Search results for: simultaneous sparse representation

Authors: Joudia Akil, Stephane Siffert, Laurence Pirault-Roy, Renaud Cousin, Christophe Poupin

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The CO2 emitted from anthropic activities is perceived as a constraint in industrial activity due to taxes, stringent environmental regulations, impact on global warming… To limit these CO2 emissions, reuse of CO2 represents a promising alternative, with important applications in chemical industry and for power generation. However, CO2 valorization process requires a gas as pure as possible Oxyfuel-combustion that enables obtaining a CO2 rich stream, with water vapor (10%) is then interesting. Nevertheless to decrease the amount of the by-products found with the CO2 (especially CO and NOx which are harmful to the environment) a catalytic treatment must be applied. Nowadays three-way catalysts are well-developed material for simultaneous conversion of unburned hydrocarbons, carbon monoxide (CO) and nitrogen oxides (NOx). The use of Pd attracted considerable attention on the basis of economic factors (the high cost and scarcity of Pt and Rh). This explains the large number of studies concerning the CO-NO reaction on Pd in the recent years. In the present study, we will compare a series of Pd materials supported on different oxides for CO2 purification from the oxyfuel combustion system, by reducing NO with CO in an oxidizing environment containing CO2 rich stream and presence of 8.2% of water. Al2O3, CeO2, MgO, SiO2 and TiO2 were used as support materials of the catalysts. 1wt% Pd/Support catalysts were obtained by wet impregnation on supports with a precursor of palladium [Pd(acac)2]. The obtained samples were subsequently characterized by H2 chemisorption, BET surface area and TEM. Finally, their catalytic performances were evaluated in CO2 purification which is carried out in a fixed-bed flow reactor containing 150 mg of catalyst at atmospheric pressure. The flow of the reactant gases is composed of: 20% CO2, 10% O2, 0.5% CO, 0.02% NO and 8.2% H2O (He as eluent gas) with a total flow of 200mL.min−1, in the same GHSV. The catalytic performance of the Pd catalysts for CO2 purification revealed that: -The support material has a strong influence on the catalytic activity of 1wt.% Pd supported catalysts. depending of the nature of support, the Pd-based catalysts activity changes. -The highest reduction of NO with CO is obtained in the following ranking: TiO2>CeO2>Al2O3. -The supports SiO2 and MgO should be avoided for this reaction, -Total oxidation of CO occurred over different materials, -CO2 purification can reach 97%, -The presence of H2O has a positive effect on the NO reduction due to the production of the reductant H2 from WGS reaction H2O+CO → H2+CO2

Keywords: carbon dioxide, environmental chemistry, heterogeneous catalysis, oxyfuel combustion

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Authors: Pascal Rey, Anaïs Weber

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Many mining projects are being developed in Africa the last decades. Due to the economic opportunities they offer, these projects result in a massive and rapid influx of migrants to the surrounding area. In areas where central government representation is low and local administration lack financial resources, urban development is often anarchical, beyond all public control. It leads to socio-spatial segregation, insecurity and the risk of social conflicts rising. Aware that their economic development is very correlated with local situation, mining companies get more and more involved in regional planning in setting up tools and Strategic Directions document. One of the commonly used tools in this regard is the “Influx Management Plan”. It consists in looking at the region’s absorption capacities in order to ensure its coherent development and by developing several urban centers than one macrocephalic city. It includes many other measures such as urban governance support, skills transfer, creation of strategic guidelines, financial support (local taxes, mining taxes, development funds etc.) local development projects. Through various examples of mining projects in Guinea, A country that is host to many large mining projects, we will look at the implications of regional and urban planning of which mining companies are key playor as well as public authorities. While their investment capacity offers advantages and accelerates development, their actions raise questions of the unilaterality of interests and local governance. By interfering in public affairs are mining companies not increasing the risk of central and local government shirking their responsibilities in terms of regional development, or even calling their legitimacy into question? Is such public-private collaboration really sustainable for the region as a whole and for all stakeholders?

Keywords: Africa, guinea, mine, urban planning

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: David C. Ni

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Contemporary models for N-body systems are based on temporal, two-body, and mass point representation of Newtonian mechanics. Other mainstream models include 2D and 3D Ising models based on local neighborhood the lattice structures. In Quantum mechanics, the theories of collective modes are for superconductivity and for the long-range quantum entanglement. However, these models are still mainly for the specific phenomena with a set of designated parameters. We are therefore motivated to develop a new construction directly from the complex-variable N-body systems based on the extended Blaschke functions (EBF), which represent a non-temporal and nonlinear extension of Lorentz transformation on the complex plane – the normalized momentum spaces. A point on the complex plane represents a normalized state of particle momentums observed from a reference frame in the theory of special relativity. There are only two key parameters, normalized momentum and nonlinearity for modelling. An algorithm similar to Jenkins-Traub method is adopted for solving EBF iteratively. Through iteration, the solution sets show a form of σ + i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various distributions, such as 1-peak, 2-peak, and 3-peak etc. distributions and some of them are analog to the canonical distributions. The results of the numerical analysis demonstrate continuum-to-discreteness transitions, evolutional invariance of distributions, phase transitions with conjugate symmetry, etc., which manifest the construction as a potential candidate for the unification of statistics. We hereby classify the observed distributions on the finite convergent domains. Continuous and discrete distributions both exist and are predictable for given partitions in different regions of parameter-pair. We further compare these distributions with canonical distributions and address the impacts on the existing applications.

