Search results for: deep vibro techniques

Authors: Alam Anshary, Flora Pasaru, Shahabuddin

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The Cocoa Pod Borer (CPB), Conopomorpha cramerella (Snell.) is present on most of the larger cocoa producing islands in Indonesia. Various control measures CPB has been carried out by the farmers, but the results have not been effective. This study aims to determine the effect of application of Beauveria bassiana treatments and pruning technique to the control of CPB in the cocoa plantation people. Research using completely randomized design with 4 treatments and 3 replications, treatment consists of B.bassiana, Pruning, B. bassiana+pruning (Bb + Pr), as well as the control. The results showed that the percentage of PBK attack on cocoa pods in treatment (Bb + Pr) 3.50% the lowest compared to other treatments. CPB attack percentage in treatment B.bassiana 6.15%; pruning 8.75%, and 15.20% control. Results of the analysis of production estimates, the known treatments (Bb + Pr) have the highest production (1.95 tonnes / ha). The model results estimated production is Y= 0,20999 + 0,53968X1 + 0,34298X2+ 0,31410X3 + 0,35629X4 + 0,08345X5 + 0,29732X6. Farm production costs consist of fixed costs and variable costs, fixed costs are costs incurred by the farmer that the size does not affect the results, such as taxes and depreciation of production equipment. Variable costs are costs incurred by farmers who used up in one year cocoa farming activities. The cost of production in farming cocoa without integrated techniques control of CPB is Rp. 9.205.550 million/ha, while the cost of production with integrated techniques control is Rp. 6.666.050 million/ha.

Keywords: cacao, cocoa pod borer, pruning, Beauveria bassiana, production costs

Procedia PDF Downloads 285

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

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The purpose of this paper is to describe the growing problem of various cyber fraud schemes that exist on the internet and are currently among the most prevalent. The main focus of this paper is to provide a detailed description of the modus operandi, tools, and techniques utilized in four basic typologies of cyber frauds: Business Email Compromise (BEC) attacks, investment fraud, romance scams, and online sales fraud. The paper aims to shed light on the methods employed by cybercriminals in perpetrating these types of fraud, as well as the strategies they use to deceive and victimize individuals and businesses on the internet. Furthermore, this study outlines defense strategies intended to tackle the issue head-on, with a particular emphasis on the crucial role played by European Legislation. European legislation has proactively adapted to the evolving landscape of cyber fraud, striving to enhance cybersecurity awareness, bolster user education, and implement advanced technical controls to mitigate associated risks. The paper evaluates the advantages and innovations brought about by the European Legislation while also acknowledging potential flaws that cybercriminals might exploit. As a result, recommendations for refining the legislation are offered in this study in order to better address this pressing issue.

Keywords: business email compromise, cybercrime, European legislation, investment fraud, NIS, online sales fraud, romance scams

Procedia PDF Downloads 98

Authors: Chor Yi Ng, Christine Kong, Loretta Teo, Stephen Yau, FC Cheung, TL Poon, Francis Lee

