Performance evaluation of framework of VoIP/SIP server under virtualization environment along with the most common security threats

Neural Computing and Applications - Virtualization is the central point empowering cloud infrastructure. Many services, such as web-based applications, databases, and instant messaging servers, are...     

Animal‐borne wireless network: Remote imaging of community ecology

This article describes the design, construction, and field‐testing of a standalone networked animal‐borne monitoring system conceived to study community ecology remotely. The system consists of an assemblage of identical battery‐powered sensing devices with wireless communication capabilities that are each collar‐mounted on a study animal and together form a mobile ad hoc network. The sensing modalities of each device include high‐definition video, inertial accelerometry, and location resolved via a global positioning system module. Our system is conceived to use information exchange across the network to enable the devices to jointly decide without supervision when and how to use each sensing modality. The ultimate goal is to extend battery life while making sure that important events are appropriately documented. This requires judicious use of highly informative but power‐hungry sensing modalities, such as video, because battery capacity is constrained by stringent weight and dimension restrictions. We have proposed algorithms to regulate sensing rates, data transmission among devices, and triggering for video recording based on location and animal group movements and configuration. We have also developed the hardware and firmware of our devices to reliably execute these algorithms in the exacting conditions of real‐life deployments. We describe validation of the performance and reliability of our system using deployment results for a mission in Gorongosa National Park (Mozambique) to monitor two species in their natural habitat: the waterbuck and the African buffalo. We present movement data and snapshots of animal point‐of‐view videos collected by 14 fully operational devices collared on 10 waterbucks and 4 buffaloes.     

University Learning and Anti-Plagiarism Back-End Services

Plagiarism refers to the use of other people’s ideas and information without acknowledging the source. In this research, anti-plagiarism software was designed especially for the university and its campuses to identify plagiarized text in students’ written assignments and laboratory reports. The proposed framework collected original documents to identify plagiarized text using natural language processing. Our research proposes a method to detect plagiarism by applying the core concept of text, which is semantic associations of words and their syntactic composition. Information on the browser was obtained through Request application programming interface by name Url.AbsoluteUri, and it is stored in a centralized Microsoft database Server. A total of 55,001 data samples were collected from 2015 to 2019. Furthermore, we assimilated data from a university website, specifically from the psau.edu.sa network, and arranged the data into students’ categories. Furthermore, we extracted words from source documents and student documents using the WordNet library. On a benchmark dataset consisting of 785 plagiarized text and 4,716 original text data, a significant accuracy of 90.2% was achieved. Therefore, the proposed framework demonstrated better performance than the other available tools. Many students mentioned that working on assignments using the framework was suitable because they were able to work on the assignments in harmony, as per their timeframe and from different network locations. The framework also recommends procedures that can be used to avoid plagiarism.     

Storage allocation scheme for virtual instances of cloud computing

Cloud computing delivers resources and services through virtual machines on a pay-as-you-go basis. The allocation of storage space to users is usually determined by means of open allocation mechanisms that cannot guarantee an efficient allocation. Current allocation mechanisms do not consider user requests when making provisioning decisions. In other words, they assume that the storage spaces are fixed. In this study, we propose an algorithm for allocating storage spaces based on the requests of users. We present a unified storage allocation scheme (USAS) for cloud computing. USAS is a dynamic storage allocation framework for unlimited, limited, and free users. Our proposed approach is based on a storage partitioning policy, and we have compared our proposed scheme with open storage scheme and fixed storage scheme with common partition. We show through simulation study that USAS dynamically allocates space for different user requirements for all traffic loads.

     

Multi Criteria Decision Making System for Parking System

System supported smart parking can reduce traffic by making it stress free to locate empty parking spaces, hence lowering the risk of unfocussed driving. In this study, we propose a smart parking system using deep learning and an application-based approach. This system has two modules, one module detects and recognizes a license plate (LP), and the other selects a parking space; both modules use deep learning techniques. We used two modules that work independently to detect and recognize an LP by using an image of the vehicle. To detect parking space, only deep learning techniques were used. The two modules were compared with other state-of-the-art solutions. We utilized the You Only Look Once (YOLO) architecture to detect and recognize an LP because its performance in the context of Saudi Arabian LP numbers was superior to that of other solutions. Compared with existing state-of-the-art solutions, the performance of the proposed solution was more effective. The solution can be further improved for use in the city and large organizations that have priority parking spaces. A dataset of LP-annotated images of vehicles was used. The results of this study have considerable implications for smart parking, particularly in universities; in addition, they can be utilized for smart cities.     

