Introduction to Nanotechnology

New research into human-computer interaction seeks to consider the consumer's emotional status to provide a seamless human-computer interface. This would make it possible for people to survive and be used in widespread fields, including education and medicine. Multiple techniques can be defined through human feelings, including expressions, facial images, physiological signs, and neuroimaging strategies. This paper presents a review of emotional recognition of multimodal signals using deep learning and comparing their applications based on current studies. Multimodal affective computing systems are studied alongside unimodal solutions as they offer higher accuracy of classification. Accuracy varies according to the number of emotions observed, features extracted, classification system and database consistency. Numerous theories on the methodology of emotional detection and recent emotional science address the following topics. This would encourage studies to understand better physiological signals of the current state of the science and its emotional awareness problems.

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Multimodal Emotion Recognition using Deep Learning

In recent years, smart cities have been significantly developed and have greatly expanded their potential. In fact, novel advancements to the Internet of things (IoT) have paved the way for new possibilities, representing a set of key enabling technologies for smart cities and allowing the production and automation of innovative services and advanced applications for the different city stakeholders. This paper presents a review of the research literature on IoT-enabled smart cities, with the aim of highlighting the main trends and open challenges of adopting IoT technologies for the development of sustainable and efficient smart cities. This work first provides a survey on the key technologies proposed in the literature for the implementation of IoT frameworks, and then a review of the main smart city approaches and frameworks, based on classification into eight domains, which extends the traditional six domain classification that is typically adopted in most of the related works.

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IoT-Enabled Smart Cities: A Review of Concepts, Frameworks and Key Technologies

The distributed energy system (DES) architecture is subject to confusion about renewable energy limits, primary energy supply and energy carriers' costs. For the grid to use unreliable electricity sources, the end-user's on-demand presence in the intelligent energy management context is essential. The participation of end-users could influence the management of the system and the volatility of energy prices. By delivering auxiliary services using demand side-resource to increase system reliability, robust planning, constraint control and scheduling, consumers may support grid operators. The optimized approach to managing energy resources enhances demand response to renewable energy sources integrally, controls the demand curve with load versatility as the system requires it. The opportunity to adjust/regulate the charging profile by choosing a particular device. This article discusses a literature and policy analysis that looks at the role of energy management system aggregators and the end-users participating in subsidiary systems within Smart Grid programmers and technologies. In the implementation of aggregators for energy management systems, the objective is to understand the patterns, threats, obstacles and potential obstacles.

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Energy Management for Internet of Things via Distributed Systems

Cloud computing is the requirement based on clients and provides many resources that aim to share it as a service through the internet. For optimal use, Cloud computing resources such as storage, application, and other services need managing and scheduling these services. The principal idea behind the scheduling is to minimize loss time, workload, and maximize throughput. So, the scheduling task is essential to achieve accuracy and correctness on task completion. This paper gives an idea about various task scheduling algorithms in the cloud computing environment used by researchers. Finally, many authors applied different parameters like completion time, throughput, and cost to evaluate the system.

https://turcomat.org/index.php/turkbilmat/article/download/612/413

Task Scheduling Algorithms in Cloud Computing: A Review

Cloud computing, data mining, and big online data are discussed in this paper as hybridization possibilities. The method of analyzing and visualizing vast volumes of data is known as the visualization of data mining. The effect of computing conventions and algorithms on detailed storage and data communication requirements has been studied. When researching these approaches to data storage in big data, the data analytical viewpoint is often explored. These terminology and aspects have been used to address methodological development as well as problem statements. This will assist in the investigation of computational capacity as well as new knowledge in this area. The patterns of using big data were compared in about fifteen articles. In this paper, we research Big Data Mining Approaches in Cloud Systems and address cloud-compatible problems and computing techniques to promote Big Data Mining in Cloud Systems.

https://journal.qubahan.com/index.php/qaj/article/download/46/30

Comprehensive Survey of Big Data Mining Approaches in Cloud Systems

In recent days, increasing numbers of Internet and wireless network users have helped accelerate the need for encryption mechanisms and devices to protect user data sharing across an unsecured network. Data security, integrity, and verification may be used due to these features. In internet traffic encryption, symmetrical block chips play an essential role. Data Encryption Standard (DES) and Advanced Encryption Standard (AES) ensure privacy encryption underlying data protection standards. The DES and the AES provide information security. DES and AES have the distinction of being introduced in both hardware and applications. DES and AES hardware implementation has many advantages, such as increased performance and improved safety. This paper provides an exhaustive study of the implementation by DES and AES of field programming gate arrays (FPGAs) using both DES and AES. Since FPGAs can be defined as just one mission, computers are superior to them.

