Search results for: wireless sensor networks (WSN)

Authors: Virag Vass, Ilona Bereczki, Erzsebet Szabo, Nora Debreczeni, Aniko Borbas, Pal Herczegh, Arpad Tosaki

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Hydrogen sulfide (H₂S) is a toxic gas, but it is produced by certain tissues in a small quantity. According to earlier studies, ibuprofen and H₂S has a protective effect against damaging heart tissue caused by ischemia-reperfusion. Recently, we have been investigating the effect of a new water-soluble H₂S releasing ibuprofen molecule administered after artificially generated ischemia-reperfusion on isolated rat hearts. The H₂S releasing property of the new ibuprofen derivative was investigated in vitro in medium derived from heart endothelial cell isolation at two concentrations. The ex vivo examinations were carried out on rat hearts. Rats were anesthetized with an intraperitoneal injection of ketamine, xylazine, and heparin. After thoracotomy, hearts were excised and placed into ice-cold perfusion buffer. Perfusion of hearts was conducted in Langendorff mode via the cannulated aorta. In our experiments, we studied the dose-effect of the H₂S releasing molecule in Langendorff-perfused hearts with the application of gradually increasing concentration of the compound (0- 20 µM). The H₂S releasing ibuprofen derivative was applied before the ischemia for 10 minutes. H₂S concentration was measured with an H₂S detecting electrochemical sensor from the coronary effluent solution. The 10 µM concentration was chosen for further experiments when the treatment with this solution was occurred after the ischemia. The release of H₂S is occurred by the hydrolyzing enzymes that are present in the heart endothelial cells. The protective effect of the new H₂S releasing ibuprofen molecule can be confirmed by the infarct sizes of hearts using the Triphenyl-tetrazolium chloride (TTC) staining method. Furthermore, we aimed to define the effect of the H₂S releasing ibuprofen derivative on autophagic and apoptotic processes in damaged hearts after investigating the molecular markers of these events by western blotting and immunohistochemistry techniques. Our further studies will include the examination of LC3I/II, p62, Beclin1, caspase-3, and other apoptotic molecules. We hope that confirming the protective effect of new H₂S releasing ibuprofen molecule will open a new possibility for the development of more effective cardioprotective agents with exerting fewer side effects. Acknowledgment: This study was supported by the grants of NKFIH- K-124719 and the European Union and the State of Hungary co- financed by the European Social Fund in the framework of GINOP- 2.3.2-15-2016-00043.

Keywords: autophagy, hydrogen sulfide, ibuprofen, ischemia, reperfusion

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Authors: Omer Burak Iskender, Keck Voon Ling, Vincent Dubanchet, Luca Simonini

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This paper presents Guidance and Control (G&C) strategy to approach and synchronize with potentially rotating targets. The proposed strategy generates and tracks a safe trajectory for space servicing missions, including tasks like approaching, inspecting, and capturing. The main objective of this paper is to validate the G&C laws using a Hardware-In-the-Loop (HIL) setup with realistic rendezvous and docking equipment. Throughout this work, the assumption of full relative state feedback is relaxed by onboard sensors that bring realistic errors and delays and, while the proposed closed loop approach demonstrates the robustness to the above mentioned challenge. Moreover, G&C blocks are unified via the Model Predictive Control (MPC) paradigm, and the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description. In this work, G&C is formulated as a convex optimization problem where constraints such as thruster limits and the output constraints are explicitly handled. Furthermore, the Monte-Carlo method is used to evaluate the robustness of the proposed method to the initial condition errors, the uncertainty of the target's motion and attitude, and actuator errors. A capture scenario is tested with the robotic test bench that has onboard sensors which estimate the position and orientation of a drifting satellite through camera imagery. Finally, the approach is compared with currently used robust H-infinity controllers and guidance profile provided by the industrial partner. The HIL experiments demonstrate that the proposed strategy is a potential candidate for future space servicing missions because 1) the algorithm is real-time implementable as convex programming offers deterministic convergence properties and guarantee finite time solution, 2) critical physical and output constraints are respected, 3) robustness to sensor errors and uncertainties in the system is proven, 4) couples translational motion with rotational motion.

