Search results for: smart hybrid powerpack (SHP)

Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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Authors: Hilal Turkoglu Sasmazel, Ozan Ozkan, Seda Surucu

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Tissue engineering is the field of treating defects caused by injuries, trauma or acute/chronic diseases by using artificial scaffolds that mimic the extracellular matrix (ECM), the natural biological support for the tissues and cells within the body. The main aspects of a successful artificial scaffold are (i) large surface area in order to provide multiple anchorage points for cells to attach, (ii) suitable porosity in order to achieve 3 dimensional growth of the cells within the scaffold as well as proper transport of nutrition, biosignals and waste and (iii) physical, chemical and biological compatibility of the material in order to obtain viability throughout the healing process. By hybrid scaffolds where two or more different materials were combined with advanced fabrication techniques into complex structures, it is possible to combine the advantages of individual materials into one single structure while eliminating the disadvantages of each. Adding this to the complex structure provided by advanced fabrication techniques enables obtaining the desired aspects of a successful artificial tissue scaffold. In this study, fibroblast compatibility of poly(ε-caprolactone) (PCL)/chitosan core-shell electrospun hybrid scaffolds with proper mechanical, chemical and physical properties successfully developed in our previous study was investigated. Standard 7-day cell culture was carried out with L929 fibroblast cell line. The viability of the cells cultured with the scaffolds was monitored with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) viability assay for every 48 h starting with 24 h after the initial seeding. In this assay, blank commercial tissue culture polystyrene (TCPS) Petri dishes, single electrospun PCL and single electrospun chitosan mats were used as control in order to compare and contrast the performance of the hybrid scaffolds. The adhesion, proliferation, spread and growth of the cells on/within the scaffolds were observed visually on the 3rd and the 7th days of the culture period with confocal laser scanning microscopy (CSLM) and scanning electron microscopy (SEM). The viability assay showed that the hybrid scaffolds caused no toxicity for fibroblast cells and provided a steady increase in cell viability, effectively doubling the cell density for every 48 h for the course of 7 days, as compared to TCPS, single electrospun PCL or chitosan mats. The cell viability on the hybrid scaffold was ~2 fold better compared to TCPS because of its 3D ECM-like structure compared to 2D flat surface of commercially cell compatible TCPS, and the performance was ~2 fold and ~10 fold better compared to single PCL and single chitosan mats, respectively, even though both fabricated similarly with electrospinning as non-woven fibrous structures, because single PCL and chitosan mats were either too hydrophobic or too hydrophilic to maintain cell attachment points. The viability results were verified with visual images obtained with CSLM and SEM, in which cells found to achieve characteristic spindle-like fibroblast shape and spread on the surface as well within the pores successfully at high densities.

Keywords: chitosan, core-shell, fibroblast, electrospinning, PCL

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Sinan Alsaadi, Mustafa Merdan

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Communication and access systems can be made with many methods in today’s world. These systems are such standards as Wifi, Wimax, Bluetooth, GPS and GPRS. Devices which use these standards also use system resources excessively in direct proportion to their transmission speed. However, large-scale data communication is not always needed. In such cases, a technology which will use system resources as little as possible and support smart network topologies has been needed in order to enable the transmissions of such small packet data and provide the control for this kind of devices. IEEE issued 802.15.4 standard upon this necessity and enabled the production of Zigbee protocol which takes these standards as its basis and devices which support this protocol. In our project, this communication protocol was preferred. The aim of this study is to provide the immediate data transmission of our robot from the field within the scope of the project. In addition, making the communication with the robot through Zigbee Protocol has also been aimed. While sitting on the computer, obtaining the desired data from the region where the robot is located has been taken as the basis. Arduino Uno R3 microcontroller which provides the control mechanism, 1298 shield as the motor driver.

