Surface Water Pollution by Open Refuse Dumpsite in North Central of Nigeria

Water is a vital resource that is important in ensuring the growth and development of any country. To sustain the basic human needs and the demands for agriculture, industry, conservational and ecosystem, enough quality and quantity water is needed. Contamination of water resources is now a global and public health concern. Hence, this study assessed the water quality of Ndawuse River by measuring the physicochemical parameters and heavy metals concentrations of the river using standard methods. In total, 16 surface water samples were obtained from five locations along the river, from upstream to downstream as well as samples from the dumpsite. The results obtained were compared with the standard limits set by both the World Health Organization and the Federal Environmental Protection Agency for domestic purposes. The results of the measured parameters indicated that biological oxygen demand (85.88 mg/L), turbidity (44.51 NTU), Iron (0.014 - 3.511 mg /L) and chromium (0.078 - 0.14 mg /L) were all above the standard limits. The results further showed that the quality of surface water is being significantly affected by human activities around the Ndawuse River which could pose an adverse health risk to several communities that rely on this river as their primary source of water. Therefore, there is a need for strict enforcement of environmental laws to protect the aquatic ecosystem and to avoid long term cumulative exposure risk that heavy metals may pose on human health.

Igbo Art: A Reflection of the Igbo’s Visual Culture

Visual culture is the expression of the norms and social behavior of a society in visual images. A reflection simply shows you how you look when you stand before a mirror, a clear water or stream. The mirror does not alter, improve or distort your original appearance, neither does it show you a caricature of what stands before it, this is the case with visual images created by a tribe or society. The ‘uli’ is hand drawn body design done on Igbo women and speaks of a culture of body adornment which is a practice that is appreciated by that tribe. The use of pattern of the gliding python snake ‘ije eke’ or ‘ijeagwo’ for wall painting speaks of the Igbo culture as one that appreciates wall paintings based on these patterns. Modern life came and brought a lot of change to the Igbo-speaking people of Nigeria. Change cloaked in the garment of Westernization has influenced the culture of the Igbos. This has resulted in a problem which is a break in the cultural practice that has also affected art produced by the Igbos. Before the colonial masters arrived and changed the established culture practiced by the Igbos, visual images were created that retained the culture of this people. To bring this point to limelight, this paper has adopted a historical method. A large number of works produced during pre and post-colonial era which range from sculptural pieces, paintings and other artifacts, just to mention a few, were studied carefully and it was discovered that the visual images hold the culture or aspects of the culture of the Igbos in their renditions and can rightly serve as a mirror of the Igbo visual culture.

Quantification of Biomethane Potential from Anaerobic Digestion of Food Waste at Vaal University of Technology

The global urbanisation and worldwide economic growth have caused a high rate of food waste generation, resulting in environmental pollution. Food waste disposed on landfills decomposes to produce methane (CH4), a greenhouse gas. Inadequate waste management practices contribute to food waste polluting the environment. Thus effective organic fraction of municipal solid waste (OFMSW) management and treatment are attracting widespread attention in many countries. This problem can be minimised by the employment of anaerobic digestion process, since food waste is rich in organic matter and highly biodegradable, resulting in energy generation and waste volume reduction. The current study investigated the Biomethane Potential (BMP) of the Vaal University of Technology canteen food waste using anaerobic digestion. Tests were performed on canteen food waste, as a substrate, with total solids (TS) of 22%, volatile solids (VS) of 21% and moisture content of 78%. The tests were performed in batch reactors, at a mesophilic temperature of 37 °C, with two different types of inoculum, primary and digested sludge. The resulting CH4 yields for both food waste with digested sludge and primary sludge were equal, being 357 Nml/g VS. This indicated that food waste form this canteen is rich in organic and highly biodegradable. Hence it can be used as a substrate for the anaerobic digestion process. The food waste with digested sludge and primary sludge both fitted the first order kinetic model with k for primary sludge inoculated food waste being 0.278 day-1 with R2 of 0.98, whereas k for digested sludge inoculated food waste being 0.034 day-1, with R2 of 0.847.