Keywords: blaschke, lorentz transformation, complex variables, continuous, discrete, canonical, classification

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Authors: Getenet Dessie, Jinhu Li, Son Nghiem, Tinh Doan

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Background: Concerns regarding malnutrition have evolved from focusing solely on single forms to addressing the simultaneous occurrence of multiple types, commonly referred to as the double or triple burden of malnutrition. Nevertheless, data concerning the concurrent occurrence of various types of malnutrition are scarce. Therefore, this systematic review and meta-analysis aims to assess the pooled prevalence of the double burden of malnutrition among children under five in Sub-Saharan Africa and other least-developed countries (LDCs). Methods: Electronic, web-based searches were conducted from January 15 to June 28, 2023, across several databases, including PubMed, Embase, Google Scholar, and the World Health Organization's Hinari portal, as well as other search engines, to identify primary studies published up to June 28, 2023. Laboratory-based cross-sectional studies on children under the age of five were included. Two independent authors assessed the risk of bias and the quality of the identified articles. The primary outcomes of this study were micronutrient deficiencies and the comorbidity of stunting and anemia, as well as wasting and anemia. The random-effects model was utilized for analysis. The association of identified variables with the various forms of malnutrition was also assessed using adjusted odds ratios (AOR) with a 95% confidence interval (CI). This review was registered in PROSPERO with the reference number CRD42023409483. Findings: The electronic search generated 6,087 articles, 93 of which matched the inclusion criteria for the final meta-analysis. Micronutrient deficiencies were prevalent among children under five in Sub-Saharan Africa and other LDCs, with rates ranging from 16.63% among 25,169 participants for vitamin A deficiency to 50.90% among 3,936 participants for iodine deficiency. Iron deficiency anemia affected 20.56% of the 63,121 participants. The combined prevalence of wasting anemia and stunting anemia was 5.41% among 64,709 participants and 19.98% among 66,016 participants, respectively. Both stunting and vitamin A supplementation were associated with vitamin A and iron deficiencies, with adjusted odds ratios (AOR) of 1.54 (95% CI: 1.01, 2.37) and 1.37 (95% CI: 1.21, 1.55), respectively. Interpretation: The prevalence of the double burden of malnutrition among children under the age of five was notably high in Sub-Saharan Africa and other LDCs. These findings indicate a need for increased attention and a focus on understanding the factors influencing this double burden of malnutrition.

Keywords: children, Sub-Saharan Africa, least developed countries, double burden of malnutrition, systematic review, meta-analysis

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Authors: Gülay Dalgıç, Gildis Tachir

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Architectural design studios are ambiencein where architecture design is realized as a palpable product in architectural education. In the design studios that the architect candidate will use in the design processthe information, the methods of approaching the design problem, the solution proposals, etc., are set uptogetherwith the studio coordinators. The architectural design process, on the other hand, is complex and uncertain.Candidate architects work in a process that starts with abstre and ill-defined problems. This process starts with the generation of alternative solutions with the help of representation tools, continues with the selection of the appropriate/satisfactory solution from these alternatives, and then ends with the creation of an acceptable design/result product. In the studio ambience, many designs and thought relationships are evaluated, the most important step is the early design phase. In the early design phase, the first steps of converting the information are taken, and converted information is used in the constitution of the first design decisions. This phase, which positively affects the progress of the design process and constitution of the final product, is complex and fuzzy than the other phases of the design process. In this context, the aim of the study is to investigate the effects of face-to-face learning model and e-learning model on the early design phase. In the study, the early design phase was defined by literature research. The data of the defined early design phase criteria were obtained with the feedback graphics created for the architect candidates who performed e-learning in the first year of architectural education and continued their education with the face-to-face learning model. The findings of the data were analyzed with the common graphics program. It is thought that this research will contribute to the establishment of a contemporary architectural design education model by reflecting the evaluation of the data and results on architectural education.

Keywords: education modeling, architecture education, design education, design process

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Authors: William Feng, Qingyu Gao

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Despite the extensive discussions about Hong Kong’s sentiments towards the Chinese Mainland since the sovereignty transfer in 1997, there has been no large-scale empirical analysis of the changing attitudes in the mainstream media, which both reflect and shape sentiments in the society. To address this gap, the present study uses an optimised semantic-based automatic sentiment analysis method to examine a corpus of news about China from 1997 to 2020 in three main Chinese-language newspapers in Hong Kong, namely Apple Daily, Ming Pao, and Oriental Daily News. The analysis shows that although the Hong Kong press had a positive emotional tone toward China in general, the overall trend of sentiment was becoming increasingly negative. Meanwhile, the alignment and antagonism toward China have both increased, providing empirical evidence of attitudinal polarisation in the Hong Kong society. Specifically, Apple Daily’s depictions of China have become increasingly negative, though with some positive turns before 2008, whilst Oriental Daily News has consistently expressed more favourable sentiments. Ming Pao maintained an impartial stance toward China through an increased but balanced representation of positive and negative sentiments, with its subjectivity and sentiment intensity growing to an industry-standard level. The results provide new insights into the complexity of sentiments towards China in the Hong Kong press and media attitudes in general in terms of the “us” and “them” positioning by explicating the cross-newspaper and cross-period variations using an enhanced sentiment analysis method which incorporates sentiment-oriented and semantic role analysis techniques.

