Artificial Neural Network Approach to Mobile Location Estimation in GSM Network

The increase in utilisation of mobile location-based services (LBS) for commercial, safety and security purposes among others are the key drivers for improving location estimation accuracy to better serve those purposes. Hence, developing mobile location estimation with high accuracy has been an issue of a major research concern as so many methods have been proposed. Among these methods include Cell ID, global positioning system (GPS), fingerprinting, statistical, geometrical, angle, time based and recently artificial intelligence methods. The GPS techniques have offered superior measurement accuracy to others but suffer accuracy degradation in indoor and dense urban area due to non-line of sight (NLOS) propagation. This paper proposes the application of Levenberg Marquardt (LMA) training algorithm on new robust multilayered perceptron (MLP) neural network architecture for mobile positioning fitting for the urban area in the considered GSM network using received signal strength (RSS). The key performance metrics such as accuracy, cost, reliability and coverage are the major points considered in this paper. The technique was evaluated through a simulation using real data from field measurement and the results obtained proved the proposed model provides a practical positioning that meet Federal Communication Commission (FCC) accuracy requirement

An optimum dynamic priority-based call admission control scheme for universal mobile telecommunications system

The dynamism associated with quality of service (QoS) requirement for traffic emanating from smarter end users devices founded on the internet of things (IoTs) drive, places a huge demand on modern telecommunication infrastructure. Most telecom networks, currently utilize robust call admission control (CAC) policies to ameliorate this challenge. However, the need for smarter CAC has becomes imperative owing to the sensitivity of traffic currently being supported. In this work, we developed a prioritized CAC algorithm for third Generation (3G) wireless cellular network. Based on the dynamic priority CAC (DP-CAC) model, we proposed an optimal dynamic priority CAC (ODP-CAC) scheme for Universal Mobile Telecommunication System (UMTS). We then carried out simulation under heavy traffic load while also exploiting renegotiation among different call traffic classes. Also, we introduced queuing techniques to enhance the new calls success probability while still maintaining a good handoff failure across the network. Results show that ODP-CAC provides an improved performance with regards to the probability of call drop for new calls, network load utilization and grade of service with average percentage value of 15.7%, 5.4% and 0.35% respectively

APPLICATION OF SELF-ORGANIZING MAP TO INTELLIGENT ANALYSIS OF CELLULAR NETWORKS

ABSTRACT In this work, the efficacy and scalability of the self-organizing map (SOM) algorithm, which is a class of artificial neural network (ANN), over traditional methods of analyzing cellular network variables was shown using key performance indicators (KPIs) data collected from an operational network service provider in Nigeria. Performance trends of various cells over a period of time were evaluated and rules of significance measure extracted which could form the basis for network optimization

Phytochemical and Vitamin Composition of Cucumis metuliferus Juice

The pursuit of healthy lifestyle has led to increased demand for fruits and vegetables. Fruit juice in particular, is increasingly receiving attention because of the therapeutic benefits derived from its consumption. The bioactive compounds in fruit juice have various pharmacological applications. Cucumis metuliferus is a plant of the Cucurbitaceae family. The fruit has a high water content and sought after to quench thirst. The ethno-medicinal properties of the fruit requires investigation of all the parts in order to maximally utilize it. Therefore, in this study, the phytochemical and vitamin composition of the juice were investigated. The assays were conducted using standard methods. From the result, the phytochemicals present were phytate (0.33 ± 0.03%), alkaloids (0.48 ± 0.06%), saponins (0.19 ± 0.04%), cardiac glycosides (0.46 ± 0.16%), Oxalate (3.24 ± 0.38 mg/ml), tannins (108.79 ± 5.16 mg TAE/g) and phenols (0.06 ± 0.01 mg GAE/ml). The vitamin present were vitamin A (198.51 mg/kg), vitamin B1 (0.09 mg/ml), Vitamin B2 (0.11 mg/ml), Vitamin B3 (0.07 mg/ml), vitamin B6 (835.0 mg/ml), vitamin B9 (2.089 mg/ml), vitamin B12 (0.1 mg/ml), Vitamin C (682.0 mg/ml), vitamin D (5.28 mg/ml), vitamin E (4.42 mg/ml) and vitamin K (2.4336 mg/ml). These results have shown that Cucumis metuliferus juice have pharmacological properties and could also be utilized as an alternative source of vitamins.</jats:p

Nutritional and Phytochemical Content of Cissus populnea (Okoho) Stem Bark

In this study, the nutritional and chemical contents of the stem bark of Cissus populnea were determined. The analyses were carried out using standard methods. The proximate analyses showed that the sample contains crude protein (1.49±0.02%), crude fibre (22.13±0.62%), crude fat (13.07±0.26%), carbohydrates (56.04±0.78%), ash (4.605±0.23%) and moisture (2.665±0.33%). The vitamin content comprise of vitamin A (2.805±0.03 mg/g), β-Carotene (1.795±0.03 mg/g), vitamin B1 (0.93±0.02 mg/g), vitamin B2 (1.755±0.15 mg/g), vitamin B9 (1.67±0.10 mg/g), vitamin C (2.235±0.17 mg/g), vitamin D (2.02±0.1 mg/g), vitamin E (1.41±0.08 mg/g) and vitamin K (2.425±0.21 mg/g). The phytochemical screening revealed the presence of alkaloids (1.551 ±0.03 mg/g), flavonoids (0.761±0.10 mg/g), saponins (2.208±0.07 mg/g), steroids (1.452±0.04 mg/g), tannins (1.987±0.01 mg/g), terpenoids (1.530±0.09 mg/g) and phenols (0.447±0.06 mg/g). Glycoside was not detected. The results indicate that the stem bark of Cissus populnea is a good source of food nutrients and phytochemicals. These phytochemicals may be responsible for the medicinal properties of the plant.</jats:p