AR-based serious game framework for post-stroke rehabilitation

Stroke is considered one of the main causes of death around the world. Survivors often suffer different kinds of disabilities in terms of their cognitive and motor capabilities, and are therefore unable to perform their day-to-day activities. To regain some of their cognitive as well as motor abilities, they require rehabilitation. To this end, we present a serious game framework based on augmented reality technology that may motivate the patients’ involvement in the rehabilitation exercise. Additionally, we analyze the requirements for such a framework and describe the concept and implementation of the proposed approach. Furthermore, we designed a wireless vibrotactile output device that is attached to a tangible object. The tangible object that is connected to the framework can give haptic as well as audio-visual feedback to the patient in a more motivating and entertaining environment for rehabilitation exercises. The suitability and utility of the proposed framework was evaluated with real stroke patients and compared against the performance of a healthy control group, thus facilitating occupational therapists in assessing a patient’s progress. Our evaluations show that the serious games with vibrotactile feedback are well accepted by patients.     

Adsorption kinetics and enhanced oil recovery by silica nanoparticles in sandstone

This study addresses adsorption kinetics of silica nanoparticles on sandstone mineral surfaces and Enhanced oil recovery (EOR) by nanoparticles. It was shown that nanoparticle adsorption on quartz which is the major constituent of sandstone reservoirs was best described as second order process. Both rate and equilibrium adsorption increases with salinity. However, salinity reduces Intraparticle diffusion while enhancing film diffusion. Spontaneous imbibition with nanoparticles dispersed in low salinity water showed higher incremental recovery which may be due to increased structural disjoining pressure. This was supported by surface forces analysis based on particle size and zeta potential measurements of the nanofluids.     

H∞ filtering of discrete-time interconnected systems with failed interconnections

The H_∞ filtering problem for interconnected systems is addressed in this paper. In order to facilitate the stability analysis of interconnected systems under the conditions of failed interconnections, a strategy related to switched systems is introduced. Assume that the interconnections among these subsystems disconnect based on the mode-dependent average dwell time (MDADT), a switching signal is implemented to denote the failed interconnections cases. In the aid of the MDADT method, a filter is designed such that the fault detection (FD) system is asymptotically stable and satisfies the weighted H_∞ performance. Finally, a numerical simulation is provided to show the effectiveness of the proposed filter.     

Joint QoE-based user association and efficient cell–carrier distribution for enabling fully hybrid spectrum sharing approach in 5G mmWave cellular networks

Densifying the network by adding more minicell towers or relays throughout a hot spot area while extensively reusing the available spectrum is an essential choice to improve QoS. Unfortunately, this approach can be prohibitively costly. One possible solution to reduce the capital and operating expenditure in such overdensified networks is the adoption of the spectrum-sharing approach. However, both approaches would complicate the interference phenomenon either among inter- or intraoperators, which may cause serious performance degradation. In this paper, a fully hybrid spectrum-sharing (FHSS) approach aided by an efficient cell–carrier distribution was proposed with consideration to the interference dilemma. Moreover, an adaptive hybrid QoE-based mmWave user association (mUA) scheme was presented to assign a typical user to the serving mmWave base station (mBS), which offers the highest achievable data rate. The proposed FHSS approach (with the presented QoE-based mUA) was compared with recent works and with both FHSS approach using the conventional max-SINR-based mUA, which assigns a typical user to the tagged mBS carrying the highest signal-to-interference-plus noise ratio and the baseline scenario (licensed spectrum access). In particular, three spectrum access methods (licensed, semipooled, and fully pooled) were integrated in a hybrid manner to engage improved data rates to users. Numerical results show that the joint cell–carrier distribution and FHSS approach with QoE-based mUA outperform both baselines FHSS with the max-SINR mUA scheme and the licensed spectrum access. Furthermore, results demonstrate the effectiveness of the proposed approach in terms of both operators’ independence and fairness.

     

Efficient Computation Offloading Decision in Mobile Cloud Computing over 5G Network

Due to the significant advancement of Smartphone technology, the applications targeted for these devices are getting more and more complex and demanding of high power and resources. Mobile cloud computing (MCC) allows the Smart phones to perform these highly demanding tasks with the help of powerful cloud servers. However, to decide whether a given part of an application is cost-effective to execute in local mobile device or in the cloud server is a difficult problem in MCC. It is due to the trade-off between saving energy consumption while maintaining the strict latency requirements of applications. Currently, 5th generation mobile network (5G) is getting much attention, which can support increased network capacity, high data rate and low latency and can pave the way for solving the computation offloading problem in MCC. In this paper, we design an intelligent computation offloading system that takes tradeoff decisions for code offloading from a mobile device to cloud server over the 5G network. We develop a metric for tradeoff decision making that can maximize energy saving while maintain strict latency requirements of user applications in the 5G system. We evaluate the performances of the proposed system in a test-bed implementation, and the results show that it outperforms the state-of-the-art methods in terms of accuracy, computation and energy saving.     

A two-stage approach for task and resource management in multimedia cloud environment

In recent years, multimedia cloud computing is becoming a promising technology that can effectively process multimedia services and provide quality of service (QoS) provisioning for multimedia applications from anywhere, at any time and on any device at lower costs. However, there are two major challenges exist in this emerging computing paradigm: one is task management, which maps multimedia tasks to virtual machines, and the other is resource management, which maps virtual machines (VMs) to physical servers. In this study, we aim at providing an efficient solution that jointly addresses these challenges. In particular, a queuing based approach for task management and a heuristic algorithm for resource management are proposed. By adopting allocation deadline in each VM request, both task manager and VM allocator receive better chances to optimize the cost while satisfying the constraints on the quality of multimedia service. Various simulations were conducted to validate the efficiency of the proposed task and resource management approaches. The results showed that the proposed solutions provided better performance as compared to the existing state-of-the-art approaches.     

Privacy preserving secure data exchange in mobile P2P cloud healthcare environment

Cloud computing technology offers the possibility of inter-organizational medical data sharing at a larger scale. The different organizations can maintain their own cloud environment while exchanging healthcare data among them in a peer-to-peer(P2P) fashion according to some defined polices. However, there are many security and privacy challenges that hamper the adoption of cloud computing solutions in healthcare domain. Besides, due to the privacy sensitivity of healthcare data, an organization may not wish to disclose its identity to others when exchanging data in the network to avoid different attacks by the intruders. Hence, anonymously authenticated data exchange is essential between the different peer organizations. In this paper we propose an anonymous on-the-fly secure data exchange protocol for such environment based on pairing-based cryptography. Our proposed solution allows cloud peers to dynamically generate temporary identities that are used to produce a session key for each session of data exchange. The proposed protocol is robust against different attacks, such as target-oriented, man-in-the middle, masquerade, and message manipulation attacks.