The phenomenon of internet and social media addiction has attracted the attention of many people. We have conducted a research to examine whether or not the phenomenon of addiction to the internet and social media is a scientific reality. Then, we follow up this research. About 2014 respondents have been surveyed. Pearson’s Product Moment and Cronbach's Alpha tests were conducted to find out whether or not all the questions on this survey questionnaire were valid and reliable. The Chi Square hypothesis test was put forward Helmert’s theory around 1960; Helmert was a German Mathematical Physicist who mainly studied the field of Geodesy, even though Ernst Abbe and Irenne Jules Bienayme had already discovered this Chi Square distribution. The results of the internet addiction survey showed that 74.68% of respondents were not addicted and the rest were addicted mildly, moderately and severely. For the social media addiction survey, 79.94% of respondents were not addicted and the rest were addicted. Variables affecting addiction are age, occupation, and education. Internet and social media addiction is mostly experienced by Generation Y and Z, while Generation X has less addiction. The results of the measurement of Internet and social media addiction include scientific reality and attention should be paid to it and steps should be taken in the context of prevention and recovery for those who are addicted. Prevention and recovery for those who are addicted can be done by involving three major components: family, community, and state.
To communicate with the ground station, nano satellite requires a communication system that serves in real time to regulate the procedure with ground station. One of the missions of nano satellites is the retrieval of telemetry data from sensors that transmitted using APRS technology (Automatic Packet Reporting System). We designed a prototype to monitor sensor by utilizing the APRS. Real-time sensor data was transmitted to monitor through radio using AX.25 protocol. On the transmitter side, an APRS Tracker integrated with a microprocessor ATMEGA 1284P to modulate the AFSK signal. The existence of this AFSK signal is used to transmit and receive telemetry data using handy talky. We use a computer with AGWPE software to demodulate the AFSK signal and UI-View32 to show the telemetry data. The results showed that the telemetry data can be displayed on the receiver side and acquired in real time. The accuracy of temperature sensor received by the receiver is 92.97%, and humidity sensor is 90.57%. There was a delay of 1 second for the reception of telemetry data directly.
The D2D communication is expected to improve devices' energy-efficiency, which has become a major requirement of the future wireless network. Before the D2D communication can be performed, the device discovery between devices must be done. The previous works usually only assumed one mode of device discovery, i.e. either use network-assisted (with network supervision) or independent (without network supervision) device. Therefore, we propose a selective device discovery for device-to-device (D2D) communication that can utilize both device discovery modes and maintain devices' energyefficiency. Different from previous works, our proposed method selects the best device discovery mode to get the best energy-efficiency. Moreover, to further improve the energy-efficiency, our proposed method also deployed in D2D cluster with multiple cluster heads. The proposed method selects the most suitable mode using thresholds (cluster energy consumption and new device acceptance) and cluster energy expectation. Our experiment result indicates that the proposed method provides lowest energy consumption per new accepted device while compared with schemes with full network-assisted and independent device discovery in low numbers of new device arrival (for the number of new devices arrival = 1 ~ 3).
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