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This paper proposes the design of a dual-band integrated rectenna. The rectenna has compact size of 0.4 &times, 0.3 &times, 0.25 cm3 and operates at 925 MHz and 2450 MHz bands. In general, the rectenna consists of two main parts, the metal-rimmed dual-band antenna used for harvesting the radio frequency (RF) signals from the environment and the rectifier circuit to convert these receiving powers to the direct current (DC). Because of the dual resonant structure of the antenna, the rectifier circuit can be optimized in terms of size and the frequency bandwidth, while the conversion efficiencies are always obtained 60% at the RF input power &minus, 2.5 dBm and &minus, 1 dBm for the lower band and the higher band, respectively. Measured results show that the metal-rimmed antenna exhibits &minus, 10 dB reflection coefficient in both desired frequency bands. Moreover, the antenna achieves 47% and 89% of total efficiency respectively at 925 MHz and 2450 MHz, which confirms that the proposed rectenna is well applicable in most of the miniaturized wireless sensor networks and IoT systems.

Herein, a novel colorimeter based on the Beer-Lambert law was designed for detection of environmental pollutants in water with a high precision, simple, and miniaturized device using a tetracycline-Eu3+ complex, cadmium reduction, diazotization, 1,10-phenanthroline, and periodate oxidation. The newly developed colorimeter could detect many environmental pollutants including tetracycline, nitrate, nitrite, Fe, and Mn, which were used to evaluate its performance. Simultaneously, a modified algorithm was applied to extend the linear response range. The colorimeter was comprised of an Red Green Blue Light Emitting Diode (RGB LED) light, focusing len, 3D printed stand for the cuvette, and light-sensitive photodiode detector. Microcontroller Arduino Uno processing technology was used to form a stable integrated structure. With the use of a novel algorithm, the device exhibited a wide linear response, ranging from 0–20, 0–17, 0–0.3, 0–1.75, and 0–15 mg/L for tetracycline, N-NO3-, N-NO2-, Fe, and Mn, respectively, and low limits of detection (0.88, 0.34, 0.031, 0.08, and 0.47 mg/L for tetracycline, N-NO3-, N-NO2-, Fe, and Mn, respectively). The advantages of high precision and low cost allow the novel design to be used for the detection of environmental pollutants.

This paper gives an introduction of speech recognition systems for human-computer interaction using Vietnamese language. First, the paper investigates the two most common speech recognition toolkits currently used, HTK and Sphinx, and apply these tools into Vietnamese speech recognition. Then, only HTK is selected to design an application that control a web browser (Google Chrome) and an application that control a robot. The results obtained give a comparison between the uses of the two tool kits for Vietnamese speech recognition. 

A decentralized cooperative control strategy engaging offline and online computations for constrained multi-agent vehicle systems is presented in this paper. Intermittent data dropouts may incur concurrently to all vehicle agents in this formulation. Demands on communication links and online data are limited with a perturbed state-feedback strategy, which consists of a static cooperative-state feedback and an online-optimizing perturbation. The former compensates for the interagent communication-coupled dynamics. The latter attends to constraints and data losses, adopting only decoupled objective functions. The state feedback gain is determined in accordance with the interconnection topology of the formation, which is described by a directed graph in this paper. The ADC - asymptotically dissipative constraint, is employed in the overriding control strategy of stabilizing agents such that the inter-operability between remote manoeuvres and local autonomous commands becomes practically realizable. The equilibrium-independent supply rate and storage function are used in the stabilizability condition in this development for the final-state tracking of the cooperative formation problem.

Spam filtering is seen as the considerable concern to the researchers, and there are some techniques and email filtering systems are implemented. They are, however, not so effective for Vietnamese language. Although methods for filtering English spam email can be still used in Vietnamese language, but Vietnamese has its own particular characteristic. The biggest difference is a signified word in Vietnamese usually a compound. When a compound used in spam email is separated into single words, it becomes words that are usually used in both spam and ham emails. This leads to the difficulty for the system to filter spam emails. The objective of this paper is to present a new model using the application of Naive Bayesian algorithms to analyze the segmentation of Vietnamese language. The process of demonstration and evaluation of this model shows the feasibility of this technique in filtering Vietnamese email.

Most visual multi-target tracking techniques in the literature employ a detection routine to map the image data to point measurements that are usually further processed by a filter. In this paper, we present a visual tracking technique based on a multi-target filtering algorithm that operates directly on the image observations and does not require any detection nor training patterns. Instead, we use the recent history of image data for non-parametric background subtraction and apply an efficient multi-target filtering technique, known as the multi-Bernoulli filter, on the resulting grey scale image data. In our experiments, we applied our method to track multiple people in three video sequences from the CAVIAR dataset. The results show that our method can automatically track multiple interacting targets and quickly finds targets entering or leaving the scene.