Search results for: traditional techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11156

Search results for: traditional techniques

9776 Dynamic Bandwidth Allocation in Fiber-Wireless (FiWi) Networks

Authors: Eman I. Raslan, Haitham S. Hamza, Reda A. El-Khoribi

Abstract:

Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques.

Keywords: fiber-wireless (FiWi), dynamic bandwidth allocation (DBA), passive optical networks (PON), media access control (MAC)

Procedia PDF Downloads 532
9775 Passport Bros: Exploring Neocolonial Masculinity and Sex Tourism as a Response to Shifting Gender Dynamics

Authors: Kellen Sharp

Abstract:

This study explores the phenomenon of ‘Passport Bros’, a subset within the manosphere responding to perceived crises in masculinity amidst changing gender dynamics. Focusing on a computational analysis of the passport bro community, the research addresses normative beliefs, deviations from MGTOW ideology, and discussions on nationality, race, and gender. Originating from the MGTOW movement, passport bros engage in a neocolonial approach by seeking traditional, non-Western women, attributing this pursuit to dissatisfaction with modern Western women. The paper examines how hetero pessimism within MGTOW shapes the emergence of passport bros, leading to the adoption of red pill ideologies and ultimately manifesting in the form of sex tourism. Analyzing data collected from passport bro forums through computer-assisted content analysis, the study identifies key discourses such as questions and answers, money, attitudes towards Western and traditional women, and discussions about the movement itself. The findings highlight the nuanced intersection of gender, race, and global power dynamics within the passport bro community, shedding light on their motivations and impact on neocolonial legacies.

Keywords: toxic online community, manosphere, gender and media, neocolonialism

Procedia PDF Downloads 79
9774 Iris Cancer Detection System Using Image Processing and Neural Classifier

Authors: Abdulkader Helwan

Abstract:

Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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9773 The Development of Iranian Theatrical Performance through the Integration of Narrative Elements from Western Drama

Authors: Azadeh Abbasikangevari

Abstract:

Background and Objectives: Theatre and performance are two separate themes. What is presented in Iran as a performance is the species and ritual and traditional forms of the play. The Iranian performance has its roots in myth and ritual. Drama is essentially a Western phenomenon that has gradually entered Iran and influenced Iranian performance. A theatre is based on antagonism (axis) and protagonism (anti-axis), while performance has a monotonous and steady motion. The elements of Iranian performance include field, performance on the stage, and magnification in performance, all of which are based on narration. This type of narration has been present in Iranian modern drama. The objective of this study was to analyze the drama structure according to narration elements by a comparison between the Western theater and the Iranian performance and determining the structural differences in the type of narrative. Materials and Methods: In this study, the elements of the drama were analyzed using the library method among the available library resources. The review of the literature included research articles and textbooks which focused on Iranian plays, as well as books and articles which encompassed narrative and drama element. Data were analyzed in the comparative-descriptive method. Results: Examining and studying different kinds of Iranian performances, showed that the narrative has always been a characteristic feature of Iranian plays. Iranians have narrated the stories and myths and have had a particular skill of oral literature. Over time, they slowly introduced narrative culture into their art, where this element is the most important structural element in Iran's dramatic art. Considering the fact that narration in Iranian traditional play, such as Ta'ziyeh and Naghali, was oral and consequently, it was slowly forgotten and excluded from written theatrical texts. Since the drama has entered in its western form in Iran, the plays written by the authors were influenced by narrative elements existing in western plays. Conclusions: The narrative’s element has undoubtedly had an impact on modern Iranian drama and Iranian contemporary drama. Therefore, the element of narration is an integral part of the Iranian traditional play structure.

