When stricken by a catastrophic natural disaster, emergency rescue operation is very critical to many lives. Many people trapped in the disastrous areas under collapsed buildings or landslides may have a large chance to survive if they are rescued in "Golden 72 Hours". Victims rescued from the debris and evacuated from their home jammed in shelters need life support material to support their lives. They also need to communicate to each other for various reasons. However, communication systems were usually down due to various reasons. The loss of communication systems and information networks made the rescue and relief operation extremely difficult. Many people died before they got a chance to be rescued. This paper analyzes the causes that paralyzed the entire communication systems in Jiji/Taiwan Earthquake and proposes a MANET based communication platform as well as a Rescue Information System for Earthquake Disasters that can support a large number of rescue volunteers under catastrophic natural disasters.

When stricken by a catastrophic natural disaster, emergency rescue operation is very critical to many lives. Many people trapped in the disastrous areas under collapsed buildings or landslides may have a large chance to survive if they are rescued in "Golden 72 Hours". People evacuated from their home jammed in highways or dome shelters need to communicate to each other for various reasons. However, communication systems were usually down due to various reasons. The loss of communication systems made the rescue operation extremely difficult. Many people died before they got a chance to be rescued. This paper analyzes the causes that paralyzed the entire communication systems in Jiji earthquake and proposes a MANET based emergency communication and information system that can support a large number of rescue volunteers under catastrophic natural disasters.

A formal requirement specification language, the frame-and-rule oriented requirement specification language FRORL, developed to facilitate the specification, analysis, and development of a software system is presented. The surface syntax of FRORL is based on the concepts of frames and production rules that may bear hierarchical relationships to each other, relying on multiple inheritance. To provide thorough semantic foundations, FRORL is based on a nonmonotonic variant of Horn-clause logic. Using the machinery of Horn-clause logic, various properties of a FRORL specification can be analyzed. Among the external properties of FRORL are formality, object-orientedness, and a wide spectrum of life cycle phases. Intrinsic properties are modularity, provision for incremental development, inheritance, refinement, reusability, prototyping, and executability. A software development environment based on FRORL has been implemented using the C language on a Sun workstation.<>

In recent years the research on Vehicular Ad Hoc Network (VANET) has been paid much attention due to the development of wireless network becoming mature, people think highly of traffic safety issue, the popularity of Global Positioning System (GPS), promising applications of VANET being exploited. However, VANET has the essential property of rapid change of large scale network topology. Besides, the vehicles distributed over the road usually causes serious signal collisions and interferences. Thus, it calls for special concern to deal with the performances of throughput, collision and delay. In this paper we propose a Detection-Based MAC mechanism by modifying RTS/CTS to detect network congestion through message exchange and predict number of competing nodes. Both these information is used to dynamically adjust contention window size. Simulations focus on the MAC layer of IEEE 802.11p and the results show that the proposed method is able to effectively increase overall throughput, reduce packet collision rate and delay time.

For smart cities, the issue of how to solve traffic chaos has always attracted public attention. Many studies have proposed various solutions for traffic flow prediction, such as ARIMA, ANN, and SVM. With the breakthrough of deep learning technology, the evolutionary models of RNN, such as LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Units) models, have been proven to have excellent performance in traffic flow prediction. By using LSTM and GRU models, we explore more features and multi-layer models to increase the accuracy of traffic flow prediction. We compare the prediction accuracy of LSTM and GRU models in urban traffic flow prediction. The data collected in this study are divided into three categories, namely “regular traffic flow data”, “predictable episodic event data”, and “meteorological data”. The regular traffic flow data source is the “Vehicle Detector (VD) data of Taipei Open Data Platform”. Predictable episodic event data are predictable as non-routine events such as concerts and parades. We use a crawler program to collect this information through ticketing systems, tourism websites, news media, social media, and government websites and the meteorological data from the Central Meteorological Bureau. Through these three types of data, the accuracy in predicting traffic flow is enhanced to predict the degree of traffic congestion that may be affected.

Long Term Evolution (LTE) is the most promising technology for 4G mobile communication networks. The goal of LTE is to provide high data transmission rate, scalable bandwidth, low latency, and high-mobility. LTE employs Orthogonal Frequency Division Multiplexing (OFDM) and Single Carrier - Frequency Division Multiple Access (SC-FDMA) for downlink and uplink data transmission, respectively. As to SC-FDMA, there are two constraints in resource allocation. First, the allocated resource blocks (RB) should be contiguous. Second, these allocated resource blocks are forced to use the same modulation technique. This paper focuses on the resource allocation problem of LTE SC-FDMA system. The aim of this paper is to propose a QoS-constraint resource allocation scheduling to enhance data transmission on uplink SC-FDMA. The proposed scheduling is a three-stage approach. In the first stage, it uses a time domain scheduler to differentiate UE services according to different QoS service requirements. In the second stage, it uses a frequency domain scheduler to prioritize UE services based on channel quality. In the third stage, it limits the times of modulation downgrade in RBs allocation to enhance system throughput. In the simulations, the proposed method is compared to fixed sub-carrier dynamic resource allocation algorithm and adaptive dynamic sub-carrier resource allocation algorithm. Simulation results show that our method outperforms the other two methods in terms of throughput, transmission delay, packet loss ratio, and RB utilization.