Localizing wireless sensor networks poses a persistent challenge in accurately determining sensor node locations based on known anchor node positions, especially when nodes move between different locations. Conventional techniques like Trilateration, relying on Received Signal Strength Indicators (RSSIs), frequently employed in Wireless Sensor Networks (WSNs), serve the purpose of localizing and tracking moving targets. However, the inherent nonlinear relationship between RSSI and distance often leads to substantial errors in localization estimations. This paper introduces an innovative approach by proposing the utilization of an Adaptive Neural Fuzzy Inference System (ANFIS) as a departure from the conventional RSSI-based method. This ANFIS-based approach aims to initially estimate the locations of single moving targets in a 2-D WSN setup. Subsequently, these initial estimates undergo further refinement within an Unscented Kalman Filter (UKF). The results demonstrate the superior performance of the proposed algorithms in tracking targets, showcasing high accuracy levels within a few centimeters is evident from the mean localization errors for standard RSSI, ANFIS, and ANFIS+UKF, that the ANFIS+UKF framework can handle real-time target tracking issues in WSN utilizing RSSI (5.657, 0.805, and 0.068, respectively). By contrast, the proposed method offers an impressive improvement of 98.797% over the standard RSSI method.
{"title":"ANFIS-based Indoor localization and Tracking in Wireless Sensor Networking","authors":"S. M. Tariq, I.S. Al-Mejibli","doi":"10.4314/njtd.v21i2.2271","DOIUrl":"https://doi.org/10.4314/njtd.v21i2.2271","url":null,"abstract":"Localizing wireless sensor networks poses a persistent challenge in accurately determining sensor node locations based on known anchor node positions, especially when nodes move between different locations. Conventional techniques like Trilateration, relying on Received Signal Strength Indicators (RSSIs), frequently employed in Wireless Sensor Networks (WSNs), serve the purpose of localizing and tracking moving targets. However, the inherent nonlinear relationship between RSSI and distance often leads to substantial errors in localization estimations. This paper introduces an innovative approach by proposing the utilization of an Adaptive Neural Fuzzy Inference System (ANFIS) as a departure from the conventional RSSI-based method. This ANFIS-based approach aims to initially estimate the locations of single moving targets in a 2-D WSN setup. Subsequently, these initial estimates undergo further refinement within an Unscented Kalman Filter (UKF). The results demonstrate the superior performance of the proposed algorithms in tracking targets, showcasing high accuracy levels within a few centimeters is evident from the mean localization errors for standard RSSI, ANFIS, and ANFIS+UKF, that the ANFIS+UKF framework can handle real-time target tracking issues in WSN utilizing RSSI (5.657, 0.805, and 0.068, respectively). By contrast, the proposed method offers an impressive improvement of 98.797% over the standard RSSI method. ","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141705253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A.O. Ogunsanya, E.B. Iorohol, D. Arinze, O. Ogundoyin
Biodegradable polyester obtained from renewable, eco-friendly materials, and natural additives made from debris of production of seafood to create biocomposites is nowadays a possibility. This paper evaluates the physical, morphological, and chemical properties and the degradation stability of polylactic acid/biofillers (magnesium oxide/zinc oxide/crab shell particles) composite as a viable biocomposite material in bone engineering applications. The biofiller showed hygroscopic characteristics. Surface morphology of the composite showed fractured surfaces with interconnected pores suitable for bone cells’ implantation enhancement and propagation. Biofillers effect accelerates the precipitation of calcium apatite formation after 28 days of immersion. The XRD spectra confirmed high composite crystallinity structure of 93.4% due to the nucleation effects of the biofillers. The beneficial role of reinforcing polylactic acid polymer with biofiller showed average pH value of 7.36 and apparent porosity of 40%. Findings from this paper have revealed that the use of crab shell debris such as crab shell can become a resource in biocomposite fabrication. The addition of biofillers provided an effective reinforcement in polylactic acid polymer matrix and hence contributed towards sustainable developments of natural resource materials and biodegradable and bioresorbable material without polluting the environment.
