Search results for: cloud storage

Authors: Ying Han, Weirong Chen, Qi Li

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An energy management method based on equivalent hydrogen consumption minimum strategy is proposed in this paper aiming at the direct-current (DC) microgrid consisting of photovoltaic cells, fuel cells, energy storage devices, converters and DC loads. The rational allocation of fuel cells and battery devices is achieved by adopting equivalent minimum hydrogen consumption strategy with the full use of power generated by photovoltaic cells. Considering the balance of the battery’s state of charge (SOC), the optimal power of the battery under different SOC conditions is obtained and the reference output power of the fuel cell is calculated. And then a droop control method based on time-varying droop coefficient is proposed to realize the automatic charge and discharge control of the battery, balance the system power and maintain the bus voltage. The proposed control strategy is verified by RT-LAB hardware-in-the-loop simulation platform. The simulation results show that the designed control algorithm can realize the rational allocation of DC micro-grid energy and improve the stability of system.

Keywords: DC microgrid, equivalent minimum hydrogen consumption strategy, energy management, time-varying droop coefficient, droop control

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Authors: Pratibha Srivastava, Chithra V. J., Sudhakar S., Nitin K. D.

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A closed-loop system comprises of a controller, a response system, and an actuating system. The controller, which is the system under test for us, excites the actuators based on feedback from the sensors in a periodic manner. The sensors should provide the feedback to the System Under Test (SUT) within a deterministic time post excitation of the actuators. Any delay or miss in the generation of response or acquisition of excitation pulses may lead to control loop controller computation errors, which can be catastrophic in certain cases. Such systems categorised as hard real-time systems that need special strategies. The real-time operating systems available in the market may be the best solutions for such kind of simulations, but they pose limitations like the availability of the X Windows system, graphical interfaces, other user tools. In this paper, we present strategies that can be used on a general purpose operating system (Bare Linux Kernel) to achieve a deterministic deadline and hence have the added advantages of a GPOS with real-time features. Techniques shall be discussed how to make the time-critical application run with the highest priority in an uninterrupted manner, reduced network latency for distributed architecture, real-time data acquisition, data storage, and retrieval, user interactions, etc.

Keywords: real time data acquisition, real time kernel preemption, scheduling, network latency

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Authors: Govind Kumar

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The concept of ‘e-governance’ that was brought about by the new wave of reforms, namely ‘LPG’ in the early 1990s, has been enabling governments across the globe to digitally transform themselves. Digital transformation is leading the governments with qualitative decisions, optimization in rational use of resources, facilitation of cost-benefit analyses, and elimination of redundancy and corruption with the help of ICT-based applications interface. ICT-based applications/technologies have enormous potential for impacting positive change in the social lives of the global citizenry. Supercomputers test and analyze millions of drug molecules for developing candidate vaccines to combat the global pandemic. Further, e-commerce portals help distribute and supply household items and medicines, while videoconferencing tools provide a visual interface between the clients and hosts. Besides, crop yields are being maximized with the help of drones and machine learning, whereas satellite data, artificial intelligence, and cloud computing help governments with the detection of illegal mining, tackling deforestation, and managing freshwater resources. Such e-applications have the potential to take governance an extra mile by achieving 5 Es (effective, efficient, easy, empower, and equity) of e-governance and six Rs (reduce, reuse, recycle, recover, redesign and remanufacture) of sustainable development. If such digital transformation gains traction within the government framework, it will replace the traditional administration with the digitalization of public administration. On the other hand, it has brought in a new set of challenges, like the digital divide, e-illiteracy, technological divide, etc., and problems like handling e-waste, technological obsolescence, cyber terrorism, e-fraud, hacking, phishing, etc. before the governments. Therefore, it would be essential to bring in a rightful mixture of technological and humanistic interventions for addressing the above issues. This is on account of the reason that technology lacks an emotional quotient, and the administration does not work like technology. Both are self-effacing unless a blend of technology and a humane face are brought in into the administration. The paper will empirically analyze the significance of the technological framework of digital transformation within the government set up for the digitalization of public administration on the basis of the synthesis of two case studies undertaken from two diverse fields of administration and present a future framework of the study.