Keywords: dual quaternion, model predictive control, real-time experimental test, rendezvous and docking, spacecraft autonomy, space servicing

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Authors: Amber Brittain-Hale

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This research investigates the evolving role of social media in crisis situations by employing discourse analysis methodology and honing in on the Russo-Ukrainian War, particularly Ukraine's use of LinkedIn. The study posits that social media platforms, such as LinkedIn, play a crucial role in shaping communication, disseminating information, and influencing geopolitical strategies during conflicts. Focusing on Ukraine's official state account on LinkedIn and analyzing its posts and interactions, the research aims to unveil discourse dynamics in high-stakes scenarios and provide valuable insights for leaders navigating complex global challenges. A comprehensive analysis of the data will contribute to a deeper understanding of the tactics adopted by political leaders in managing communication, the bidirectional nature of discourse provided by online social networks, and the rapid advancement of technology that has led to the growing significance of social media platforms in crisis situations. Through this approach, the geopolitical factors that influenced the country's social media strategy during the Russo-Ukrainian War will be illuminated, offering a broader perspective on the role of social media in such challenging times. Ultimately, the study seeks to uncover lessons that can be drawn from Ukraine's LinkedIn approach, informing future strategies for utilizing social media during crises and advancing the understanding of how social media can be harnessed to address intricate global issues.

Keywords: russo-ukrainian war, social media, crisis, discourse analysis

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Authors: Anupam Bhatia

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Upon reviewing the literature and the pragmatic work done in the field of E- textiles, it is observed that the applications of wearable technologies have found a steady growth in the field of military, medical, industrial, sports; whereas fashion is at a loss to know how to treat this technology and bring it to market. The purpose of this paper is to understand the practical issues of integration of electronics in garments; cutting patterns for mass production, maintaining the basic properties of textiles and daily maintenance of garments that hinder the wide adoption of interactive fabric technology within Fashion and leisure wear. To understand the practical hindrances an experimental and laboratory approach is taken. “Techno Meets Fashion” has been an interactive fashion project where sensor technologies have been embedded with textiles that result in set of ensembles that are light emitting garments, sound sensing garments, proximity garments, shape memory garments etc. Smart textiles, especially in the form of textile interfaces, are drastically underused in fashion and other lifestyle product design. Clothing and some other textile products must be washable, which subjects to the interactive elements to water and chemical immersion, physical stress, and extreme temperature. The current state of the art tends to be too fragile for this treatment. The process for mass producing traditional textiles becomes difficult in interactive textiles. As cutting patterns from larger rolls of cloth and sewing them together to make garments breaks and reforms electronic connections in an uncontrolled manner. Because of this, interactive fabric elements are integrated by hand into textiles produced by standard methods. The Arduino has surely made embedding electronics into textiles much easier than before; even then electronics are not integral to the daily wear garments. Soft and flexible interfaces of MEMS (micro sensors and Micro actuators) can be an option to make this possible by blending electronics within E-textiles in a way that’s seamless and still retains functions of the circuits as well as the garment. Smart clothes, which offer simultaneously a challenging design and utility value, can be only mass produced if the demands of the body are taken care of i.e. protection, anthropometry, ergonomics of human movement, thermo- physiological regulation.

Keywords: ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology

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Authors: Sara Chinnasamy, Michelle Gun, M. Adnan Hashim

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Federal Constitution guarantees Malaysians the right to free speech and expression; yet hatred speech can be commonly found on social media platforms such as Facebook, Twitter, and Instagram. In Malaysia social media sphere, most hatred speech involves religion, race and politics. Recent cases of racial attacks on social media have created social tensions among Malaysians. Many Malaysians always argue on their rights to freedom of speech. However, there are laws that limit their expression to the public and protecting social media users from being a victim of hate speech. This paper aims to explore the attitude and involvement of Malaysian netizens towards freedom of speech and hatred speech on social media. It also examines the relationship between involvement in hatred speech among Malaysian netizens and attitude towards freedom of speech. For most Malaysians, practicing total freedom of speech in the open is unthinkable. As a result, the best channel to articulate their feelings and opinions liberally is the internet. With the advent of the internet medium, more and more Malaysians are conveying their viewpoints using the various internet channels although sensitivity of the audience is seldom taken into account. Consequently, this situation has led to pockets of social disharmony among the citizens. Although this unhealthy activity is denounced by the authority, netizens are generally of the view that they have the right to write anything they want. Using the quantitative method, survey was conducted among Malaysians aged between 18 and 50 years who are active social media users. Results from the survey reveal that despite a weak relationship level between hatred speech involvement on social media and attitude towards freedom of speech, the association is still considerably significant. As such, it can be safely presumed that hatred speech on social media occurs due to the freedom of speech that exists by way of social media channels.