Keywords: media attitude, sentiment analysis, Hong Kong press, one country two systems

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Authors: Bashair Al Riyami

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Background: Acylation stimulating protein (ASP) is a small basic protein that was isolated based on its function as a potent lipogenic factor. The role of ASP in lipid metabolism has been described in numerous studies. Several association studies suggest that ASP may play a prominent role in female fat metabolism and distribution. Progesterone is established as a female lipogenic hormone, however the mechanisms by which progesterone exert its effects are not fully understood. AIM: Since ASP is an established potent lipogenic factor with a known mechanism of action, in this study we aim to investigate acute effects of different hormone treatments on ASP levels in vivo after a fat load. Methods: This is a longitudinal study including 24 female wister rats that were randomly divided into 4 groups including controls (n=6). The rats were ovariectomized, and fourteen days later the fasting rats were injected subcutaneously with a single dose of different hormone treatments (progesterone, estrogen and testosterone). An hour later, olive was administered by oral gavage, and plasma blood samples were collected at several time points after oil administration for ASP and triglyceride measurements. Area under the curve (TG-AUC) was calculated to represent TG clearance Results: RM-ANCOVA and post-analysis showed that only the progesterone treated group had a significant postprandial ASP increase at two hours compared to basal levels and to the controls (439.8± 62.4 vs 253.45± 59.03 ug/ml), P= 0.04. Interestingly, increased postprandial ASP levels coordinated negatively with corresponding TG levels and TG-AUC across the postprandial period most apparent in the progesterone and testosterone treated groups that behaved in an opposite manner. ASP levels were 3-fold higher in the progesterone compared to the testosterone treated group, whereas TG-AUC was significantly lower in the progesterone treated group compared to the testosterone treated group. Conclusion: These findings suggest that progesterone treatment enhances ASP production and TG clearance in a simultaneous manner. The strong association of postprandial ASP levels and TG clearance in the progesterone treated group support the notion of a stimulatory role for progesterone on ASP mediated TG clearance. This is the first functional study to demonstrate a cause-effect relationship between hormone treatment and ASP levels in vivo. These findings are promising and may contribute to further understanding the mechanism of progesterone function as a female lipogenic hormone through enhancing ASP production and plasma levels.

Keywords: ASP, lipids, sex hormones, wister rats

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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

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

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

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Authors: Zoaib Mirza

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Half of the Muslim countries in the world have declared Islam the state religion in their constitutions. Yet, none of these countries have implemented authentic Islamic laws in line with the Quran (Holy Book), practices of Prophet Mohammad (P.B.U.H) called the Sunnah, and his four successors known as the Rightly Guided - Khalifa. Since their independence, these countries have adopted different government systems like Democracy, Dictatorship, Republic, Communism, and Monarchy. Instead of benefiting the people, these government systems have put these countries into political, social, and economic crises. These Islamic countries do not have equal representation and membership in worldwide political forums. Western countries lead these forums. Therefore, it is now imperative for the Muslim leaders of all these countries to collaborate, reset, and implement the original Islamic form of government, which led to the prosperity and success of people, including non-Muslims, 1400 years ago. They should unite as one nation under Khalifat, which means establishing the authority of Allah (SWT) and following the divine commandments related to the social, political, and economic systems. As they have declared Islam in their constitution, they should work together to apply the divine framework of the governance revealed by Allah (SWT) and implemented by Prophet Mohammad (P.B.U.H) and his four successors called Khalifas. This paper provides an overview of the downfall and the end of the Khalifat system by 1924, the ways in which the West caused political, social, and economic crises in the Muslim countries, and finally, a summary of the social, political, and economic systems implemented by the Prophet Mohammad (P.B.U.H) and his successors, Khalifas, called the Rightly Guided – Hazrat Abu Bakr (RA), Hazrat Omar (RA), Hazrat Usman (RA), and Hazrat Ali (RA).

Keywords: khalifat, khilafat-e-Rashida, the rightly guided, colonization, capitalism, neocolonization, government systems

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Authors: Davies Obaromi, Qin Yongsong, James Ndege

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To interpolate scattered or regularly distributed data, there are imprecise or exact methods. However, there are some of these methods that could be used for interpolating data in a regular grid and others in an irregular grid. In spatial epidemiology, it is important to examine how a disease prevalence rates are distributed in space, and how they relate with each other within a defined distance and direction. In this study, for the geographic and graphic representation of the disease prevalence, linear and biharmonic spline methods were implemented in MATLAB, and used to identify, localize and compare for smoothing in the distribution patterns of tuberculosis (TB) in Eastern Cape Province. The aim of this study is to produce a more “smooth” graphical disease map for TB prevalence patterns by a 3-D curve fitting techniques, especially the biharmonic splines that can suppress noise easily, by seeking a least-squares fit rather than exact interpolation. The datasets are represented generally as a 3D or XYZ triplets, where X and Y are the spatial coordinates and Z is the variable of interest and in this case, TB counts in the province. This smoothing spline is a method of fitting a smooth curve to a set of noisy observations using a spline function, and it has also become the conventional method for its high precision, simplicity and flexibility. Surface and contour plots are produced for the TB prevalence at the provincial level for 2012 – 2015. From the results, the general outlook of all the fittings showed a systematic pattern in the distribution of TB cases in the province and this is consistent with some spatial statistical analyses carried out in the province. This new method is rarely used in disease mapping applications, but it has a superior advantage to be assessed at subjective locations rather than only on a rectangular grid as seen in most traditional GIS methods of geospatial analyses.