{"title":"Evaluation of MgO-ZnO-Crab Shell Biofillers as Reinforcement for Biodegradable Polylactic Acid (PLA) Composite","authors":"A.O. Ogunsanya, E.B. Iorohol, D. Arinze, O. Ogundoyin","doi":"10.4314/njtd.v21i2.2127","DOIUrl":"https://doi.org/10.4314/njtd.v21i2.2127","url":null,"abstract":"Biodegradable polyester obtained from renewable, eco-friendly materials, and natural additives made from debris of production of seafood to create biocomposites is nowadays a possibility. This paper evaluates the physical, morphological, and chemical properties and the degradation stability of polylactic acid/biofillers (magnesium oxide/zinc oxide/crab shell particles) composite as a viable biocomposite material in bone engineering applications. The biofiller showed hygroscopic characteristics. Surface morphology of the composite showed fractured surfaces with interconnected pores suitable for bone cells’ implantation enhancement and propagation. Biofillers effect accelerates the precipitation of calcium apatite formation after 28 days of immersion. The XRD spectra confirmed high composite crystallinity structure of 93.4% due to the nucleation effects of the biofillers. The beneficial role of reinforcing polylactic acid polymer with biofiller showed average pH value of 7.36 and apparent porosity of 40%. Findings from this paper have revealed that the use of crab shell debris such as crab shell can become a resource in biocomposite fabrication. The addition of biofillers provided an effective reinforcement in polylactic acid polymer matrix and hence contributed towards sustainable developments of natural resource materials and biodegradable and bioresorbable material without polluting the environment. ","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"70 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141691017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In an attempt to enhance the surface integrity of machined parts in the manufacturing industries, facemilled surface profiles of pearlitic ductile iron were characterized and analysed based on the effects of some cutting parameters. The pearlitic ductile iron used was locally prepared. Atomic Force Microscope and Scanning Electron Microscope were used to characterizing the roughness profile of the machined workpiece. The results showed increase in depth of cut from 400.37 to 652.37 nm at constant cutting fluid flow rate, cutting speed and feed rate. Also, at varying cutting fluid flow rate, the roughness parameter decreased from 733.56 to 272.84 nm at constant feed rate, depth of cut and cutting speed. Similar result was obtained with varying feed rate. However, there exists no definable course as cutting speed increases at constant cutting fluid flow rate, depth of cut and feed rate. In conclusion, it was found that machining at cutting fluid flow rate of 4 l/min, feed rate of 30 mm/rev, depth of cut of 0.2 mm and cutting speed of 1000 rev/min produced better quality surfaces. Therefore, the findings in this study will be useful for the manufacturing industries to improve on the surface reliability of the face milling process.
{"title":"Characterization And Impact Of Cutting Parameters On Face-Milled Surfaces Of Pearlitic Ductile Iron","authors":"O.O. Ilori, T.F. Oyewusi, O.A. Fadare, F.F. Adeyemi","doi":"10.4314/njtd.v21i2.2350","DOIUrl":"https://doi.org/10.4314/njtd.v21i2.2350","url":null,"abstract":"In an attempt to enhance the surface integrity of machined parts in the manufacturing industries, facemilled surface profiles of pearlitic ductile iron were characterized and analysed based on the effects of some cutting parameters. The pearlitic ductile iron used was locally prepared. Atomic Force Microscope and Scanning Electron Microscope were used to characterizing the roughness profile of the machined workpiece. The results showed increase in depth of cut from 400.37 to 652.37 nm at constant cutting fluid flow rate, cutting speed and feed rate. Also, at varying cutting fluid flow rate, the roughness parameter decreased from 733.56 to 272.84 nm at constant feed rate, depth of cut and cutting speed. Similar result was obtained with varying feed rate. However, there exists no definable course as cutting speed increases at constant cutting fluid flow rate, depth of cut and feed rate. In conclusion, it was found that machining at cutting fluid flow rate of 4 l/min, feed rate of 30 mm/rev, depth of cut of 0.2 mm and cutting speed of 1000 rev/min produced better quality surfaces. Therefore, the findings in this study will be useful for the manufacturing industries to improve on the surface reliability of the face milling process. ","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"32 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141715886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There is usually a need to enhance the properties of soils with poor geotechnical properties encountered during construction. The utilisation of Rice Husk Ash (RHA) - based geopolymer for improving some properties of two selected tropical soils was investigated. The Atterberg’s limits (Liquid limit, LL and plastic limit, PL), compaction properties (maximum dry density, MDD and optimum moisture content, OMC), California bearing ratio (CBR) and unconfined compression strength (UCS) of the un-stabilized and stabilized soils were estimated. The soil samples were stabilized with alkali activated RHA varying from 3 to 15% (in 3% increment). Alkaline activation was achieved by using a mixture of NaOH(aq) and Na2SiO3(aq) in ratio 1:2. Mineralogy and elemental analysis of the un-stabilized soils, RHA and stabilized soils were obtained using X-Ray diffraction, X-Ray Fluorescence, EDS and SEM. The LL and PI of the stabilized soils decreased with as much as 30 and 40%, respectively, while the CBR and UCS increased as much as 300% and 1500%, respectively. SEM and EDS analysis of the treated soil showed the formation of crystalline hydration products. It is concluded that RHA based geopolymer is a potential environmentally sustainable stabiliser in tropical climatic condition.
