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Fentie</title> <meta name="description" content="Search results for: Tarekegn Fentie"> <meta name="keywords" content="Tarekegn Fentie"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Tarekegn Fentie"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 14</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Tarekegn Fentie</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">14</span> Electrochemical Treatment and Chemical Analyses of Tannery Wastewater Using Sacrificial Aluminum Electrode, Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dessie%20Tibebe">Dessie Tibebe</a>, <a href="https://publications.waset.org/abstracts/search?q=Muluken%20Asmare"> Muluken Asmare</a>, <a href="https://publications.waset.org/abstracts/search?q=Marye%20Mulugeta"> Marye Mulugeta</a>, <a href="https://publications.waset.org/abstracts/search?q=Yezbie%20Kassa"> Yezbie Kassa</a>, <a href="https://publications.waset.org/abstracts/search?q=Zerubabel%20Moges"> Zerubabel Moges</a>, <a href="https://publications.waset.org/abstracts/search?q=Dereje%20Yenealem"> Dereje Yenealem</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarekegn%20Fentie"> Tarekegn Fentie</a>, <a href="https://publications.waset.org/abstracts/search?q=Agmas%20Amare"> Agmas Amare</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The performance of electrocoagulation (EC) using Aluminium electrodes for the treatment of effluent-containing chromium metal using a ﬁxed bed electrochemical batch reactor was studied. In the present work, the efficiency evaluation of EC in removing physicochemical and heavy metals from real industrial tannery wastewater in the Amhara region, collected from Bahirdar, Debre Brihan, and Haik, was investigated. The treated and untreated samples were determined by AAS and ICP OES spectrophotometers. The results indicated that selected heavy metals were removed in all experiments with high removal percentages. The optimal results were obtained regarding both cost and electrocoagulation efficiency with initial pH = 3, initial concentration = 40 mg/L, electrolysis time = 30 min, current density = 40 mA/cm2, and temperature = 25oC favored metal removal. The maximum removal percentages of selected metals obtained were 84.42% for Haik, 92.64% for Bahir Dar and 94.90% for Debre Brihan. The sacrificial electrode and sludge were characterized by FT-IR, SEM and XRD. After treatment, some metals like chromium will be used again as a tanning agent in leather processing to promote a circular economy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrochemical" title="electrochemical">electrochemical</a>, <a href="https://publications.waset.org/abstracts/search?q=treatment" title=" treatment"> treatment</a>, <a href="https://publications.waset.org/abstracts/search?q=aluminum" title=" aluminum"> aluminum</a>, <a href="https://publications.waset.org/abstracts/search?q=tannery%20effluent" title=" tannery effluent"> tannery effluent</a> </p> <a href="https://publications.waset.org/abstracts/174363/electrochemical-treatment-and-chemical-analyses-of-tannery-wastewater-using-sacrificial-aluminum-electrode-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174363.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">110</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">13</span> Treatment and Characterization of Cadmium Metal From Textile Factory Wastewater by Electrochemical Process Using Aluminum Plate Electrode</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dessie%20Tibebe">Dessie Tibebe</a>, <a href="https://publications.waset.org/abstracts/search?q=Yeshifana%20Ayenew"> Yeshifana Ayenew</a>, <a href="https://publications.waset.org/abstracts/search?q=Marye%20Mulugeta"> Marye Mulugeta</a>, <a href="https://publications.waset.org/abstracts/search?q=Yezbie%20Kassa"> Yezbie Kassa</a>, <a href="https://publications.waset.org/abstracts/search?q=Zerubabel%20Moges"> Zerubabel Moges</a>, <a href="https://publications.waset.org/abstracts/search?q=Dereje%20Yenealem"> Dereje Yenealem</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarekegn%20Fentie"> Tarekegn Fentie</a>, <a href="https://publications.waset.org/abstracts/search?q=Agmas%20Amare"> Agmas Amare</a>, <a href="https://publications.waset.org/abstracts/search?q=Hailu%20Sheferaw%20Ayele"> Hailu Sheferaw Ayele</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Electrochemical treatment technology is a technique used for wastewater treatment due to its ability to eliminate impurities that are not easily removed by chemical processes. The objective of the study is the treatment and characterization of textile wastewater by an electrochemical process. The results obtained at various operational parameters indicated that at 20 minutes of electrochemical process at ( pH =7), initial concentration 10 mg/L, current density 37.5 mA/cm², voltage 9 v and temperature 25⁰C the highest removal efficiency was achieved. The kinetics of removal of selected metal by electrochemical treatment has been successfully described by the first-order rate equation. The results of microscopic techniques using SEM for the scarified electrode before treatment were uniform and smooth, but after the electrochemical process, the morphology was completely changed. This is due to the detection of the adsorbed aluminum hydroxide coming from adsorption of the conducting electrolyte, chemicals used in the experiments, alloying and the scrap impurities of the anode and cathode. The FTIR spectroscopic analysis broad bands at 3450 cm-¹ representing O-H functional groups, while the presence of H-O-H and Al-H groups are indicated by the bands at 2850-2750 cm-¹ and 1099 representing C-H functional groups. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrochemical" title="electrochemical">electrochemical</a>, <a href="https://publications.waset.org/abstracts/search?q=treatment" title=" treatment"> treatment</a>, <a href="https://publications.waset.org/abstracts/search?q=textile%20wastewater" title=" textile wastewater"> textile wastewater</a>, <a href="https://publications.waset.org/abstracts/search?q=kinetics" title=" kinetics"> kinetics</a>, <a href="https://publications.waset.org/abstracts/search?q=removal%20efficiency" title=" removal efficiency"> removal efficiency</a> </p> <a href="https://publications.waset.org/abstracts/174364/treatment-and-characterization-of-cadmium-metal-from-textile-factory-wastewater-by-electrochemical-process-using-aluminum-plate-electrode" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174364.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">97</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">12</span> Deep Learning-Based Channel Estimation for RIS-Assisted Unmanned Aerial Vehicle-Enabled Wireless Communication System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getaneh%20Berie%20Tarekegn">Getaneh Berie Tarekegn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=channel%20estimation" title="channel estimation">channel estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=reconfigurable%20intelligent%20surfaces" title=" reconfigurable intelligent surfaces"> reconfigurable intelligent surfaces</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=unmanned%20aerial%20vehicles" title=" unmanned aerial vehicles"> unmanned aerial vehicles</a> </p> <a href="https://publications.waset.org/abstracts/184507/deep-learning-based-channel-estimation-for-ris-assisted-unmanned-aerial-vehicle-enabled-wireless-communication-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184507.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">57</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11</span> Deep Learning-Based Channel Estimation for Reconfigurable Intelligent Surface-Assisted Unmanned Aerial Vehicle-Enabled Wireless Communication System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getaneh%20Berie%20Tarekegn">Getaneh Berie Tarekegn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=channel%20estimation" title="channel estimation">channel estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=reconfigurable%20intelligent%20surfaces" title=" reconfigurable intelligent surfaces"> reconfigurable intelligent surfaces</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=unmanned%20aerial%20vehicles" title=" unmanned aerial vehicles"> unmanned aerial vehicles</a> </p> <a href="https://publications.waset.org/abstracts/174128/deep-learning-based-channel-estimation-for-reconfigurable-intelligent-surface-assisted-unmanned-aerial-vehicle-enabled-wireless-communication-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174128.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">111</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10</span> Campaigns of Youth Empowerment and Unemployment In Development Discourses: In the Case of Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fentie">Fentie</a>, <a href="https://publications.waset.org/abstracts/search?q=Belay"> Belay</a>, <a href="https://publications.waset.org/abstracts/search?q=Mulat"> Mulat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In today’s high decrement figure of the global economy, nations are facing many economic, social and political challenges; universally, there is high distress of food and other survival insecurity. Further, as a result of conflict, natural disasters, and leadership influences, youths are existentially less empowered and unemployed, especially in developing countries. With this situation to handle well challenges, it’s important to search, investigate and deliberate about youth, unemployment, empowerment and possible management fashions, as youths have the potential to carry and fight such battles. The method adopted is a qualitative analysis of secondary data sources in youth empowerment, unemployment and development as an inclusive framework. Youth unemployment is a major development headache for most African countries. In Ethiopia, following weak youth empowerment, youth unemployment has increased from time to time, and quality education and organization linkage matter as an important constraint. As a management challenge, although accessibility of quality education for Ethiopian youths is an important constraint, the country's youths are fortified deceptively and harassed in a vicious political challenge in their struggle to fetch social and economic changes in the country. Further, thousands of youths are inactivated, criminalized and lost their lives and this makes youths hopeless anger in their lives and pushes them further to be exposed for addictions, prostitution, violence, and illegitimate migrations. This youth challenge wasn’t only destined for African countries; rather, indeed, it was a global burden and headed as a global agenda. As a resolution, the construction of a healthy education