Search results for: deep networks

Authors: Hammadi Larbi, Bergane Cheikh

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Drilling for oil is done through many mechanisms. The goal is first to dig deep and then, after arriving at the oil source, to simply suck it up. And for this, it is important to know the role of oil-based drilling muds, which had many benefits for the drilling tool and for drilling generally, and also and essentially to know the rheological behavior of the emulsion system in particular water-in-oil inverse emulsions (Water/crude oil). This work contributes to the improvement of the stability and rheological properties of crude oil-based drilling mud by organophilic clay. Experimental data from steady-state flow measurements of crude oil-based drilling mud are classically analyzed by the Herschel-Bulkley model. The effects of organophilic clay type VG69 are studied. Microscopic observation showed that the addition of quantities of organophilic clay type VG69 less than or equal to 3 g leads to the stability of inverse Water/Oil emulsions; on the other hand, for quantities greater than 3g, the emulsions are destabilized.

Keywords: drilling, organophilic clay, crude oil, stability

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Nam Chol Yu, GyongIl Chu, HoJong Ri

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Using DLTS (Deep-level transient spectroscopy) measurement techniques, we determined the dominant recombination center levels (defects of both A and B) in gold and platinum doped n-type silicon. Also, the injection and temperature dependence of the Shockley-Read-Hall (SRH) carrier lifetime was studied under low-level injection and high-level injection. Here measurements show that the dominant level under low-level injection located at EC-0.25 eV (A) correlated to the Pt+G1 and the dominant level under high-level injection located at EC-0.54 eV (B) correlated to the Au+G4. Finally, A and B are the same dominant levels for controlling the lifetime in gold-platinum doped n-silicon.

Keywords: recombination center level, lifetime, carrier lifetime control, Gold, Platinum, Silicon

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Authors: Fotis I. Giasemis, Alexandros Sopasakis

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This study focuses on detecting traffic anomalies using generative models applied to real-time observations. By integrating a Graph Neural Network with an attention-based mechanism within the Spatiotemporal Generative Adversarial Network framework, we enhance the capture of both spatial and temporal dependencies in traffic data. Leveraging minute-by-minute observations from cameras distributed across Gothenburg, our approach provides a more detailed and precise anomaly detection system, effectively capturing the complex topology and dynamics of urban traffic networks.

Keywords: traffic, anomaly detection, GNN, GAN

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Authors: M. Tsebia, H. Bentarzi

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In the inter-connected power systems, a phenomenon called inter-area oscillation may be caused by several defects. In this paper, a study of the Maghreb countries inter-area power networks oscillation has been investigated. The inter-area oscillation monitoring can be enhanced by integrating Phasor Measurement Unit (PMU) technology installed in different places. The data provided by PMU and recorded by PDC will be used for the monitoring, analysis, and control purposes. The proposed approach has been validated by simulation using MATLAB/Simulink.

Keywords: PMU, inter-area oscillation, Maghrebian power system, Simulink

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Pawan Kumar, Dhananjoy Shaw, Manoj Kumar Rathi

