Low SNR

Under the condition of low signal-to-noise ratio (SNR) or non-stationary noise, the performance of endpoint detection is poor. Therefore, this paper proposes a speech endpoint detection algorithm for low SNR. In this paper, Savitzky-Golay filtering, improved sub-band energy entropy and constant Q-transform (CQT) are used to extract features, and single parameter double threshold method is used to realize endpoint detection. In this paper, clean speech and noise-92 speech fragments are used to evaluate the algorithm. Experimental results show that the algorithm in this paper can distinguish speech endpoints well. For Gaussian white noise, Factory noise and Volvo noise, the detection accuracy of the improved algorithm is improved by 5.5%, 5.3% and 4.6% respectively. Therefore, the algorithm in this paper can separate the mute and voice in complex environment.

Waveguide with double threshold resonance at a simple threshold

A threshold resonance generated by an almost standing wave occurring at a threshold — a solution of the problem that do not decay at infinity, but rather stabilizes there — brings about various anomalies in the diffraction pattern at near-threshold frequencies. Examples when a simple threshold resonance occurs or does not occur are trivial. For the first time an acoustic waveguide (the Neumann spectral problem for the Laplace operator) of a special shape is constructed in which there is a maximum possible number (namely two) of linearly independent almost standing waves at a threshold (equal to a simple eigenvalue of the model problem on the cross-section of the cylindrical outlets to infinity). Effects in the scattering problem for acoustic waves, which are caused by these standing waves are discussed. Bibliography: 54 titles.

Managerial equity incentives and R&D investments in emerging economies: study based on threshold effects

ABSTRACT Do managerial equity incentives benefit or impede R&D investments? To address this question and the inconsistent empirical findings on the topic, this study investigates the relationship between equity incentives and R&D investments as well as the threshold effects of some contextual factors. Our study evidence a curvilinear inverted U-shaped relationship between equity incentives and R&D investments by using GMM system estimators for a sample of 158 Chinese firms for the 2006–2018 period. Our findings also indicated that the influence of equity incentives on R&D investments is constrained by contextual factors such as financial slack and equity concentration, suggesting that financial slack plays a double threshold effect on the above relationship, while equity concentration performed a significant single threshold effect.

Волновод с двойным пороговым резонансом на простом пороге

Пороговый резонанс, вызванный появлением на пороге непрерывного спектра почти стоячей волны - решения задачи, не затухающего, но стабилизирующегося на бесконечности, - провоцирует разнообразные аномалии дифракционной картины на околопороговых частотах. Примеры однократного порогового резонанса или его отсутствия очевидны. В статье впервые построен акустический (спектральная задача Неймана для оператора Лапласа) волновод специфической формы, у которого на пороге (простое собственное число модельной задачи на сечении цилиндрических выходов на бесконечность) имеется максимально возможное количество (две) линейно независимых почти стоячих волн. Обсуждаются проистекающие от этих волн эффекты в задаче рассеяния акустических волн. Библиография: 54 названия.

Energy and resource efficient workflow scheduling in a virtualized cloud environment

High energy consumption (EC) is one of the leading and interesting issue in the cloud environment. The optimization of EC is generally related to scheduling problem. Optimum scheduling strategy is used to select the resources or tasks in such a way that system performance is not violated while minimizing EC and maximizing resource utilization (RU). This paper presents a task scheduling model for scheduling the tasks on virtual machines (VMs). The objective of the proposed model is to minimize EC, maximize RU, and minimize workflow makespan while preserving the task’s deadline and dependency constraints. An energy and resource efficient workflow scheduling algorithm (ERES) is proposed to schedule the workflow tasks to the VMs and dynamically deploy/un-deploy the VMs based on the workflow task’s requirements. An energy model is presented to compute the EC of the servers. Double threshold policy is used to perceive the server’ status i.e. overloaded/underloaded or normal. To balance the workload on the overloaded/underloaded servers, live VM migration strategy is used. To check the effectiveness of the proposed algorithm, exhaustive simulation experiments are conducted. The proposed algorithm is compared with power efficient scheduling and VM consolidation (PESVMC) algorithm on the accounts of RU, energy efficiency and task makespan. Further, the results are also verified in the real cloud environment. The results demonstrate the effectiveness of the proposed ERES algorithm.

