Summary In the field of bioinformatics and DNA computing, simulated hybridization experiments can replace real molecular hybridization experiments to some extent, avoiding some disadvantages of the actual experimental design. However, the core techniques, which are employed by the popular DNA simulation software, are limited to the exponential computational complexity of the combinatorial problems. As a result, it is impossible to decide whether a specific hybridization among complex DNA molecules is effective or not within acceptable time. To address this common problem, we hereby introduce a new method based on the machine learning technique. First, a sample set is employed to train the boosted tree algorithm, which resulted in a corresponding machine learning model. Second, this model is applied to predict the classification results of molecular hybridization for a given group of DNA molecular coding. The experiment results showed that the new method had an average accuracy level of 94.2% and an average efficiency level 90 839 times higher than that of the existing representative approaches. Especially for the case study in this paper, the efficiency of the new method is 235 000, 250 000, and 990 000 times higher than that of the three existing methods, respectively. These experimental results indicate that our new approach can quickly and accurately determine the biological effectiveness of molecular hybridization for a given DNA design.

The high-power dissipation and the low-heat conduction between stacked chips in 3-D structures lead to a high temperature, which has become a critical design constraint for high-performance 3-D integrated circuits (ICs). Naturally, a power distribution network (PDN) in 3-D ICs consists of good heat conductor, but many existing methods do not fully show its thermal removal capability, and the thermal models of a 3-D PDN are imperfect. In this paper, compact and accurate physically based models to compute effective thermal conductivities of a 3-D PDN are proposed. By combining the equivalent thermal conductivity and the proposed complete thermal models for a 3-D PDN, a fast temperature analysis procedure can be expediently applied using the finite volume method. Finite element method (FEM) tools are used to verify the accuracy of the proposed models, and the errors in the temperature responses of our proposed method are within 3% compared with the results from the FEM. In addition, our method also improves the computational efficiency.

We developed an improved algorithm for an indoor positioning system based on an image sensor. By using the algorithm that tilts the image sensor when it is placed at room corners, the authors reduced the positioning error at the corners and increased the effective positioning area. When in room corners, the image sensor is placed at an appropriate angle that allows the reception of light from all three light‐emitting diodes (LEDs). The unknown sensor position is calculated from the geometrical relations among the LED images created on the tilted image sensor plane. According to the obtained experimental results, signal–to‐noise ratio of the received signal can be improved when the image sensor tilts at certain angle at the corner. It was found that the effective range of the tilt angle of the image sensor is estimated to be within the range of 30°–60° at the corners. The root mean‐square of the positioning error obtained with the developed algorithm is 0.6 mm when the image sensor is located within the effective positioning area. The effective positioning area was increased by 15.3% at the corner areas when the image sensor was tilted by the optimal angle.

the results of a field trials campaign in a park, a wide street, a narrow street and office environments are presented in this paper. The trials are carried out using a real time 4x4 MIMO-OFDM testbed working in the 2.4 GHz ISM band and a 20 MHz bandwidth. The testbed supports both spatial multiplexing and transmit and receive diversity. We compare the system performance using different number of spatial streams in different environments. We also determine the maximum number of spatial streams that can be supported in the indoor and outdoor environments respectively. We found that the maximum achievable throughput for the system in the indoor environment is almost double the maximum achievable throughput in the outdoor environment at the same receive power. This is mainly due to the richness of scattering elements in an indoor setting. Our outdoor trials showed that supporting more than two spatial streams will not introduce any throughput gain.

This paper proposes a new peak-to-average power ratio (PAPR) reduction scheme in multiple transmit antenna environments. By applying a unitary rotation, overall PAPR of the multiple transmits antenna system is reduced. This scheme doesn't require any side information to decode the signal in the receiver, enabling throughput-lossless PAPR reduction. Furthermore, there is no increase in the complexity of the receiver.

This paper provides details about experiments in realistic, urban, and frequency flat channels with space-time coding that specifically examines the impact of the number of receive antennas and the design criteria for code selection on the performance. Also the performance characteristics are examined of the coded modulations in the presence of finite size array geometries. This paper gives some insight into which of the theories are most useful in realistic deployments