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A Methodology for Evaluating Sustainable Building Technology to Raise the Efficiency of Urban Clusters: Analytical Study
Get PDFSustainability evaluation methodologies are distinguished from other evaluation tools, such as the LEED system and the BREEAM system, in that they include a new local evaluation methodology. The life cycle of a building is divided into distinct phases, including production of materials and components, construction and implementation, use/operation, maintenance, demolition, and disposal. Understanding the classification of assessment tools based on the building to be assessed, tool users, and building life cycle stages will inform selection of appropriate assessment tools and development of a comprehensive methodology. The study aimed to extract and evaluate opinions and perspectives from users, stakeholders, and researchers about the current status of sustainable technology in urban communities and to analyze the basic factors and indicators that contributed to the efficiency of urban communities and their relationship to sustainable technology. An inductive and analytical research was conducted using a questionnaire form on a sample of 100 participants to collect the opinions of users, relevant authorities, and researchers in the field. The questionnaire was designed to collect opinions and perspectives from different groups, including residents, local authorities (such as provincial officials, engineering administration, etc.), and experts in the field of sustainable technology. It covered a range of topics related to sustainable technology, including perceptions of current sustainability practices, barriers to implementation, potential areas for improvement, and proposals to enhance the efficiency of urban clusters. The research provided a comprehensive understanding of views on sustainable technology and help identify key areas for evaluation and improvement
“Novel Diiodobenzaldehyde Derivatives of 4-Aminopyrrolo[2,3-d] pyrimidine: Synthesis, Characterization, and Biological Activity.”
Get PDFThe main objectives of this study were to create new pyrrolopyrimidine compounds, analyze their properties, and assess their effectiveness against both fungi and bacteria. Specifically, the focus was on synthesizing diiodobenzaldehyde derivatives of pyrrolopyrimidine. Various spectroscopic methods were employed to characterize the chemically synthesized substances. These compounds were then tested for their ability to inhibit the growth of four bacterial strains (S. aureus, B. subtilis, E. coli, P. aeruginosa) and two fungal strains (C. albicans, S. cerevisiae). Each synthesized compound exhibited distinct peaks in FT(IR), 1H, and 13C NMR, as well as UV spectral studies. In vitro testing revealed that compound 2a displayed significantly higher antibacterial and antifungal activity compared to streptomycin and fluconazole, the gold standards
HerbaVisionNet: Optimized CNN And Resnet50v2 Model For Enhanced Medicinal Plant Identification And Application Design
Get PDFAddressing the escalating demand for medicinal plants, this study undertakes the critical task of establishing an efficient identification system. Employing Convolutional Neural Networks (CNNs) with ResNet50v2 architecture, the project endeavours to develop a robust model capable of classifying 30 distinct medicinal plant types from high-resolution images. This classification relies on the precision of feature extraction to ensure accurate identification. Notably, the dataset used is meticulously curated to ensure its adaptability to the diverse botanical characteristics inherent in medicinal plants. Central to achieving high accuracy is the ResNet50v2 model, which forms the cornerstone of the project. Integrated into a real-time web application implemented with Flask, this model facilitates swift and accessible plant identification for various users, including researchers, herbalists, and enthusiasts. The study underscores the efficacy of deep learning algorithms in medicinal plant identification, showcasing remarkable accuracy and reliability in classification tasks. Beyond mere identification, the model demonstrates an ability to precisely categorize plant species, thereby bridging the gap between identification and exploration. This precision is underscored by an exceptional 99% accuracy rate in distinguishing between 30 medicinal plant species, attributed to meticulous model training with a diverse, high-resolution dataset capturing intricate plant features. Continual efforts are directed towards expanding the dataset to encompass variations in real-world scenarios. Strategies to address class imbalance through oversampling techniques and class weight adjustments are being rigorously pursued. Additionally, the model undergoes refinement through fine-tuning its architecture and integrating advanced data augmentation techniques. The research significantly contributes to the broader field of AI applications in sustainable practices, particularly in the conservation of medicinal plant resources. Serving as a potent tool for accurate identification, it holds promising implications for future advancements in deep learning and botanical research
Self-Tuned Controller for Achieving Enhanced Voltage Stability in a Multi-Machine System
Get PDFThe paper will provide proof of the efficacy of remote sensors in agriculture as a process control approach using an online laboratory. Data of environmental parameter, such as temperature, humidity, soil moisture and light intensity, were gathered from sensor node system which had been installed in open land of agricultural field. Four machine learning models including ours have been put into going forward and back to the future of agriculture. These are the Simple Linear Regression, Decision Tree, k-Nearest Neighbors, and Support Vector Machine that have been established and examined for their efficacy in predicting and managing agriculture processes using this data you provided. The findings indicated that the Decision Tree method qualified for the best 92% of the accuracy index, while Support Vector Machine produced the accuracy of 90% in their outcome. Neural Network algorithm showed an 88% accuracy, while Simple Linear Regression algorithm trailed with 85% accuracy The result signifies the fact that computer learning software, such as tree of decisions and support schemes can highly be used in improvement of agriculture systems through real-time control and responses. The combining of online remote experiments serves to create a scalable and affordable platform on which agricultural scientists and specialists can work together and make progress in agricultural technology which supports the advancement of more efficient and sustainable food production systems
