Universiti Teknikal Malaysia Melaka: UTeM Open Journal System
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Analysis on C++ Topic Difficulties Ranking: A Case Study on Mechanical Engineering Students in UiTM Pasir Gudang
Full text linkThe aim of this paper is to analyse student’s performance obtained from the course “Fundamentals of Computer Problem Solving” (CSC128) final examination results. This is a C++ programming course and it is a mandatory subject for all Diploma in Mechanical Engineering and Diploma in Civil Engineering students at Universiti Teknologi MARA Pasir Gudang Campus. Through the analysis, this paper identify which topics in CSC128 is not being well mastered by the students. The data was collected from 163 students score marks and the analysis was conducted by categorizing the final examination questions into five different topics according to CSC128 syllabus. An indicator has been used to classify students’ performance for each topic by comparing the percentage of students who scored 50% above and below of total marks for every topic. The study identified that Topic 4, “Repetition Control Structure” was placed in the first rank as the most difficult topic encountered by the students and Topic 3, “Selection Control Structure” was ranked as the least difficult topic. The findings will be used to improve the subject in order to achieve the course outcomes and can be a guideline for the lecturers to improve their teaching method in order to increase students’ understanding, interest and performance in programming
TRAFFIC LIGHT ARROW SHAPE RECOGNITION USING HOG DESCRIPTORS AND SVM CLASSIFIER
No full textAbstract – Autonomous intelligent vehicles are keep expanding under a real development in this era after many researches have been made to implement a better safety features in a transportation sector. In this paper, an algorithm of recognition of the traffic light arrow in the daytime specifically for the operation of the video system has been proposed using the technology of the image processing and machine learning. In the machine learning technique, the Support Vector Machine, SVM classifier has been used for the learning process and conduct a classification process as well. Firstly, the images are converted to Hue Saturation Value (HSV) color space while the color thresholding has been used to obtain the region of interest for the traffic light arrow in the image. In the learning process, each of the traffic light arrows in the dataset will go through the pre-processing phase, detection phase before going through the hog descriptor for feature extraction purpose. Prior to send the image to the SVM, the hog descriptor process is to extract the features for each of the shape of the traffic light arrow. As a result, this algorithm has achieved 98.52% accuracy, 1.48% error, 98.52% precision and 98.68% of recall through the testing process
PARAMETER EXTRACTION OF PV CELL SINGLE DIODE MODEL USING ANIMAL MIGRATION OPTIMIZATION
No full textPhotovoltaic cell model is designed to induce nonlinear current versus voltage (I-V) curves. Due to its nonlinearity, the model parameters cannot be obtained by the use of standard measurement tools. As a consequence, the optimization procedure usually carried out to accomplish this aim. Among many PV cell models, the single diode model (SDM), consisting of a single diode with shunt and series resistance, has become a common simulation option. There are five parameters to be extracted in this model. These are photo-generated current, diode saturation current, series resistance, shunt resistance and diode ideality factor. In this paper, the Animal Migration Optimization (AMO) algorithm has been proposed to extract these parameters. Standard measurement data from the R.T.C France silicon cell is taken as a test bench. The results of AMO contrast with the state-of-the-art algorithm for further verification. As a conclusion, the AMO produced quick, reliable and accurate results. However, further improvement of the exploitation capability is required in order to achieve outstanding performance
IOT Based Approach On Aquarium Monitoring System With Fish Feeder Automation
Full text linkAbstract— The monitoring system is known to be very useful for alleviating human activities and can been utilized in many ways. The idea to automate the monitoring system originated from a couple of problems. The time consuming process for manually checking and measuring every parameter at every part in an aquarium is one of the problem. The second problem is the lack of availability of time to keep the aquarium meeting the mandatory fish needs that need to be reviewed regularly. Along with these there are known that important parameters such as condition of pH water and the availability of food is essential to keep the habitat conducive for living. Therefore this paper proposed an aquarium monitoring system utilizing Internet of Thing (IoT) with automatic fish feeder. With the existence of IoT system, user can be continuously notified in real time. The monitoring system is utilized as a platform to remind the user to clean or filling food in the feeder when necessary. The system also equipped with automatic feeder fulfilling the fish mandatory needs. The result showed that the developed system able to display the current conditions of pH water value and the level of the fish food through Blynk application. This user friendly and compact fish tank design can be implemented almost anywhere
Efficient and Secure Data Transmission Approach in Cloud-MANET-IoT Integrated Framework
Full text linkThe Internet of Things (IoT) devices have the capabilities to interact and communicate in 5G heterogeneous networks. They also have the capabilities to form a network with neighborhood devices without a centralized approach. This network is called the mobile ad hoc network (MANET). Through an infrastructure-less system of the Internet of Things environment, the MANET enables IoT nodes to interact with one another. Those IoT nodes could interactively connect, communicate as well as share knowledge between several nodes. The role of cloud throughout this structure is to store as well as interpret information through IoT nodes. The communication security has been introduced as one of the techniques to solve the data transmission security issue that could result in increased performance in cloud consumption and ubiquity. The purpose of this research is to establish a communication system among IoT nodes in an embedded Cloud and MANET structure. Aiming to create an efficient and secure approach for communication in Cloud-MANET-IoT integrated framework, this approach has been implemented and tested
