d. kumar

In response to the escalating complexity of network environments and the heightened sophistication of cyber threats, the demand for robust and efficient Network Intrusion Detection Systems (NIDS) is now crucial. This paper presents an innovative NIDS approach utilizing Convolutional Long Short-Term Memory (ConvLSTM) networks and attention mechanisms for precise and timely intrusion detection. Our proposed model integrates ConvLSTM's ability to capture spatiotemporal dependencies in network traffic data with attention mechanisms that enable the model to focus on pertinent information and filter out noise. We preprocess network traffic data into a sequential format, employ ConvLSTM layers to learn spatial and temporal features, and introduce an attention mechanism that assigns varying weights to different input data parts. This dynamic weighting emphasizes regions most likely to contain malicious activity. Extensive experiments on the CICIDS2017 Dataset validate the effectiveness of our approach, achieving an accuracy of 99.98%. This underscores its potential to revolutionize modern network intrusion detection and proactively safeguard digital assets.

The manufacturing industry is the foundation of the Malaysian economy. The manufacturing industry in Malaysia is diverse, but it has consistently demonstrated superiority in several industries, including semiconductors, pharmaceuticals, medical technology, oil and gas, and the processing and management of palm oil and rubber. Businesses may find themselves in a very hazardous situation if their employees are dissatisfied. Improving employee performance can help an organization increase its production volume and productivity. A lack of worker satisfaction can lead to disinterest and an inability to achieve specific goals. When new employees notice a pay disparity, dissatisfaction, disengagement, and disloyalty arise. It happens when workers believe they are being mistreated or unfairly treated. Businesses must prioritize the well-being of their employees because it is more important to retain them than to let them go. To remain competitive, the organization must keep qualified or competent staff motivated. The study aims to determine the mediating effect of job satisfaction in the relationship between wages, appreciation, recognition, and promotion on employee performance among employees at a multinational semiconductor company in Melaka.   For this investigation, the quantitative method was used to analyze information using partial least squares structural equation modeling. This study's sample size is 137, based on the partial least squares structural equation modeling sample size recommendation for an 80% statistical power. Employees of multinational semiconductor companies in Melaka received 142 questionnaires. The partial least squares structural equation modeling sample size table determines the sample size in this study, which combines convenience and nonprobability sampling. The relationship between the variables is determined through hypothesis testing. partial least squares structural equation modeling was used to analyze the data. As a result, all eleven hypotheses were evaluated based on the variables - wages, appreciation, recognition, promotion, and job satisfaction have a positive and significant relationship with employee performance. The hypotheses have been accepted with a p-value ranging from 0.005 to 0.048. For direct relationship, the hypothesis from 1-7, there is a positive correlation (t = 2.993 to t=4.521, p ≤ 0.005) between wages, appreciation, recognition, promotion, job satisfaction, and employee performance. Therefore, hypotheses 8-11 show an indirect relationship (mediating effect) that positive correlation with a significant p-value of 0.010 to 0.048 between an independent variable (wages, appreciation, recognition, and promotion), mediating variable (job satisfaction), and dependent variable (employee performance). The study provides empirical evidence and conceptual proof that the establishment of policy recommendations derived from the findings should consider Malaysian legal regulations. The management by objectives policy was implemented to improve organizational performance by establishing well-defined goals that management and employees can agree on. The management by objectives approach is a technique for inspiring workers through constructive management techniques because the management objectives approach can increase communication between management and employees. As a result, the management strategy contributes to improving employees' wages, appreciation, recognition, promotion, job satisfaction, and performance.

This paper presents the steady state behavior and maintenance planning of the bleaching system in a paper plant. The paper plant comprises of various systems including feeding, chipping, digesting, wash-ing, bleaching, screening, stock preparation and paper making, etc. One of the most important functionaries of a paper plant, on which quality of paper depends, is the bleaching system, where removal of coloring constituents is done to obtain the desired degree of brightness. The bleaching system consists of two subsystems A and B arranged in series with two states; good and failed. The mathematical modeling is carried out on the basis of Markov birth-death process using a probabilistic approach. An expression for steady state availability is also developed. Based upon the maintenance data available from medium sized paper plant, the effect of each working unit on the system availability behavior has been explained. In this regard, the behavioral chart for bleaching system has been given. Besides, a maintenance schedule has also been suggested and utilized for the purpose of maintenance planning of the bleaching system in a paper plant. The findings of this paper have been discussed with the concerned plant personnel and found to be highly beneficial for enhancing the performance level of the plant concerned.

The paper presents a multi-factor decision-making approach for prioritizing failure modes as an alternative to traditional approach of failure mode and effect analysis (FMEA). The approach is based on the ‘technique for order preference by similarity to ideal solution’ (TOPSIS). The priority ranking is formulated on the basis of six parameters (failure occurrence, non-detection, maintainability, spare parts, economic safety and eco-nomic cost). The Shannon`s entropy concept has been used for assigning objective weights to maintenance pa-rameters. The application of the approach has been reported with an actual case from a paper industry to illus-trate the use of the proposed methodology.