Keywords: ZigBee, wireless network, remote monitoring, smart home, agricultural industry

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Authors: T. Wanyama, B. Far

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Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

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Authors: L. Sun, C. Hardacre, A. Garforth, N. Zhang

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Higher Education (HE) degrees in the UK are attractive for international students. The recognized reputation of the HE and the world-leading researchers in some areas in the UK imply that the HE degree from the UK might be a passport to a successful career for abroad students. However, it is a challenge to inspire outstanding students applying for the universities in the UK. The incentives should be country-specific for undergraduates and postgraduates. The potential obstacles to stop students applying for the study in the UK mainly lie in these aspects: different HE systems between the UK and other countries, such as China; less information for the application procedures; worries for the study in English for those non-native speakers; and expensive international tuition fees. The hybrid incentives have been proposed by the efforts from the institutions, stuffs, and students themselves. For example, excellent students from top universities would join us based on the abroad exchange programs or ‘2+2 programme’ with discount tuition. They are potential PhD candidates in the further study in the UK. Diversity promotions are implemented to share information and answer queries for potential students and their guardians. Face to face presentations, workshops, and seminars deliver chances for students to admire teaching and learning in the UK, and give students direct answers for their confusions. WeChat official account and Twitter as the online information platform are set up to post messages of recruitment, the guidance for the application procedures, and international collaboration in teaching and research as well. Students who are studying in the UK and the alumni would share their experiences in the study and lives in the UK and their careers after obtaining the HE degree would play as a positive stimulus to our potential students. Short term modules in the UK with exchangeable credits in summer holidays would give abroad students firsthand experiences of the study in the reputable schools with excellent academics, different cultures and the network with international students. Successful cases at the University of Manchester illustrated the effectiveness of these presented methodologies.

Keywords: abroad students, degree study, high education, hybrid incentives

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Authors: Ghulam Hasan Abbasi, Moazzam Jamil, M. Anwar-Ul-Haq

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Heavy metals are significant pollutants in environment and their toxicity is a problem for survival of living things while Silicon (Si) is one of the most ubiquitous macroelements, performing an essential function in healing plants in response to environmental stresses. A hydroponic experiment was conducted to investigate the role of exogenous application of silicon under cadmium stress in six different maize hybrids with five treatments comprising of control, 7.5 µM Cd + 5 mM Si, 7.5 µM Cd + 10 mM Si, 15 µM Cd + 5 mM Si and 15 µM Cd + 10 mM Si. Results revealed that treatments of plants with 10mM Si application under both 7.5µM Cd and 15 µM Cd stress resulted in maximum improvement in plant morphological attributes (root and shoot length, root and shoot fresh and dry weight, leaf area and relative water contents) and antioxidant enzymes (POD and CAT) relative to 5 mM Si application in all maize hybrids. Results regarding Cd concentrations showed that Cd was more retained in roots followed by shoots and then leaves and maximum reduction in Cd uptake was observed at 10mM Si application. Maize hybrid 6525 showed maximum growth and least concentration of Cd whereas maize hybrid 1543 showed the minimum growth and maximum Cd concentration among all maize hybrids.

Keywords: antioxidant, cadmium, maize, silicon

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Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Weiwei Cao, Xiaodong Xing

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In order to effectively resolve the microbial pollution and contamination, synthetic nano-antibacterial materials are widely used in daily life. Among them, nanodiamonds (NDs) have recently been demonstrated to hold promise as useful materials in biomedical applications due to their high specific surface area and biocompatibility. In this work, the copolymer, poly(4-vinylpyridine-co-2-hydroxyethyl methacrylate) was applied for the surface functionalization of NDs to produce the quaternized poly(4-vinylpyridine-co-2-hydroxyethyl methacrylate)-functionalized NDs (QNDs). Then, QNDs were used as a substrate for silver nanoparticles (AgNPs) to produce a QND@Ag hybrid. The composition and morphology of the resultant nanostructures were confirmed by Fourier transform infrared spectra (FT-IR), transmission electron microscope (TEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). The mass fraction of AgNPs in the nanocomposites was about 35.7%. The antibacterial performances of the prepared nanocomposites were evaluated with Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus by minimum inhibitory concentration (MIC), inhibition zone testing and time-kill study. As a result, due to the synergistic antibacterial activity of QND and AgNPs, this hybrid showed substantially higher antibacterial activity than QND and polyvinyl pyrrolidone (PVP)-stabilized AgNPs, and the AgNPs on QND@Ag were more stable than the Ag NPs on PVP, resulting in long-term antibacterial effects. More importantly, this hybrid showed excellent water solubility and low cytotoxicity, suggesting the great potential application in biomedical applications. The present work provided a simple strategy that successfully turned NDs into nanosized antibiotics with simultaneous superior stability and biocompatibility, which would broaden the applications of NDs and advance the development of novel antibacterial agents.

