A multidimensional data descriptor tool based on fuzzy min max neural network algorithm

The purpose of this project is to introduce different techniques and methods that have been used before to analyze the data. The main objective is to build an data analytic tool for a multidimensional dataset. In this project, the technique that will be used is Fuzzy Min Max method. By using this method, the data visualization will displaying the minimum and maximum value in range of zero to one. In this project, it will be compare a few techniques and determine which techniques is the most suitable. The techniques is in the Neural Network which has a few popular techniques such as K-Nearest Neighbour Fuzzy Min Max, general Reflex Fuzzy Min Max to get some idea of methodologies, algorithm, techniques and concept of the whole existing project and research study. Besides that, in this paper, it will also compare three existing system such as Tableau Public, Qlikview and IBM InfoSphere Streams. They have been compare for their advantages and disadvantages. The implementation of Fuzzy Min Max Neural Network technique has been applied using Matlab Programming. Therefore, in this project, it will explain more about why I am using the Fuzzy Min Max method rather than other methods

Mobile Learning Adoption: A perspective from a Form Six Students in Sabah, Malaysia

Despite the availability of studies on mobile learning adoption, its theoretical foundations have not yet matured. However, studies on mobile learning adoption in the context of form six student in Malaysia is still very limited. Against this concern, a study was conducted with the aim of investigating factors that could influence the adoption of mobile learning. Based on The Unified Theory of Acceptance and Use of Technology (UTAUT) and two other variables which are Perceived Playfulness and Self-Directed Learning, an empirical structured has been developed to identify predictors of mobile learning. A self-administered questionnaire was adopted and a total of 314 responses were employed for the analysis, using Structural Equation Modelling (SEM). The findings of the analysis revealed that all key constructs (except social influence) affect mobile learning adoption among form six students. Besides that, Self-Directed Learning become the strongest predictor and followed by Effort Expectancy. These findings provide crucial implications for educators and practitioners to take individual characteristic (Self-Directed Learning) into consideration while promoting mobile learning. This study represents one of the few attempts to reveal the extended UTAUT model could be increased explanation power of technology acceptance by the users. Directions for future study are suggested at the end of the paper

Physical and mechanical properties of kenaf/seaweed reinforced polypropylene composite

Wood plastics composites (WPCs) refer to any composites that consist of natural fibers combined with thermosets or thermoplastics polymers. Natural fibers are preferably used as reinforcement in WPCs due to their availability, low cost, and low density. Currently, kenaf fiber has been used widely in making composite while seaweed is more used in cosmetics and food. In this study, kenaf fiber and seaweed fiber is mixed with different ratio. This study aims to investigate the potential of kenaf/seaweed to be converted into WPCs and the physical and mechanical properties of kenaf/seaweed reinforced polypropylene composite were figured out. The techniques used for making this composite are using extrusion and hot-pressing techniques. Kenaf reinforced composite and seaweed reinforced composite are prepared as a control sample in the research. The result shows that the tensile and impact strength of kenaf/seaweed reinforced composite is low compared to kenaf reinforced composite but higher than seaweed reinforced composite with a value of 0.1098 MPa and 49.53 J/m respectively. Melt flow index (MFI) result was displayed through the rate of flow of composite under two different loads at 120 kg and 216 kg at temperature 1900C. The rate of flow was affected by the increment of viscosity. It is shown that adding fiber into composite results in an increase in MFI index. The amount of water absorption of kenaf/seaweed reinforced polypropylene composite was lower than kenaf composite but higher than seaweed composite. It is shown that seaweed improved the properties of kenaf/polypropylene reinforced composite in terms of water absorption properties but lower in mechanical properties

Reliability Of Clinical Indicators In Nursing Diagnosis: Acute Pain

Background: Determine accurate nursing diagnosis based on patient’s data is the one of nurse’s responsibility. Patient’s response in nursing field called clinical indicator. Reliability of clinical indicator research is important to be conducted to help nurse determine accurate nursing diagnosis.Purpose: The aim of this study is to investigate inter-rater reliability score of clinical indicators in nursing diagnosis: acute pain.Methods: Respondents of this study is patients undertaking hemodialysis. Two raters assess 30 respondents with instruments based on clinical indicators of acute pain according NANDA-I taxonomy. The data analyzes use Cohen’s Kappa.Results: Ten items of clinical indicator in nursing diagnosis: acute pain was unreliable or low reliability score (<0,40). Otherwise, the number of items with moderate reliability score (0,41-0,60) and high reliability score (0,61-1,00) was 13 items.Conclusions: More than 50% items of indicator in nursing diagnosis: acute pain had moderate and high reliability score.Keywords: Clinical Indicators, Inter-Rater Reliability, Nursing Diagnosis, Pai

PAIN CHARACTERISTICS ON PATIENT UNDERTAKING HEMODYALISIS

Background: Research in pain especially in patient undertake hemodialysis is important to be conducted in order to help this population in the process of their hemodialysis therapy. Aim: The aim this study is to identify pain characteristic on hemodialysis patient using Visual Analogue Scale (VAS) and mnemonic PQRST. Method: This is a descriptive quantitative cross-sectional research. The number of respondent were 72 and they routinely undertake hemodialysis therapy twice a week. Research was conducted in one Central Hospital in Yogyakarta, Indonesia on February to March 2017. Univariate analysis was used to describe respondents’s pain characteristic. Results:The majority of respondents (51.39%) experience moderate pain, following by mild pain (33.33%) and severe pain (15.28%). In Provocation aspect the most characteristic was movement (87.50%), for the Quality characteristic the most aspect was knife-like pain (83.33%). Moreover, in Regio characteristic was on hand (84.72%), No Radiation of pain (91.67%), and for Time characteristic was intermitten (97.22%). As many as 53% respondents expressed that pain have an impact on their life. Consequences of pain most was in their activities (52.63%), following with others (15.79%.), nausea/vomiting (15.79%), sleep disturbance and appetite (both 13.16%). However, pain did not have an impact on their emotion. Conclusion: Respondents experience mostly moderate pain. The percentage of characteristics on PQRST mnenomic each percentage of Provocation, Quality, Regio, Radiation and Time reach was above 80% of respondents, while for Severity more than half of the respondent experienced moderate pain. The majority of respondents felt the impact of pain in their life