Automated study plan generator using rule-based and knapsack problem

Undergraduate students are given the flexibility of arranging courses throughout their study duration especially when they are eligible for credit exemption for the courses taken during their diploma study. Issues arise when students arrange their studies manually. Improper course arrangement in the study plan may be resulting some of the selected courses do not correspond to the courses offered, and imbalance credit hours. Hence, this study aims to propose an algorithm to generate an automated and accurate study plan throughout the study duration. A combination of rule-based and knapsack problem were proposed to generate an automated study plan. A quantitative methodology through expert’s reviews and questionnaire survey was conducted to evaluate the accuracy of the proposed algorithm. The proposed algorithm shows high accuracy. In conclusion, the combination of rule-based and knapsack problem is appropriate to generate an automated and accurate study plan. The automated study plan generator can help students generate an effective study plan

Antecedents Of Safe Use Of Hospital Information Systems Based On Sociotechnical Perspective

Hospital Information System (HIS) could potentially improve the quality of healthcare services and patient safety. Nevertheless, there is a number of growing evidence that show HIS can pose risk to patient safety when it is poorly designed, implemented, or adopted. Most of the preventive solutions have been focusing on improving the software design. Conversely, patient safety is not merely dependent upon HIS, but also influenced by its interactions with users, other technologies, and environment. Therefore, this research proposes a conceptual model for a safe use of HIS by considering the sociotechnical aspect. Exploratory mixed methods methodology was employed. The first phase involved qualitative exploration of the safe use of HIS and its antecedents. Interview transcripts from 31 medical doctors at three Malaysian government hospitals implementing Total Hospital Information System (THIS) were collected. A quantitative data collection followed as the second phase to evaluate the research model. A total of 450 medical doctors from the three hospitals participated in the questionnaire survey. Structural Equation Modelling (SEM) was used for quantitative data analysis. The findings showed that knowledge, system quality, and team work has a significant direct effect on vigilance, while task stressor has a significant direct effect on procedure compliance. Teamwork emerged as the most important factor in determining the safe use of HIS. In addition, vigilance has a significant direct effect on both patient safety and patient care quality, whereas procedure compliance has significant direct effect on patient safety. Besides that, vigilance mediates the effect of knowledge, system quality, and teamwork on patient care quality. Procedure compliance mediates the effect of task stressor on patient safety. The model has portrayed predictive capability and predictive relevance, implying that the model could effectively explain the safe use of HIS and its outcomes. Hence, this research concludes that healthcare organisations and practitioners should give attention to the sociotechnical aspect of the safe use of HIS antecedents in reducing error, as well as increasing the quality of patient care

Hospital Information Systems (HIS) In The Examination Rooms And Wards:Doctors Perceived Positive Impact On Quality Of Care And Patient Safety

Hospital Information Systems [HIS] is developed to support healthcare organizations in providing efficient, quality,and safe healthcare services.The objective of this study is to identify and describe doctors’ perspective on the impact of HIS use in the examination rooms and wards on quality of care and patient safety. Semi-structured interviews were carried out with thirty one doctors from three Malaysian government hospitals. Thematic qualitative analysis was performed by using ATLAS.ti to deduce the relevant themes.HIS were commonly believed to improve quality of care and patient safety in terms of :[1] accessibility of patients’ record,[2] efficient patient-care,[3] well-structured report viewing,[4] less missing patients’ records,[5]legibility of patients’ records,and [6] safety features.In conclusion,the use of HIS in examination rooms and wards suggests to improve the quality of care and patient safety

A Review On Electronic Personalized Health Records

In accordance with the current information communication technology growth up in widely used at everywhere. Therefore the implementation in ICT is highly assisted patient on their health.As the current technology can be access at everywhere in anytime,the electronic personalized health records are considered as the best solution for the patient to care and monitor their health.This research paper provides a cross review of relevant literature from the previous study in order to clarify the rationality.Its continue with reviewing, comparing and contrasting the existing studies in order to obtain the factors that influence the adoption of electronic personalized health records.A summary that clarifies the relation each factor has been mentioned serve as the foundation for this empirical analysis.In addition,a logical justification is provided concerning the theory based meta-analysis from other studies

Developing lung cancer post-diagnosis system using pervasive data analytic framework

The data from lung cancer patients using wearable sensors and clinical assessments after observation is available to predict the disease’s recurrence. In recurrence prediction, pervasive data analysis is required to prevent flaws in clinical correlations and data observations. This article proposes a Pervasive Data Analytical Framework (PDAF) for recurrence prediction. The proposed framework incorporates three processes: data segregation using Butterfly Optimisation, feature correlation using Jaya Optimisation, and autoencoder prediction. First, the data from the wearable sensor is segregated using observation count for its availability and discreteness. It prevents missing errors under different observation sequences for which the correlation rate is determined using the next optimization. In the Jaya optimization process, the features correlate with the clinical assessments to improve precision. The autoencoder predicts the occurrence of previous missing and non-correlated inputs for maximizing the detection rate. Using the proposed framework, the maximum gains of 9.22% in accuracy, 9.29% in detection, and 7.96% in recommendations