Keywords: cationic copolymer, nanodiamonds, silver nanoparticles, dual antibacterial activity, lower cytotoxicity

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Authors: K. M. Jananni, R. Nandini

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The proposed wireless, inverter type design of a LPG leakage monitoring system aims to provide a smart and safe kitchen. The system detects the LPG gas leak using Nano-sensors and alerts the concerned individual through GSM system. The system uses two sensors, one attached to the chimney and other to the regulator of the LPG cylinder. Upon a leakage being detected, the sensor at the regulator actuates the system to cut off the gas supply immediately using a solenoid control valve. The sensor at the chimney checks for the permissible level of LPG mix in the air and when the level exceeds the threshold, the system sends an automatic SMS to the numbers saved. Further the sensor actuates the mini suction system fixed at the chimney within 20 seconds of a leakage to suck out the gas until the level falls well below the threshold. As a safety measure, an automatic window opening and alarm feature is also incorporated into the system. The key feature of this design is that the system is provided with a special inverter designed to make the device function effectively even during power failures. In this paper, utilization of sensors in the kitchen area is discussed and this gives the proposed architecture for real time field monitoring with a PIC Micro-controller.

Keywords: nano sensors, global system for mobile communication, GSM, micro controller, inverter

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Authors: Tesfaye Walle Mekonnen

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Maize is one of the most important staple food crops for most low-income households in the Sub-Saharan (SSA). Combined heat and drought stress is the major production threats that reduce the yield potential of biofortified maize and restrain various macro and micronutrient deficiencies highly prevalent in low-income people who rely solely on maize-based diets, SSA. This problem can be alleviated by crossing the biofortified inbred lines with different nutritional attributes, Fe, Zn, Protein, and Provitamin A, and developing agronomically superior and stable multi-nutrient maize of various genetic backgrounds. This aimed to understand the correlation between biofortified inbred lines per se and hybrid performance under combined heat and drought stress conditions (CSC). The experiment was conducted at CIMMYT, Zimbabwe, using α-lattice design with three replications. The hybrid effect was highly significant for zein fractions (α-, β-, γ- and δ-zein) zinc, (Zn), and iron (Fe) provitamin A, phytic acid, and grain yield. Under CSC, Fe, Zn concentration, provitamin A in grain and grain yield of hybrids were significantly decreased, however, the zein fraction content and phytic acid content increases in grain were increased under CSC. The phenotypic correlation between grain yield with Zn, Fe concentration, and Provitamin A in grain was strongly positive and higher under CSC than in well-watered conditions. The present investigation confirmed that under CSC, Fe, and Zn-enhanced hybrids could be forecasted to a certain scope based on the performance of and scientifically selected for desirable grain yield and related traits with CSC tolerance during hybrid development programs. In conclusion, the development of high-yielding and micronutrient-dense maize variety is possible under CSC, which could reduce the highly prevalent micronutrient in SSA.

Keywords: drought, Fe, heat, maize, protein, zein fractions, Zn

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Authors: Nancy Sakr, Mohamed Abou-Zeid

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World energy consumption has increased rapidly in the past few years. Due to population growth, total energy consumption is increasing; a large amount of energy is wasted on the cooling and heating processes in buildings. However, using thermal heating management can minimize costs, heat consumption and create a management system for the heat insulation for buildings. This concept is being implemented through different approaches. Based on analysis and research, there is evidence in the energy consumption before and after testing and applying construction approaches for thermal heating management in building units. This investigation addresses the evaluation of the influence of external coatings on energy consumption. Coatings are considered one of the smart effective available approaches for energy efficiency. Unfortunately, this approach is not widely applied in the construction industry. It needs more data to prove effectiveness and credibility between people to use it as a smart thermal insulation approach. Two precedents have been analyzed in order to monitor buildings’ heat exposure, and how the buildings will be affected by thermal insulation materials. Data sheets from chemical companies which produce similar coatings are compared with the usual products and the protective thermal products.

