Spektrum Industri

Employing Emotion Detection in Short Messaging Systems to Safeguard Health and Well-being

2023-08-10T13:59:21+00:00

Health issues such as high blood pressure and other heart-related ailments can occur when users read messages with negative emotions or content. Therefore, detecting negative emotions in text can be a valuable tool in addressing some health concerns. Emotions can be conveyed through various means such as text, speech, and facial expressions. This study aims to develop a Text-based emotion detection system that can easily detect emotions in text messages. By blocking messages with negative emotions, users can be prevented from reading messages that could negatively affect their health. Meanwhile, messages with positive or neutral emotions can still be read. To achieve this, three machine learning algorithms (Naïve Bayes, Support Vector Machine, and Logistic Regression) were used, following the CRISP-DM methodology. The Logistic Regression algorithm gave the highest accuracy of 98.4% and was used to build the detection system. The system's Graphical User Interface was designed using HTML and CSS, and the various components were integrated to create a fully functioning interface for the user

Prevalence of Work Musculoskeletal Disorders in patients’ handling tasks among nursing staff in critical care-unit

2023-08-30T04:23:31+00:00

Awkward postures imposed by nursing duties are a main source of work-related musculoskeletal disorders among nursing staff. The purpose of this article is to describe the prevalence of work-related musculoskeletal disorders among critical care nurses, in two patient handling tasks, transferring and repositioning of patients, and assess their training level and acquaintance of ergonomics rules and principles in patients’ handling tasks.

Results of the study revealed a large number of nurses in intensive care unit exhibit musculoskeletal disorders symptoms. Nurses knowledge of safe patients handling technics are superficial and lacking basic human factors /ergonomics principles. The study recommended the immediate hiring of an adequate number of physically able nursing staff and providing the necessary work equipment to assist nurses perform patient handling tasks. In the near future, a human factors/ergonomics intervention program should be launched, incorporating a “Safe Patient Handling Training Program” for the critical care-unit staff.

Modelling of thermal processes that occur during laser welding of multi-component heat-resistant alloy thin-walled butt joints

2023-08-10T13:48:34+00:00

Niobium-based alloys is a rapidly developing group of heat-resistant alloys, used widely in many industries thanks to their performance in a high-temperature environments. This is achieved by many factors, including its chemical composition and phase structure, as well as high density and oxidation resistance at high temperatures. For these reasons, niobium-based alloys found a number of applications in various industries, such as medicine, engine manufacturing, as well as space industry. Modelling of laser welding processes is an extremely complex process due to the large number of dynamic parameters that must be selected individually for each configuration of the treated surfaces. Finite element modelling of the heat transfer analysis of the butt joint between Nb-15W-5Mo-1Zr alloy plates was performed at a 400 W laser radiation power. All models were made using COMSOL Multiphysics. The models take into account non-uniform movement at the beginning and end of the welding process, the Gaussian distribution of the heat flux along the radius of the laser spot, and the reflection coefficient, which depends on the temperature. Thin plates made of Nb-15W-5Mo-1Zr (F-48) alloy, due to their thermodynamic properties (such as a high initial cooling rate of 1.2-1.3 s), can be welded by selected laser processing modes. At the same time, it should be noted that the quality of the weld in this case must be ensured by a complex of auxiliary production processes aimed at preventing the possible failure of the part.

Designing the Decision Support System to Determine the Major and Higher Education Institution based on Preferences of Prospective Students

2023-10-20T02:27:06+00:00

There are several factors considered by students toward determining the major and higher education institution. As a result, determining the best choices for further studies becomes difficult. Moreover, there are many choices of higher education. This study contributes to developing a decision support system (DSS) to help students determine the major and higher education institution considered several criteria based on Analytical Hierarchy Process (AHP). Several criteria and subcriteria were chosen by distributing 186 questionnaires to final grade students. Based on the result, criteria and subcriteria used were tuition fee, scholarship, infrastructure (library, classroom, laboratory, transportation, teaching staff), curriculum, quality (accreditation, study period, achievement), reputation, and international collaboration. According to these criteria and sub-criteria, a DSS was built to help students determine their major and higher education institution according to their preferences. The algorithm used was AHP, which was then built with Borland Delphi. Context Diagram, Data Flow Diagram (DFD), and Entity Relationship Diagram (ERD) were made as a guide to design the DSS. This DSS was tested using black box test, beta test and compatibility test with manual calculations. The black box test showed that the DSS has performed the functions according to the design. Later, the beta test resulted in a correctness score of 20.4, reliability of 16.8, usability of 25.5, which means they were in the very good category and integrity of 3.4, which means good. Meanwhile, based on manual calculations, the DSS provides output in accordance with the results of manual calculations. Finaly, he DSS was proven to be used as a decision-making tool in determining the major and higher education institution for students.

