Search results for: mobile Ad Hoc networks

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: Pakinee Pooprasert, Wanxin Wang, Tina Parmar, Dana Ahnood, Tafadzwa Young-Zvandasara, James Morgan

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Homelessness has been shown to be correlated to poor health outcomes, including increased visual health morbidity. Despite this, there are relatively few studies regarding visual health in the homeless population, especially in the UK. This research aims to investigate visual disability and access barriers prevalent in the homeless population in Cardiff, South Wales. Data was collected from 100 homeless participants in three different shelters. Visual outcomes included near and distance visual acuity as well as non-cycloplegic refraction. Qualitative data was collected via a questionnaire and included socio-demographic profile, ocular history, subjective visual acuity and level of access to healthcare facilities. Based on the participants’ presenting visual acuity, the total prevalence of myopia and hyperopia was 17.0% and 19.0% respectively based on spherical equivalent from the eye with the greatest absolute value. The prevalence of astigmatism was 8.0%. The mean absolute spherical equivalent was 0.841D and 0.853D for right and left eye respectively. The number of participants with sight loss (as defined by VA= 6/12-6/60 in the better-seeing eye) was 27.0% in comparison to 0.89% and 1.1% in the general Cardiff and Wales population respectively (p-value is < 0.05). Additionally, 1.0% of the homeless subjects were registered blind (VA less than 3/60), in comparison to 0.17% for the national consensus after age standardization. Most participants had good knowledge regarding access to prescription glasses and eye examination services. Despite this, 85.0% never had their eyes examined by a doctor and 73.0% had their last optometrist appointment in more than 5 years. These findings suggested that there was a significant disparity in ocular health, including visual acuity and refractive error amongst the homeless in comparison to the general population. Further, the homeless were less likely to receive the same level of support and continued care in the community due to access barriers. These included a number of socio-economic factors such as travel expenses and regional availability of services, as well as administrative shortcomings. In conclusion, this research demonstrated unmet visual health needs within the homeless, and that inclusive policy changes may need to be implemented for better healthcare outcomes within this marginalized community.

Keywords: homelessness, refractive error, visual disability, Wales

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Authors: Alexander García Mariaca, Rodrigo Morillo Castaño, Juan Rolón Ríos

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The government of Colombia has promoted the use of biofuels in the last 20 years through laws and resolutions, which regulate their use, with the objective to improve the atmospheric air quality and to promote Colombian agricultural industry. However, despite the use of blends of biofuels with fossil fuels, the air quality in large cities does not get better, this deterioration in the air is mainly caused by mobile sources that working with spark ignition internal combustion engines (SI-ICE), operating with a mixture in volume of 90 % gasoline and 10 % ethanol called E10, that for the case of Bogota represent 84 % of the fleet. Another problem is that Colombia has big cities located above 2200 masl and there are no accurate studies on the impact that the E10 mixture could cause in the emissions and performance of SI-ICE. This study aims to establish the optimal blend between gasoline ethanol in which an SI engine operates more efficiently in urban centres located at 2600 masl. The test was developed on SI engine four-stroke, single cylinder, naturally aspirated and with carburettor for the fuel supply using blends of gasoline and anhydrous ethanol in different ratios E10, E15, E20, E40, E60, E85 and E100. These tests were conducted in the city of Bogota, which is located at 2600 masl, with the engine operating at 3600 rpm and at 25, 50, 75 and 100% of load. The results show that the performance variables as engine brake torque, brake power and brake thermal efficiency decrease, while brake specific fuel consumption increases with the rise in the percentage of ethanol in the mixture. On the other hand, the specific emissions of CO2 and NOx present increases while specific emissions of CO and HC decreases compared to those produced by gasoline. From the tests, it is concluded that the SI-ICE worked more efficiently with the E40 mixture, where was obtained an increases of the brake power of 8.81 % and a reduction on brake specific fuel consumption of 2.5 %, coupled with a reduction in the specific emissions of CO2, HC and CO in 9.72, 52.88 and 76.66 % respectively compared to the results obtained with the E10 blend. This behaviour is because the E40 mixture provides the appropriate amount of the oxygen for the combustion process, which leads to better utilization of available energy in this process, thus generating a comparable power output to the E10 mixing and producing lower emissions CO and HC with the other test blends. Nevertheless, the emission of NOx increases in 106.25 %.