system can create independent youths who acquire success and accelerate development. Developing countries should ensue development in the cultivation of empowerment tools through long and short-term education, implementing policy in action, diminishing wide-ranging gaps of (religion, ethnicity & region), and take high youth population as an opportunity and empower them. Further managing and empowering youths to be involved in decision-making, giving political weight and building a network of organizations to easily access job opportunities are important suggestions to save youths in work, for both increasing their income and the country's food security balance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=development" title="development">development</a>, <a href="https://publications.waset.org/abstracts/search?q=Ethiopia" title=" Ethiopia"> Ethiopia</a>, <a href="https://publications.waset.org/abstracts/search?q=management" title=" management"> management</a>, <a href="https://publications.waset.org/abstracts/search?q=unemployment" title=" unemployment"> unemployment</a>, <a href="https://publications.waset.org/abstracts/search?q=youth%20empowerment" title=" youth empowerment"> youth empowerment</a> </p> <a href="https://publications.waset.org/abstracts/181877/campaigns-of-youth-empowerment-and-unemployment-in-development-discourses-in-the-case-of-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181877.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">59</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9</span> Campaigns of Youth Empowerment and Unemployment in Development Discourses: Case of Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Belay%20Mulat%20Fentie">Belay Mulat Fentie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In today’s high decrement figure of the global economy, nations are facing many economic, social, and political challenges; universally, there is high distress of food and other survival insecurity. Further, as a result of conflict, natural disaster, and leadership influences, youths are existentially less empowered and unemployed, especially in developing countries. With this situation to handle well challenges, it’s important to search, investigate and deliberate about youth, unemployment, empowerment, and possible management fashions, as youths has a potential to carry and fight such battles. The method adopted is qualitative analysis of secondary data sources in youth empowerment, unemployment, and development as inclusive framework. Youth unemployment is a major development headache for most African countries. In Ethiopia, following weak youth empowerment, youth unemployment has been increased time to time; and quality education and organizations linkage matters as an important constraint. As a management challenge, although accessibility of quality education for Ethiopian youths is an important constraint; the country youths fortified deceptively and harassed in a vicious political challenge in their struggle to fetch social and economic changes in the country. Further, thousands of youths inactivated, criminalized, and lost their lives, and this makes youths to be hopeless, anger in their lives and pushes further to expose for addictions, prostitution, violence, and illegitimate migrations. This youth challenge didn’t only destinate in African countries, rather, indeed, the global burden and headed as a global agenda. As a resolution, the construction of a healthy education system can create independent youths that acquire success and accelerate development. Developing countries should ensue development in cultivation of empowerment tool through long and short-term education, implementing policy in action, diminishing wide ranged gaps of (religion, ethnicity & region), and take the high youth population as an opportunity and empower them. And further manage and empower youths to involve in decision making, in giving political weight and build a network on organizations to easily access jobs opportunities are important suggestion to alive youths in work, for both increasing their income and country food security balance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=development" title="development">development</a>, <a href="https://publications.waset.org/abstracts/search?q=Ethiopia" title=" Ethiopia"> Ethiopia</a>, <a href="https://publications.waset.org/abstracts/search?q=management" title=" management"> management</a>, <a href="https://publications.waset.org/abstracts/search?q=unemployment" title=" unemployment"> unemployment</a>, <a href="https://publications.waset.org/abstracts/search?q=youth%20empowerment" title=" youth empowerment"> youth empowerment</a> </p> <a href="https://publications.waset.org/abstracts/161621/campaigns-of-youth-empowerment-and-unemployment-in-development-discourses-case-of-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161621.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">138</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8</span> Improving Fingerprinting-Based Localization System Using Generative AI</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getaneh%20Berie%20Tarekegn">Getaneh Berie Tarekegn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=location-aware%20services" title="location-aware services">location-aware services</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction%20technique" title=" feature extraction technique"> feature extraction technique</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20adversarial%20network" title=" generative adversarial network"> generative adversarial network</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/184493/improving-fingerprinting-based-localization-system-using-generative-ai" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184493.