Performance Evaluation of Distributed Deep Learning Frameworks in Cloud Environment

2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Intelligent Parking Systems for Quasi-Close Communities

This paper presents the experimental design and needs justifications for a localized intelligent parking system (L-IPS), ideal for quasi-close communities with increasing vehicular volume that depends on limited or constant parking facilities. For a constant supply in parking facilities, the demand for an increasing vehicular volume could lead to poor time conservation or extended travel time, traffic congestion or impeded mobility, and safety issues. Increased negative environmental and economic externalities are other associated and consequent downsides of disparities in demand and supply. This L-IPS is designed using a microcontroller, ultrasonic sensors, LED indicators, such that the current status, in terms of parking spots availability, can be known from the main entrance to the community or a parking zone on a LCD screen. As an advanced traffic management system (ATMS), the L-IPS is designed to resolve aspects of infrastructure-to-driver (I2D) communication and parking detection issues. Thus, this L-IPS can act as a timesaver for users by helping them know the availability of parking spots. Providing on-time, informed routing, to a next preference or seamless moving to berth on the available spot on a proximate facility as the case may be. Its use could also increase safety and increase mobility, and fuel savings and costs, therefore, reducing negative environmental and economic externalities due to transportation systems.

Simultaneous Optimization of Design and Maintenance through a Hybrid Process Using Genetic Algorithms

In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Non-Invasive Data Extraction from Machine Display Units Using Video Analytics

Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

A Theoretical Analysis of Air Cooling System Using Thermal Ejector under Variable Generator Pressure

Due to energy and environment context, research is looking for the use of clean and energy efficient system in cooling industry. In this regard, the ejector represents one of the promising solutions. The thermal ejector is a passive component used for thermal compression in refrigeration and cooling systems, usually activated by heat either waste or solar. The present study introduces a theoretical analysis of the cooling system which uses a gas ejector thermal compression. A theoretical model is developed and applied for the design and simulation of the ejector, as well as the whole cooling system. Besides the conservation equations of mass, energy and momentum, the gas dynamic equations, state equations, isentropic relations as well as some appropriate assumptions are applied to simulate the flow and mixing in the ejector. This model coupled with the equations of the other components (condenser, evaporator, pump, and generator) is used to analyze profiles of pressure and velocity (Mach number), as well as evaluation of the cycle cooling capacity. A FORTRAN program is developed to carry out the investigation. Properties of refrigerant R134a are calculated using real gas equations. Among many parameters, it is thought that the generator pressure is the cornerstone in the cycle, and hence considered as the key parameter in this investigation. Results show that the generator pressure has a great effect on the ejector and on the whole cooling system. At high generator pressures, strong shock waves inside the ejector are created, which lead to significant condenser pressure at the ejector exit. Additionally, at higher generator pressures, the designed system can deliver cooling capacity for high condensing pressure (hot season).

Analyzing Irbid’s Food Waste as Feedstock for Anaerobic Digestion

Food waste samples from Irbid were collected from 5 different sources for 12 weeks to characterize their composition in terms of four food categories; rice, meat, fruits and vegetables, and bread. Average food type compositions were 39% rice, 6% meat, 34% fruits and vegetables, and 23% bread. Methane yield was also measured for all food types and was found to be 362, 499, 352, and 375 mL/g VS for rice, meat, fruits and vegetables, and bread, respectively. A representative food waste sample was created to test the actual methane yield and compare it to calculated one. Actual methane yield (414 mL/g VS) was greater than the calculated value (377 mL/g VS) based on food type proportions and their specific methane yield. This study emphasizes the effect of the types of food and their proportions in food waste on the final biogas production. Findings in this study provide representative methane emission factors for Irbid’s food waste, which represent as high as 68% of total Municipal Solid Waste (MSW) in Irbid, and also indicate the energy and economic value within the solid waste stream in Irbid.

The Role of Fluid Catalytic Cracking in Process Optimisation for Petroleum Refineries

Petroleum refining is a chemical process in which the raw material (crude oil) is converted to finished commercial products for end users. The fluid catalytic cracking (FCC) unit is a key asset in refineries, requiring optimised processes in the context of engineering design. Following the first stage of separation of crude oil in a distillation tower, an additional 40 per cent quantity is attainable in the gasoline pool with further conversion of the downgraded product of crude oil (residue from the distillation tower) using a catalyst in the FCC process. Effective removal of sulphur oxides, nitrogen oxides, carbon and heavy metals from FCC gasoline requires greater separation efficiency and involves an enormous environmental significance. The FCC unit is primarily a reactor and regeneration system which employs cyclone systems for separation.  Catalyst losses in FCC cyclones lead to high particulate matter emission on the regenerator side and fines carryover into the product on the reactor side. This paper aims at demonstrating the importance of FCC unit design criteria in terms of technical performance and compliance with environmental legislation. A systematic review of state-of-the-art FCC technology was carried out, identifying its key technical challenges and sources of emissions.  Case studies of petroleum refineries in Nigeria were assessed against selected global case studies. The review highlights the need for further modelling investigations to help improve FCC design to more effectively meet product specification requirements while complying with stricter environmental legislation.