Keywords: freedom of speech, hatred speech, social media, Malaysia, netizens

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Authors: Ayman M. Othman, Hassan Y. Ahmed, Tallat A. Ali

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Inadequate maintenance programs and funds allocated for highway networks in the developed countries have led to fast deterioration of road side elements. Therefore, this research focuses on developing a performance model for road side elements periodic maintenance activities. Road side elements that receive periodic maintenance include; earthen shoulder, road signs and traffic markings. Using the level of service concept, the developed model can determine the optimal periodic maintenance intervals for those elements based on a selected level of service suitable with the available periodic maintenance budget. Data related to time periods for progressive deterioration stages for the chosen elements were collected. Ten maintenance experts in Aswan, Sohag and Assiut cities were interviewed for that purpose. Time in months related to 10%, 25%, 40%, 50%, 75%, 90% and 100% deterioration of each road side element was estimated based on the experts opinion. Least square regression analysis has shown that a power function represents the best fit for earthen shoulders edge drop-off and damage of road signs with time. It was also evident that, the progressive dirtiness of road signs could be represented by a quadratic function an a linear function could represent the paint degradation nature of both traffic markings and road signs. Actual measurements of earthen shoulder edge drop-off agree considerably with the developed model.

Keywords: deterioration, level of service, periodic maintenance, performance model, road side element

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Authors: Ande Nesmith

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There is an ongoing shortage of foster parents worldwide to take on a growing population of children in need of out-of-home care. Currently, resources are primarily aimed at recruitment rather than retention. Retention rates are extraordinarily low, especially in the first two years of fostering. Qualitative interviews with 19 foster parents averaging 20 years of service provided insight into the challenges they faced and how they overcame them. Thematic analysis of interview transcripts identified sources of stress and resiliency. Key stressors included lack of support and responsiveness from the children’s social workers, false maltreatment allegations, and secondary trauma from children’s destructive behaviors and emotional dysregulation. Resilient parents connected with other foster parents for support, engaged in creative problem-solving, recognized that positive feedback from children usually arrives years later, and through training, understood the neurobiological impact of trauma on child behavior. Recommendations include coordinating communication between the foster parent licensing agency social workers and the children’s social workers, creating foster parent support networks and mentoring, and continuous training on trauma including effective parenting strategies. Research is needed to determine whether these resilience indicators in fact lead to long-term retention. Policies should include a mechanism to develop a cohesive line of communication and connection between foster parents and the children’s social workers as well as their respective agencies.

Keywords: foster care stability, foster parent burnout, foster parent resiliency, foster parent retention, trauma-informed fostering

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Authors: Daniel S. Gamba, Marc Sánchez, Javier Pérez, Juan J. Castillo, Juan A. Cabrera

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The conventional hydraulic braking system operates through the activation of a master cylinder and solenoid valves that distribute and regulate brake fluid flow, adjusting the pressure at each wheel to prevent locking during sudden braking. However, in recent years, there has been a significant increase in the integration of electronic units into various vehicle control systems. In this context, one of the technologies most recently researched is the Brake-by-wire system, which combines electronic, hydraulic, and mechanical technologies to manage braking. This proposal introduces the design and control of a Brake-by-wire system, which will be part of a fully electric and teleoperated vehicle. This vehicle will have independent four-wheel drive, braking, and steering systems. The vehicle will be operated by embedded controllers programmed into a Speedgoat test system, which allows programming through Simulink and real-time capabilities. The braking system comprises all mechanical and electrical components, a vehicle control unit (VCU), and an electronic control unit (ECU). The mechanical and electrical components include a permanent magnet synchronous motor from Odrive and its inverter, the mechanical transmission system responsible for converting torque into pressure, and the hydraulic system that transmits this pressure to the brake caliper. The VCU is responsible for controlling the pressure and communicates with the other components through the CAN protocol, minimizing response times. The ECU, in turn, transmits the information obtained by a sensor installed in the caliper to the central computer, enabling the control loop to continuously regulate pressure by controlling the motor's speed and current. To achieve this, tree controllers are used, operating in a nested configuration for effective control. Since the computer allows programming in Simulink, a digital model of the braking system has been developed in Simscape, which makes it possible to reproduce different operating conditions, faithfully simulate the performance of alternative brake control systems, and compare the results with data obtained in various real tests. These tests involve evaluating the system's response to sinusoidal and square wave inputs at different frequencies, with the results compared to those obtained from conventional braking systems.

