Volume 1 Issue 4
1: Electrochemical Analysis of Sulfamethoxazole by Differential pulse voltammograms Method
Manganese and Molybdenum oxides are well-known electro-catalysts in fuel cells systems; they are usually used as anodic materials for the oxidation of low molecular weight alcohols. The utilization of MoO2 and MnO2 as catalysts in the pharmaceutical analysis is not common yet an analytical method for the determination of Sulfamethoxazole (SMX) antibacterial agents in Pharmaceutical Dosage form is developed. The method is based on the voltammetric determination of SMX using modified glassy carbon electrode by molybdenum oxide. The two components are oxidized at the modified electrode surface with the development of current that is linearly proportional to their concentrations in the range of 7.04*10-7- 1*10-3 M for SMX. The oxidation reaction of the two components is pH-dependent, in which the buffer used is Britton-Robinson at pH = 7.00 where maximum peak current and maximum peak separation is obtained. The regression factors obtained from the calibration curves are 0.9790 for SMX and 0.9812 for TMP. The method of analysis was validated, where the limit of detection (LOD) and the limit of quantitation (LOQ) of SMX were calculated to be 1.44*10-4 M, 4.36*10-4 M and 1.27*10-4 M, 3.84*10-4 M respectively, The percentage recovery of both components was also calculated to 81 % for SMX.
Keywords: Sulfamethoxazole, Differential pulse voltammograms, Cyclic Voltammetry, Molybdenum, Nanoparticle, TMP.
2: Seasonal Variation in Physicochemical Properties Of Water From Fish Ponds in Osagin Fish Farm At Akinyele Local Government, Ibadan, Oyo State
Assessment of the quality of water in fish pond is necessary in order to determine its suitability for fish production. One of the problems facing fish farming is inadequate monitoring of water used in fish pond and this has posed serious threat to survival and growth of fish. Constant monitoring of the water from fish farm through physicochemical analysis is one of the main solutions to this problem. This study is aim at examine the seasonal variation in physicochemical properties in water samples from Osagin Fish farm in Akinyele Local Government, Ibadan, Oyo State. Water samples were collected under aseptic condition at a month interval for a year period. Physicochemical properties were assessed by standard methods. The water temperature ranged from 23.67 to 30.00oC, Air temperature ranged from 24.00-33.67oC, the surface pH ranged from 6.73 to 8.80 mg/L, Dissolved oxygen 4.87-8.07 mg/L, Electrical conductivity of the surface water varied from 6.53 µS/cm to 15.23 µS/cm, Total Dissolved Solids ranges from 15.90-52.27 mg/L, Total hardness ranged between 28.3 and 64.67 mg/L, Total Alkalinity varied from 29.67 to 49.67 mg/L, Phosphate ranged from 0.16 to 1.95 mg/L, Chloride ranges between 8.50 to 10.72 mg/L, Nitrate varies from 1.24 to 3.97 mg/L, Calcium ranged from 18.67 to 84.67 mg/L, Sodium ranges between 22.94 to 26.92 mg/L, Magnesium varied from 1.08 to 1.38 mg/L, Potassium ranges between 1.01 to 1.09 mg/L and Iron varied between 0.29 and 0.59 mg/L. The findings of seasonal variation in physicochemical parameters of water samples showed the results were mostly within the required regulatory requirements standards limits. The analysis showed that the water sampled in the fish ponds is suitable for fish and other aquaculture production.
Keywords: Physicochemical, Seasonal, Rainy Season, Dry Season, Fish Pond and Water Quality.
3: REVIEW OF THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN SIGN LANGUAGE RECOGNITION SYSTEM
Communication is the process human beings understand what is said to them and the way they say or express their thoughts, needs and feelings to other people and this is mostly through speech. Although, when it comes to people with hearing impairment, sign language is inevitable. Thus, sign language is the most natural and effective way for communicating among deaf and other people. This study reviewed various schemes in the application of AI in the recognition and interpretation of sign language for machine and human understanding. This study revealed that numerous researchers have proposed and implemented diverse computer and android based application to aid learning and teaching sign language while others developed numerous machine learning algorithms and frameworks to foster sign language recognition system. Thus, this study established that artificial intelligence has greatly developed the teaching, learning and communication with sign language and obviously, artificial intelligence will be capable to resolve the future challenges that may arise in that regards.
Keywords: Artificial Intelligence; Natural Language Processing; Gesture; Sign Language.
