Error Correction Mechanism Research Articles

SpeciFingers

The inadequate use of finger properties has limited the input space of touch interaction. By leveraging the category of contacting fingers, finger-specific interaction is able to expand input vocabulary. However, accurate finger identification remains challenging, as it requires either additional sensors or limited sets of identifiable fingers to achieve ideal accuracy in previous works. We introduce SpeciFingers, a novel approach to identify fingers with the capacitive raw data on touchscreens. We apply a neural network of an encoder-decoder architecture, which captures the spatio-temporal features in capacitive image sequences. To assist users in recovering from misidentification, we propose a correction mechanism to replace the existing undo-redo process. Also, we present a design space of finger-specific interaction with example interaction techniques. In particular, we designed and implemented a use case of optimizing the performance in pointing on small targets. We evaluated our identification model and error correction mechanism in our use case.

Identification and Verification of Error-Related Potentials Based on Cerebellar Targets.

The error-related potential (ErrP) is a weak explicit representation of the human brain for individual wrong behaviors. Previously, ErrP-related research usually focused on the design of automatic correction and the error correction mechanisms of high-risk pipeline-type judgment systems. Mounting evidence suggests that the cerebellum plays an important role in various cognitive processes. Thus, this study introduced cerebellar information to enhance the online classification effect of error-related potentials. We introduced cerebellar regional characteristics and improved discriminative canonical pattern matching (DCPM) in terms of data training and model building. In addition, this study focused on the application value and significance of cerebellar error-related potential characterization in the selection of excellent ErrP-BCI subjects (brain-computer interface). Here, we studied a specific ErrP, the so-called feedback ErrP. Thirty participants participated in this study. The comparative experiments showed that the improved DCPM classification algorithm proposed in this paper improved the balance accuracy by approximately 5-10% compared with the original algorithm. In addition, a correlation analysis was conducted between the error-related potential indicators of each brain region and the classification effect of feedback ErrP-BCI data, and the Fisher coefficient of the cerebellar region was determined as the quantitative screening index of the subjects. The screened subjects were superior to other subjects in the performance of the classification algorithm, and the performance of the classification algorithm was improved by up to 10%.

Effect of Monetary Policy on Macro Economic Variables of Nepal

This study examines the effect of monetary policy on macroeconomic variables such as gross domestic product, real interest rate, inflation, unemployment and balance of payment etc. All the variables are intertwined with each other, and one way or the other it affects each other in both short run and long run. It is secondary research with causal comparative research design. It has quantitative nature and time series data are extracted from year 1990 to 2017 of six different macro-economic variables for the study. Statistical tools and applied econometrics namely, descriptive statistics, ADF, Johansen cointegration test, Engle- Granger error correction model are applied. The result from the statistical analysis shows that instruments of monetary policy has influence on the selected macroeconomic variables to some extent and satisfies to be relatively effective. Findings of the study reveals that there is long-run relationship between monetary policy and the selected macroeconomic variables in the Nepalese economy significantly from the error correction mechanism.

Contribution of Foreign Direct Investment on Real Gross Domestic Product of Nepal

The objective of this article is to measure the contribution of Real Foreign Direct Investment (RFDI) on Real Gross Domestic Product (RGDP) covering the sample period of 2000 – 2021 AD, employing time-series data. The period 2000 AD was the peak policy changes of Nepal’s openness and updated data are available up to 2021AD. Co-integration analysis is introduced to capture long-run relationship, and Pairwise Engel Granger test, and Error Correction Mechanism (ECM) are for short-run relationship among variables. On the paper, RFDI contributes to RGDP; the coefficient is positive as well as significant at the 5 percent level in the short run only. In the long run, RFDI is not effective for the Nepalese RGDP growth like African country of Botswana. The research finds remittance, domestic capital and export, tourism earning, are important tools to RGDP growth for long run and these variables are positive and significant at 5 percent level. All the stability and diagnostic test of the model has no symbols of misspecification, residuals are normally distributed, homoscedasticity and no serially correlated.

