Analysis of Work Measurement Using a Stopwatch in a Motorcycle Workshop

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Abstract

In realizing competitiveness, a company/ business organization must have operational excellence. Operational excellence is obtained through the provision of facilities in the form of tools or work systems that enable workers to operate them more efficiently and effectively, where efficiency and effectiveness are two things that produce productivity. Apart from many influencing factors, such as worker experience and knowledge, CV. XYZ – a work organization engaged in the repair of two-wheeled motorized vehicles – is also trying to create an advantage that allows them to increase their productivity. This research is a quantitative descriptive study, which takes time data from the two jobs most routinely carried out by CV. XYZ, namely changing engine oil and gear oil. This research was carried out with the aim of finding out the standard time needed for workers to complete their work and making recommendations for possible improvements to be implemented by CV management. XYZ, namely recommendations for the layout of work facilities and also the sequence of work processes. The measurement results show that the standard time required to complete the job of changing engine oil and garden oil is 372.68 seconds and 417.99 seconds, respectively. Creating an operational flow map (current FPC) shows that the average distance that workers need to travel while working on engine oil and garden oil is 22 meters. The results of the FPC recommendation provided show that the distance has decreased to 16.5 meters or 5.5 meters shorter.

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A Study to Evaluate Psychological Distress and Self-Esteem Among Patients with Hemodialysis

Yogesh Kumar. C (2024)

Background: Chronic kidney disease (CKD) is a progressive disease that affects more than 800 million people worldwide, representing more than 10% of the global population. It is more common in older people, women, and racial minorities, as well as in people with diabetes mellitus and high blood pressure. CKD has become one of the top causes of mortality worldwide, and is one of the few non-communicable diseases that have seen an increase in related deaths over the last few decades. The high number of affected people and the serious negative consequences of chronic disease should lead to increased efforts to improve prevention and treatment efforts. Around the world, there are an estimated 1,800-1,600 extra deaths per 10000 patients who are on dialysis.  Aim: The aim of the study is to determine the psychological distress and self-esteem among dialysis patients.  Research Methodology: A quantitative cross-sectional investigate plan was utilized to conduct a research study among 30 dialysis patients. Convenient sampling techniques were utilized to collect data from standardized tool using questionnaire techniques.  Result: Study showed that 36.7% of the samples were doing well, 23.3% had mild psychological distress, 23.3% of the samples had moderate psychological distress and severe distress is seen in 16.7% of the samples. 73.3% of them had normal self-esteem, 20% of the study population had low self-esteem and 6.7% had above average self-esteem. Significant relationship is seen between social and family support with self-esteem (p=0.033).  Conclusion: About half of the samples were having psychological distress which is of mild and moderate, severe psychological distress were seen in 16.7% of the samples, ordinal self-esteem were seen in 73% of the samples, 27% of samples had mild and average self- esteem.

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Implications of Adnexal Invasions in Primary Extramammary Paget’s Disease: A Systematic Review

Sabita Aryal, Liu Ye Qiang (2024)

Extramammary Paget’s disease (EMPD) is an erratic malignant skin disorder primarily affecting skin areas abundant with skin appendages like hair follicles. The vulva is most involved site, followed by genital areas, penoscrotal regions and axillary skin. EMPD presents as erythematous skin lesions resembling eczema, typically progressing slowly, either primary or secondary manifestations. Primary EMPD originates as an intraepithelial neoplasm of the epidermis, often leading to local lymph node metastases and distant metastases. A systematic literature search using targeted keywords across multiple databases was conducted. Studies focusing on EMPD, adnexal involvement, depth, recurrence, and prognosis were included by keeping in view the objective which is to determine the significance of adnexal involvement and depth concerning recurrence and prognosis in the primary EMPD. Adnexal involvement, especially in hair follicles and eccrine ducts, is prevalent in primary EMPD. However, its correlation with tumor progression or recurrence rates remains inconclusive. Surgical excision, including Mohs micrographic surgery, is the primary therapeutic approach, with topical agents and systemic treatments used in advanced cases. Future studies regarding understanding adnexal involvement's depth and significance are essential in designing effective targeted therapeutic approaches in EMPD.

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Enhancements in Immediate Speech Emotion Detection: Harnessing Prosodic and Spectral Characteristics

ZEWAR Shah, SHAN Zhiyong, Adnan . (2024)

Speech is essential to human communication for expressing and understanding feelings. Emotional speech processing has challenges with expert data sampling, dataset organization, and computational complexity in large-scale analysis. This study aims to reduce data redundancy and high dimensionality by introducing a new speech emotion recognition system. The system employs Diffusion Map to reduce dimensionality and includes Decision Trees and K-Nearest Neighbors(KNN)ensemble classifiers. These strategies are suggested to increase voice emotion recognition accuracy. Speech emotion recognition is gaining popularity in affective computing for usage in medical, industry, and academics. This project aims to provide an efficient and robust real-time emotion identification framework. In order to identify emotions using supervised machine learning models, this work makes use of paralinguistic factors such as intensity, pitch, and MFCC. In order to classify data, experimental analysis integrates prosodic and spectral information utilizing methods like Random Forest, Multilayer Perceptron, SVM, KNN, and Gaussian Naïve Bayes. Fast training times make these machine learning models excellent for real-time applications. SVM and MLP have the highest accuracy at 70.86% and 79.52%, respectively. Comparisons to benchmarks show significant improvements over earlier models.