Correction Mechanism Research Articles

The organization for roadmap sales & marketing

Roadmap sales & marketing is a medium- to long-term solution sales & marketing conducted by teams. Compared to one off sales & marketing, the sales scale will be dozens of times. As a result, Company X changed its sales & marketing strategy from improving the efficiency of one-time sales to roadmap sales & marketing; however, the sales organization could not immediately adapt. Nevertheless, Company X adapted its sales organization through trial and error, and, as a result, achieved a dramatic increase in sales. This paper analyzes these efforts and presents them as three standardizations and one course correction mechanism. At first glance, this seems to be a case of organizational sales & marketing being superior to individual sales & marketing. However, the main aim was to switch to a superior strategy, and the organization succeeded in adapting to it later.

Design and Parameter Optimization of Trajectory Correction Control Strategy for Air Duct Structure Projectile

In order to make the new air duct structure trajectory correction projectile have good dynamic correction control effect, the control strategy of the projectile’s correction mechanism is studied in this paper. A design method of trajectory correction control strategy based on particle swarm optimization-cuckoo search (PSO-CS) hybrid algorithm is proposed to obtain the optimal control parameters that can make the projectile flight stable and correct accurately. Firstly, the mathematical model of the air duct structure projectile is established. Secondly, the multiobjective optimization problem is analyzed. The projectile’s correction control strategy optimization model is established by taking the start control time, the number of corrections, the correction working time, and the interval time as the control variables. The optimization model innovatively considers the influence of the correction action on the flight stability of the projectile and the influence of the start control time on the correction range. Finally, the PSO-CS hybrid algorithm is used to design the calculation method of the optimization model and solve the optimal correction working parameters. The simulation results indicate that the control strategy optimization model can be solved by the proposed calculation method. Moreover, optimal correction working parameters of the correction mechanism in the current state can be obtained. Compared with the results of using single PSO algorithm and CS algorithm, the correction scheme calculated by PSO-CS hybrid optimization algorithm is better. This correction control scheme can effectively reduce the impact point deviation and make the projectile flight stable. At the same time, the circular error probable (CEP) of the projectile after correction is reduced from 42.3 m to 4.6 m while the impact point dispersion is lowered. The research results show that the design method of correction control strategy proposed in this paper is effective for trajectory correction of the new air duct structure projectile.

Double-checking chromosome segregation.

Enduring chromosome segregation errors represent potential threats to genomic stability due to eventual chromosome copy number alterations (aneuploidy) and formation of micronuclei-key intermediates of a rapid mutational process known as chromothripsis that is found in cancer and congenital disorders. The spindle assembly checkpoint (SAC) has been viewed as the sole surveillance mechanism that prevents chromosome segregation errors during mitosis and meiosis. However, different types of chromosome segregation errors stemming from incorrect kinetochore-microtubule attachments satisfy the SAC and are more frequent than previously anticipated. Remarkably, recent works have unveiled that most of these errors are corrected during anaphase and only rarely result in aneuploidy or formation of micronuclei. Here, we discuss recent progress in our understanding of the origin and fate of chromosome segregation errors that satisfy the SAC and shed light on the surveillance, correction, and clearance mechanisms that prevent their transmission, to preserve genomic stability.

Generalized Space-Time Architecture for Ambient Backscatter Communication

Multiple-antenna backscatter is emerging as a promising approach to combat the cascaded backscatter channel fading to offer a high data rate for ambient backscatter communication (AmBC). However, related designs in AmBC fail to provide both diversity and multiplexing gains to backscatter tags. To address this issue, in this paper, we present a unified generalized space-time shift keying (GSTSK)-Backscatter architecture for AmBC to strike a flexible tradeoff between the attainable diversity and multiplexing gains in an efficient but low-complexity manner. Moreover, taking the non-identically distributed characteristics of the backscatter channel into account, we first derive asymptotic BER bounds for both the source and backscatter signals, which are verified by simulation results. Furthermore, we propose a residual- and threshold-based joint error correction mechanism (JECM) and design the near-optimal and low-complexity detector for GSTSK-Backscatter systems. Simulation results validate the analysis and show that our proposed JECM-based detector approaches the optimal detector and balances the BER and complexity performance.

