othman mohd

COVID-19 Self-Monitoring Tool (COV-SMT) is the research developed to address multiple issues in monitoring quarantined individuals due to COVID-19 infection. As COVID-19 is still highly infectious despite the availability of vaccines, the implementation of contactless Internet of Things (IoT) technology should be encouraged to minimize the need for medical staff to perform daily health checks and thus prevent them from being directly infected during checking. This research aims to develop an effective method to monitor quarantined individuals regarding their vital signs, such as body temperature, heart rate, and oxygen level. A contactless self-monitoring tool integrated with a stages algorithm is developed to monitor these quarantined individuals with the help of IoT technology. It can provide a consistent platform for patients or users to transfer information or data through networks, including personalized healthcare domains. COV-SMT is an effective tool to streamlet the overall ...

Purpose – This paper seeks to discover the factors that influence the supervisor to give the punishment level to civil servant staff—the data being used is a questionnaire to several civil servants in public academic institutions. Methodology/approach – This research used computational tools to classify transgressions into punishment categories (light, medium, or severe) with the model using the data science technique based on the partial least square-structural equation modeling (PLS-SEM) approach. Findings – It was found that the model of civil servant discipline in Indonesia is based on 14 hypotheses from bootstrapping technique and by using data science technique to support the result analysis of PLS-SEM. Novelty/value – This research contributed to providing civil servant supervisors to understand factors that influence the discipline of their staff, so it can be used to determine the punishment categorization.

Moodle is an open-source Learning Management System (LMS) that is used widely around the world. Moodle is the most popular and most used learning management system because of its flexibility and open source. There are more than 68 millions Moodle users and more than 55, 000 Moodle systems are used with different purposes around the world. The vast numbers of Moodle user is due to the user friendliness of the system that caters the needs of learning and training for all people from any institutes or organizations. This study is conducted to prevent information security threats especially information integrity threats that happen in Olympia College Moodle. To achieve the goal of this study, there are two objectives that have been indentified, which is to scrutinize learning materials handling procedures that are currently implemented by Olympia College and the effects of those procedures towards information integrity in the Moodle. At the same time, this study also proposes some mitig...

In healthcare applications, numerous sensors and devices produce massive amounts of data which are the focus of critical tasks. Their management at the edge of the network can be done by Fog computing implementation. However, Fog Nodes suffer from lake of resources That could limit the time needed for final outcome/analytics. Fog Nodes could perform just a small number of tasks. A difficult decision concerns which tasks will perform locally by Fog Nodes. Each node should select such tasks carefully based on the current contextual information, for example, tasks’ priority, resource load, and resource availability. We suggest in this paper a Multi-Agent Fog Computing model for healthcare critical tasks management. The main role of the multi-agent system is mapping between three decision tables to optimize scheduling the critical tasks by assigning tasks with their priority, load in the network, and network resource availability. The first step is to decide whether a critical task can ...

The phenomenon of having an Open Data initiatives becomes pervasive in every country. In Malaysia, it started with Open Government Data Framework approach from The Malaysian Administrative Modernization and Management Planning Unit (MAMPU) and currently the initiative has been extended to the ministries and agencies level. In addition, it is important to implement Higher Education Open Data Framework as the agency plays a major role as contributors to support the needs of citizen in current and future education world. Every country has its own governance structure and open data policies. In implementing Open Data Initiatives, there are some rules need to be followed; principles and models. Three (3) countries have been reviewed relating to Higher Education Open Data which are United Kingdom (UK), Saudi Arabia and South Africa. These countries are chosen based on its country classification. UK presented as a developed country. Meanwhile South Africa and Saudi Arabia acted as develope...

An effort to minimize illegal logging by utilizing advanced technology such as Wireless Sensor Network (WSN) are highly required. WSN is a communication solution between remote sensors located in isolated wide forest areas. However, the WSN challenge in a remote and wide-area has the energy resources limitation. This research proposed a weights-based energy-efficient WSN data communication protocol with firefly synchronization, namely Firefly Synchronization Multi-hop Geographical Energy-Aware Routing (FSM-GEAR) Protocol. This protocol aimed to increase the network lifetime of each node by shortening the transmission distance. Firefly synchronization between sensors is conducted to reduce the data transmission waiting time. A weights-based approach in cluster head (CH) selection phases and energy consumption analysis are formulated according to the comparison between nearest distance to Gateway and the maximum residual energy of each node based on received signal strength indicator ...

In the last decade, the developments in healthcare technologies have been increasing progressively in practice. Healthcare applications such as ECG monitoring, heartbeat analysis, and blood pressure control connect with external servers in a manner called cloud computing. The emerging cloud paradigm offers different models, such as fog computing and edge computing, to enhance the performances of healthcare applications with minimum end-to-end delay in the network. However, many research challenges exist in the fog-cloud enabled network for healthcare applications. Therefore, in this paper, a Critical Healthcare Task Management (CHTM) model is proposed and implemented using an ECG dataset. We design a resource scheduling model among fog nodes at the fog level. A multi-agent system is proposed to provide the complete management of the network from the edge to the cloud. The proposed model overcomes the limitations of providing interoperability, resource sharing, scheduling, and dynami...

Moodle is an open-source Learning Management System (LMS) that is used widely around the world. Moodle is the most popular and most used learning management system because of its flexibility and open source. There are more than 68 millions Moodle users and more than 55, 000 Moodle systems are used with different purposes around the world. The vast numbers of Moodle user is due to the user friendliness of the system that caters the needs of learning and training for all people from any institutes or organizations. This study is conducted to prevent information security threats especially information integrity threats that happen in Olympia College Moodle. To achieve the goal of this study, there are two objectives that have been indentified, which is to scrutinize learning materials handling procedures that are currently implemented by Olympia College and the effects of those procedures towards information integrity in the Moodle. At the same time, this study also proposes some mitig...