Exchange Rate Dynamics and Agricultural Sector Performance Nexus: The Nigerian Experience

The main objective of the study is to investigate the impact of exchange rate dynamics on agricultural sector performance in Nigeria. The study employed time series data obtained from the Central Bank of Nigeria statistical bulletin, World Development Indicators and National Bureau of Statistics. Agricultural sector performance was disaggregated into the overall agricultural, crop, livestock and fishery output. Autoregressive Distributive Lag (ARDL) and Generalized Autoregressive Conditional heteroskedasticity (GARCH) estimation techniques were used to establish the long run relationship among the variables, and the responsiveness of overall agricultural output, crop, livestock and fishery production to changes in exchange rate. It was revealed that long run relationship exists among the variables in all the estimated models. The result of the Error Correction Mechanism (ECM) within the framework of the ARDL shows that exchange rate has significant impact on agricultural sector performance. The GARCH results revealed that the responsiveness of aggregate agricultural output, crop, livestock and fishery production to changes in exchange rate is negative and statistically significant. This study concludes that the government must consciously direct policy actions towards the agricultural sector to achieve its full potentials in order to place the Nigerian economy on the path of self- sufficiency in agricultural production. The study recommends that; the government should implement appropriate exchange rate policy that will ensure sufficient crop production for both domestic consumption and exports. The movement in the market determined exchange rate should be strictly monitored by the apex bank, in order to ensure that the deregulation in exchange rate is not counterproductive through distortionary prices on agricultural production.

Health Infrastructure and Economic Development Nexus in Nigeria

Nigeria like many other Sub-Saharan African countries has been plagued with lack of functional infrastructure in order to grow the economy. Recent events in Nigeria, such as the COVID-19 pandemic, which emerged in late 2019 and continues to impact Nigeria, has exposed the vulnerabilities and weaknesses in the country's health infrastructure. This study investigates the impact of health infrastructure on economic development in Nigeria. The study employed time series data. Health infrastructure was captured by government recurrent and capital expenditure on health while economic development was proxied by per capita gross national product. The Autoregressive Distributive Lag (ARDL) estimation technique was used to establish the long run relationship among the variables. It was revealed that long run relationship exists among the variables in the estimated model. The results of the Error Correction Mechanism (ECM) within the framework of the ARDL shows that health infrastructure has significant impact on economic development in Nigeria. The study concludes that health infrastructure plays key roles in influencing economic development in Nigeria, and for the optimal performance of the economy, the government must increase infrastructural spending on health care in order to reduce the rate of maternal, infant and under-five mortality in the country. The study recommends that; there is a need for the government at all levels to massively invest in the provision of health infrastructure which is a strong viable means of reducing mortality incidence and enhancing economic development in Nigeria. Nigeria’s share of government expenditure to the health sector ranges between 5-7 percent, which falls immensely below the minimum standard of 16 percent as recommended by UNESCO for a developing country, which calls for emergency intervention in the health sect

Stabilizing Error Correction Mechanism in the Presence of Explosiveness

In the presence of explosiveness of the adjustment term in the error correction model, the adjustment of the dependent variable Y was too large and overshoots the equilibrium, creating a divergent pattern. The error correction model fails to capture the deviation from equilibrium appropriately, thereby resulting in overshooting of the model. In this paper, a new model to stabilize the explosiveness in an Error Correction model called the stabilizing Error Correction Mechanism was proposed. Mathematical methodology for obtaining the estimate of the model using the Ordinal Least Square method was derived. Error Correction model was used to model the relationship among the variables and the result was compared with the Stabilizing Error Correction Mechanism using root mean square error. A Monte-Carlo simulation was performed, and the stimulation results showed that the error correction model exhibited some explosiveness, and the damping coefficient of the stabilizing model exerted a stabilizing effect on the error correction mechanism, thereby reducing the overshooting in the error correction model. The proposed model contributed to a smoother and more stable response to deviations from the long-run equilibrium. The root mean square error of the stabilizing Error Correction model was observed to be 1.30663, 1.04533, 12.55786, 10.49876, 10.0034, and 19.41545 as compared to the adjustment model in the Error Correction model (60.6888, 35.5929, 315238, 24.31958, 10.1485 and 19.7687) when the persistence is high and . Therefore, the Stabilizing Error Correction model performs better than the Error Correction model.

