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A Novel Interactive IoT-Based Smart Electricity Power Consumption Management System
Ibrahim Mohammed Abdullahi,Peter Nanpon Gambo,Martins Ake,Ibrahim Aliyu,Seungmin Oh,Jinsul Kim 한국디지털콘텐츠학회 2021 The Journal of Contents Computing Vol.3 No.2
Effective and efficient management of electric power is of significant benefit to the end users and a nation’s economy at large. The unnecessary huge bills and feuds that occur very often in developing countries like Nigeria after every billing period are often because of energy wastage and improper use of energy. This challenge hereby presents us with the need to not only create awareness but to also develop systems that allow for efficient and economic use of electric power. The existing meters that attempt to handle this challenge are in some cases analog, or not interactive, expensive and imposing. These systems are said to be imposing because they do not afford the user the right of deciding what he/she wants to spend in a billing period. Even with the emergence of prepaid meters, users are still unable to interact with individual connection points and decide what is consumed there so as to enhance conservation. These problems have already brought to table the need to develop systems that are automated, yet interactive and smart. The solution is an interactive smart electric consumption management system. Thus, this research work is formed around interaction and smartness. A linPrec Scheduling Algorithm is used to predict what each connection point requires in a billing period by interpolating between previous data points on the system. With the Android App, the User is allowed to communicate with every connection point in the apartment and comfortably determine how much they are willing to spend on electricity in a billing period. The http client guarantees data arrival with a worst-case average response time of 2.095s and a best-case average response time of 0.894s. Also, the power measurement had a Mean Absolute Error of 8.89% which implies high accuracy of 91.1%.
Intelligent Offline Multi Object Recognition Walking Stick for The Blind
Ibrahim Mohammed Abdullahi,Olayemi Mikail Olaniyi,Jacob Omokhafe Irefu,Sangwon Oh,Ibrahim Aliyu 한국디지털콘텐츠학회 2021 The Journal of Contents Computing Vol.3 No.2
Vision is one of the most important characteristics of a human that aid their day to day activities. Loss of vision however affects the ability of humans to freely navigate their environment and recognized objects along their path. Existing object recognition systems for the blind are mostly cloud based and its performance depends on reliable internet access. This makes them unsuitable in places with unreliable internet. Therefore, in this paper, a multi-object recognition intelligent walking stick for the blind that is completely independent of the internet was developed. The system is divided into three units, detection, recognition and communication units. The detection unit make use of an ultrasonic sensor and a buzzer, for informing the user of an impending obstacle. The recognition system makes use of a camera for capturing images with Convolutionary Neural Network architecture and Mobile Network Single Shot Multi-Box Detector (MobileNet SSD) for detecting objects in images. The communication unit transmits the recognised objects through voice to the user in English Language. The entire system was deployed in a Raspberry Pi microcontroller due to its processing power. The result obtained from testing of the device on the field showed that the recognition unit achieved an average sensitivity, specificity, precision and accuracy of 87.26%, 67.45%, 89.07%, 82.50% respectively. This shows that the system is reliable and can be used in recognizing objects for the blind.
Mohammed Faruk,Sani Ibrahim,Ahmed Adamu,Abdulmumini Hassan Rafindadi,Yahaya Ukwenya,Yawale Iliyasu,Abdullahi Adamu,Surajo Mohammed Aminu,Mohammed Sani Shehu,Danladi Amodu Ameh,Abdullahi Mohammed,Saad 대한장연구학회 2018 Intestinal Research Vol.16 No.1
Background/Aims: Colorectal cancer (CRC) is now a major public health problem with heavy morbidity and mortality in rural Africans despite the lingering dietary fiber-rich foodstuffs consumption. Studies have shown that increased intake of dietary fiber which contribute to low fecal pH and also influences the activity of intestinal microbiota, is associated with a lowered risk for CRC. However, whether or not the apparent high dietary fiber consumption by Africans do not longer protects against CRC risk is unknown. This study evaluated dietary fiber intake, fecal fiber components and pH levels in CRC patients. Methods: Thirty-five subjects (CRC=21, control=14), mean age 45 years were recruited for the study. A truncated food frequency questionnaire and modified Goering and Van Soest procedures were used. Results: We found that all subjects consumed variety of dietary fiber-rich foodstuffs. There is slight preponderance in consumption of dietary fiber by the control group than the CRC patients. We also found a significant difference in the mean fecal neutral detergent fiber, acid detergent fiber, hemicellulose, cellulose and lignin contents from the CRC patients compared to the controls (P <0.05). The CRC patients had significantly more fecal pH level than the matched apparently healthy controls (P =0.017). Conclusions: The identified differences in the fecal fiber components and stool pH levels between the 2 groups may relate to CRC incidence and mortality in rural Africans. There is crucial need for more hypothesis-driven research with adequate funding on the cumulative preventive role of dietary fiber-rich foodstuffs against colorectal cancer in rural Africans “today.” (Intest Res 2018;16:99-108)
Multi Query Optimization Algorithm Using Semantic and Heuristic Approaches
L. J. Muhammad,Abdullahi Garba Ali,Yahaya Bala Zakariyau,Ibrahim A. Mohammed 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.6
Multi Query Optimization is one of the most important tasks in Relational Database Management System (RBMS) and it becomes common due to high usage of online decision support management systems in every industry nowadays. In multi query optimization, queries are optimized and executed in batches. However, there are many algorithms use to detect and unified common sub-expressions among multiple queries and unified them so that the more encompassing sub- expression is executed and the other sub-expressions are derived from. In this work, multi-query optimization algorithm using heuristics and semantic approaches was proposed and encoded on SQL Server version 10.0.1600 and three queries were used for the experiment between the proposed algorithm and most recent basic Multi Query Optimization Algorithm (Volcano RU). The result of experiment showed that, Proposed Algorithm gave the best plans compared Volcano RU Algorithm, across all three queries and was best for all queries in terms of execution time and CPU time.