Investigating Untapped Capacity at Single-Runway Airports using Short Final Curved Approach, Dual Glide Slope, and Double Threshold

In Europe more than one third of the 100 busiest airports have only one runway and most of them have no possibility to build another one. Aircraft of all types and sizes must use that same runway which affects operational complexity. In such situations the problem of capacity appears since separation between aircraft is based on all of them following the same path and smaller aircraft following larger ones have to wait for the wake vortex to dissipate, in the case of both arrivals and departures. This paper offers a possible concept for increasing single-runway airport landing capacity. It is based on separating smaller aircraft to a final approach path that is not affected by the wake vortices produced by the larger aircraft. Published references dealing with this topic are included and discussed. The operation rules proposed are based on existing standards and some best practices. This paper does not discuss available technological solutions.

SEMG-Based Human-in-the-Loop Control of Elbow Assistive Robots for Physical Tasks and Muscle Strength Training

In this letter we present a sEMG-driven human-in-the-loop (HITL) control designed to allow an assistive robot produce proper support forces for both muscular effort compensations, i.e. for assistance in physical tasks, and muscular effort generations, i.e. for the application in muscle strength training exercises related to the elbow joint. By employing our control strategy based on a Double Threshold Strategy (DTS) with a standard PID regulator, we report that our approach can be successfully used to achieve a target, quantifiable muscle activity assistance. In this relation, an experimental concept validation was carried out involving four healthy subjects in physical and muscle strength training tasks, reporting with single-subject and global results that the proposed sEMG-driven control strategy was able to successfully limit the elbow muscular activity to an arbitrary level for effort compensation objectives, and to impose a lower bound to the sEMG signals during effort generation goals. Also, a subjective qualitative evaluation of the robotic assistance was carried out by means of a questionnaire. The obtained results open future possibilities for a simplified usage of the sEMG measurements to obtain a target, quantitatively defined, robot assistance for human joints and muscles.

Resource Misallocation Threshold for High-Tech Industrial Specialization on Technological Innovation Performance for Pharmaceutical Manufacturing

This paper examines the threshold effect of resource misallocation between specialization and technological innovation performance in the high-tech industry in China. Contrary to the existing literature, this paper applies the static panel threshold model to evaluate the threshold effect of industrial specialization on the innovation performance, including the single threshold effect and double threshold effect. The empirical results shed new light on the topic and signified that high-tech industry specialization has a nonlinear effect on innovation performance and the resource misallocation threshold. This paper unveils a novel, double threshold effect of resource misallocation between industrial specialization and innovation performance. Moreover, the twenty-eight regions in China are divided into three types according to a resource misallocation, which unfold the current situation of the resource misallocation in pharmaceutical manufacturing—providing directional guidance for structural reforms of the supply side of pharmaceutical manufacturing in various regions.

Double threshold construction method for attribute‐induced three‐way concept lattice in incomplete fuzzy formal context

Concept lattice theory is the basis of formal concept analysis. It is an effective tool for knowledge representation and discovery. Three-way decision theory is a new decision theory based on rough sets and decision rough sets. In this study, a method is proposed for constructing attribute-induced three-way concept lattices in an incomplete fuzzy formal context. First, the authors introduce the related knowledge of the classical formal context, the fuzzy formal context and incomplete fuzzy formal context in detail. They put forward a method to fill the incomplete formal context. Secondly, they propose a double threshold operation, which divides the relationship between objects and attributes into three parts: belonging, not belonging and undetermined. Thirdly, they propose three methods to complement incomplete formal context and introduce their advantages and disadvantages. Fourthly, they deal with incomplete formal context by special symbol completion method and get related algorithms of attribute-induced three-way concept lattice. Finally, a case is given to verify the effectiveness of the algorithm for constructing attribute-induced three-way concept lattices.

Contrast Enhancement Using Optimum Threshold Selection

In the recent era, a boom was observed in the field of information retrieval from images. Digital images with high contrast are sources of abundant information. The gathered information is useful in the precise detection of an object, event, or anomaly captured in an image scene. Existing systems do uniform distribution of intensities and apply intensity histogram equalization. These improve the characteristics of an image in terms of visual appearance. The problem of over enhancement and the increase in noise level produces undesirable visual artefacts. The use of Otsu's single threshold method in existing systems is inefficient for segmenting an image with multiple objects and complex background. Additionally, these are incapable to improve the yield of the maximum entropy and brightness preservation. The aforementioned limitations motivate us to propose an efficient statistical pipelined approach, the Range Limited Double Threshold Weighted Histogram Equalization (RLDTWHE). This approach is an integration of Otsu's double threshold, dynamic range stretching, weighted distribution, adaptive gamma correction, and homomorphic filtering. It provides optimum contrast enhancement by selecting the best appropriate threshold value for image segmentation. The proposed approach is efficient in the enhancement of low contrast medical MRI images and digital natural scene images. It effectively preserves all essential information recorded in an image. Experimental results prove its efficacy in terms of maximum entropy preservation, brightness preservation, contrast enhancement, and retaining the natural appearance of an image.