Keywords: energy consumption, building envelope, thermal insulation, protective coatings

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Authors: Md. Rezaul Karim, Andreas Thiel

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Bangladesh is known as one of the most climate vulnerable countries in the world. Innovative technologies are always the key responses to the management of climate impacts. The objectives of this study are to determine the farmer’s perception of climate variability, to compare farmers’ perceptions with metrological data, and to explore the determinants that affect the likelihood of adoption of the selected Climate Smart Agricultural (CSA) technologies. Data regarding climate change perception, determinants and adoption were collected based on the household survey from stratified and randomly selected 365 farmers of the Biral sub-district under Dinajpur district in drought-prone northern Bangladesh. The likelihood of adoption of CSA technologies was analyzed following a multivariate probit model. The findings show that about 82.5% of the farmers perceived increasing temperature, and 75.1 % of farmers perceived decreasing dry season rainfall over the years, which is similarly relevant to metrological data. About 76.4.7% and 80.85% of farmers were aware of the drought tolerance crops and vermicompost, respectively; more than half of the farmers adopted these practices. Around 70.7% of farmers were aware of perching for insect control, but 46.3% of farmers adopted this practice. Although two-thirds of farmers were aware of crop diversification and pheromone trap, adoption was lower compared to the other three CSAs. Results also indicate that the likelihood of adoption of the selected CSAs is significantly influenced by different factors such as socio-economic characteristics, institutional factors and perceived technological or innovation attributes. The likelihood of adopting drought tolerance crops is affected by 11, while crop diversification and perching method by 7, pheromone trap by 9 and vermicompost by 8 determining factors. Lack of information and unavailability of input appear to be major obstacles to the non-adoption of CSA technologies. This study suggests that policy implications are necessary to promote extension services and overcome the obstacles to the non-adoption of individual CSA technologies. It further recommends that the research study should be conducted in a diverse context, nationally or globally.

Keywords: determinants, adoption, climate smart agriculture, northern Bangladesh

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Authors: Nan Hu, Wujun Wang

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In the ever-changing digital arena, augmented reality (AR) applications have transitioned from technological enthusiasm into business endeavors, signaling a near future in which AR applications are integrated into daily life. While practitioners in the design industry continue to explore AR’s potential for innovative communication, educators have taken steps to incorporate AR into the curricula for design, explore its creative potential, and realize early initiatives for teaching AR in design-related disciplines. In alignment with recent advancements, this paper presents a pedagogical model for a hybrid studio course in which students collaborate with AR alongside 3D modeling and graphic design. The course extended students’ digital capacity, fostered their design thinking skills, and immersed them in a multidisciplinary design process. This paper outlines the course and evaluates its effectiveness by discussing challenges encountered and outcomes generated in this particular pedagogical context. By sharing insights from the teaching experience, we aim to empower the community of design educators and offer institutions a valuable reference for advancing their curricular approaches. This paper is a testament to the ever-evolving landscape of design education and its response to the digital age.

Keywords: 3D, AR, augmented reality, design thinking, graphic design

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Authors: Anupoju Rajeev, Joanne Mathew, Amit Shelke

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In the current study, a new type of Composite Structural Insulated Panels (CSIPs) is developed and investigated its performance against shock loading which can replace the conventional wooden structural materials. The CSIPs is made of Fibre Cement Board (FCB)/aluminum as the facesheet and the expanded polystyrene foam as the core material. As tornadoes are very often in the western countries, it is suggestable to monitor the health of the CSIPs during its lifetime. So, the composite structure is installed with three smart sensors located randomly at definite locations. Each smart sensor is fabricated with an embedded half stainless phononic crystal sensor attached to both ends of the nylon shaft that can resist the shock and impact on facesheet as well as polystyrene foam core and safeguards the system. In addition to the granular crystal sensors, the accelerometers are used in the horizontal spanning and vertical spanning with a definite offset distance. To estimate the health and damage of the CSIP panel using granular crystal sensor, shock wave loading experiments are conducted. During the experiments, the time of flight response from the granular sensors is measured. The main objective of conducting shock wave loading experiments on the CSIP panels is to study the effect and the sustaining capacity of the CSIP panels in the extreme hazardous situations like tornados and hurricanes which are very common in western countries. The effects have been replicated using a shock tube, an instrument that can be used to create the same wind and pressure intensity of tornado for the experimental study. Numerous experiments have been conducted to investigate the flexural strength of the CSIP. Furthermore, the study includes the damage detection using three smart sensors embedded in the CSIPs during the shock wave loading.

