No abstract

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.

In this paper, several works has been presented related to the clustering parallel computing for distributed system. The trend of the paper is to focus on the strength points of previous works in this field towards enhancing performance of the distributed systems. This concentration conducted via presenting several techniques where each of them has the weak and strong features. The most challenging points for all techniques vary from increasing the performance of the system to time responding to overcome overhead running of the system. For more specific addressing concurrent computation besides parallel computing classifications for distributed systems, this paper depended comprehensive features study and comparison between SYNC and ASYNC Modes.

This paper produces an efficient proposed student affairs system for Duhok Polytechnic University (DPU) called DPU Electronic Student Affairs System (DPU-ESAS). The proposed system consists of thirteen modules that provide four group of services, which are (student services: registration, ID card, postponement, transfer and waiver, certificate of graduation, Non-failure year and absence), (department services: plan acceptance and minimum limits), and (institution service: decisions approving), and (university service: authentication, decision approving and statistics). The proposed DPU-ESAS is designed according to the structure of DPU, which contains two different study systems. These systems are four years studying system depended at the colleges, and two years studying system for the institutes. The obtained results recorded and evaluated via special questionnaires form (system usability scale) that checked by students and staff of the same institutions. The evaluation score of the questionnaire is (72.44%) which can be considered as a good percentage.

The ability to provide massive data storage, applications, platforms plus many other services leads to make the number of clouds services providers been increased. Providing different types of services and resources by various providers implies to get a high level of complexity. This complexity leads to face many challenges related to security, reliability, discovery, service selection, and interoperability. In this review, we focus on the use of many technologies and methods for utilizing the semantic web and ontology in cloud computing and distributed system as a solution for these challenges. Cloud computing does not have an own search engine to satisfy the needs of the providers of the cloud service. Using ontology enhances the cloud computing self-motivated via an intelligent framework of SaaS and consolidating the security by providing resources access control. The use RDF and OWL semantic technologies in the modeling of a multi-agent system are very effective in increases coordination the interoperability. One of the most efficient proposed frameworks is building cloud computing marketplace that collects the consumer's requirements of cloud services provider and managing these needs and resources to provide quick and reliable services.

Physical layer protection, which protects data confidentiality using information-theoretic methods, has recently attracted a lot of research attention. Using the inherent randomness of the transmission channel to ensure protection in the physical layer is the core concept behind physical layer security. In 5G wireless communication, new challenges have arisen in terms of physical layer security. This paper introduces the most recent survey on various 5G technologies, including millimeter-Wave, massive multi-input multiple outputs, microcells, beamforming, full-duplex technology, etc. The mentioned technologies have been used to solve this technology, such as attenuation, millimeter-Wave penetration, antenna array architecture, security, coverage, scalability, etc. Besides, the author has used descriptions of the techniques/algorithms, goals, problems, and meaningful outcomes, and the results obtained related to this approach were demonstrated.

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 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.

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.