MONEY MARKET INSTRUMENTS AND ECONOMIC GROWTH IN NIGERIA

<p>This paper examined the effect of money market instruments on economic growth in Nigeria from 1980 to 2020. To achieve the above objective, secondary data on real gross domestic product, treasury bills, commercial papers, bankers’ acceptances and monetary policy rate were sourced from the statistical bulletin of Nigeria’s apex bank. The Error Correction Mechanism (ECM) was used as the main analytical tool. The result revealed that all the instruments of money market – treasury bills, commercial papers and bankers’ acceptances have positive effect on economic growth in Nigeria during the period of study. This means that money market instruments – treasury bills, commercial papers and bankers acceptances enhanced economic growth in Nigeria during the period of study. However, only bankers’ acceptances significantly (meaningfully) influenced economic growth in Nigeria during the period of study. What this suggests is that though treasury bills and commercial papers have contributed to economic growth in Nigeria from 1980 to 2020, but their contribution is very low to trigger a meaningful increase in economic growth. At the same time, Monetary Policy Rate has negative and insignificant relationship with economic growth in Nigeria during the period considered in this study. The study concluded that money market instruments - treasury bills, commercial papers and bankers’ acceptances have impacted on economic growth in Nigeria. Therefore, recommended that government should put in place policies that will increase the operations of money market in Nigeria in order to make short-term securities and loans available for investment. Deposit money banks and other operators in the money market should be encouraged to possess sufficient approved securities for trading in the money market. Government should ensure easy and effective communication between the operators in the money market. At the same time, there should be a downward review of the cost of raising funds in the Nigerian money market so as to enhance competitiveness and improve the attractiveness of the market as one of the major sources of raising funds for investment which in turn will increase economic growth in Nigeria.</p><p><strong>JEL</strong>: E44; G14</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0214/a.php" alt="Hit counter" /></p>

Retracted: An Automatic Pronunciation Error Detection and Correction Mechanism in English Teaching Based on an Improved Random Forest Model

Retracted: An Automatic Pronunciation Error Detection and Correction Mechanism in English Teaching Based on an Improved Random Forest Model

Industrialization and Employment Generation in Nigeria: An Empirical Analysis<b></b>

This study examined the impact of industrialization on employment creation, taking evidence from the Nigerian economy and using annual data covering the period of 1990 to 2022. The specific objectives were to determine the causal relationship between industrialization and employment creation in Nigeria and to examine the impact of industrialization on employment creation in Nigeria. To draw empirical evidence, the econometric methods of autoregressive distributed lag (ARDL) with Error Correction Mechanism (ECM) and the Granger causality test were employed as the analytical techniques. The results of the ARDL and ECM reveal that a short-run and long-run relationship exists between industrial sector output and employment creation (proxied by the unemployment rate) in Nigeria. With the establishment of a long-run relationship and the aid of the ARDL bounds test for cointegration, the long-run and short-run estimates were estimated. The findings of the study reveal that industrial sector performance has a negative and significant impact on the unemployment rate in Nigeria. In other words, it has a positive and significant impact on employment creation in Nigeria. Therefore, the study, among other requisite recommendations, suggests that the Nigerian authority prioritize the growth and improvement of the industrial sector through the provision of basic infrastructure such as transport networks, energy systems, and communication technologies, among others.

