Moving Students of Color from Consumers to Producers of Technology PDF Download
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Author: Rankin, Yolanda
Publisher: IGI Global
ISBN: 1522520066
Category : Education
Languages : en
Pages : 339
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Book Description
In recent years, diversity in learning environments has become a pivotal topic of conversation for educators. By enhancing underrepresented students’ computational thinking skills, it creates more room for future career opportunities. Moving Students of Color from Consumers to Producers of Technology is a comprehensive reference source that provides innovative perspectives on the need for diversity in computer science and engineering disciplines and examines best practices to build upon students’ knowledge bases. Featuring coverage on an expansive number of topics and perspectives, such as, computational algorithmic thinking, STEM diversity, and distributed mentorship, this publication is ideally designed for academicians, researchers, and students interested in efforts to broaden participation in computer science careers fields for underrepresented students.
Author: Rankin, Yolanda
Publisher: IGI Global
ISBN: 1522520066
Category : Education
Languages : en
Pages : 339
Get Book Here
Book Description
In recent years, diversity in learning environments has become a pivotal topic of conversation for educators. By enhancing underrepresented students’ computational thinking skills, it creates more room for future career opportunities. Moving Students of Color from Consumers to Producers of Technology is a comprehensive reference source that provides innovative perspectives on the need for diversity in computer science and engineering disciplines and examines best practices to build upon students’ knowledge bases. Featuring coverage on an expansive number of topics and perspectives, such as, computational algorithmic thinking, STEM diversity, and distributed mentorship, this publication is ideally designed for academicians, researchers, and students interested in efforts to broaden participation in computer science careers fields for underrepresented students.
Author:
Publisher:
ISBN: 9781522520078
Category :
Languages : en
Pages :
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Book Description
Author: Vignesh, U.
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 306
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Book Description
In the dynamic landscape of bioinformatics and blockchain technology, a profound challenge is evident: ensuring secure exchange and analysis of complex biological data while maintaining data integrity and ownership. Traditional methods fall short in seamlessly transferring genomic data, spurring the fusion of blockchain innovation and optimization algorithms as a groundbreaking solution. Biology-Inspired Optimization Techniques in Blockchain Systems directly addresses the data integrity and ownership dilemma in bioinformatics and blockchain. Despite the intricacies of genomic data, blockchain's potential solution faces obstacles like data volume and slow transactions. These challenges are adeptly overcome through optimization algorithms. The book, authored by experts in bioinformatics, blockchain, and optimization, offers a comprehensive guide, showcasing how blockchain architecture and biological data intricacies can harmonize. It provides a blueprint for using blockchain to store genomic variants and aligned reads. This work empowers developers, data scientists, and researchers to overcome technological barriers, redefining the landscape of bioinformatics and beyond.
Author: Ananth, Christo
Publisher: IGI Global
ISBN: 1668476819
Category : Mathematics
Languages : en
Pages : 238
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Book Description
Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.
Author: Vignesh, U.
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 272
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Book Description
The amalgamation of artificial intelligence (AI), optimization techniques, and blockchain is revolutionizing how to conceptualize, design, and operate aerospace systems. While optimization techniques are pivotal in streamlining aerospace processes, security challenges have recently surfaced. AI and Blockchain Optimization Techniques in Aerospace Engineering delves into the transformative impact of technologies on various facets of the aerospace industry, offering a multidimensional solution to overcome security concerns and enhance the overall efficiency of aerospace systems The book explores how machine learning reshapes aerospace systems by automating complex tasks through self/reinforced learning methods. From air traffic data analysis to flight scheduling, geographical information, and navigation, machine learning has become an indispensable tool, offering valuable insights that enhance aerospace operations. Simultaneously, blockchain technology, with its inherent characteristics of decentralization and tamper-proof ledgers, ensures transparency, accountability, and security in transactions, providing an innovative approach to data integrity and system resilience. Designed for technology development professionals, academicians, data scientists, industrial experts, researchers, and students, the book offers a panoramic view of the latest innovations in the field.
Author: Madhulika, Bhatia
Publisher: IGI Global
ISBN: 1668452561
Category : Computers
Languages : en
Pages : 249
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Book Description
Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices. Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.