Keywords: composite structural insulated panels, damage detection, flexural strength, sandwich structures, shock wave loading

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Authors: S. Mahdi Sadatmansouri, Maryam Khalili

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World, nowadays, encounters serious water scarcity problem. During the past few years, by advent of Smart Energy and Water Meter (SEWM) and its installation at the electro-pumps of the water wells, one had believed that it could be the golden key to address the groundwater resources over-pumping issue. In fact, implementation of these Smart Meters managed to control the water table drawdown for short; but it was not a sustainable approach. SEWM has been considered as law enforcement facility at first; however, for solving a complex socioeconomic problem like shared groundwater resources management, more than just enforcement is required: participation to conserve common resources. The well owners or farmers, as water consumers, are the main and direct stakeholders of this system and other stakeholders could be government sectors, investors, technology providers, privet sectors or ordinary people. Designing a socio-technical system not only defines the role of each stakeholder but also can lubricate the communication to reach the system goals while benefits of each are considered and provided. Farmers, as the key participators for solving groundwater problem, do not trust governments but they would trust a fair system in which responsibilities, privileges and benefits are clear. Technology could help this system remained impartial and productive. Social aspects provide rules, regulations, social objects and etc. for the system and help it to be more human-centered. As the design methodology, Design Thinking provides probable solutions for the challenging problems and ongoing conflicts; it could enlighten the way in which the final system could be designed. Using Human Centered Design approach of IDEO helps to keep farmers in the center of the solution and provides a vision by which stakeholders’ requirements and needs are addressed effectively. Farmers would be considered to trust the system and participate in their groundwater resources management if they find the rules and tools of the system fair and effective. Besides, implementation of the socio-technical system could change farmers’ behavior in order that they concern more about their valuable shared water resources as well as their farm profit. This socio-technical system contains nine main subsystems: 1) Measurement and Monitoring system, 2) Legislation and Governmental system, 3) Information Sharing system, 4) Knowledge based NGOs, 5) Integrated Farm Management system (using IoT), 6) Water Market and Water Banking system, 7) Gamification, 8) Agribusiness ecosystem, 9) Investment system.

Keywords: human centered design, participatory management, smart energy and water meter (SEWM), social object, socio-technical system, water table drawdown

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Authors: Ludovic Favre, Thibaut M. Schafer, Jean-Luc Robyr, Elena-Lavinia Niederhäuser

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This paper presents an optimization method based on genetic algorithm for the energy management inside buildings developed in the frame of the project Smart Living Lab (SLL) in Fribourg (Switzerland). This algorithm optimizes the interaction between renewable energy production, storage systems and energy consumers. In comparison with standard algorithms, the innovative aspect of this project is the extension of the smart regulation over three simultaneous criteria: the energy self-consumption, the decrease of greenhouse gas emissions and operating costs. The genetic algorithm approach was chosen due to the large quantity of optimization variables and the non-linearity of the optimization function. The optimization process includes also real time data of the building as well as weather forecast and users habits. This information is used by a physical model of the building energy resources to predict the future energy production and needs, to select the best energetic strategy, to combine production or storage of energy in order to guarantee the demand of electrical and thermal energy. The principle of operation of the algorithm as well as typical output example of the algorithm is presented.

Keywords: building's energy, control system, energy management, energy storage, genetic optimization algorithm, greenhouse gases, modelling, renewable energy

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Antonella D'Alessandro, Filippo Ubertini, Annibale Luigi Materazzi

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The progress of nanotechnology resulted in the development of new instruments in the field of civil engineering. In particular, the introduction of carbon nanofillers into construction materials can enhance their mechanical and electrical properties. In construction, concrete is among the most used materials. Due to the characteristics of its components and its structure, concrete is suitable for modification, at the nanometer level too. Moreover, to guarantee structural safety, it is desirable to achieve a widespread monitoring of structures. The ideal thing would be to realize structures able to identify their behavior modifications, states of incipient damage or conditions of possible risk for people. This paper presents a research work about novel cementitious composites with conductive carbon nanoinclusions able of monitoring their state of deformation, with particular attention to concrete. The self-sensing ability is achieved through the correlation between the variation of stress or strain and that of electrical resistance. Carbon nanofillers appear particularly suitable for such applications. Nanomodified concretes with different carbon nanofillers has been tested. The samples have been subjected to cyclic and dynamic loads. The experimental campaign shows the potentialities of this new type of sensors made of nanomodified concrete for diffuse Structural Health Monitoring.

Keywords: carbon nanofillers, cementitious nanocomposites, smart sensors, structural health monitoring.

