Search results for: complex event processing

Authors: Woei-Shyan Lee, Shuo-Ling Chang

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The nanoindentation behaviour and phase transformation of annealed single-crystal silicon wafers are examined. The silicon specimens are annealed at temperatures of 250, 350 and 450ºC, respectively, for 15 minutes and are then indented to maximum loads of 30, 50 and 70 mN. The phase changes induced in the indented specimens are observed using transmission electron microscopy (TEM) and micro-Raman scattering spectroscopy (RSS). For all annealing temperatures, an elbow feature is observed in the unloading curve following indentation to a maximum load of 30 mN. Under higher loads of 50 mN and 70 mN, respectively, the elbow feature is replaced by a pop-out event. The elbow feature reveals a complete amorphous phase transformation within the indented zone, whereas the pop-out event indicates the formation of Si XII and Si III phases. The experimental results show that the formation of these crystalline silicon phases increases with an increasing annealing temperature and indentation load. The hardness and Young’s modulus both decrease as the annealing temperature and indentation load are increased.

Keywords: nanoindentation, silicon, phase transformation, amorphous, annealing

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: H. M. Soroush

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The problem of scheduling products and services for on-time deliveries is of paramount importance in today’s competitive environments. It arises in many manufacturing and service organizations where it is desirable to complete jobs (products or services) with different weights (penalties) on or before their due dates. In such environments, schedules should frequently decide whether to schedule a job based on its processing time, due-date, and the penalty for tardy delivery to improve the system performance. For example, it is common to measure the weighted number of late jobs or the percentage of on-time shipments to evaluate the performance of a semiconductor production facility or an automobile assembly line. In this paper, we address the problem of scheduling a set of jobs on a server where processing times or due-dates of jobs are random variables and fixed weights (penalties) are imposed on the jobs’ late deliveries. The goal is to find the schedule that minimizes the expected weighted number of tardy jobs. The problem is NP-hard to solve; however, we explore three scenarios of the problem wherein: (i) both processing times and due-dates are stochastic; (ii) processing times are stochastic and due-dates are deterministic; and (iii) processing times are deterministic and due-dates are stochastic. We prove that special cases of these scenarios are solvable optimally in polynomial time, and introduce efficient heuristic methods for the general cases. Our computational results show that the heuristics perform well in yielding either optimal or near optimal sequences. The results also demonstrate that the stochasticity of processing times or due-dates can affect scheduling decisions. Moreover, the proposed problem is general in the sense that its special cases reduce to some new and some classical stochastic single machine models.

Keywords: number of late jobs, scheduling, single server, stochastic

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Authors: Mei Hong, Wei Liu, Xuemin Dai, Yanxiong Pan, Xiangling Ji

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Polyamic acid (PAA) is the precursor of polyimide (PI) prepared by a two-step method, its molecular weight and molecular weight distribution not only play an important role during the preparation and processing, but also influence the final performance of PI. However, precise characterization on molecular weight of PAA is still a challenge because of the existence of very complicated interactions in the solution system, including the electrostatic interaction, hydrogen bond interaction, dipole-dipole interaction, etc. Thus, it is necessary to establisha suitable strategy which can completely suppress these complex effects and get reasonable data on molecular weight. Herein, the gel permeation chromatography (GPC) coupled with differential refractive index (RI) and multi-angle laser light scattering (MALLS) detectors were applied to measure the molecular weight of (6FDA-DMB) PAA using different mobile phases, LiBr/DMF, LiBr/H3PO4/THF/DMF, LiBr/HAc/THF/DMF, and LiBr/HAc/DMF, respectively. It was found that combination of LiBr with HAc can shield the above-mentioned complex interactions and is more conducive to the separation of PAA than only addition of LiBr in DMF. LiBr/HAc/DMF was employed for the first time as a mild mobile phase to effectively separate PAA and determine its molecular weight. After a series of conditional experiments, 0.02M LiBr/0.2M HAc/DMF was fixed as an optimized mobile phase to measure the relative and absolute molecular weights of (6FDA-DMB) PAA prepared, and the obtained Mw from GPC-MALLS and GPC-RI were 35,300 g/mol and 125,000 g/mol, respectively. Particularly, such a mobile phase is also applicable to other PAA samples with different structures, and the final results on molecular weight are also reproducible.