Polymer nanoneedle-mediated intracellular drug delivery

Delivery of drugs into the cellular cytoplasm of target cells represents a major hurdle in treating various diseases. This challenge can be addressed by encapsulation of drugs onto or within nanoparticles, which can then be targeted to diseased cells. Here, needle-shaped particles are shown to exhibit substantially higher cytoplasmic delivery of drugs such as siRNA compared to their spherical counterparts. Furthermore, these needles are designed to lose their sharp tips over time and can render themselves ineffective over time, thereby offering control over their duration of activity and toxicity. Such polymer nanoneedles open new avenues for delivering drug molecules directly into the cytoplasm with low toxicity.     

Survey and Analysis of VoIP Frame Aggregation Methods over A-MSDU IEEE 802.11n Wireless Networks

The IEEE 802.11n standard has provided prominent features that greatly contribute to ubiquitous wireless networks. Over the last ten years, voice over IP (VoIP) has become widespread around the globe owing to its low-cost or even free call rate. The combination of these technologies (VoIP and wireless) has become desirable and inevitable for organizations. However, VoIP faces a bandwidth utilization issue when working with 802.11 wireless networks. The bandwidth utilization is inefficient on the grounds that (i) 80 bytes of 802.11/RTP/UDP/IP header is appended to 10–730 bytes of VoIP payload and (ii) 765 µs waiting intervals follow each 802.11 VoIP frame. Without considering the quality requirements of a VoIP call, be including frame aggregation in the IEEE 802.11n standard has been suggested as a solution for the bandwidth utilization issue. Consequently, several aggregation methods have been proposed to handle the quality requirements of VoIP calls when carried over an IEEE 802.11n wireless network. In this survey, we analyze the existing aggregation methods of VoIP over the A-MSDU IEEE 802.11n wireless standard. The survey provides researchers with a detailed analysis of the bandwidth utilization issue concerning the A-MSDU 802.11n standard, discussion of the main approaches of frame aggregation methods and existing aggregation methods, elaboration of the impact of frame aggregation methods on network performance and VoIP call quality, and suggestion of new areas to be investigated in conjunction with frame aggregation. The survey contributes by offering guidelines to design an appropriate, reliable, and robust aggregation method of VoIP over 802.11n standard.     

Smart CardioWatch System for Patients with Cardiovascular Diseases Who Live Alone

The widespread use of smartwatches has increased their specific and complementary activities in the health sector for patient’s prognosis. In this study, we propose a framework referred to as smart forecasting CardioWatch (SCW) to measure the heart-rate variation (HRV) for patients with myocardial infarction (MI) who live alone or are outside their homes. In this study, HRV is used as a vital alarming sign for patients with MI. The performance of the proposed framework is measured using machine learning and deep learning techniques, namely, support vector machine, logistic regression, and decision-tree classification techniques. The results indicated that the analysis of heart rate can help health services that are located remotely from the patient to render timely emergency health care. Further, taking more cardiac parameters into account can lead to more accurate results. On the basis of our findings, we recommend the development of health-related software to aid researchers to develop frameworks, such as SCW, for effective provision of emergency health.     

Polymer Microparticles Exhibit Size and Shape Dependent Accumulation around the Nucleus after Endocytosis

Particulate drug delivery has received significant attention in the last few decades. The effect of particle properties such as size, shape and surface properties on particle‐cell interaction has been studied. Here, intracellular accumulation and subsequent spatial segregation of spherical and rod shaped microparticles is investigated. It is observed that both spherical and rod shaped particles exhibit perinuclear accumulation. However, when the cells are fed with binary mixtures of particles, they spatially segregate in the cytoplasm based on their shape and size. Larger particles exhibit preferential accumulation closer to the nucleus. These results have potential implications in understanding the biophysical forces operating in the cells that impact the intracellular organization of drug carriers as well as organelles.