New methods of partial transmit sequence for reducing the high peak-to-average-power ratio with low complexity in the ofdm and f-ofdm systems

The orthogonal frequency division multiplexing system (OFDM) is one of the most important components for the multicarrier waveform design in the wireless communication standards. Consequently, the OFDM system has been adopted by many high-speed wireless standards. However, the high peak-to-average- power ratio (PAPR) is the main obstacle of the OFDM system in the real applications because of the non-linearity nature in the transmitter. Partial transmit sequence (PTS) is one of the effective PAPR reduction techniques that has been employed for reducing the PAPR value 3 dB; however, the high computational complexity is the main drawback of this technique. This thesis proposes novel methods and algorithms for reducing the high PAPR value with low computational complexity depending on the PTS technique. First, three novel subblocks partitioning schemes, Sine Shape partitioning scheme (SS-PTS), Subsets partitioning scheme (Sb-PTS), and Hybrid partitioning scheme (H-PTS) have been introduced for improving the PAPR reduction performance with low computational complexity in the frequency-domain of the PTS structure. Secondly, two novel algorithms, Grouping Complex iterations algorithm (G-C-PTS), and Gray Code Phase Factor algorithm (Gray-PF-PTS) have been developed to reduce the computational complexity for finding the optimum phase rotation factors in the time domain part of the PTS structure. Third, a new hybrid method that combines the Selective mapping and Cyclically Shifts Sequences (SLM-CSS-PTS) techniques in parallel has been proposed for improving the PAPR reduction performance and the computational complexity level. Based on the proposed methods, an improved PTS method that merges the best subblock partitioning scheme in the frequency domain and the best low-complexity algorithm in the time domain has been introduced to enhance the PAPR reduction performance better than the conventional PTS method with extremely low computational complexity level. The efficiency of the proposed methods is verified by comparing the predicted results with the existing modified PTS methods in the literature using Matlab software simulation and numerical calculation. The results that obtained using the proposed methods achieve a superior gain in the PAPR reduction performance compared with the conventional PTS technique. In addition, the number of complex addition and multiplication operations has been reduced compared with the conventional PTS method by about 54%, and 32% for the frequency domain schemes, 51% and 65% for the time domain algorithms, 18% and 42% for the combining method. Moreover, the improved PTS method which combines the best scheme in the frequency domain and the best algorithm in the time domain outperforms the conventional PTS method in terms of the PAPR reduction performance and the computational complexity level, where the number of complex addition and multiplication operation has been reduced by about 51% and 63%, respectively. Finally, the proposed methods and algorithms have been applied to the OFDM and Filtered-OFDM (F-OFDM) systems through Matlab software simulation, where F-OFDM refers to the waveform design candidate in the next generation technology (5G)

A Comprehensive Survey of Convolutions in Deep Learning: Applications, Challenges, and Future Trends

In today's digital age, Convolutional Neural Networks (CNNs), a subset of Deep Learning (DL), are widely used for various computer vision tasks such as image classification, object detection, and image segmentation. There are numerous types of CNNs designed to meet specific needs and requirements, including 1D, 2D, and 3D CNNs, as well as dilated, grouped, attention, depthwise convolutions, and NAS, among others. Each type of CNN has its unique structure and characteristics, making it suitable for specific tasks. It's crucial to gain a thorough understanding and perform a comparative analysis of these different CNN types to understand their strengths and weaknesses. Furthermore, studying the performance, limitations, and practical applications of each type of CNN can aid in the development of new and improved architectures in the future. We also dive into the platforms and frameworks that researchers utilize for their research or development from various perspectives. Additionally, we explore the main research fields of CNN like 6D vision, generative models, and meta-learning. This survey paper provides a comprehensive examination and comparison of various CNN architectures, highlighting their architectural differences and emphasizing their respective advantages, disadvantages, applications, challenges, and future trends

Artificial Intelligence in Landscape Architecture: A Survey of Theory, Culture, and Practice

This dissertation explores the role of artificial intelligence (AI) in shaping the landscape architecture profession. It looks at how AI has evolved in the field, its current influence, and its potential to change research, teaching, and professional practice. The research includes a detailed review of existing literature to identify trends in AI applications and gaps in knowledge. It also examines landscape architects\u27 attitudes towards AI, revealing a mix of enthusiasm for its benefits and concerns about its impact on creativity and design processes, and proposes new ways of thinking about and working with AI. The work brings a unique perspective on AI in the field and gives valuable insights for future research and practice

Selected Papers from the 8th Annual Conference of Energy Economics and Management