Keywords: Polyamic acids, Polyelectrolyte effects, Gel permeation chromatography, Mobile phase, Molecular weight

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Authors: Maurice Bilioniere, Katie Lanneau

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Suddenly appeared in 2011, invasions of sargasso seaweeds Fluitans and Natans are a climatic hazard which causes many problems in the Caribbean. Faced with the growth and frequency of the phenomenon of massive sargasso stranding on their coasts, the French West Indies are moving towards the path of industrial recovery. In this context of innovative projects, we will analyze the necessary requirements for the management and performance of the supply chain, taking into account the observed volatility of the sargasso input. Our prospective approach will consist in studying the theoretical framework of modeling a hybrid supply chain by coupling the discreet event simulation (DES) with a valuation of the process costs according to the "activity-based costing" method (ABC). The PREVA approach (PRocess EVAluation) chosen for our modeling has the advantage of evaluating the financial flows of the logistic process using an analytical model chained with an action model for the evaluation or optimization of physical flows.

Keywords: sargasso, PREVA modeling, supply chain, ABC method, discreet event simulation (DES)

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Authors: Awad Khireldin, Colin Law

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Runways are the major infrastructure of airports around the world. Efficient operations of runways are key to ensure that airports are running smoothly with minimal delays. There are many factors that affect the efficiency of runway operations, such as the aircraft wake separation, runways system configuration, the fleet mix, and the runways separation distance. This paper aims to address how to maximize runway operations using a Discrete Event Simulation model. A case study of Cairo International Airport (CIA) is developed to maximize the utilizing of three parallel runways using a simulation model. Different scenarios have been designed where every runway could be assigned for arrival, departure, or mixed operations. A benchmarking study was also included to compare the actual to the proposed results to spot the potential improvements. The simulation model shows that there is a significant difference in utilization and delays between the actual and the proposed ones, there are several recommendations that can be provided to airport management, in the short and long term, to increase the efficiency and to reduce the delays. By including the recommendation with different operations scenarios, such as upgrading the airport slot Coordination from Level 1 to Level 2 in the short term. In the long run, discuss the possibilities to increase the International Air Transport association (IATA) slot coordination to Level 3 as more flights are expected to be handled by the airport. Technological advancements such as radar in the approach full airside simulation model could improve the airport performance where the airport is recommended to review the standard operations procedures with the appropriate authorities. Also, the airport can adopt a future operational plan to accommodate the forecasted additional traffic density in case of adding a fourth terminal building to increase the airport capacity.

Keywords: airport performance, runway, discrete event simulation, capacity, airside

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Authors: Neslihan Sahin Celik, Ali Eraslan

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As a result of PISA (Program for International Student Assessments) survey that tests how well students can apply the knowledge and skills they have learned at school to real-life challenges, the new and redesigned mathematics education programs in many countries emphasize the necessity for the students to face complex and multifaceted problem situations and gain experience in this sense allowing them to develop new skills and mathematical thinking to prepare them for their future life after school. At this point, mathematical models and modeling approaches can be utilized in the analysis of complex problems which represent real-life situations in which students can actively participate. In particular, model eliciting activities that bring about situations which allow the students to create solutions to problems and which involve mathematical modeling must be used right from primary school years, allowing them to face such complex, real-life situations from early childhood period. A qualitative study was conducted in a university foundation primary school in the city center of a big province in 2013-2014 academic years. The participants were 4th grade students in a primary school. After a four-week preliminary study applied to a fourth-grade classroom, three students included in the focus group were selected using criterion sampling technique. A focus group of three students was videotaped as they worked on the Crime Problem. The conversation of the group was transcribed, examined with students’ written work and then analyzed through the lens of Blum and Ferri’s modeling processing cycle. The results showed that primary fourth-grade students can successfully work with model eliciting problem while they encounter some difficulties in the modeling processes. In particular, they developed new ideas based on different assumptions, identified the patterns among variables and established a variety of models. On the other hand, they had trouble focusing on problems and occasionally had breaks in the process.