Analysis of the effects of climate change on palm oil output in Nigeria

The study examined the effect of climate change on palm oil output in Nigeria from 1965-2015. It focused on the trend of oil palm output during the period, the effects of climatic factors on the output. Secondary data were used for the analyses using tables, graph and time series analyses. The result of the Augmented Dickey Fuller (ADF) unit root test showed that all the variables became stationary after the first difference was taken while the Johansen cointegration test indicated the existence of a long run equilibrium relationship among the variables. Error Correction Mechanism (ECM) result indicated that rainfall (t= 3.01), relative humidity (t=2.56), temperature (t=4.50) and solar radiation (t=4.23) were significant at 5% level (p<0.05): were significant climatic factors affecting palm oil output. This validates the alternative hypothesis one (Ha1), that climatic factors have significant effect on palm oil output in Nigeria. The study recommends that concerted effort should be made to reduce the level of solar radiation by mitigation in Nigeria.

A Data-Driven Topology and Parameter Joint Estimation Method in Non-PMU Distribution Networks

For distribution networks, topology and line parameter information is the pre-requisite of further functions such as network analysis, operation and control. To identify the topology or estimate the parameters, a lot of existing literature relies on the knowledge of feasible topologies or full-scale deployment of advanced measuring devices, such as phase measurement units (PMUs), which is unrealistic in practice. Therefore, we propose a data-driven topology and parameter joint estimation method for non-PMU distribution networks, only using historical measurement data from smart meters. First, the topology label matrix, as a unique label of the network topology and corresponding parameters, is created and calculated based on historical data. The numeric characteristics of the topology label matrix is further analyzed to extract the topology and parameter information. Subsequently, a clustering based topology identification and parameter estimation methodology is proposed as a data-driven linear regression model. To reduce the coupling during regression, a power supply path matrix is utilized to improve the accuracy. Moreover, to improve the credibility of the method, an error-correction mechanism is proposed to indicate whether the inaccurate identification exists and how to correct it. Finally, the proposed method is tested in IEEE 33-node, 123-node networks and a large-scale system. The results demonstrate that the proposed method can provide an accurate estimation of the topology and line parameters based on samples of measurement with noise and is also effective in a large-scale system.

Neurologically Motivated Simulation of Ensemble Performance

A “rhythmic agent” is simulated based on the foundation of a previously published behavioral sensorimotor synchronization (SMS) model. The model is adjustable to control the auditory and tactile modalities of the tap's feedback. In addition to the conventional mechanisms of phase and period error correction, as well as their activation conditions, the period is estimated by modeling a central timekeeper impacted by a novel short-term memory. Inspired by The ADaptation and Anticipation Model (ADAM), a mechanism for linearly extrapolating anticipation is also tested. To better match the perceptual and motor cognitive functions, the model's parameters have been tuned to observations from experimental neurosensory literature with an emphasis on transduction delays. The agent is programmed to synchronize with various external rhythmic input signals while accounting for both adaptive and predictive mechanisms. The definition of the agent is based on a minimal set of rules yet has successfully replicated results of real-world observations: against a metronome; it produces the well-known negative mean asynchrony. In a rhythmic joint action, the simulation of joint delayed coordination shows a behavior previously observed in human subjects: in a rhythmic collaboration, a moderate amount of delay is necessary to keep the tempo steady, and below that threshold, the rhythm tends to speed up. It is also shown that giving more weight to the tactile afferent feedback than the auditory intensifies this effect. Moreover, it is observed that including anticipation in addition to the reactive mechanism will decrease the effect. The proposed model as a rhythmic engine, combined with other standard modules such as a beat detection algorithm, can be used to implement musical co-performers that could improvise with a human rhythmically or perform a given score in a way that feels human-like.

The Role of Private Investment and the Relationship between Monetary Policy and Economic Growth in Nigeria.

Despite government initiatives and policy reforms promoting private investment, such as the Structural Adjustment Programmes and various economic reform policies, Nigeria has experienced minimal improvement in private investment indicators, with the share of private investment in economic growth fluctuating over the years, characterized by intermittent increases and declines. Thus, the study investigates the role of private investment and the relationship between monetary policy and economic growth in Nigeria. The study utilized secondary data obtained from the Central Bank of Nigeria through an ex-post facto research design spanning from 1985 to 2022. Employing an autoregressive distributed lag model, which includes an error correction mechanism and cointegration test, the analysis examined variables, revealing that private investment mediates positively in the relationship between monetary policy and economic growth in Nigeria. The findings underscored the significant impact of private investment on the nexus between monetary policy and economic growth, suggesting policy recommendations including incentivizing private investment through the removal of capital controls and investment regulations, reducing or eliminating taxes and regulatory burdens, and fostering a supportive environment for business creation.