https://journal.qubahan.com/index.php/qaj/article/download/38/22

FPGA Implementations for Data Encryption and Decryption via Concurrent and Parallel Computation: A Review

Automation frees workers from excessive human involvement to promote ease of use while still reducing their input of labor. There are about 2 billion people on Earth who live in cities, which means about half of the human population lives in an urban environment. This number is rising which places great problems for a greater number of people, increased traffic, increased noise, increased energy consumption, increased water use, and land pollution, and waste. Thus, the issue of security, coupled with sustainability, is expected to be addressed in cities that use their brain. One of the most often used methodologies for creating a smart city is the Internet of Things (IoT). IoT connectivity is understood to be the very heart of the city of what makes a smart city. such as sensor networks, wearables, mobile apps, and smart grids that have been developed to harness the city's most innovative connectivity technology to provide services and better control its citizens The focus of this research is to clarify and showcase ways in which IoT technology can be used in infrastructure projects for enhancing both productivity and responsiveness. Review Article Hassan et al.; AJRCOS, 8(3): 32-48, 2021; Article no.AJRCOS.68484 33

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State of Art Survey for IoT Effects on Smart City Technology: Challenges, Opportunities, and Solutions

Many policymakers envisage using a community model and Big Data technology to achieve the sustainability demanded by intelligent city components and raise living standards. Smart cities use different technology to make their residents more successful in their health, housing, electricity, learning, and water supplies. This involves reducing prices and the utilization of resources and communicating more effectively and creatively for our employees. Extensive data analysis is a comparatively modern technology that is capable of expanding intelligent urban facilities. Digital extraction has resulted in the processing of large volumes of data that can be used in several valuable areas since digitalization is an essential part of daily life. In many businesses and utility domains, including the intelligent urban domain, successful exploitation and multiple data use is critical. This paper examines how big data can be used for more innovative societies. It explores the possibilities, challenges, and benefits of applying big data systems in intelligent cities and compares and contrasts different intelligent cities and big data ideas. It also seeks to define criteria for the creation of big data applications for innovative city services.

https://journal.qubahan.com/index.php/qaj/article/download/52/37

A Survey of Data Mining Implementation in Smart City Applications

Many applications in the real world include optimizing specific targets, such as cost minimization, energy conservation, climate, and maximizing production, efficiency, and sustainability. The optimization problem is strongly non-linear with multifunctional landscapes under several dynamic, non-linear constraints in some instances. It is challenging to address those issues. Also, with the increasing strength of modern computers, simplistic brute force methods are still inefficient and unwanted. Practical algorithms are also vital for these implementations whenever possible. Cloud computing has become an essential and popular emerging computing environment that supports on-demand services and provides internet-based services. Cloud computing allows a range of services and tools to be easily accessed from anywhere in the world. Since cloud computing has global access to its services, there will always be threats and challenges facing its servers and services, such as; task scheduling, security, energy efficiency, network load, and other challenges. In the research area, many algorithms have been addressed to solve these problems. This paper investigates relevant analysis and surveys on the above topics, threats, and outlooks. This paper offers an overview of nature-inspired algorithms, their applications, and valuation, emphasizing cloud computing problems. Many problems in science and engineering can be viewed Review Article Yahia et al.; AJRCOS, 8(2): 1-16, 2021; Article no.AJRCOS.68322 2 as optimization problems with complex non-linear constraints. Highly nonlinear solutions typically need advanced optimization algorithms, and conventional algorithms can have difficulty addressing these issues. Because of its simplicity and usefulness, nature-inspired algorithms are currently being used. There are nevertheless some significant concerns with computing and swarming intelligence influenced by evolution.

/pdf/comprehensive-survey-for-cloud-computing-based-nature-3rk1ufa76a.pdf

Shakir Fattah Kak

Papers

Comprehensive Survey of Big Data Mining Approaches in Cloud Systems

FPGA Implementations for Data Encryption and Decryption via Concurrent and Parallel Computation: A Review

State of Art Survey for IoT Effects on Smart City Technology: Challenges, Opportunities, and Solutions

A Survey of Data Mining Implementation in Smart City Applications

Comprehensive Survey for Cloud Computing Based Nature-Inspired Algorithms Optimization Scheduling