A Survey on Generative Adversarial Networks: Variants, Applications, and Training

The Generative Models have gained considerable attention in unsupervised learning via a new and practical framework called Generative Adversarial Networks (GAN) due to their outstanding data generation capability. Many GAN models have been proposed, and several practical applications have emerged in various domains of computer vision and machine learning. Despite GANs excellent success, there are still obstacles to stable training. The problems are Nash equilibrium, internal covariate shift, mode collapse, vanishing gradient, and lack of proper evaluation metrics. Therefore, stable training is a crucial issue in different applications for the success of GANs. Herein, we survey several training solutions proposed by different researchers to stabilize GAN training. We discuss (I) the original GAN model and its modified versions, (II) a detailed analysis of various GAN applications in different domains, and (III) a detailed study about the various GAN training obstacles as well as training solutions. Finally, we reveal several issues as well as research outlines to the topic.

Computer Vision for Autonomous UAV Flight Safety: An Overview and a Vision-based Safe Landing Pipeline Example

Recent years have seen an unprecedented spread of Unmanned Aerial Vehicles (UAVs, or “drones”), which are highly useful for both civilian and military applications. Flight safety is a crucial issue in UAV navigation, having to ensure accurate compliance with recently legislated rules and regulations. The emerging use of autonomous drones and UAV swarms raises additional issues, making it necessary to transfuse safety- and regulations-awareness to relevant algorithms and architectures. Computer vision plays a pivotal role in such autonomous functionalities. Although the main aspects of autonomous UAV technologies (e.g., path planning, navigation control, landing control, mapping and localization, target detection/tracking) are already mature and well-covered, ensuring safe flying in the vicinity of crowds, avoidance of passing over persons, or guaranteed emergency landing capabilities in case of malfunctions, are generally treated as an afterthought when designing autonomous UAV platforms for unstructured environments. This fact is reflected in the fragmentary coverage of the above issues in current literature. This overview attempts to remedy this situation, from the point of view of computer vision. It examines the field from multiple aspects, including regulations across the world and relevant current technologies. Finally, since very few attempts have been made so far towards a complete UAV safety flight and landing pipeline, an example computer vision-based UAV flight safety pipeline is introduced, taking into account all issues present in current autonomous drones. The content is relevant to any kind of autonomous drone flight (e.g., for movie/TV production, news-gathering, search and rescue, surveillance, inspection, mapping, wildlife monitoring, crowd monitoring/management), making this a topic of broad interest.

Narrow Genetic Diversity of Wolbachia Symbionts in Acrididae Grasshopper Hosts (Insecta, Orthoptera)

Bacteria of the Wolbachia genus are maternally inherited symbionts of Nematoda and numerous Arthropoda hosts. There are approximately 20 lineages of Wolbachia, which are called supergroups, and they are designated alphabetically. Wolbachia strains of the supergroups A and B are predominant in arthropods, especially in insects, and supergroup F seems to rank third. Host taxa have been studied very unevenly for Wolbachia symbionts, and here, we turn to one of largely unexplored insect families: Acrididae. On the basis of five genes subject to multilocus sequence typing, we investigated the incidence and genetic diversity of Wolbachia in 41 species belonging three subfamilies (Gomphocerinae, Oedipodinae, and Podisminae) collected in Turkey, Kazakhstan, Tajikistan, Russia, and Japan, making 501 specimens in total. Our results revealed a high incidence and very narrow genetic diversity of Wolbachia. Although only the strains belonging to supergroups A and B are commonly present in present, the Acrididae hosts here proved to be infected with supergroups B and F without A-supergroup variants. The only trace of an A-supergroup lineage was noted in one case of an inter-supergroup recombinant haplotype, where the ftsZ gene came from supergroup A, and the others from supergroup B. Variation in the Wolbachia haplotypes in Acrididae hosts within supergroups B and F was extremely low. A comprehensive genetic analysis of Wolbachia diversity confirmed specific features of the Wolbachia allelic set in Acrididae hosts. This result can help to elucidate the crucial issue of Wolbachia biology: the route(s) and mechanism(s) of Wolbachia horizontal transmission.

Recent Developments in State-of-the-art Silica-Modified Catalysts for Fixation of CO2 into Epoxides to Organic Carbonates

The discharge of CO2 into the atmosphere has become a crucial issue for mankind and a great threat to the environment due to escalating consequences of global warming. This grants...

Ensemble based on Accuracy and Diversity Weighting for Evolving Data Streams

Ensemble classification is an actively researched paradigm that has received much attention due to increasing real-world applications. The crucial issue of ensemble learning is to construct a pool of base classifiers with accuracy and diversity. In this paper, unlike conventional data-streams oriented ensemble methods, we propose a novel Measure via both Accuracy and Diversity (MAD) instead of one of them to supervise ensemble learning. Based on MAD, a novel online ensemble method called Accuracy and Diversity weighted Ensemble (ADE) effectively handles concept drift in data streams. ADE mainly uses the following three steps to construct a concept-drift oriented ensemble: for the current data window, 1) a new base classifier is constructed based on the current concept when drift detect, 2) MAD is used to measure the performance of ensemble members, and 3) a newly built classifier replaces the worst base classifier. If the newly constructed classifier is the worst one, the replacement has not occurred. Comparing with the state-of-art algorithms, ADE exceeds the current best-related algorithm by 2.38% in average classification accuracy. Experimental results show that the proposed method can effectively adapt to different types of drifts.