4: Techniques and Assessment of Lean Manufacturing Implementation: An Overview
Lean manufacturing is absolutely required for distinct industries to create a competitive industrial standard. Therefore, Lean manufacturing became a standard manufacturing mode of the 21st century. Lean manufacturing could have various corresponding synonyms for example lean management and Lean production. It implicates techniques and tools to minimize non value-added activities from the customer point of view. Waste (Muda) is a serious problem in the industry; it creates non value-added services and poor quality of the product. Waste has seven types which can totally or individually occur in the industry that are transport, inventory, motion, waiting, over-production, over-processing, and defect. Using lean tools and techniques all several wastes can be eliminated. Hence implementing the lean manufacturing system is becoming a core competency for any type of organization to sustain. This paper aims to conduct a quick review of Lean principles, the most commonly used Lean techniques, and Lean assessment. In order to obtain the goals of this work, the previous literature has been examined and the most important lean tools applied in the process of conversion to lean in companies and lean assessment have been also identified. This investigation elaborates that there is an obvious difference in the assessment methodologies according to many factors including the size of the companies, type of companies and the main objective of the assessment.
Keywords: Lean Principle, Lean Tools and Techniques, Lean Assessment.
5: Intelligent Medical Companion using Internet of Things
Improvement in quality of health and medicine has become of paramount importance. The solution to this problem requires a wearable device for continuous monitoring for the patient. As a result, Medical companion was the best choice for the patient who suffers Arrhythmia due to its low-cost and efficacy to save the life of the patient. Moreover, this system is able to deliver reliable heartbeat and body temperature data to a user in a real-time, with a smart mobile application. This system mainly consists of MAX30100 and LM35 that detect heart rate and temperature of the human respectively. The output of these sensors is given to the esp32 section, which runs an Arrhythmia algorithm, which is already programmed, into it. If an abnormal heartbeat is detected, then it activates the alert in the mobile application. This mobile application will automatically send an alert message for the emergency centre and the patient's caregiver; thereby the life of the person can be saved.
Keywords: Arrhythmia, Symptoms of Arrhythmia, Smart System, Internet of Things (IoT), Sensor, Biosensor.
6: Software Bug Prediction Using Static Analysis with Abstract Syntax Trees
Predicting software bugs in the early stage of the software development life cycle had some challenges, such as generating test data that had been used into the test, and exploring the method paths. This paper aims to explore the importance of using and applying abstract syntax trees (AST) with static program analysis in software testing to predict the software bugs that can be found to increase software quality and reduce the time required for discovering the software bugs and money cost by automating the unit tests. To achieve these goals, a new approach proposes to identify the potential bugs in the source code for the method under test by constructing an abstract syntax tree model for the method, then traversing the tree and exploring all paths to find the bugs. Hence, Smart Unit Tests are generated accurately to cover all possible executions paths for the tested method. At the end, the proposed approach uses static analysis, is able to predict all kinds of static bugs and generates the minimal suite of unit tests which are able to cover all the possible execution paths for the tested code. This indicates that the proposed approach achieves good results compared with other techniques regarding the type of bugs that can be predicted as well as the number of generated unit tests that are required to test the code.
Keywords: Bug Prediction; Software Bugs; Software Testing; Software Quality; Test Automation; Unit Testing; White Box Testing
7: Empirical Design Framework for Development of Convolutional Neural Network Based Model
Convolutional Neural Network (CNN) has been described by most researchers as the best when it comes to image classification problems. This Neural Network is made up of high sensitive hyperparameters, such that if not properly design could lead to model misclassification and such returns high false positive (FP) and high false negative(FN). In other to solve this problem, this research proposed and developed design frameworks that mitigate this identified problem when it comes to image classification model using a Convolutional Neural Network.
Keywords: Convolutional Neural Network, Hyperparameters, Model, False Positive, False Negative.
8: Bimodal Biometric Recognition System Based On Score Level Fusion
Biometric system have emerged over the last decade as the most effective method for recognizing individuals and have considerably drawn attention for its various potentials in many applications because of its efficiency in authentication. Unimodal biometric system which uses single biometric trait lacks operational advantages in terms of performance and accuracy. The limitations of unimodal biometric system can be overcome by combining two physiological or behavioral traits to form a bimodal recognition system in ensuring efficiency and effectiveness in identification and verification of individual. In this paper, we developed a face-iris bimodal biometrics recognition system based on score level fusion using Support Vector Machines (SVMs). The system has a recognition accuracy (RA) of 97.9%, false acceptance rate (FRR) of 1.3% and false rejection rate (FAR) of 0.8%.
Keywords: Biometric System, Bimodal, Fusion.
9: A Review on Land Leveling Processing
This paper describes the leveling process and its role in the advancement of technology, the changes that it brought about in achieving the desired levels, and its development from traditional methods to modern technology methods, especially the laser leveling methods that used in the agricultural and the construction and its advantages that make it desirable in these areas and Multiple methods of laser leveling that makes the laser leveling more desirable and used in different fields.
Keywords: Laser leveling; Laser screed; Laser scan; ALLCS; GNSS; GPS; 3D scanner; Types of laser land levelers.