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Infertility has recently emerged as a severe medical problem. The essential elements in male infertility are sperm morphology, sperm motility, and sperm density. In order to analyze sperm motility, density, and morphology, laboratory experts do a semen analysis. However, it is simple to err when using a subjective interpretation based on laboratory observation. In this work, a computer-aided sperm count estimation approach is suggested to lessen the impact of experts in semen analysis. Object detection techniques concentrating on sperm motility estimate the number of active sperm in the semen. This study provides an overview of other techniques that we can compare. The Visem dataset from the Association for Computing Machinery was used to test the proposed strategy. We created a labelled dataset to prove that our network can detect sperms in images. The best not-super tuned result is mAP 72.15.

The deployment of optical network infrastructure and development of new network services are growing rapidly for beyond 5/6G networks. However, optical networks are vulnerable to several types of security threats, such as single-point failure, wormhole attacks, and Sybil attacks. Since the uptake of e-commerce and e-services has seen an unprecedented surge in recent years, especially during the COVID-19 pandemic, the security of these transactions is essential. Blockchain is one of the most promising solutions because of its decentralized and distributed ledger technology, and has been employed to protect these transactions against such attacks. However, the security of blockchain relies on the computational complexity of certain mathematical functions, and because of the evolution of quantum computers, its security may be breached in real-time in the near future. Therefore, researchers are focusing on combining quantum key distribution (QKD) with blockchain to enhance blockchain network security. This new technology is known as quantum-secured blockchain. This article describes different attacks in optical networks and provides a solution to protect networks against security attacks by employing quantum-secured blockchain in optical networks. It provides a brief overview of blockchain technology with its security loopholes, and focuses on QKD, which makes blockchain technology more robust against quantum attacks. Next, the article provides a broad view of quantum-secured blockchain technology. It presents the network architecture for the future research and development of secure and trusted optical networks using quantum-secured blockchain. The article also highlights some research challenges and opportunities.

This paper reports a simple three-dimensional autonomous system with a single stable node equilibrium. The system has a constant controller which adjusts the dynamic of the system. It is revealed that the system exhibits both chaotic and non-chaotic dynamics. Moreover, chaotic or periodic attractors coexist with a single stable equilibrium for some control parameter based on initial conditions. The system dynamics are studied by analyzing bifurcation diagrams, Lyapunov exponents, and basins of attractions. Beyond a fixed-point analysis, a new analysis known as connecting curves is provided. These curves are one-dimensional sets of the points that are more informative than fixed points. These curves are the skeleton of the system, which shows the direction of flow evolution.

Cyber-attack detection via on-gadget embedded models and cloud systems are widely used for the Internet of Medical Things (IoMT). The former has a limited computation ability, whereas the latter has a long detection time. Fog-based attack detection is alternatively used to overcome these problems. However, the current fog-based systems cannot handle the ever-increasing IoMT’s big data. Moreover, they are not lightweight and are designed for network attack detection only. In this work, a hybrid (for host and network) lightweight system is proposed for early attack detection in the IoMT fog. In an adaptive online setting, six different incremental classifiers were implemented, namely a novel Weighted Hoeffding Tree Ensemble (WHTE), Incremental K-Nearest Neighbors (IKNN), Incremental Naïve Bayes (INB), Hoeffding Tree Majority Class (HTMC), Hoeffding Tree Naïve Bayes (HTNB), and Hoeffding Tree Naïve Bayes Adaptive (HTNBA). The system was benchmarked with seven heterogeneous sensors and a NetFlow data infected with nine types of recent attack. The results showed that the proposed system worked well on the lightweight fog devices with ~100% accuracy, a low detection time, and a low memory usage of less than 6 MiB. The single-criteria comparative analysis showed that the WHTE ensemble was more accurate and was less sensitive to the concept drift.

The impact of polymer-based slow-release urea formulations on soil microbial N dynamics in potatoes has been sparingly deciphered. The present study investigated the effect of a biodegradable nano-polymer urea formulation on soil enzymatic activities and microflora involved in the N cycling of potato (Solanum tuberosum L.). The nano-chitosan-urea composite (NCUC) treatment significantly increased the soil dehydrogenase activity, organic carbon content and available potassium compared to the conventional urea (CU) treatment. The soil ammonical nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) contents and urease activity were significantly decreased in the NCUC-amended soil. The slow urea hydrolysis rate led to low concentrations of NH4+-N and NO3−-N in the tested potato soil. Furthermore, these results corroborate the low count of ammonia oxidizer and nitrate reducer populations. Quantitative PCR (q-PCR) studies revealed that the relative abundance of eubacterial (AOB) and archaeal ammonia-oxidizing (AOA) populations was reduced in the NCUC-treated soil compared to CU. The abundance of AOA was particularly lower than AOB, probably due to the more neutral and alkaline conditions of the tested soil. Our results suggest that the biodegradable polymer urea composite had a significant effect on the microbiota associated with soil N dynamics. Therefore, the developed NCUC could be used as a slow N-release fertilizer for enhanced growth and crop yields of potato.