Keywords: drama methodology, Iranian performance, Iranian modern drama, narration

Procedia PDF Downloads 133
9772 Use of Multivariate Statistical Techniques for Water Quality Monitoring Network Assessment, Case of Study: Jequetepeque River Basin

Authors: Jose Flores, Nadia Gamboa

Abstract:

A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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9771 AI-Powered Models for Real-Time Fraud Detection in Financial Transactions to Improve Financial Security

Authors: Shanshan Zhu, Mohammad Nasim

Abstract:

Financial fraud continues to be a major threat to financial institutions across the world, causing colossal money losses and undermining public trust. Fraud prevention techniques, based on hard rules, have become ineffective due to evolving patterns of fraud in recent times. Against such a background, the present study probes into distinct methodologies that exploit emergent AI-driven techniques to further strengthen fraud detection. We would like to compare the performance of generative adversarial networks and graph neural networks with other popular techniques, like gradient boosting, random forests, and neural networks. To this end, we would recommend integrating all these state-of-the-art models into one robust, flexible, and smart system for real-time anomaly and fraud detection. To overcome the challenge, we designed synthetic data and then conducted pattern recognition and unsupervised and supervised learning analyses on the transaction data to identify which activities were fishy. With the use of actual financial statistics, we compare the performance of our model in accuracy, speed, and adaptability versus conventional models. The results of this study illustrate a strong signal and need to integrate state-of-the-art, AI-driven fraud detection solutions into frameworks that are highly relevant to the financial domain. It alerts one to the great urgency that banks and related financial institutions must rapidly implement these most advanced technologies to continue to have a high level of security.

Keywords: AI-driven fraud detection, financial security, machine learning, anomaly detection, real-time fraud detection

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9770 Information Construction of Higher Education in Teaching Practice

Authors: Yang Meng, James L. Patnao

Abstract:

With the rapid development of information technology and the impact of the epidemic environment, the traditional teaching model can’t longer meet the requirements of the development of the times. The development of teaching mechanism is the inevitable trend of the future development of higher education. We must further promote the informatization of higher education in teaching practice, let modern information technology penetrate and practice in classroom teaching, and provide promising opportunities for the high-quality development of higher education. This article mainly through the distribution of questionnaires to teachers of colleges and universities, so as to understand the degree of informatization in the teaching of colleges and universities. And on the basis of domestic and foreign scholars' research on higher education informatization, it analyzes the existing problems, and finds the optimal solution based on the needs of education and teaching development. According to the survey results, most college teachers will use information technology in teaching practice, but the information technology teaching tools used by teachers are relatively simple, and most of them only use slides. In addition, backward informatization infrastructure and less informatization training are the main challenges facing the current teaching informatization construction. If colleges and universities can make good use of information technology and multimedia technology and combine it with traditional teaching, it will definitely promote the development of college education and further promote the modernization and informatization of higher education.

Keywords: higher education, teaching practice, informatization construction, e-education

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9769 Auteur 3D Filmmaking: From Hitchcock’s Protrusion Technique to Godard’s Immersion Aesthetic

Authors: Delia Enyedi

Abstract:

Throughout film history, the regular return of 3D cinema has been discussed in connection to crises caused by the advent of television or the competition of the Internet. In addition, the three waves of stereoscopic 3D (from 1952 up to 1983) and its current digital version have been blamed for adding a challenging technical distraction to the viewing experience. By discussing the films Dial M for Murder (1954) and Goodbye to Language (2014), the paper aims to analyze the response of recognized auteurs to the use of 3D techniques in filmmaking. For Alfred Hitchcock, the solution to attaining perceptual immersion paradoxically resided in restraining the signature effect of 3D, namely protrusion. In Jean-Luc Godard’s vision, 3D techniques allowed him to explore perceptual absorption by means of depth of field, for which he had long advocated as being central to cinema. Thus, both directors contribute to the foundation of an auteur aesthetic in 3D filmmaking.