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Purpose of the study were to compare between (a) frequencies among the four quartiles of percentile norms of autonomic variables from power events and (b) frequencies among the four quartiles percentile norms of autonomic variables from aerobic events of Indian sportspersons withdrawn from competitive games and sports in regard to number of samples falling in each quartile. The study was conducted on 430 males of 30 to 35 years of age. Based on the nature of game/sports the retired sportspersons were classified into power events (throwers, judo players, wrestlers, short distance swimmers, cricket fast bowlers and power lifters) and aerobic events (long distance runners, long distance swimmers, water polo players). Date was collected using ECG polygraphs. Data were processed and extracted using frequency domain analysis and time domain analysis. Collected data were computed with frequency, percentage of each quartile and finally the frequencies were compared with the chi square analysis. The finding pertaining to norm reference comparison of frequencies among the four quartiles of Indian sportspersons withdrawn from competitive games and sports from (a) power events suggests that frequency distribution in four quartile namely Q1, Q2, Q3, and Q4 are significantly different at .05 level in regard to variables namely, SDNN, Total Power (Absolute Power), HF (Absolute Power), LF (Normalized Power), HF (Normalized Power), LF/HF ratio, deep breathing test, expiratory respiratory ratio, valsalva manoeuvre, hand grip test, cold pressor test and lying to standing test, whereas, insignificantly different at .05 level in regard to variables namely, SDSD, RMSSD, SDANN, NN50 Count, pNN50 Count, LF (Absolute Power) and 30: 15 Ratio (b) aerobic events suggests that frequency distribution in four quartile are significantly different at .05 level in regard to variables namely, SDNN, LF (Normalized Power), HF (Normalized Power), LF/HF ratio, deep breathing test, expiratory respiratory ratio, hand grip test, cold pressor test, lying to standing test and 30: 15 ratio, whereas, insignificantly different at .05 level in regard to variables namely, SDSD, RMSSD. SDANN, NN50 count, pNN50 count, Total Power (Absolute Power), LF(Absolute Power) HF(Absolute Power), and valsalva manoeuvre. The study concluded that comparison of frequencies among the four quartiles of Indian retired sportspersons from power events and aerobic events are different in four quartiles in regard to selected autonomic functions, hence the developed percentile norms are not homogenously distributed across the percentile scale; hence strengthen the percentage distribution towards normal distribution.

Keywords: power, aerobic, absolute power, normalized power

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Authors: A. Assad, T. Zayed

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Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

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Authors: Amel Ltifi, Ahmed Zouinkhi, Mohamed Salim Bouhlel

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Security and trust management in Vehicular Ad-hoc NETworks (VANET) is a crucial research domain which is the scope of many researches and domains. Although, the majority of the proposed trust management systems for VANET are based on specific road infrastructure, which may not be present in all the roads. Therefore, road security should be managed by vehicles themselves. In this paper, we propose a new Self Organized Trust Management system (SOTM). This system has the responsibility to cut with the spread of false warnings in the network through four principal components: cooperation, trust management, communication and security.

Keywords: ative vehicle, cooperation, trust management, VANET

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Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

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Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

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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: 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: 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: 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: Asia Majeed

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The learning of mathematics in science, engineering and social science programs can be enhanced through practical problem-solving techniques. The instructors can design their lessons with some strategies to improve students’ educational needs and accomplishments in mathematics classrooms. The use of technology in class problem solving and application sessions can enhance deep understanding of mathematics among students. As mathematician, we believe in subject specific and content-driven teaching methods. Through technology the relationship between the physical problems and the mathematical models can be analyzed. This paper is about selective use of technology in mathematics classrooms and helpful to others mathematics instructors who wishes to improve their traditional teaching techniques to improve students’ attitude in learning mathematics. These techniques corpus can be used in teaching large mathematics classes in science, technology, engineering, and social science.

Keywords: attitude in learning mathematics, mathematics, non-mathematics undergraduate students, technology

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Authors: Ren-Jieh Kuo, Chun-Shou Huang

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The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractively. Thus, this study intends to introduce the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN and LR to forecast the flavor of grapes juice in real data, the result shows that SVR is more suitable and effective at predicting performance.

Keywords: flavor forecasting, artificial neural networks, Support Vector Regression, China

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Authors: Qiankun Zhong

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In a global cultural context, film festival awards become authorities to define the aesthetic value of films. To study which genres and producing countries are valued by different film festivals and how those evaluations interact with each other, this research explored the interactions between the film festivals through their selection of movies and the factors that lead to the tendency of film festivals to nominate the same movies. To do this, the author employed a two-mode network on the movies that won the highest awards at five international film festivals with the highest attendance in the past ten years (the Venice Film Festival, the Cannes Film Festival, the Toronto International Film Festival, Sundance Film Festival, and the Berlin International Film Festival) and the film festivals that nominated those movies. The title, genre, producing country and language of 50 movies, and the range (regional, national or international) and organizing country or area of 129 film festivals were collected. These created networks connected by nominating the same films and awarding the same movies. The author then assessed the density and centrality of these networks to answer the question: What are the film festivals that tend to have more shared values with other festivals? Based on the Eigenvector centrality of the two-mode network, Palm Springs, Robert Festival, Toronto, Chicago, and San Sebastian are the festivals that tend to nominate commonly appreciated movies. In contrast, Black Movie Film Festival has the unique value of generally not sharing nominations with other film festivals. A homophily test was applied to access the clustering effects of film and film festivals. The result showed that movie genres (E-I index=0.55) and geographic location (E-I index=0.35) are possible indicators of film festival clustering. A blockmodel was also created to examine the structural roles of the film festivals and their meaning in real-world context. By analyzing the same blocks with film festival attributes, it was identified that film festivals either organized in the same area, with the same history, or with the same attitude on independent films would occupy the same structural roles in the network. Through the interpretation of the blocks, language was identified as an indicator that contributes to the role position of a film festival. Comparing the result of blockmodeling in the different periods, it is seen that international film festivals contrast with the Hollywood industry’s dominant value. The structural role dynamics provide evidence for a multi-value film festival network.

