AN IMPROVED Research Articles

SAW GIN WITH AN IMPROVED FIBER CLEANING UNIT

SAW GIN WITH AN IMPROVED FIBER CLEANING UNIT

A MENTAL ILLNESS EARLY WARNING ANALYSIS MODEL USING AN IMPROVED SVM ALGORITHM AND EEG SIGNALS

The fast-paced lifestyle, intense competition, and constantly changing environment of modern society are important factors contributing to the emergence of psychological disorders. Factors such as work pressure, family conflicts, and interpersonal relationship difficulties pose challenges to individual mental health. Prolonged use of electronic devices and the widespread use of social media further exacerbate mental health issues, as the constant influx of information makes it difficult for people to relax and focus. The harm of psychological disorders to individuals and society cannot be ignored. It not only diminishes the quality of life for patients but also affects work efficiency and social participation. In extreme cases, psychological disorders can lead to serious consequences like suicide, causing immense pain to families and society. Therefore, prioritizing mental health, raising awareness of mental well-being, and timely intervention and treatment of psychological disorders are crucial for individual happiness and social stability. Based on this, this study employs an improved Support Vector Machine (SVM) and Electroencephalogram (EEG) signals for the diagnosis of psychological disorders, aiming for more effective treatment of mental health conditions. Specifically, the EEG signals of the experimental subjects are first collected as training data for the model. The dataset undergoes preprocessing operations such as cleaning and normalization. Due to the limited availability of published information about individuals with psychological disorders, an ensemble SVM algorithm is used as a warning model to improve the accuracy of psychological disorder diagnosis. This algorithm utilizes a differential measurement method to adjust the selection of SVM parameters. The training sample size remains constant, with several iterations of training performed. By combining the differential measurement method, a specific parameter combination is obtained, maximizing the differentiation between base classifiers. This ultimately addresses issues such as small sample size and insufficient sample information in the dataset. Experimental results demonstrate that the model used in this study exhibits good performance in diagnosing psychological disorders.

DESIGN AND DEVELOPMENT OF AN IMPROVED SS-15A SEPARATOR

DESIGN AND DEVELOPMENT OF AN IMPROVED SS-15A SEPARATOR

MP24-09 MEN WITH AN IMPROVEMENT IN URINARY SYMPTOMS HAVE A LOWER RISK OF MORTALITY

You have accessJournal of UrologyCME1 Apr 2023MP24-09 MEN WITH AN IMPROVEMENT IN URINARY SYMPTOMS HAVE A LOWER RISK OF MORTALITY Blayne Welk and J Andrew McClure Blayne WelkBlayne Welk More articles by this author and J Andrew McClureJ Andrew McClure More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003249.09AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Male lower urinary tract symptoms (LUTS) have been correlated with an increased risk of death, and it is unclear if this is a causal association. Our objective was to determine whether a reduction in LUTS is associated with a reduced risk of mortality. METHODS: We conducted a secondary analysis of the pivotal Medical Treatment of Prostate Symptoms (MTOPS) randomised trial. Men age >50 years with moderate to severe LUTS on the AUASS were randomised to placebo, doxazosin, finasteride, or doxazosin and finasteride. Our primary exposure was the change in the AUASS from baseline. This was modelled as a time-varying covariate and recalculated for each of the biyearly protocolized visits. Our primary outcome was death, which was prospectively recorded during the study. We used an extended cox model and adjusted it for age and treatment assignment. We conducted a similarly adjusted sensitivity analysis among those who were assigned active treatment only. Means and standard deviations (SD) and hazard ratios (HR) with 95% confidence intervals are reported. RESULTS: A total of 3046 men were randomised and had a baseline AUASS; 27 baseline variables were similar between the 705 men who did not have any LUTS improvement and the 2341 men who did have improvement. The mean age was 62.6 (SD7.3), and the mean baseline AUASS was 17.2 (SD 6.1). During the mean observation period of 6.1 (SD1.2) years there were 117 (3.8%) deaths. For each 1-point improvement in the AUASS, the HR for death was 0.96 (0.94-0.99, p=0.01); a 5-point improvement in the AUASS resulted in a HR for death of 0.83 (95% CI 0.72-0.96). This relationship was similar among the 2309 men who received some form of active treatment (HR 0.95, 0.92-0.98, p<0.01), independent of treatment group. A comparable significant reduction in death was seen with improvements in the storage and voiding subscales individually. CONCLUSIONS: Improvement in male LUTS was associated with a reduced risk of death. Unmeasured confounding was partly mitigated by using clinical trial data, where randomisation determined the likelihood of LUTS improvement. Further study is warranted to determine if the male LUTS treatment paradigm should shift towards symptom treatment independent of bother. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e321 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Blayne Welk More articles by this author J Andrew McClure More articles by this author Expand All Advertisement PDF downloadLoading ...

