A Subtle Serial Key based Software Protection Scheme

Software piracy is a modern day war between malicious software pirates and software developers. Annually, developers lose billions of dollars in revenue to piracy, making it an industry bane that must be controlled by all means. The drivefor improved software protection systems has increased the complexity of both proposed and implemented schemes. Some of the methods are cost intensive in terms of development, management and hardware requirement (smart card tokens), while this may be justified for costly software applications, for low cost and basic applications by small scale study presents a subtle software protection model using serial keys. The model implements a form of obfuscation by using hidden codes, encrypted functions and uses a distraction technique by diverting the attention of potential hackers to the serial key while trickily using coded strings for the actual user authenticatio

Handover in Mobile Wireless Communication Network - A Review

Mobility is the characteristics of mobile communication that makes it irresistible by all and sundry. The whole world is now engaging in wireless communication as it provides users\u27 ability to communicate on-the-go. This is achieved by transferring users from a radio network to another. This process is called handover. Handover occurs either by cell crossing or by deterioration in signal quality of the current channel. The continuation of an active call is a critical characteristic in cellular systems. Brief overview of handover, handover type, commonly used handover parameters, some methods employed in the literature and we present the convergent point for furtherance in the area of mobile wireless communication Handover

An Intelligent Online Diagnostic System With Epidemic Alert

In many parts of the world and especially in developing nations, qualified doctors are overworked. This situation is the direct result of not ensuring that the number of qualified and available doctors keep pace with the exponential population growth rate that is obtainable in developing countries. Despite this, accurate diagnosis of ailments is a must. This paper proposes a novel way to ease the work burden on doctors with an intelligent online diagnosis system that can accurately diagnose diseases and prescribe medications without the need for physical interaction between patient and doctor. The proposed system uses an application programming interface (Infermedica) and has the added advantage of being able to give alerts at the onset of any epidemic

Adaptive Network Based Fuzzy Inference System Model For Minimizing Handover Failure in Mobile Networks

For seamless connection between mobile users on the same and different mobile technologies there is need for the deployment of a more complex algorithm for a successful switching of mobile users. Signal to interference ratio, speed of the mobile users and traffic distance are the three input used in the Adaptive network based Fuzzy inference system (ANFIS) which is an hybrid of two techniques of artificial intelligence which make it suitable to handle complexities such as ping-pong effect and interference which impair on the quality of service (QoS) during call handover process as the mobile users move from one coverage area (cell) to anothe

Design and implementation of a java based virtual laboratory for data communication simulation

Students in this modern age find engineering courses taught in the university very abstract and difficult, and cannot relate theoretical calculations to real life scenarios. They consequently lose interest in their coursework and perform poorly in their grades. Simulation of classroom concepts with simulation software like MATLAB, were developed to facilitate learning experience. This paper involves the development of a virtual laboratory simulation package for teaching data communication concepts such as coding schemes, modulation and filtering. Unlike other simulation packages, no prior knowledge of computer programming is required for students to grasp these concepts

An Intelligent Online Diagnostic System With Epidemic Alert

In many parts of the world and especially in developing nations, qualified doctors are overworked. This situation is the direct result of not ensuring that the number of qualified and available doctors keep pace with the exponential population growth rate that is obtainable in developing countries. Despite this, accurate diagnosis of ailments is a must. This paper proposes a novel way to ease the work burden on doctors with an intelligent online diagnosis system that can accurately diagnose diseases and prescribe medications without the need for physical interaction between patient and doctor. The proposed system uses an application programming interface (Infermedica) and has the added advantage of being able to give alerts at the onset of any epidemic

Development of an ANN-based Estimated Electricity Billing System

This paper presents an Artificial Neural Network (ANN) model to determine the estimated monthly payment for electricity consumed by residential consumers. The network was trained, validated and tested with five consumer input attributes which comprises type of apartment, number of occupants, average daily power supply, scored categories of electrical appliances and scored behavioural energy usage pattern. The corresponding output data comprises of the average monthly payment obtained from metered residential customers. A combined R-value of 0.99923 was obtained for the trained network. This indicates a very accurate ANN training. The developed network was then utilised to compute the estimated monthly amount to be paid by unmetered residential consumers. Comparisons were also made with the rather unclear and controversial estimated amount utilised by the electricity distribution companies in Nigeria. This work therefore provides a better method for estimated billing in the absence of prepaid meter, which has been of inadequate supply to electricity users in developing countries like Nigeria

Ping-pong reduction for handover process using adaptive hysteresis margin: a methodological approach

The technology, Long Term Evolution (LTE) developed by 3rd Generation Partnership Project is considered an improved standard in mobile communications when compared to previously attained network standards. LTE with prospects of decreased latency levels and support of downlink and uplink transmission at data rates exceeding 100Mbps and 50Mbps, an effective handover framework needs to be put in place to improve quality of service rendered to the network users and decrease wastage of network resources. This study examines several works carried out on a handover criteria (hysteresis margin) needed for designing an effective handover framework. This margin is based on the received signal strength between both target and serving eNodeBs, and its proper determination amongst other advantages mitigates the rate of unnecessary and repeated handover (ping-pong effect). The model presented in this research integrates the artificial neural network (ANN) mechanism into the determination of hysteresis margin in the LTE handover process which is to minimize handover delay and ping-pong taking into consideration the speed of the user equipment (UE)

Development of a Web and Mobile Applications-Based Cassava Disease Classification Interface Using Convolutional Neural Network

Cassava is one of the six food items identified as a critical food product for Africa, owing to its importance to African farmers' lives and ability to alter African economies. However, Cassava plant diseases have affected the yield of farmers significantly which has led to a decline in the agricultural production of cassava. Therefore, the aim of this research work is to develop a web and mobile applications-based system that would be able to detect cassava diseases based on its leaf images. To achieve this aim, pre-trained Convolutional Neural Network (CNN) models were selected using their previous performance and the application of transfer learning technique, new models were developed to classify cassava diseases based on the dataset curated and pre-processed. The best three models were selected: MobileNetV2, VGG16 and ResNet50. After training, the accuracy for each model was: 98%, 92% and 75% for MobileNetV2, VGG16 and ResNet50 respectively. Following evaluation of performance, the model with the best accuracy (MobileNetV2) was deployed using a web application interface. After deploying as a web and mobile apps interface, it was further tested to see how it would perform on the field. This research work was found capable of aiding farmers in being able to timely detect the type of disease affecting their cassava plants and the correct treatment to utilize; this also contribute towards Sustainable development goal

Design of a digital fuel gauge with distance-to-zero indicator

The fuel gauge in automobiles measures the amount of fuel in the tank through the sensing unit located in the tank and the analog indicator on the dashboard of the vehicle shows the quantity of fuel per time. This work is designed to ensure the display of the exact volume of fuel in the vehicle in digital form instead of the usual analog fuel indicator. It will also help to prevent inaccurate measurement of fuel at the filling station by showing the quantity of fuel during refuelling. So, a digital fuel gauge system has been designed and constructed to measure the exact quantity of fuel in the tank and display this measured quantity digitally in litres, by making use of an ultrasonic sensor and programmable microcontroller and the result obtain is ±0.96% accurate