The economic growth of every nation is highly related to its electricity infrastructure, network, and availability since electricity has become the central part of everyday life in this modern world. Hence, the global demand for electricity for residential and commercial purposes has seen an incredible increase. On the other side, electricity prices keep fluctuating over the past years and not mentioning the inadequacy in electricity generation to meet global demand. As a solution to this, numerous studies aimed at estimating future electrical energy demand for residential and commercial purposes to enable electricity generators, distributors, and suppliers to plan effectively ahead and promote energy conservation among the users. Notwithstanding, load forecasting is one of the major problems facing the power industry since the inception of electric power. The current study tried to undertake a systematic and critical review of about seventy-seven (77) relevant previous works reported in academic journals over nine years (2010–2020) in electricity demand forecasting. Specifically, attention was given to the following themes: (i) The forecasting algorithms used and their fitting ability in this field, (ii) the theories and factors affecting electricity consumption and the origin of research work, (iii) the relevant accuracy and error metrics applied in electricity load forecasting, and (iv) the forecasting period. The results revealed that 90% out of the top nine models used in electricity forecasting was artificial intelligence based, with artificial neural network (ANN) representing 28%. In this scope, ANN models were primarily used for short-term electricity forecasting where electrical energy consumption patterns are complicated. Concerning the accuracy metrics used, it was observed that root-mean-square error (RMSE) (38%) was the most used error metric among electricity forecasters, followed by mean absolute percentage error MAPE (35%). The study further revealed that 50% of electricity demand forecasting was based on weather and economic parameters, 8.33% on household lifestyle, 38.33% on historical energy consumption, and 3.33% on stock indices. Finally, we recap the challenges and opportunities for further research in electricity load forecasting locally and globally.
The Development in Information Technology (IT) have raised up a lot of fears about the risk to information concomitant with feeble IT security, including weakness to malware, attacks, virus and compromise of network systems and services. Anyone who goes on the net is vulnerable to security threats. Inadequate IT security may result in compromised integrity, confidentiality and the release of sensitive data to unauthorized persons. In most development communities and countries, IT vulnerability has become an important concept employed to guide the evaluation, design and targeting of programs. Remaining ahead of the everevolving threat of an information break on websites and web application necessitates conscientiousness on the part webmasters and heads of IT sections within an organization in understanding and anticipating the risks. This paper seek to examine the knowledge of webmasters and heads of IT sections on threats and vulnerabilities on the cyber world of selected institutions in Ghana through semi-structured questioners and one-on-one interview and proposed away forward in boosting the knowledge base of IT and Webmaster, hence contribute to the reduction of cyber-crime in the country and also outline some guidelines on how to surf the web safely to end-users. The survey showed that, on an average 47% of the respondent have little or no knowledge in at least one or more of the existing website vulnerabilities. General TermsWebsites and web application vulnerabilities
Optical cables are enormous transmission media that carry high‐speed data across transatlantic, intercontinental, international boundaries, and cities. The optical cable is essential in data communication. The cable has become an indispensable component in optical communications infrastructure; hence, conscious efforts are always adopted to prevent or minimize faults in the optical network infrastructure. Typically, tracing fault in the underground optical network has been difficult even though the optical time‐domain reflectometer (OTDR) has been used to measure the distance of faults in the underground fiber cable. The methodologies deployed in the reviewed literature indicate a vast gap between the fault distance measured by the OTDR and the actual distance of fault. This paper observed the difficulties involved in tracing the actual spot of fault in the underground optical networks. The difficulty of tracing these underground faults mostly result in an undue delay and loss of revenue. This research presents a machine learning approach to predict the actual location of a fiber cable fault in an underground optical transmission link. Linear regression in the python sci‐kit learn library was used to predict the actual location of a fault in an underground optical network. The mean square error and MAE evaluation matrix used provided good accuracy results of 0.061291 and 0.080143, respectively. The result obtained in this paper indicates that faults in underground optical networks can be found quickly to avoid the delays in the fault tracing process, which leads to an excessive revenue loss.
The telecommunication industry in Ghana has undergone various stages of transformation. The industry has experienced exponential growth over the last decades. Sustaining this growth hinges on efficient infrastructural deployment and management. Fiber optics technology has become the primary network infrastructure and a communication medium, which provides higher bandwidth capacity high speed for current and emerging technologies. As the demand for new technology and services increases, fiber optics technology brings the promise of a flexible, scalability, full‐service network platform with potentially unlimited capacity. Although mobile network operators have invested significantly and strategically in fiber optic infrastructure, there has been an increase in the number of network outages caused by frequent failures in fiber optics networks such as fiber cable cuts. Fiber cable cuts have become the single most significant cause of transmission failure or disruption to telecommunication services in Ghana with an enormous impact on the subscriber's experience. This research seeks to investigate the challenges in fiber cable deployment in Ghana, with emphasis on the technical, regulatory, managerial challenges and recommend the appropriate solutions. The challenges of frequent fiber cuts can be attributed to external factors such as dig‐ups during road construction. Lack of regulatory guidelines and policies on fiber deployment and management poses a major threat to the fiber management in Ghana.
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