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Purpose: Dynamic conformal arc (DCA) and intensity modulated radiotherapy (IMRT) are two treatment techniques commonly used for stereotactic radiosurgery/radiotherapy of cranial lesions. IMRT plans usually give better dose conformity while DCA plans have better dose fall off. Rapid dose fall off is preferred for radiotherapy of cranial lesions, but dose conformity is also important. For certain lesions, DCA plans have good conformity, while for some lesions, the conformity is just unacceptable with DCA plans, and IMRT has to be used. The choice between the two may not be apparent until each plan is prepared and dose indices compared. We described a deviation index (DI) which is a measurement of the deviation of the target shape from a sphere, and test its functionality to choose between the two techniques. Method and Materials: From May 2015 to May 2017, our institute has performed stereotactic radiotherapy for 105 patients treating a total of 115 lesions (64 DCA plans and 51 IMRT plans). Patients were treated with the Varian Clinac iX with HDMLC. Brainlab Exactrac system was used for patient setup. Treatment planning was done with Brainlab iPlan RT Dose (Version 4.5.4). DCA plans were found to give better dose fall off in terms of R50% (R50% (DCA) = 4.75 Vs R50% (IMRT) = 5.242) while IMRT plans have better conformity in terms of treatment volume ratio (TVR) (TVR(DCA) = 1.273 Vs TVR(IMRT) = 1.222). Deviation Index (DI) is proposed to better facilitate the choice between the two techniques. DI is the ratio of the volume of a 1 mm shell of the PTV and the volume of a 1 mm shell of a sphere of identical volume. DI will be close to 1 for a near spherical PTV while a large DI will imply a more irregular PTV. To study the functionality of DI, 23 cases were chosen with PTV volume ranged from 1.149 cc to 29.83 cc, and DI ranged from 1.059 to 3.202. For each case, we did a nine field IMRT plan with one pass optimization and a five arc DCA plan. Then the TVR and R50% of each case were compared and correlated with the DI. Results: For the 23 cases, TVRs and R50% of the DCA and IMRT plans were examined. The conformity for IMRT plans are better than DCA plans, with majority of the TVR(DCA)/TVR(IMRT) ratios > 1, values ranging from 0.877 to1.538. While the dose fall off is better for DCA plans, with majority of the R50%(DCA)/ R50%(IMRT) ratios < 1. Their correlations with DI were also studied. A strong positive correlation was found between the ratio of TVRs and DI (correlation coefficient = 0.839), while the correlation between the ratio of R50%s and DI was insignificant (correlation coefficient = -0.190). Conclusion: The results suggest DI can be used as a guide for choosing the planning technique. For DI greater than a certain value, we can expect the conformity for DCA plans to become unacceptably great, and IMRT will be the technique of choice.

Keywords: cranial lesions, dynamic conformal arc, IMRT, image guided radiotherapy, stereotactic radiotherapy

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Authors: Elif Doğru, Bülent Kızılduman, Huriye İcil

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Throughout history, Cyprus has been involved in various commercial and cultural relationships with different civilizations, owing to its strategic location. Particularly during the Late Bronze Age, Cyprus emerged as a significant region engaged in interactions with the Mycenaeans and other Mediterranean civilizations. Presently, findings from archaeological excavations provide valuable insights into Cyprus' cultural history and its connections with other civilizations. Painted Mycenaean ceramics discovered during the excavations at Kaleburnu-Kral Tepesi (Galinaporni-Vasili), dated to the Late Bronze Age in Cyprus, are considered significant archaeological findings that carry traces of the art and culture of that era, reflecting the island's commercial and cultural connections. Considering these findings, there is a need for archaeometric studies to aid in the understanding of the commercial and cultural ties at Kaleburnu-Kral Tepesi. In line with this need, analytical studies have been initiated concerning the provenance and production techniques of the Mycenaean ceramics discovered in the excavations at Kaleburnu-Kral Tepesi, dated to the Late Bronze Age. In the context of origin analysis studies, it is advocated that understanding the techniques and materials used for the figures and designs applied on Mycenaean ceramics would significantly contribute to a better comprehension of historical contexts. Hence, the adopted approach involves not only the analysis of the ceramic raw material but also the characterization of the pigments on the ceramics as a whole. In light of this, in addition to the studies aimed at determining the provenance and production techniques of the Mycenaean ceramic bodies, the characterization of the pigments used in the decorations of the relevant ceramics has been included in the research scope. Accordingly, this study aims to characterize the pigments used in the decorations of Mycenaean ceramics discovered at Kaleburnu-Kral Tepesi, dated to the Late Bronze Age. The X-Ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM-EDX) methods have been employed to determine the surface morphology and chemical properties of the Mycenaean pigments. The characterization has been conducted through the combination of multiple analytical methods. The characterization of the pigments of Mycenaean ceramics aims to enhance the scientific perspective adopted for understanding the contributions of Mycenaean ceramics found in Cyprus to the island's culture, by providing scientific data on the types and origins of pigments used during the Late Bronze Age.