An Improved Approach for Quality of Service in Vehicular Ad Hoc Network (VANET) Using Secure-AODV (SAODV) Protocol
Get PDFVehicular Ad-hoc NETworks (VANETs) is a modern technology which help a vehicle and a driver in several ways. The main characteristics of VANETs are nodes i.e. vehicles with relatively high mobility and constantly changing topology. In case of data communication in VANETs, a source node must depend on the intermediate nodes to send its data packets to the destination node on multi-hop routes. VANETs can give better performance if all its nodes work properly with full cooperation during the communication. In VANETs, a node can generate and broadcast important and essential messages to other nodes in the network for safety reason. However, the generated message by a vehicle may not be reliable every time. In this situation, we have proposed a trusted and secured routing technique that evaluates the trust of a vehicle and also checks the message reliability. The proposed protocol is named as Secure Ad-hoc On Demand Distance Vector (SAODV) routing protocol which is the modification of Ad-hoc On-demand Distance Vector routing protocol. Since VANETs are mostly attacked by the malicious nodes; therefore better security solution is needed to stop such attacks. The proposed work introduces a trust model to establish a malicious node free route for source node to send its data packets to the destination node on multi-hop routes. In VANETs, a malicious node can broadcast false messages and can divert other vehicles in wrong direction. Therefore, to stop such activities an effective trust management scheme is required for VANETs. The proposed work, addressed the above mentioned problem of selection of reliable or trusty vehicles i.e. to establish a malicious node free route by proposing a trust based model for VANETs. The proposed approach evaluated the reliability and trustworthiness of the message or the vehicle based on the trust metrics of that message or the vehicle
An Analysis Based on Amazon S3 That Makes Use of Real-World Service Simulation Techniques Is Presented in This Study, Which Aims to Investigate the Latency Performance of Distributed Storage Systems
No full textThe generation of parity nodes is strongly dependent on data nodes in the erasure codes that are currently in use. The higher the tolerance for mistake, and the more people are willing to It is possible that our chances of successfully recovering the original data will improve if we are able to increase the number of parity nodes as well. The storage overhead will increase as the number of parity nodes increases, and the repair load on data nodes will also increase. This is due to the fact that data nodes are queried often in order to assist in the repair of parity nodes at the same time. In the event that a global parity node fails in LRC [25, 26], for example, it is necessary to solve all of the data nodes. As a consequence of the "increasing demands on the network's data nodes," the amount of time required to process read requests for data nodes would increase more than before. Google search is an example of an application that should not be used for retrieving data on a regular basis. "Produces both data and parity nodes, it is possible for the latter to take over some of the repair work that is normally done by the former. This is done in an effort to reduce the amount of time that is spent waiting." To put it another way, the number of data nodes that may be accessed does not change under any circumstances, regardless of whether or not a parity node is operational. When it comes to storage costs, it would seem that parity nodes suffer extra expenses. If the design is correct, generating parity nodes by employing parity nodes may help reduce access latency without increasing or lowering the storage needs. This is something that we will demonstrate in the coming sections, which are over your head
Overview Of Channel Coding Schemes and Its Comparative Analysis For 5G Wireless Networks
No full textNowadays 5G wireless communication is a fast-growing technology. The data transmitted by the 5G wireless communication channel is exposed to error due to the unpredictable noise, interference, fading, device limitations, and other factors. Channel coding is used to fix those problems produced during data transmission and reception in 5G wireless communication networks this means channel coding is a vital unit of 5G wireless communication networks. One best solution for 5G communication is to use polar coding which achieves the capacity of binary memoryless symmetric channels with the best errorcorrecting performance. Successive cancellation (SC), successive cancellation list (SCL), and their modification are the most known polar decoding algorithms used for 5G. This article presents an overview on latest research on polar decoding algorithms and the performance comparison on appropriate polar coding techniques. The performance affecting parameters have been identified based on the analysis. The performance evaluation is done for different values of bit energy to noise spectral ratio (Eb/No), code rate, and list size to compare the performance of polar code with SC decoding, interleaving polar code with SC decoding (I-SC), cyclic redundancy check aided polar code with SCL decoding (CRC-A-SCL), interleaved cyclic redundancy check aided polar code with SCL decoding (I-CRC-A-SCL), cyclic redundancy check aided interleaved polar code with SCL decoding (CRC-A-I-SCL) and interleaved cyclic redundancy check aided interleaved polar code with SCL decoding (I-CRC-A-I-SCL) under BPSK modulation and AWGN channel model. The most performance-affecting parameters are code rate, CRC length, and list size when comparison on polar coding techniques have been done based performance measure of BER and FER. It is found based on results and analysis that the CRC-A-SCL polar coding scheme has a BER value of 0.94%, the I-CRC-A-SCL polar coding scheme has 0.45%, the CRC-A-I-SCL polar coding scheme has 0.14%, and the I-CRC-A-I-SCL polar coding scheme has 0.03% at Eb/No of 2.4dB, list size 8 and CRC length 16 over AWGN channel and BPSK modulation. The I-CRC-A-I-SCL polar coding scheme has proven to be a promising candidate for 5G wireless communication networks.