Keywords: film festivals, film studies, media industry studies, network analysis

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

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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: John Ayoade

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Cloud computing is a model that enables the delivery of on-demand computing resources such as networks, servers, storage, applications and services over the internet. Cloud Computing is a relatively growing concept that presents a good number of benefits for its users; however, it also raises some security challenges which may slow down its use. In this paper, we identify some of those security issues that can serve as barriers to realizing the full benefits that cloud computing can bring. One of the key security problems is security trust. A security trust model is proposed that can enhance the confidence that users need to fully trust the use of public and mobile cloud computing and maximize the potential benefits that they offer.

Keywords: cloud computing, trust, security, certificate authority, PKI

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Authors: Danuvasin Charoen

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Online romance scams are conducted by criminals using social networks and dating sites. These criminals use love to deceive the victims to send them money. The victims not only lose money to the criminals, but they are also heartbroken. This study investigates how online romance scams work and why people become victims to them. The researcher also identifies the characteristics of the perpetrators and victims. The data were collected from in-depth interviews with former victims and police officers responsible for the cases. By studying the methods and characteristics of the online romance scam, we can develop effective methods and policies to reduce the rates of such crimes.

Keywords: romance scam, online scam, phishing, cybercrime

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Authors: Surita Maini

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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

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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: Amin Hamrahi, Niloofar Moghaddam

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Denial of Service is for denial-of-service attack, a type of attack on a network that is designed to bring the network to its knees by flooding it with useless traffic. Denial of Service (DoS) attacks have become a major threat to current computer networks. Many recent DoS attacks were launched via a large number of distributed attacking hosts in the Internet. These attacks are called distributed denial of service (DDoS) attacks. To have a better understanding on DoS attacks, this article provides an overview on existing DoS and DDoS attacks and major defense technologies in the Internet.

Keywords: denial of service, distributed denial of service, traffic, flooding

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Authors: C. P. Autry, A.W. Roscoe

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Authentication protocols based on public key infrastructure (PKI) and trusted third party (TTP) are no longer adequate for industrial scale IoT networks thanks to issues such as low compute and power availability, the use of widely distributed and commercial off-the-shelf (COTS) systems, and the increasingly sophisticated attackers and attacks we now have to counter. For example, there is increasing concern about nation-state-based interference and future quantum computing capability. We have examined this space from first principles and have developed several approaches to group and point-to-point authentication for IoT that do not depend on the use of a centralised client-server model. We emphasise the use of quantum resistant primitives such as strong cryptographic hashing and the use multi-factor authentication.

Keywords: authentication, enterprise IoT cybersecurity, PKI/TTP, IoT space

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Authors: Ayanda Magida, Brian Armstrong