Keywords: mycenaean, ceramic, provenance, pigment

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Authors: Lene Granzau Juel-Jacobsen

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The problem of beautification is an obvious concern of photography, claiming reference to reality, but it also lies at the very heart of social theory. As we become accustomed to sophisticated visualizations of statistical data in pace with the development of software programs, we should not only be inclined to ask new types of research questions, but we also need to confront social theories based on such visualization techniques with new types of questions. Correspondence Analysis, GIS analysis, Social Network Analysis, and Perceptual Maps are current examples of visualization techniques popular within the social sciences and neighboring disciplines. This article discusses correspondence analysis, arguing that the graphic plot of correspondence analysis is to be interpreted much similarly to a photograph. It refers no more evidently or univocally to reality than a photograph, representing social life no more truthfully than a photograph documents. Pierre Bourdieu’s theoretical corpus, especially his theory of fields, relies heavily on correspondence analysis. While much attention has been directed towards critiquing the somewhat vague conceptualization of habitus, limited focus has been placed on the equally problematic concepts of social space and field. Based on a re-reading of the Distinction, the article argues that the concepts rely on ‘a small graphic lie’ very similar to a photograph. Like any other piece of art, as Bourdieu himself recognized, the graphic display is a politically and morally loaded representation technique. However, the correspondence analysis does not necessarily serve the purpose he intended. In fact, it tends towards the pitfalls he strove to overcome.

Keywords: datavisualization, correspondance analysis, bourdieu, Field, visual representation

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Authors: Saeed Delara, Kendra MacKay

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Varying methodologies are considered for pile design for both Russian and Western approaches. Although both approaches rely on toe and side frictional resistances, different calculation methods are proposed to estimate pile capacity. The Western approach relies on compactness (internal friction angle) of soil for cohesionless soils and undrained shear strength for cohesive soils. The Russian approach relies on grain size for cohesionless soils and liquidity index for cohesive soils. Though most recommended methods in the Western approaches are relatively simple methods to predict pile settlement, the Russian approach provides a detailed method to estimate single pile and pile group settlement. Details to calculate pile axial capacity and settlement using the Russian and Western approaches are discussed and compared against field test results.

Keywords: pile capacity, pile settlement, Russian approach, western approach

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Authors: Megh Patel, Arjun Chauhan, Jay Thakkar

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Hydrofracturing is the most prominent but at the same time expensive, highly skilled and time consuming well stimulation technique. Due to high cost and skilled labor involved, it is generally carried out as the consummate solution among other well stimulation techniques. Considering today’s global petroleum market, no gaffe or complications could be entertained during fracturing, as it would further hamper the current dwindling economy. The literature would be dealing with the challenges encountered during fracturing low temperature waxy reservoirs and the prominent solutions to overcome such teething troubles. During fracturing treatment for, shallow and high freezing point waxy oil reservoirs, the first line problems are to overcome uncompleted breakdown, uncompleted cleanup of fracturing fluids and cold damages to the formations by injecting cold fluid (fluid at ambient conditions). Injecting fracturing fluids at ambient conditions have the tendency to decrease the near wellbore reservoir temperature below the freezing point of oil reservoir and hence leading to wax deposition around the wellbore thereby hampering the fluid production as well as fracture propagation. To overcome such problems, solutions such as hot fracturing fluid injection, encapsulated heat generating hydraulic fracturing fluid system, and injection of wax inhibitor techniques would be discussed. The paper would also be throwing light on changes in rheological properties occurred during heating fracturing fluids and solutions to deal with it taking economic considerations into account.