Author: Emma Tumilty
Publisher: Springer Nature
ISBN: 3031143280
Category : Philosophy
Languages : en
Pages : 245
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Book Description
This book surveys the distinctions that underlie the unbound potential and existential risks of life expansion and radical modifications posed by a transhuman world. Humanness is in flux as human bodies are being hacked and altered in their quest for super wellness, super intelligence and super longevity. Now is the time to discuss how best to think about dealing with bodies that have been hacked to exceed natural physical limits or more technically, species typical functioning. Enter the advent of transhumanism to take uncertainty by the horns. According to transhumanists, death is unnecessary and medical conventions undermine the possibility to radically evolve. To biohackers, there is no need to wait to explore the risks that conventional medicine dares not. This book is of interest to anyone interested in tapping into this growing movement of modifying the human body as it is right now.
Author: Varghese, Abraham
Publisher: IGI Global
ISBN: 1799883442
Category : Medical
Languages : en
Pages : 278
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Book Description
Communicable diseases have been an important part of human history. Epidemics afflicted populations, causing many deaths before gradually fading away and emerging again years after. Epidemics of infectious diseases are occurring more often, and spreading faster and further than ever, in many different regions of the world. The scientific community, in addition to its accelerated efforts to develop an effective treatment and vaccination, is also playing an important role in advising policymakers on possible non-pharmacological approaches to limit the catastrophic impact of epidemics using mathematical and machine learning models. Controlling Epidemics With Mathematical and Machine Learning Models provides mathematical and machine learning models for epidemical diseases, with special attention given to the COVID-19 pandemic. It gives mathematical proof of the stability and size of diseases. Covering topics such as compartmental models, reproduction number, and SIR model simulation, this premier reference source is an essential resource for statisticians, government officials, health professionals, epidemiologists, sociologists, students and educators of higher education, librarians, researchers, and academicians.
Author: Rajput, Dharmendra Singh
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 318
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Book Description
Experts continue to struggle with developing methods to effectively navigate the intricate landscape of the Internet of Things (IoT). As the IoT landscape continues to expand and influence various industries, from healthcare to smart cities and beyond, scholars often find themselves facing an absence of comprehensive guidance in navigating this evolving technological landscape. The challenges are multifaceted and include the need for intelligent modeling techniques, the intricacies of managing IoT applications, and the relentless pace of technological advancements. This issue of staying well-informed and equipped to address these challenges demands an insightful solution. To tackle these challenges, Scalable Modeling and Efficient Management of IoT Applications emerges as a valuable resource, offering a multitude of effective solutions to address these concerns. This is a book that was meticulously crafted to empower scholars with the knowledge and tools they need. By tackling the scarcity of guidance on intelligent modeling techniques, the book equips readers with a profound understanding of the fundamental concepts, algorithms, and methodologies crucial for designing and managing intelligent IoT systems.
Author: Sobczak-Michalowska, Marzena
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 315
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Book Description
The need for tailored data for machine learning models is often unsatisfied, as it is considered too much of a risk in the real-world context. Synthetic data, an algorithmically birthed counterpart to operational data, is the linchpin for overcoming constraints associated with sensitive or regulated information. In high-dimensional data, where the dimensions of features and variables often surpass the number of available observations, the emergence of synthetic data heralds a transformation. Applications of Synthetic High Dimensional Data delves into the algorithms and applications underpinning the creation of synthetic data, which surpass the capabilities of authentic datasets in many cases. Beyond mere mimicry, synthetic data takes center stage in prioritizing the mathematical domain, becoming the crucible for training robust machine learning models. It serves not only as a simulation but also as a theoretical entity, permitting the consideration of unforeseen variables and facilitating fundamental problem-solving. This book navigates the multifaceted advantages of synthetic data, illuminating its role in protecting the privacy and confidentiality of authentic data. It also underscores the controlled generation of synthetic data as a mechanism to safeguard private information while maintaining a controlled resemblance to real-world datasets. This controlled generation ensures the preservation of privacy and facilitates learning across datasets, which is crucial when dealing with incomplete, scarce, or biased data. Ideal for researchers, professors, practitioners, faculty members, students, and online readers, this book transcends theoretical discourse.
