This paper focus on the asymptotic synchronization issue of coupled time-delay PDSs via pinning control and boundary control. The asymptotic synchronization of PDSs with both node-delay and coupling delay is discussed firstly. Then the pinning controller and boundary controller are also presented in order to achieve the asymptotic synchronization. Further more, synchronization criteria are established by using the Lyapunov function method and inequality techniques. Obviously, it is an efficient control technique to combine the pinning control with the boundary control for the asymptotic synchronization of the PDSs. Finally, an example of digital simulation is used to elucidate the practicability and validity of our control method and the correctness of the theorem.

The motivations behind 5G networks include seamless handovers, higher data rates, lower latencies of about one millisecond, and enhanced coverage compared to 4G networks. To achieve these goals, network densification has been implemented to cope with increasing capacity demands. Networks with ultra-densification have large numbers of heterogeneous small cell deployments such as femto-cells, relays and microcells which complicate mobility management, resulting in unnecessary, frequent, and ping-pong handovers as UEs move within the network. To address these challenges, state of the art approaches using fuzzy logic, adaptive neuro-networks or their combination have been proposed. However, these approaches majorly address the QoS issues, ignoring the security aspect of handovers. In this paper, a handover protocol that incorporates both security and QoS in the handover process is proposed. The simulation results showed that this protocol reduced handover latency, packet losses, number of executed handovers and ping pong rate by 56.1%, 38.8 %, 74.6% and 24.1% respectively. In addition, the developed protocol yielded a 27.1% increase in the handover success rate, and a 27.3% reduction in handover failure rate. This protocol was also shown to be robust against de-synchronization and session hijacking attacks.

Solving an optimization task in any domain is a very challenging problem, especially when dealing with nonlinear problems and non-convex functions. Many meta-heuristic algorithms are very efficient when solving nonlinear functions. A meta-heuristic algorithm is a problem-independent technique that can be applied to a broad range of problems. In this experiment, some of the evolutionary algorithms will be tested, evaluated, and compared with each other. We will go through the Genetic Algorithm, Differential Evolution, Particle Swarm Optimization Algorithm, Grey Wolf Optimizer, and Simulated Annealing. They will be evaluated against the performance from many points of view like how the algorithm performs throughout generations and how the algorithm’s result is close to the optimal result. Other points of evaluation are discussed in depth in later sections.

Nowadays, within the period of having huge information, literary information is rapidly developing and is accessible in numerous diverse languages. Often due to time limitations, we are not able to devour all the information that is accessible. With the fast-paced world, it is troublesome to peruse all the textual content. Therefore, the necessity for content summarization comes to the spotlight. It is in this manner we are able to summarize the content so that it gets easier to ingest the data, keeping up the substance, and understanding the data. A few content summarization approaches have been presented in the past for a long time for English and some other European languages but there are startlingly few methods that can be found for the local languages of India. This paper presents a study of extractive content summarization methods for multiple Indian and international languages like Hindi, Kannada, Telugu, Marathi, German, French, etc. This paper proposes a system of Optical Character Recognition (OCR) which extracts the content from the uploaded picture. The main motive of the OCR is the creation of editable records from documents that already exist or picture files. The Optical Character Recognition also works on sentence discovery to protect a document’s structure. The paper also presents a strategy for programmed sentence extraction utilizing the Text-rank algorithm. This approach relegates scores to the sentences by weighting the highlights like term frequency, word events, and noun weight and expressions. The outcome of this work demonstrates that our approach gives more accuracy and also provides text-to-speech with the interpretation of one language to another while maintaining coherence and accomplishes superior results when compared with existing methods.

Computer and Internet-Based Communication Technologies aka Cybernetic Communication play important role in communication over a distance. This work gauged uses of cybernetic communication as major means of communication during COVID-19 outbreak based on measured (Social Distance, Self-Quarantine, Isolation, Lockdown) put in place by the government to curtail spreading of the disease in Nigeria. Data were randomly collected through online publication, newsprints, and telephone calls from 290 sampled population. Data Collected were discussed and analyses using Pie chart, Percentile, and Histogram as statistical tools. Findings shows that Cybernetic communication play major role to bridge the communication gaps between the Nigerian people during the outbreak of the Covid-19 outbreak as majority of Nigerians spent more hours using cybernetic tools to communicate and more money was spent on airtime and data to keep their mobile phone running during the trying period of COVID-19 rash. Majority of the sampled population spent their useful time on social medial as in Facebook, whattsapp, Instagram, YouTube and for social interactions and meetings. The implications of our findings are: majority of Nigeria may have computer linked diseases or syndrome such Sleeping Problems and others due to prolong uses of computers; the cybernetic tools (mobile phones, computer, laptop etc.) used by the infected people may be a carrier of the symptoms in the nearest future; Nigerians spent more on data and airtime credit in this trying period and it may affect their financial economy later. This work ends with proposal for roles to be played by Nigeria government and other stakeholders in cybernetic sustained communication processes for pandemic response and to prevent future outbreak of covid-19 after overcoming recent happenings, and also recommended organization strategy for workforce continuity and recovery.