Keywords: braking, CAN protocol, permanent magnet motor, pressure control

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Authors: Rohit Dey, Sailendra Karra

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This paper aims at solving the problem of multi-target searching in a Global Positioning System (GPS) denied environment using swarm robots with limited sensing and communication abilities. Typically, existing swarm-based search algorithms rely on the presence of a global coordinate system (vis-à-vis, GPS) that is shared by the entire swarm which, in turn, limits its application in a real-world scenario. This can be attributed to the fact that robots in a swarm need to share information among themselves regarding their location and signal from targets to decide their future course of action but this information is only meaningful when they all share the same coordinate frame. The paper addresses this very issue by eliminating any dependency of a search algorithm on the need of a predetermined global coordinate frame by the unification of the relative coordinate of individual robots when within the communication range, therefore, making the system more robust in real scenarios. Our algorithm assumes that all the robots in the swarm are equipped with range and bearing sensors and have limited sensing range and communication abilities. Initially, every robot maintains their relative coordinate frame and follow Levy walk random exploration until they come in range with other robots. When two or more robots are within communication range, they share sensor information and their location w.r.t. their coordinate frames based on which we unify their coordinate frames. Now they can share information about the areas that were already explored, information about the surroundings, and target signal from their location to make decisions about their future movement based on the search algorithm. During the process of exploration, there can be several small groups of robots having their own coordinate systems but eventually, it is expected for all the robots to be under one global coordinate frame where they can communicate information on the exploration area following swarm search techniques. Using the proposed method, swarm-based search algorithms can work in a real-world scenario without GPS and any initial information about the size and shape of the environment. Initial simulation results show that running our modified-Particle Swarm Optimization (PSO) without global information we can still achieve the desired results that are comparable to basic PSO working with GPS. In the full paper, we plan on doing the comparison study between different strategies to unify the coordinate system and to implement them on other bio-inspired algorithms, to work in GPS denied environment.

Keywords: bio-inspired search algorithms, decentralized control, GPS denied environment, swarm robotics, target searching, unifying coordinate systems

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Authors: Chyuan Haur Kao, Hsiang Chen, Yu Sheng Tsai, Chen Hao Hung, Yu Shan Lee

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Dielectric electrolyte-insulator-semiconductor sensing membranes-based biosensors have been intensively investigated because of their simple fabrication, low cost, and fast response. However, to enhance their sensing performance, it is worthwhile to explore alternative materials, distinct processes, and novel treatments. An ISFET can be viewed as a variation of MOSFET with the dielectric oxide layer as the sensing membrane. Then, modulation on the work function of the gate caused by electrolytes in various ion concentrations could be used to calculate the ion concentrations. Recently, owing to the advancement of CMOS technology, some high dielectric materials substrates as the sensing membranes of electrolyte-insulator-semiconductor (EIS) structures. The EIS with a stacked-layer of SiO₂ layer between the sensing membrane and the silicon substrate exhibited a high pH sensitivity and good long-term stability. IGZO is a wide-bandgap (~3.15eV) semiconductor of the III-VI semiconductor group with several preferable properties, including good transparency, high electron mobility, wide band gap, and comparable with CMOS technology. IGZO was sputtered by reactive radio frequency (RF) on a p-type silicon wafer with various gas ratios of Ar:O₂ and was treated with rapid thermal annealing in O₂ ambient. The sensing performance, including sensitivity, hysteresis, and drift rate was measured and XRD, XPS, and AFM analyses were also used to study the material properties of the IGZO membrane. Moreover, IGZO was used as a sensing membrane in dielectric EIS bio-sensor structures. In addition to traditional pH sensing capability, detection for concentrations of Na+, K+, urea, glucose, and creatinine was performed. Moreover, post rapid thermal annealing (RTA) treatment was confirmed to improve the material properties and enhance the multi-analyte sensing capability for various ions or chemicals in solutions. In this study, the IGZO sensing membrane with annealing in O₂ ambient exhibited a higher sensitivity, higher linearity, higher H+ selectivity, lower hysteresis voltage and lower drift rate. Results indicate that the IGZO dielectric sensing membrane on the EIS structure is promising for future bio-medical device applications.