Keywords: hydrofracturing, waxy reservoirs, low temperature, viscosity, crosslinkers

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Authors: M. Koray Cetin, Mehmet Mert

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The purpose of the study is to examine impacts on tourism revenues of the exchange rate and country overall security level. There are numerous studies that examine the bidirectional relation between macroeconomic factors and tourism revenues and tourism demand. Most of the studies support the existence of impact of tourism revenues on growth rate but not vice versa. Few studies examine the impact of factors like real exchange rate or purchasing power parity on the tourism revenues. In this context, firstly impact of real exchange rate on tourism revenues examination is aimed. Because exchange rate is one of the main determinants of international tourism services price in guests currency unit. Another determinant of tourism demand for a country is country’s overall security level. This issue can be handled in the context of the relationship between tourism revenues and overall security including turmoil, terrorism, border problem, political violence. In this study, factors are handled for several countries which have tourism revenues on a certain level. With this structure, it is a panel data, and it is evaluated with panel data analysis techniques. Panel data have at least two dimensions, and one of them is time dimensions. The panel data analysis techniques are applied to data gathered from Worldbank data web page. In this study, it is expected to find impacts of real exchange rate and security factors on tourism revenues for the countries that have noteworthy tourism revenues.

Keywords: exchange rate, panel data analysis, security, tourism revenues

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Authors: Devon Brown, Liu Chunmei

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This paper will present an analysis as part of the researchers dissertation topic focusing on the intersection of affective and analytical directed acyclic graphs (DAGs) in the context of Decision Support Systems (DSS). The researcher’s work involves analyzing decision theory models like Affective and Bayesian Decision theory models and how they could be implemented under an Affective Computing Framework using Information Fusion and Human-Centered Design. Additionally, the researcher is beginning research on an Affective-Analytic Decision Framework (AADF) model for their dissertation research and are looking to merge logic and analytic models with empathetic insights into affective DAGs. Data-collection efforts begin Fall 2024 and in preparation for the efforts this paper looks to analyze previous research in this area and introduce the AADF framework and propose conceptual models for consideration. For this paper, the research emphasis is placed on analyzing Bayesian networks and Markov models which offer probabilistic techniques during uncertainty in decision-making. Ideally, including affect into analytic models will ensure algorithms can increase user trust with algorithms by including emotional states and the user’s experience with the goal of developing emotionally intelligent A.I. systems that can start to navigate the complex fabric of human emotion during decision-making.

Keywords: decision support systems, explainable AI, HCAI techniques, affective-analytical decision framework

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Thayalan Nall, Harry Poulos

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Piling is the most widely used foundation method for heavy structures in poor soil conditions. The geotechnical engineer can choose among a variety of piling methods, but in most cases, driving piles by impact hammer is the most cost-effective alternative. Under unfavourable conditions, driving piles can cause environmental problems, such as noise, ground movements and vibrations, with the risk of ground disturbance leading to potential damage to proposed structures. In one of the project sites in which the authors were involved, three offshore container terminals, namely CT1, CT2 and CT3, were constructed over thick compressible marine mud. The seabed was around 6m deep and the soft clay thickness within the project site varied between 9m and 20m. CT2 and CT3 were connected together and rectangular in shape and were 2600mx800m in size. CT1 was 400m x 800m in size and was located on south opposite of CT2 towards its eastern end. CT1 was constructed first and due to time and environmental limitations, it was supported on a “forest” of large diameter driven piles. CT2 and CT3 are now under construction and are being carried out using a traditional dredging and reclamation approach with ground improvement by surcharging with vertical drains. A few months after the installation of the CT1 piles, a 2600m long sand bund to 2m above mean sea level was constructed along the southern perimeter of CT2 and CT3 to contain the dredged mud that was expected to be pumped. The sand bund was constructed by sand spraying and pumping using a dredging vessel. About 2000m length of the sand bund in the west section was constructed without any major stability issues or any noticeable distress. However, as the sand bund approached the section parallel to CT1, it underwent a series of deep seated failures leading the displaced soft clay materials to heave above the standing water level. The crest of the sand bund was about 100m away from the last row of piles. There were no plausible geological reasons to conclude that the marine mud only across the CT1 region was weaker than over the rest of the site. Hence it was suspected that the pile driving by impact hammer may have caused ground movements and vibrations, leading to generation of excess pore pressures and cyclic softening of the marine mud. This paper investigates the probable cause of failure by reviewing: (1) All ground investigation data within the region; (2) Soil displacement caused by pile driving, using theories similar to spherical cavity expansion; (3) Transfer of stresses and vibrations through the entire system, including vibrations transmitted from the hammer to the pile, and the dynamic properties of the soil; and (4) Generation of excess pore pressure due to ground vibration and resulting cyclic softening. The evidence suggests that the problems encountered at the site were primarily caused by the “side effects” of the pile driving operations.