Keywords: Alfred Hitchcock, authorship, 3D filmmaking, Jean-Luc Godard, perceptual absorption, perceptual immersion

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9768 Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines

Authors: Alexander Guzman Urbina, Atsushi Aoyama

Abstract:

The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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9767 Bio-Guided of Active New Alkaloids from Alstonia Brassi Toxicity Antitumour Activity in Silico and Molecular Modeling

Authors: Mesbah Khaled, Bouraoui Ouissal, Benkiniouar Rachid, Belkhiri Lotfi

Abstract:

Alstonia, which are tropical plants with a wide geographical distribution, have been divided into different sections by different authors based on previous studies of several species within the genus. Monachino divides Alstonia into 5 sections, while Pichon divides it into 3 sections. Several plants belonging to this genus, such as Alstonia brassii, have been used in traditional folk medicine to treat ailments such as fever, malaria and dysentery]. Previous studies focusing on the chemical composition of these plants have successfully identified indol alkaloids with cytotoxic, anti-diabetic and anti-inflammatory properties. The newly discovered monomers are structurally similar to the backbones of picralin, affinisin and macrolin. On the other hand, all recently isolated dimeric compounds have a macrolin moiety. In this study, a computational analysis was performed on a series of novel molecules, including both monomeric and dimeric compounds with different structural frameworks. This investigation represents the first computational study of these molecules using an in silico approach incorporating 2D-QSAR data. The analysis involved various computational techniques, including 2D-QSAR modelling, molecular docking studies and subsequent validation by molecular dynamics simulation and assessment of ADMET properties. The chemical composition was identified by 1D and 2D NMR. Eight new alkaloids were isolated, 5 monomers and 3 dimers. In this section, we focus on the biological activity of 4 new alkaloids belonging to two different skeletons, the affinisine skeleton.

Keywords: affinisine, talcarpine, macroline, cytotoxicity, alkaloids

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9766 Forecasting Equity Premium Out-of-Sample with Sophisticated Regression Training Techniques

Authors: Jonathan Iworiso

Abstract:

Forecasting the equity premium out-of-sample is a major concern to researchers in finance and emerging markets. The quest for a superior model that can forecast the equity premium with significant economic gains has resulted in several controversies on the choice of variables and suitable techniques among scholars. This research focuses mainly on the application of Regression Training (RT) techniques to forecast monthly equity premium out-of-sample recursively with an expanding window method. A broad category of sophisticated regression models involving model complexity was employed. The RT models include Ridge, Forward-Backward (FOBA) Ridge, Least Absolute Shrinkage and Selection Operator (LASSO), Relaxed LASSO, Elastic Net, and Least Angle Regression were trained and used to forecast the equity premium out-of-sample. In this study, the empirical investigation of the RT models demonstrates significant evidence of equity premium predictability both statistically and economically relative to the benchmark historical average, delivering significant utility gains. They seek to provide meaningful economic information on mean-variance portfolio investment for investors who are timing the market to earn future gains at minimal risk. Thus, the forecasting models appeared to guarantee an investor in a market setting who optimally reallocates a monthly portfolio between equities and risk-free treasury bills using equity premium forecasts at minimal risk.

Keywords: regression training, out-of-sample forecasts, expanding window, statistical predictability, economic significance, utility gains

Procedia PDF Downloads 108
9765 The Role of Uzbek Music Culture in Tourism

Authors: Odina Omonjonova

Abstract:

The Uzbek people have a rich history and a rapidly developing music culture for several centuries. Monuments, shrines, places of culture and spirituality, which are the most beautiful proofs of history, show that this country has been a center of wisdom since ancient times. Nowadays, Uzbekistan is opening its face to the world with its unique spiritual heritage, historical monuments, peaceful corners and beautiful landscapes. Tourists from many countries visit and get acquainted with Uzbek culture and history and acknowledge it with great respect. The place of traditional music in describing the national color on the world scale is incomparable. Oral folk works that have reached this period, lapar, yalla, songs and ‘Shashmaqom’ are the intangible spiritual wealth of the Uzbek people. They embody the ancient and great history, spiritual world, artistic philosophy, spirit and values of our nation. National music is the main part of the culture of the nation, and here it is worth emphasizing the importance of music in the tourism of Uzbekistan. Foreign guests can enjoy our national music in various ways: (1) Concerts: There are many concert halls and cultural centers in the cities of Uzbekistan, where many concerts and events are held. Well-known musicians, singers and ensembles add more beauty to the beauty of these places, performing musical samples in Shashmaqom and other traditional styles. In these concert programs, tourists will have the opportunity to listen to works of art in an attractive live performance. (2) Festivals: Many music festivals are held in Uzbekistan throughout the year. The ‘Sharq Taronalari’ international music festival is a unique holiday where musicians from all over the world gather to celebrate the diversity of musical traditions. In recent years, traditional music has been played regularly in a number of festivals such as the ‘International Maqom Festival’, ‘International Craft Festival’ and ‘Boysun Bahari’ held in our country, which has increased the attention of travelers to our music culture. (3) Cultural seminars. Tourists interested in hands-on musical experience can participate in musical workshops. These classes allow tourists to learn to play traditional musical instruments and even participate in group activities. (4) Street musicians: In the central places and ancient streets of Uzbekistan's cities, we can meet street musicians playing soulful tunes. Performing and singing folklore samples on modern instruments directly attracts foreign guests. In Uzbekistan, national music and tourism have a direct and indirect connection. Music serves as a bridge between the country's history and its modern identity and enriches the travel experience. The impact of national music on tourism goes beyond mere statistics. Although tourist arrivals have increased significantly due to music-related attractions, the real impact lies in the stories and live testimonies of visitors. Travelers often say that the rhythms of Uzbekistan touched their hearts and broadened their worldview. In addition, music tourism strengthens the country's economy, provides employment, supports local artisans and performers, and provides an opportunity to showcase their talents to a global audience. In short, Uzbekistan is not only a place of interest, but it is among the countries that attract travelers with its unique national music. Uzbek music, folklore, songs, from the wonderful melodies of ‘Shashmaqom’ to the attractive sounds of traditional musical instruments, give aesthetic and spiritual pleasure and are important in organizing a large-scale trip for tourists visiting the country.

Keywords: traditional music, folklore, shashmaqom, tourism, festivals, street musicians, traditional musical instruments

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9764 Determination of Weathering at Kilistra Ancient City by Using Non-Destructive Techniques, Central Anatolia, Turkey

Authors: İsmail İnce, Osman Günaydin, Fatma Özer

Abstract:

Stones used in the construction of historical structures are exposed to various direct or indirect atmospheric effects depending on climatic conditions. Building stones deteriorate partially or fully as a result of this exposure. The historic structures are important symbols of any cultural heritage. Therefore, it is important to protect and restore these historical structures. The aim of this study is to determine the weathering conditions at the Kilistra ancient city. It is located in the southwest of the Konya city, Central Anatolia, and was built by carving into pyroclastic rocks during the Byzantine Era. For this purpose, the petrographic and mechanical properties of the pyroclastic rocks were determined. In the assessment of weathering of structures in the ancient city, in-situ non-destructive testing (i.e., Schmidt hardness rebound value, relative humidity measurement) methods were applied.

Keywords: cultural heritage, Kilistra ancient city, non-destructive techniques, weathering

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9763 Agile Manifesto Construct for the Film Industry

Authors: Kiri Trier, Theresa Treffers

Abstract:

In the course of continuous volatility like production stops due to the COVID-19 pandemic, video-on-demand player monopolizing the film industry, filmmakers are stuck in traditional, linear content development processes. The industry has to become more agile in order to react quickly and easily to changes. Since content development in agile project management is scientifically–empirically not at all recorded, and a lack beyond the software development in terms of agile methods consists, we examined if the agile manifesto values and principles from the software development can be adapted to the film industry to enable agility and digitalization of content development in the industry. We conducted an online questionnaire with 184 German filmmakers (producers, authors, directors, actors, film financiers) for a first cross-sectional assessment for adaptability of the agile manifesto from the software development to the film industry, factor analysis was used to validate the construct. Our results show that it is crucial to digitalize traditional content development to agile content development end-to-end, with tools, lean processes, new collaboration structures, and holacracy to prepare for any volatility. Overall, we examined the first construct for an agile manifesto for the film industry with four values related to nine own principles. Our findings help to get a better understanding of the agile manifesto beyond the software development as a guideline for implementing agility in the film industry.