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The study aimed to assess the third level of the digital divide among the millennials and post-millennials in South Africa. The millennials are people born from 1981-to 1996, that is, people between the ages of 25-40 years old and post-millennials are people born from 1997 to date. For the study, only post-millennials born between 1997-2003 were included as they were old enough to consent to participation in the study. Data was collected as part of the Ph.D. project that focuses on the relationship between income inequality, the digital divide, and social cohesion in South Africa. The digital divide has three main levels, namely the first, second and third. The first and second focus on access and usage, respectively. The third-level digital divide can be defined as the differences in the benefits associated with being online. The current paper focuses on the third level: the benefits derived by being online using four domains: economic, educational, social, and personal benefits. The economic benefits include income, employment and finance-related activities; the social benefits include socializing belonging, identity, and informal networks. The personal benefits include personal wellbeing and self-actualization. A total of 763 participants completed the survey, and 61.3% were post-millennials between the ages of 18-24 and s 38.6 % were millennials between 25 and 40. The majority of the respondents were female (62%), male (34%) and nonbinary (1%), respectively. Most of the respondents were black, followed by whites, Indians and colored, respectively. Thus, they represented the status of the demographics of the country. Most of the respondents had access to the internet and smartphone. Most expressed that they use laptops (68%) or mobile (71%) to access the internet and 54 % access the internet using wireless/Wi-Fi. There were no differences between the millennial and post-millennial economic and educational benefits of being online. However, the post-millennials were more inclined to use the internet for social and personal benefits than the millennials. This could be attributed to many factors, such as age. The post-millennials are still discovering themselves and therefore would derive social and personal benefits associated with being online. The findings confirm studies that argue that younger generations derive more benefits from being online than the older generation. Based on the findings, it is evident that the post-millennials are not using the internet or online activities for social networks and socializing but can derive economic benefits such as job looking and education benefits from being online. It can be inferred that there are no significant differences between the two groups, and it seems like the third-level digital divide is not evident among the two groups as they both have been able to derive meaningful benefits from being online. Further studies should focus on the third-level divide between the baby boomers and Generation X.

Keywords: third-level digital divide, millennials, post-millennials, online activities

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Authors: Adeep Hande, Shubham Agarwal

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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: A. Bhandari, S. Mukherjee

Abstract:

Two frames in a Hilbert space are called woven or weaving if all possible merge combinations between them generate frames of the Hilbert space with uniform frame bounds. Weaving frames are powerful tools in wireless sensor networks which require distributed data processing. Considering the practical applications, this article deals with finite woven frames. We provide methods of constructing finite woven frames, in particular, bounded linear operators are used to construct woven frames from a given frame. Several examples are discussed. We also introduce the notion of woven frame sequences and characterize them through the concepts of gaps and angles between spaces.

Keywords: frames, woven frames, gap, angle

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Authors: Beatriz Martinez-Pastor, Maria Nogal, Alan O'Connor

Abstract:

During the last years, the number of extreme weather events has increased. A variety of extreme weather events, including river floods, rain-induced landslides, droughts, winter storms, wildfire, and hurricanes, have threatened and damaged many different regions worldwide. These events have a devastating impact on critical infrastructure systems resulting in high social, economical and environmental costs. These events have a huge impact in transport systems. Since, transport networks are completely exposed to every kind of climatological perturbations, and its performance is closely related with these events. When a traffic network is affected by a climatological hazard, the quality of its service is threatened, and the level of the traffic conditions usually decreases. With the aim of understanding this process, the concept of resilience has become most popular in the area of transport. Transport resilience analyses the behavior of a traffic network when a perturbation takes place. This holistic concept studies the complete process, from the beginning of the perturbation until the total recovery of the system, when the perturbation has finished. Many concepts are included in the definition of resilience, such as vulnerability, redundancy, adaptability, and safety. Once the resilience of a transport network can be evaluated, in this case, the methodology used is a dynamic equilibrium-restricted assignment model that allows the quantification of the concept, the next step is its improvement. Through the improvement of this concept, it will be possible to create transport networks that are able to withstand and have a better performance under the presence of climatological hazards. Analyzing the impact of a perturbation in a traffic network, it is observed that the response of the different links, which are part of the network, can be completely different from one to another. Consequently and due to this effect, many questions arise, as what makes a link more critical before an extreme weather event? or how is it possible to identify these critical links? With this aim, and knowing that most of the times the owners or managers of the transport systems have limited resources, the identification of the critical links of a transport network before extreme weather events, becomes a crucial objective. For that reason, using the available resources in the areas that will generate a higher improvement of the resilience, will contribute to the global development of the network. Therefore, this paper wants to analyze what kind of characteristic makes a link a critical one when an extreme weather event damages a transport network and finally identify them.

Keywords: critical links, extreme weather events, hazard, resilience, transport network

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Authors: Babak Forouraghi

Abstract:

A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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