Keywords: pile driving, ground vibration, excess pore pressure, cyclic softening

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Authors: Satish Kumar Peddapelli

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This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have become popular and considerable interest by researcher are given on them. A fast Space-Vector Pulse Width Modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analysed.

Keywords: five-level inverter, space vector pulse wide modulation, diode clamped inverter, electrical engineering

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Authors: Eng Lye, Ooi

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The Old Man and The Sea is a novella written by Ernest Hemingway that depicts an old fisherman’ journey out into the deep sea in his pursuit to catch a big fish. Through this novella, Hemingway creates a world for his protagonist, Santiago who is portrayed as an old man who has gone eighty-four days without catching a fish, at last hooks an eighteen-foot marlin, the largest he ever known. The old man endures pain and struggles to bring back to shore. Looking through the lens of gerotranscendence, we can see that the old man has his dreams, and goals in life. In his pursuit for happiness, he has fought tirelessly to ward off the shark attacks and finally he won even though only half of his fish is left. Hemingway has portrayed Santiago as an old man as a transcendent self leaping from the dimension of “The Self” to the cosmic dimension with the personal and social relationship dimension in tow. The Old Man and The Sea offers a glimpse of the struggles of an old man, who is old and gaunt but spiritually undefeated in his battle out in the sea. He is surprisingly strong and powerful despite his old age, he respects the sea, the birds. the turtles, the sharks and the fish. He can endure suffering and is focussed on achieving his goals. This is what Hemingway has portrayed Santiago to be a gerotranscendent in the eyes of the gerotranscendental approach in respect of the changes and development as seen in Santiago, the protagonist in this novella.

Keywords: gerotranscendence, gerotranscendenatal, old man, the sea, hemingway

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Authors: Kirstin Burger, Paul Watts, Nicole Vorster

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Green chemistry focuses on synthesis which has a low negative impact on the environment. This research focuses on synthesizing novel compounds from an all-natural Eucalyptus citriodora oil. Eight novel plasticizer compounds are synthesized and optimized using flow chemistry technology. A precursor to one novel compound can be synthesized from the lauric acid present in coconut oil. Key parameters, such as catalyst screening and loading, reaction time, temperature, residence time using flow chemistry techniques is investigated. The compounds are characterised using GC-MS, FT-IR, 1H and 13C-NMR techniques, X-ray crystallography. The efficiency of the compounds is compared to two commercial plasticizers, i.e. Dibutyl phthalate and Eastman 168. Several PVC-plasticized film formulations are produced using the bio-based novel compounds. Tensile strength, stress at fracture and percentage elongation are tested. The property of having increasing plasticizer percentage in the film formulations is investigated, ranging from 3, 6, 9 and 12%. The diastereoisomers of each compound are separated and formulated into PVC films, and differences in tensile strength are measured. Leaching tests, flexibility, and change in glass transition temperatures for PVC-plasticized films is recorded. Research objective includes using these novel compounds as a green bio-plasticizer alternative in plastic products for infants. The inhibitory effect of the compounds on six pathogens effecting infants are studied, namely; Escherichia coli, Staphylococcus aureus, Shigella sonnei, Pseudomonas putida, Salmonella choleraesuis and Klebsiella oxytoca.