Keywords: dielectric sensing membrane, IGZO, hydrogen ion, plasma, rapid thermal annealing

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Authors: L. Freeborn

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Recent years have seen an increasing number of neuroimaging studies related to language learning as imaging techniques such as fMRI and EEG have become more widely accessible to researchers. By using a variety of structural and functional neuroimaging techniques, these studies have already made considerable progress in terms of our understanding of neural networks and processing related to first and second language acquisition. However, the methodological designs employed in neuroimaging studies to test language learning have been questioned by applied linguists working within the field of second language acquisition (SLA). One of the major criticisms is that tasks designed to measure language learning gains rarely have a communicative function, and seldom assess learners’ ability to use the language in authentic situations. This brings the validity of many neuroimaging tasks into question. The fundamental reason why people learn a language is to communicate, and it is well-known that both first and second language proficiency are developed through meaningful social interaction. With this in mind, the SLA field is in agreement that second language acquisition and proficiency should be measured through learners’ ability to communicate in authentic real-life situations. Whilst authenticity is not always possible to achieve in a classroom environment, the importance of task authenticity should be reflected in the design of language assessments, teaching materials, and curricula. Tasks that bear little relation to how language is used in real-life situations can be considered to lack construct validity. This paper first describes the typical tasks used in neuroimaging studies to measure language gains and proficiency, then analyses to what extent these tasks can validly assess these constructs.

Keywords: neuroimaging studies, research design, second language acquisition, task validity

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Authors: Deepak Khare, Radha Krishan, Bhaskar Nikam

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The present study deals with the results of the Ortho-rectified Cartosat-1 PAN (2.5 m resolution) satellite data analysis for the extraction of canal networks under the Eastern Ganga Canal (EGC) command. Based on the information derived through the remote sensing data, in terms of the number of canals, their physical status and hydraulic connectivity from the source, irrigation potential (IP) created in the command was assessed by comparing with planned/design canal-wise irrigation potentials. All the geospatial information generated in the study is organized in a geodatabase. The EGC project irrigates the command through one main canal, five branch canals, 36 distributaries and 186 minors. The study was conducted with the main objectives of inventory and mapping of irrigation infrastructure using geographic information system (GIS), remote sensing and field data. Likewise, the assessment of irrigation potential created using the mapped infrastructure was performed as on March 2017. Results revealed that the canals were not only pending but were also having gap/s, and hydraulically disconnected in each branch canal and also in minors of EGC. A total of 16622.3 ha of commands were left untouched with canal water just due to the presence of gaps in the EGC project. The sum of all the gaps present in minor canals was 11.92 km, while in distributary, it was 2.63 km. This is a very good scenario that balances IP can be achieved by working on the gaps present in minor canals. Filling the gaps in minor canals can bring most of the area under irrigation, especially the tail reaches command.

Keywords: canal command, GIS, hydraulic connectivity, irrigation potential

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Mohamed Rehan, Gamil E. Ibrahim, Mohamed S. Abdel-Aziz, Shaimaa R. Ibrahim, Tawfik A. Khattab

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The utilization of natural products in finishing textiles toward multifunctional applications without side effects is an extremely motivating goal. Hibiscus sabdariffa usually has been used for many traditional medicine applications. To develop an additional use for Hibiscus sabdariffa, an extraction of bioactive compounds from Hibiscus sabdariffa followed by finishing on cellulosic fibers was designed to cleaner production of the value-added textiles fibers with multifunctional applications. The objective of this study is to explore, identify, and evaluate the bioactive compound extracted from Hibiscus sabdariffa by different solvent via ultrasonic technique as a potential eco-friendly agent for multifunctional cellulosic fabrics via two approaches. In the first approach, Hibiscus sabdariffa extract was used as a source of sustainable eco-friendly for simultaneous coloration and multi-finishing of cotton fabrics via in situ incorporations of nanoparticles (silver and metal oxide). In the second approach, the micro-capsulation of Hibiscus sabdariffa extracts was followed by coating onto cotton gauze to introduce multifunctional healthcare applications. The effect of the solvent type was accelerated by ultrasonic on the phytochemical, antioxidant, and volatile compounds of Hibiscus sabdariffa. The surface morphology and elemental content of the treated fabrics were explored using Fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), and energy-dispersive X-ray spectroscopy (EDX). The multifunctional properties of treated fabrics, including coloration, sensor properties and protective properties against pathogenic microorganisms and UV radiation as well as wound healing property were evaluated. The results showed that the water, as well as ethanol/water, was selected as a solvent for the extraction of natural compounds from Hibiscus Sabdariffa with high in extract yield, total phenolic contents, flavonoid contents, and antioxidant activity. These natural compounds were utilized to enhance cellulosic fibers functionalization by imparting faint/dark red color, antimicrobial against different organisms, and antioxidants as well as UV protection properties. The encapsulation of Hibiscus Sabdariffa extracts, as well as wound healing, is under consideration and evaluation. As a result, the current study presents a sustainable and eco-friendly approach to design cellulosic fabrics for multifunctional medical and healthcare applications.

