Motion Estimation and Compensation in the Redundant Wavelet Domain

Despite being the prefered approach for still-image compression for nearly a decade, wavelet-based coding for video has been slow to emerge, due primarily to the fact that the shift variance of the discrete wavelet transform hinders motion estimation and compensation crucial to modern video coders. Recently it has been recognized that a redundant, or overcomplete, wavelet transform is shift invariant and thus permits motion prediction in the wavelet domain. In this dissertation, other uses for the redundancy of overcomplete wavelet transforms in video coding are explored. First, it is demonstrated that the redundant-wavelet domain facilitates the placement of an irregular triangular mesh to video images, thereby exploiting transform redundancy to implement geometries for motion estimation and compensation more general than the traditional block structure widely employed. As the second contribution of this dissertation, a new form of multihypothesis prediction, redundant wavelet multihypothesis, is presented. This new approach to motion estimation and compensation produces motion predictions that are diverse in transform phase to increase prediction accuracy. Finally, it is demonstrated that the proposed redundant-wavelet strategies complement existing advanced video-coding techniques and produce significant performance improvements in a battery of experimental results

Reconstruction Improvements on Compressed Sensing

This paper presents the design of Improvements on Reconstruction of Compressive Sensed images. The proposed techniques will improve the reconstruction time consumption. Those improvements use techniques including matrix simplification, multi-thread and GPU computations.  Implementing those improvements achieve gains on time consumption, compared to the baseline. This paper also presents a novel scheme of buffering steamed image (video) to achieve optimum performance

Perspective Chapter: Deep Reinforcement Learning for Co-Resident Attack Mitigation in The Cloud

Cloud computing brings convenience and cost efficiency to users, but multiplexing virtual machines (VMs) on a single physical machine (PM) results in various cybersecurity risks. For example, a co-resident attack could occur when malicious VMs use shared resources on the hosting PM to control or gain unauthorized access to other benign VMs. Most task schedulers do not contribute to both resource management and risk control. This article studies how to minimize the co-resident risks while optimizing the VM completion time through designing efficient VM allocation policies. A zero-trust threat model is defined with a set of co-resident risk mitigation parameters to support this argument and assume that all VMs are malicious. In order to reduce the chances of co-residency, deep reinforcement learning (DRL) is adopted to decide the VM allocation strategy. An effective cost function is developed to guide the reinforcement learning (RL) policy training. Compared with other traditional scheduling paradigms, the proposed system achieves plausible mitigation of co-resident attacks with a relatively small VM slowdown ratio

Stability analysis of differential scheme for dynamic equations of mooring cable system

The mooring cable system in plane motion can be modeled as two coupled partial differential equations, which can be numerical solved by finite difference method directly. The difference scheme is analyzed, and parameters selection for time-marching of displacement and velocity are deduced. The stability condition of the scheme is analyzed through Fourier series method, and parameters range which match stable scheme is given. Then, the parameters range is verified by a numerical example

Cyber-Physical Systems: A Literature Review

Cyber-physical systems (CPSs) are smart systems that depend on the synergy of cyber and physical components. They link the physical world (e.g. through sensors, actuators, robotics, and embedded systems) with the virtual world of information processing. Applications of CPS have the tremendous potential of improving convenience, comfort, and safety in our daily life. This paper provides a brief introduction to CPSs and their applications

Continued Efforts in TI ARM M4 Microcontroller Curricula Developments and Assessments Between Three Different Institutions and Programs

This project is a continuation in efforts to upgrade the curricula in microcontroller related courses that are facing difficulties in the disappearing and lack technical supports in hardware and software of 68XXX and 80XXX microcontrollers. Through the study of a NSF supported project Transform the Innovated Design and Development of an Embedded Design Training System and Associated Support Curricula into a Commercial Available Product that interviewed 130 faculty/teachers/students across the U.S. has revealed on finding newly available microcontrollers is an urgent issue in the academic communities. Based on the supports on hardware and software and function libraries, the TI ARM M4 core is the choice for the join efforts in the new curriculum development and assessment between Old Dominion University, Farmingdale State College, Prairie View A&M University, and Ohio Northern University within the programs of CET, ECE, EET, and Tech Studies. The efforts were also a direct response to the industries suggestions and the needs of 32 bits ARM microcontroller’s skills from engineer and technology programs graduates to fill the job markets. This article presents a study and comparison that introduce a concept of collaborated efforts among different institutions and programs can work together to develop the comprehensive ARM curricula that fit the industry’s needs. These curricula development efforts are not only aim at on-campus face-to-face teaching and learning but also distance hands-on learning through delivering course modules using both synchronous and asynchronous. The assessment of this jointed efforts are part of the studies. Engineering and technology programs focus on both hands-on and mind-on design work and this article demonstrates the collaborated efforts in advanced curriculum development in the ARM microcontroller which is the key ingredient for success. Through the development efforts and online Learning Management System (LMS) designs that make the distance collaboration, delivery, and cyber-enabled learning possible. These efforts not only benefit the interested faculty/teachers in better teaching and learning, but also support the students who can learn more advanced technical concepts that are needed for emerging high-tech job skills. Highlights of the presentation will address the following: • Research and development of the virtual classrooms and open source service server. • Design and development of the supported material. • Implementation strategies and planning for the distance hands-on approach. • Assessment of the teaching and learning. • Recommendations of potential adoption of the development. • Continuous improvement of teaching and learning in academic community