Keywords: agile manifesto, agile project management, agility, film industry

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9762 Drive Sharing with Multimodal Interaction: Enhancing Safety and Efficiency

Authors: Sagar Jitendra Mahendrakar

Abstract:

Exploratory testing is a dynamic and adaptable method of software quality assurance that is frequently praised for its ability to find hidden flaws and improve the overall quality of the product. Instead of using preset test cases, exploratory testing allows testers to explore the software application dynamically. This is in contrast to scripted testing methodologies, which primarily rely on tester intuition, creativity, and adaptability. There are several tools and techniques that can aid testers in the exploratory testing process which we will be discussing in this talk.Tests of this kind are able to find bugs of this kind that are harder to find during structured testing or that other testing methods may have overlooked.The purpose of this abstract is to examine the nature and importance of exploratory testing in modern software development methods. It explores the fundamental ideas of exploratory testing, highlighting the value of domain knowledge and tester experience in spotting possible problems that may escape the notice of traditional testing methodologies. Throughout the software development lifecycle, exploratory testing promotes quick feedback loops and continuous improvement by giving testers the ability to make decisions in real time based on their observations. This abstract also clarifies the unique features of exploratory testing, like its non-linearity and capacity to replicate user behavior in real-world settings. Testers can find intricate bugs, usability problems, and edge cases in software through impromptu exploration that might go undetected. Exploratory testing's flexible and iterative structure fits in well with agile and DevOps processes, allowing for a quicker time to market without sacrificing the quality of the final product.

Keywords: exploratory, testing, automation, quality

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9761 The Effects of Co-Teaching on Study Achievement by Teaching Unite of Teaching Strategy Course on a Sample of Student at Education College at King Faisal University

Authors: Layla Alzarah

Abstract:

The purpose of this research was to study the effects of co-teaching upon study achievement by teaching unite of teaching strategy course to a sample of students at education college at King Faisal University. The sample of this study, which consisted of 100 students, was divided into two equal groups. 50 students were selected to be the Control group which had been taught by the traditional way with one teacher, whereas the remaining 50 students represented the experimental group who had been taught by co-teaching. The study had lasted for 4 weeks. Related achievement test had been prepared, consisted of 23 questions, from multi choice question type, which had been divided on the chosen unite syllabus. The validity and reliability had been tested. The study conducted at the second semester of 1433-1434 HT tests had been used to analysis the data. The research findings showed that the average exam scores of students receiving team teaching were higher than those of students receiving traditional teaching as there were significant differences in means at (<0.05) between the two groups in favor of the experimental group. Based on the study findings the researcher recommended applying co-teaching in teaching the course of teaching strategies and other courses also to conduct similar studies.

Keywords: co-teaching, cooperative teaching, teaching strategies, study achievement

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9760 Transformation of Traditional Marketplaces in an Urban Context: Case of Chalai Market, Thiruvananthapuram

Authors: Aswathy Vijayan, Sharath Sunder Rajeev

Abstract:

Trade has been fundamental in the footprint of human civilization since ancient time. In most of the historic cities, city development was along trading routes, where marketplaces are the major entrance to a city and hence a major element of the urban fabric. Marketplaces are where the commercial activities flourish, people, having a sense of belonging to the place, where they easily fit in. Acknowledging the built environment in and around the market in a way, creating a sense of place is an important factor in the success of public spaces. Local markets are developed in an organic manner, which adds on to the people experience and perception of urban space. With the city development, the commercial needs within the city increase, hence marketplaces flourish, irrespective of the functional segregation within. The work-live culture in the marketplaces diminishes as the commercial expansion washes away the residential patches within it. Real estate flourishes as the newer infills are without considering the carrying capacity of the place. Chalai market is a prominent business center serving the regional level of Thiruvananthapuram city. The transformation trend of marketplaces in city cores are understood from case study on Fatimid Cairo Marketplace. The parameters that led to transformation of marketplaces in a global context is considered for the analysis of the Chalai market. The structure of the marketplace over the years is analyzed in terms of transformation in location, transformation in the land- use, change in commodity, and transformation in movement and activity. The aim of the research is to emphasize the need to understand the transformation trend, in creating a suitable development pattern for the city. The unregulated transformation within the city core has led to tremendous transformation in the user group and user pattern and eventually to the commercial trend. With the change in lifestyle and need for new amenities have led to addition of new infills leading to the degradation of the native commerce. Hence addressing the transformation of marketplaces are crucial to maintaining the locational significance and cultural importance and heritage of the place.

