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Inefficient data transmission has been a development bottleneck of Vehicular Ad-hoc NETworks (VANETs), especially in urban areas. It has been proved that many complex IP-based solutions are difficult to be applied in the highly dynamic and link-interrupted vehicular environment. In recent years, Named Data Networking (NDN) has become the most popular realization of Information-Centric Networking (ICN) for future networks. Its characteristics of multi-source, multi-path and in-network caching are helpful for improving the data transmission in VANETs. However, the bottom layer of vehicles cannot provide multiple interfaces to different domains like the routers in wired networks. Thus interface-based forwarding degenerates into directionless broadcasting with low performance and high overhead. Against this problem, we propose COMPASS, a novel named data transmission protocol for VANETs. Firstly, a dynamic directional interface model is built as the cornerstone of our COMPASS. Secondly, the forwarding strategies are improved for rapid interest dissemination and named data retrieving. Besides, an interface remapping method and the update strategies of Forwarding Information Base (FIB) and Pending Interest Table (PIT) are designed to enhance the robustness in high-mobility environment. Finally, the performance of COMPASS is verified on ndnSIM. Compared with the other three state-of-the-art protocols, COMPASS obtains the highest interest satisfaction ratio and the shortest transmission delay in urban traffic scenarios with restricted communication and storage overhead.

LoRa, more generically Low-Power Wide Area Network (LPWAN), is a promising platform to connect Internet of Things. It enables low-cost low-power communication at a few kbps over upto tens of kilometers with a 10-year battery lifetime. However, practical LPWAN deployments suffer from collisions, given the dense deployment of devices and wide coverage area. We propose CoLoRa, a protocol to decompose large numbers of concurrent transmissions from one collision in LoRa networks. At the heart of CoLoRa, we utilize packet time offset to disentangle collided packets. CoLoRa incorporates several novel techniques to address practical challenges. (1) We translate time offset, which is difficult to measure, to frequency features that can be reliably measured. (2) We propose a method to cancel inter-packet interference and extract accurate feature from low SNR LoRa signal. (3) We address frequency shift incurred by CFO and time offset for LoRa decoding. We implement CoLoRa on USRP N210 and evaluate its performance in both indoor and outdoor networks. CoLoRa is implemented in software at the base station and it can work for COTS LoRa nodes. The evaluation results show that CoLoRa improves the network throughput by 3.4× compared with Choir and by 14× compared with LoRaWAN.

LoRa is recently a rising star in Low Power Wide Area Network (LPWAN) family to provide low power and long range communication for large number of devices in Internet of Things. LoRa is based on Chirp Spread Spectrum (CSS) and uses chirp frequency shift to encode data. It has been shown that collision significantly degrades LoRa performance in practice. We propose FlipLoRa, a new mechanism to disentangle LoRa collisions, which allows concurrent transmission of multiple packets. The key idea of FlipLoRa is to utilize the quasi-orthogonality between upchirp and downchirp. FlipLoRa encodes packets with interleaved upchirps and downchirps instead of only using upchirps as in LoRa. We then propose a novel method to disentangle chirps and decode multiple collided packets. To evaluate the performance, we formally prove the quasi-orthogonality and analyze its applicable conditions. We validate the performance improvement by theoretical analysis. Further, we implement FlipLoRa on software-defined radio and extensively evaluate its performance for real LoRa networks. The evaluation results show that FlipLoRa can improve the throughput by 3.84x over LoRa physical layer.

The spatial resolution is increasingly high as development of optical remote sensing, and more and more optical sensors can achieve the detection ability of sub meter, which lays down the data foundation for automatic recognition of ship targets. However, mature technology is lacked to identify the ship models automatically with remote sensing images. In this study, an automatic recognition method for ship targets is proposed based on the local invariant feature extraction algorithm SIFT (Scale Invariant Feature Transform), which is consist of feature extraction and description, feature matching and target recognition. The model of unknown target is identified based on the target library using the matching difference of targets with the same model and different models. The experiment results show that this automatic recognition flow is effective to identify the ship targets of interest based on the target library, and the total correct recognition rate is 92%. This method provides a new flow for automatic model recognition of ship targets, and has considerable potential for wide applications.

The dual non-point source model independently developed by China is chosen to study its practical applicability in the experimental catchment area of Hebei Yuecheng Reservoir in combination with the remote sensing and GIS data, and to study the spatial distribution pattern of the non-point source Phosphorus (P) pollution. The result shows that: (1) the simulated non-point source P load is strongly related to the observation data of the hydrologic stations such as Liujiazhuang, Guantai and etc; (2) the farmlands, urban and rural residential areas in the catchment area are the major risk sources of non-point source pollution; (3) the two assessment units, catchment unit and administration unit, are employed in this study. They are complementary to each other.

Naval ship formation is one of the main counterwork forms in modern sea battles. Reliability theory is used to study naval ship formation deployment. First, a measure method for the cooperative quality of the shipborne equipments in the formation is given based on the concept of reliability degree. Then an optimized deployment of naval fleet is established with consideration of the cooperative quality of the shipborne equipments, and a solving algorithm based on Genetic Algorithm(GA) model is proposed. The effectiveness of the model is proved with massive simulations.

This paper proposes a new theory of adder and its basic structure. The new adder is an asynchronous adder whose basic unit is half adder,called Parallel Feedback Carry Adder (PFCA) as its carry mode is parallel feedback.In theory, compared to the adders (e.g. RCA,CLA,CSeA) based on full adder, PFCA is faster in speed and smaller in area. A CMOS gate implementation is proposed to verify the new design theory in this paper. HSPICE simulation results show that PFCA has obvious advantage over RCA,CLA,CSeA in speed and area,showing potential applications especially when adder bits n is larger.