Keywords: emissions, ethanol, gasoline, engine, performance

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Authors: Enes Caliskan, Hatice Camgoz Akdag

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There is no doubt that humanity needs to realize the sustainability problems in the world and take serious action regarding that. All members of the United Nations adopted the 2030 Agenda for Sustainable Development, the most comprehensive study on sustainability internationally, in 2015. The summary of the study is 17 sustainable development goals. It covers everything about sustainability, such as environment, society and governance. The use of Information and Communication Technology (ICT), such as the Internet, mobile phones, and satellites, is essential for tackling the main issues facing sustainable development. Hence, the contributions of 3 major ICT companies to the sustainable development goals are assessed in this study. Quality Function Deployment (QFD) is utilized as a methodology for this study. Since QFD is an excellent instrument for comparing businesses on relevant subjects, a House of Quality must be established to complete the QFD application. In order to develop a House of Quality, the demanded qualities (voice of the customer) and quality characteristics (technical requirements) must first be determined. UN SDGs are used as demanded qualities. Quality characteristics are derived from annual sustainability and corporate social responsibility reports of ICT companies. The companies' efforts, as indicated by the QFD results, are concentrated on the use of recycled raw materials and recycling, reducing GHG emissions through energy saving and improved connectivity, decarbonizing the value chain, protecting the environment and water resources by collaborating with businesses that have completed CDP water assessments and paying attention to reducing water consumption, ethical business practices, and reducing inequality. The evaluations of the three businesses are found to be very similar when they are compared. The small differences between the companies are usually about the region they serve. Efforts made by the companies mostly concentrate on responsible consumption and production, life below water, climate action, and sustainable cities and community goals. These efforts include improving connectivity in needed areas for providing access to information, education and healthcare.

Keywords: multi-criteria decision-making, sustainable supply chain risk, supply chain agility, quality function deployment, Sustainable development goals

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Authors: K. Eryilmaz, G. Mercanoglu

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Aim: Purification of the final product, which is the last step in the synthesis of lanthanide-labeled peptide compounds, can be accomplished by different methods. Among these methods, the two most commonly used methods are C18 solid phase extraction (SPE) and weak cation exchanger cartridge elution. SPE C18 solid phase extraction method yields high purity final product, while elution from the weak cation exchanger cartridge is pH dependent and ineffective in removing colloidal impurities. The aim of this work is to develop an additional purification method for the lanthanide-labeled peptide compound in cases where the desired radionuclidic and radiochemical purity of the final product can not be achieved because of pH problem or colloidal impurity. Material and Methods: For colloidal impurity formation, 3 mL of water for injection (WFI) was added to 30 mCi of 177LuCl3 solution and allowed to stand for 1 day. 177Lu-DOTATATE was synthesized using EZAG ML-EAZY module (10 mCi/mL). After synthesis, the final product was mixed with the colloidal impurity solution (total volume:13 mL, total activity: 40 mCi). The resulting mixture was trapped in SPE-C18 cartridge. The cartridge was washed with 10 ml saline to remove impurities to the waste vial. The product trapped in the cartridge was eluted with 2 ml of 50% ethanol and collected to the final product vial via passing through a 0.22μm filter. The final product was diluted with 10 mL of saline. Radiochemical purity before and after purification was analysed by HPLC method. (column: ACE C18-100A. 3µm. 150 x 3.0mm, mobile phase: Water-Acetonitrile-Trifluoro acetic acid (75:25:1), flow rate: 0.6 mL/min). Results: UV and radioactivity detector results in HPLC analysis showed that colloidal impurities were completely removed from the 177Lu-DOTATATE/ colloidal impurity mixture by purification method. Conclusion: The improved purification method can be used as an additional method to remove impurities that may result from the lanthanide-peptide synthesis in which the weak cation exchange purification technique is used as the last step. The purification of the final product and the GMP compliance (the final aseptic filtration and the sterile disposable system components) are two major advantages.