Keywords: digital transformation, electronic governance, public administration, knowledge framework

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Authors: Hanieh Sadat Jannesari, Hoori Jannesar, Alireza Hajian HosseinAbadi

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In general, buildings are responsible for a considerable share of consumed energy and carbon emissions worldwide and play a significant role in formulating sustainable development strategies. Therefore, a lot of effort is put into the design and construction of zero-energy buildings (ZEBs) to help eliminate the problems associated with the reduction of energy resources and environmental degradation. Two strategies are significant in designing ZEBs: minimizing the need for energy utilization in buildings (particularly for cooling and heating) through highly energy-efficient designs and using renewable energies and other technologies to meet the remaining energy needs. This paper reviews the works related to these two strategies concerning sustainable energy-saving solutions using renewable energy technologies and the Internet of Things in ZEBs. Drawing on the theories and recently implemented projects of energy engineers in ZEBs, we have reported the required technologies within the framework of this paper’s objectives. Overall, solutions based on renewable and sustainable technologies such as photovoltaic (PV) modules, thermal collectors, Phase Change Material (PCM) techniques, etc., are used in active and passive systems designed for various applications in such buildings as cooling, heating, lighting, cooking, etc. The results obtained from examining these projects show that it is possible to minimize the amount of energy required to be produced for and consumed by these buildings.

Keywords: active and passive renewable energy systems, internet of things, storage, zero energy buildings

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Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: S. Benessam, T. H. Debieche, A. Drouiche, S. Mahdid, F. Zahi

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The marsh is the impermeable depression. It is not very deep and presents the stagnant water. Their water level varies according to the contributions of water (rain, groundwater, stream etc.), when this last reaches the maximum level of the marsh, it flows towards the downstream through the discharge system. The marsh accumulates all the liquid and solid contributions of upstream part. In the North-East Algerian, the Redjla marsh is located on the course of the Tassift river. Its contributions of water come from the upstream part of the river, often characterized by the presence of several pollutants in water related to the urban effluents, and its discharge system supply the downstream part of the river. In order to determine the effect of the marsh on the water quality of the river this study was conducted. A two-monthly monitoring of the physicochemical parameters and water chemistry of the river were carried out, before and after the marsh, during the period from November 2013 to January 2015. The results show that the marsh plays the role of a natural purifier of water of Tassift river, present by drops of conductivity and concentration of the pollutants (ammonium, phosphate, iron, chlorides and bicarbonates) between the upstream part and downstream of the marsh. That indicates that these pollutants are transformed with other chemical forms (case of ammonium towards nitrate), precipitated in complex forms or/and adsorbed by the sediments of the marsh. This storage of the pollutants in the ground of the marsh will be later on a source of pollution for the plants and river water.

Keywords: marsh, natural purification, urban pollution, nitrogen

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Authors: L. E. Mphahama, A. Mushunje, A. Taruvinga

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Although broiler production does not generate any large incomes among the smallholder community, it represents the main source of livelihood and part of nutritional requirement. As a result, market for broiler meat is growing faster than that of any other meat products and is projected to continue growing in the coming decades. However, the implication is that a multitude of factors manipulates transformation of smallholder broiler farmers participating in the mainstream markets. From 217 smallholder broiler farmers, socio-economic and institutional factors in broiler farming were incorporated into Binary model to estimate the probability of broiler farmers’ participation in the mainstream markets within the Maseru district in Lesotho. Of the thirteen (13) predictor variables fitted into the model, six (6) variables (household size, number of years in broiler business, stock size, access to transport, access to extension services and access to market information) had significant coefficients while seven (7) variables (level of education, marital status, price of broilers, poultry association, access to contract, access to credit and access to storage) did not have a significant impact. It is recommended that smallholder broiler farmers organize themselves into cooperatives which will act as a vehicle through which they can access contracts and formal markets. These cooperatives will also enable easy training and workshops for broiler rearing and marketing/markets through extension visits.

Keywords: broiler chicken, mainstream market, Maseru district, participation, smallholder farmers

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Authors: Siti N. M. Rozali, A. H. J. Paterson, J. P. Hindmarsh

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Spray drying of fruit juices from liquid to powder is desirable as the powders are easier to handle, especially for storage and transportation. In this project, pomace fibres will be used as a drying aid during spray drying, replacing the commonly used maltodextrins. The main attraction of this drying aid is that the pomace fibres are originally derived from the fruit itself. However, the addition of micro-sized fibres to fruit juices is expected to affect the rheology and subsequent atomization behaviour during the spray drying process. This study focuses on the determination and characterization of the rheology of juice-fibre suspensions specifically inside a spray dryer nozzle. Results show that the juice-fibre suspensions exhibit shear thinning behaviour with a significant extensional viscosity. The shear and extensional viscosities depend on several factors which include fibre fraction, shape, size and aspect ratio. A commercial capillary rheometer is used to characterize the shear behaviour while a portable extensional rheometer has been designed and built to study the extensional behaviour. Methods and equipment will be presented along with the rheology results. Rheology or behaviour of the juice-fibre suspensions provides an insight into the limitations that will be faced during atomization, and in the future, this finding will assist in choosing the best nozzle design that can overcome the limitations introduced by the fibre particles thus resulting in successful spray drying of juice-fibre suspensions.