Keywords: linear, biharmonic splines, tuberculosis, South Africa

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Authors: Mojtaba Noghabaei, Khashayar Asadi, Kevin Han

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Simultaneous Localization and Mapping (SLAM) technology has recently attracted the attention of construction companies for real-time performance monitoring. To effectively use SLAM for construction performance monitoring, SLAM results should be registered to a Building Information Models (BIM). Registring SLAM and BIM can provide essential insights for construction managers to identify construction deficiencies in real-time and ultimately reduce rework. Also, registering SLAM to BIM in real-time can boost the accuracy of SLAM since SLAM can use features from both images and 3d models. However, registering SLAM with the BIM in real-time is a challenge. In this study, a novel SLAM platform named Model-Based SLAM (MB-SLAM) is proposed, which not only provides automated registration of SLAM and BIM but also improves the localization accuracy of the SLAM system in real-time. This framework improves the accuracy of SLAM by aligning perspective features such as depth, vanishing points, and vanishing lines from the BIM to the SLAM system. This framework extracts depth features from a monocular camera’s image and improves the localization accuracy of the SLAM system through a real-time iterative process. Initially, SLAM can be used to calculate a rough camera pose for each keyframe. In the next step, each SLAM video sequence keyframe is registered to the BIM in real-time by aligning the keyframe’s perspective with the equivalent BIM view. The alignment method is based on perspective detection that estimates vanishing lines and points by detecting straight edges on images. This process will generate the associated BIM views from the keyframes' views. The calculated poses are later improved during a real-time gradient descent-based iteration method. Two case studies were presented to validate MB-SLAM. The validation process demonstrated promising results and accurately registered SLAM to BIM and significantly improved the SLAM’s localization accuracy. Besides, MB-SLAM achieved real-time performance in both indoor and outdoor environments. The proposed method can fully automate past studies and generate as-built models that are aligned with BIM. The main contribution of this study is a SLAM framework for both research and commercial usage, which aims to monitor construction progress and performance in a unified framework. Through this platform, users can improve the accuracy of the SLAM by providing a rough 3D model of the environment. MB-SLAM further boosts the application to practical usage of the SLAM.

Keywords: perspective alignment, progress monitoring, slam, stereo matching.

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Authors: Abu Afree Andalib, Rafiur Rahman, Md Mezbah Uddin

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The main objective of this work is to anatomize on the various parameters of AGM 88 missile anatomized using FSI module in Ansys. Computational fluid dynamics is used for the study of fluid flow pattern and fluidic phenomenon such as drag, pressure force, energy dissipation and shockwave distribution in water. Using finite element analysis module of Ansys, structural parameters such as stress and stress density, localization point, deflection, force propagation is determined. Separate analysis on structural parameters is done on Abacus. State of the art coupling module is used for FSI analysis. Fine mesh is considered in every case for better result during simulation according to computational machine power. The result of the above-mentioned parameters is analyzed and compared for two phases using graphical representation. The result of Ansys and Abaqus are also showed. Computational Fluid Dynamics and Finite Element analyses and subsequently the Fluid-Structure Interaction (FSI) technique is being considered. Finite volume method and finite element method are being considered for modelling fluid flow and structural parameters analysis. Feasible boundary conditions are also utilized in the research. Significant change in the interaction and interference pattern while the impact was found. Theoretically as well as according to simulation angled condition was found with higher impact.

Keywords: FSI (Fluid Surface Interaction), impact, missile, high viscous fluid, CFD (Computational Fluid Dynamics), FEM (Finite Element Analysis), FVM (Finite Volume Method), fluid flow, fluid pattern, structural analysis, AGM-88, Ansys, Abaqus, meshing, k-omega, turbulence model

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Authors: Andrew D. Henshaw

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The research examines the influence of familial and kinship based leadership on the resilience of politically violent organizations. Organizations of this type frequently fight in the same conflicts though are called 'terrorist' or 'insurgent' depending on political foci of the time, and thus different approaches are used to combat them. The research considers them correlated phenomena with significant overlap and identifies strengths and vulnerabilities in resilience processes. The research employs paired case studies to examine resilience in organizations under significant external pressure, and achieves this by measuring three variables. 1: Organizational robustness in terms of leadership and governance. 2. Bounce-back response efficiency to external pressures and adaptation to endogenous and exogenous shock. 3. Perpetuity of operational and attack capability, and political legitimacy. The research makes three hypotheses. First, familial/kinship leadership groups have a significant effect on organizational resilience in terms of informal operations. Second, non-familial/kinship organizations suffer in terms of heightened security transaction costs and social economics surrounding recruitment, retention, and replacement. Third, resilience in non-familial organizations likely stems from critical external supports like state sponsorship or powerful patrons, rather than organic resilience dynamics. The case studies pair familial organizations with non-familial organizations. Set 1: The Haqqani Network (HQN) - Pair: Lashkar-e-Toiba (LeT). Set 2: Jemaah Islamiyah (JI) - Pair: The Abu Sayyaf Group (ASG). Case studies were selected based on three requirements, being: contrasting governance types, exposure to significant external pressures and, geographical similarity. The case study sets were examined over 24 months following periods of significantly heightened operational activities. This enabled empirical measurement of the variables as substantial external pressures came into force. The rationale for the research is obvious. Nearly all organizations have some nexus of familial interconnectedness. Examining familial leadership networks does not provide further understanding of how terrorism and insurgency originate, however, the central focus of the research does address how they persist. The sparse attention to this in existing literature presents an unexplored yet important area of security studies. Furthermore, social capital in familial systems is largely automatic and organic, given at birth or through kinship. It reduces security vetting cost for recruits, fighters and supporters which lowers liabilities and entry costs, while raising organizational efficiency and exit costs. Better understanding of these process is needed to exploit strengths into weaknesses. Outcomes and implications of the research have critical relevance to future operational policy development. Increased clarity of internal trust dynamics, social capital and power flows are essential to fracturing and manipulating kinship nexus. This is highly valuable to external pressure mechanisms such as counter-terrorism, counterinsurgency, and strategic intelligence methods to penetrate, manipulate, degrade or destroy the resilience of politically violent organizations.