Keywords: lanthanide, peptide, labeling, purification, radionuclide, radiopharmaceutical, synthesis

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Authors: Sanjay Dhiraaj, Puneet Goyal, Aditya Kapoor, Gaurav Misra

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In electrocardiography, an ECG artefact is used to indicate something that is not heart-made. Although technological advancements have produced monitors with the potential of providing accurate information and reliable heart rate alarms, despite this, interference of the displayed electrocardiogram still occurs. These interferences can be from the various electrical gadgets present in the operating room or electrical signals from other parts of the body. Artefacts may also occur due to poor electrode contact with the body or due to machine malfunction. Knowing these artefacts is of utmost importance so as to avoid unnecessary and unwarranted diagnostic as well as interventional procedures. We report a case of ECG artefacts occurring due to patient warming blanket and its consequences. A 20-year-old male with a preoperative diagnosis of exstrophy epispadias complex was posted for surgery under epidural and general anaesthesia. Just after endotracheal intubation, we observed nonspecific ECG changes on the monitor. At a first glance, the monitor strip revealed broad QRs complexes suggesting a ventricular bigeminal rhythm. Closer analysis revealed these to be artefacts because although the complexes were looking broad on the first glance there was clear presence of normal sinus complexes which were immediately followed by 'broad complexes' or artefacts produced by some device or connection. These broad complexes were labeled as artefacts as they were originating in the absolute refractory period of the previous normal sinus beat. It would be physiologically impossible for the myocardium to depolarize so rapidly as to produce a second QRS complex. A search for the possible reason for the artefacts was made and after deepening the plane of anaesthesia, ruling out any possible electrolyte abnormalities, checking of ECG leads and its connections, changing monitors, checking all other monitoring connections, checking for proper grounding of anaesthesia machine and OT table, we found that after switching off the patient’s warming apparatus the rhythm returned to a normal sinus one and the 'broad complexes' or artefacts disappeared. As misdiagnosis of ECG artefacts may subject patients to unnecessary diagnostic and therapeutic interventions so a thorough knowledge of the patient and monitors allow for a quick interpretation and resolution of the problem.

Keywords: ECG artefacts, patient warming blanket, peri-operative arrhythmias, mobile messaging services

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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

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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

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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

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Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

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Authors: Chante Van Tonder, Bart Bossink, Chris Schachtebeck, Cecile Nieuwenhuizen

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Small and Medium-Sized Enterprises (SMEs) play a key role in national economies around the world, being contributors to economic and social well-being. Due to this, the success, growth and competitiveness of SMEs are critical. However, there are many factors that undermine this, such as resource constraints, poor information communication infrastructure (ICT), skills shortages and poor management. The Fourth Industrial Revolution offers new tools and opportunities such as digital transformation and business model innovation (BMI) to the SME sector to enhance its competitiveness. Adopting and leveraging digital technologies such as cloud, mobile technologies, big data and analytics can significantly improve business efficiencies, value proposition and customer experiences. Digital transformation can contribute to the growth and competitiveness of SMEs. However, SMEs are lagging behind in the participation of digital transformation. Extant research lacks conceptual and empirical research on how digital transformation drives BMI and the impact it has on the growth and competitiveness of SMEs. The purpose of the study is, therefore, to close this gap by developing and empirically validating a conceptual model to determine if SMEs are achieving BMI through digital transformation and how this is impacting the growth, competitiveness and overall business performance. An empirical study is being conducted on 300 SMEs, consisting of 150 South-African and 150 Dutch SMEs, to achieve this purpose. Structural equation modeling is used, since it is a multivariate statistical analysis technique that is used to analyse structural relationships and is a suitable research method to test the hypotheses in the model. Empirical research is needed to gather more insight into how and if SMEs are digitally transformed and how BMI can be driven through digital transformation. The findings of this study can be used by SME business owners, managers and employees at all levels. The findings will indicate if digital transformation can indeed impact the growth, competitiveness and overall performance of an SME, reiterating the importance and potential benefits of adopting digital technologies. In addition, the findings will also exhibit how BMI can be achieved in light of digital transformation. This study contributes to the body of knowledge in a highly relevant and important topic in management studies by analysing the impact of digital transformation on BMI on a large number of SMEs that are distinctly different in economic and cultural factors