Keywords: extensional rheology, fibre suspensions, portable extensional rheometer, shear rheology

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Authors: Bo Jin

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A variety of process equipment having flow in and out is widely used in industrial land-based cryogenic facilities. In some of this equipment, such as vapor-liquid separator, a liquid level is established during the steady operation. As the implementation of such industrial processes extends to off-shore floating facilities, it is important to investigate the effect of sea motion on the process equipment partially filled with liquid. One important aspect to consider is the occurrence of sloshing therein. The flow characteristics are different from the classical study of sloshing, where the fluid is enclosed inside a vessel (e.g., storage tank) with no flow in or out. Liquid inside process equipment continuously flows in and out of the system. To understand this key difference, a Computational Fluid Dynamics (CFD) model is developed to simulate the liquid motion inside a partially filled cylinder with and without continuous flow in and out. For a partially filled vertical cylinder without any continuous flow in and out, the CFD model is found to be able to capture the well-known sloshing behavior documented in the literature. For the cylinder with a continuous steady flow in and out, the CFD simulation results demonstrate that the continuous flow suppresses sloshing. Given typical cryogenic fluid has very low viscosity, an analysis based on potential flow theory is developed to explain why flow into and out of the cylinder changes the natural frequency of the system and thereby suppresses sloshing. This analysis further validates the CFD results.

Keywords: computational fluid dynamics, CFD, cryogenic process equipment, off-shore floating processes, sloshing

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Authors: Abdelkader Anouzla, Soukaina Bouaouda, Roukaya Bouyakhsass, Salah Souabi, Abdeslam Taleb

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During storage and under the combined action of rainwater and natural fermentation, these wastes produce over 800.000 m3 of landfill leachates. Due to population growth and changing global economic activities, the amount of waste constantly generated increases, making more significant volumes of leachate. Leachate, when leaching into the soil, can negatively impact soil, surface water, groundwater, and the overall environment and human life. The leachate must first be treated because of its high pollutant load before being released into the environment. This article reviews the different leachate treatments in September 2022 techniques. Different techniques can be used for this purpose, such as biological, physical-chemical, and membrane methods. Young leachate is biodegradable; in contrast, these biological processes lose their effectiveness with leachate aging. They are characterized by high ammonia nitrogen concentrations that inhibit their activity. Most physical-chemical treatments serve as pre-treatment or post-treatment to complement conventional treatment processes or remove specific contaminants. After the introduction, the different types of pollutants present in leachates and their impacts have been made, followed by a discussion highlighting the advantages and disadvantages of the various treatments, whether biological, physicochemical, or membrane. From this work, due to their simplicity and reasonable cost compared to other treatment procedures, biological treatments offer the most suitable alternative to limit the effects produced by the pollutants in landfill leachates.

Keywords: landfill leachate, landfill pollution, impact, wastewater

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Authors: A. Parra Parra, M. Vlasova, P. A. Marquez, M. Kakazey, M. C. Resendiz Gonzalez

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The work of water treatment plants from various sources of pollution includes a biological treatment stage using activated sludge. Due to the large volume of toxic activated sludge waste (WAS) generated and soil contamination during its storage, WAS disposal technologies are being continuously developed. The most common is the carbonization of WAS. The carbonization products are various forms of ordered and disordered carbon material having different reactivity. The aim of this work was to study the reduction process of Fe₂O₃ mixed with activated sludge waste (WAS). It could be assumed that the simultaneous action of the WAS thermal decomposition process, accompanied by the formation of reactive nano-carbon, with carbothermal reduction of the Fe₂O₃, will permit intensify reduction of metal oxide up to stage of metal and iron carbide formation. The studies showed that the temperature treatment in the region of (800-1000) °C for 1 hour under conditions of oxygen deficiency is accompanied by the occurrence of reactions: Fe₂O₃ → Fe₃O₄ → FeO → Fe, which are typical for the metallurgical process of iron smelting, but less energy-intensive. Depending on the ratio of the WAS - Fe₂O₃ components and the temperature-time regime of reduction of iron oxide, it is possible to distinguish the stages of the predominant formation of ferromagnetic compounds, cast iron, and iron carbide. The results indicated the promise of using WAS as a metals oxide reducing agent and obtaining of ceramic-based on metal carbides.