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Authors: Sneha Thakur, Sanjeev Karmakar

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This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

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Authors: Afroditi Zamanidou, Dionysios Giannakopoulos, Konstantinos Manolitsis

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A notable amount of electrical energy demand in many countries worldwide is used to cover public energy demand for road, square and other public spaces’ lighting. Renewable energy can contribute in a significant way to the electrical energy demand coverage for public lighting. This paper focuses on the sizing and design of a hybrid energy system (HES) exploiting the solar-wind energy potential to meet the electrical energy needs of lighting roads, squares and other public spaces. Moreover, the proposed HES provides coverage of the electrical energy demand for a Wi-Fi hotspot and a charging hotspot for the end-users. Alongside the sizing of the energy production system of the proposed HES, in order to ensure a reliable supply without interruptions, a storage system is added and sized. Multiple scenarios of energy consumption are assumed and applied in order to optimize the sizing of the energy production system and the energy storage system. A database with meteorological prediction data for 51 areas in Greece is developed in order to assess the possible deployment of the proposed HES. Since there are detailed meteorological prediction data for all 51 areas under investigation, the use of these data is evaluated, comparing them to real meteorological data. The meteorological prediction data are exploited to form three hourly production profiles for each area for every month of the year; minimum, average and maximum energy production. The energy production profiles are combined with the energy consumption scenarios and the sizing results of the energy production system and the energy storage system are extracted and presented for every area. Finally, the economic performance of the proposed HES in terms of Levelized cost of energy is estimated by calculating and assessing construction, operation and maintenance costs.

Keywords: energy production system sizing, Greece’s deployment potential, meteorological prediction data, wind-solar hybrid energy system, levelized cost of energy

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Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

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Authors: Samuel Ahamefula

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Turbulent motion is a highly nonlinear and complex phenomenon, and its modelling is still very challenging. In this study, we developed a hybrid computational approach to accurately simulate fluid turbulence phenomenon. The focus is coupling and transitioning between Direct Numerical Simulation (DNS) and Large Eddy Simulating Wall Models (LES-WM) regions. In the framework, high-order fidelity fluid dynamical methods are utilized to simulate the unsteady compressible Navier-Stokes equations in the Eulerian format on the unstructured moving grids. The coupling and transitioning of DNS and LES-WM are conducted through the linearly staggered Dirichlet-Neumann coupling scheme. The high-fidelity framework is verified and validated based on namely, DNS ability for capture full range of turbulent scales, giving accurate results and LES-WM efficiency in simulating near-wall turbulent boundary layer by using wall models.

Keywords: computational methods, turbulence modelling, turbulence entropy, navier-stokes equations

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Authors: Fátima Farinha, Miguel J. Oliveira, Gina Matias, Armando Inverno, Jânio Monteiro, Cristiano Cabrita

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In the last decades, the construction of swimming pools for recreational activities has grown exponentially in southern Europe. Swimming pools are used both for private use in villas and for collective use in hotels or condominiums. However, they have a high environmental impact, mainly in terms of water and energy consumption, being used for a short period of time, depending significantly on favorable atmospheric conditions. Contrary to what would be expected, not enough research has been conducted to reduce the negative impact of this equipment. In this context, this work proposes and analyses technological measures to reduce the environmental impacts of swimming pools, such as thermal insulation of the tank, water balance in order to detect leaks and optimize the backwash process, integration of renewable energy generation, and a smart control system that meets the requirements of the user. The work was developed within the scope of the Ecopool+++ project, which aims to create innovative heated pools with reduced thermal losses and integration of SMART energy plus water management systems. The project is in the final phase of its development, with very encouraging results.

Keywords: swimming pools, sustainability, thermal losses, water management system

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Authors: D. Aydinoglu, N. Karaca, O. Ceylan

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Limited water resources on the earth come first among the most alarming issues. In this respect, several solutions from treatment of waste water to water management have been proposed. Recently, use of hydrogels as soil additive, which is one of the water management ways in agriculture, has gained increasing interest. In traditional agriculture applications, water used with irrigation aim, rapidly flows down between the pore structures in soil, without enough useful for soil. To overcome this fact and increase the abovementioned limit values, recently, several natural based hydrogels have been suggested and tested to find out their efficiency in soil. However, most of these researches have dealt with grafting of synthetic acrylate based monomers on natural gelling agents, most probably due to reinforced of the natural gels. These results motivated us to search a natural based hydrogel formulations, not including any synthetic component, and strengthened with montmorillonite clay instead of any grafting polymerization with synthetic monomer and examine their potential in this field, as well as characterize of them. With this purpose, carrageenan-psyllium/ montmorillonite hybrid hydrogels have been successively prepared. Their swelling capacities were determined both in deionized and tap water and were found to be dependent on the carrageenan, psyllium and montmorillonite ratios, as well as the water type. On the other hand, mechanical tests revealed that especially carrageenan and montmorillonite contents have a great effect on gel strength, which is one of the essential features, preventing the gels from cracking resulted in readily outflow of all the water in the gel without beneficial for soil. They found to reach 0.23 MPa. The experiments carried out with soil indicated that hydrogels significantly improved the water uptake capacities and water retention degrees of the soil from 49 g to 85 g per g of soil and from 32 to 67%, respectively, depending on the ingredient ratios. Also, biodegradation tests demonstrated that all the hydrogels undergo biodegradation, as expected from their natural origin. The overall results suggested that these hybrid hydrogels have a potential for use as soil additive and can be safely used owing to their totally natural structure.