Keywords: bio-based compounds, plasticizer, tensile strength, microbiological inhibition , synthesis

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: Jae Soo Do, Kyoung-Seok Kim

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Radical changes in the industrial environment, and spectacular developments of IT have changed the current of managements from people-centered to technology- or IT-centered. Interpersonal emotion exchanges have long become insipid and interactive services have also come as mechanical reactions. This study offers various concepts for the emotional labor based on traditional studies on emotional labor. Especially the present day, on which human emotions are subject to being served as machinized thing, is the time when the study on human emotions comes momentous. Precedent researches on emotional labors commonly and basically dealt with the relationship between the active group who performs actions and the passive group who is done with the action. This study focuses on the passive group and tries to offer a new perspective of 'liquid emotion' as a defence mechanism for the passive group from the external environment. Especially, this addresses a concrete discussion on directions of following studies on the liquid labor as a newly suggested perspective.

Keywords: emotion labor, surface acting, deep acting, liquid emotion

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: Mateusz Paszko, Ksenia Siadkowska

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Due to the low-altitude and relatively low-speed flight, helicopters are easy targets for actual combat assets e.g. infrared-guided missiles. Current techniques aim to increase the combat effectiveness of the military helicopters. Protection of the helicopter in flight from early detection, tracking and finally destruction can be realized in many ways. One of them is cooling hot exhaust gasses, emitting from the engines to the atmosphere in special heat exchangers. Nowadays, this process is realized in ejective coolers, where strong heat and momentum exchange between hot exhaust gases and cold air ejected from atmosphere takes place. Flow effects of air, exhaust gases; mixture of those two and the heat transfer between cold air and hot exhaust gases are given by differential equations of: Mass transportation–flow continuity, ejection of cold air through expanding exhaust gasses, conservation of momentum, energy and physical relationship equations. Calculation of those processes in ejective cooler by means of classic mathematical analysis is extremely hard or even impossible. Because of this, it is necessary to apply the numeric approach with modern, numeric computer programs. The paper discussed the general usability of the Computational Fluid Dynamics (CFD) in a process of projecting the ejective exhaust gases cooler cooperating with helicopter turbine engine. In this work, the CFD calculations have been performed for ejective-based cooler cooperating with the PA W3 helicopter’s engines.

Keywords: aviation, CFD analysis, ejective-cooler, helicopter techniques

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

Abstract:

Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

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Authors: Safwat E. Musa, Nuha E. Mohamed, Nuha A. Bagi

Abstract:

In this study, several crossplots of the P-impedance with the lithology logs (gamma ray, neutron porosity, deep resistivity, water saturation and Vp/Vs curves) were made in three available wells, which were drilled in central part of the Blue Nile basin in depths varies from 1460 m to 1600 m. These crossplots were successful to discriminate between sand and shale when using P-Impedance values, and between the wet sand and the pay sand when using both P-impedance and Vp/Vs together. Also, some impedance sections were converted to porosity sections using linear formula to characterize the reservoir in terms of porosity. The used crossplots were created on log resolution, while the seismic resolution can identify only the reservoir, unless a 3D seismic angle stacks were available; then it would be easier to identify the pay sand with great confidence; through high resolution seismic inversion and geostatistical approach when using P-impedance and Vp/Vs volumes.

Keywords: basin, Blue Nile, inversion, seismic

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Authors: Surita Maini

Abstract:

There are many perceived advantages of microwave ablation have driven researchers to develop innovative antennas to effectively treat deep-seated, non-resectable hepatic tumors. In this paper a coaxial antenna with a miniaturized sleeve choke has been discussed for microwave interstitial ablation therapy, in order to reduce backward heating effects irrespective of the insertion depth into the tissue. Two dimensional Finite Element Method (FEM) is used to simulate and measure the results of miniaturized sleeve choke antenna. This paper emphasizes the importance of factors that can affect simulation accuracy, which include mesh resolution, surface heating and reflection coefficient. Quarter wavelength choke effectiveness has been discussed by comparing it with the unchoked antenna with same dimensions.