Keywords: cellulosic fibers, Hibiscus sabdariffa extract, multifunctional application, nanoparticles

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Authors: Abdulqader Alkhouzaam, Hazim Qiblawey, Majeda Khraisheh

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Membrane treatment for desalination and wastewater treatment is one of the promising solutions to affordable clean water. It is a developing technology throughout the world and considered as the most effective and economical method available. However, the limitations of membranes’ mechanical and chemical properties restrict their industrial applications. Hence, developing novel membranes was the focus of most studies in the water treatment and desalination sector to find new materials that can improve the separation efficiency while reducing membrane fouling, which is the most important challenge in this field. Graphene oxide (GO) is one of the materials that have been recently investigated in the membrane water treatment sector. In this work, ultrafiltration polysulfone (PSF) membranes with high antifouling properties were synthesized by incorporating different loadings of GO. High-oxidation degree GO had been synthesized using a modified Hummers' method. The synthesized GO was characterized using different analytical techniques including elemental analysis, Fourier transform infrared spectroscopy - universal attenuated total reflectance sensor (FTIR-UATR), Raman spectroscopy, and CHNSO elemental analysis. CHNSO analysis showed a high oxidation degree of GO represented by its oxygen content (50 wt.%). Then, ultrafiltration PSF membranes incorporating GO were fabricated using the phase inversion technique. The prepared membranes were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM) and showed a clear effect of GO on PSF physical structure and morphology. The water contact angle of the membranes was measured and showed better hydrophilicity of GO membranes compared to pure PSF caused by the hydrophilic nature of GO. Separation properties of the prepared membranes were investigated using a cross-flow membrane system. Antifouling properties were studied using bovine serum albumin (BSA) and humic acid (HA) as model foulants. It has been found that GO-based membranes exhibit higher antifouling properties compared to pure PSF. When using BSA, the flux recovery ratio (FRR %) increased from 65.4 ± 0.9 % for pure PSF to 84.0 ± 1.0 % with a loading of 0.05 wt.% GO in PSF. When using HA as model foulant, FRR increased from 87.8 ± 0.6 % to 93.1 ± 1.1 % with 0.02 wt.% of GO in PSF. The pure water permeability (PWP) decreased with loadings of GO from 181.7 L.m⁻².h⁻¹.bar⁻¹ of pure PSF to 181.1, and 157.6 L.m⁻².h⁻¹.bar⁻¹ with 0.02 and 0.05 wt.% GO respectively. It can be concluded from the obtained results that incorporating low loading of GO could enhance the antifouling properties of PSF hence improving its lifetime and reuse.

Keywords: antifouling properties, GO based membranes, hydrophilicity, polysulfone, ultrafiltration

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Elizelle Juaneé Cilliers

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The green hype is becoming stronger within various disciplines, modern practices and academic thinking, enforced by concepts such as eco-health, eco-tourism, eco-cities, and eco-engineering. There is currently also an expanded scientific understanding regarding the value and benefits relating to green infrastructure, for both communities and their host cities, linked to broader sustainability and resilience thinking. The integration and implementation of green infrastructure as part of spatial planning approaches and municipal planning, are, however, more complex, especially in South Africa, inflated by limitations of budgets and human resources, development pressures, inequities in terms of green space availability and political legacies of the past. The prevailing approach to spatial planning is further contributing to complexity, linked to misguided perceptions of the function and value of green infrastructure. As such, green spaces are often considered a luxury, and green infrastructure a costly alternative, resulting in green networks being susceptible to land-use changes and under-prioritized in local authority decision-making. Spatial planning, in this sense, may well be a valuable tool to realise the green agenda, encapsulating various initiatives of sustainability as provided by a range of disciplines. This paper aims to clarify the importance and value of green infrastructure planning as a component of spatial planning approaches, in order to inform and encourage local authorities to embed sustainability thinking into city planning and decision-making approaches. It reflects on the decisive role of land-use management to guide the green agenda and refers to some recent planning initiatives. Lastly, it calls for trans-disciplinary planning approaches to build a case towards green(er) cities.