A self-adjusting ant colony clustering algorithm for ECG arrhythmia classification based on a correction mechanism

Background and objectiveAs a representative type of cardiovascular disease, persistent arrhythmias can often become life-threatening. In recent years, machine learning-based ECG arrhythmia classification aided methods have been effective in assisting physicians with their diagnosis, but these methods have problems such as complex model structures, poor feature perception ability, and low classification accuracy. MethodsIn this paper, a self-adjusting ant colony clustering algorithm for ECG arrhythmia classification based on a correction mechanism is proposed. This method does not distinguish between subjects when establishing the dataset in order to reduce the effect of differences in ECG signal features between individuals, thus improving the robustness of the model. When the classification is achieved, a correction mechanism is introduced to correct outliers caused by the accumulation of errors in the classification process in order to improve the classification accuracy of the model. According to the principle that the flow rate of gas can be increased under the convergence channel, a dynamically updated pheromone volatilization coefficient ρ, namely the increased flow rate ρ, is introduced to help the model converge more stably and faster. As the ants move, the next transfer target is selected by a truly self-adjusting transfer method, and the transfer probability is dynamically adjusted according to the pheromone concentration and the path distance. ResultsBased on the MIT-BIH arrhythmia dataset, the new algorithm achieved classification of five heart rhythm types, with an overall accuracy of 99.00%. Compared to other experimental models, the classification accuracy of the proposed method represents a 0.2% to 16.6% improvement, and compared to other current studies, the classification accuracy of the proposed method is 0.65% to 7.5% better. ConclusionsThis paper addresses the shortcomings of ECG arrhythmia classification methods based on feature engineering, traditional machine learning and deep learning, and presents a self-adjusting ant colony clustering algorithm for ECG arrhythmia classification based on a correction mechanism. Experiments demonstrate the superiority of the proposed method compared to basic models as well as those with improved partial structures. Furthermore, the proposed method achieves very high classification accuracy with a simple structure and fewer iterations than other current methods.

Determinan Utang Luar Negeri Indonesia Tahun 1981-2020

Indonesia is one of the developing countries that is actively advancing development. However, limited funding for development is the main obstacle for developing countries, including Indonesia, in increasing development. To overcome these cost problems, a large injection of funds is needed, one of which comes from foreign debt. Although foreign debt helps to advance development, its uncontrolled increase will result in default on debt payments until a crisis occurs. Theoretically, foreign debt is influenced by various faktors including foreign investment (FDI), gross domestic product (GDP), exchange rates, imports, exports, and foreign exchange reserves. This study aims to analyze the effect of FDI, GDP, exchange rate, imports, exports, and foreign exchange reserves on Indonesia's foreign debt in the long term and short term. The analytical method used in this study is the Error Correction Mechanism (ECM) for the period 1981-2020. The results of the study indicate that in the long term and short term the variabels of FDI, foreign exchange reserves, and the exchange rate have a significant and positive effect on Indonesia's foreign debt. Meanwhile, the variabels of GDP, imports, and exports have no significant effect on Indonesia's foreign debt in the long and short term.

Door-to-door livestock treatment in Boyolali Regency: Ruminant health evaluation strategy in Household Farms

Ruminant husbandry is a fundamental economic aspect of Boyolali Regency. Animal health management is an important factor to guarantee the husbandry meets optimal production. The community service activity is aimed to contribute in controlling animal diseases at Boyolali. The service is carried out door to door accompanied by discussions with breeders and direct treatment of sick livestock. Interaction with breeders aims to provide practical education on the role of health in achieving efficient livestock production. The treatment provided included worming, vitamins, anti-ectoparasites, and pregnancy checks. The injection treatment was performed by veterinarians on 50 beef cattle, goats and sheep and proved to be effective in its implementation. This activity has been successful and all livestock can be diagnosed and treated according to the correct treatment mechanism.

Dynamics of Industrial Electricity Demand in the State of Bahia (Brazil): Evolution of Price and Income and COVID-19 Implications

The growth in demand for electricity is a determining factor for the regional development. This research aimed to estimate the price and income elasticity parameters of the industrial demand for electricity in the State of Bahia, Brazil, from January 2003 to June 2022, in addition to making forecasts for the period from July to December 2022. After verifying that some of the analyzed data were non-stationary, we chose to use the cointegration method, estimating the econometric model through the Error Correction Mechanism (ECM). The ECM considers the model’s variables and their lags, relating the series’ short and long-run trends. The estimated parameters were inelastic and presented the following values: 0.501 and 0.762 (price and income, long-run) and 0.482 and 0.702 (price and income, short-run). The adjustment coefficient between the short and long-run was also statistically significant and indicated that approximately 8% of the difference between the effective value and the long-run value (balance value) is corrected in each period, demonstrating the rigidity of the consumption structure of electricity in the industrial sector in Bahia. The model also demonstrated an 8.1% reduction in consumption during COVID-19 incidence period. Regarding the forecasts, they proved to be robust and with an average difference of 5.4% in relation to what actually happened in the months of July and August 2022. Thus, the calculated parameters are configured as another source of information for public policymakers and private investors interested in the electricity sector in the State of Bahia.