Keywords: carbothermal reduction, Fe₂O₃, FeₓOᵧ-C, waste activated sludge

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Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

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Authors: Josif Figueroa, Kush Bubbar, Greg Young-Morris

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The reliability evaluation of composite generation and bulk transmission systems is crucial for ensuring a reliable supply of electrical energy to significant system load points. However, evaluating adequacy indices using probabilistic methods like sequential Monte Carlo Simulation can be computationally expensive. Despite this, it is necessary when time-varying and interdependent resources, such as renewables and energy storage systems, are involved. Recent advances in solving power network optimization problems and parallel computing have improved runtime performance while maintaining solution accuracy. This work introduces CompositeSystems, an open-source Composite System Reliability Evaluation tool developed in Julia™, to address the current deficiencies of commercial and non-commercial tools. This work introduces its design, validation, and effectiveness, which includes analyzing two different formulations of the Optimal Power Flow problem. The simulations demonstrate excellent agreement with existing published studies while improving replicability and reproducibility. Overall, the proposed tool can provide valuable insights into the performance of transmission systems, making it an important addition to the existing toolbox for power system planning.

Keywords: open-source software, composite system reliability, optimization methods, Monte Carlo methods, optimal power flow

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Authors: M. F. Amado, A. Amado, F. Poggi, J. Correia de Freitas

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Today it is widely understood that global energy consumption patterns are directly related to the ongoing urban expansion and development process. This expansion is based on the natural growth of human activities and has left most urban areas totally dependent on fossil fuel derived external energy inputs. This status-quo of production, transportation, storage and consumption of energy has become inefficient and is set to become even more so when the continuous increases in energy demand are factored in. The territorial management of land use and related activities is a central component in the search for more efficient models of energy use, models that can meet current and future regional, national and European goals. In this paper, a methodology is developed and discussed with the aim of improving energy efficiency at the municipal level. The development of this methodology is based on the monitoring of energy consumption and its use patterns resulting from the natural dynamism of human activities in the territory and can be utilized to assess sustainability at the local scale. A set of parameters and indicators are defined with the objective of constructing a systemic model based on the optimization, adaptation and innovation of the current energy framework and the associated energy consumption patterns. The use of the model will enable local governments to strike the necessary balance between human activities, economic development, and the local and global environment while safeguarding fairness in the energy sector.

Keywords: solar urban planning, solar smart city, urban development, energy efficiency

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Authors: Noureddine Ramdani

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In recent years, extensive attention has been given to the study of conductive nanocomposites due to their unique properties, which are dependent on their size and shape. The potential applications of these materials include electromagnetic interference shielding, energy storage, photovoltaics, and others. These outstanding properties have led to increased interest and research in this field. In this work, a conductive poly benzoxazine nanocomposite, PBZ/Gr-Cu, was synthesized through a compression molding technique to achieve a high-performance material suitable for electromagnetic interference (EMI) shielding applications. The microstructure of the nanocomposites was analyzed using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The thermal stability, electrical conductivity, and EMI shielding properties of the nanocomposites were evaluated using thermogravimetric analysis, a four-point probe, and a VNA analyzer, respectively. The TGA results revealed that the thermal stability and electrical conductivity of the nanocomposites were significantly enhanced by the incorporation of Gr/Cu nanoparticles. The nanocomposites exhibited a low percolation threshold of about 3.5 wt.% and an increase in carrier concentration and mobility of the carriers with increasing hybrid nanofiller content, causing the composites to behave as n-type semiconductors. These nanocomposites also displayed a high dielectric constant and a high dissipation factor in the frequency range of 8-12 GHz, resulting in higher EMI shielding effectiveness (SE) of 25-44 dB. These characteristics make them promising candidates for lightweight EMI shielding materials in aerospace and radar evasion applications.

Keywords: polybenzoxazine matrix, conductive nanocomposites, electrical conductivity, EMI shielding

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Authors: Basak Ozkendirci

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The discovery of chemical dyes, the development of regenerated fibers, and warp knitting technology have enormous effects on the fashion world. The trends created by the information obtained in the context of various studies today shape the fashion world. Trend analysts must follow scientific developments as well as sociological events, political developments and artwork to obtain healthy data on trends. Digital printing technologies have changed the dynamics of textile printing production and also the style of printed designs. Fashion designers already have started design 3D printed accessories and garments. The research fields like the internet of things, artificial intelligence, hologram technologies, mechatronics, energy storage systems, nanotechnology are seen as the technologies that will change the social life and economy of the future. It is clear that research carried out in these areas will affect the textiles of the future and whereat the trends of fashion. The article aims to create a future vision for trend researchers and designers by giving clues about the changes to be experienced in the fashion world. In the first part of the article, information about the scientific studies that are thought to shape the future is given, and the forecasting about how the inventions that can be obtained from these studies can be adapted at the textile are presented. In the second part of the article, examples of how the new generation of innovative textiles will affect the daily life experience of the user are given.