Keywords: primary school, modeling, mathematical modeling, crime problem

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Authors: Xiaochen Mu

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Data rights confirmation, as a key legal issue in the development of the digital economy, is undergoing a transition from a traditional rights paradigm to a more complex private-economic paradigm. In this process, data rights confirmation has evolved from a simple claim of rights to a complex structure encompassing multiple dimensions of personality rights and property rights. Current data rights confirmation practices are primarily reflected in two models: holistic rights confirmation and process rights confirmation. The holistic rights confirmation model continues the traditional "one object, one right" theory, while the process rights confirmation model, through contractual relationships in the data processing process, recognizes rights that are more adaptable to the needs of data circulation and value release. In the design of the data property rights system, there is a hierarchical characteristic aimed at decoupling from raw data to data applications through horizontal stratification and vertical staging. This design not only respects the ownership rights of data originators but also, based on the usufructuary rights of enterprises, constructs a corresponding rights system for different stages of data processing activities. The subjects of data property rights include both data originators, such as users, and data producers, such as enterprises, who enjoy different rights at different stages of data processing. The intellectual property rights system, with the mission of incentivizing innovation and promoting the advancement of science, culture, and the arts, provides a complete set of mechanisms for protecting innovative results. However, unlike traditional private property rights, the granting of intellectual property rights is not an end in itself; the purpose of the intellectual property system is to balance the exclusive rights of the rights holders with the prosperity and long-term development of society's public learning and the entire field of science, culture, and the arts. Therefore, the intellectual property granting mechanism provides both protection and limitations for the rights holder. This perfectly aligns with the dual attributes of data. In terms of achieving the protection of data property rights, the granting of intellectual property rights is an important institutional choice that can enhance the effectiveness of the data property exchange mechanism. Although this is not the only path, the granting of data property rights within the framework of the intellectual property rights system helps to establish fundamental legal relationships and rights confirmation mechanisms and is more compatible with the classification and grading system of data. The modernity of the intellectual property rights system allows it to adapt to the needs of big data technology development through special clauses or industry guidelines, thus promoting the comprehensive advancement of data intellectual property rights legislation. This paper analyzes data protection under the virtual property layer theory and two-fold virtual property rights system. Based on the “bundle of right” theory, this paper establishes specific three-level data rights. This paper analyzes the cases: Google v. Vidal-Hall, Halliday v Creation Consumer Finance, Douglas v Hello Limited, Campbell v MGN and Imerman v Tchenquiz. This paper concluded that recognizing property rights over personal data and protecting data under the framework of intellectual property will be beneficial to establish the tort of misuse of personal information.

Keywords: data protection, property rights, intellectual property, Big data

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Authors: Dahi Ghareab Abdelsalam Ibrahim, R. H. Bakr

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Ionizing radiation, such as gamma radiation and X-rays, has many applications in medical diagnoses and cancer treatment. In this paper, we used the windowed Fourier transform to extract the complex image of the deformed red blood cells. The real values of the complex image are used to extract the best fitting of the deformed cell boundary. Male albino rats are irradiated by γ-rays from ⁶⁰Co. The male albino rats are anesthetized with ether, and then blood samples are collected from the eye vein by heparinized capillary tubes for studying the radiation-damaging effect in-vivo by the proposed windowed Fourier transform. The peripheral blood films are prepared according to the Brown method. The peripheral blood film is photographed by using an Automatic Image Contour Analysis system (SAMICA) from ELBEK-Bildanalyse GmbH, Siegen, Germany. The SAMICA system is provided with an electronic camera connected to a computer through a built-in interface card, and the image can be magnified up to 1200 times and displayed by the computer. The images of the peripheral blood films are then analyzed by the windowed Fourier transform method to extract the precise deformation from the best fitting. Based on accurate deformation evaluation of the red blood cells, diseases can be diagnosed in their primary stages.