Application development with J2ME for mobile phone

With mobile commerce technology continuously being taken more into use and introduced in new markets, the transition to mobile commerce (m-commerce) will make mobile shopping exceedingly popular. In the near future mobile shopping will probably replace today's markets or shopping complex. This project presents a mobile application which is built using Mobile Information Device Profile (MIDP) of the Java 2 Platform Micro Edition (J2ME), that enable users to purchase flowers without a trip to the market or elsewhere. Users can access the application or service through mobile phones and view the available items. The application has been deployed and run on an emulator (Wireless Toolkit 2.5 Beta) with a DefaultColorPhone as the default emulator

Design of Low Cost Greenhouse Monitoring using ZigBee Technology

Greenhouses are often used for growing flowers, vegetables, fruits, and tobacco plants. Most greenhouse systems still use the manual system in monitoring the temperature and humidity in the greenhouse, a lot of problems can occur not for worker but also affected production rate because the temperature and humidity of the greenhouse must be constantly monitored to ensure optimal conditions. The Wireless Sensor Network (WSN) can be used to gather the data from point to point to trace down the local climate parameters in different parts of the big greenhouse to make the greenhouse automation system work properly. This paper presents the design of low cost greenhouse monitoring system to monitor a greenhouse temperature and humidity parameters by applying the ZigBee technology as the WSN system. During the design process, Peripheral Interface Controller (PIC), LCD Display and Zigbee as the main hardware components is used as hardware components while C compiler and MP Lab IDE were used for software elements. The data from the greenhouse was measured by the sensor then the data will be displayed on the LCD screen on the receiver which support up to 100 m range. By using this system, the process of monitoring is easier and it also cheaper for installation and maintenance. The feasibility of the developed node was tested by deploying a simple sensor network into the Agriculture Department of Melaka Tengah greenhouse in Malaysia

Factors influencing patients' adoption and use of mobile health applications for diabetes selfmanagement : A systematic review

Mobile health (mHealth) apps can facilitate diabetes self-management (DSM) and assist in reducing the risk of complications, enhancing diabetes control and improving patient outcomes. The objectives of this systematic review were to (1) determine the adoption level of DSM apps among diabetes patients, (2) identify the factors associated with the adoption and use of DSM apps, and (3) explore patients’ perspectives of DSM apps and the predominant preferred features. A comprehensive literature search was performed in four electronic databases: PubMed, Scopus, PsychNet, and IEEE Xplore digital library using the PRISMA guidelines. Relevant data and information were collected from studies published between 2016 and 2023, fulfilling the inclusion criteria (n = 26), and thematic analysis was performed. The adoption level of mHealth apps for DSM among diabetic patients ranged from 7.0% to 47.0%, and diverse factors relating to patients’ demographics, preferences and experiences were identified. Overall, older, male and less educated patients were less likely to adopt DSM apps, while the intention to use these apps was influenced by patients’ perceived benefits, recommendations by patients and healthcare professionals, and ease of use. Given that most of the reviewed studies were conducted in developed countries, the present patients’ adoption level of mHealth apps for DSM is relatively low, thereby highlighting the need for improvement. The factors identified in this study may be considered when attempting to encourage patients to use these apps. More research is needed to elucidate how mobile health apps can be effectively integrated into diabetes care and management pathways

Analysis Of Texture Features For Wood Defect Classification

Selecting important features in classifying wood defects remains a challenging issue to the automated visual inspection domain. This study aims to address the extraction and analysis of features based on statistical texture on images of wood defects. A series of procedures including feature extraction using the Grey Level Dependence Matrix (GLDM) and feature analysis were executed in order to investigate the appropriate displacement and quantisation parameters that could significantly classify wood defects. Samples were taken from the Kembang Semangkuk (KSK), Meranti and Merbau wood species. Findings from visual analysis and classification accuracy measures suggest that the feature set with the displacement parameter, d=2, and quantisation level, q=128, shows the highest classification accuracy. However, to achieve less computational cost, the feature set with quantisation level, q=32, shows acceptable performance in terms of classification accurac

Socio-technical factors influencing big data analytics adoption in healthcare

The purpose of this study is to determine the key socio-technical factors influencing big data analytics adoption in healthcare services. A systematic literature review was conducted using peer-reviewed scholarly publications spanning from 2013 to 2023 to illuminate the influencing factors. Twelve papers focused on the factors influencing big data analytics (BDA) adoption in healthcare services were included for review. The factors were divided into four major groups namely i) person, ii) technology, iii) organization, and iv) environment. Analytical skills define a person, whereas technology is characterized by system quality and information quality. Organization support, organization resources, training, data governance, and evidence-based decision-making are all associated with the organization. Finally, government regulations are allocated to the environment. This review presents evidence of the socio-technical factors that influence big data analytics adoption in healthcare services. The findings from this review recommend future big data analytics adoption in healthcare services to carefully evaluate the factors identified in this study