Keywords: biotextiles, fashion trends, nanotextiles, new materials, smart textiles, techno textiles

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Authors: Hyunuk Kim, Yang No Yun, Muhammad Sohail, Jong-Ho Moon, Young Cheol Park

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Metal-organic frameworks (MOFs), which are emerging absorbents assembled from metal ions and organic ligands, have attracted attention for their permanent porosity and design of tunable pore size. These microporous materials showed interesting properties for CO₂ storage and separation. In particular, MOFs with high surface area and open metal sites showed the remarkable adsorption capacity and selectivity for CO₂. [Mg₂ (DOBDC)] (DOBDC = 2,5-dioxidobenzene-1,4-dicarboxylate) (MOF-74 or CPO-27) is a well-known absorbent showing an exceptionally high CO₂ sorption capacity at low partial pressure and room temperature. In this work, we synthesized [M₂(DOBDC)(DMF)₂] (M = Mg, Co, Ni) and determined their single-crystal structures by X-ray crystallography. The removal of coordinated guest molecules generates Lewis acidic sites and showed high CO₂ adsorption affinity. Both CO₂ adsorption capacity and surface area are much higher than reported values in literature. To fabricate MMMs, microcrystalline [M₂ (DOBDC)(DMF)₂] was synthesized by microwave reaction and dispersed in PDMS solution. The MMMs with a various amount of [M₂ (DOBDC)(DMF) ₂] in PDMS were fabricated by a solution casting method. [M₂ (DOBDC)(DMF)₂]@PDMS membrane showed higher CO2 permeability and CO₂/N₂ selectivity than those of PDMS. Therefore, we believe that MMMs combining polymer and MOFs provide new materials for CO₂ separation technology.

Keywords: metal-organic frameworks, mixed matrix membrane, CO2/N2 separation, polydimethylsiloxane (PDMS)

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Authors: Ahmad Mohammad Sharqi, Mohamed Hechmi El Ouni, Saleh Alsulamy

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Due to the emerging technologies revolution worldwide, the need to exploit and employ innovative technologies for other functions and purposes in different aspects has become a remarkable matter. Saudi Arabia is considered one of the most powerful economic countries in the world, where the construction sector participates effectively in its economy. Thus, the construction sector in KSA should convoy the rapid digital revolution and transformation and implement smart devices on sites. A Smart Construction Site (SCS) includes smart devices, artificial intelligence, the internet of things, augmented reality, building information modeling, geographical information systems, and cloud information. This paper aims to study the level of implementation of SCS in KSA, analyze the obstacles and challenges of adopting SCS and find out critical success factors for its implementation. A survey of close-ended questions (scale and multi-choices) has been conducted on professionals in the construction sector of Saudi Arabia. A total number of twenty-nine questions has been prepared for respondents. Twenty-four scale questions were established, and those questions were categorized into several themes: quality, scheduling, cost, occupational safety and health, technologies and applications, and general perception. Consequently, the 5-point Likert scale tool (very low to very high) was adopted for this survey. In addition, five close-ended questions with multi-choice types have also been prepared; these questions have been derived from a previous study implemented in the United Kingdom (UK) and the Dominic Republic (DR), these questions have been rearranged and organized to fit the structured survey in order to place the Kingdom of Saudi Arabia in comparison with the United Kingdom (UK) as well as the Dominican Republic (DR). A total number of one hundred respondents have participated in this survey from all regions of the Kingdom of Saudi Arabia: southern, central, western, eastern, and northern regions. The drivers, obstacles, and success factors for implementing smart devices and technologies in KSA’s construction sector have been investigated and analyzed. Besides, it has been concluded that KSA is on the right path toward adopting smart construction sites with attractive results comparable to and even better than the UK in some factors.