{"title":"Impact of Rice Husk Ash Based-Geopolymer on Some Geotechnical Properties of Selected Residual Tropical Soils","authors":"A. L. Ayodele, I.K. Ajibola, A. Fajobi","doi":"10.4314/njtd.v21i2.2417","DOIUrl":"https://doi.org/10.4314/njtd.v21i2.2417","url":null,"abstract":"There is usually a need to enhance the properties of soils with poor geotechnical properties encountered during construction. The utilisation of Rice Husk Ash (RHA) - based geopolymer for improving some properties of two selected tropical soils was investigated. The Atterberg’s limits (Liquid limit, LL and plastic limit, PL), compaction properties (maximum dry density, MDD and optimum moisture content, OMC), California bearing ratio (CBR) and unconfined compression strength (UCS) of the un-stabilized and stabilized soils were estimated. The soil samples were stabilized with alkali activated RHA varying from 3 to 15% (in 3% increment). Alkaline activation was achieved by using a mixture of NaOH(aq) and Na2SiO3(aq) in ratio 1:2. Mineralogy and elemental analysis of the un-stabilized soils, RHA and stabilized soils were obtained using X-Ray diffraction, X-Ray Fluorescence, EDS and SEM. The LL and PI of the stabilized soils decreased with as much as 30 and 40%, respectively, while the CBR and UCS increased as much as 300% and 1500%, respectively. SEM and EDS analysis of the treated soil showed the formation of crystalline hydration products. It is concluded that RHA based geopolymer is a potential environmentally sustainable stabiliser in tropical climatic condition. ","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"101 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141695671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abdulrahaman Okino Otuoze, M. W. Mustafa, U. Sultana, E. A. Abiodun, B. Jimada-Ojuolape, O. Ibrahim, I. O. Avazi-Omeiza, A. I. Abdullateef
The successful implementation of Smart Grids heavily relies on energy efficiency, particularly through the Advanced Metering Infrastructure (AMI) and Smart Electricity Meters (SEM). However, cyber-attacks pose a threat to SEM, with electricity theft being a primary motivation. Despite the valuable data provided by SEM for analytical purposes, existing methods to identify theft involve cumbersome and costly on-site inspections. This research proposes an electricity theft detection model using the Long Short-Term Memory (LSTM) network. The model employs a collective anomaly approach, defining prediction errors through a threshold and forecast horizon. Suspicious consumption profiles are analysed, and a fuzzy inference system (FIS) implemented in MATLAB 2021b is used to model security risks based on these profiles. The study utilizes energy consumption data from four diverse consumer profiles (consumers 1, 2, 3, and 4) to develop consumer-specific LSTM models for detection and an FIS model for confirmation. Tampered consumer data is identified and confirmed based on selected AMI parameters. While all consumers exhibit suspicious profiles at times, only consumers 2 and 3 are confirmed as engaging in electricity theft. This research provides a robust approach to detecting and verifying fraudulent consumption profiles within the context of AMI, offering a more reliable dimension to theft detection and confirmation.