Keywords: windowed Fourier transform, red blood cells, phase wrapping, Image processing

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Authors: V. Singh, S. Singh, S. S. Garewal

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Metal matrix composites with aluminum as the matrix material have been heralded as the next great development in advanced engineering materials. Aluminum metal matrix composites (AMMC) refer to the class of light weight high performance material systems. Properties of AMMCs can be tailored to the demands of different industrial applications by suitable combinations of matrix, reinforcement and processing route. AMMC finds its application in automotive, aerospace, defense, sports and structural areas. This paper presents an overview of AMMC material systems on aspects relating to processing, types and applications with case studies.

Keywords: aluminum metal matrix composites, applications of aluminum metal matrix composites, lighting material processing of aluminum metal matrix composites

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Authors: Yosra M. Badiei, Evelyn Ortiz, Marisa Portenti, David Szalda

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Water-oxidation half-reaction is a critical reaction that can be driven by a sustainable energy source (e.g., solar or wind) and be coupled with a chemical fuel making reaction which stores the released electrons and protons from water (e.g., H₂ or methanol). The use of molecular water-oxidation catalysts (WOC) allow the rationale design of redox active metal centers and provides a better understanding of their structure-activity-relationship. Herein, the structure of a Ru(III) complex bearing a doubly deprotonated N,N'-bis(aryl)pyridine-2,6-dicarboxamide ligand which contains a water molecule in its primary coordination sphere was elucidated by single-crystal X-ray diffraction. Further spectroscopic experimental data and pH-dependent electrochemical studies reveal its water-oxidation reactivity. Emphasis on mechanistic details for O₂ formation of this complex will be addressed.

Keywords: water-oxidation, catalysis, ruthenium, artificial photosynthesis

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Authors: Fatemeh Sadat Miri, Morteza Ehsani, Seyed Farshid Hosseini

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The present research is concerned with the optimization of extrusion parameters of ABS sheets by the Taguchi experimental design method. In this design method, three parameters of % recycling ABS, processing temperature and degassing time on mechanical properties, hardness, HDT, and color matching of ABS sheets were investigated. The variations of this research are the dosage of recycling ABS, processing temperature, and degassing time. According to experimental test data, the highest level of tensile strength and HDT belongs to the sample with 5% recycling ABS, processing temperature of 230°C, and degassing time of 3 hours. Additionally, the minimum level of MFI and color matching belongs to this sample, too. The present results are in good agreement with the Taguchi method. Based on the outcomes of the Taguchi design method, degassing time has the most effect on the mechanical properties of ABS sheets.

Keywords: ABS, process optimization, Taguchi, mechanical properties

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Authors: Petra Dilling

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This study examines the market reaction to the publication of integrated reports for a sample of 316 global companies for the reporting year 2018. Applying event study methodology, we find significant cumulative average abnormal returns (CAARs) after the publication date. To ensure robust estimation resultsthe three-factor model, according to Fama and French, is used as well as a market-adjusted model, a CAPM and a Frama-French model taking GARCH effects into account. We find a significant positive CAAR after the publication day of the integrated report. Our results suggest that investors react to information provided in the integrated report and that they react differently to the annual financial report. Furthermore, our cross-sectional analysis confirms that companies with a significant positive cumulative average abnormal show certain characteristic. It was found that European companies have a higher likelihood to experience a stronger significant positive market reaction to their integrated report publication.