Służba na rzecz totalitarnego państwa jako przesłanka obniżenia zaopatrzenia emerytalnego funkcjonariuszy zatrudnionych w organach bezpieczeństwa w latach 1944–1990

The paper describes term of service in a totalitarian state as a basis for reducing the pension of officers employed in the security service in the years 1944–1990. The legislators decided to hold liable the officers of the communist political police by reducing their pensions again, 26 years after the transformation. In this aspect, the crucial issue is the concept of service in a totalitarian state. The thesis of the paper is that the qualification of service in a totalitarian state cannot be determined only by formal conditions, that is, the time and place of service, but should also take into account substantive criteria, especially violation of the fundamental rights of individuals by former officers.

Students’ Elements of Motivation in Joining the EFL Virtual Classroom Using the Zoom Application During the Covid 19 Pandemic

The students’ motivation in learning has been a crucial issue for many researchers so far. It is because motivation takes an important role to support the students’ learning achievement. Hence, motivation cannot be separated from the teaching and learning activities conducted by the EFL teachers. This current research was aimed at investigating the elements of the students’ motivation in joining the EFL virtual learning activities using the zoom application during the covid 19 pandemic. The research applied a qualitative descriptive approach. To collect the data, the researcher observed one elective class and interviewed some students from the class investigated. The results revealed that the students’ motivation was mostly influenced by the positive effect related to the learning situations created by the teacher when using the zoom application to conduct the teaching and learning activities. This also implied that the zoom application could lead the teachers to think of being creative in conducting the virtual teaching and learning activities.

Speech Scrambling based on Particle Swarm Optimisation

Securing any communication system where important data may be transmitted through the channel is a very crucial issue. One of the good solutions in providing security for the speech is to use speech scrambling techniques. The chaotic system used in security has properties that make it a good choice for scrambling speech signal and the optimisation algorithm can provide a perfect performance when used to enhance the hybrid of more than one method. In this paper, we suggest a system that uses an optimisation method, namely, particle swarm optimisation. The evaluation measures prove that the output of the optimisation method has better performance among the methods used in the comparison, including chaotic maps and hybrid chaotic maps.

Framework for CLIL materials for Russian heritage language learners

The increasing number of immigrants made heritage language learning a crucial issue of 21-st century education. The neediness for an effective educational approach in this field leaded to CLIL (Content and Language Integrated Learning). CLIL materials are high-contextualized by age, skills, language, subject content, etc. So, teachers ought to become materials designers to provide their learners with an effective tool of learning. Usually, teachers did not specifically train for materials design. Thus, easy-to-use framework for materials is essential to provide high-quality materials. This article provides a framework for CLIL materials design for Russian heritage language learners. The framework is based on the main materials design principles, heritage learners` pedagogical needs, and CLIL-specific materials design principles. It is written in the easy-to-use form of a checklist. The checklist has seven sections and 32 questions. The framework may be used in different contexts of teachers from different countries who use CLIL to teach the Russian heritage language.

قضية خلق القرآن عند الجبرية والمعتزلة وأهل السنة

The discussion of khalqul qur'an is a very crucial issue among the Mutakallimin. The Jabariyyah and Mu'tazilah groups say that the Qur'an is a creature in order to purify Allah from human-like characteristics. In fact, saying khalqul qur'an (the Qur'an is a creature) is the same as negating the nature of God, in the form of kalam. Belief like this will lead to three imperatives: first, as if God as the essence of the nature is a creature. Second, Allah is a mute Rabb, while being mute is a deficiency trait. Third, Allah's knowledge is a creature, because the Qur'an is His knowledge, then how could Allah have created knowledge first in order to have knowledge. Therefore the scholars of the Ahli Sunnah are unanimously agreed that the Qur'an is kalamullah. Among the scholars of the Ahli Sunnah who are very firm in defending the beliefs of the Sunnah are Imam Ahmad bin Hanbal. He not only gave strong arguments, but also refuted the group that said khalqul qur'an with a solid rebuttal. Based on a qualitative method and a comparative critical approach, it was found that, first, Jabariyyah and Mu'tazilah agreed that the Qur'an was a creature. Second, the Sunnah experts in general and Imam Ahmad bin Hanbal in particular insist that the Qur'an is the kalamullah. Third, when their arguments are found, the strongest is the opinion of the Ahli Sunnah. The basis for this difference of opinion is based on their beliefs about the nature of Allah.