Keywords: green infrastructure, spatial planning, transdisciplinary, integrative

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Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

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Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

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Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

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Authors: Gaurav Kumar Sinha

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The oil and gas industry is a critical component of the global economy, relying heavily on industrial control systems (ICS) to manage and monitor operations. However, these systems are increasingly becoming targets for cyber-attacks, posing significant risks to operational continuity, safety, and environmental integrity. This paper explores comprehensive cybersecurity strategies for protecting oil and gas industrial control systems. It delves into the unique vulnerabilities of ICS in this sector, including outdated legacy systems, integration with IT networks, and the increased connectivity brought by the Industrial Internet of Things (IIoT). We propose a multi-layered defense approach that includes the implementation of robust network security protocols, regular system updates and patch management, advanced threat detection and response mechanisms, and stringent access control measures. We illustrate the effectiveness of these strategies in mitigating cyber risks and ensuring the resilient and secure operation of oil and gas industrial control systems. The findings underscore the necessity for a proactive and adaptive cybersecurity framework to safeguard critical infrastructure in the face of evolving cyber threats.

Keywords: cybersecurity, industrial control systems, oil and gas, cyber-attacks, network security, IoT, threat detection, system updates, patch management, access control, cybersecurity awareness, critical infrastructure, resilience, cyber threats, legacy systems, IT integration, multi-layered defense, operational continuity, safety, environmental integrity

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Authors: Fariba Ebrahimi, Mehdi Ghorbani

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Comprehensive water management considers economic, environmental, technical and social sustainability of water resources for future generations. Integrated water management implies cooperative approach and involves all stakeholders and also introduces issues to managers and decision makers. Solving these issues needs integrated and system approach according to the recognition of actors or key persons in necessary to apply cooperative management of water resources. Therefore, social network analysis can be used to demonstrate the most effective actors for environmental base decisions. The linkage of diverse sets of actors and knowledge systems across management levels and institutional boundaries often poses one of the greatest challenges in adaptive water management. Bridging stakeholder can facilitate interactions among actors in management settings by lowering the transaction costs of collaboration. This research examines how network connections between group members affect in co- management. Cohesive network structures allow groups to more effectively achieve their goals and objectives Strong; centralized leadership is a better predictor of working group success in achieving goals and objectives. Finally, geometric position of each actor was illustrated in the network. The results of the research based on between centrality index have a key and bridging actor in recognition of cooperative management of water resources in Darbandsar village and also will help managers and planners of water in the case of recognition to organization and implementation of sustainable management of water resources and water security.

Keywords: co-management, water management, social network, bridging stakeholder, darbandsar village

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Authors: Leo Latasch, Mario Di Gennaro

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Introduction: The goal of this project was to increase the resilience of the population as well as rescue organizations to make both quality and time-related improvements in handling crises. A helper network was created for this purpose. Methods: Social questions regarding the structure and purpose of helper networks were considered - specifically with regard to helper motivation, the level of commitment and collaboration between populations and agencies. The exchange of information, the coordinated use of volunteers, and the distribution of available resources will be ensured through defined communication and cooperation routines. Helper smartphones will also be used provide a picture of the situation on the ground. Results: The helper network was established and deployed based on the RESIBES information technology system. It consists of a service platform, a web portal and a smartphone app. The service platform is the central element for collaboration between the various rescue organizations, as well as for persons, associations, and companies from the population offering voluntary aid. The platform was used for: Registering helpers and resources and then requesting and assigning it in case of a disaster. These services allow the population's resources to be organized. The service platform also allows for a secure data exchange between services and external systems. Conclusions: The social and technical work priorities have allowed us to cover a full cycle of advance structural work, gaining an overview, damage management, evaluation, and feedback on experiences. This cycle allows experiences gained while handling the crisis to feed back into the cycle and improve preparations and management strategies.

Keywords: coordination, disaster, resilience, volunteers

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Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

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Authors: Zahra Tork

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Before the spread of the Internet and the use of mobile phones, women were generally far from society and many restrictions were applied to them, but after the spread of the Internet and the cultural and social changes brought about by it, women in society got a new one and many restrictions regarding them disappeared; As we can see today, many women, like men, have a high social base, they earn for themselves, they can travel alone, stay out late at night, take personal and family photos or videos on virtual pages. Publish themselves (while before this, showing or publishing photos of women was considered dishonorable or indecent). In this article, an attempt is made to examine the effect of the internet on mobile phones and virtual social networks in changing beliefs, norms and social values and their relationship with the social mobility of women and the effect of these factors on social and human development be paid. For this reason, social and human development is discussed first, and then the role of the media in development is explained, and finally, the social mobility of women is discussed. Since the purpose of this study is to better understand the social mobility of Iranian women through the development of the Internet in mobile phones, a qualitative study using focus groups has been adopted. The results of this research indicated that the Internet has caused changes in the value and cultural system of the Iranian people, and women have also redefined their roles and identity. In this new definition, many of the past restrictions have disappeared and women have gained the same freedoms as men. Finally, these factors (change in values and norms and redefinition of the role of women) joined hands and caused the social mobility of women in Iran.