Keywords: artificial intelligence, construction projects management, internet of things, smart construction sites, smart devices

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Authors: Golda Honey Madhu, Priyanka Gupta, Anil Kumar Yadav

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The study is aimed at analyzing and understanding the design and performance properties of leno woven sacks specifically meant for holding lower weight goods under the category of lower weight capacities. The sacks are a huge part of the agro-based packaging industries which helps in keeping the perishable produce, especially fruits, fresh during transit and storage. Nowadays, Leno bags are primarily made from polypropylene, mainly due its cost-effectiveness, reusability and high strength with low weight property making it an ideal packaging solution for transportation. The design parameters are noted, and major properties like tensile strength, abrasion resistance, bursting strength, impact resistance, stiffness and bagging behaviour has been analyzed for lower weight capacities. An examination of these particular weight categories will provide valuable information on how to scale performance. Currently there are standards available for only 25 kg and 50 kg Leno sacks, and this study will further enhance the already existing testing standards and also provide tested structure-property analysis for lower weight Leno sacks. Hence the results of this research can provide significant insights for researchers, manufacturers and industry-experts with the goal of improving the quality and longevity of Leno woven sacks, thereby developing the packaging technology.

Keywords: leno bags, structure-property analysis, agro-based packaging, lower weight sacks

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Authors: Radovan Cobanovic, Milica Rankov Sicar

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Biodiesel refers to a vegetable oil - or animal fat-based diesel fuel consisting of long-chain alkyl (methyl, ethyl, or propyl) esters. It is derived by alcoholysis of triacylglycerols (triglycerides) from various lipid based materials that can be traditionally categorized into the following main groups: vegetable oils, animal fats, waste and algal oils. The goal of this study was to evaluate microbiological stability of biodiesel samples since it has been made from vegetable oil or animal fat which was stored on room temperature. For the purposes of this study, analyzes were conducted on six samples of biodiesel first at zero sample at the reception day than fifth, thirtieth, sixtieth, ninetieth and one hundred twentieth day from the day of reception. During this period, biodiesel samples were subjected to microbiological analyses (Salmonella spp., Listeria monocytogenes, Enterobacteriaceae and total plate count). All analyses were tested according to ISO methodology: Salmonella spp ISO 6579, Listeria monocytogenes ISO 11290-2, Enterobacteriaceae ISO 21528-1, total plate count ISO 4833-1. The results obtained after the analyses which were done according to the plan during the 120 days indicate that are no changes of products concerning microbiological analyses. Salmonella spp., Listeria monocytogenes, Enterobacteriaceae were not detected and results for total plate count showed values < 10 cfu/g for all six samples. On the basis of this monitoring under defined storage conditions at room temperatures, the results showed that biodiesel is very stable as far as microbiological analysis were concerned.

Keywords: biodiesel, microbiology, room temperature, stability

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Authors: H. M. Nuralam, Z. Xiao-lan, B. K. Dubey, D. Wen-Chuan

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Healthcare waste (HCW) is one of the major concerns in environmental issues due to its infectious and hazardous nature that is requires specific treatment and systematic management prior to final disposal. This study aimed to assess HCW management system in Dhaka City (DC), Bangladesh, by investigating the present practices implemented by the city. In this study, five different healthcare establishments were selected in DC. Field visits and interviews with health personnel and staff who are concerned with the waste management were conducted. The information was gathered through questionnaire focus on the different aspect of HCW management like, waste segregation and collection, storage and transport, awareness as well. The results showed that a total of 7,215 kg/day (7.2 ton/day) of waste were generated, of which 79.36% (5.6 ton/day) was non-hazardous waste and 20.6% (1.5 ton/day) was hazardous waste. The rate of waste generation in these healthcare establishments (HCEs) was 2.6 kg/bed/day. There was no appropriate and systematic management of HCWs except at few private HCEs that segregate their hazardous waste. All the surveyed HCEs dumped their HCW together with the municipal waste, and some staff members were also found to be engaged in improper handling of the generated waste. Furthermore, the used sharp instruments, saline bags, blood bags and test tubes were collected for resale or reuse. Nevertheless, the lack of awareness, appropriate policy, regulation and willingness to act, were responsible for the improper management of HCW in DC. There was lack of practical training of concerned healthcare to handle the waste properly, while the nurses and staff were found to be aware of the health impacts of HCW.

Keywords: awareness, disposal, Dhaka city, healthcare waste management, waste generation

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Authors: Mouna Hamed, Ammar B. Brahim

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The objective of this work was to develop a theoretical model to study the dynamic thermal behavior of a flat plate solar collector integrated with a phase change material (PCM). The PCM acted as a heat source for the solar system during low intensity solar radiation and night. The energy balance equations for the various components of the collector as well as for the PCM were formulated and numerically solved using MATLAB computational program. The effect of natural convection on heat during the melting process was taken into account by using an effective thermal conductivity. The model was used to investigate the effect of inlet water temperature, water mass flow rate, and PCM thickness on the outlet water temperature and the melt fraction during charging and discharging modes. A comparison with a collector without PCM was made. Results showed that charging and discharging processes of PCM have six stages. The adding of PCM caused a decrease in temperature during charge and an increase during discharge. The rise was most enhanced for higher inlet water temperature, PCM thickness and for lower mass flow rate. Analysis indicated that the complete melting time was shorter than the solidification time due to the high heat transfer coefficient during melting. The increases in PCM height and mass flow rate were not linear with the melting and solidification times.