Keywords: business models, business model innovation, digital transformation, SMEs

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Authors: Jelena Riznić

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Sexual violence is a social fact that is both ubiquitous and invisible. From the myth of Medusa and Lucretia, through legends about sexual violence in war conflicts, to Hollywood films and other productions — sexual violence exists as a motive, implicitly or explicitly. Many Hollywood films contain a scene of rape, and the media is increasingly reporting on cases of sexual violence, often not following the guidelines for sensitized and ethical reporting. On the other hand, sexual violence remains an invisible phenomenon if we are talking from the perspective of the survivors. Only the wave of women's testimonies that flooded social networks after the #MeToo campaign in 2017 pointed to the prevalence and to the existing ideas about sexual violence that persist at the level of myths in society, but also through formal norms in the hearing of justice systems. The problem is also in the way rape is defined in the criminal codes of different countries, and all of this affects the reproduction of sexual violence. Precisely because it is a deeply intimate experience of violence, but also a structural problem; on the other hand, understanding sexual violence requires sociological imagination. Accordingly, the subject of this paper is the presentation and analysis of various discourses on sexual violence throughout history — pre/anti-feminist, feminist and criminal law, with particular reference to the situation in Serbia. The paper uses a critical review and comparative analysis of various sources on sexual violence, as well as an analysis of the impact of these sources on the modern legal framework that regulates sexual violence. Research has shown that despite feminist contributions, myths about sexual violence persist and influence the treatment of women who have survived violence in criminal systems and society in general.

Keywords: sexual violence, gender-based violence, MeToo campaign, feminism, Serbia

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Authors: Goudjil kamel, Boukhatem Ghania, Jlailia Djihene

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This paper delves into the development of a sophisticated desktop application designed to calculate soil bearing capacity and predict limit pressure. Drawing from an extensive review of existing methodologies, the study meticulously examines various approaches employed in soil bearing capacity calculations, elucidating their theoretical foundations and practical applications. Furthermore, the study explores the burgeoning intersection of artificial intelligence (AI) and geotechnical engineering, underscoring the transformative potential of AI- driven solutions in enhancing predictive accuracy and efficiency.Central to the research is the utilization of cutting-edge machine learning techniques, including Artificial Neural Networks (ANN), XGBoost, and Random Forest, for predictive modeling. Through comprehensive experimentation and rigorous analysis, the efficacy and performance of each method are rigorously evaluated, with XGBoost emerging as the preeminent algorithm, showcasing superior predictive capabilities compared to its counterparts. The study culminates in a nuanced understanding of the intricate dynamics at play in geotechnical analysis, offering valuable insights into optimizing soil bearing capacity calculations and limit pressure predictions. By harnessing the power of advanced computational techniques and AI-driven algorithms, the paper presents a paradigm shift in the realm of geotechnical engineering, promising enhanced precision and reliability in civil engineering projects.