Analysis of Productivity Measurement in CPO Production Using OMAX Method

2023-08-09T02:24:20+00:00

The primary focus of this research revolves around the measurement of productivity and the factors that impact Crude Palm Oil (CPO) production which currently faces challenges in assessing whether existing productivity falls into the 'satisfactory' category. The contribution of this study is conducting a comprehensive productivity assessment, focusing on metrics and identifying the causes of productivity decline, especially potential points of failure. The measurement indicators use the Objective Matrix (OMAX) method which includes five ratios, including raw material utilization, energy consumption, labor efficiency, optimization of production targets, and production capacity utilization. The Analytical Hierarchy Process (AHP) is used to assign relative weight to factors that contribute to overall productivity. In addition, Failure Modes and Effects Analysis (FMEA) functions as a tool to determine the causes of decreased productivity by considering the potential for failure to occur. The research results show that productivity reached its highest point in March at 219.93% and the lowest in July at -67.33%. Based on the score assessment, this decline was mainly caused by the lack of optimal achievement of production targets, symbolized by a ratio of 4 to a score of 45. Potential causes for this ratio include non-compliance in selecting FFB that meets standards, and production standards that are too ambitious. targets, and mental and physical fatigue and stress. To improve overall performance, proposed improvements include the application of Internet of Things (IoT) technology, such as the use of sensors and automation systems in production processes, as well as investment in agricultural technology as a monitoring system. This increase is aimed at achieving higher production targets and overall efficiency.

Patient Experience Management as a Tool for Internationalization in Fundación Cardiovascular de Colombia

2023-10-20T03:47:10+00:00

Medical tourism, also known as healthcare tourism or medical travel, refers to traveling to a foreign country to receive medical treatment. Medical tourism has recently become increasingly popular, with millions traveling abroad for healthcare services yearly. However, medical tourism is not without its challenges. Patients must carefully research and select healthcare providers and facilities, considering factors such as accreditation, quality of care, and patient safety. Patients may also face cultural and language barriers when seeking treatment in a foreign country. The present work aims to establish the bases and knowledge to determine the importance of patient satisfaction as a factor of competitiveness. This work presents a study case centralized in the institutions providing health services (IPS in Spanish): Cardiovascular Foundation of Colombia (FCV) and a detailed analysis of the internationalization processes established by the Cardiovascular Foundation. For this, each of the processes was categorized and detailed in such a way that it would allow identifying which are the determining factors in the patient's experience and how to improve them. Each proposed strategy consists of a theoretical framework of the topic to be developed, objectives, approach, methodology, and development. Finally, the results obtained are the product of the analysis of surveys applied to the objective users, theoretical verifications, interviews, and work groups with directors of the Cardiovascular Foundation of Colombia

Determining The Optimal Milk Distribution Route Using The Ant Colony Optimization Method on Milk Industry

2023-03-21T07:08:47+00:00

A good distribution system will ensure the availability of products or goods needed by the community. The objective of this research is to identify the most efficient route for distributing UHT milk on Milk Industry, with the goal of minimizing the overall distance traveled during distribution. The contribution of this study is to determine the optimal distribution route for UHT milk on Milk Industry. Data analysis or data calculation is done using Ant Colony optimization. The independent variables used are the initial distribution route data of the company, agent location data, product demand data, and distance data between agents. The results of this study found that the company's route resulted in a total route distance of 251.95 km while for the optimal total distance Ant Colony Optimization method is the total route distance of 230.2 km. Thus, the optimal route of the distribution of Ant Colony Optimization method is better than the initial route of the company with a total route distance savings of 21.75 km with a percentage of savings of 8.63%.