Keywords: integrated report, event methodology, cumulative abnormal return, sustainability, CAPM

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Authors: A. M. Naraghi, V. Gonzalez, M. O'Sullivan, C. G. Walker, M. Poshdar, F. Ying, M. Abdelmegid

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Discrete Event Simulation (DES) and Agent Based Simulation (ABS) are two simulation approaches that have been proposed to support decision-making in the construction industry. Despite the wide use of these simulation approaches in the construction field, their applications for production and material planning is still limited. This is largely due to the dynamic and complex nature of construction material supply chain systems. Moreover, managing the flow of construction material is not well integrated with site logistics in traditional construction planning methods. This paper presents a hybrid of DES and ABS to simulate on-site and off-site material supply processes. DES is applied to determine the best production scenarios with information of on-site production systems, while ABS is used to optimize the supply chain network. A case study of a construction piling project in New Zealand is presented illustrating the potential benefits of using the proposed hybrid simulation model in construction material flow planning. The hybrid model presented can be used to evaluate the impact of different decisions on construction supply chain management.

Keywords: construction supply-chain management, simulation modeling, decision-support tools, hybrid simulation

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Authors: A. Bayle, F. Plouraboué

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Water Distribution Network (WDN) still suffers from a lack of knowledge about fast pressure transient events prediction, although the latter may considerably impact their durability. Accidental or planned operating activities indeed give rise to complex pressure interactions and may drastically modified the local pressure value generating leaks and, in rare cases, pipe’s break. In this context, a numerical predictive analysis is conducted to prevent such event and optimize network management. A couple of Python/FORTRAN 90, home-made software, has been developed using Method Of Characteristic (MOC) solving for water-hammer equations. The solver is validated by direct comparison with theoretical and experimental measurement in simple configurations whilst afterward extended to network analysis. The algorithm's most costly steps are designed for parallel computation. A various set of boundary conditions and energetic losses models are considered for the network simulations. The results are analyzed in both real and frequencies domain and provide crucial information on the pressure distribution behavior within the network.

Keywords: energetic losses models, method of characteristic, numerical predictive analysis, water distribution network, water hammer

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Authors: Diana Pombo, Maria Loaiza, Mauricio Quijano, Alberto Cadena, Juan Pablo Tello

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In this paper, we present a semi-automatic tool for calculating ejection fraction from an echocardiographic video signal which is derived from a database in DICOM format, of Clinica de la Costa - Barranquilla. Described in this paper are each of the steps and methods used to find the respective calculation that includes acquisition and formation of the test samples, processing and finally the calculation of the parameters to obtain the ejection fraction. Two imaging segmentation methods were compared following a methodological framework that is similar only in the initial stages of processing (process of filtering and image enhancement) and differ in the end when algorithms are implemented (Active Contour and Region Growing Algorithms). The results were compared with the measurements obtained by two different medical specialists in cardiology who calculated the ejection fraction of the study samples using the traditional method, which consists of drawing the region of interest directly from the computer using echocardiography equipment and a simple equation to calculate the desired value. The results showed that if the quality of video samples are good (i.e., after the pre-processing there is evidence of an improvement in the contrast), the values provided by the tool are substantially close to those reported by physicians; also the correlation between physicians does not vary significantly.

Keywords: echocardiography, DICOM, processing, segmentation, EDV, ESV, ejection fraction

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Authors: Ibrahim A. Aref, Tarek El-Mihoub, Khadiga Ben Musa

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This paper presents Carrier Sense Multiple Access (CSMA) communication model based on SoC design methodology. Such model can be used to support the modelling of the complex wireless communication systems, therefore use of such communication model is an important technique in the construction of high performance communication. SystemC has been chosen because it provides a homogeneous design flow for complex designs (i.e. SoC and IP based design). We use a swarm system to validate CSMA designed model and to show how advantages of incorporating communication early in the design process. The wireless communication created through the modeling of CSMA protocol that can be used to achieve communication between all the agents and to coordinate access to the shared medium (channel).