Reliable and energy-efficient UAV-assisted air-to-ground transmission: Design, modeling and analysis

In this paper, a novel reliable and energy-efficient transmission scheme is proposed for unmanned aerial vehicle (UAV) assisted air-to-ground (A2G) communication. The scheme is tailored to handle burst errors in transmission caused by network collision, switching or interference. Application Layer Forward Error Correction (AL-FEC) mechanism is proposed to enhance the reliability of the A2G communication. By avoiding retransmissions, energy efficiency can be guaranteed. Based on Gilbert-Elliott channel model, we perform a detailed mathematical analysis on the performance of the proposed AL-FEC scheme. The packet delivery ratio and energy efficiency are studied and validated by comprehensive simulations. An application layer Automatic Repeat reQuest (AL-ARQ) protocol based on selective retransmission is used as a baseline scheme and compared with the proposed scheme. It is shown that the proposed AL-FEC scheme can significantly reduce the energy consumption and ensure the same or even higher application packet delivery ratio compared with the baseline scheme. In addition, the proposed scheme is especially preferable when the channel quality is poor. These specific findings can provide guidance for practical applications relying on UAV-assisted A2G communication, which require reliable and energy-efficient UAV-to-ground transmission in harsh wireless conditions.

EFFECT OF MONETARY POLICY ON SELECTED MACROECONOMIC VARIABLES IN NIGERIAN

This study analyzed the effects of monetary policy on selected macroeconomic variables in Nigeria from 1986 to 2019. The relationship between monetary policy and macroeconomic variables in Nigeria has been a contentious issue due to inconsistent implementation and empirical findings. The study specifically evaluated the impact of monetary policy rate, cash reserve ratio, liquidity ratio, and money supply, as independent variables, on inflation and employment rate, the dependent variables. The study design was ex-post facto and utilized the Error Correction Mechanism (ECM) Model for estimation. The analysis revealed a negative and insignificant relationship between the monetary policy instruments and the selected macroeconomic variables. The conclusion was that the Central Bank of Nigeria's monetary policy adjustments have not effectively improved macroeconomic conditions in Nigeria. The study recommended increasing awareness of financial inclusion in rural areas, promoting collaboration between monetary and fiscal policy managers, and directing efforts towards enhancing the development of both the money and capital markets.
 Keywords: Monetary Policy, Macroeconomic Variables, Nigeria.

The information transmission and risk contagion effect between green bond market and government bond market in China

The problem of correlation between the Chinese green bond market and the government bond market may affect the smooth operation of the national economy. In this paper, a total of 3,181 sets of data representing the China’s green bond market and the government bond market for the period 2010–2022 are selected, and the VECM-DCC-VARMA-AGARCH model is used to analyse the spillover effects between the two in terms of information transmission and risk contagion. The results indicate that 1) The dynamic correlation between the China’s green bond market and the government bond market is significant, with obvious information transmission and risk contagion effects. 2) Compared to the government bond market, the green bond market is more sensitive to new information and the intensity of the reflection is stronger. 3) There is a long-term equilibrium relationship between the China’s green bond market and the government bond market, and the government bond market will adjust in the direction of green bonds through an error correction mechanism when deviations occur. 4) There is a significant two-way risk contagion effect between the green bond market and the government bond market, but the intensity of the effect is asymmetric. 5) The dynamic correlation between the green bond market and the government bond market has been deepening. Based on the above findings, we have put forward some rationalisation proposals.

Predictive Coding and Internal Error Correction in Speech Production.

Speech production involves the careful orchestration of sophisticated systems, yet overt speech errors rarely occur under naturalistic conditions. The present functional magnetic resonance imaging study sought neural evidence for internal error detection and correction by leveraging a tongue twister paradigm that induces the potential for speech errors while excluding any overt errors from analysis. Previous work using the same paradigm in the context of silently articulated and imagined speech production tasks has demonstrated forward predictive signals in auditory cortex during speech and presented suggestive evidence of internal error correction in left posterior middle temporal gyrus (pMTG) on the basis that this area tended toward showing a stronger response when potential speech errors are biased toward nonwords compared to words (Okada et al., 2018). The present study built on this prior work by attempting to replicate the forward prediction and lexicality effects in nearly twice as many participants but introduced novel stimuli designed to further tax internal error correction and detection mechanisms by biasing speech errors toward taboo words. The forward prediction effect was replicated. While no evidence was found for a significant difference in brain response as a function of lexical status of the potential speech error, biasing potential errors toward taboo words elicited significantly greater response in left pMTG than biasing errors toward (neutral) words. Other brain areas showed preferential response for taboo words as well but responded below baseline and were less likely to reflect language processing as indicated by a decoding analysis, implicating left pMTG in internal error correction.

