This work implements an intelligent forest monitoring system using the Internet of things (IoT) with the wireless network communication technology of a low-power wide-area network (LPWAN), a long range (LoRa), and a narrow-band Internet of things (NB-IoT). A solar micro-weather station with LoRa-based sensors and communications was built to monitor the forest status and information such as the light intensity, air pressure, ultraviolet intensity, CO₂, etc. Moreover, a multi-hop algorithm for the LoRa-based sensors and communications is proposed to solve the problem of long-distance communication without 3G/4G. For the forest without electricity, we installed solar panels to supply electricity for the sensors and other equipment. In order to avoid the problem of insufficient solar panels due to insufficient sunlight in the forest, we also connected each solar panel to a battery to store electricity. The experimental results show the implementation of the proposed method and its performance.

Recommended travel itinerary planning is an important issue in travel platforms or travel systems. Most research focuses on minimizing the time spent traveling between attractions or the cost of attractions. This study makes four contributions to recommended travel itinerary planning in travel platforms or travel systems. The first contribution is to consider recommended travel itinerary planning which can account for attractions, restaurants, and hotels at the same time. Due to the fact that restaurants and hotels can be repeated on the recommended itinerary, the second contribution is to propose an improved ant colony system (ACS) with repeatedly used nodes for the optimization of travel itinerary planning. In the third contribution, the proposed improved ACS allows repeated use of certain nodes without falling into a pattern of infinitely hovering within a certain interval or over certain nodes, through the interactive operation of a Watch List and a Tabu List. In the fourth contribution, the user satisfaction calculation for restaurants and hotels is also added to the travel itinerary planning in order to fully meet the needs of tourists. The experimental results verify the efficiency of the proposed improved ACS.

The transform domain provides a useful tool in the field of confidential data hiding and protection. In order to protect and transmit patients’ information and competence, this study develops an amplitude quantization system in a transform domain by hiding patients’ information in an electrocardiogram (ECG). In this system, we first consider a non-linear model with a hiding state switch to enhance the quality of the hidden ECG signals. Next, we utilize particle swarm optimization (PSO) to solve the non-linear model so as to have a good signal-to-noise ratio (SNR), root mean square error (RMSE), and relative root mean square error (rRMSE). Accordingly, the distortion of the shape in each ECG signal is tiny, while the hidden information can fulfill the needs of physiological diagnostics. The extraction of hidden information is reversely similar to a hiding procedure without primary ECG signals. Preliminary outcomes confirm the effectiveness of our proposed method, especially an Amplitude Similarity of almost 1, an Interval RMSE of almost 0, and SNRs all above 30.

Light-emitting electronic devices are widely used at present, and this increases the risk of myopia. Thus, the early identification of myopia and the prevention of further exacerbation has become an essential issue in ophthalmology. Recently, choroidal imaging has been used to assist in the early identification and prevention of high myopia due to the fact that swept-source optical coherence tomography (SS-OCT) is an essential diagnostic tool in ophthalmology. This study presents a novel method to judge high myopia using the SS-OCT image dataset obtained from a university hospital. In order to relate the proposed method to the region of the SS-OCT image, the curvature analysis of an arbitrary segmented curve similar to the region of the SS-OCT is first illustrated by quadratic functions and matrix operations. Next, the curvature formula is derived and then applied to the choroidal curve obtained manually in each patient’s choroidal image. In particular, we applied the curvature analysis and its results to find the maximal curvature and average curvature of each patient’s choroidal curve. Finally, we used the maximal curvature and average curvature to evaluate high myopia. The accuracy of the proposed maximal curvature method and average curvature method in the experimental results to verify the proposed method.