This work is partially supported by the project "Prediction of diseases through computer assisted diagnosis system using images captured by minimally-invasive and non-invasive modalities", Computer Science and Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing, Jabalpur India (under ID: SPARCMHRD-231). This work is also partially supported by the project "Smart Solutions in Ubiquitous Computing Environments", Grant Agency of Excellence, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic (under ID: UHK-FIM-GE-2204/2021); project at Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-20H04, Malaysia Research University Network (MRUN) Vot 4L876 and the Fundamental Research Grant Scheme (FRGS) Vot5F073 supported by the Ministry of Education Malaysia for the completion of the research., Calculating and monitoring customer churn metrics is important for companies to retain customers and earn more profit in business. In this study, a churn prediction framework is developed by modified spectral clustering (SC). However, the similarity measure plays an imperative role in clustering for predicting churn with better accuracy by analyzing industrial data. The linear Euclidean distance in the traditional SC is replaced by the non-linear S-distance (Sd). The Sd is deduced from the concept of S-divergence (SD). Several characteristics of Sd are discussed in this work. Assays are conducted to endorse the proposed clustering algorithm on four synthetics, eight UCI, two industrial databases and one telecommunications database related to customer churn. Three existing clustering algorithms-k-means, density-based spatial clustering of applications with noise and conventional SC-are also implemented on the above-mentioned 15 databases. The empirical outcomes show that the proposed clustering algorithm beats three existing clustering algorithms in terms of its Jaccard index, f-score, recall, precision and accuracy. Finally, we also test the significance of the clustering results by the Wilcoxon's signed-rank test, Wilcoxon's rank-sum test, and sign tests. The relative study shows that the outcomes of the proposed algorithm are interesting, especially in the case of clusters of arbitrary shape., project "Prediction of diseases through computer assisted diagnosis system using images captured by minimally-invasive and non-invasive modalities", Computer Science and Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing SPARCMHRD-231, project "Smart Solutions in Ubiquitous Computing Environments", Grant Agency of Excellence, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic UHK-FIM-GE-2204/2021, Universiti Teknologi Malaysia (UTM) 20H04, Malaysia Research University Network (MRUN) 4L876, Fundamental Research Grant Scheme (FRGS) by the Ministry of Education Malaysia 5F073

Increasing demand for modern treatments and significant profit margins are strong incentives for investors and producers. However, the production and use of medical devices is subject to a number of laws, regulations, strict standards, and certification processes. Therefore, the aim of this paper is to analyze patent activity based on the example of the selected country (Czech Republic), compare it with selected foreign countries, and discuss the development of this industry in the context of new medical device regulation (MDR) implementation. The paper is based on the theoretical concept of the relationship between regulation and innovation. The main challenge in the implementation of the new medical device regulations lies in the area of innovation. This is because most innovative research in the medical device sector is undertaken by small to medium enterprises (SMEs) rather than by large companies. SMEs are more vulnerable than big companies when it comes to development because the accompanying administrative costs can be so high that it may force the company to leave the market. Given that the main reason for the existence of economic regulations are various forms of market failure, which occurs when market mechanisms do not lead to results that benefit society, any attempts to redress this situation should naturally lead to greater benefits for society and hence benefits for the given industry as well.

Next to climate change on the list of challenges faced by humankind in today&rsquo, s technological age is energy management. While &ldquo, smart&rdquo, ideas continue to gather momentum as some of the ways earmarked to combat the menace of a changing climate, coupled with efficient management of energy, research and development in the blockchain is not retracting, recently giving rise to digital currencies capable of fueling massive energy consumption via mining of &ldquo, crypto-coins&rdquo, Given that sustainability is a crucial goal in the design of smart cities nowadays, there are currently no assurances of sustainable cities where cryptocurrency mining is at full scale. Nevertheless, alternative energy sources may come to the rescue in no distant time. In this paper, we contextualize energy-use in smart cities through mining of virtual currencies, in order to predict whether or not smart cities can truly be sustainable if crypto-mining is sustained. An attempt is also made to emphasize the possible ways of reducing energy use and all activities involving digital currencies by seeking to replace &ldquo, Proof of Work&rdquo, (PoW) with improved alternatives.

Today’s digital society is interconnected and networked, with modern smart devices ubiquitously built into and embedded within smart environments and other environments, where people (their users) typically live. It is very important to mention that sensorial awareness of an environment depends on one’s current location and equipment, as well as the equipment’s real-time capabilities. Personal sensorial information is considered to be the key factor for progress in the improvement of the productivity of everyday life and creation of a smart surrounding environment. This paper describes the design, implementation, and testing process of a new sensorial framework based on the current possibilities created by ubiquitous smart mobile devices with sensors, which involves computing power and battery power issues. The two parts of the proposed framework have been designed, implemented, and tested. The client part is represented by a front-end mobile application, and the back-end part is represented by a server-side application. The analysis of the data, captured during the testing phase, involves the analysis of the processing time, battery consumption, and transmitted data amount. This analysis reveals that Transmission Control Protocol (TCP) and user datagram protocol (UDP) protocols have a comparable performance, although TCP is preferable for use in local networks. In comparison to other solutions such as MobiSense or Feel the World framework, the final solution of the proposed and developed sensorial framework has two main capabilities, which are the security support and social networking possibilities. The advantage of the MobiSense platform is the existence of several real-world applications, whereas the proposed sensorial framework needs to be verified in the massive context of many users in real time.

The need for smart and sustainable communication systems has led to the development of mobile communication networks. In turn, the vast functionalities of the global system of mobile communication (GSM) have resulted in a growing number of subscribers. As the number of users increases, the need for efficient and effective planning of the &ldquo, limited&rdquo, frequency spectrum of the GSM is inevitable, particularly in densely-populated areas. As such, there are ongoing discussions about frequency (channel) allocation methods to resolve the challenges of channel allocation, which is a complete NP (Nondeterministic Polynomial time) problem. In this paper, we propose an algorithm for channel allocation which takes into account soft constraints (co-channel interference and adjacent channel interference). By using the Manhattan distance concept, this study shows that the formulation of the algorithm is correct and in line with results in the literature. Hence, the Manhattan distance concept may be useful in other scheduling and optimization problems. Furthermore, this unique concept makes it possible to develop a more sustainable telecommunication system with ease of connectivity among users, even when several subscribers are on a common frequency.