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">59</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7</span> Production and Application of Organic Waste Compost for Urban Agriculture in Emerging Cities</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alemayehu%20Agizew%20Woldeamanuel">Alemayehu Agizew Woldeamanuel</a>, <a href="https://publications.waset.org/abstracts/search?q=Mekonnen%20Maschal%20Tarekegn"> Mekonnen Maschal Tarekegn</a>, <a href="https://publications.waset.org/abstracts/search?q=Raj%20Mohan%20Balakrishina"> Raj Mohan Balakrishina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Composting is one of the conventional techniques adopted for organic waste management, but the practice is very limited in emerging cities despite the most of the waste generated is organic. This paper aims to examine the viability of composting for organic waste management in the emerging city of Addis Ababa, Ethiopia, by addressing the composting practice, quality of compost, and application of compost in urban agriculture. The study collects data using compost laboratory testing and urban farm households’ survey and uses descriptive analysis on the state of compost production and application, physicochemical analysis of the compost samples, and regression analysis on the urban farmer’s willingness to pay for compost. The findings of the study indicated that there is composting practice at a small scale, most of the producers use unsorted feedstock materials, aerobic composting is dominantly used, and the maturation period ranged from four to ten weeks. The carbon content of the compost ranges from 30.8 to 277.1 due to the type of feedstock applied, and this surpasses the ideal proportions for C:N ratio. The total nitrogen, pH, organic matter, and moisture content are relatively optimal. The levels of heavy metals measured for Mn, Cu, Pb, Cd and Cr⁶⁺ in the compost samples are also insignificant. In the urban agriculture sector, chemical fertilizer is the dominant type of soil input in crop productions but vegetable producers use a combination of both fertilizer and other organic inputs, including compost. The willingness to pay for compost depends on income, household size, gender, type of soil inputs, monitoring soil fertility, the main product of the farm, farming method and farm ownership. Finally, this study recommends the need for collaboration among stakeholders’ along the value chain of waste, awareness creation on the benefits of composting and addressing challenges faced by both compost producers and users. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=composting" title="composting">composting</a>, <a href="https://publications.waset.org/abstracts/search?q=emerging%20city" title=" emerging city"> emerging city</a>, <a href="https://publications.waset.org/abstracts/search?q=organic%20waste%20management" title=" organic waste management"> organic waste management</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20agriculture" title=" urban agriculture"> urban agriculture</a> </p> <a href="https://publications.waset.org/abstracts/136992/production-and-application-of-organic-waste-compost-for-urban-agriculture-in-emerging-cities" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/136992.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">308</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6</span> Improving Fingerprinting-Based Localization System Using Generative Artificial Intelligence</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getaneh%20Berie%20Tarekegn">Getaneh Berie Tarekegn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=location-aware%20services" title="location-aware services">location-aware services</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction%20technique" title=" feature extraction technique"> feature extraction technique</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20adversarial%20network" title=" generative adversarial network"> generative adversarial network</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/174097/improving-fingerprinting-based-localization-system-using-generative-artificial-intelligence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174097.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">71</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5</span> GAILoc: Improving Fingerprinting-Based Localization System Using Generative Artificial Intelligence</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getaneh%20Berie%20Tarekegn">Getaneh Berie Tarekegn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=location-aware%20services" title="location-aware services">location-aware services</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction%20technique" title=" feature extraction technique"> feature extraction technique</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20adversarial%20network" title=" generative adversarial network"> generative adversarial network</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/174095/gailoc-improving-fingerprinting-based-localization-system-using-generative-artificial-intelligence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174095.