智能电网的成功实施在很大程度上依赖于能源效率，特别是通过先进计量基础设施（AMI）和智能电表（SEM）。然而，网络攻击对 SEM 构成了威胁，偷电是其主要动机。尽管智能电表为分析目的提供了宝贵的数据，但现有的窃电识别方法涉及繁琐而昂贵的现场检查。本研究提出了一种使用长短期记忆（LSTM）网络的窃电检测模型。该模型采用集体异常方法，通过阈值和预测范围来定义预测误差。对可疑的消耗曲线进行了分析，并使用在 MATLAB 2021b 中实施的模糊推理系统 (FIS) 对基于这些曲线的安全风险进行建模。该研究利用四种不同消费者（消费者 1、2、3 和 4）的能源消耗数据，开发了用于检测的特定消费者 LSTM 模型和用于确认的 FIS 模型。根据选定的 AMI 参数识别和确认被篡改的用户数据。虽然所有消费者有时都表现出可疑特征，但只有消费者 2 和 3 被证实参与了窃电行为。这项研究提供了一种在 AMI 背景下检测和验证欺诈性消费特征的可靠方法，为窃电检测和确认提供了一个更可靠的维度。
{"title":"Detection and confirmation of electricity thefts in Advanced Metering Infrastructure by Long Short-Term Memory and fuzzy inference system models","authors":"Abdulrahaman Okino Otuoze, M. W. Mustafa, U. Sultana, E. A. Abiodun, B. Jimada-Ojuolape, O. Ibrahim, I. O. Avazi-Omeiza, A. I. Abdullateef","doi":"10.4314/njtd.v21i1.2294","DOIUrl":"https://doi.org/10.4314/njtd.v21i1.2294","url":null,"abstract":"The successful implementation of Smart Grids heavily relies on energy efficiency, particularly through the Advanced Metering Infrastructure (AMI) and Smart Electricity Meters (SEM). However, cyber-attacks pose a threat to SEM, with electricity theft being a primary motivation. Despite the valuable data provided by SEM for analytical purposes, existing methods to identify theft involve cumbersome and costly on-site inspections. This research proposes an electricity theft detection model using the Long Short-Term Memory (LSTM) network. The model employs a collective anomaly approach, defining prediction errors through a threshold and forecast horizon. Suspicious consumption profiles are analysed, and a fuzzy inference system (FIS) implemented in MATLAB 2021b is used to model security risks based on these profiles. The study utilizes energy consumption data from four diverse consumer profiles (consumers 1, 2, 3, and 4) to develop consumer-specific LSTM models for detection and an FIS model for confirmation. Tampered consumer data is identified and confirmed based on selected AMI parameters. While all consumers exhibit suspicious profiles at times, only consumers 2 and 3 are confirmed as engaging in electricity theft. This research provides a robust approach to detecting and verifying fraudulent consumption profiles within the context of AMI, offering a more reliable dimension to theft detection and confirmation.","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"137 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140251509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. K. Lawal, I. O. Muniru, S. A. Yahaya, M. O. Ibitoye
Sudden cardiac death and arrhythmia are responsible for about 15-20% of cardiovascular disease incidences. Conventionally, the prediction and diagnosis of cardiovascular disorders (CVDs) have been mainly through the evaluation of ECG patterns by cardiologists. To improve the accuracy of and automate this process, and facilitate early detection, Heart Rate Variability (HRV) analysis has been promoted as a diagnostic and predictive tool for CVDs. In the present study, a machine learning model capable of detecting the presence of arrhythmia, using HRV indices obtained from ECG signals was built. Unlike similar works in the literature, this study deployed the developed model on Raspberry Pi with Streamlit software. Two ECG datasets from the Physionet database, one with arrhythmia patients (48 half-hour recordings) and another with healthy individuals (18 24-hour recordings), were employed. An ensemble of seven different machine learning models was used on the two sets of datasets to classify ECG recordings into Arrhythmia and Normal Sinus Rhythm (NSR). The best models were able to predict the presence of Arrhythmia in a 3-minute recording with an accuracy of 95.96%, and in a 10-minute recording with an accuracy of 96.20%. These performance measures were calculated using test dataset. The Random Forest models also had the highest precision, AUC, (Area under the Curve) recall, and F1 scores compared to the other models tested. The highest performing model (i.e., Random Forest Model) was then deployed onto a Raspberry Pi with Streamlit as the software interface for usability. This was done to facilitate a smooth user experience for faster and seamless diagnoses for cardiologists.