The Double Threshold: Consequences for Identifying Low-Dose Radiation Effects.

Prior to observing low-dose-induced cell signaling and adaptive protection, radiogenic stochastic effects were assumed to be linearly related to absorbed dose. Now, abundant data prove the occurrence of radiogenic adaptive protection specifically at doses below ∼ 200 mGy (with some data suggesting such protection at a dose even higher than 200 mGy). Moreover, cells do not thrive properly when deprived of radiation below background dose.Two threshold doses need be considered in constructing a valid dose-response relationship. With doses beginning to rise from zero, cells increasingly escape radiation deprivation. The dose at which radiation-deprived cells begin to function homeostatically provides dose Threshold A. With further dose increase, adaptive protection becomes prominent and then largely disappears at acute doses above ∼ 200 mGy. The dose at which damage begins to override protection defines Threshold B.Thresholds A and B should be terms in modeling dose-response functions. Regarding whole-body responses, current data suggest for low-LET acute, non-chronic, irradiation a Threshold B of about 100 mGy prevails, except for leukemia and probably some other malignancies, and for chronic, low dose-rate irradiation where the Threshold B may well reach 1 Gy per year. A new Research and Development Program should determine individual Thresholds A and B for various radiogenic cell responses depending on radiation quality and target.

A sEMG-Driven Soft ExoSuit Based on Twisted String Actuators for Elbow Assistive Applications

The scope of this letter is to show the applicability of the Twisted String Actuators (TSAs) for lightweight, wearable and assistive robotic applications. To this aim, we have developed a novel surface electromyography (sEMG)-driven soft ExoSuit using the TSAs to perform both single and dual-arm elbow assistive applications. The proposed ExoSuit, with an overall weight of 1650 g, uses a pair of TSAs mounted in the back of the user, connected via tendons to the user's forearms to actuate each arm independently for supporting external loads. We confirm this new light-weight and customizable wearable solution via multiple user studies based on the biceps and tricep' sEMG measurements. We demonstrate that user's muscles can automatically activate and regulate the TSAs and compensate for the user's effort: by using our controller based on a Double Threshold Strategy (DTS) with a standard PID regulator, we report that the system was able to limit the biceps' sEMG activity under an arbitrary target threshold, compensating a muscular activity equal to 220% (related to a single arm 3 kg load) and 110% (related to a dual arm 4 kg load) of the threshold value itself. Moreover, the triceps' sEMG signal detects the external load and, depending on the threshold, returns the system to the initial state where it requires no assistance from the ExoSuit. The experimental results show the proposed ExoSuit's capabilities in both single and dual-arm load compensation tasks. Therefore, the applicability of the TSAs is experimentally demonstrated for a real-case assistive device, fostering future studies and developments of this kind of actuation strategy for wearable robotic systems.

Study on the Influence of Household Consumption on Energy Consumption under the Threshold of Rising House Price

In order to understand the impact of residents’ consumption on energy consumption in a more comprehensive way, this paper divides the residents’ consumption into two dimensions: total consumption and consumption structure, and introduces the house price as the threshold variable, using the provincial data of 2007-2017, constructs the panel threshold model of residents’ consumption on energy consumption. The results show that: the total consumption and consumption structure of residents have a double threshold effect on energy consumption; the promotion of total consumption promotes energy consumption, while the upgrading of consumption structure restrains energy consumption; when the rise of house price is in the middle level, due to the “wealth effect” caused by the rise of house price, the rise of total consumption and consumption structure The upgrading of the structure has the strongest effect on energy consumption, but when the house price further rises beyond the maximum threshold, the “crowding effect” brought by the rising house price will significantly weaken the impact of total consumption and consumption upgrading on energy consumption.

Research on tobacco foreign body detection device based on machine vision

Foreign body detection is an important aspect that affects the quality of tobacco production. This paper describes a direct foreign body detection scheme using machine vision, which uses three cameras arranged around a tobacco bale to record its multiple surfaces and directly identify foreign bodies. In this study, color sorting table method (CSTM) was first used to identify and remove color-sensitive foreign bodies; thereafter, gray threshold method and double threshold method were used to further identify and remove foreign bodies with similar colors. The experimental results indicate that the multi-step hybrid identification method proposed herein can effectively identify and remove various foreign bodies in the production process of tobacco packs, with an accuracy rate of 97.8%, which meets the industrial requirements for foreign body detection. Compared with various existing devices and methods, it has the advantages of high detection efficiency and low cost.