This collection represents successful invited submissions from the papers presented at the 8th Annual Conference of Energy Economics and Management held in Beijing, China, 22–24 September 2017. With over 500 participants, the conference was co-hosted by the Management Science Department of National Natural Science Foundation of China, the Chinese Society of Energy Economics and Management, and Renmin University of China on the subject area of “Energy Transition of China: Opportunities and Challenges”. The major strategies to transform the energy system of China to a sustainable model include energy/economic structure adjustment, resource conservation, and technology innovation. Accordingly, the conference and its associated publications encourage research to address the major issues faced in supporting the energy transition of China. Papers published in this collection cover the broad spectrum of energy economics issues, including building energy efficiency, industrial energy demand, public policies to promote new energy technologies, power system control technology, emission reduction policies in energy-intensive industries, emission measurements of cities, energy price movement, and the impact of new energy vehicle

Socio-Cognitive and Affective Computing

Social cognition focuses on how people process, store, and apply information about other people and social situations. It focuses on the role that cognitive processes play in social interactions. On the other hand, the term cognitive computing is generally used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. In this sense, it is a type of computing with the goal of discovering more accurate models of how the human brain/mind senses, reasons, and responds to stimuli. Socio-Cognitive Computing should be understood as a set of theoretical interdisciplinary frameworks, methodologies, methods and hardware/software tools to model how the human brain mediates social interactions. In addition, Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects, a fundamental aspect of socio-cognitive neuroscience. It is an interdisciplinary field spanning computer science, electrical engineering, psychology, and cognitive science. Physiological Computing is a category of technology in which electrophysiological data recorded directly from human activity are used to interface with a computing device. This technology becomes even more relevant when computing can be integrated pervasively in everyday life environments. Thus, Socio-Cognitive and Affective Computing systems should be able to adapt their behavior according to the Physiological Computing paradigm. This book integrates proposals from researchers who use signals from the brain and/or body to infer people's intentions and psychological state in smart computing systems. The design of this kind of systems combines knowledge and methods of ubiquitous and pervasive computing, as well as physiological data measurement and processing, with those of socio-cognitive and affective computing

A Review of Resonant Converter Control Techniques and The Performances

paper first discusses each control technique and then gives experimental results and/or performance to highlights their merits. The resonant converter used as a case study is not specified to just single topology instead it used few topologies such as series-parallel resonant converter (SPRC), LCC resonant converter and parallel resonant converter (PRC). On the other hand, the control techniques presented in this paper are self-sustained phase shift modulation (SSPSM) control, self-oscillating power factor control, magnetic control and the H-∞ robust control technique

OBSERVER-BASED-CONTROLLER FOR INVERTED PENDULUM MODEL

This paper presents a state space control technique for inverted pendulum system. The system is a common classical control problem that has been widely used to test multiple control algorithms because of its nonlinear and unstable behavior. Full state feedback based on pole placement and optimal control is applied to the inverted pendulum system to achieve desired design specification which are 4 seconds settling time and 5% overshoot. The simulation and optimization of the full state feedback controller based on pole placement and optimal control techniques as well as the performance comparison between these techniques is described comprehensively. The comparison is made to choose the most suitable technique for the system that have the best trade-off between settling time and overshoot. Besides that, the observer design is analyzed to see the effect of pole location and noise present in the system

A Review of Resonant Converter Control Techniques and The Performances

paper first discusses each control technique and then gives experimental results and/or performance to highlights their merits. The resonant converter used as a case study is not specified to just single topology instead it used few topologies such as series-parallel resonant converter (SPRC), LCC resonant converter and parallel resonant converter (PRC). On the other hand, the control techniques presented in this paper are self-sustained phase shift modulation (SSPSM) control, self-oscillating power factor control, magnetic control and the H-∞ robust control technique

State-Feedback Controller Based on Pole Placement Technique for Inverted Pendulum System

This paper presents a state space control technique for inverted pendulum system using simulation and real experiment via MATLAB/SIMULINK software. The inverted pendulum is difficult system to control in the field of control engineering. It is also one of the most important classical control system problems because of its nonlinear characteristics and unstable system. It has three main problems that always appear in control application which are nonlinear system, unstable and non-minimumbehavior phase system. This project will apply state feedback controller based on pole placement technique which is capable in stabilizing the practical based inverted pendulum at vertical position. Desired design specifications which are 4 seconds settling time and 5 % overshoot is needed to apply in full state feedback controller based on pole placement technique. First of all, the mathematical model of an inverted pendulum system is derived to obtain the state space representation of the system. Then, the design phase of the State-Feedback Controller can be conducted after linearization technique is performed to the nonlinear equation with the aid of mathematical aided software such as Mathcad. After that, the design is simulated using MATLAB/Simulink software. The controller design of the inverted pendulum system is verified using simulation and experiment test. Finally the controller design is compared with PID controller for benchmarking purpose