Gu Fei

Soochow University | SUDA · School of Computer Science and Technology

Premature ventricular complexes (PVCs) are irregularities in heart rhythm where the ventricles contract earlier than expected, disrupting the normal cardiac cycle. Identifying the origin of PVCs before surgery is crucial as it can reduce operation duration, lower radiation exposure, and potentially enhance ablation success rates. Current detection...

Traffic congestion, air pollution, fuel wastage, and car accidents are all exacerbated by increased traffic. Thus, vehicular communications, which refer to information transmission between cars, pedestrians, and infrastructures, have lately gained popularity and been extensively explored due to their enormous potential to enable intelligent transpo...

Edge computing is an efficient computing paradigm, which can utilize computing devices at the edge of network to provide real-time proximity service. Since edge devices lack centralized management, they are more vulnerable to being attacked. Therefore, the issues of data security and user privacy in edge computing are particularly important. A larg...

Compliance with security requirements in Wireless Sensor Networks (WSNs) is known as an important phenomenon in conserving energy consumption due to its dynamic topology. Energy consumption management in WSN can be achieved through secure routing protocols. Authentication, firewall and intrusion detection, and trust management are common ways to pr...

Background: Preoperative prediction of the origin site of premature ventricular complexes (PVCs) is critical for the success of operations. However, current methods are not efficient or accurate enough. In addition, among the proposed strategies, there are few good prediction methods for electrocardiogram (ECG) images combined with deep learning c...

Existing studies of mobile edge computing resource allocation strategy problem merely optimize delay and energy cost, seldom considering the benefit of edge servers. So, a two-way update strategy based on game theory (TUSGT) was proposed. TUSGT converts the task competition relationship among edge servers into a noncollaborative game issue and adop...

Tracking aircraft and parachutes plays a vital role in airdrop experiments. It is necessary to study a parachute’s open state and flight trajectory. More scholars are looking into how to efficiently and accurately obtain parachute deformation data and trajectory data. At present, the actual data collection primarily involves experimenters holding h...

Object detection has attracted great attention in recent years. Many experts and scholars have proposed efficient solutions to address object detection problems and achieve perfect performance. For example, coordinate-based anchor-free (CBAF) module was proposed recently to predict the category and the adjustments to the box of the object by its fe...

In order to better assist the rehabilitation treatment of patients with musculoskeletal injury, standard rehabilitation actions are needed to guide the musculoskeletal rehabilitation process. With more and more urgent demands, the musculoskeletal rehabilitation evaluation systems have attracted a high degree of attention. Experts have proposed a se...

Traditional video object segmentation often has low detection speed and inaccurate results due to the jitter caused by the pan-and-tilt or hand-held devices. Deep neural network (DNN) has been widely adopted to address these problems; however, it relies on a large number of annotated data and high-performance computing units. Therefore, DNN is not...

To improve safety in public transportation, a major issue is how to avoid traffic accidents. To this end, a recent report has demonstrated that more than 90% of accidents in the United States were due to drivers’ abnormal behaviors. Relevant to this observation, many recent studies have proposed to use different sensors to monitor drivers’ behavior...

Every year, over 4700 traffic fatalities and 75000 crash injuries involve pedestrians in the United States. Effective solutions are urgently needed to prevent vehicle-pedestrian collision accidents. Many driving assistance systems are proposed to address this problem, however, they require additional infrastructures that may result in higher costs...

Deep learning provides many new and efficient solutions for edge computing. We study training image classification models on edge devices in this paper. Although there have been many researches on deep learning in edge computing. Most of them did not consider the impact of the limited service capabilities of edge devices, the problem of straggler a...

Currently, many computation offloading studies in Mobile Edge Computing (MEC) mainly focus on the multi-user and multi-task offloading, where the tasks are independent and inseparable. However, nowadays many mobile applications, such as Augmented Reality (AR) glasses, face recognition, etc., can be classified into sequential tasks. Dependencies amo...

In recent years, edge computing (EC) has attracted great attention for its high-speed computing and low-latency characteristics. However, there are many challenges in the implementation of EC. Firstly, user's privacy has been raised as a major concern because the edge devices may be untrustworthy. In the case of Private Edge Computing (PEC), a user...