Keywords: Counterinsurgency (COIN), counter-terrorism, familial influence, insurgency, intelligence, kinship, resilience, terrorism

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Authors: Yoganathan Karthik, Guhanathan Poravi

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Colorizing near-infrared (NIR) images poses unique challenges due to the absence of color information and the nuances in light absorption. In this paper, we present an approach to NIR image colorization utilizing a synthetic dataset generated from visible light images. Our method addresses two major challenges encountered in NIR image colorization: accurately colorizing objects with color variations and avoiding over/under saturation in dimly lit scenes. To tackle these challenges, we propose a Generative Adversarial Network (GAN)-based framework that learns to map NIR images to their corresponding colorized versions. The synthetic dataset ensures diverse color representations, enabling the model to effectively handle objects with varying hues and shades. Furthermore, the GAN architecture facilitates the generation of realistic colorizations while preserving the integrity of dimly lit scenes, thus mitigating issues related to over/under saturation. Experimental results on benchmark NIR image datasets demonstrate the efficacy of our approach in producing high-quality colorizations with improved color accuracy and naturalness. Quantitative evaluations and comparative studies validate the superiority of our method over existing techniques, showcasing its robustness and generalization capability across diverse NIR image scenarios. Our research not only contributes to advancing NIR image colorization but also underscores the importance of synthetic datasets and GANs in addressing domain-specific challenges in image processing tasks. The proposed framework holds promise for various applications in remote sensing, medical imaging, and surveillance where accurate color representation of NIR imagery is crucial for analysis and interpretation.

Keywords: computer vision, near-infrared images, automatic image colorization, generative adversarial networks, synthetic data

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Authors: Valery Gulyayev, Sergey Glazunov, Elena Andrusenko, Nataliya Shlyun

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Enhancement of technology and techniques for drilling deep directed oil and gas bore-wells are of essential industrial significance because these wells make it possible to increase their productivity and output. Generally, they are used for drilling in hard and shale formations, that is why their drivage processes are followed by the emergency and failure effects. As is corroborated by practice, the principal drilling drawback occurring in drivage of long curvilinear bore-wells is conditioned by the need to obviate essential force hindrances caused by simultaneous action of the gravity, contact and friction forces. Primarily, these forces depend on the type of the technological regime, drill string stiffness, bore-hole tortuosity and its length. They can lead to the Eulerian buckling of the drill string and its sticking. To predict and exclude these states, special mathematic models and methods of computer simulation should play a dominant role. At the same time, one might note that these mechanical phenomena are very complex and only simplified approaches (‘soft string drag and torque models’) are used for their analysis. Taking into consideration that now the cost of directed wells increases essentially with complication of their geometry and enlargement of their lengths, it can be concluded that the price of mistakes of the drill string behavior simulation through the use of simplified approaches can be very high and so the problem of correct software elaboration is very urgent. This paper deals with the problem of simulating the regimes of drilling deep curvilinear bore-wells with prescribed imperfect geometrical trajectories of their axial lines. On the basis of the theory of curvilinear flexible elastic rods, methods of differential geometry, and numerical analysis methods, the 3D ‘stiff-string drag and torque model’ of the drill string bending and the appropriate software are elaborated for the simulation of the tripping in and out regimes and drilling operations. It is shown by the computer calculations that the contact and friction forces can be calculated and regulated, providing predesigned trouble-free modes of operation. The elaborated mathematic models and software can be used for the emergency situations prognostication and their exclusion at the stages of the drilling process design and realization.

Keywords: curvilinear drilling, drill string tripping in and out, contact forces, resistance forces

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Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

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In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

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Authors: Tasir Khan, Ishfaq Ahmad, Yejuan Wang, Muhammad Salam

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Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy.

Keywords: wind-speed modeling, goodness of fit, maximum likelihood method, linear moment

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Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

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The paper presents logical-probabilistic methods, models, and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. It is important to design systems based on structural analysis, research, and evaluation of efficiency indicators. One of the important efficiency criteria is the reliability of the system, which depends on the components of the structure. Quantifying the reliability of large-scale systems is a computationally complex process, and it is advisable to perform it with the help of a computer. Logical-probabilistic modeling is one of the effective means of describing the structure of a complex system and quantitatively evaluating its reliability, which was the basis of our application. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of “weights” of elements of system. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research, and designing of optimal structure systems are carried out.

Keywords: complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability of systems, “weights” of elements

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Authors: Priti S. Tidke, Chandragouda R. Patil

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The present study was designed to investigate the effect of Magnesia phosphorica, a biochemical medicine on urine screeing, biochemical, histopathological, and electron microscopic images in ethylene glycol induced nepholithiasis in rats.Male Wistar albino rats were divided into six groups and were orally administered saline once daily (IR-sham and IR-control) or Magnesia phosphorica 100 mg/kg twice daily for 24 days.The effect of various dilutions of biochemical Mag phos3x, 6x, 30x was determined on urine output by comparing the urine volume collected by keeping individual animals in metabolic cages. Calcium oxalate urolithiasis and hyperoxaluria in male Wistar rats was induced by oral administration of 0.75% Ethylene glycol p.o. daily for 24 days. Simultaneous administration of biochemical 3x, 6x, 30xMag phos (100mg/kg p.o. twice a day) along with ethylene glycol significantly decreased calcium oxalate, urea, creatinine, Calcium, Magnesium, Chloride, Phosphorus, Albumin, Alkaline Phosphatase content in urine compared with vehicle-treated control group.After the completion of treatment period animals were sacrificed, kidneys were removed and subjected to microscopic examination for possible stone formation. Histological estimation of kidney treated with biochemical Mag phos (3x, 6x, 30xMag phos 100 mg/kg, p.o.) along with ethylene glycol inhibited the growth of calculi and reduced the number of stones in kidney compared with control group. Biochemical Mag phos of 3x dilution and its crude equivalent also showed potent diuretic and antiurolithiatic activity in ethylene glycol induced urolithiasis. A significant decrease in the weight of stones was observed after treatment in animals which received biochemical Mag phos of 3x dilution and its crude equivalent in comparison with control groups. From this study, it can be proposed that the 3x dilution of biochemical Mag phos exhibits a significant inhibitory effect on crystal growth, with the improvement of kidney function and substantiates claims on the biological activity of twelve tissue remedies which can be proved scientifically through laboratory animal studies.