Keywords: carrageenan, hydrogel, montmorillonite, psyllium

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Authors: Hanane Belayachi, Fadila Nemchi, Amel Belayachi, Sarra Bourahla, Mostefa Belhakem

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In this work, two photocatalytic processes for the degradation of phenol in water are presented. The first one is extensive (EP), which is carried out in a treatment chain of two steps, allowing the adsorption of the pollutant by a naturally activated carbon from the grapes. This operation is followed by a photocatalytic degradation of the residual phenol in the presence of TiO₂. The second process is intensive (IP) and is realized in one step in the presence of a hybrid photocatalytic nanomaterial prepared from naturally activated carbon and TiO₂. The evaluation of the two processes, EP and IP, is based on the analytical monitoring of the initial and final parameters of the water to be treated, i.e., the phenol concentration by liquid phase chromatography (HPLC) and total organic carbon (TOC). For both processes, the sampling was carried out every 10 min for 120 min of treatment time to measure the phenol concentrations. The elimination and degradation rates in the case of the intensive process are better than the extensive process. In both processes, the catechol molecule was detected as an under product of degradation. In the IP case, this intermediate phenol was totally eliminated, and only traces of catechol persisted in the water.

Keywords: photocatalysis, hybrid, activated carbon, phenol

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Authors: M. Invigorito, G. Elia, M. Panelli

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Hybrid propulsion combines beneficial properties of both solid and liquid rockets, such as multiple restarts, throttability as well as simplicity and reduced costs. A nitrous oxide (N2O)/paraffin-based hybrid rocket engine demonstrator is currently under development at the Italian Aerospace Research Center (CIRA) within the national research program HYPROB, funded by the Italian Ministry of Research. Nitrous oxide belongs to the class of self-pressurizing propellants that exhibit a high vapor pressure at standard ambient temperature. This peculiar feature makes those fluids very attractive for space rocket applications because it avoids the use of complex pressurization systems, leading to great benefits in terms of weight savings and reliability. To avoid feed-system-coupled instabilities, the phase change is required to occur through the injectors. In this regard, the oxidizer is stored in liquid condition while target chamber pressures are designed to lie below vapor pressure. The consequent cavitation and flash vaporization constitute a remarkably complex phenomenology that arises great modelling challenges. Thus, it is clear that the design of the injection system is fundamental for the full exploitation of hybrid rocket engine throttability. The Analytical Hierarchy Process has been used to select the injection architecture as best compromise among different design criteria such as functionality, technology innovation and cost. The impossibility to use engineering simplified relations for the dimensioning of the injectors led to the needs of applying a numerical approach based on OpenFOAM®. The numerical tool has been validated with selected experimental data from literature. Quantitative, as well as qualitative comparisons are performed in terms of mass flow rate and pressure drop across the injector for several operating conditions. The results show satisfactory agreement with the experimental data. Modeling assumptions, together with their impact on numerical predictions are discussed in the paper. Once assessed the reliability of the numerical tool, the injection plate has been designed and sized to guarantee the required amount of oxidizer in the combustion chamber and therefore to assure high combustion efficiency. To this purpose, the plate has been designed with multiple injectors whose number and diameter have been selected in order to reach the requested mass flow rate for the two operating conditions of maximum and minimum thrust. The overall design has been finally verified through three-dimensional computations in cavitating non-reacting conditions and it has been verified that the proposed design solution is able to guarantee the requested values of mass flow rates.