Keywords: limit pressure of soil, xgboost, random forest, bearing capacity

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Authors: Rosiris Maturo Domingues, Patricia Luissa Masmo, Cibele Cavalheiro Neves, Juliana Dalla Martha Rodriguez

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This article reports the experience of the pedagogical consultants responsible for the curriculum development of Senac São Paulo courses when facing the emergency need to maintain the pedagogical process in their schools in the face of the Covid-19 pandemic. The urgent adjustment to distance education resulted in the improvement of the process and the adoption of new teaching and learning strategies mediated by technologies. The processes for preparing and providing guidelines for professional education courses were also readjusted. Thus, a bank of teaching-learning strategies linked to digital resources was developed, categorized, and identified by their didactic-pedagogical potential, having as an intersection didactic planning based on learning objectives based on Bloom's taxonomy (revised), given its convergence with the competency approach adopted by Senac. Methodologically, a relationship was established between connectivity and digital networks and digital evolution in school environments, culminating in new paradigms and processes of educational communication and new trends in teaching and learning. As a result, teachers adhered to the use of digital tools in their practices, transposing face-to-face classroom methodologies and practices to online media, whose criticism was the use of ICTs in an instrumental way, reducing methodologies and practices to teaching only transmissive. There was recognition of the insertion of technology as a facilitator of the educational process in a non-palliative way and the development of a web curriculum, now and fully, carried out in contexts of ubiquity.

Keywords: technologies, education, teaching-learning strategies, Bloom taxonomy

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Authors: Deng Tingting

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The coordinated and integrated development of regions is an inevitable requirement for China to move towards high-quality, sustainable development. As one of the regions with the best economic foundation and the strongest economic strength in western China, it is a typical area with national importance and strong network connection characteristics in terms of the comprehensive effect of linking the inland hinterland and connecting the western and national urban networks. The integrated development of the Chengdu-Chongqing economic circle is of great strategic significance for the rapid and high-quality development of the western region. In the context of new urbanization, this paper takes 16 urban units within the economic circle as the research object, based on the 5-year panel data of population, regional economy, and spatial construction and development from 2016 to 2020, using the entropy method and Theil index to analyze the three target layers, and cause analysis. The research shows that there are temporal and spatial differences in the Chengdu-Chongqing economic circle, and there are significant differences between the core city and the surrounding cities. Therefore, by reforming and innovating the regional coordinated development mechanism, breaking administrative barriers, and strengthening the "polar nucleus" radiation function to release the driving force for economic development, especially in the gully areas of economic development belts, not only promote the coordinated development of internal regions but also promote the coordinated and sustainable development of the western region and take a high-quality development path.

Keywords: Chengdu-Chongqing economic circle, new urbanization, coordinated regional development, Theil Index

Procedia PDF Downloads 117

Authors: Almas Athif Fathin Wiyantoro, Fransiskus Xaverius Ivan Budiman, Fithra Faisal Hastiadi

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The growth of clothing and technology as a marketing tool has a great influence on online business owners to know how much the characteristics and psychology of consumers in influencing purchasing decisions made by Indonesian women consumers. One of the most important issues faced by Indonesian women consumers is the suitability of clothing. The suitability of clothing can affect the body cathexis, identity, and confidence. So the thematic analysis of clothing fitness and body cathexis of women consumers when and after using virtual fitting room technology to purchase decision is important to do. This research using group method of pre-post treatment and considers how the recruitment technique of snowball sampling, which uses interpersonal relations and connections between people, both includes and excludes individuals into 39 participants' social networks to access specific populations. The results obtained from the study that the results of body scans and photos of virtual fitting room results can be made an intervention in women consumers in assessing their body cathexis objectively in the process of making purchasing decisions. The study also obtained a regression equation Y = 0.830 + 0.290X1 + 0.292X2, showing a positive relationship between suitability of clothing and body cathexis which influenced purchasing decisions on women consumers and after (personal and psychological factors) using virtual fitting room, meaning that all independent variables influence Positive towards the purchasing decision of the women consumers.