Keywords: Mag phos, Magnesia phosphorica, ciochemic medicine, urolithiasis, kidney stone, ethylene glycol

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Authors: Zexiao Zheng, Irene M. C. Lo

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Organic pollutants, ammonia, and bacteria are major contaminants in sewage, which may adversely impact ecosystems without proper treatment. Conventional wastewater treatment plants (WWTPs) are operated to remove these contaminants from sewage but suffer from high carbon emissions and are powerless to remove emerging organic pollutants (EOPs). Herein, we have developed a low operational carbon emissions multifunctional photoelectrochemical (PEC) system for saline sewage treatment to simultaneously remove organic compounds, ammonia, and bacteria, coupled with H2 evolution. A reduced BiVO4 (r-BiVO4) with improved PEC properties due to the construction of oxygen vacancies and V4+ species was developed for the multifunctional PEC system. The PEC/r-BiVO4 process could treat saline sewage to meet local WWTPs’ discharge standard in 40 minutes at 2.0 V vs. Ag/AgCl and completely degrade carbamazepine (one of the EOPs), coupled with significant evolution of H2. A remarkable reduction in operational carbon emissions was achieved by the PEC/r-BiVO4 process compared with large-scale WWTPs, attributed to the restrained direct carbon emissions from the generation of greenhouse gases. Mechanistic investigation revealed that the PEC system could activate chloride ions in sewage to generate reactive chlorine species and facilitate •OH production, promoting contaminants removal. The PEC system exhibited operational feasibility at different pH and total suspended solids concentrations and has outstanding reusability and stability, confirming its promising practical potential. The study combined the simultaneous removal of three major contaminants from saline sewage and H2 evolution in a single PEC process, demonstrating a viable approach to supplementing and extending the existing wastewater treatment technologies. The study generated profound insights into the in-situ activation of existing chloride ions in sewage for contaminants removal and offered fundamental theories for applying the PEC system in sewage remediation with low operational carbon emissions. The developed PEC system can fit well with the future needs of wastewater treatment because of the following features: (i) low operational carbon emissions, benefiting the carbon neutrality process; (ii) higher quality of the effluent due to the elimination of EOPs; (iii) chemical-free in the operation of sewage treatment; (iv) easy reuse and recycling without secondary pollution.

Keywords: contaminants removal, H2 evolution, multifunctional PEC system, operational carbon emissions, saline sewage treatment, r-BiVO4 photoanodes

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Authors: E. K. K. Agyeman, P. Mousseau, A. Sarda, D. Edelin

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During the cooling of hot metals by the circulation of water in canals formed by boring holes in the metal, the rapid phase change of the water due to the high initial temperature of the metal leads to a non homogenous distribution of the phases within the canals. The liquid phase dominates towards the entrance of the canal while the gaseous phase dominates towards the exit. As a result of the different thermal properties of both phases, the metal is not uniformly cooled. This poses a problem during the cooling of moulds, where a uniform temperature distribution is needed in order to ensure the integrity of the part being formed. In this study, the simultaneous use of multiple water jets and an airflow for the uniform and controlled cooling of a steel block is investigated. A circular hole is bored at the centre of the steel block along its length and a perforated steel pipe is inserted along the central axis of the hole. Water jets that impact the internal surface of the steel block are generated from the perforations in the steel pipe when the water within it is put under pressure. These jets are oriented in the opposite direction to that of gravity. An intermittent airflow is imposed in the annular space between the steel pipe and the surface of hole bored in the steel block. The evolution of the temperature with respect to time of the external surface of the block is measured with the help of thermocouples and an infrared camera. Due to the high initial temperature of the steel block (350 °C), the water changes phase when it impacts the internal surface of the block. This leads to high heat fluxes. The strategy used to control the cooling speed of the block is the intermittent impingement of its internal surface by the jets. The intervals of impingement and of non impingement are varied in order to achieve the desired result. An airflow is used during the non impingement periods as an additional regulator of the cooling speed and to improve the temperature homogeneity of the impinged surface. After testing different jet positions, jet speeds and impingement intervals, it’s observed that the external surface of the steel block has a uniform temperature distribution along its length. However, the temperature distribution along its width isn’t uniform with the maximum temperature difference being between the centre of the block and its edge. Changing the positions of the jets has no significant effect on the temperature distribution on the external surface of the steel block. It’s also observed that reducing the jet impingement interval and increasing the non impingement interval slows down the cooling of the block and improves upon the temperature homogeneity of its external surface while increasing the duration of jet impingement speeds up the cooling process.