The Macroeconomic Determinants of Economic Growth in Bangladesh: An ARDL Approach

The study aims to explore the impact of major macroeconomic variables (Capital, Government Expenditure, Net Trade and Domestic Credit) on Gross Domestic Products (GDP) of Bangladesh. In this study we have employed Autoregressive Distributive Lag (ARDL) mode to the short run as well as long run relationship between major macroeconomic variables and GDP of Bangladesh. The findings of the study is that in the short run capital and domestic credit have showed negative relationship at lag 1, while the remaining variables have showed positive relationship with GDP. However, the error correction mechanism shows that disequilibrium in the short run converges to equilibrium at a rate of 34%. Capital, Government Expenditure, Net Trade and Domestic Credit all are positively associated with GDP in the long run. Gross capital formation and government expenditure have strong positive effects on GDP of Bangladesh.

Plant kinetochore complex: composition, function, and regulation.

The kinetochore complex, an important protein assembly situated on the centromere, plays a pivotal role in chromosome segregation during cell division. Like in animals and fungi, the plant kinetochore complex is important for maintaining chromosome stability, regulating microtubule attachment, executing error correction mechanisms, and participating in signaling pathways to ensure accurate chromosome segregation. This review summarizes the composition, function, and regulation of the plant kinetochore complex, emphasizing the interactions of kinetochore proteins with centromeric DNAs (cenDNAs) and RNAs (cenRNAs). Additionally, the applications of the centromeric histone H3 variant (the core kinetochore protein CENH3, first identified as CENP-A in mammals) in the generation of ploidy-variable plants and synthesis of plant artificial chromosomes (PACs) are discussed. The review serves as a comprehensive roadmap for researchers delving into plant kinetochore exploration, highlighting the potential of kinetochore proteins in driving technological innovations in synthetic genomics and plant biotechnology.

Banking Sector as a Long-Term Catalyst for Economic Growth in Poland

This study investigates the banking sector's influence on Poland's economic growth from Q4 2010 to Q1 2023. Employing the Autoregressive Distributed Lag (ARDL) model with an Error Correction Mechanism (ECM) and Granger causality, the relationship between the banking sector and economic development in Poland is explored. The model includes macroeconomic control variables such as inflation, interest rates, the domestic demand to GDP ratio, the general business climate index in the industry, and a dummy variable to account for the economic impacts of the COVID-19 pandemic and the Ukraine conflict. Findings show an inverse relationship between the bank assets to GDP ratio and GDP growth in the short run. At the same time, a positive correlation is observed in the long run, underlining the banking sector's essential role in Poland's economic progression. Additional banking variables like Return on Assets (ROA), Non-Performing Loans (NPL), and the ratio of equity to assets were analysed. However, only the bank assets to GDP ratio exhibited a statistically significant positive long-term effect on Poland's GDP. This research offers crucial insights into the complex interplay between the banking sector and economic growth in Poland, with particular emphasis on recent geopolitical and pandemic events.

Encoding fluorescence intensity with tetrahedron DNA nanostructure based FRET effect for bio-detection

Biocoding technology constructed by readable tags with distinct signatures is a brand-new bioanalysis method to realize multiplexed identification and bio-information decoding. In this study, a novel fluorescence intensity coding technology termed Tetra-FICT was reported based on tetrahedron DNA nanostructure (TDN) carrier and Főrster Resonance Energy Transfer (FRET) effect. By modulating numbers and distances of Cy3 and Cy5 at four vertexes of TDN, different fluorescence intensities of twenty-six samples were produced at ∼565.0 nm (FICy3) and ∼665.0 nm (FICy5) by detecting fluorescence spectra. By developing an error correction mechanism, eleven codes were established based on divided intensity ranges of the final FICy3 together with FICy5 (Final-FICy3&FICy5). These resulting codes were used to construct barcode probes, with three miRNA biomarkers (miRNA-210, miRNA-199a and miRNA-21) as cases for multiplexed bio-assay. The high specificity and sensitivity were also demonstrated for the detection of miRNA-210. Overall, the proposed Tetra-FICT enriched the toolbox of fluorescence coding, which could be applied to multiplexing biomarkers detection.