Abstract Context: A fog computing architecture that is geographically distributed and to which a variety of heterogeneous devices are ubiquitously connected at the end of a network in order to provide collaboratively variable and flexible communication, computation, and storage services. Fog computing has many advantages and it is suited for the applications whereby real-time, high response time, and low latency are of the utmost importance, especially healthcare applications. Objectives: The aim of this study was to present a systematic literature review of the technologies for fog computing in the healthcare IoT systems field and analyze the previous. Providing motivation, limitations faced by researchers, and suggestions proposed to analysts for improving this essential research field. Methods: The investigations were systematically performed on fog computing in the healthcare field by all studies; furthermore, the four databases Web of Science (WoS), ScienceDirect, IEEE Xplore Digital Library, and Scopus from 2007 to 2017 were used to analyze their architecture, applications, and performance evaluation. Results: A total of 99 articles were selected on fog computing in healthcare applications with deferent methods and techniques depending on our inclusion and exclusion criteria. The taxonomy results were divided into three major classes; frameworks and models, systems (implemented or architecture), review and survey. Discussion: Fog computing is considered suitable for the applications that require real-time, low latency, and high response time, especially in healthcare applications. All these studies demonstrate that resource sharing provides low latency, better scalability, distributed processing, better security, fault tolerance, and privacy in order to present better fog infrastructure. Learned lessons: numerous lessons related to fog computing. Fog computing without a doubt decreased latency in contrast to cloud computing. Researchers show that simulation and experimental proportions ensure substantial reductions of latency is provided. Which it is very important for healthcare IoT systems due to real-time requirements. Conclusion: Research domains on fog computing in healthcare applications differ, yet they are equally important for the most parts. We conclude that this review will help accentuating research capabilities and consequently expanding and making extra research domains.

Mangrove forest is an important costal ecosystem in the t ropical and sub-tropical coastal reg ions. It is among the most productivity, ecologically, environ mentally and biologically diverse ecosystem in the world. With the improvement of remote sensing technology such as remote sensing images, it provides the alternative for better way of mangrove mapping because covered wider area of ground survey. Image classification is the impo rtant part of remote sensing, image analysis and pattern recognition. It is defined as the extraction o f d ifferentiated classes; land use and land cover categories fro m raw re mote sensing digital satellite data. One p ixel in the satellite image possibly covers more than one object on the ground, within -class variability, or other complex surface cover patterns that cannot be properly described by one class. A pixel in remote sensing images might represent a mixture of class covers, within-class variability, or other co mplex surface cover patterns...

This study aims to evaluate the effects of pixel aggregation on the radiometric properties of Landsat-8 satellite imagery. Two images of north-western Peninsular Malaysia (i.e. clear day and cloudy day) were selected for the study. The aggregated average method was used due to its simplicity and practicality. Paired sample t-test and similarity matrix analysis were performed to assess and evaluate the effects of aggregation to Landsat-8 radiometric properties. The results show that the higher the aggregation scale the lower the similarity to the original pixel value for all bands. However, pixel aggregation does not significantly change the radiometric properties of all bands in both images except for the infrared bands in the clear image.

The need for an automation system from a remote area cannot be separated from the role of the wireless sensor network. However, the battery consumption is still a problem that influences the lifetime of the system. This research focused on studying how to characterize the power consumption on each sensor node using multihop routing protocol in the illegal logging field, to get the prediction lifetime of the network. The system is designed by using six sensor nodes in a master-slave connection and implemented in a tree topology. Each sensor node is consisting of a sound sensor, vibration sensor, Xbee communication, current and voltage sensor, and Arduino nano. The system is tested using battery 10050 mAH with several scenarios to have calculated how long the battery lifetime can be predicted. The results stated that the master node on the network depleted the power of the battery faster than the slave node since the more slaves connected to the master, the more energy the battery consumes.

Nowadays, the need for wireless sensing applications is increasing. Along with the increased illegal cutting of logs in the forest, however, it requires the integration application to tackle the illegal logging and forest preservation. The wireless sensor network is a suitable network architecture for remotely monitoring or tracking applications in the environment. This paper proposed an integrated system that can identify and track the position of a moving cutting log. An Arduino Uno, Raspberry Pi 3 B+, sound sensor, accelerometer sensor, LoRa GPS HAT Shield, and Outdoor LoRa Gateway OLG01 performed the hardware monitoring and tracking of the proposed system. The network of STAR topology configuration between master and slaves is represented by the LoRa Network embedded with the sensors, as an architecture of the wireless sensor network. The system was examined the performance of the network and the tracking process. The result determined that the LoRa can detect and identify the o...

Nowadays, the need for wireless sensing applications is increasing. Along with the increased illegal cutting of logs in the forest, however, it requires the integration application to tackle the illegal logging and forest preservation. The wireless sensor network is a suitable network architecture for remotely monitoring or tracking applications in the environment. This paper proposed an integrated system that can identify and track the position of a moving cutting log. An Arduino Uno, Raspberry Pi 3 B+, sound sensor, accelerometer sensor, LoRa GPS HAT Shield, and Outdoor LoRa Gateway OLG01 performed the hardware monitoring and tracking of the proposed system. The network of STAR topology configuration between master and slaves is represented by the LoRa Network embedded with the sensors, as an architecture of the wireless sensor network. The system was examined the performance of the network and the tracking process. The result determined that the LoRa can detect and identify the o...