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">75</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Effect of Supplementation of Hay with Noug Seed Cake (Guizotia abyssinica), Wheat Bran and Their Mixtures on Feed Utilization, Digestiblity and Live Weight Change in Farta Sheep</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fentie%20Bishaw%20Wagayie">Fentie Bishaw Wagayie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study was carried out with the objective of studying the response of Farta sheep in feed intake and live weight change when fed on hay supplemented with noug seed cake (NSC), wheat bran (WB), and their mixtures. The digestibility trial of 7 days and 90 days of feeding trial was conducted using 25 intact male Farta sheep with a mean initial live weight of 16.83 ± 0.169 kg. The experimental animals were arranged randomly into five blocks based on the initial live weight, and the five treatments were assigned randomly to each animal in a block. Five dietary treatments used in the experiment comprised of grass hay fed ad libitum (T1), grass hay ad libitum + 300 g DM WB (T2), grass hay ad libitum + 300 g DM (67% WB: 33% NSC mixture) (T3), grass hay ad libitum + 300 g DM (67% NSC: 33% WB) (T4) and 300 g DM/ head/day NSC (T5). Common salt and water were offered ad libitum. The supplements were offered twice daily at 0800 and 1600 hours. The experimental sheep were kept in individual pens. Supplementation of NSC, WB, and their mixtures significantly increased (p < 0.01) the total dry matter (DM) (665.84-788 g/head/day) and (p < 0.001) crude protein (CP) intake. Unsupplemented sheep consumed significantly higher (p < 0.01) grass hay DM (540.5g/head/day) as compared to the supplemented treatments (365.8-488 g/h/d), except T2. Among supplemented sheep, T5 had significantly higher (p < 0.001) CP intake (99.98 g/head/day) than the others (85.52-90.2 g/head/day). Supplementation significantly improved (p < 0.001) the digestibility of CP (66.61-78.9%), but there was no significant effect (p > 0.05) on DM, OM, NDF, and ADF digestibility between supplemented and control treatments. Very low CP digestibility (11.55%) observed in the basal diet (grass hay) used in this study indicated that feeding sole grass hay could not provide nutrients even for the maintenance requirement of growing sheep. Significant final and daily live weight gain (p < 0.001) in the range of 70.11-82.44 g/head/day was observed in supplemented Farta sheep, but unsupplemented sheep lost weight by 9.11g/head/day. Numerically, among the supplemented treatments, sheep supplemented with a higher proportion of NSC in T4 (201 NSC + 99 g WB) gained more weight than the rest, though not statistically significant (p > 0.05). The absence of statistical difference in daily body weight gain between all supplemented sheep indicated that the supplementation of NSC, WB, and their mixtures had similar potential to provide nutrients. Generally, supplementation of NSC, WB, and their mixtures to the basal grass hay diet improved feed conversion ratio, total DM intake, CP intake, and CP digestibility, and it also improved the growth performance with a similar trend for all supplemented Farta sheep over the control group. Therefore, from a biological point of view, to attain the required level of slaughter body weight within a short period of the growing program, sheep producer can use all the supplement types depending upon their local availability, but in the order of priority, T4, T5, T3, and T2, respectively. However, based on partial budget analysis, supplementation of 300 g DM/head /day NSC (T5) could be recommended as profitable for producers with no capital limitation, whereas T4 supplementation (201 g NSC + 99 WB DM/day) is recommended when there is capital scarcity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=weight%20gain" title="weight gain">weight gain</a>, <a href="https://publications.waset.org/abstracts/search?q=supplement" title=" supplement"> supplement</a>, <a href="https://publications.waset.org/abstracts/search?q=Farta%20sheep" title=" Farta sheep"> Farta sheep</a>, <a href="https://publications.waset.org/abstracts/search?q=hay%20as%20basal%20diet" title=" hay as basal diet"> hay as basal diet</a> </p> <a href="https://publications.waset.org/abstracts/180209/effect-of-supplementation-of-hay-with-noug-seed-cake-guizotia-abyssinica-wheat-bran-and-their-mixtures-on-feed-utilization-digestiblity-and-live-weight-change-in-farta-sheep" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/180209.