The Internet of Things (IoT) became the basic axis in the information and network technology to create a smart environment. To build such an environment; it needs to use some IoT simulators such as Cooja Simulator. Cooja simulator creates an IoT environment and produces an IoT routing dataset that contains normal and malicious motes. The IoT routing dataset may have redundant and noisy features. The feature selection can affect on the performance metrics of the learning model. The feature selection can reduce complexity and over-fitting problem. There are many approaches for feature selection especially meta-heuristic algorithms such as Cuckoo search (CS). This paper presented a proposed model for feature selection that is built on using a standard cuckoo search algorithm to select near-optimal or optimal features. A proposed model may modify the CS algorithm which has implemented using Dagging with base learner Bayesian Logistic Regression (BLR). It increases the speed of the CS algorithm and improves the performance of BLR. Support Vector Machine (SVM), Deep learning, and FURIA algorithms are used as classification techniques used to evaluate the performance metrics. The results have demonstrated that the algorithm proposed is more effective and competitive in terms of performance of classification and dimensionality reduction. It achieved high accuracy that is near to 98 % and low error that is about 1.5%.

Cloud computing is actually a developing ideal to provide on-demand IT services to end-users. The get accesses to command to information situated in the cloud is just one of the essential parts to enable service to change right into the cloud. Some latest works offer access management models ideal for the cloud; nonetheless, there are essential shortages that need to be resolved in this field. This work offers a progression in the state-of the-craft to get access to management for cloud processing. We illustrate a higher meaningful consent version that permits the management of state-of-the-art attributes such as role-based to get access to management (RBAC), hierarchical RBAC (hRBAC), relative RBAC (cRBAC) and also ordered objects (HO). The get access to management design takes benefit of the logic formalism delivered due to the Semantic Internet technologies to designate both the rooting framework and also the certification style, as well as the rules worked with to guard the get access to sources in the cloud. The access control style has actually been specially established taking into consideration the multi-tenancy model of this type of environment. Moreover, this rely on a style that allows a powdery meaning of what information is on call for every specific tenant has been actually illustrated. This multi-tenant endorsement model permits a fine-grained definition of information sets is being available for the individual tenants. Certainly this assures formation of business associations among cloud tenants resulting in confederation and association agreements. The suggested model has actually been confirmed via verification of concept implementation of the gain access to management device for OpenStack along with promising efficiency end results.

The 21st century is the digital world, where everything is done through electronics and autonomous devices. In this era where no one wants to do any task which takes more effort and time, they do the same task by digital which makes effortless as well as time-saving. During COVID-19 pandemic many exams were discontinued. Remote Proctored Theory and Objective Online Examination is a case study for providing a solution for conducting online examination instead of manual examination. This will be a web application that allows examinees to conduct the exam for examinees by colleges/universities/organizations. This application will allow your theory as well as objective type’s examinations for professional and non-professional courses.

This paper explains how to detect the 2D pose of multiple people in an image. We use in this paper Part Affinity Fields for Part Association (It is non-parametric representation), Confidence Maps for Part Detection, Multi-Person Parsing using PAFs, Simultaneous Detection and Association, this method achieve high accuracy and performance regardless the number of people in the image. This architecture placed first within the inaugural COCO 2016 key points challenge. Also, this architecture exceeds the previous state-of-the-art result on the MPII Multi-Person benchmark, both in performance and efficiency.

The research on group mobility in the opportunity network concerns what nodes’ mobility may bring about, in contrast to the preciously-proposed group mobility approaches that are unilateral in the thoughts of the constitution of groups by nodes, resulting in, the distortion of reality to reflect group behavior characteristics that are revealed in the situations of their application. Based on the Spectral Clustering algorithm, this paper proposes the group mobility model (SCM), which takes the advantage of node’s own properties, such as its spatial position, to set up node’s affinity matrix, extract main characteristics from arbitrarily distributed nodes with the aid of spectral clustering algorithm, and regarding the needs of a task assigned cluster nodes dynamically in a fixed time. The model depicts truly and effectively the group characteristics of node’s mobility, accomplish the conducts of group mobility and clustering well.