{"title":"Automated identification of heart arrhythmias through HRV analysis and machine learning","authors":"S. K. Lawal, I. O. Muniru, S. A. Yahaya, M. O. Ibitoye","doi":"10.4314/njtd.v21i1.2208","DOIUrl":"https://doi.org/10.4314/njtd.v21i1.2208","url":null,"abstract":"Sudden cardiac death and arrhythmia are responsible for about 15-20% of cardiovascular disease incidences. Conventionally, the prediction and diagnosis of cardiovascular disorders (CVDs) have been mainly through the evaluation of ECG patterns by cardiologists. To improve the accuracy of and automate this process, and facilitate early detection, Heart Rate Variability (HRV) analysis has been promoted as a diagnostic and predictive tool for CVDs. In the present study, a machine learning model capable of detecting the presence of arrhythmia, using HRV indices obtained from ECG signals was built. Unlike similar works in the literature, this study deployed the developed model on Raspberry Pi with Streamlit software. Two ECG datasets from the Physionet database, one with arrhythmia patients (48 half-hour recordings) and another with healthy individuals (18 24-hour recordings), were employed. An ensemble of seven different machine learning models was used on the two sets of datasets to classify ECG recordings into Arrhythmia and Normal Sinus Rhythm (NSR). The best models were able to predict the presence of Arrhythmia in a 3-minute recording with an accuracy of 95.96%, and in a 10-minute recording with an accuracy of 96.20%. These performance measures were calculated using test dataset. The Random Forest models also had the highest precision, AUC, (Area under the Curve) recall, and F1 scores compared to the other models tested. The highest performing model (i.e., Random Forest Model) was then deployed onto a Raspberry Pi with Streamlit as the software interface for usability. This was done to facilitate a smooth user experience for faster and seamless diagnoses for cardiologists.","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"42 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140253605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Under Partial Shading Conditions (PSCs), conventional MPPT techniques fail to locate the Global Maximum Power Point (GMPP) for PV generators, and when PSCs change suddenly and repetitively, several GMPP tracking techniques takes time to find or miss the target. To overcome these shortcomings, this paper proposes a new and fast technique that can identify and catch very quickly the GMPP. Due to the use of a PID controller, the PV system is improved in terms of response time and becomes very fast. On the other hand, the proposed algorithm is developed upon other known algorithms and enhanced in order to identify the occurrence of PSCs and to find the GMPP. The measured points during identification and searching process are reduced which increases the power efficiency of the PV system. The time required for the algorithm to catch the GMPP is minimized by 25% compared with other works. To examine the performance of the system a hard scenario, that contains several uniform and partial shading conditions, is used. The simulation is implemented in Matlab/Simulink. The obtained results show clearly the advantage of the proposed technique over others.
{"title":"Fast indirect GMPPT method for PV systems under uniform and partial shading conditions","authors":"K. Ameur, A. Hadjaissa, N. Abouchabana, A. Rabehi","doi":"10.4314/njtd.v21i1.1931","DOIUrl":"https://doi.org/10.4314/njtd.v21i1.1931","url":null,"abstract":"Under Partial Shading Conditions (PSCs), conventional MPPT techniques fail to locate the Global Maximum Power Point (GMPP) for PV generators, and when PSCs change suddenly and repetitively, several GMPP tracking techniques takes time to find or miss the target. To overcome these shortcomings, this paper proposes a new and fast technique that can identify and catch very quickly the GMPP. Due to the use of a PID controller, the PV system is improved in terms of response time and becomes very fast. On the other hand, the proposed algorithm is developed upon other known algorithms and enhanced in order to identify the occurrence of PSCs and to find the GMPP. The measured points during identification and searching process are reduced which increases the power efficiency of the PV system. The time required for the algorithm to catch the GMPP is minimized by 25% compared with other works. To examine the performance of the system a hard scenario, that contains several uniform and partial shading conditions, is used. The simulation is implemented in Matlab/Simulink. The obtained results show clearly the advantage of the proposed technique over others.","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"72 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140251860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. O. Abu, H. I. Adegoke, E. Odebunmi, M. A. Shehzad
The efficiencies of raw and modified kaolinite mineral in removing selected heavy metal ions from their respective aqueous solutions were investigated. The mineral was modified through two different methods; i) activation with HNO3, H2SO4, H3PO4, CH3COOH and C2H2O4 acids to form NK, SK, PK, AK and OK acid activated clays respectively and ii) preparations of 3:1 and 1:1 Kaolinite: Bentonite blends to form UBK and EBK composites respectively through manual blending. The adsorbents were characterized by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Fourier Transform Infra-Red Spectroscopy (FTIR) and Brunauer Emmett Teller (BET) analysis for surface area determination. The surface area increased in some of the modified clays from 114.9457 m2/g (RK) to 288.685 m2/g (EBK), 205.92 m2/g (UBK), 162.227 m2/g (NK), 151.335 m2/g (SK), and 115.837 m2/g (OK) but reduced to 113.872 m2/g (PK) and 112.865 m2/g (AK) after modification. Adsorption studies were subsequently conducted out to remove Pb2+, Cd2+ and Ni2+ ions from synthetic solutions. Pb2+ was found to be most removed (383.5 mg g-1 (RK), 591.13 mg g-1 (EBK), 576.61 mg g-1 (UBK), 475 mg g-1 (NK), 450 mg g-1 (SK), and 425 mg g-1 (PK), 375 mg g-1 (OK) and 375 mg g-1 (AK)) with highest removals on the composites.