Galloping behavior analysis of transmission line with thin ice accretions

A dynamic model of a galloping transmission line able to describe for the coupling of its longitudinal, in-plane, out-of-plane and torsional vibrations is established. It also considers the effects of geometrical nonlinearity and aerodynamic nonlinearity. By the static configuration, the reduced model is obtained. Then, the equations of motion are obtained through the Galerkin method. It contains two in-plane, two out-of-plane and two torsional components. By numerical calculation, the maximum amplitudes at wind speeds are drawn and the galloping behavior of transmission line with thin ice accretions is analyzed. The obtained results show that the second galloping mode is more triggered. The double-mode galloping occurs in all motions, in which the maximum amplitude is bigger than in single-mode galloping. And the double-mode galloping presents the track of inclined ‘8’ in longitudinal direction

Compressive Sensing Based Image Compression and Transmission for Noisy Channels

This paper presents the design of an optimized Compressive Sensing image compression technique for data transmission over noisy mobile wireless channel. The proposed technique is more robust to channel noise. It uses individual measurement driven coding scheme, which facilitates simpler encoder design. The shift of computational burden from encoder to decoder is more suitable for mobile devices applications where computational power and battery life are limited. This paper also presents a novel quantizer which allows the encoder to dynamically adapt to the channel conditions and provides optimum performance

Connecting Incoming Freshmen With Engineering Through Hands-On Projects

Engineering programs suffer a high attrition rate, which causes the nation to graduate much less engineers. A survey of the literature reveals that the high attrition rate is due mainly to the fact that the first year of an engineering program is all fundamental theory and students don't see the connection to their future engineering careers. To address this problem, educators in the Roy G. Perry College of Engineering at Prairie View A&M University launched a five-week summer camp entitled “College of Engineering Enhancement Institute (CE2I)” aimed at improving the performance of incoming freshmen in mathematics by one level and a smoother transition between high school and college. Each department in the college participated by introducing their individual curriculum through hands-on projects designed by faculty members. Computer Engineering, Computer Science and Computer Engineering Technology programs implemented multimedia projects to tie the incoming freshman to their selected majors. Results show that the camp met the expectations and successfully points the directions for our future engineering education practices.

Calcium-binding protein S100P promotes tumor progression but enhances chemosensitivity in breast cancer

Background: Chemoresistance remains one of the obstacles to overcome in the treatment of breast cancer. S100 calcium-binding protein P (S100P) has been observed to be overexpressed in several cancers and has been associated with drug resistance, metastasis, and prognosis. However, the role of S100P in chemoresistance in breast cancer has not been thoroughly determined. Methods: Immunohistochemistry was used to evaluate the expression level of S100P protein in 22 pairs (pre-chemo and post-chemo) of breast cancer tissue from patients who underwent neoadjuvant chemotherapy. The influence of S100P on the biological behavior and chemosensitivity of breast cancer cells was then investigated. Results: The protein level of S100P in breast cancer tissue was significantly higher than in benign fibroadenoma (p<0.001). The S100P expression level was shown to be decreased by 46.55% after neoadjuvant chemotherapy (p=0.015). Subgroup analysis revealed that S100P reduction (57.58%) was mainly observed in the HER2+ tumors (p=0.027). Our in-vitro experiments showed that the knockdown of S100P suppressed the proliferation, adhesion, migration and invasion abilities of T47D and SK-BR-3 breast cancer cells. We further demonstrated that this knockdown increased the chemoresistance to paclitaxel and cisplatin in SK-BR-3 cells. We found that S100P exerted its function by activating NF-κB, CCND1 and Vimentin, but downregulating E-cadherin. Conclusions: S100P promotes the aggressive properties of breast cancer cells and may be considered as a promising therapeutic target. Moreover, S100P can be used to predict the therapeutic effect of chemotherapy in HER2+ breast cancer patients