Keywords: thermal energy storage, phase change material, melting, solidification

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Authors: S. Patel, T. Mitra, R. Dubey, J. Keller

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In the present investigations, an attempt has been made to study the charge storage mechanism and mechanism for the flow of transient charging and discharging current in an amorphous polymer (Polysulfone) (PSF) and a semi-crystalline polar Polyvinylidene fluoride (PVDF) blends in ratio PSF: PVDF: 80:20;85:15;90:10 and 95:05 at various poling temperatures (i.e. 60, 75, 90 and 1150C) and with field strength (100, 150, 200 and 250kVcm⁻¹). Thermally stimulated depolarizing current TSDC thermograms for (Polysulfone (PSF) and Polyvinylidene fluoride (PVDF) Blends sample have been obtained under different polarizing conditions. Peaks are found at high-temperature side. The variation of structure on blending and poling condition affects the magnitude of TSDC. The activation energy values have been calculated using the initial rise method of Garlick and Gibson. The transient current with the similar polarizing condition has been investigated over a period of 3X10³ sec. The observed characteristics obey Curie-Von Schweidler law in the studied temperature range. The charging current versus polarizing temperature curves at a constant time, i.e., isochronal current characteristics were studied and the activation energies were calculated. The activation energy in transient thermograms calculated by different methods is in good agreement with the values obtained from TSDC studies.

Keywords: activation energy, polysulfone (PSF), polyvinylidenefluoride (PVDF), thermally stimulated depolarizing current (TSDC)

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Authors: Taghreed Abu-Salim

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This paper develops and investigates a framework for the assessment of customer involvement in the service design process of result oriented product-service systems in order to improve the service offering in a business to business (B2B) context. The framework comprises five main criteria and fifteen sub-criteria that contribute to customer involvement in a hierarchy using a maturity grid to highlight the strengths and weaknesses for each criterion. To develop the customer involvement framework, an extensive literature review related to service design, result oriented product-service system (PSS) and customer involvement in service design was carried out. Key factors that significantly influence customer involvement from industry and literature were identified to develop an initial framework. This framework was tested in six companies from four different sectors of industry: district cooling, medical equipment, transportation and oil storage. Validation of the framework was carried out using expert opinions and industrial case studies. A major contribution of the developed framework includes a hierarchy of appropriate criteria for assessing customer involvement in the service design process within results oriented PSS; the definition of four maturity levels which are suitable to describe the whole spectrum of customer involvement in the service design process; and finally, The paper concludes by enabling service providers to: take proactive decisions; screen and evaluate new services; improve perceived service quality; and provide barriers against imitation.

Keywords: customer involvement, maturity grid, new service development, result oriented product-service system, service design

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Authors: Geeta Kumari, Prabu Vairakannu

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Coal is the largest fossil fuel. In India, around 37 % of coal resources found at a depth of more than 300 meters. In India, more than 70% of electricity production depends on coal. Coal on combustion produces greenhouse and pollutant gases such as CO₂, SOₓ, NOₓ, and H₂S etc. Underground coal gasification (UCG) technology is an efficient and an economic in-situ clean coal technology, which converts these unmineable coals into valuable calorific gases. The UCG syngas (mainly H₂, CO, CH₄ and some lighter hydrocarbons) which can utilized for the production of electricity and manufacturing of various useful chemical feedstock. It is an inherent clean coal technology as it avoids ash disposal, mining, transportation and storage problems. Gasification of underground coal using steam as a gasifying medium is not an easy process because sending superheated steam to deep underground coal leads to major transportation difficulties and cost effective. Therefore, for reducing this problem, we have used CO₂ as a gasifying medium, which is a major greenhouse gas. This paper focus laboratory scale underground coal gasification experiment on a coal block by using CO₂ as a gasifying medium. In the present experiment, first, we inject oxygen for combustion for 1 hour and when the temperature of the zones reached to more than 1000 ºC, and then we started supplying of CO₂ as a gasifying medium. The gasification experiment was performed at an atmospheric pressure of CO₂, and it was found that the amount of CO produced due to Boudouard reaction (C+CO₂  2CO) is around 35%. The experiment conducted to almost 5 hours. The maximum gas composition observed, 35% CO, 22 % H₂, and 11% CH4 with LHV 248.1 kJ/mol at CO₂/O₂ ratio 0.4 by volume.