Keywords: bazaar, market centers, marketplaces, traditional city, traditional market, urban fabric

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9759 Neutral Heavy Scalar Searches via Standard Model Gauge Boson Decays at the Large Hadron Electron Collider with Multivariate Techniques

Authors: Luigi Delle Rose, Oliver Fischer, Ahmed Hammad

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In this article, we study the prospects of the proposed Large Hadron electron Collider (LHeC) in the search for heavy neutral scalar particles. We consider a minimal model with one additional complex scalar singlet that interacts with the Standard Model (SM) via mixing with the Higgs doublet, giving rise to an SM-like Higgs boson and a heavy scalar particle. Both scalar particles are produced via vector boson fusion and can be tested via their decays into pairs of SM particles, analogously to the SM Higgs boson. Using multivariate techniques, we show that the LHeC is sensitive to heavy scalars with masses between 200 and 800 GeV down to scalar mixing of order 0.01.

Keywords: beyond the standard model, large hadron electron collider, multivariate analysis, scalar singlet

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9758 Radar Fault Diagnosis Strategy Based on Deep Learning

Authors: Bin Feng, Zhulin Zong

Abstract:

Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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9757 Safe and Scalable Framework for Participation of Nodes in Smart Grid Networks in a P2P Exchange of Short-Term Products

Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

Abstract:

Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

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9756 Effect of Building Construction Sizes on Project Delivery Methods in Nigeria

Authors: Nuruddeen Usman, Mohammad Sani

Abstract:

The performance of project delivery methods has been an issue of concern to various stakeholders in the construction industry. The contracting system of project delivery is the traditional system used in the delivery of most public projects in Nigeria. The direct labor system is used most times as an alternative to the traditional system. There were so many complain about the performance of contracting system and the suitability of direct labor as an alternative to the delivery of public projects. Therefore, this paper is aimed at investigating the effect of project size on the project delivery methods in the completed public buildings. Questionnaires were self-administered to managerial staff in the study area and analyzed using descriptive statistics. The findings reveals that contracting system was choosing for large size building construction project delivery with higher frequency (F) of 40 (76.9%) against direct labor with 12 (23.1%). While the small size project, the result revealed a frequency (F) of 26 (50%) for contracting system and direct labor system respectively. Base on the research findings, the contracting system, was recommended for all sizes of building construction project delivery while direct labor system can only use as an alternative for small size building construction projects delivery.

Keywords: construction size, contracting system, direct labour, effect

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9755 Implementing 3D Printed Structures as the Newest Textile Form

Authors: Banu Hatice Gürcüm, Pınar Arslan, Mahmut Yalçın

Abstract:

From the oldest production methods with yarns used to weave, knit, braid and knot to the newest production methods with fibres used to stitch, bond or structures of innovative technologies, laminates, nanoparticles, composites or 3D printing systems, textile industry advanced through materials, processes and context mostly within the last five decades. The creative momentum of fabric like 3D printed structures have come to the point of transforming as for the newest form of textile applications. Moreover, pioneering studies on the applications of 3D Printing Technology and Additive Manufacturing have been focusing on fashion and apparel sector from the last two decades beginning with fashion designers. After the advent of chain-mail like structures and flexible micro or meso structures created by SLS rapid manufacturing a more textile-like behavior is achieved. Thus, the primary aim of this paper is to discuss the most important properties of traditional fabrics that are to be expected of future fabrics. For this reason, this study deals primarily with the physical properties like softness, hand, flexibility, drapability and wearability of 3D Printed structures necessary to identify the possible ways in which it can be used instead of contemporary textile structures, namely knitted and woven fabrics. The aim of this study is to compare the physical properties of 3D printed fabrics regarding different rapid manufacturing methods (FDM and SLS). The implemented method was Material Driven Design (MDD), which comprise the use of innovative materials according to the production techniques such as 3D printing system. As a result, advanced textile processes and materials enable to the creation of new types of fabric structures and rapid solutions in the field of textiles and 3D fabrics on the other hand, are to be used in this regard.

Keywords: 3D printing technology, FDM, SLS, textile structure

Procedia PDF Downloads 339
9754 Attack Redirection and Detection using Honeypots

Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

Abstract:

A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

Procedia PDF Downloads 156
9753 Study on Control Techniques for Adaptive Impact Mitigation

Authors: Rami Faraj, Cezary Graczykowski, Błażej Popławski, Grzegorz Mikułowski, Rafał Wiszowaty

Abstract:

Progress in the field of sensors, electronics and computing results in more and more often applications of adaptive techniques for dynamic response mitigation. When it comes to systems excited with mechanical impacts, the control system has to take into account the significant limitations of actuators responsible for system adaptation. The paper provides a comprehensive discussion of the problem of appropriate design and implementation of adaptation techniques and mechanisms. Two case studies are presented in order to compare completely different adaptation schemes. The first example concerns a double-chamber pneumatic shock absorber with a fast piezo-electric valve and parameters corresponding to the suspension of a small unmanned aerial vehicle, whereas the second considered system is a safety air cushion applied for evacuation of people from heights during a fire. For both systems, it is possible to ensure adaptive performance, but a realization of the system’s adaptation is completely different. The reason for this is technical limitations corresponding to specific types of shock-absorbing devices and their parameters. Impact mitigation using a pneumatic shock absorber corresponds to much higher pressures and small mass flow rates, which can be achieved with minimal change of valve opening. In turn, mass flow rates in safety air cushions relate to gas release areas counted in thousands of sq. cm. Because of these facts, both shock-absorbing systems are controlled based on completely different approaches. Pneumatic shock-absorber takes advantage of real-time control with valve opening recalculated at least every millisecond. In contrast, safety air cushion is controlled using the semi-passive technique, where adaptation is provided using prediction of the entire impact mitigation process. Similarities of both approaches, including applied models, algorithms and equipment, are discussed. The entire study is supported by numerical simulations and experimental tests, which prove the effectiveness of both adaptive impact mitigation techniques.

Keywords: adaptive control, adaptive system, impact mitigation, pneumatic system, shock-absorber

Procedia PDF Downloads 91
9752 Traditional Values and Their Adaptation in Social Housing Design: Towards a New Typology and Establishment of 'Airhouse' Standard in Malaysia

Authors: Mohd Firrdhaus Mohd Sahabuddin, Cristina Gonzalez-Longo

Abstract:

Large migration from rural areas to urban areas like Kuala Lumpur has led to some implications for economic, social and cultural development. This high population has placed enormous demand on the existing housing stocks, especially for low-income groups. However, some issues arise, one of which is overheated indoor air temperature. This problem contributes to the high-energy usage that forces huge sums of money to be spent on cooling the house by using mechanical equipment. Therefore, this study focuses on thermal comfort in social housing, and incorporates traditional values into its design to achieve a certain measurement of natural ventilation in a house. From the study, the carbon emission and energy consumption for an air-conditioned house is 67%, 66% higher than a naturally ventilated house. Therefore, this research has come up with a new typology design, which has a large exposed wall area and full-length openings on the opposite walls to increase cross ventilation. At the end of this research, the measurement of thermal comfort for a naturally ventilated building called ‘AirHouse’ has been identified.

