Internet of Things (IoT) Technology for the Development of Intelligent Decision Support Education Platform

Improving the intelligence of teaching environment and making the multimedia teaching equipment has become a major concern of the colleges and universities. To this end, the design of Internet of Things (IoT) technology based wisdom of higher education platform is of great interest. Designing the structure of online management platform for college education and realizing the functions of examination result inquiry, online teaching, and attendance management have gained more importance in the educational research. The wisdom classroom is the key structure of the wisdom education platform. A smart classroom architecture based on IoT technology is designed, which connects with traditional network facilities through the IoT gateway. Different layers of the architectures have been designed and implemented. The proposed platform tests results and shows that the intelligent education platform can effectively control classroom utilization and has high throughput, low application latency, and good practicability.

A Custom Sensor Network for Autonomous Water Quality Assessment in Fish Farms

The control of water quality is crucial to ensure the survival of fish in aquaculture production facilities. Today, the combination of sensors with communication technologies permits to monitor these crucial parameters in real-time, allowing to take fast management decisions. However, out-of-the-box solutions are expensive, due to the small market and the industrial nature of sensors, besides being little customizable. To solve this, the present work describes a low-cost hardware and software architecture developed to achieve the autonomous water quality assessment and management on a remote facility for fish conservation aquaculture within the framework of the Smart Comunidad Rural Digital (smartCRD) project. The developed sensor network has been working uninterruptedly since its installation (20 April 2021). It is based on open source technology and includes a central gateway for on-site data monitoring of water quality nodes as well as an online management platform for data visualization and sensor network configuration. Likewise, the system can detect autonomously water quality parameters outside configurable thresholds and deliver management alarms. The described architecture, besides low-cost, is highly customizable, compatible with other sensor network projects, machine-learning applications, and is capable of edge computing. Thus, it contributes to making open sensorization more accessible to real-world applications.

Development and Testing of a Roleplaying Gamification Module to Enhance Deeper Learning of Case Studies in an Accelerated Online Management Theory Course

Research has established that “cognitive rehearsal,” (CR) or the visualization of application of a behavioral response to a situation, can increase self-efficacy through vicarious experience, but is challenging to induce online. Online higher education curricula can include collaborative game-based learning (GBL) in the form or roleplaying, which can facilitate CR. The purpose of this study was to develop an online GBL module to facilitate CR in online business graduate students learning management theory case studies, and to evaluate its ability to induce CR. A convenience sample of students voluntarily participated in a proof-of-conduct study using a mixed-methods design to gauge whether use of the module facilitated CR, a descriptive and thematic analysis was conducted. Data were collected from 106 students within two course sections in an online Master of Business Administration (MBA) program. The module was used as an optional supplement to a management case study assignment and approximately 50% of students used it. Scores on the assignment were compared between students who used the module and students who did not, and those who did scored statistically significantly higher (p = 0.0003). Students reported in a survey that the module induced CR about applying management theory. Students also expressed satisfaction with the module and provided feedback for its improvement in the areas of format and content. Our findings suggest that collaborative roleplaying GBL and other methods to induce CR in online higher education should be explored and formally studied.

TechDoc - System for Queue Management of Pharmacies and Online Consultation of Doctors

A TechDoc system has been developed for online management of pharmacies and consultation of doctors and presented in this paper. TechDoc serves the purpose of queue management outside pharmacies, by providing a delivery system of online ordered medicines from registered pharmacies nearby to customers’ residence; checking of symptoms using the free symptom checker that can diagnose a large number of diseases and gives relevant details on remedies for the diagnosed disease along with a video for home remedies of the particular disease; booking an appointment with a physical practitioner through the doctor’s consultation section in case the user is unsatisfied with the home remedies generated by the system. All these facilities are implemented into a single platform – a website accessible by any device, an android application especially for android phones and an IVR system to be accessed by the users who don’t have access to high end devices or internet connection. This innovative implementation helps in easy availability of essential services like, ordering of medicines, provisional diagnosis of curable disease and consultation of doctors, online and promoting social distancing.

An Energy-Efficient Inference Method in Convolutional Neural Networks Based on Dynamic Adjustment of the Pruning Level

In this article, we present a low-energy inference method for convolutional neural networks in image classification applications. The lower energy consumption is achieved by using a highly pruned (lower-energy) network if the resulting network can provide a correct output. More specifically, the proposed inference method makes use of two pruned neural networks (NNs), namely mildly and aggressively pruned networks, which are both designed offline. In the system, a third NN makes use of the input data for the online selection of the appropriate pruned network. The third network, for its feature extraction, employs the same convolutional layers as those of the aggressively pruned NN, thereby reducing the overhead of the online management. There is some accuracy loss induced by the proposed method where, for a given level of accuracy, the energy gain of the proposed method is considerably larger than the case of employing any one pruning level. The proposed method is independent of both the pruning method and the network architecture. The efficacy of the proposed inference method is assessed on Eyeriss hardware accelerator platform for some of the state-of-the-art NN architectures. Our studies show that this method may provide, on average, 70% energy reduction compared to the original NN at the cost of about 3% accuracy loss on the CIFAR-10 dataset.

The Determinants of User Satisfaction of Engineering Maintenance System (EMESYS) in the Malaysian Army

Engineering Maintenance System (EMESYS) is the online Management Information System (MIS) on equipment maintenance performed by the Royal Electrical and Mechanical Engineers (REME) Corps including maintenance on vehicle, weapon, electronic and miscellaneous equipment. This study attempts to identify the determinants of user satisfaction in adopting the EMESYS based on an information system success model by De Lone and Mc Lean (2003). This study is important as it is the first empirical study focusing on the user satisfaction of EMESYS in the context of the Malaysian Army. The data were collected using online surveys from 309 EMESYS users. Standard multiple regressions was used to analyse the data gathered. The results of this study indicate that three of the hypothesis are supported and users’ satisfaction of EMESYS is influenced by the three dimensions, namely, system quality, information quality and IT infrastructure. EMESYS has been proven successful in transforming the tedious procedures involving multiple parties and documents to the process of a simple data entry to EMESYS.

Economic effect of corona pandemic on Saudi pro league football tournament (Applied in Saudi Pro League

The study aims to identify economic effects of Corona pandemic on Saudi football represented in SPL sector, and precautionary measures to reduce these effects on Saudi football. the researcher used the descriptive approach (survey studies), and the study sample was (75) academics specialists in sports administration and experts in the field of sports economics, and officials in the different sectors of SPL. There are negative effects of the Corona pandemic on the Saudi football sector, but also it has a positive impact that is to try to activate online management and virtual training, while the negative economic effects on players, administrators, clubs and the professional league’s revenues increase as the time of the pandemic continues. The Saudi footballer should have a plan to work online in case of natural disasters, and put a term in the contracts in the sports field In case of natural disasters that lead to the cancellation of a sporting event before its establishment, its postponement or non-completion, the method of termination of the contract shall be determined according to each case, with the activation of the role of online training in the association and sports clubs, and the activation of the role of electronic services.