Hierarchical Fuzzy Systems: Interpretability and Complexity

Hierarchical fuzzy systems (HFSs) have been regarded as a useful solution for overcoming the major issues in fuzzy logic systems (FLSs), i.e., rule explosion due to the increase in the number of input variables. In HFS, the standard FLS are reformed into a low-dimensional FLS subsystem network. Moreover, the rules in HFS usually have antecedents with fewer variables than the rules in standard FLS with equivalent functions, because the number of input variables in each subsystem is less. Consequently, HFSs manage to decrease rule explosion, which minimises complexity and improves model interpretability. Nevertheless, the issues related to the question of “Does the complexity reduction of HFSs that have multiple subsystems, layers and different topologies really improve their interpretability?” are not clear and persist. In this paper, a comparison focusing on interpretability and complexity is made between two HFS’ topologies: parallel and serial. A detailed measurement of the interpretability and complexity with different configurations for both topologies is provided. This comparative study aims to examine the correlation between interpretability and complexity in HFS

Designing an IoT-based System to Detect the Out-of-pitch Balls in a Football Match

The incorrect decision making that referee made during a football match is becoming unsatisfied game or biased game. The problem of how a decision made by the referee when coming to an error in football had been issues that being debate. The player or fans did not seem satisfied when referee decide such as a goal or no goal, penalty or no penalty, direct red card, and mistaken identity. Hence, there must be a plan to tackle the problem by using technology, especially in this era. Therefore, as an initial approach, this paper is focusing on developing a design for the ball out detection using the assistants of the IoT (Internet of Things). Correctly, the IoT approach was used for detecting the ball out of play, i.e. from a football match. Note that this proposed design was built based on data obtained from a survey questionnaire conducted with the experts in football and fans of football regarding the ball out of play system. The evaluation of the proposed design suggested that the proposed design promising to improve the decision-making made in the football match.  It is hoped that the study can contribute to the improvement of overall decision making by the referee when coming to ball out or other error that player made

Utilising Target Adjacency Information for Multi-target Prediction

In this paper, we explored how information on the cost of misprediction can be used to train supervised learners for multi-target prediction (MTP). In particular, our work uses depression, anxiety and stress severity level prediction as the case study. MTP describes proposals which results require the concurrent prediction of multiple targets. There is an increasing number of practical applications that involve MTP. They include global weather forecasting, social network users’ interaction and the thriving of different species in a single habitat. Recent work in MTP suggests the utilization of “side information” to improve prediction performance. Side information has been used in other areas, such as recommender systems, information retrieval and computer vision. Existing side information includes matrices, rules, feature representations, etc. In this work, we review very recent work on MTP with side information and propose the use of knowledge on the cost of incorrect prediction as side information. We apply this notion in predicting depression, anxiety and stress of 270,322 anonymous respondents to the DASS-21 psychometric scale in Malaysia. Predicting depression, anxiety and stress based on the DASS-21 fit an MTP problem. Often, a patient experiences anxiety as well as depression at the same time. This is not unusual since it has been discovered that both tend to co-exist at different degrees depending on a patient’s experience. By using existing machine learning algorithms to predict the severity levels of each category (i.e., depression, anxiety and stress), the result shows improved precision with the use of cost matrix as side information in MTP

Design and Development of Mobile Application for Parking Reservation System

Every emerging country face the issue of public parking congestion in the urban area. Ignoring the issue would breed a series of problems; from traffic disruption to violating the laws related to traffic. In Malaysia, the City Council has made an effort to mitigate the problem by using a coupon - which largely handled manually by the user by purchasing and paying the coupon through a machine. However, the procedure of using a coupon is considered inefficient due to challenges such as; extensive time, coupon exploitation and material waste. Therefore, to mitigate the problem surfaced in the current procedure, a mobile application is developed to handle the parking reservation process. The reservation process included the function to view the parking's availability thus presented the user the advantage of reserving parking earlier in the case of parking usage are at the peak. This paper highlighted the requirement identification and design and development phases

Adaptation of .NET MVC Framework in Developing an Agriculture Sources Inventory System