{"title":"Enhancing adsorption capacity of a kaolinite mineral through acid activation and manual blending with a 2:1 clay","authors":"T. O. Abu, H. I. Adegoke, E. Odebunmi, M. A. Shehzad","doi":"10.4314/njtd.v21i1.2269","DOIUrl":"https://doi.org/10.4314/njtd.v21i1.2269","url":null,"abstract":"The efficiencies of raw and modified kaolinite mineral in removing selected heavy metal ions from their respective aqueous solutions were investigated. The mineral was modified through two different methods; i) activation with HNO3, H2SO4, H3PO4, CH3COOH and C2H2O4 acids to form NK, SK, PK, AK and OK acid activated clays respectively and ii) preparations of 3:1 and 1:1 Kaolinite: Bentonite blends to form UBK and EBK composites respectively through manual blending. The adsorbents were characterized by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Fourier Transform Infra-Red Spectroscopy (FTIR) and Brunauer Emmett Teller (BET) analysis for surface area determination. The surface area increased in some of the modified clays from 114.9457 m2/g (RK) to 288.685 m2/g (EBK), 205.92 m2/g (UBK), 162.227 m2/g (NK), 151.335 m2/g (SK), and 115.837 m2/g (OK) but reduced to 113.872 m2/g (PK) and 112.865 m2/g (AK) after modification. Adsorption studies were subsequently conducted out to remove Pb2+, Cd2+ and Ni2+ ions from synthetic solutions. Pb2+ was found to be most removed (383.5 mg g-1 (RK), 591.13 mg g-1 (EBK), 576.61 mg g-1 (UBK), 475 mg g-1 (NK), 450 mg g-1 (SK), and 425 mg g-1 (PK), 375 mg g-1 (OK) and 375 mg g-1 (AK)) with highest removals on the composites.","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"23 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. K. Ibrahim, M. Abolarin, A. S. Abdulrahman, O. Adedipe, U. G. Okoro
Traditional prosthetic materials often lack the desired properties to mimic the mechanical behaviour of natural bone, leading to complications and reduced implant longevity. This study aims to conduct a biomechanical and physical properties selection analysis for biocomposite prostheses' suitable for replacing bone atrophy. This involves evaluating the mechanical properties of developed biocomposites with different structures (dense, porous and gradient) to ensure compatibility with the mechanical properties of bone. The radar chart was adopted to compare and evaluate the mechanical strength of various biocomposite implants and identify the most suitable prosthesis for load-bearing bone replacement. The study utilises powder metallurgy, scanning electron microscopy (SEM), and ImageJ software to produce and characterise the pore size distribution of the biocomposites, respectively. The findings of this study revealed the gradient and porous biocomposites exhibited desired mechanical properties with porosity of 20.67 and 27.72 % pore size up to 134 and 256 μm, compressive strength of 174 and 149.29 MPa and compressive modulus of 30.42 and 28.3 GPa respectively. The SEM analysis, coupled with pore size distribution and porosity percentage measurements, offers valuable information for designing and fabricating biomaterials with enhanced properties. The gradient biocomposite was identified to be the best sample for load-bearing bone replacements by the selection analysis because of its high compressive strength and low modulus, which is within the established cortical bone mechanical properties.