EFFECT OF LOAD AND TEMPERATURE ON FRICTION USING BANANA PEEL BLENDED WITH PARAFFIN OIL UNDER HIGH LOADING CAPACITY
Full text link Increased severity in operating conditions coupled with the environmental and toxicity issues related with using conventional lubricants. In addition, high price of fossil fuels has led to exploration of new kind natural additives as bio-lubricant. Banana Peel as agricultural wastes are potential to be developed as bio-oils that to replace the petroleum products, due to their environmentally friendly characteristics, biodegradable, nontoxic and renewable. The purpose of this study is to produce lubricant oil from Banana Peel (BP) as bio additives in paraffin oil, as well as to determine their physical and tribological properties as bio-lubricant under severe operation conditions to identify their ability for lubricants. Tribological performance of Banana Peel (BP) as a bio-lubricant was tested using four-ball test machined under extreme pressure conditions, according to ASTM D 2783-03. Experimental results showed significant improvement in overall performance with increased BP content compared with paraffin oil (PO) through Coefficient of Friction parameter (COF) at 100 ˚C, lower value of COF which 0.086 for 50 %BP followed by 20% BP, 5% BP and 100 %PO at values 0.089, 0.456 and 0.595 respectively. As results, banana peel as Extreme Pressure and Anti-Wear additives has been proven itself able for use in lubrication applications for gear and engine oils
Bibliometric Analysis Of Agile Software Development
Full text linkAgile methodologies are currently considered one of the main paradigms of software development. Its study, from a scientific point of view, has deserved prominence in recent years by the scientific community related to the area of software engineering. This study intends to perform a bibliometric analysis of the quantity, characteristics and scope of the most relevant studies published in this area of knowledge. The findings indicate that the number of studies published from 2010 to 2016 significantly increased, having reached a peak in 2015. The study identifies the main journals and conferences in the field and we also concluded that the majority of published studies are literature reviews of agile software development, and qualitative and quantitative research methods have identical number of publications
An investigation of the relationship between Service Quality and Customer Satisfaction in Melaka Bookstore
Full text linkCustomer satisfaction is a significant factor in influencing the service sector’s revenue. In this competitive environment which full of advance technologies, delivering a high quality of service is a factor for a stable competitive advantage. Customer satisfaction has a beneficial impact on the profitability of an organization. Service quality will reflect the customer's satisfaction in dimension of tangibles, reliability, assurances, empathy and responsiveness. Although there are many researches about SERVQUAL Model, but there are not much academic evidence measuring customer satisfaction in the bookstore services. Therefore, this research attempts to describe the relationship of service quality and customer satisfaction in the business-to-consumer (B2C). Business to Consumer or B2C is used by businesses that intend to market the products or services to consumers. B2C will conduct directly that business with customers without middleman. Data collection covers 15 bookstores in Melaka state. This research will focusing on selected bookstores such as Popular bookstore, MPH bookstore, TS Commerce bookstore, Kedai Buku Pintar Sdn Bhd and other bookstores that situated in the area of Melaka Tengah. The 151 survey questionnaires received and analyzed using SPSS software. Based on the regression analysis, onlytwo variables from five variables are significant. The two significant variables are reliability and empathy but have positive relationship with customer satisfaction
Demonstration of Palm Vein Pattern Biometric Recognition by Machine Learning
Full text linkThis paper aims to demonstrate the extraction of palm vein pattern features by local binary pattern (LBP) and its different recognition rate by two types of classification methods. The first classification method is by K-nearest neighbour (KNN) while the second method is support vector machine (SVM). Whilst SVM is optimized for direct classification between two classes, the KNN is best for multi-class classification. Based on the biometric recognition framework shared in this paper, both techniques shared comparable performance in terms of the recognition rate. The difference in the recognition rate can only be seen if the LBP features extracted for the classification are different. In general, higher recognition rate can be achieved for palm vein pattern biometric system if all LBP bins are used for the classification, compared to if only selected features are used for the purpose. Best recognition rate that can be achieved by the three datasets demonstrated in this paper are 60%, 70% and 100% respectively for the CASIA, PolyU and self-dataset
Oil Palm Fruit Image Ripeness Classification with Computer Vision using Deep Learning and Visual Attention
Full text linkOil palm is one of the leading agricultural industries, especially in the South East Asian region. However, oil palm fruit ripeness classification based on computer vision has not gained many satisfactory results. Therefore, most of the ripeness sorting processes are still done manually by labor works. The objective of this research is to develop a model using a residual-based attention mechanism that could recognize the small detail differences between images. Thus, the model could classify oil palm fruit ripeness better. The dataset consists of 400 images with seven levels of ripeness. Since the number of images in the dataset, Ten Crop preprocessing is utilized to augment the data. The experiment showed that the proposed model ResAtt DenseNet model, which uses residual visual attention could improve the F1 Score by 1.1% compared to the highest F1 Score from other models in the experiment of this study