Productivity in Indonesian agriculture: Impacts of domestic and international research

AbstractTotal factor productivity growth contributed 38% of Indonesia's agricultural output growth from the mid‐1970s to the mid‐2000s. This study uses time series data analysed with an error correction mechanism to examine the contribution that Indonesian publicly funded agricultural research made to this outcome, allowing for other possible determinants of productivity growth, including international agricultural research, extension, government price policy and weather. The results imply a 27% real annual rate of return from a marginal increase in Indonesian agricultural research expenditure. Indonesia's public agricultural research explains virtually all of its agricultural total factor productivity growth between 1975 and 2006.

ОСОБЕННОСТИ ФИНАНСОВОГО ОБЕСПЕЧЕНИЯ ВНЕДРЕНИЯ НАИЛУЧШИХ ДОСТУПНЫХ ТЕХНОЛОГИЙ КАК ВАЖНОГО КОМПОНЕНТА ЦИРКУЛЯРНОЙ ЭКОНОМИКИ НА ПРОИЗВОДСТВЕННЫХ ПРЕДПРИЯТИЯХ

The article discusses the issues of financing the best available technologies (BAT) at Russian enterprises, the relevance of the introduction of which is increasing every year, especially against the background of the processes of greening the economy, as well as the need for the country to achieve technological sovereignty. The competent selection of sources of financing for the modernization of production processes based on new technologies is one of the most important tasks of the financial strategies of domestic enterprises at this stage, but no less important is the development of a correct financing mechanism, which necessitates its detailing, taking into account the specific features of the process of introducing BAT and identifying sources of financing, depending on whether the financing of BAT is perceived as an additional object of capital investments or is considered as an innovative project, meets the criteria of a "green" investment project. The author substantiates that the formation of a financial support system for BAT is the foundation for optimizing the financial strategy of the enterprise, which in the future will contribute to a faster transition to a closed-cycle economy.

FORC diagram features of Co particles due to reversal by domain nucleation

First Order Reversal Curve (FORC) diagrams are a popular tool in geophysics and materials science for the characterization of magnetic particles of natural and synthetic origin. However, there is still a lot of controversy about the rigorous interpretation of the origin of certain features in a FORC diagram. In this study, we analyze FORCs computed by micromagnetic simulations of Co cubes with dimensions of 50, 100 and 150 nm and uniaxial magnetocrystalline anisotropy. For the larger cubes we observe the formation of a stable two-domain state. The nucleation of a reversed domain and its subsequent annihilation are clearly visible as separate peaks in the FORC diagram. They spread out along the coordinate axis in the FORC diagram, which is associated with the bias field HU of a Preisach hysteron. Based on our findings, we state that a FORC diagram peak spreading along the HU axis can have its origin in the step-wise magnetization reversal driven by nucleation of domains in a single particle. This means that we have identified another mechanism apart from the well-known magnetostatic interaction between a set of particles that leads to features in the FORC diagram extending along the HU-axis. Our study demonstrates that if FORCs shall be used as a quantitative tool to assess the microstructure of samples containing magnetic material, more information from other methods will be required to identify the correct physical mechanism by which a certain “fingerprint” in a FORC diagram is produced.

Adaptive aberration correction using an electrowetting array.

We demonstrate a method that permits wavefront aberration correction using an array of electrowetting prisms. A fixed high fill factor microlens array followed by a lower fill factor adaptive electrowetting prism array is used to correct wavefront aberration. The design and simulation of such aberration correction mechanism is described. Our results show significant improvement to the Strehl ratio by using our aberration correction scheme which results in diffraction limited performance. Compactness and effectiveness of our design can be implemented in many applications that require aberration correction, such as microscopy and consumer electronics.

Revisiting the economic theory of crime A state-level analysis in India

The economic theory of crime tends to suggest that deterrence variables have a significant impact on crime rates in a society. From an economic perspective, criminals are rational economic agents who weigh the likelihood of being arrested and apprehended before committing a crime. An increase in the likelihood of arrest and apprehension should deter criminals as it increases the expected costs of committing crimes. This paper revisits the behavioral links between deterrence variables and crime rates in the Indian context. Empirically, we draw on state level data for India in 2001–2014 and employ the system GMM estimator technique to support our claims. The study reports that deterrence factors (probability of arrest and apprehension) have a perverse impact on India’s crime rates. The paper reveals that an increase in the probability of deterrence variables does not lead to a reduction in crime rates, indicating a fundamental flaw in India’s corrective mechanisms. The research recommends penal system reform in order to accurately reconfigure the behavioral links between deterrence variables and crime rates.