{"title":"Biomechanical and physical properties selection of Ti-Ha-CaCO3 biocomposite prostheses for replacement of bone atrophy","authors":"H. K. Ibrahim, M. Abolarin, A. S. Abdulrahman, O. Adedipe, U. G. Okoro","doi":"10.4314/njtd.v21i1.2174","DOIUrl":"https://doi.org/10.4314/njtd.v21i1.2174","url":null,"abstract":"Traditional prosthetic materials often lack the desired properties to mimic the mechanical behaviour of natural bone, leading to complications and reduced implant longevity. This study aims to conduct a biomechanical and physical properties selection analysis for biocomposite prostheses' suitable for replacing bone atrophy. This involves evaluating the mechanical properties of developed biocomposites with different structures (dense, porous and gradient) to ensure compatibility with the mechanical properties of bone. The radar chart was adopted to compare and evaluate the mechanical strength of various biocomposite implants and identify the most suitable prosthesis for load-bearing bone replacement. The study utilises powder metallurgy, scanning electron microscopy (SEM), and ImageJ software to produce and characterise the pore size distribution of the biocomposites, respectively. The findings of this study revealed the gradient and porous biocomposites exhibited desired mechanical properties with porosity of 20.67 and 27.72 % pore size up to 134 and 256 μm, compressive strength of 174 and 149.29 MPa and compressive modulus of 30.42 and 28.3 GPa respectively. The SEM analysis, coupled with pore size distribution and porosity percentage measurements, offers valuable information for designing and fabricating biomaterials with enhanced properties. The gradient biocomposite was identified to be the best sample for load-bearing bone replacements by the selection analysis because of its high compressive strength and low modulus, which is within the established cortical bone mechanical properties.","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"21 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140252744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In multi-agent systems, achieving consensus among autonomous agents is a fundamental problem with wide-ranging applications, from autonomous robotics to distributed sensor networks. However, the real-world deployment of such systems often involves communication links prone to impairments, including packet loss, delays, and network congestion. These communication challenges present formidable obstacles to achieving consensus reliably and efficiently. In this paper, consensus protocols were introduced for network with and without communication impairments and convergence analysis were provided in all the cases. The intricate dynamics of consensus issues in multi-agent-based distributed control under the influence of communication link impairments, connectivity and consensus protocol were established. Undirected communication graphs used to model the topology for agents’ connectivity is significant to addressing consensus issues of communicating agents. The paper also discusses the tradeoffs and design considerations in developing consensus strategies resilient to communication failures while optimizing performance. Simulation results show that an isolated agent in a network can achieve consensus only when there is a reference value. It was also established that communication impairments significantly degrade the performance of distributed agents in a network.
{"title":"Consensus issues in multi-agent-based distributed control with communication link impairments","authors":"O. S. Akinwale, D. F. Mojisola, P. A. Adediran","doi":"10.4314/njtd.v21i1.2212","DOIUrl":"https://doi.org/10.4314/njtd.v21i1.2212","url":null,"abstract":"In multi-agent systems, achieving consensus among autonomous agents is a fundamental problem with wide-ranging applications, from autonomous robotics to distributed sensor networks. However, the real-world deployment of such systems often involves communication links prone to impairments, including packet loss, delays, and network congestion. These communication challenges present formidable obstacles to achieving consensus reliably and efficiently. In this paper, consensus protocols were introduced for network with and without communication impairments and convergence analysis were provided in all the cases. The intricate dynamics of consensus issues in multi-agent-based distributed control under the influence of communication link impairments, connectivity and consensus protocol were established. Undirected communication graphs used to model the topology for agents’ connectivity is significant to addressing consensus issues of communicating agents. The paper also discusses the tradeoffs and design considerations in developing consensus strategies resilient to communication failures while optimizing performance. Simulation results show that an isolated agent in a network can achieve consensus only when there is a reference value. It was also established that communication impairments significantly degrade the performance of distributed agents in a network.","PeriodicalId":31273,"journal":{"name":"Nigerian Journal of Technological Development","volume":"26 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140253338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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