Keywords: tropical architecture, natural ventilation, passive design, AirHouse, social housing design

Procedia PDF Downloads 676
9751 Optimization Techniques for Microwave Structures

Authors: Malika Ourabia

Abstract:

A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The discontinuities is characterized using a hybrid spectral/numerical technique. This structure presents an arbitrary number of ports, each one with different orientation and dimensions. This article presents a hybrid method based on multimode contour integral and mode matching techniques. The process is based on segmentation and dividing the structure into key building blocks. We use the multimode contour integral method to analyze the blocks including irregular shape discontinuities. Finally, the multimode scattering matrix of the whole structure can be found by cascading the blocks. Therefore, the new method is suitable for analysis of a wide range of waveguide problems. Therefore, the present approach can be applied easily to the analysis of any multiport junctions and cascade blocks. The accuracy of the method is validated comparing with results for several complex problems found in the literature. CPU times are also included to show the efficiency of the new method proposed.

Keywords: segmentation, s parameters, simulation, optimization

Procedia PDF Downloads 530
9750 Quantitative Elemental Analysis of Cyperus rotundus Medicinal Plant by Particle Induced X-Ray Emission and ICP-MS Techniques

Authors: J. Chandrasekhar Rao, B. G. Naidu, G. J. Naga Raju, P. Sarita

Abstract:

Particle Induced X-ray Emission (PIXE) and Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) techniques have been employed in this work to determine the elements present in the root of Cyperus rotundus medicinal plant used in the treatment of rheumatoid arthritis. The elements V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Rb, and Sr were commonly identified and quantified by both PIXE and ICP-MS whereas the elements Li, Be, Al, As, Se, Ag, Cd, Ba, Tl, Pb and U were determined by ICP-MS and Cl, K, Ca, Ti and Br were determined by PIXE. The regional variation of elemental content has also been studied by analyzing the same plant collected from different geographical locations. Information on the elemental content of the medicinal plant would be helpful in correlating its ability in the treatment of rheumatoid arthritis and also in deciding the dosage of this herbal medicine from the metal toxicity point of view. Principal component analysis and cluster analysis were also applied to the data matrix to understand the correlation among the elements.

Keywords: PIXE, CP-MS, elements, Cyperus rotundus, rheumatoid arthritis

Procedia PDF Downloads 334
9749 Opinion Mining to Extract Community Emotions on Covid-19 Immunization Possible Side Effects

Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

Abstract:

The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

Procedia PDF Downloads 172
9748 Effect of Plowing the Soil of Faba Bean on Soil Productivity and Quality Improvement

Authors: Khattab E. A., Gehan A. Amin

Abstract:

The aim of the experiment was to investigate yield and yield components under effect of three different tillage systems and three faba bean varieties on clay-loamy soils. The experiment was conducted as split plot design having tillage systems in main plot and varieties in subplot. A field trial was conducted during the winter seasons of 2021-2022 and 2022-2-23, respectively in private of the agricultural lands of Shobra Beddin village, which belongs to Mansoura District of Dakahlia Province 31°, (04457)- N latitude and 31°4757- E longitude. The soil was prepared. The Seeds covered with a thin layer of soil, sown and watered. Three weeks later, the developed plants were thinned. Finally, the plants collected after 110 days of growth. Growth, yield and chemical contents determined. The results showed that the highest yield in the traditional tillage system corresponds to the superior to other tillage systems. In addition, In the variety comparison, the Sakha 1 variety was characterized by the highest yield as well as the highest values of plant growth properties among the three varieties. Conclusion: The traditional tillage system is increase grain yield of variety Sakha 1 compared with other varieties.

Keywords: yield, tillage system, varieties, faba bean

Procedia PDF Downloads 68
9747 A Review on Modeling and Optimization of Integration of Renewable Energy Resources (RER) for Minimum Energy Cost, Minimum CO₂ Emissions and Sustainable Development, in Recent Years

Authors: M. M. Wagh, V. V. Kulkarni

Abstract:

The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

Procedia PDF Downloads 347