 
Assessment of Electromechanical Performance of Graphene-Reinforced Aluminum Nanocomposites for Energy Storage Solutions
No full textGraphene insertion into aluminium matrix composites (AMCs) has demonstrated a great deal of promise for improving the electromechanical characteristics that are essential for energy storage applications. This work explores the electromechanical properties of aluminium nanocomposites reinforced with graphene, with a particular emphasis on the materials' conductivity, capacity for storing charge, and general appropriateness for applications in super capacitors and advanced batteries. Aluminium can be reinforced with graphene because of its superior mechanical strength, large surface area, and outstanding electrical conductivity. A range of fabrication techniques, including chemical reduction procedures and powder metallurgy, were utilized to attain the best possible dispersion of graphene in the aluminium matrix. Optimising the interfacial connection between graphene and aluminium resulted in improved electromechanical performance and efficient load transmission.The results of this study highlight the potential contribution of aluminium nanocomposites reinforced with graphene to the advancement of energy storage technologies. Future research will concentrate on understanding the fundamental principles that control these materials' electromechanical behaviour and investigating the materials' long-term stability and scalability for commercial uses
In Vitro Photo-Catalytic Degradation of Chloramphenicol Using Pharmaceutical Wastewater
No full textAbstract: In this work, the performance of composite membranes for the treatment of Chloramphenicol (CAP) pollutants was investigated from pharmaceutical industrial wastewater. The composite membrane was under operated with different concentrations of CAP with Titanium dioxide (TiO2) in 10mg/L, 20mg/L and 30 mg/L. The composite membranes were cross-linked with glutaraldehyde for the elimination of H2SO4. Characterizations of synthesized composite membranes were carried out to analyze functionality, morphology, and hydrophilic behaviours. In continuous operation, the different time intervals of TiO2 were removed in centrifuging. The performance of the composite membrane is the removal of pollutant CAP by UV analysis, and kinetics model at different concentrations. The degree of swelling and contact angle were measured in different concentrations of CAP at TiO2. Liquid Chromatography (LC) is used to CAP with Titanium dioxide mixtures. Mass Spectrometry (MS) can be used for structural identity with high specificity. The MS is also used to analyze CAP from pharmaceutical industrial wastewater. The membranes were subjected to filtration of pharmaceutical wastewater which gave a maximum rejection of 95% of Chloramphenicol
A Theoretical Study on the Simultaneous Hydrogen Production and Consumption in Proton Exchange Membrane Fuel Cell/Battery Electric Vehicles
No full textAbstract: Hybrid electric vehicles are new technologies that will be used in future transportation networks in response to the need for sustainable development of environmentally friendly processes. Some of the energy sources used to develop these vehicles are batteries and proton exchange membrane (PEM) fuel cells (FCs), which cannot guarantee the energy required for life in the long term. Electricity storage systems (ESSs) such as the Ultra Batteries (UBs) are suitable candidates for solving the FC transient response issues. The combination of FCs and UBs in electric vehicles is called Fuel Cell Batteries Electric Vehicles (FCBEVs). In this work, an energy consumption model is adopted to simulate the performance of a FCBEV, by considering the power losses of various components, such as the FC, electric motor, the state of charge (SOC) of the battery, and breaks as well as by implementing a reinforcement-learning energy management strategy (EMS), pursuing this scope through the optimization of the hydrogen fuel consumption. In this regard, the motor prototype, after a transient period of around 2.5 min, was able to reach a number of runs equal to 2000, remaining stable for 10 min before coming down to zero.
Keywords: Fuel cell, Fuel cell battery electric vehicle modeling, Energy management, Hydrogen