Nexus Between Pension Funds and Stock Market Sustainability Development in Nigeria

Objective: It has long been recognized that pension systems across the emerging markets including Nigeria have undergone dramatic reforms over the last twenty-eight years. This process has mainly been fueled by the demographic problem faced by modern financial systems. Hence, this study examines the short-run and long-run dynamic of pension funds on capital market development in Nigeria using ex-post facto research design. Method: Data were collected from the Central Bank of Nigeria (CBN) statistical bulletin and annual report of the pension fund commission from 1995 to 2022. Data collected were analyzed using descriptive statistics, unit root test and auto regressive lag model (ARDL) and Toda Yamamoto multivariate granger causality approach. The unit root test reveal that all the variables used in the study are non-stationary at first difference except inflation which is stationary at level. Results: The findings from the ARDL analysis reveal a short-run dynamic impact between pension funds and capital market development due to the coefficient of error correction mechanism (speed of adjustment) which is negative and significant at 5% level of significant. The result suggests that over 22% of the short run disequilibrium is corrected in the long run equilibrium. However, the results from the long-run dynamic impact reveal a positively significant impact between the proxies of pension funds (pension contributory fund, pension investment) and control variable - inflation to be positively significant with capital market development proxied by market capitalization as a ratio to GDP at 5% level of significant. The results of the Toda Yamamoto granger causality results suggest a bidirectional relationship between pension funds (pension contributory fund, pension investment) and market capitalization as a ratio of Gross Domestic Product (GDP) in Nigeria at aggregate level. This suggest that the relationship between pension funds (pension contributory fund, pension investment) and market capitalization as a ratio of Gross Domestic Product (GDP) in Nigeria was two-ways. Conclusion: The study concludes that pension fund administrators in Nigeria should understand that the rate of inflation is dynamic in Nigeria and the value of money is being lost as money is not worth it values in the next five years.

Bitter Rate of Performance in Wireless Communications on 5G Technology

Wireless communications have become an integral part of our modern society, enabling seamless connectivity and data exchange. The bit rate of performance in wireless communication systems plays a crucial role in determining the quality of service and user experience. This abstract provides an overview of key factors influencing bit rate in wireless communications and highlights the challenges and advancements in optimizing performance. The bit rate, often measured in bits per second (bps) or multiples thereof, quantifies the rate at which data can be transmitted over a wireless channel. Several factors impact the bit rate in wireless communications, including the available bandwidth, modulation schemes, signal-to- noise ratio (SNR), and channel conditions. The bit rate is closely related to the achievable data throughput and is a critical metric for assessing the efficiency of wireless networks. Wireless technologies, such as 4G and 5G, have significantly increased the bit rates achievable for mobile communication. These technologies employ advanced modulation techniques and multiple-input, multiple- output (MIMO) systems to enhance spectral efficiency and data rates. Additionally, the deployment of small cells and the use of high-frequency bands have improved data rates and reduced latency in wireless networks. However, challenges persist in optimizing bit rates for wireless communications. Factors like signal interference, fading, and path loss can degrade performance. Moreover, the ever- increasing demand for data-intensive applications and the proliferation of IoT devices put additional pressure on wireless networks to deliver higher bit rates with low latency. To address these challenges, ongoing research focuses on developing advanced signal processing algorithms, beamforming techniques, and error correction mechanisms. Machine learning and artificial intelligence are also being employed to optimize wireless communication systems and enhance bit rates.