Researches have shown that taking parting in family activities could establish good relationships with family members. Fine-grained family activities detection is proven effective for increasing self-awareness and motivating people to modify their life styles for improved well being. Mobile health provides the possibility to solve this problem. How...

With the number of connected devices in Internet of Things (IoT) increasing, the requirements for connectivity (e.g., battery life, deployment cost and coverage) are evolving to ensure effective communication between these devices. The emerging low power wide area (LPWA) technologies pave a way to address the problem as they can provide affordable...

Heart rate directly reflects heart health and the detection of heart rate contributes to finding the abnormal performance of heart activity in a timely manner. Nevertheless, there is scope for a significant improvement in current heart rate detection systems and devices, especially during strenuous exercise. Motion compensation algorithm is used in...

After the Local Outlier Factor (LOF) was first proposed, there is a large family of local outlier detection approaches derived from it. Since the existing approaches only focus on the extent of overall separation between an object and its neighbors, and ignore the degree of dispersion between them, the precision of these approaches will be affected...

Mobile applications, such as augment reality, natural language processing, object recognition and multimedia-based services, are becoming increasingly ubiquitous and can provide better user experience on mobile devices. However, such applications are draining increasingly more computational resources and energy of mobile devices. Partitioning and o...

Delay optimization has recently attracted significant attention. However, few studies have focused on the delay optimization of mixed-polarity Reed-Muller (MPRM) logic circuits. In this paper, we propose an efficient delay optimization approach (EDOA) for MPRM logic circuits under the unit delay model, which can derive an optimal MPRM logic circuit...

The bottleneck of integrated circuit design could potentially be alleviated by using Reed-Muller (RM) logic circuits due to their remarkable superiority in power, area and testability. In this paper, we propose a Novel Binary Differential Evolution (DE) algorithm (NBDE) to solve the discrete binary-encoded combination optimization problem. Moreover...

Running is a kind of whole body movement, which enables the whole body muscle rhythmic contraction and relaxation. A stable and harmonic running rhythm can not only postpone runners’ fatigue but also improve their exercise effectiveness. The paper presents an effective method of detecting runner’s breathing frequency continuously and maintaining a...

Indoor localization based on smartphone can enhance user's experiences in indoor environments. Although some innovative solutions have been proposed in the past two decades, how to accurately and efficiently localize users in indoor environments is still a challenging problem. Traditional indoor positioning systems based on Wi-Fi fingerprints or de...

Although the genetic algorithm has been widely used in the polarity optimization of mixed polarity Reed-Muller (MPRM) logic circuits, few studies have taken into account the polarity conversion sequence. In order to improve the efficiency of polarity optimization of MPRM logic circuits, we propose an efficient and fast polarity optimization approac...

The power and area optimization of Reed-Muller (RM) circuits has been widely concerned. However, almost none of the exiting power and area optimization approaches can obtain all the Pareto optimal solutions of the original problem and are efficient enough. Moreover, they have not considered the don’t care terms, which makes the circuit performance...

Running is one of the most important workouts to keep your body fit. This paper presents RunnerPal – a runner monitoring and advisory system by harmonizing the rhythms of breathing, heart beating and striding based on smart devices. RunnerPal is a convenient, biofeedback-based, automated music recommendation system, which utilizes Bluetooth headset...

Breathing plays an important role in the process of running. A stable and harmonic breathing rhythm can postpone runners' fatigue and help to improve their running performances. This paper presents a method that can detect runner's breathing frequency continuously. We utilize Bluetooth headset and smart phone to obtain sensed data, such as striding...

With an exploding growth of the mobile applications and emerging of cloud computing, mobile cloud computing (MCC) has become a potential technology for mobile services. MCC is the combination of cloud computing, mobile computing and wireless networks to bring rich computational resources to mobile users, network operators, as well as cloud computin...

There are a lot of links among monitoring points of airport noise. To mine association rules among these monitoring points is very important in order to predict airport noise scientifically and effectively. Due to the low efficiency of the Apriori algorithm for mining association rules, this paper proposes a new algorithm called 'Adapt to Noise Set...