International Journal of Computer (IJC - Global Society of Scientific Research and Researchers, GSSRR)
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SEN-Iot: A Smart Emergency Notification System Suitable for Developing Countries using Internet of Things
Get PDFResearch has shown that disaster effects on properties and lives can be drastically reduced through wide dissemination of information on the impending danger to people at the appropriate time. Generally, the emergency alert systems are usually proactive systems; they are meant to gather data in surrounding using the necessary tools, alert the specified listeners about an impending danger and gives suggestion on the necessary actions to be taken in each situation. In addition, some emergency alert systems also activate automatic responses. Furthermore, the integration of Internet of things (IoT) technology with emergency notification systems is rapidly attracting new discovery in this domain. In this paper, an effective smart emergency notification system named SEN-IoT was design using IOT technology. SEN-IoT was modeled to manage domestic hazard with a scope of water, fire and gas leaks; by creating an emergence notification and immediate response systems. The SEN- IOT was implemented using arduino, sensors and the GSM module. The system was tested for maintainability, functionality, efficiency, usability and reliability, and results revealed that SEN-IoT can effectively handle domestic hazard
Supervisory Control and Data Acquisition (SCADA) System Forensics Based on the Modbus Protocol
Get PDFSupervisory Control and Data Acquisition (SCADA) has been at the cored of Operational Technology (OT) used in industries and process plants to monitor and control critical processes, especially in the energy sector. In petroleum sub-sector, it has been used in monitoring transportation, storage and loading of petroleum products. It is linked to instruments that collect and monitor parameters such as temperature, pressure and product densities. It gives commands to actuators by the use of the application programs installed on the programmable logic controllers (PLCs). Earlier SCADA systems were isolated from the internet, hence protected by an airgap from attacks taking place on interconnected systems. The recent trend is that SCADA systems are becoming more integrated with other business systems using Internet technologies such as Ethernet and TCP/IP. However, TCP/IP and web technologies which are predominantly used by IT systems have become increasingly vulnerable to cyberattacks that are experienced by IT systems such as malwares and other attacks. It is important to conduct vulnerability assessment of SCADA systems with a view to thwarting attacks that can exploit such vulnerabilities. Where the vulnerabilities have been exploited, forensic analysis is required so as to know what really happened. This paper reviews SCADA systems configuration, vulnerabilities, and attacks scenarios, then presents a prototype SCADA system and forensic tool that can be used on SCADA. The tool reads into the PLC memory and Wireshark has been to capture network communication between the SCADA system and the PLC
An Adaptation of DSRC Protocol for V2V Communications in Developing Countries: End-to-End Delay Evaluation
Get PDFVehicular Ad hoc NETworks (VANETs) help in improving road traffic safety and efficiency. In V2V communications, vehicles exchange kinematic information over a suitable protocol in order, either to warn other vehicles of a dangerous situation or inform them about the current status of the traffic flow. When using Wireless Access in Vehicular Environments (WAVE), also referred to as Dedicated Short Range Communication (DSRC) protocol, kinematic information is called Wave Short Messages (WSM), based on Basic Safety Message (BSM) defined by the SAE J2735 dictionary set. BSM is used for safety advertisement, either in one hop or multi-hop broadcasts. However, DSRC evaluations in many urban and sub-urban environments have shown that this protocol is highly sensitive to transmission conditions such as the density and speed of vehicles, antenna position, interference, etc., which makes it difficult to predict its performance. In this paper, we are interested in evaluating, based on various scenarios, the end-to-end delays when a particular emergency vehicle broadcasts BSM to all its nearby vehicles. The results are obtained by modeling and simulating a modified version of the DSRC protocol to fit the Cameroonian environment. Our results reveal that our adapted version of DSRC protocol performs very well and outperform others proposed protocols
Modelling of Indoor Positioning Systems Based on Location Fingerprinting
Get PDFIn recent years, localization systems for indoor vicinity using the present wireless local area (WLAN) network infrastructure have been proposed. Such positioning systems create the usage of location fingerprinting instead of direction or time of arrival techniques for deciding the location of mobile users. However experimental study associated to such localization systems have been proposed, high attenuation and signal scattering related to greater density of wall attenuation still affecting the indoor positioning performance. This paper presents an analytical model for minimizing high signal attenuation effect for WLAN fingerprinting indoor positioning systems. The model employs the probabilistic algorithm that using signal relation method
An Improved Rapid Response Model for University Admission Enquiry System Using Chatbot
Get PDFA model for real-time response on admission related enquiries was developed in this research with the aim of bridging the lag usually experienced through the conventional approach of phone call and email. The model was implemented using IBM Watson to design a Chatbot for rapid response to admission enquiries. Botium was used to evaluate the performance of the Chatbot which gave an accuracy of 95.9% with instance of 212successful test cases and 9failed test cases. The approach introduces users to new and emerging technological solutions for optimal and rapid response in the educational sector
An Improved Model for the Implementation of Web-Based Learning in Adult Secondary School Education in Kenya
Get PDFThe development of technology, which evolves continuously, has led to the transformation of traditional courses into web-based courses. However, as these e-learning systems grow more complex, involving numerous users with different levels of need, there is a need to have web-based learning models that adequately address such users’ needs, taking into consideration their levels of expertise, access and ability to interact with such systems. Most of the existing models present the adult learners with difficulties, as most of them have to concentrate mostly on learning the technology rather than learning the desired content. Most of the difficulties arise from the web-based learning model configurations in use in the country. The majority lack features and capabilities of highly interactive, fast-paced multimedia-supported learning currently demanded by most learners and tutors. Therefore, the main aim of this research was to devise an improved model for implementing a web-based learning programme in adult secondary school education. After analysing the existing models and establishing their operational challenges, an improved model was proposed. The proposed model was statistically tested using sample data. The results showed that recognizing both technological and user attributes along the recognized theoretical frameworks was important in increasing the users’ behavioural inclination to use the improved model.