EWSR1 prevents the induction of aneuploidy through direct regulation of Aurora B.

EWSR1 (Ewing sarcoma breakpoint region 1) was originally identified as a part of an aberrant EWSR1/FLI1 fusion gene in Ewing sarcoma, the second most common pediatric bone cancer. Due to formation of the EWSR1/FLI1 fusion gene in the tumor genome, the cell loses one wild type EWSR1 allele. Our previous study demonstrated that the loss of ewsr1a (homologue of human EWSR1) in zebrafish leads to the high incidence of mitotic dysfunction, of aneuploidy, and of tumorigenesis in the tp53 mutant background. To dissect the molecular function of EWSR1, we successfully established a stable DLD-1 cell line that enables a conditional knockdown of EWSR1 using an Auxin Inducible Degron (AID) system. When both EWSR1 genes of DLD-1 cell were tagged with mini-AID at its 5'-end using a CRISPR/Cas9 system, treatment of the (AID-EWSR1/AID-EWSR1) DLD-1 cells with a plant-based Auxin (AUX) led to the significant levels of degradation of AID-EWSR1 proteins. During anaphase, the EWSR1 knockdown (AUX+) cells displayed higher incidence of lagging chromosomes compared to the control (AUX-) cells. This defect was proceeded by a lower incidence of the localization of Aurora B at inner centromeres, and by a higher incidence of the protein at Kinetochore proximal centromere compared to the control cells during pro/metaphase. Despite these defects, the EWSR1 knockdown cells did not undergo mitotic arrest, suggesting that the cell lacks the error correction mechanism. Significantly, the EWSR1 knockdown (AUX+) cells induced higher incidence of aneuploidy compared to the control (AUX-) cells. Since our previous study demonstrated that EWSR1 interacts with the key mitotic kinase, Aurora B, we generated replacement lines of EWSR1-mCherry and EWSR1:R565A-mCherry (a mutant that has low affinity for Aurora B) in the (AID-EWSR1/AID-EWSR1) DLD-1 cells. The EWSR1-mCherry rescued the high incidence of aneuploidy of EWSR1 knockdown cells, whereas EWSR1-mCherry:R565A failed to rescue the phenotype. Together, we demonstrate that EWSR1 prevents the induction of lagging chromosomes, and of aneuploidy through the interaction with Aurora B.

A probability smoothing Bi-RRT path planning algorithm for indoor robot

Bidirectional rapidly exploring random trees (Bi-RRTs) have been widely applied in path planning and have been demonstrated to yield the optimal path for indoor robots. However, the quality of the initial solution is not guaranteed, and the convergence speed to the optimal solution is slow. To overcome these limitations, this paper proposes a novel probability-smoothing Bi-RRT (PSBi-RRT) algorithm for path planning. Specifically, the kinematic model is established, and the posture of the indoor robot is estimated. Thereafter, a target biasing strategy is introduced to select sampling points in the sampling region. In addition, a node correction mechanism is applied to correct node coordinates to reduce the collision probability in cluttered environments. Finally, two trees are connected using the direct connection method. The θ-cut mechanism is designed to remove the redundancy points, and the remaining nodes are connected using a triangular inequality-based RRT to ensure that the final path is optimal. Furthermore, the proposed method benefits from the properties of Bi-RRT, which offers low-cost solutions with fewer iterations compared with Bi-RRT alone. Different simulations were performed to demonstrate the significance of PSBi-RRT in comparison with Bi-RRT, InformedBi-RRT*, and QuickBi-RRT*.

Inaccuracy in the Scientific Record and Open Postpublication Critique.

There is growing evidence that the published psychological literature is marred by multiple errors and inaccuracies and often fails to reflect the changing nature of the knowledge base. At least four types of error are common-citation error, methodological error, statistical error, and interpretation error. In the face of the apparent inevitability of these inaccuracies, core scientific values such as openness and transparency require that correction mechanisms are readily available. In this article, I reviewed standard mechanisms in psychology journals and found them to have limitations. The effects of more widely enabling open postpublication critique in the same journal in addition to conventional peer review are considered. This mechanism is well established in medicine and the life sciences but rare in psychology and may assist psychological science to correct itself.