A viable inventory management system is crucial to an organization, especially those who deals with stock going in and out of their premise. The system should cover several aspects in managing the collection of the available stocks to ensure an efficiency. An inventory management system comprises crucial functions that the goal is to produce accurate information – a minor mis-information could lead to a wrong decision making. Improper system design could lead to the problem; thus, the design of this inventory system is supported by .NET Model View Controller (MVC) Framework as its backbone. The .NET MVC Framework is one of the most widely used framework that is written in C# programming language. By utilizing the MVC Framework, its three main components; data model (Model), user interface (View), and business logic (Controller) can be managed separately without affecting the entire system. Thus, the risk of the system functions to produce inaccurate information is reduced significantly. Moreover, MVC also supports scalability, extend-ability and maintainability which is a very important aspect for an information system with growing needs of new functions

Towards Designing A Hierarchical Fuzzy System for Early Diagnosis of Heart Disease

Heart disease may represent a range of conditions that affect our heart. Disease under heart diseases umbrella include coronary heart disease, heart attack, congestive heart failure, and congenital heart disease, is the leading cause of death. Mor eover, heart disease not only attacks the elderly. In the present day, lots of younger people might be getting affected by the number of heart diseases. In order to decrease the mortality rate caused by heart disease, it is necessary for the disease, to be diagnosed at an early stage. In this paper, we have proposed the use of hierarchical fuzzy systems (HFSs) for early diagnosis of heart disease. However, to design the HFSs is challenging, especially for the complex system. Therefore, in this paper, we foc us on designing a hierarchical fuzzy system to handle the complex medical application. The designed HFS consists of six key main steps implemented on heart disease. The input variables of heart disease includes shortness of breath, discomfort, pressure, he aviness, or pain in the chest, arm, or below the breastbone, fatigue, nausea, difficulties in climbing stairs, swelling in ankles, difficulty to sleep at night, irregular heartbeats, fullness, sweating, take frequent break during the day, dizzy and depress ed. Additionally, the output of heart disease is to classify whether the patient is healthy or suspecting with heart disease. The study contributes to providing insight into a way of designing the HFSs, particularly for the complex medical application

My-Wakaf: A Waqf of Property Management Application

In almost every Islamic country, the number of waqf properties is increasing at an exponential rate. As a result, managing such abundant amount of waqf properties can be very tedious and challenging. In Malaysia, waqf properties is managed by respective State Islamic Religious Council and are still using traditional method of recording all waqf asset. As a result, the My-Wakaf prototype mobile application was created to aid with the workload of managing waqf assets or properties. The methodology used for the project is the Waterfall model that is based on the original System Development Life Cycle (SDLC) that have 5 phases which are Planning, Design, Development, Testing and Documentation phase. My-Wakaf application is developed using Android Studio and it is integrated with Firebase Cloud database to help store waqf assets information securely to be accessed anywhere, reducing the human errors and cost of managing such properties. According to a user acceptability test conducted on numerous responders, the majority of them were highly happy with the My-Wakaf application's general functionality. Finally, it is intended that My-Wakaf would help the Muslim community as a whole by increasing awareness of waqf knowledge and stimulating economic growth

iNutritionApp: Mobile Application for Nutrition Monitoring using FatSecret API

Mobile application is a software designed to run on smartphones, tablet computers, and other mobile devices. The growing millions of users who are using mobile applications have contributed to an increase in the development of the mobile applications for enterprises, education, the social network and healthcare. Widely used healthcare application nowadays includes general health and wellness, tele-medicine, personal coaching and consultation, medical record tracking, custom reminders and various health management apps. This paper presents a mobile application related to general health and wellness named as iNutritionApp for providing nutrient information, tracking nutrition and calorie intakes with the integration of FatSecret API. The API provides nutritional information based on type of food provided by user. The application was intended to overcome manual calorie intake calculations and assists diet plan. Development methodology of this mobile application utilizes three phases that are system requirements, system design and development, as well as testing. Technology acceptance model with three parts were conducted with 30 respondents by evaluating the developed mobile application through questionnaires. Results of the testing showed that perceived of usefulness (PU) part achieved highest mean score compared to perceived ease of use (PEOU) that include user interface design and navigation parts. Therefore, features and functionality offered by the iNutritionApp is proven to be useful for user in tracking calorie intakes and provide access to nutritional information