Keywords: body cathexis, clothing fitness, purchasing decision making and virtual fitting room

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Authors: Syed Jawad Hussain, Abir Touati, Farid Touati

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Free-Space Optics (FSO) is a wireless technology that enables the optical transmission of data though the air. FSO is emerging as a promising alternative or complementary technology to fiber optic and wireless radio-frequency (RF) links due to its high-bandwidth, robustness to EMI, and operation in unregulated spectrum. These systems are envisioned to be an essential part of future generation heterogeneous communication networks. Despite the vibrant advantages of FSO technology and the variety of its applications, its widespread adoption has been hampered by rather disappointing link reliability for long-range links due to atmospheric turbulence-induced fading and sensitivity to detrimental climate conditions. Qatar, with modest cloud coverage, high concentrations of airborne dust and high relative humidity particularly lies in virtually rainless sunny belt with a typical daily average solar radiation exceeding 6 kWh/m2 and 80-90% clear skies throughout the year. The specific objective of this work is to study for the first time in Qatar the effect of solar irradiation on the deliverability of the FSO Link. In order to analyze the transport media, we have ported Embedded Linux kernel on Field Programmable Gate Array (FPGA) and designed a network sniffer application that can run into FPGA. We installed new FSO terminals and configure and align them successively. In the reporting period, we carry out measurement and relate them to weather conditions.

Keywords: free space optics, solar irradiation, field programmable gate array, FSO outage

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Authors: Xiaoshuang Jia, Huiling Feng, Li Niu, Wei Hai

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Led by Humanistic Beijing Studies Center in Renmin University of China, My Peking Memory Project(MPMP) is a long-time digital memory project under guarantee of public participation to enable the cultural and intellectual memory of Beijing to be collected, organized, preserved and promoted for discovery and research. Taking digital memory as a new way, MPMP is an important part of Peking Memory Project(PMP) which is aimed at using digital technologies to protect and (re)present the cultural heritage in Beijing. The key outcome of MPMP is the co-building of a total digital collection of knowledge assets about Beijing. Institutional memories are central to Beijing’s collection and consist of the official published documentary content of Beijing. These have already fall under the archival collection purview. The advances in information and communication technology and the knowledge form social memory theory have allowed us to collect more comprehensively beyond institutional collections. It is now possible to engage citizens on a large scale to collect private memories through crowdsourcing in digital formats. Private memories go beyond official published content to include personal narratives, some of which are just in people’s minds until they are captured by MPMP. One aim of MPMP is to engage individuals, communities, groups or institutions who have formed memories and content about Beijing, and would like to contribute them. The project hopes to build a culture of remembering and it believes ‘Every Memory Matters’. Digital memory contribution was achieved through the development of the MPMP. In reducing barriers to digital contribution and promoting high public Participation, MPMP has taken explored the harvesting of transcribe service for digital ingestion, mobile platform and some off-line activities like holding social forum. MPMP has also cooperated with the ‘Implementation Plan of Support Plan for Growth of Talents in Renmin University of China’ to get manpower and intellectual support. After six months of operation, now MPMP have more than 2000 memories added and 7 Special Memory Collections now online. The work of MPMP has ultimately helped to highlight the important role in safeguarding the documentary heritage and intellectual memory of Beijing.

Keywords: digital memory, public participation, MPMP, cultural heritage, collection

Procedia PDF Downloads 169

Authors: Narumon Jiwattanasuk, Phrakrupalad Pannavoravat, Pataraporn Sirikanchana