Keywords: cooling speed, homogenous cooling, jet impingement, phase change

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Authors: Omar Nouri, Wafa Mnejja, Nejla Fourati, Fatma Dhouib, Wicem Siala, Ilhem Charfeddine, Afef Khanfir, Jamel Daoud

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Background and objective: Induction chemotherapy (IC) followed by concomitant chemo radiotherapy with intensity modulated radiation (IMRT) technique is actually the recommended treatment modality for locally advanced nasopharyngeal carcinomas (NPC). The aim of this study was to evaluate the prognostic factors predicting loco regional relapse with this new treatment protocol. Patients and methods: A retrospective study of 52 patients with NPC treated between June 2016 and July 2019. All patients received IC according to the protocol of the Head and Neck Radiotherapy Oncology Group (Gortec) NPC 2006 (3 TPF courses) followed by concomitant chemo radiotherapy with weekly cisplatin (40 mg / m2). Patients received IMRT with integrated simultaneous boost (SIB) of 33 daily fractions at a dose of 69.96 Gy for high-risk volume, 60 Gy for intermediate risk volume and 54 Gy for low-risk volume. Median age was 49 years (19-69) with a sex ratio of 3.3. Forty five tumors (86.5%) were classified as stages III - IV according to the 2017 UICC TNM classification. Loco regional relapse (LRR) was defined as a local and/or regional progression that occurs at least 6 months after the end of treatment. Survival analysis was performed according to Kaplan-Meier method and Log-rank test was used to compare anatomy clinical and therapeutic factors that may influence loco regional free survival (LRFS). Results: After a median follow up of 42 months, 6 patients (11.5%) experienced LRR. A metastatic relapse was also noted for 3 of these patients (50%). Target volumes coverage was optimal for all patient with LRR. Four relapses (66.6%) were in high-risk target volume and two (33.3%) were borderline. Three years LRFS was 85,9%. Four factors predicted loco regional relapses: histologic type other than undifferentiated (UCNT) (p=0.027), a macroscopic pre chemotherapy tumor volume exceeding 100 cm³ (p=0.005), a reduction in IC doses exceeding 20% (p=0.016) and a total cumulative cisplatin dose less than 380 mg/m² (p=0.0.34). TNM classification and response to IC did not impact loco regional relapses. Conclusion: For nasopharyngeal carcinoma, tumors with initial high volume and/or histologic type other than UCNT, have a higher risk of loco regional relapse. Therefore, they require a more aggressive therapeutic approaches and a suitable monitoring protocol.

Keywords: loco regional relapse, modulation intensity radiotherapy, nasopharyngeal carcinoma, prognostic factors

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Authors: Elsadig Naseraddeen Ahmed Mohamed

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In contrast to the uncertainty and complementary principle, it will be shown in the present paper that the probability of the simultaneous occupation event of any definite values of coordinates by any definite values of momentum and energy at any definite instance of time can be described by a binary definite function equivalent to the difference between their numbers of occupation and evacuation epochs up to that time and also equivalent to the number of exchanges between those occupation and evacuation epochs up to that times modulus two, these binary definite quantities can be defined at all point in the time’s real-line so it form a binary signal represent a complete mechanical description of physical reality, the time of these exchanges represent the boundary of occupation and evacuation epochs from which we can calculate these binary signals using the fact that the time of universe events actually extends in the positive and negative of time’s real-line in one direction of extension when these number of exchanges increase, so there exists noninvertible transformation matrix can be defined as the matrix multiplication of invertible rotation matrix and noninvertible scaling matrix change the direction and magnitude of exchange event vector respectively, these noninvertible transformation will be called actual transformation in contrast to information transformations by which we can navigate the universe’s events transformed by actual transformations backward and forward in time’s real-line, so these information transformations will be derived as an elements of a group can be associated to their corresponded actual transformations. The actual and information model of the universe will be derived by assuming the existence of time instance zero before and at which there is no coordinate occupied by any definite values of momentum and energy, and then after that time, the universe begin its expanding in spacetime, this assumption makes the need for the existence of Laplace’s demon who at one moment can measure the positions and momentums of all constituent particle of the universe and then use the law of classical mechanics to predict all future and past of universe’s events, superfluous, we only need for the establishment of our analog to digital converters to sense the binary signals that determine the boundaries of occupation and evacuation epochs of the definite values of coordinates relative to its origin by the definite values of momentum and energy as present events of the universe from them we can predict approximately in high precision it's past and future events.

Keywords: binary-signal mechanics, actual-information model of the universe, actual-transformation, information-transformation, uncertainty principle, Laplace's demon

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Gerald Gwamba, Bo Zhou, Yajun Song, Dong Changyin

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The challenges that sand production presents to the oil and gas industry, particularly while working in poorly consolidated reservoirs, cannot be overstated. From restricting production to blocking production tubing, sand production increases the costs associated with production as it elevates the cost of servicing production equipment over time. Production in reservoirs that present with high viscosities, flow rate, cementation, clay content as well as fine sand contents is even more complex and challenging. As opposed to the one-factor at a-time testing, investigating the interactive effects arising from a combination of several factors offers increased reliability of results as well as representation of actual field conditions. It is thus paramount to investigate the conditions leading to the onset of sanding during production to ensure the future sustainability of hydrocarbon production operations under viscous conditions. We adopt the Design of Experiments (DOE) to analyse, using Taguchi factorial designs, the most significant interactive effects of sanding. We propose an optimized regression model to predict the drawdown time at sand production. The results obtained underscore that reservoirs characterized by varying (high and low) levels of viscosity, flow rate, cementation, clay, and fine sand content have a resulting impact on sand production. The only significant interactive effect recorded arises from the interaction between BD (fine sand content and flow rate), while the main effects included fluid viscosity and cementation, with percentage significances recorded as 31.3%, 37.76%, and 30.94%, respectively. The drawdown time model presented could be useful for predicting the time to reach the maximum drawdown pressure under viscous conditions during the onset of sand production.