Keywords: development of communication in Iran, development of mobile phones, development of the Internet, women's social group, social mobility

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Lopamudra Bakshi Basu

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Transport is one of the most important characteristic features of Indian cities. The physical and societal requirements determine the selection of a particular transport system along with the uniqueness of road networks. Kolkata has a mixed traffic of which Paratransit system plays a crucial role. It is an indispensable transport system in Kolkata mainly because of its size and service flexibility which has led to a unique network character. The paratransit system, mainly the autorickshaws, is the most favoured mode of transport in the city. Its fast movement and comfortability make it a vital transport system of the city. Since the inception of the autorickshaws in Kolkata in 1981, this mode has gained popularity and presently serves nearly 80 to 90 percent of the total passenger trips. This employment generating mode of transport has increased its number rapidly affecting the city’s traffic. Minimal check on their growth by the authority has led to traffic snarls along many streets of Kolkata. Indiscipline behavior, violation of traffic rules and rash driving make situations even worse. The rise in the number and increasing popularity of the autorickshaws make it an interesting study area. Autorickshaws as a paratransit mode play its role as a leader or a follower. However, it is informal in its planning and operations, which makes it a problem area for the city. The entire research work deals with the growth and expansion of the number of vehicles and the routes within the city. The development of transport system has been interesting in the city, which has been studied. The growth of the paratransit modes in the city has been rapid. The network pattern of the paratransit mode within Kolkata has been analysed.

Keywords: growth, informal, network characteristics, paratransit, service flexibility

Procedia PDF Downloads 238

Authors: Banu Karasah, Derya Sarı

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Nature changes as a result of human necessities constantly. This change mostly feels in natural water sources which are reconstructed with an effect of dams and motorways. On the other hand, dams and motorways demolish and re-shape nature while the visual quality of landscape gets a new character. Changing and specialization new landscapes will be very important to protection-usage balance to explore sustainable usage facilities. The main cause of the selection of Artvin city is, it has very important geographical location and one of the most attraction points in the World with its biodiversity, conservation areas and natural landscape characteristics. Coruh River is one of the most significant landscape identity element of Artvin. This river begins with Erzurum and falls into the Black Sea in Batumi in Georgia, many dams, and hydroelectric station are located during this basin. Borcka, Muratli and Deriner dams have already been built. Moreover, Deriner is 6th highest dams all over the world. As a result of dams, motorways route were re-shaped and the ways which have already changed because of elevation is directly affected several of natural destruction. In contrast, many different reservoirs in Coruh Basin provide new vista point that has high visual quality. In this study, we would like to evaluate with sustainable landscape design in 76 km river corridor, which is mainly based on Deriner, Borcka and Muratli Dams and determination of their basin-lakes recreational potential and opportunities. Lastly, we are going to give some suggestion about the potential of the corridor.

Keywords: Artvin, dam reservoirs, landscape assessment, river corridor, visual quality

Procedia PDF Downloads 529

Authors: Eğinç Simay Ertürk, Ferhan Gezi̇ci̇

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The decline of large cities and the rise of second-tier cities have been observed as a global trend with significant implications for economic development and urban planning. In this context, the concepts of agglomeration shadow and borrowed size have gained importance as network externalities that affect the growth and development of surrounding areas. Istanbul, Izmir, and Ankara are Turkey's most significant metropolitan cities and play a significant role in the country's economy. The surrounding cities rely on these metropolitan cities for economic growth and development. However, the concentration of resources and investment in a single location can lead to agglomeration shadows in the surrounding areas. On the other hand, network connectivity between metropolitan and second-tier cities can result in borrowed function and performance, enabling smaller cities to access resources, investment, and knowledge they would not otherwise have access. The study hypothesizes that the network connectivity between second-tier and metropolitan cities in Turkey enables second-tier cities to increase their urban performance by borrowing size through these networks. Regression analysis will be used to identify specific network connectivity parameters most strongly associated with urban performance. Network connectivity will be measured with parameters such as transportation nodes and telecommunications infrastructure, and urban performance will be measured with an index, including parameters such as employment, education, and industry entrepreneurship, with data at the province levels. The contribution of the study lies in its research on how networking can benefit second-tier cities in Turkey.

Keywords: network connectivity, borrowed size, agglomeration shadow, secondary cities

Procedia PDF Downloads 81