Keywords: hybrid rocket, injection system design, OpenFOAM®, cavitation

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

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Authors: Slawomir Wnuk

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Due to widespread implementation of the renewable energy development programs the, solar energy use increasing constantlyacross the world. Accordingly to REN21, in 2020, both on-grid and off-grid solar photovoltaic systems installed capacity reached 760 GWDCand increased by 139 GWDC compared to previous year capacity. However, the photovoltaic solar cells used for primary solar energy conversion into electrical energy has exhibited significant drawbacks. The fundamentaldownside is unstable andlow efficiencythe energy conversion being negatively affected by a rangeof factors. To neutralise or minimise the impact of those factors causing energy losses, researchers have come out withvariedideas. One ofpromising technological solutionsoffered by researchers is PV-MTEG multilayer hybrid system combiningboth photovoltaic cells and thermoelectric generators advantages. A series of experiments was performed on Glasgow Caledonian University laboratory to investigate such a system in operation. In the experiments, the solar simulator Sol3A series was employed as a stable solar irradiation source, and multichannel voltage and temperature data loggers were utilised for measurements. The two layer proposed hybrid systemsimulation model was built up and tested for its energy conversion capability under a variety of the exposure angles to the solar irradiation with a concurrent examination of the temperature distribution inside proposed PV-MTEG structure. The same series of laboratory tests were carried out for a range of various loads, with the temperature and voltage generated being measured and recordedfor each exposure angle and load combination. It was found that increase of the exposure angle of the PV-MTEG structure to an irradiation source causes the decrease of the temperature gradient ΔT between the system layers as well as reduces overall system heating. The temperature gradient’s reduction influences negatively the voltage generation process. The experiments showed that for the exposureangles in the range from 0° to 45°, the ‘generated voltage – exposure angle’ dependence is reflected closely by the linear characteristics. It was also found that the voltage generated by MTEG structures working with the optimal load determined and applied would drop by approximately 0.82% per each 1° degree of the exposure angle increase. This voltage drop occurs at the higher loads applied, getting more steep with increasing the load over the optimal value, however, the difference isn’t significant. Despite of linear character of the generated by MTEG voltage-angle dependence, the temperature reduction between the system structure layers andat tested points on its surface was not linear. In conclusion, the PV-MTEG exposure angle appears to be important parameter affecting efficiency of the energy generation by thermo-electrical generators incorporated inside those hybrid structures. The research revealedgreat potential of the proposed hybrid system. The experiments indicated interesting behaviour of the tested structures, and the results appear to provide valuable contribution into thedevelopment and technological design process for large energy conversion systems utilising similar structural solutions.

Keywords: photovoltaic solar systems, hybrid systems, thermo-electrical generators, renewable energy

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Authors: komal verma, V. S. Moholkar

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In this current study, the challenge of effectively treating and mineralizing industrial wastewater prior to its discharge into natural water bodies, such as rivers and lakes, is being addressed. Particularly, the focus is on the wastewater produced by chemical process industries, including refineries, petrochemicals, fertilizer, pharmaceuticals, pesticides, and dyestuff industries. These wastewaters often contain stubborn organic pollutants that conventional techniques, such as microbial processes cannot efficiently degrade. To tackle this issue, a ternary hybrid technique comprising of adsorption, heterogeneous Fenton process, and sonication has been employed. The study aims to evaluate the effectiveness of this approach for treating and mineralizing wastewater from a fertilizer industry located in Northeast India. The study comprises several key components, starting with the synthesis of the Fe3O4@AC nanocomposite using the co-precipitation method. The nanocomposite is then subjected to comprehensive characterization through various standard techniques, including FTIR, FE-SEM, EDX, TEM, BET surface area analysis, XRD, and magnetic property determination using VSM. Next, the process parameters of wastewater treatment are statistically optimized, focusing on achieving a high level of COD (Chemical Oxygen Demand) removal as the response variable. The Fe3O4@AC nanocomposite's adsorption characteristics and kinetics are also assessed in detail. The remarkable outcome of this study is the successful application of the ternary hybrid technique, combining adsorption, Fenton process, and sonication. This approach proves highly effective, leading to nearly complete mineralization (or TOC removal) of the fertilizer industry wastewater. The results highlight the potential of the Fe3O4@AC nanocomposite and the ternary hybrid technique as a promising solution for tackling challenging wastewater pollutants from various chemical process industries. This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result results from synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Micro-convection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe3O4@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater. The Fe3O4@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: chemical oxygen demand (cod), fe3o4@ac nanocomposite, kinetics, lc-ms, rsm, toxicity

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