Keywords: factorial designs, DOE optimization, sand production prediction, drawdown time, regression model

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Authors: Titanilla Komenda

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Human-machine-collaboration defines a direct interaction between humans and machines to fulfil specific tasks. Those so-called collaborative machines are used without fencing and interact with humans in predefined workspaces. Even though, human-machine-collaboration enables a flexible adaption to variable degrees of freedom, industrial applications are rarely found. The reasons for this are not technical progress but rather limitations in planning processes ensuring safety for operators. Until now, humans and machines were mainly considered separately in the planning process, focusing on ergonomics and system performance respectively. Within human-machine-collaboration, those aspects must not be seen in isolation from each other but rather need to be analysed in interaction. Furthermore, a simulation model is needed that can validate the system performance and ensure the safety for the operator at any given time. Following on from this, a holistic simulation model is presented, enabling a simulative representation of collaborative tasks – including both, humans and machines. The presented model does not only include a geometry and a motion model of interacting humans and machines but also a numerical behaviour model of humans as well as a Boole’s probabilistic sensor model. With this, error scenarios can be simulated by validating system behaviour in unplanned situations. As these models can be defined on the basis of Failure Mode and Effects Analysis as well as probabilities of errors, the implementation in a collaborative model is discussed and evaluated regarding limitations and simulation times. The functionality of the model is shown on industrial applications by comparing simulation results with video data. The analysis shows the impact of considering human factors in the planning process in contrast to only meeting system performance. In this sense, an optimisation function is presented that meets the trade-off between human and machine factors and aids in a successful and safe realisation of collaborative scenarios.

Keywords: human-machine-system, human-robot-collaboration, safety, simulation

Procedia PDF Downloads 359

Authors: Vibeke Sorensen, Nagaraju Thummanapalli, J. Stephen Lansing

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Inspired by the indigenous people of Borneo, Indonesia and their traditional bark cloth, artist and professor Vibeke Sorensen executed a “digital unwrapping” of several trees in Southeast Asia using a digital panorama camera and digitally “stitched” them together for printing onto sustainable silk and fashioning into the “Tree Dress”. This dress is a symbolic “un-wrapping” and “re-wrapping” of the tree’s bark onto a person as a second skin. The “digital bark” is directly responsive to the real tree through embedded and networked electronics that connect in real-time to sensors at the physical site of the living tree. LEDs and circuits inserted into the dress display the continuous measurement of the O2 / CO2, temperature, humidity, and light conditions at the tree. It is an “Internet of Living Things” (IOLT) textile that can be worn to track and interact with it. The computer system connecting the dress and the tree converts the gas emission data at the site of the real tree into sound and music as sonification. This communicates not only the scientific data but also translates it into a poetic representation. The wearer of the garment can symbolically identify with the tree, or “become one” with it by adorning its “skin.” In this way, the wearer also becomes a human agent for the tree, bringing its actual condition to direct perception of the wearer and others who may engage it. This project is an attempt to bring greater awareness to issues of deforestation by providing a direct access to living things separated by physical distance, and hopefully, to increase empathy for them by providing a way to sense individual trees and their daily existential condition through remote monitoring of data. Further extensions to this project and related issues of sustainability include the use of recycled and alternative plant materials such as bamboo and air plants, among others.

Keywords: IOLT, sonification, sustainability, tree, wearable technology

Procedia PDF Downloads 130

Authors: Madjid Karimirad

Abstract:

Floating solar was not very well-known in the renewable energy field a decade ago; however, there has been tremendous growth internationally with a Compound Annual Growth Rate (CAGR) of nearly 30% in recent years. To reach the goal of global net-zero emission by 2050, all renewable energy sources including solar should be used. Considering that 40% of the world’s population lives within 100 kilometres of the coasts, floating solar in coastal waters is an obvious energy solution. However, this requires more robust floating solar solutions. This paper tries to enlighten the fundamental requirements in the design of floating solar for offshore installations from the hydrodynamic and offshore engineering points of view. In this regard, a closer look at dynamic characteristics, stochastic behaviour and nonlinear phenomena appearing in this kind of structure is a major focus of the current article. Floating solar structures are alternative and very attractive green energy installations with (a) Less strain on land usage for densely populated areas; (b) Natural cooling effect with efficiency gain; and (c) Increased irradiance from the reflectivity of water. Also, floating solar in conjunction with the hydroelectric plants can optimise energy efficiency and improve system reliability. The co-locating of floating solar units with other types such as offshore wind, wave energy, tidal turbines as well as aquaculture (fish farming) can result in better ocean space usage and increase the synergies. Floating solar technology has seen considerable developments in installed capacities in the past decade. Development of design standards and codes of practice for floating solar technologies deployed on both inland water-bodies and offshore is required to ensure robust and reliable systems that do not have detrimental impacts on the hosting water body. Floating solar will account for 17% of all PV energy produced worldwide by 2030. To enhance the development, further research in this area is needed. This paper aims to discuss the main critical design aspects in light of the load and load effects that the floating solar platforms are subjected to. The key considerations in hydrodynamics, aerodynamics and simultaneous effects from the wind and wave load actions will be discussed. The link of dynamic nonlinear loading, limit states and design space considering the environmental conditions is set to enable a better understanding of the design requirements of fast-evolving floating solar technology.

Keywords: floating solar, offshore renewable energy, wind and wave loading, design space

Procedia PDF Downloads 69