Observed changes in heat waves with different severities in China during 1961\u20132015

Heat waves (HWs) exert severe impacts on ecosystem, social economy, and human lives. Thus, changes in HWs under a warming climate have triggered extensive interests. In this study, the authors developed a new method to identify the HW events in China by double thresholds and further classified them into four categories (i.e., mild, moderate, severe, and extreme HWs) according to their magnitudes by using the daily maximum temperature data from 701 observation stations. On this basis, the spatiotemporal features of HWs with different severities in China from 1961 to 2015 were investigated. The results show that the high HW frequency mainly appears in Jianghuai, South China and western Northwest China. Moreover, the high frequencies of moderate, severe, and extreme HWs occur from June to August and reach the peak in July, while the mild HW frequency is compared from May to September. Since the 1960s, the frequencies of the mild, moderate, severe, and extreme HWs in China have increased significantly with rates of 7.5, 4.3, 1.4, and 1.8 events per year, respectively. The increases are the greatest in July for the moderate, severe, and extreme HWs while comparable during May to September for the mild HW. Besides, an interdecadal change is found to occur in the late 1990s. Compared with the former period (1961–1996), the occurrence of the extreme HWs during the latter period (1997–2015) has increased most significantly in eastern Northwest China and North China, while the frequency of the mild HWs increases most significantly in Jianghuai and South China.

In situ capture of spatter signature of SLM process using maximum entropy double threshold image processing method based on genetic algorithm

Although selective laser melting (SLM) has the advancements of fabricating complex geometric, multi-material and multi-functional structures, several defects still affect the process stability, in particular spatter. The formation of spatter in SLM depends on the process parameters, and these can potentially be used to tune the process to obtain better product quality. However, there is still a lack of efficient methods for processing spatter images to allow in situ detection of the onset of spatter. In this paper, an in situ monitoring method for acquiring spatter images in SLM was presented. A maximum-entropy double-threshold image processing algorithm based on genetic algorithm (MEDTIA-GA) was proposed to recognize spatter from images, and its results were compared with three conventional threshold segmentation methods: Otsu’s method, Triangle threshold segmentation algorithm, and K-means clustering algorithm. Results show that MEDTIA-GA method was able to eliminate three types of errors: noise sensitivity, spatter conglutination, and spatter omission. In addition, the average processing time of 37 ms for MEDTIA-GA method was far shorter than those for other three conventional threshold segmentation methods. Finally, the relationship between the spatter area as well as the number and the laser energy density were analyzed

Research on Spectrum Sensing in 230MHz Power Wireless Private Network

With the proposal of ubiquitous electric power internet of things, the power industry’s demand for communication network is more and more intense, and the development of power wireless private network also puts forward higher requirements and more stringent standards for the wireless communication technology involved in it. Therefore, a spectrum sensing technology for 230MHz power wireless private network is proposed in this paper. By taking advantage of the relationship between the two threshold values and the signal-to-noise ratio, adjustment factors are set to achieve different two threshold values corresponding to different signal-to-noise ratios on the premise of avoiding frequent adjustment of threshold values. On the one hand, when the channel condition is good, the distance between the double threshold is reduced also reduce the system computation. On the other hand, when the channel condition is poor, the distance between the double threshold is increased to increase the extraction opportunity of the trust function, so as to improve the detection probability of the system. Finally, experimental results show that the proposed algorithm can effectively improve the communication performance of 230MHz power wireless private network.

Model for Malicious Node Recognition Based on Environmental Parameter Optimization and Time Reputation Sequence

Wireless sensor network (WSN) works in a complex environment. To interdict the malicious nodes which attacks the safety of network, such as interrupt attacks and selective forwarding attacks, based on TS-BRS reputation model, a model for malicious node identification based on MNRT-OEP&RS algorithm is constructed. Using the linear regression of machine learning and combining the energy of nodes, data volume, number of adjacent nodes, the node sparsity and other deterministic parameters can solve environmental parameters. Then the similarity of between the benchmark reputation sequence and cycle reputation sequence sets the dynamic reputation double threshold are calculated in order to identify the malicious nodes by dynamically considering the information forwarding behavior. The simulated results show that the improved algorithm can guarantee the security of wireless sensor networks in complex environments effectively with above 90% recognition of malicious nodes and below 8% false positive rate.