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">63</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Standardization of the Roots of Gnidia stenophylla Gilg: A Potential Medicinal Plant of South Eastern Ethiopia Traditionally Used as an Antimalarial</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mebruka%20Mohammed">Mebruka Mohammed</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Bisrat"> Daniel Bisrat</a>, <a href="https://publications.waset.org/abstracts/search?q=Asfaw%20Debella"> Asfaw Debella</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarekegn%20Birhanu"> Tarekegn Birhanu </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Lack of quality control standards for medicinal plants and their preparations is considered major barrier to their integration in to effective primary health care in Ethiopia. Poor quality herbal preparations led to countless adverse reactions extending to death. Denial of penetration for the Ethiopian medicinal plants in to the world’s booming herbal market is also another significant loss resulting from absence of herbal quality control system. Thus, in the present study, Gnidia stenophylla Gilg (popular antimalarial plant of south eastern Ethiopia), is standardized and a full monograph is produced that can serve as a guideline in quality control of the crude drug. Morphologically, the roots are found to be cylindrical and tapering towards the end. It has a hard, corky and friable touch with saddle brown color externally and it is relatively smooth and pale brown internally. It has got characteristic pungent odor and very bitter taste. Microscopically it has showed lignified xylem vessels, wider medullary rays with some calcium oxalate crystals, reddish brown secondary metabolite contents and slender shaped long fibres. Physicochemical standards quantified and resulted: foreign matter (5.25%), moisture content (6.69%), total ash (40.80%), acid insoluble ash (8.00%), water soluble ash (2.30%), alcohol soluble extractive (15.27%), water soluble extractive (10.98%), foaming index (100.01 ml/g), swelling index (7.60 ml/g). Phytochemically: Phenols, flavonoids, steroids, tannins and saponins were detected in the root extract; TLC and HPLC fingerprints were produced and an analytical marker was also tentatively characterized as 3-(3,4-dihydro-3,5-dihydroxy-2-(4-hydroxy-5-methylhex-1-en-2-yl)-7-methoxy-4-oxo-2H-chromen-8-yl)-5-hydroxy-2-(4-hydroxyphenyl)-7-methoxy-4H-chromen-4-one. Residue wise pesticides (i.e. DDT, DDE, g-BHC) and radiochemical levels fall below the WHO limit while Heavy metals (i.e. Co, Ni, Cr, Pb, and Cu), total aerobic count and fungal load lie way above the WHO limit. In conclusion, the result can be taken as signal that employing non standardized medicinal plants could cause many health risks of the Ethiopian people and Africans’ at large (as 80% of inhabitants in the continent depends on it for primary health care). Therefore, following a more universal approach to herbal quality by adopting the WHO guidelines and developing monographs using the various quality parameters is inevitable to minimize quality breach and promote effective herbal drug usage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gnidia%20stenophylla%20Gilg" title="Gnidia stenophylla Gilg">Gnidia stenophylla Gilg</a>, <a href="https://publications.waset.org/abstracts/search?q=standardization%2Fmonograph" title=" standardization/monograph"> standardization/monograph</a>, <a href="https://publications.waset.org/abstracts/search?q=pharmacognostic" title=" pharmacognostic"> pharmacognostic</a>, <a href="https://publications.waset.org/abstracts/search?q=residue%2Fimpurity" title=" residue/impurity"> residue/impurity</a>, <a href="https://publications.waset.org/abstracts/search?q=quality" title=" quality"> quality</a> </p> <a href="https://publications.waset.org/abstracts/7458/standardization-of-the-roots-of-gnidia-stenophylla-gilg-a-potential-medicinal-plant-of-south-eastern-ethiopia-traditionally-used-as-an-antimalarial" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7458.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">289</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Improving Fingerprinting-Based Localization System Using Generative AI</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getaneh%20Berie%20Tarekegn">Getaneh Berie Tarekegn</a>, <a href="https://publications.waset.org/abstracts/search?q=Li-Chia%20Tai"> Li-Chia Tai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=location-aware%20services" title="location-aware services">location-aware services</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction%20technique" title=" feature extraction technique"> feature extraction technique</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20adversarial%20network" title=" generative adversarial network"> generative adversarial network</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/185954/improving-fingerprinting-based-localization-system-using-generative-ai" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185954.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">42</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Improving Fingerprinting-Based Localization (FPL) System Using Generative Artificial Intelligence (GAI)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Getaneh%20Berie%20Tarekegn">Getaneh Berie Tarekegn</a>, <a href="https://publications.waset.org/abstracts/search?q=Li-Chia%20Tai"> Li-Chia Tai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=location-aware%20services" title="location-aware services">location-aware services</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction%20technique" title=" feature extraction technique"> feature extraction technique</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20adversarial%20network" title=" generative adversarial network"> generative adversarial network</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20short-term%20memory" title=" long short-term memory"> long short-term memory</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a> </p> <a 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