Therefore, it is recommended that more sensitization to web-based learning should be implemented by the adult education department in the Ministry of Education among adult learners in the country. It is also recommended that system developers should find ways of incorporating additional features into the model without affecting its architecture and function. Finally, there is need for future studies on the causal antecedents of the constructs presented in this research model to provide more precise practical implications
Achieving Agile Team Efficiency by the Application of Lean Approach Through Change Management
Get PDFAgile teams are meant to function promptly to deliver product components on time, within budget and to the quality expected. With time, it becomes necessary to bring forward changes to the structure and processes in order to improve efficiency of the team. Unfortunately, new elements brought forward usually cause some disruptions in the smooth running of the team day to day activities. This study looks into the application of lean approach towards change management that aims at increasing team by performing proper people management and eliminating wastages. It is known that lean management is a way of analysing the way a business is being done and going forward with the elimination of rules and processes not bringing any value added. The study takes into account various projects categorized as small. medium and large to investigate whether the lean approach is beneficial in achieving team efficiency. A quantitative approach is used involving software developers with experience in using the agile methodology. The findings reveal that the application of lean approach is quite convincing in managing agile teams for the smooth integration of changes. While the benefits of lean approach is seen to be meagre on small sized projects, they are found to be quite substantial on large projects
Neural Network-Based Expression Recognition System for Static Facial Images
Get PDFAffective Computing is a field of studying the human effect to interpret, recognize, process, and simulate in computer science, psychology, and cognitive science. Humans express their emotions in a variety of ways such as body gesture, word, vocal, and mainly facial expression. Non-verbal behavior is a significant component of communication, and facial expressions of emotions are the most important complex signal. Facial Expression Recognition (FER) is an interesting and challenging task in artificial intelligence. FER system in the study three steps including preprocessing, feature extraction and expression classification. In the paper, comparative analysis of expression recognition is implemented based on Neural Network (NN) with three feature extraction methods of Sobel Edge, Histogram of Oriented Gradient and Local Binary Pattern. NN-based expression recognition system achieves an accuracy of 95.82% and 97.68% for JAFFE and CK+ dataset respectively. The result has shown that the Edge features are the effected features for recognizing human expression using still images
Machine Learning for Handwriting Recognition
Get PDFWith the knowledge of current data about particular subject, machine learning tries to extract hidden information that lies in the data. By applying some mathematical functions and concepts to extract hidden information, machine learning can be achieved and we can predict output for unknown data. Pattern recognition is one of the main application of ML. Patterns are usually recognized with the help of large image data-set. Handwriting recognition is an application of pattern recognition through image. By using such concepts, we can train computers to read letters and numbers belonging to any language present in an image. There exists several methods by which we can recognize hand-written characters. We will be discussing some of the methods in this paper
Comparative Analysis of Distinctive Features of the Ransomware Tactics in Relation to Other Malware
Get PDFRansomware have become a real threat to the use of technology. Unlike other forms of malware that could target systems by deleting or editing some files and creating backdoor for the attacker to access the system, ransomware have gone a notch higher by targeting humans. This is achieved when a ransomware encrypts data of the infected computer and a note demanding for a ransom to be paid is printed on the screen. Due to the advancement in technology, ransomware use advanced and secure encryption algorithm that is difficult to decrypt even when the computational power is not limited. In this work, we present some of the major behavioral characteristics that we found to be common with ransomware and not with other malware. Our results show that a careful analysis of suspicious network and file activities can help detect a ransomware attack. Further, careful analysis of ransomware behavior can help develop a system that can detect an impeding ransomware attack and thereby eliminate it