Exergy Analysis of Vapour Compression Refrigeration System Using R507A, R134a, R114, R22 and R717

This paper compares the energy and exergy efficiency of a vapour compression refrigeration system using refrigerants of different groups. In this study, five different refrigerants including R507A, R134a, R114, R22 and R717 have been studied. EES Program is used to solve the thermodynamic equations. The results of this analysis are shown graphically. Based on the results, energy and exergy efficiencies for R717 are higher than the other refrigerants. Also, the energy and exergy efficiencies will be decreased with increasing the condensing temperature and decreasing the evaporating temperature.

Experimental Analysis of the Plate-on-Tube Evaporator on a Domestic Refrigerator’s Performance

The evaporator is the utmost important component in the refrigeration system, since it enables the refrigerant to draw heat from the desired environment, i.e. the refrigerated space. Studies are being conducted on this component which generally affects the performance of the system, where energy efficient products are important. This study was designed to enhance the effectiveness of the evaporator in the refrigeration cycle of a domestic refrigerator by adjusting the capillary tube length, refrigerant amount, and the evaporator pipe diameter to reduce energy consumption. The experiments were conducted under identical thermal and ambient conditions. Experiment data were analysed using the Design of Experiment (DOE) technique which is a six-sigma method to determine effects of parameters. As a result, it has been determined that the most important parameters affecting the evaporator performance among the selected parameters are found to be the refrigerant amount and pipe diameter. It has been determined that the minimum energy consumption is 6-mm pipe diameter and 16-g refrigerant. It has also been noted that the overall consumption of the experiment sample decreased by 16.6% with respect to the reference system, which has 7-mm pipe diameter and 18-g refrigerant.

The Mouth and Gastrointestinal Tract of the African Lung Fish Protopterus annectens in River Niger at Agenebode, Nigeria

The West African Lung fishes are fishes rich in protein and serve as an important source of food supply for man. The kind of food ingested by this group of fishes is dependent on the alimentary canal as well as the fish’s digestive processes which provide suitable modifications for maximum utilization of food taken. A study of the alimentary canal of P. annectens will expose the best information on the anatomy and histology of the fish. Samples of P. annectens were dissected to reveal the liver, pancreas and entire gut wall. Digital pictures of the mouth, jaws and the Gastrointestinal Tract (GIT) were taken. The entire gut was identified, sectioned and micro graphed. P. annectens was observed to possess a terminal mouth that opens up to 10% of its total body length, an adaptive feature to enable the fish to swallow the whole of its pry. Its dentition is made up of incisors- scissor-like teeth which also help to firmly grip, seize and tear through the skin of prey before swallowing. A short, straight and longitudinal GIT was observed in P. annectens which is known to be common feature in lungfishes, though it is thought to be a primitive characteristic similar to the lamprey. The oesophagus is short and distensible similar to other predatory and carnivorous species. Food is temporarily stored in the stomach before it is passed down into the intestine. A pyloric aperture is seen at the end of the double folded pyloric valve which leads into an intestine that makes up 75% of the whole GIT. The intestine begins at the posterior end of the pyloric aperture and winds down in six coils through the whole length intestine and ends at the cloaca. From this study it is concluded that P. annectens possess a composite GIT with organs similar to other lung fishes; it is a detritor with carnivorous abilities.

Evaluation of Manual and Automatic Calibration Methods for Digital Tachographs

This paper presents a quantitative analysis on the need for automotive calibration methods for digital tachographs. Digital tachographs are mandatory for vehicles used in people and goods transport and they are an important aspect for road safety and inspection. Digital tachographs need to be calibrated for workshops in order for the digital tachograph to display and record speed and odometer values correctly. Calibration of digital tachographs can be performed either manual or automatic. It is shown in this paper that manual calibration of digital tachographs is prone to errors and there can be differences between manual and automatic calibration parameters. Therefore automatic calibration methods are imperative for digital tachograph calibration. The presented experimental results and error analysis clearly support the claims of the paper by evaluating and statistically comparing manual and automatic calibration methods.

