A framework for reuse of multi-view UML artifacts

Abstract-Software is typically modeled from different viewpoints such as structural view, behavioral view and functional view. Few existing works can be considered as applying multi-view retrieval approaches. A number of important issues regarding mapping of entities during multiview retrieval of UML models is identified in this study. In response, we describe a framework for reusing UML artifacts, and discuss how our retrieval approach tackles the identified issues

Information and Communication Technology (ICT) in Nigerian Libraries for Sustainable Development Goals (SDG).

The main purpose of this paper is to explore the crucial roles of Information and Communication Technology (ICT) in provision of library services, for sustainable development goals in Nigeria. The rationale behind the SDGs, understanding the content and contexts of the SDGs, analysis of the library-related SDGs, the place of the libraries in actualization of the SDGs were well articulated. Despite the availability of wide opportunities offered by the advent of ICT, it has been observed that application of ICT to library services in Nigeria seems inadequate probably due to variety of challenges. With the methodology of simple literature review, the paper made effort to review related literature on ICT resources and ICT based services in libraries, benefits of ICT and the role of library in sustainable development of Nigeria. The paper further identified the challenges of ICT application in libraries. It was recommended among others that, there should be improvement in the capacity and level of ICT adoption by libraries

Groundwater Quality Assessment in Iworoko-Ekiti Environs, South-Western Nigeria using Chemical Indices: Implications for Irrigation and Household Utilities

Groundwater quality of Iworoko-Ekiti and environs for irrigation and domestic purposes has partly been established using chemical indices. Groundwater quality assessment in the area is of great importance because of the influence of various activities in the area. The area is thickly populated by citizens and higher institution students across Nigeria. At the moment, sanitary conditions are very poor as the main occupations are trading and farming. Nineteen hand-dug wells were randomly sampled within the settlement. Flame photometry and spectrometry were used for cations and anions analyses respectively. Average values of pH, EC and TDS are 7.02, 342µS/cm and 230ppm. The average trend of major cations and anions concentrations is Ca2+>Na+>Mg2+>K+ and HCO3->Cl‑>SO42->CO32- respectively. Average values of Degree of Contamination and Revelle Index are 14 and 0.6 respectively. SAR, MAR, %Na, KI, TH, CIA-1 and CIA-2 has an average value of 0.7, 37.4, 24.8, 0.3, 162ppm, 0.4 and 0.9 respectively. Based on these values, the water is suitable for irrigation. In general, 31.6% of the hand-dug wells are slightly acidic and 10.5% have Revelle index >1 above recommended values respectively. 10.5% from the hand-dug wells have KI above one, 5.3% has MAR above recommendation making them unfit for irrigation purposes. Hence, majority of the wells are suitable for irrigation with exception of a few wells. However, the elevated Cl- concentrations in all the wells, make them unfit for human consumption. Weathering of migmatite and granite gneisses together with anthropogenic activities really contributed to the chemistry of the groundwater

Experimental and modelling of alkali-activated mortar compressive strength using hybrid support vector regression and genetic algorithm

This paper presents the outcome of work conducted to develop models for the prediction of compressive strength (CS) of alkali-activated limestone powder and natural pozzolan mortar (AALNM) using hybrid genetic algorithm (GA) and support vector regression (SVR) algorithm, for the first time. The developed hybrid GA-SVR-CS1, GA-SVR-CS3, and GA-SVR-CS14 models are capable of estimating the one-day, three-day, and 14-day compressive strength, respectively, of AALNM up to 96.64%, 90.84%, and 93.40% degree of accuracy as measured on the basis of correlation coefficient between the measured and estimated values for a set of data that is excluded from training and testing phase of the model development. The developed hybrid GA-SVR-CS28E model estimates the 28-days compressive strength of AALNM using the 14-days strength, it performs better than hybrid GA-SVR-CS28C model, hybrid GA-SVR-CS28B model, hybrid GA-SVR-CS28A model, and hybrid GA-SVR-CS28D model that respectively estimates the 28-day compressive strength using three-day strength, one day-strength, all the descriptors and seven day-strength with performance improvement of 103.51%, 124.47%, 149.94%, and 262.08% on the basis of root mean square error. The outcome of this work will promote the use of environment-friendly concrete with excellent strength and provide effective as well as efficient ways of modeling the compressive strength of concrete

Mechanical and Physical Properties of Polyester Reinforced Glass Fibre/Orange Peel Particulate Hybrid Composite

This study was focused on the development of hybrid composed using orange peel particulate dispersed in an unsaturated polyester resin reinforced with chopped strands of E-glass fibers. Orange peel particulate of about 350µm sieve size, of varying weight percentage (3, 6, 9,12 and 15) wt.% and E-glass fiber of constant weight percentage 25.1wt% was used as reinforcements in a polyester matrix. The effect of the orange peel particulate on the physical and mechanical properties of the resulting composite such as tensile strength, bending strength, impact strength and hardness strength was investigated. The results showed remarkable improvement in mechanical properties with increase in percentage of particulate reinforcement. Tensile strength varies from 50.0 to 62.6 MPa, Hardness values varies between 28.6 and 40.8HRB, Impact energy at room temperature, varies between 5.0 to 7.4 Joules, as a function of fiber weight fractions and the flexural strength varies from 74.0 to 85.2 MPa. The best mechanical properties were obtained at 15 Wt.% particulate reinforcements. The results of the physical tests show that the water absorption increases as the weight percentage of the particulate reinforcement increases and the same condition also holds for the density

Enhancing branch predictors using genetic algorithm

Dynamic branch prediction is a hardware technique used to speculate the direction of control branches. Inaccurate prediction will make all speculative works useless while accurate prediction will significantly improve microprocessors performance. In this work, we have shown that Genetic Algorithm (GA) can be used to select (near) optimal parameters for branch predictors in most cases. The GA-enhanced predictors take time to find suitable parameters, but once the values of these parameters are determined, the GA-enhanced predictors take the same time to execute as the basic predictors with increased accuracy. © 2019 IEEE.E

Empirical modelling of the compressive strength of an alkaline activated natural pozzolan and limestone powder mortar

An experimental investigation was conducted to synthesise an alkali-activated binder using natural pozzolan and limestone powder. The effect of the mix parameters such as the binder ratio, NaOH molarity (4 - 14 M), curing temperature (25 - 90 °C), sodium silicate to sodium hydroxide ratio (0.5 - 1.5), fine aggregate to binder ratio (1.4 - 2.2), alkaline activator to binder ratio (0.45 - 0.55) and curing days (1, 3, 7, 14, 28) were determined on the compressive strength of the mortar. A stepwise regression algorithm was developed to estimate the compressive strength of the mortar. Five different models (I-V) were developed using 130 experimental data sets with seven descriptors. Bayesian information criterion (BIC), Akaike's information criterion (AIC) and the sum of square error (SSE) criteria were used to fit the developed model in order to select the best model. The cubic with interactions model (V) is characterised with a high correlation coefficient (97.2 %), the lowest root means square error (1.672), and the lowest mean absolute error (1.313) in comparison with the other four models (I-IV). The outcomes of this work could provide an effective and efficient way of modelling the compressive strength of environmentally friendly binders with minimal experimental stress, limit the uncertainties and errors inherent in a laboratory