AN IMPROVED DYNAMIC TIME WARPING METHOD COMBINING DISTANCE DENSITY CLUSTERING FOR EYE MOVEMENT ANALYSIS

Analyzing eye movement data to evaluate learning status has become crucial in intelligent education. The eye movement scanning path can directly or indirectly reflect changes in thinking patterns and psychological states. By analyzing the scanning path, we can explore the commonality and differences in learners’ eye movement behaviors and provide essential references for improving visual content and giving guidance. This paper first studies the time series representation and clustering of the learner’s scanning path under the same task. Then, the three learning states of concentration, mind-wandering, and information wandering are evaluated through the clustering results. Specifically, the improved DBA algorithm (iDBA) is proposed to extract group eye movement patterns, combined with the dynamic time warping (DTW) algorithm to calculate the similarity of scanning paths and determine the clustering seeds, while the distance density clustering (DDC) algorithm is used for clustering. Experiments show that time series-based eye movement pattern mining can identify group viewing behaviors. Meanwhile, clustering reveals different reading strategies and provides the ability to assess learning status.

AN IMPROVED CORRELATION OF EVAPORATION RATE OF A WATER POOL DERIVED USING COMBINED ANN-GA

Empirical correlations are extensively utilized in applications such as the design of solar stills to estimate the evaporation rate from a pool of water. These correlations are based on specific experimental measurements carried out for a particular design and operating conditions. In a semiempirical approach, theoretical modeling is incorporated in deriving the expression for the evaporation rate. These models utilize assumptions such as zero temperature gradient in air and water and constant relative humidity in the surrounding air so as to circumvent whole field formulations. One such empirical correlation, called Dunkle's correlation, is improved in the present work by using a comprehensive ab initio approach in the background for estimating the evaporation rate, which incorporates two-layer natural convection with moisture transport for estimating the evaporative mass flux. The empirical and the ab initio approaches are compared to improve Dunkle's correlation in the inverse heat transfer framework. Here, the objective function is minimized using the combined artificial neural network-genetic algorithm (ANN-GA) tool. The uncertainties in estimating the parameters of interest are evaluated by sprinkling noise with a Gaussian distribution over the solutions of the comprehensive model. The improved Dunkle's correlation reduces the error in the predicted evaporation rate between 12&amp;#37; and 25&amp;#37;, depending on the water depth.

AN IMPROVED ENGINEERING METHOD FOR EVALUATING THE DUCTED PROPULSOR CHARACTERISTICS

AN IMPROVED ENGINEERING METHOD FOR EVALUATING THE DUCTED PROPULSOR CHARACTERISTICS

TUNING OF IMC CONTROLLER FOR SYSTEMS WITH TIME-DELAY USING AN IMPROVED STRANGE NONCHAOTIC OPTIMIZATION APPROACH

The internal model control (IMC) has received extensive attention due to strong robustness, while it is challenging to tune the parameters of the controller. So far, strange nonchaotic optimization algorithm, based on grazing bifurcation, has been proposed to tune the parameters of the IMC controller in some recent progress, which processes a strong ability to escape from local optimization. However, the nonuniformity of the strange nonchaotic sequence distribution can result in insufficient optimization capability. In this paper, in order to obtain an excellent optimization effect, an improved strange nonchaotic optimization algorithm (ISNOA) based on grazing bifurcation is proposed to tune the parameters of the IMC controller. First, the boundary of a strange nonchaotic sequence is redefined by analyzing the strange nonchaotic sequence distribution. Furthermore, normalization function is applied to determine the optimization space. Consequently, the proposed ISNOA has better ability to escape from the local minima, higher stability and finer performance than the general SNOA, which is more suitable to tune the parameters of the IMC controller. Simulation results illustrate the effectiveness of ISNOA. In addition, for mismatch model, numerical simulations demonstrate the good performance of the control system based on ISNOA, meanwhile, the ISNOA is also demonstrated to be superior to particle swarm optimization (PSO).