Keywords: underground coal gasification, clean coal technology, calorific value, syngas

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Authors: Jianfang Wang, Xianzhe Chen, Zhuoliang Liu, Cheng-An Tao, Yujiao Li

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Organophosphorus (OPs) pesticide used as insecticides are widely used in agricultural pest control, household and storage deworming. The detection of pesticides needs more simple and efficient methods. One of the best ways is to make electrochemical biosensors. In this paper, an electrochemical enzyme biosensor based on acetylcholine esterase (AChE) was constructed, and its sensing properties and sensing mechanisms were studied. Reduced graphene oxide-polydopamine complexes (RGO-PDA), gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were prepared firstly and composited with AChE and chitosan (CS), then fixed on the glassy carbon electrode (GCE) surface to construct the biosensor GCE/RGO-PDA-AuNPs-AgNPs-AChE-CS by one-pot method. The results show that graphene oxide (GO) can be reduced by dopamine (DA) and dispersed well in RGO-PDA complexes. And the composites have a synergistic catalysis effect and can improve the surface resistance of GCE. The biosensor selectively can detect acetylcholine (ACh) and OPs pesticide with good linear range and high sensitivity. The performance of the biosensor is affected by the ratio and adding ways of AChE and the adding of AuNPs and AChE. And the biosensor can achieve a detection limit of 2.4 ng/L for methyl parathion and a wide linear detection range of 0.02 ng/L ~ 80 ng/L, and has excellent stability, good anti-interference ability, and excellent preservation performance, indicating that the sensor has practical value.

Keywords: acetylcholine esterase, electrochemical biosensor, nanoparticles, organophosphates, reduced graphene oxide

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Authors: Elaid Bouchetob, Bouchra Nadji

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This research paper compares the efficiency and reliability (R(t)) of SiC-based and Si-based DC-DC buck converters in thin layer PV systems with an AI-based MPPT controller. Using Simplorer/Simulink simulations, the study assesses their performance under varying conditions. Results show that the SiC-based converter outperforms the Si-based one in efficiency and cost-effectiveness, especially in high temperature and low irradiance conditions. It also exhibits superior reliability, particularly at high temperature and voltage. Reliability calculation (R(t)) is analyzed to assess system performance over time. The SiC-based converter demonstrates better reliability, considering factors like component failure rates and system lifetime. The research focuses on the buck converter's role in charging a Lithium battery within the PV system. By combining the SiC-based converter and AI-based MPPT controller, higher charging efficiency, improved reliability, and cost-effectiveness are achieved. The SiC-based converter proves superior under challenging conditions, emphasizing its potential for optimizing PV system charging. These findings contribute insights into the efficiency, reliability, and reliability calculation of SiC-based and Si-based converters in PV systems. SiC technology's advantages, coupled with advanced control strategies, promote efficient and sustainable energy storage using Lithium batteries. The research supports PV system design and optimization for reliable renewable energy utilization.

Keywords: efficiency, reliability, artificial intelligence, sic device, thin layer, buck converter

Procedia PDF Downloads 63

Authors: Amira Abdelhafez, Rufus Brunt

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Geothermal energy in Egypt represents a significant untapped renewable resource that can reduce reliance on conventional power generation. Exploiting these geothermal resources depends on depth, temperature range, and geological characteristics. The intracontinental rift setting of the Gulf of Suez (GoS)-Red Sea rift is a favourable tectonic setting for convection-dominated geothermal plays. The geothermal gradient across the GoS ranges from 24.9 to 86.66 °C/km, with a heat flow of 31-127.2 mW/m². Surface expressions of convective heat loss emerge along the gulf flanks as hot springs (e.g., Hammam Faraun) accompanying deeper geothermal resources. These thermal anomalies are driven mainly by the local tectonic configuration. Characterizing the structural framework of major faults and their control on reservoir properties and subsurface hydrothermal fluid circulation is vital for geothermal applications in the gulf. The geothermal play systems of the GoS depend on structural and lithological properties that contribute to heat storage and vertical transport. Potential geothermal reservoirs include the Nubia sandstones, which, due to their thickness, continuity, and contact with hot basement rocks at a mean depth of 3 km, create an extensive reservoir for geothermal fluids. To develop these geothermal resources for energy production, defining the permeability anisotropy of the reservoir due to faults and facies variation is a crucial step in our study, particularly the evaluation of influence on thermal breakthrough and production rates.

Keywords: geothermal, October field, site specific study, reservoir modelling

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