Keywords: microwave ablation, tumor, finite element method, coaxial slot antenna, coaxial dipole antenna

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Authors: Muhammad Feroz-Ud-Din Shah Khagga

Abstract:

The holy Qur’ān, due to its exceptional and unique rhythmic style of expression, seems to have a deep connection with music and elegance of melodiousness of voice, on the other hand, Islam has various authentic transmissions and expound teachings regarding the prevention of music and songs. In this context, there has been a remarkable debate among Islamic scholars, jurists and Qur’ānic scientist to whether it is permissible to use the principles of Arabic musical symphonies, Maqāmāt and melodies in the recitation of the Qur’ān? Some Muslim scholars are convinced of the Sharīʻah legitimacy of the use of music, Maqāmāt and melodies in the recitation of the Qur’ān but some scholars do not consider it permissible. This study is an attempt to discover the factual Muslim jurisprudential experts’ stance on the subject by analyzing the arguments of both groups of scholars. It supports the viewpoint of the opponents, but also tries to reconcile the two positions. It maintains that there is nothing wrong with reciting the Qur’ān in a beautiful voice but it must be free from those forms of music which are not adored in Islamic Sharīʻah.

Keywords: Quranic recitation. maqāmāt, music, lahn, Uloom al-Qur’ān, Quranic sciences

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Authors: Fatai Olakunle Ogundele

Abstract:

Road construction is increasingly common in today's world as human development expands and people increasingly rely on cars for transportation on a daily basis. The construction of a large network of roads has dramatically altered the landscape and impacted well-being in a number of deleterious ways. In addition, the road can also shift population demographics and be a source of pollution into the environment. Road construction activities normally result in changes in alteration of the soil's physical properties through soil compaction on the road itself and on adjacent areas and chemical and biological properties, among other effects. Understanding roadside soil properties that are influenced by road construction activities can serve as a basis for formulating conservation-based management strategies. Therefore, this study examined the effects of road construction on soil properties and soil organic carbon along Lagos Badagry Expressway, Lagos, Nigeria. The study adopted purposive sampling techniques and 40 soil samples were collected at a depth of 0 – 30cm from each of the identified road intersections and infrastructures using a soil auger. The soil samples collected were taken to the laboratory for soil properties and carbon stock analysis using standard methods. Both descriptive and inferential statistical techniques were applied to analyze the data obtained. The results revealed that soil compaction inhibits ecological succession on roadsides in that increased compaction suppresses plant growth as well as causes changes in soil quality.

Keywords: highway, soil properties, organic carbon, road construction, land degradation

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Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

Abstract:

Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

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Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

Abstract:

In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: admissions, algorithms, cloud computing, differentiation, fog computing, levelling, machine learning

Procedia PDF Downloads 142

Authors: Adeep Hande, Shubham Agarwal

Abstract:

This paper presents a study on identifying sexism in online texts using various state-of-the-art deep learning models based on BERT. We experimented with different feature sets and model architectures and evaluated their performance using precision, recall, F1 score, and accuracy metrics. We also explored the use of pseudolabeling technique to improve model performance. Our experiments show that the best-performing models were based on BERT, and their multilingual model achieved an F1 score of 0.83. Furthermore, the use of pseudolabeling significantly improved the performance of the BERT-based models, with the best results achieved using the pseudolabeling technique. Our findings suggest that BERT-based models with pseudolabeling hold great promise for identifying sexism in online texts with high accuracy.

Keywords: large language models, semi-supervised learning, sexism detection, data sparsity

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

Abstract:

Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

Procedia PDF Downloads 130