AN IMPROVED HAUSA WORD STEMMING ALGORITHM

The explosion of scientific publications in different domains coupled with the introduction and socialization of the internet experienced in the last few decades has made information more available than ever before. Consequently, digital storage capacity has been consistently doubling to reflect this geometric increase in information. In view of this, Information Retrieval (IR), nowadays considered the dominant form of information access has become even more critical. However, the problem of using free text in indexing and retrieval arising from spelling mistake, alternative in spelling, affixes and abbreviations has continued to bedevil the field of IR. To mitigate this problem, Stemming Algorithm was introduced in the 1960s. Stemming is an automated process of stripping all word derivatives of their inflectional affixes in order to obtain stem of the word. Because stemming is language specific, there are stemming algorithms designed specifically for most of the major languages in the world. With a speaker population of about 150 million Hausa language stands in need of a better stemming algorithm. This research is an attempt to improve upon the existing Hausa word stemming algorithm. Affix stripping method of conflation with reference lookup was used. Using Sirsat’s evaluation method, this research achieved 96.9% as Correctly Stemmed Word Factor (CSWF), Index Compression Factor – 74.76%, Words Stemmed Factor (WSF) – 70.44% and Average Word Conflation Factor – 59.47%.

DESIGN AND FABRICATION OF AN IMPROVED UHF U-NOTCHED QUASI-YAGI LOG-PERIODIC ANTENNA FOR WIRELESS APPLICATIONS

DESIGN AND FABRICATION OF AN IMPROVED UHF U-NOTCHED QUASI-YAGI LOG-PERIODIC ANTENNA FOR WIRELESS APPLICATIONS

AN IMPROVED BRACKETING METHOD FOR NUMERICAL SOLUTION OF NONLINEAR EQUATIONS BASED ON RIDDERS METHOD

In the present study numerical solution for non linear equations have been studied. Ridders methodd have been discussed. An improvement of Ridders method with combination of Bisection and newton Raphson methods have been presented. An algorithm for the proposed method have been stated. Moreover, several examples are included to demonstrate the validity and applicability of the presented technique. Matlab program involved for numerical computations. The proposed method applied for given examples. The error analysis table presents the obtained numerical results. The numerical solutions which found by Matlab program has good results in terms of accuracy.

AN IMPROVED SYNTHESIS OF P -PHENYLENE-BRIDGED METHYLATED BINUCLEAR FERROCENE

AN IMPROVED SYNTHESIS OF P -PHENYLENE-BRIDGED METHYLATED BINUCLEAR FERROCENE

WIRELESS SENSOR NETWORK: TOWARDS AN IMPROVEMENT OF SECURITY POLICY

Abstract. The ad hoc network (or MANET, for Mobile Ad hoc NETwork) is a system containing a set of devices that organize themselves, thus forming an autonomous and dynamic network, communicating via radio interface. These devices can be fixed or mobile, no wired infrastructure is available, and so these objects have to dynamically discover their environment.The design of these applications is based on trust between the nodes constituting the network. Unfortunately, when deploying randomly in difficult hostile areas, seeing impossible to monitor, not to mention the uncertainty of the communication channel, the sensor nodes are exposed to all types of attacks and intrusions, which can hinder and prevent the diffusion of the information between the sensor nodes of the network, and influencing its performance.Many approaches have been proposed to solve security problems in wireless networks. The solutions can be mainly classified into two categories: symmetric and asymmetric key management schemes. Indeed it is clear, that the optimal solution in this case is to use symmetric shared key systems.In this paper, the idea of LEAP improved is to apply the same Mechanisms used in LEAP Enhanced to overcome a compromised node and also prevent a compromised base station node while using a multiple base station network, this will, on the one hand, minimize power consumption, and secondly, to replace a base station in the event of a compromise, to ensure the continuity and proper functioning of the network. The evaluation of the proposed solution was carried out using the TOSSIM simulation tool.

AN IMPROVEMENT OF PRODUCTIVITY BY REAL TIME MACHINE MONITORING SYSTEM: A case study of printing industry

Digital technologies and automation integration is one of the promising directions to increase productivity in the manufacturing. A consulting project to promoting the adoption of digital technology under the policy of the Department of Industrial Promotion, and Thailand 4.0 to help small and medium entrepreneurs (SMEs) to assess and gain readiness to the use of cyber-physical including digital technology. The real-time data gathering system for monitoring and displaying information is presented. For example, IoT based sensors is applied in digital counting of machine-made goods. This data can be used to analyze the root cause of a manufacturing process problem, for example, time lost due to discontinuity of work or setting up. Best practices are observed at a printing factory. The implementation shows the effective data acquisition even the running speed of a machine is high. The owner and manager gain real-time access to the dashboard through their mobile phone or personal computer. Therefore, they can manage their jobs instantly and remotely. Moreover, the stored data can be downloaded in Excel format. The data can be used in process waste analysis. The numerical results of using this system, overall equipment productivity and efficiency (OEE) were increased by 10% to 15%, approximately.