Main Cause of Children's Deaths in Indigenous Wayuu Community from Department of La Guajira: A Research Developed through Data Mining Use

The main purpose of this research is to discover what causes death in children of the Wayuu community, and deeply analyze those results in order to take corrective measures to properly control infant mortality. We consider important to determine the reasons that are producing early death in this specific type of population, since they are the most vulnerable to high risk environmental conditions. In this way, the government, through competent authorities, may develop prevention policies and the right measures to avoid an increase of this tragic fact. The methodology used to develop this investigation is data mining, which consists in gaining and examining large amounts of data to produce new and valuable information. Through this technique it has been possible to determine that the child population is dying mostly from malnutrition. In short, this technique has been very useful to develop this study; it has allowed us to transform large amounts of information into a conclusive and important statement, which has made it easier to take appropriate steps to resolve a particular situation.

Recent Trends on Security Constrained Economic Dispatch: A Bibliographic Review

This paper presents a survey of articles, books and reports, which articulate the recent trends and aspects of Security Constrained Economic Dispatch (SCED). The period under consideration is 2008 through 2018. This is done to provide an up-to-date review of the recent major advancements in SCED, the state-of-the-art since 2008, identify further challenging developments needed in smarter grids, and indicate ways to address these challenges. This study consists of three areas of interest, which are very important and relevant for articulating the recent trends of SCED. These areas are: (i) SCED of power system with integrated renewable energy sources (IRES), (ii) SCED with post contingency corrective actions and (iii) Artificial intelligence based SCED.

Developing a Web-Based Tender Evaluation System Based on Fuzzy Multi-Attributes Group Decision Making for Nigerian Public Sector Tendering

Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Numerical Study of the Influence of the Primary Stream Pressure on the Performance of the Ejector Refrigeration System Based on Heat Exchanger Modeling

Numerical models of the heat exchangers in ejector refrigeration system (ERS) were developed and validated with the experimental data. The models were based on the switched heat exchangers model using the moving boundary method, which were capable of estimating the zones’ lengths, the outlet temperatures of both sides and the heat loads at various experimental points. The developed models were utilized to investigate the influence of the primary flow pressure on the performance of an R245fa ERS based on its coefficient of performance (COP) and exergy efficiency. It was illustrated numerically and proved experimentally that increasing the primary flow pressure slightly reduces the COP while the exergy efficiency goes through a maximum before decreasing.

An Improved Adaptive Dot-Shape Beamforming Algorithm Research on Frequency Diverse Array

Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Recent Advances in the Valorization of Goat Milk: Nutritional Properties and Production Sustainability

Goat dairy products are gaining popularity worldwide. In developing countries, but also in many marginal regions of the Mediterranean area, goats represent a great part of the economy and ensure food security. In fact, these small ruminants are able to convert efficiently poor weedy plants and small trees into traditional products of high nutritional quality, showing great resilience to different climatic and environmental conditions. In developed countries, goat milk is appreciated for the presence of health-promoting compounds, bioactive compounds such as conjugated linoleic acids, oligosaccharides, sphingolipids and polyammines. This paper focuses on the recent advances in literature on the nutritional properties of goat milk and on innovative techniques to improve its quality as to become a promising functional food. The environmental sustainability of different methodologies of production has also been examined. Goat milk is valued today as a food of high nutritional value and functional properties as well as small environmental footprint. It is widely consumed in many countries due to high nutritional value, lower allergenic potential, and better digestibility when compared to bovine milk, that makes this product suitable for infants, elderly or sensitive patients. The main differences in chemical composition between a cow and goat milk rely on fat globules that in goat milk are smaller and in fatty acids that present a smaller chain length, while protein, fat, and lactose concentration are comparable. Milk nutritional properties have demonstrated to be strongly influenced by animal diet, genotype, and welfare, but also by season and production systems. Furthermore, there is a growing interest in the dairy industry in goat milk for its relatively high concentration of prebiotics and a good amount of probiotics, which have recently gained importance for their therapeutic potential. Therefore, goat milk is studied as a promising matrix to develop innovative functional foods. In addition to the economic and nutritional value, goat milk is considered a sustainable product for its small environmental footprint, as they require relatively little water and land, and less medical treatments, compared to cow, these characteristics make its production naturally vocated to organic farming. Organic goat milk production has becoming more and more interesting both for farmers and consumers as it can answer to several concerns like environment protection, animal welfare and economical sustainment of rural populations living in marginal lands. These evidences make goat milk an ancient food with novel properties and advantages to be valorized and exploited.