Physicochemical characteristics of the soil around the quarry sites in Ogun State, Nigeria

Quarrying of rock for construction purposes is a significant industry in Nigeria thus enhancing the economy. This study aimed at assessing the physicochemical parameters of the soil around the quarry sites across selected Local Government Areas in Ogun State. Geographic Information System approach was used to map the various quarry locations in Ogun State, from which eight sites were selected namely Isara, Idode, Iwaye, Ogbere, Ilagbe, Adelokun, Baaki Ake and Igodo. A total of 48 soil samples (topsoil and subsoil) were collected for cation exchange capacity (CEC), electrical conductivity (EC) and Particle size distribution using standard procedures. Sampling was done in dry and wet seasons. Data were subjected to descriptive and inferential statistics using SAS package (9.4 version). However Variable Quality Control Package was used to determine the Control Limit for the soil parameters. Sixty quarries were identified. The electrical conductivity of 505.1±0.6 μS/cm of the topsoil at Igodo in the wet season was above the Upper control limit (UCL) of 501.6 μS/cm. The CEC of topsoil and subsoil in all locations (dry and wet seasons) were lower than the control, with the exception of Isara and Baaki Ake in subsoil (wet season). The sand sizes and percentage weights of sizes (topsoil) of Idode and Adelakun were higher than the control (75 – 150 μm with 74.0%) in dry season; while in wet season, Adelokun (180 μm and 62.4%) was higher than the control (75 – 150 μm and 15.1%). In the subsoil during dry season Idode and Baaki Ake were higher than the control (75 – 150 μm and 71.5%); while during wet season Baaki Ake and Adelokun were higher than the control (75 – 150 μm and 19.4%). In conclusion, quarries had polluted the surrounding soils with sandy particle, EC and reduce CEC values

Intelligent agent for formal modelling of temporal multi-agent systems

Software systems are becoming complex and dynamic with the passage of time, and to provide better fault tolerance and resource management they need to have the ability of self-adaptation. Multi-agent systems paradigm is an active area of research for modeling real-time systems. In this research, we have proposed a new agent named SA-ARTIS-agent, which is designed to work in hard real-time temporal constraints with the ability of self-adaptation. This agent can be used for the formal modeling of any self-adaptive real-time multi-agent system. Our agent integrates the MAPE-K feedback loop with ARTIS agent for the provision of self-adaptation. For an unambiguous description, we formally specify our SA-ARTIS-agent using Time-Communicating Object-Z (TCOZ) language. The objective of this research is to provide an intelligent agent with self-adaptive abilities for the execution of tasks with temporal constraints. Previous works in this domain have used Z language which is not expressive to model the distributed communication process of agents. The novelty of our work is that we specified the non-terminating behavior of agents using active class concept of TCOZ and expressed the distributed communication among agents. For communication between active entities, channel communication mechanism of TCOZ is utilized. We demonstrate the effectiveness of the proposed agent using a real-time case study of traffic monitoring system

Predicting wins, losses and attributes' sensitivities in the soccer World Cup 2018 using neural network analysis

Predicting the results of soccer competitions and the contributions of match attributes, in particular, has gained popularity in recent years. Big data processing obtained from different sensors, cameras and analysis systems needs modern tools that can provide a deep understanding of the relationship between this huge amount of data produced by sensors and cameras, both linear and non-linear data. Using data mining tools does not appear sufficient to provide a deep understanding of the relationship between the match attributes and results and how to predict or optimize the results based upon performance variables. This study aimed to suggest a different approach to predict wins, losses and attributes' sensitivities which enables the prediction of match results based on the most sensitive attributes that affect it as a second step. A radial basis function neural network model has successfully weighted the effectiveness of all match attributes and classified the team results into the target groups as a win or loss. The neural network model's output demonstrated a correct percentage of win and loss of 83.3% and 72.7% respectively, with a low Root Mean Square training error of 2.9% and testing error of 0.37%. Out of 75 match attributes, 19 were identified as powerful predictors of success. The most powerful respectively were: the Total Team Medium Pass Attempted (MBA) 100%; the Distance Covered Team Average in zone 3 (15-20 km/h; Zone3_TA) 99%; the Team Average ball delivery into the attacking third of the field (TA_DAT) 80.9%; the Total Team Covered Distance without Ball Possession (Not in_Poss_TT) 76.8%; and the Average Distance Covered by Team (Game TA) 75.1%. Therefore, the novel radial based function neural network model can be employed by sports scientists to adapt training, tactics and opposition analysis to improve performance

Nutritional evaluation of yoghurt prepared by different starter cultures and their physiochemical analysis during storage

Yoghurt was prepared with two different types of starter cultures; Lactobacillus bulgaricus and Lactobacillus acidophilus. The preparation was made by 3, 4 and 5% concentrations. It was stored at 4°C for 12 days. To analyze the effect of the two different cultures and their concentrations on the properties of yoghurt, different physio-chemical tests were performed. These two starter culture slightly enhanced the quality of yoghurt. The results showed that the protein, lactose, ash, fat, acidity and total solid mass were slightly increased while pH and moisture values gradually decreased during the storage period of 12 days. The comparative study of starter cultures showed that L. acidophilus produced good quality yoghurt as compared to L. bulgaricus

An Open Educational Resources for Increasing the Geographic Information Awareness of Business Leaders

This paper describes all aspects of designing, developing and incorporating an Open Educational Resources (OER) to increase the awareness of business leaders on geographical information. The paper includes the proposed methodology for the design and development of the OER. The final proposed OER modules will be offered in various forms including synchronous E-learning modules like distance learning sessions through shared white board, virtual classrooms, scheduled online examination and asynchronous e-learning modules like the coursework through the web, email, message board or online forums and online GI System (GIS) tools. During the pilot implementation of the OER, the selected business leaders who will be primarily the OER learners aiming to build their GI awareness starting by learning the basics of the GI, addressing the business operations’ issues, identifying the GI role in solving the business operations’ issues and finally practicing the GIS & applying it in their daily business operations. In a later stage, an OER assessment should follow in order to check the progress in the business leaders’ GI awareness