AN IMPROVED APPROACH FOR SOLUTIONS OF SYSTEMS OF LINEAR FREDHOLM INTEGRO DIFFERENTIAL EQUATIONS

In this paper, a numerical matrix method is used to solve the systems of high-order linear Fredholm integro-differential equations with variable coefficients under mixed conditions. The technique consists of collocation points and the Morgan-Voyce polynomials. The residual error functions of numerical solutions of the method are also presented. Firstly, the approximate solutions are formed and secondly, an error problem is constituted in favor of the residual error function. The numerical solutions are computed for this error problem by using the present method. The approximate solutions of the original problem and the error problem are the corrected Morgan-Voyce polynomial solutions. When the exact solutions of the problem are not known, the absolute errors can be approximately constructed through the approximate solutions of the error problem. Numerical examples are included to demonstrate the validity and the applicability of the technique, and also the results are compared with the different methods. All numerical computations have been performed using MATLAB v7.11.0 (R2010b).

AN IMPROVED OPTIMIZATION TECHNIQUE FOR NETWORK CONTROLLED pH PROCESS AND DC MOTOR USING VARIOUS CONTROLLERS

ABSTRACT Networking has become the paradigm in many of the control industries, to control and diagnose the parameters or the machines. The networked environment is connection of different machines/components connected through a standard medium to transfer and receive data to monitor or control based on the application required in the environment. Generally the processes in industries are classified as the linear process and non-linear process where the classification is based on the information fetched. Linear process are generally controllable process where the errors or the problems occurred are known, whereas in the non-linear process generate random errors which are uncontrollable. In this paper two different systems such as pH process and DC motor is considered for networked control, where pH is a non-linear system and DC motor is a linear system. Majority of the industries work using the water as their main source for the manufacturing. Waste water treatment is a major issue where the quality of the waste water is connected with the pH value measured in the water. Most of the industries use DC motor to run their machines for different applications. Control of DC motor for multiple applications is considered as a difficult process where all the motors are to run at the same speed. Therefore to control both pH and DC motor Networked Control System is proposed to connect the process with the controllers. The proposed system has been concluded that Fuzzy Logic Controller under the networked environment has shown better results where the settling time and overshoot of pH and DC motor has been is 60 seconds & 0% and 8 seconds & 5.3% respectively, compared with the other controllers.

AN IMPROVED TIMING RECOVERY METHOD BASED ON GARDNER ALGORITHM

AN IMPROVED TIMING RECOVERY METHOD BASED ON GARDNER ALGORITHM

CALLIGRAPHIC MINUTES AS A FORM OF AN IMPROVEMENT OF WRITING OF PRIMARY SCHOOL PUPILS

CALLIGRAPHIC MINUTES AS A FORM OF AN IMPROVEMENT OF WRITING OF PRIMARY SCHOOL PUPILS

AN IMPROVED LOCAL ANALYSIS OF DEFORMED HALLEY METHOD IN BANACH SPACES

AN IMPROVED LOCAL ANALYSIS OF DEFORMED HALLEY METHOD IN BANACH SPACES

AN IMPROVED MULTI-LABELED LSTM TOXIC COMMENT CLASSIFICATION

The origin of text classification was far back to the early '60s. Text classification classified text into different predefined classifications. One of the techniques used for text classification long short term memory, which is an artificial recurrent neural network architecture. Today, all around the world people are expressing themselves with their opinions and also discuss among others via the media. In such a setup, it is quite observable that discussions may arise due to differences in opinion. These discussions might take a dirty side and which may further result in combats over the social media platforms and may lead to offensive language termed as toxic comments. To identify online hate speech, a large number of scientific studies have been devoted to using Natural Language Processing in combination with Machine Learning and Deep Learning methods. Among the challenges of toxic comment, classifiers are the Out-of-vocabulary words problem, which is the occurrence of words that are not present in the training data. Long-Range Dependencies are also a challenge to toxic comment classification. Which is a situation whereby the toxicity of comments often depends on expressions made in the early parts of the comment. This is especially problematic for longer comments. Another challenge is the low accuracy of comment classification techniques. Epoch was used in improving the accuracy of long short term memory. Epoch tends to improve the accuracy of the classifier since it positively affects the speed and quality of the learning process. We have an improvement of 0.4068 in precision, 0.2871 in a recall, 0.2293 in F1, and 0.4291 inaccuracy.