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Mindfulness has become a perspective addressing positive wellbeing these days. The aims of this paper are to analyze the problems of executive meditation practitioners at the Buddhamahametta Foundation in Thailand and to provide recommendations on the process to develop peaceful wellbeing in executive meditation practitioners by applying the principles of the four foundations of mindfulness. This study is particularly focused on executives because there is not much research focusing on the well-being development of executives, and the researcher recognizes that executives can be an example within their organizations. This would be a significant influence on their employees and their families to be interested in practicing mindfulness. This improvement will then grow from an individual to the surrounding community such as family, workplace, society, and the nation. This would lead to happiness at the national level, which is the expectation of this research. The paper highlights mindfulness practices that can be performed on a daily basis. This study is qualitative research, and there are 10 key participants who are executives from various sectors such as hospitality, healthcare, retail, power energy, and so on. Three mindfulness-based courses were conducted over a period of 8 months, and in-depth interviews were done before the first course as well as at the end of every course. In total, four in-depth interviews were conducted. The information collected from the interviews was analyzed in order to create the process to develop peaceful well-being. Focus group discussions with the mindfulness specialists were conducted to help develop the mindfulness program as well. As a result of this research, it is found that the executives faced the following problems: stress, negative thinking loops, losing temper, seeking acceptance, worry about uncontrollable external factors, unable to control their words, and weight gain. The cultivation of the four foundations of mindfulness can develop peaceful wellbeing. The results showed that after the key informant executives attended the mindfulness courses and practiced mindfulness regularly, they have developed peaceful well-being in all aspects such as physical, psychological, behavioral, and intellectual by applying 12 mindfulness-based activities. The development of wellbeing, in the conclusion of this study, also includes various tools to support the continuing practice, including the handout of guided mindfulness practice, VDO clips about mindfulness practice, the online dhamma channel, and mobile applications to support regular mindfulness-based practices.

Keywords: executive, mindfulness activities, stress, wellbeing

Procedia PDF Downloads 120

Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: Busra Nur Ozguler Aktel

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This research aims to understand the factors that affect the ways in which tribes perceive and respond to violent conflicts in fragile states, given that tribes are essential stakeholders in many conflict-ridden fragile states, whether Afghanistan, Iraq, Syria, Libya, Somalia, Nigeria, or Yemen. It explores the primary questions of why some tribes align with extremist groups while others align with states during civil wars and why some tribes switch alignments. It argues that tribes form and switch alignments based on their perception of threats to their traditional tribal structure (internal dynamics) and clientelist relationships (external dynamics). Put differently; threat perceptions lead them to choose either the state or extremist groups that will more likely secure their traditional structure and patronage networks. This study focuses on Iraqi tribes as a case study. It builds a theory of tribal alignment formation based on ethnographic fieldwork in the Middle East, with a particular focus on Iraqi Sunni tribes living in the Kurdish region of Iraq and Jordan. As a result of the interviews with tribal leaders and members, local journalists, researchers, and politicians, it concludes that complex (re)alignments of tribes can determine the course and outcome of the conflicts, either mitigating or escalating violence. This study contributes to the larger body of conflict management and peacebuilding literature by introducing tribes as non-state actors and exploring their interactions with other actors in civil wars.

Keywords: civil wars, tribes, alignment formation, side-switching, Iraq

Procedia PDF Downloads 87

Authors: Kenneth Harper

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The rapid growth of data-driven decision-making across various industries necessitates advanced solutions to ensure data integrity, scalability, and security. This study introduces a decentralized data platform built on blockchain technology to improve data management processes in high-volume environments such as healthcare and financial services. The platform integrates blockchain networks using Cosmos SDK and Polkadot Substrate alongside decentralized storage solutions like IPFS and Filecoin, and coupled with decentralized computing infrastructure built on top of Avalanche. By leveraging advanced consensus mechanisms, we create a scalable, tamper-proof architecture that supports both structured and unstructured data. Key features include secure data ingestion, cryptographic hashing for robust data lineage, and Zero-Knowledge Proof mechanisms that enhance privacy while ensuring compliance with regulatory standards. Additionally, we implement performance optimizations through Layer 2 scaling solutions, including ZK-Rollups, which provide low-latency data access and trustless data verification across a distributed ledger. The findings from this exercise demonstrate significant improvements in data accessibility, reduced operational costs, and enhanced data integrity when tested in real-world scenarios. This platform reference architecture offers a decentralized alternative to traditional centralized data storage models, providing scalability, security, and operational efficiency.

Keywords: blockchain, cosmos SDK, decentralized data platform, IPFS, ZK-Rollups

Procedia PDF Downloads 28

Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

Procedia PDF Downloads 480

Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

Procedia PDF Downloads 143