الصفحة 31
الصفحة 31
Design Thinking for Visual Communication
Identifies methods and thought processes used by designers in order to start the process that eventually leads to a finished piece of work. Step-by-step guidance for each part of the process is highlighted by real-life case studies, enabling the student to see teaching in practice. This focus on ideas and methods eschews an abstract, academic approach in favour of a useable approach to design as a problem-solving activity. The new edition now includes contributions from a broader international range of design practices and adds depth to existing case studies by looking in greater detail at some of the processes used
Design of Ultra Wideband Antenna Matching Networks : Via Simplified Real Frequency Technique
Design of Ultra Wideband Antenna Matching Networks: via Simplified Real Frequency Technique (SRFT) is the first of its kind and expected to fill a very important gap in the field of wireless communication.
Design of adaptive finite Element software : The finite element toolbox ALBERTA
During the last years, scientific computing has become an important research branch located between applied mathematics and applied sciences and engineering. Highly efficient numerical methods are based on adaptive methods, higher order discretizations, fast linear and non-linear iterative solvers, multi-level algorithms, etc. Such methods are integrated in the adaptive finite element software ALBERTA. It is a toolbox for the fast and flexible implementation of efficient software for real life applications, based on modern algorithms. ALBERTA also serves as an environment for improving existent, or developing new numerical methods in an interplay with mathematical analysis and it allows the direct integration of such new or improved methods in existing simulation software.
Design ethnography : Epistemology and methodology
This book describes methods for research on and research through design. It posits that ethnography is an appropriate method for design research because it constantly orients itself, like design projects, towards social realities.
Dermatoethics : Contemporary ethics and professionalism in dermatology
This extensively updated textbook reviews the ethical issues faced within dermatology. Bringing together practical real-life case scenarios and scholarly analysis, it covers the foundations of bioethics, as well as ethical issues associated with the various roles dermatologists play, including clinician, professional, educator, business person, and scholar. New chapters on the ethics of dermatologic care during pandemics, non-traditional interventions, private equity in dermatology, self-care and improvement, skin cancer screening, maintenance of certification, the ethics of clinical trial design are also included.
Dependable computing ; 2nd Latin-American symposium, LADC 2005, Salvador, Brazil, October 25-28, 2005 : proceedings
Contains the proceedings of the 'Second Latin-American Symposium' on Dependable Computing, LADC 2005. This book comprises 16 papers presented together with 3 invited talks. The papers are organized in topical sections on evaluation, certification, modelling, embedded systems, time, and distributed systems algorithms.
Dental secrets
Offering practical tips and expert answers to topics in dentistry and oral medicine, Dental Secrets, 4th Edition provides an ideal preparation tool for exams, clinical rotations, and board certification. A concise, illustrated Q & A format covers key areas such as oral pathology and radiology, periodontology, endodontics, restorative dentistry, prosthodontics, orthodontics, infection control, and oral and maxillofacial surgery. Written by Stephen Sonis and a team of expert contributors, this mini-reference makes it easier to prepare for real-world clinical scenarios and review for the NBDE and other certification exams
Dental Perspectives on Human Evolution : State of the Art Research in Dental Paleoanthropology
The objective of the volume is to bring together, in one collection, the most innovative dental anthropological research as it pertains to the study of hominid evolution. In the past few decades both the numbers of hominin dental fossils and the sophistication of the techniques used to analyze them have increased substantially. Contributions focus on dental morphometrics, growth and development, diet and dental evolution. The contributed chapters include crown morphology, microstructure, microwear, stable isotope data, recent genetic research and new methodologies, including 3-D imaging, confo.
Demand Planning : Processi, metodologie e modelli matematici per la gestione della domanda commerciale = Demand Planning : Processes, methodologies and mathematical models for managing commercial demand
Il libro Demand Planning analizza metodi quantitativi, modelli matematici e processi aziendali per la gestione e la pianificazione della domanda commerciale delle aziende, relativa ai prodotti ed ai servizi realizzati.
Delivery of drugs ; Vol.2 : Expectations and realities of multifunctional drug delivery systems
Examines the formulation of micro-nanosized drug delivery systems and recaps opportunities for using physical methods to improve efficacy via mechano-, electroporation. The book highlights innovative delivery methods like PIPAC, including discussions on the regulatory aspects of complex injectables. Written by a diverse range of international researchers from industry and academia, the chapters examine specific aspects of characterization and manufacturing for pharmaceutical applications as well as regulatory and policy aspects.This book connects formulation scientists, regulatory experts, engineers, clinical experts and regulatory stakeholders.
