Maximizing Solar Output Power: Load Shedding Design Approach

Renewable energy is currently at the centre of meeting the world energy needs. A notable number of offices and home-users have employed the renewable energy technologies, which are usually used for power backup purposes. High cost of generation is the major factor militating against solar power system affordability. Therefore, an effective way of maximizing the limited generated solar power is paramount. This research presents a viable method of minimizing the overall cost of implementing a solar power system by adequate management of the load to be powered. This paper presents a load shedding design approach in maximizing the solar output power usage in meeting the ever dynamic power need in a typical office setting. The estimated cost of implementing the full load design was compared side by side with a proposed load shedding design approach. In addition, the shed loads were carefully considered to ensure the office day to day activities were not hindered. The load shedding design was found to reduce the total effective load of the office complex. It also reduced the total cost of implementing the solar power design to meet a required load by 90.87%. Keywords: Solar Power, Maximize, Load Shedding, Renewable Energy, Full Loa

TEXT CONTENT DEPENDENT WRITER IDENTIFICATION

Text content based personal Identification system is vital in resolving problem of identifying unknown document’s writer using a set of handwritten samples from alleged known writers. Text written on paper document is usually captured as image by scanner or camera for computer processing. The most challenging problem encounter in text image processing is extraction of robust feature vector from a set of inconstant handwritten text images obtained from the same writer at different time. In this work new feature extraction method is engaged to produce active text features for developing an effective personal identification system. The feature formed feature vector which is fed as input data into classification algorithm based on Support Vector Machine (SVM). Experiment was conducted to identify writers of query handwritten texts. Result show satisfactory performance of the proposed system, it was able to identify writers of query handwritten texts

Hand Vein Based Personal Identification System

Personal Identification is necessary and useful to prevent crime in our society. Biometric traits extracted from hand image are more secure to use for identification compared to Personal Identification Number (PIN) because these features cannot be stolen. Developing an effective hand vein based personal identification system using robust feature with appropriate classifier is a serious task. Therefore this work incorporates new hand vein feature and two different classifiers to develop a personal identification system. Experiments were carried-out to affirm appropriateness of Support Vector Machine (SVM) and Euclidean Distance Measure (EDM) for the proposed system. The results obtained show that the proposed system give better result using SVM compared to EDM

DISTRIBUTION AND BIOAVAILABILITY OF METALS IN GASOLINE CONTAMINATED SITES IN LAGOS, NIGERIA

Distribution of metals in soil of two gasoline contaminated sites in Lagos were studied. Total Concentrations of twenty-five elements were investigated in composite samples collected at different depths within the sites. The elements were determined by ICP-AES after microwave assisted acid digestion of the samples. Chemical fractionation, mobility and potential bioavailability of some of the toxic and EU priority metals e.g., Pb, Cu, Cd, and Fe were evaluated in the topsoil (0-15 cm) by sequential extraction. There were great variation in the concentrations of the elements in both sites with depth. Speciation analysis showed that Pb and Cd dominated the Fe-Mn oxide fraction while the concentrations of Fe and Cu were higher in the residual fraction in site A. In site B, Pb, Cu and Cd was mainly associated with the Fe-Mn oxide fraction, while Fe was in the residual fraction. Cd has the highest mobility factors, 33.2% (site A) and 29.5% (site B), respectively. The concentrations of most of the toxic heavy metals (e.g., Pb, Zn, Cu, Cr, Cd etc.) exceed that of the control samples and heavy metal baseline values around the world. Thus, proper management of these potentially contaminated sites is imperative to prevent human health risk

The Influence of Drying on the Physical Properties of Sweet Potato Slices

The effects of varying drying conditions on the physical properties of sweet potato slices were studied. Fresh tubers were peeled, washed and cut into two shapes (rectangular: 50 x 60 mm and cylindrical 60 mm diameter) and two thicknesses (4 and 6mm) slices. Some slices were blanched in water at 90 oC for 5 mins and some untreated. The slices were dried in the sun or oven (50 oC , 70 oC , 90 oC ). The bulk density, dimensional changes and moisture loss were investigated. Moisture loss and percent shrinkage increased with higher temperature and longer drying time. 4mm thick samples lost more moisture and higher % shrinkage than 6mm thick samples, although not significantly (P>0.05). Logarithmic equations gave best fit of moisture loss with time at the different temperatures. Initial sample thickness had a greater impact on shrinkage than sample shape. Blanching minimized % shrinkage although not significantly (P>0.05). Greater shrinkage took place in the sample thickness (up to 63%) than across product diameter or length (values up to 26.3%). % shrinkage can be predicted using either the linear or logarithmic equations. The bulk densities of dried sweet potato slices were not influenced by blanching. Keywords: moisture content, drying kinetics, blanching, dimensional changes, bulk density

Online Signature for Attendance Verification System using Levenberg-Marquardt Neural Network

This work focuses on the application of Levenberg-Marquardt based Back-propagation Neural Network for training features extracted from online signature images. In implementing this, the description of Levenberg-Marquardt back-propagation Neural Network is given. This is followed by signature image processing stages needed to produce input data for the training algorithm. Signature attendance system based on the trained network was developed and tested with data collected from fifty (50) classes. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also calculated to give 8% and 12% respectivel

Effect of Taraxacum officinale Leaf Extract on Liver Antioxidant Status in Streptozotocin-Induced Diabetic Male Wistar Rats

The study aimed at evaluating liver antioxidant status in streptozotocin (STZ)-induced diabetic male Wistar rats following treatment with aqueous Taraxacum officinale leaf extract. The rats were divided into six groups of 6 rats each: Normal control, Diabetic control, Non-diabetic rats + 100 mg/kgbw extract, Non-diabetic rats + 200 mg/kgbw extract, Diabetic rats + 100 mg/kgbw extract and Diabetic rats + 200 mg/kg-bw extract. After the treatment period, the animals were sacrificed and the liver was collected, homogenized for biochemical analyses. Biochemical assays such as the levels of nitrite, lipid peroxidation product (LPO), reduced glutathione (GSH) and activities of antioxidant enzymes (superoxide dismutase, SOD and glutathione peroxidase, GPx) as well as Ferric Reducing Antioxidant Power (FRAP) were determined using established techniques. Lipid peroxidation and nitrite level decreased significantly (p < 0.05) in diabetic rats treated with 100 mg/kgbw and 200 mg/kgbw Taraxacum officinale extracts as compared to the untreated diabetic control. There was no significant difference in FRAP value in diabetic groups treated with 100mg/kgbw and 200mg/kgbw when compared with the diabetic control. Reduced GSH concentration as well as SOD activity increased significantly in diabetic groups treated with 100 mg/kgbw and 200 mg/kgbw Taraxacum officinale extracts as compared to the untreated diabetic control while GPx activity decreased significantly in the treated diabetic rats. The results indicate that Taraxacum officinale leaf extract could enhance liver anitioxidant status, hence, suggest its usefulness in ameliorating diabetic-induced liver injury

Cost Management of the Enterprise: Analysis, Regulation and Reduction of Cost in the Organization (OJSC “GZLiN”)

Материалы XXII Междунар. науч.-техн. конф. студентов, аспирантов и молодых ученых, Гомель, 28–29 апр. 2022 г