Deformable Models : Theory and Biomaterial Applications
Deformable Models: Theory and Biomaterial Applications is the second installation in the two-volume set Deformable Models which provides a wide cross-section of the methods and algorithms of variational and PDE methods in biomedical image analysis. The chapters are written by well-known researchers in this field, and the presentation style goes beyond an intricate abstraction of the theory into real application of the methods and description of the algorithms that were implemented. As such these chapters will serve the main goal of the editors of the volumes in bringing down to earth the latest in variational and PDE methods in modeling of soft tissues, covering the theory, algorithms, and applications of level sets and deformable models in medical image analysis.
Deformable Models : Biomedical and Clinical Applications
Deformable Models: Biomedical and Clinical Applications is the first entry in the two-volume set which provides a wide cross-section of the methods and algorithms of variational and Partial-Differential Equations (PDE) methods in biomedical image analysis. The chapters of Deformable Models: Biomedical and Clinical Applications are written by the well-known researchers in this field, and the presentation style goes beyond an intricate abstraction of the theory into real application of the methods and description of the algorithms that were implemented. As such these chapters will serve the main goal of the editors of these two volumes in bringing down to earth the latest in variational and PDE methods in modeling of soft tissues.
Deepfake detection = اكتشاف التزييف العميق
In the rapidly evolving era of artificial intelligence, addressing the escalating threats of deepfake technology becomes a necessity because of the increasing sophistication of AI algorithms in generating deceptive content, and since it threatens the integrity of information across diverse data. The main objective is to build a sophisticated AI-driven system to detect different types of deepfake in text, audio, and images. In English text deepfake detection, multiple pre-trained tokenizers have been used, but XLNET and BERT stand out with identifying objects outside the dataset with an accuracy of 0.9809 and both have been generalized & trained using LSTM. In Arabic text deepfake detection, Arabert has been trained using LSTM which led with an accuracy of 99.53% by generalizing the model. Both English and Arabic datasets have been generated to enhance the accuracy and effectiveness of the models. Audio deepfake detection has been generalized too, using Random Forest with an accuracy of 98.259%.
Deepfake detection
Recently, various techniques of manipulating the video content have become available to everyone – online, one can find free applications e.g., for face swapping in videos. Such universal accessibility carries a notable risk of flooding online content with false information, affecting not only the greats of this world, but also the whole societies, also the rapid progress in synthetic image generation and manipulation has now come to a point where it raises significant concerns for the implications towards society. It is therefore necessary to develop a verification tool that will help assess the authenticity of the videos posted on the internet. This project describes the approach of using artificial intelligence solutions to detect doctored videos.
Deepfake detection
The rise of large language models (LLMs) and the increasing sophistication of deepfake images have made detecting synthetic content a pressing challenge. Several approaches have been proposed to tackle this problem, including statistical analysis, and machine learning algorithms. In this project, A novel zero-shot approach is proposed that utilizes the power of LLMs to detect fake text. The pre-trained LLM is fine-tuned to enhance its ability to differentiate real and fake text. The approach uses the LLM to detect text by analyzing the log probabilities of the text. For detecting fake images, computer vision algorithms and neural networks are used to analyze facial features. The facial region is cropped and preprocessed and the neural network identifies patterns indicative of synthetic content.
Deepfake
The technology used to create such digital content has quickly become accessible to the masses, such as “DEEPFAKE.” Deep fakes refer to manipulated videos, or other digital representations produced by sophisticated artificial intelligence, that yields to synthesize a sequence of face images and voices of characters corresponding to their identities, such as voice tone, facial expression, with a good lip synchronization. Therefore, this study is about developing real-time video generation software, which generates a target video from a single input image. Several methods and algorithms have been applied to detect, analyze personalize facial expression, voice and natural head poses to present a life-like image instead of a low quality one.
Deep learning pipeline : Building a deep learning model with TensorFlow
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets.
Deep learning approach for text summarization
Machine learning and deep learning, as we know, have started ruling over almost every field in the computing industry and so, has revolutionized the process of text summarization too. Automatic text summarization is an advancing realm of the natural language processing research in which concise textual summaries are generated from lengthy input documents. Extensive research has been carried out on how automatic summarization can be prosecuted through various extractive and abstractive techniques. In this paper, we address all the approaches to text summarization and present the modus operandi of an Architecture called Encoder Decoder, under the machine learning approach.
Deep learning and computer vision in remote sensing-II
Computer vision (CV) have seen a massive rise in popularity in the remote sensing field over the last few years. This success is mostly due to the effectiveness of deep learning (DL) algorithms. However, remote sensing data acquisition and annotation, as well as information extraction from massive remote sensing data, are still challenging. This reprint collected novel developments in the field of deep learning and computer vision methods for remote sensing. Papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems, have been published. With practical examples and real-world case studies, this reprint provides a valuable resource for researchers, professionals, and students seeking to harness the power of deep learning in the field of remote sensing.
Deep learning and computer vision in remote sensing-I
In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