Keywords: systemC, modelling, simulation, CSMA

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Authors: H. Yousefnia, A. Golabi Dezfuli, S. Zolghadri, M. Hosntalab

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Peptide receptor radionuclide therapy is nowadays used for the treatment of various abnormalities with somatostatin receptors. In this study, 166Ho-DOTATOC was prepared and the best conditions for its radiolabeling was obtained. For this purpose, a certain of DOTATOC was added to a vial containing 166Ho. various experiments by varying ligand concentration, pH, temperature and time were performed to determine the best conditions. Radiochemical purity of the complex was assessed by instant thin layer chromatography method utilizing 0.9% NaCl as the mobile phase. 166Ho-DOTATOC was prepared with radiochemical purity of higher than 95% at the optimized condition (pH=4, temperature: 95° C, time:30 min). In 0.9% NaCl, free Ho cation was developed at Rf of 0.8 while the complex was remained at the front of the paper.

Keywords: Ho-166, neuroendocrine, octreotide, quality control

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Authors: Kyunghee Oh, Dooho Choi

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Although there is no theoretical weakness in a cryptographic algorithm, Side Channel Analysis can find out some secret data from the physical implementation of a cryptosystem. The analysis is based on extra information such as timing information, power consumption, electromagnetic leaks or even sound which can be exploited to break the system. Differential Power Analysis is one of the most popular analyses, as computing the statistical correlations of the secret keys and power consumptions. It is usually necessary to calculate huge data and takes a long time. It may take several weeks for some devices with countermeasures. We suggest and evaluate the methods to shorten the time to analyze cryptosystems. Our methods include distributed computing and parallelized processing.

Keywords: DPA, distributed computing, parallelized processing, side channel analysis

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Authors: Misbah Shahzadi

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The present study was conducted to identify the emotional and behavioral disturbances among the News Reporters covering Traumatic events. In the present study, a sample of 50 News Reporters belonging to the national and the local news agencies were selected from Rawalpindi and Islamabad who had covered any traumatic event in the past one year. Rotter’s Incomplete Sentence Blank (RISB) and Impact of Event Scale interpretations were used to assess a variety of emotional and behavioral patterns of News Reporters. Results showed that some of the frequent emotional and behavioral reactions exhibited by individuals like withdrawal, anxiety\depression, aggression, hyperarousal and avoidance behavior whereas gender-based comparisons indicated that there is no significant gender difference in the News Reporters in manifestations of behavioral and emotional disturbances. It is concluded that significant negative emotional and behavioral reactions are exhibited by the News Reporters who cover traumatic events. The study identifies the negative emotional and behavioral reactions/disturbances after trauma, which can be helpful for identifying problematic areas for counseling and therapeutic interventions for these News Reporters.

Keywords: behavioural disturbance, emotional disturbance, news reporters, traumatic events

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Authors: Alok Kumar Routa, Priya Ranjan Mohanty

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Complex seismic signatures are generated due to the complexity of the subsurface which is difficult to interpret. In the present study, an attempt has been made to model the complex subsurface using the Ray tracing modeling technique. Add to this, for the imaging of these geological features, Kirchhoff’s prestack depth migration is applied over the synthetic common shot gather dataset. It is found that the Kirchhoff’s migration technique in addition with the Ray tracing modeling concept has the flexibility towards the imaging of various complex geology which gives satisfactory results with proper delineation of the reflectors at their respective true depth position. The entire work has been carried out under the MATLAB environment.

Keywords: Kirchhoff's migration, Prestack depth migration, Ray tracing modelling, velocity model

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Authors: S. Zolghadri, M. Naderi, H. Yousefnia, B. Alirzapour, A. R. Jalilian, A. Ramazani

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Nowadays, 68Ga-DOTATOC has been known as a potential agent for the detection of neuroendocrine tumours and it has indicated higher sensitivity compared with the 111In-Octeroetide. The aim of this study was to evaluate the effectiveness of this new agent in the diagnosis of adenocarcinoma breast cancer. 68Ga-DOTATOC was prepared with the radiochemical purity of higher than 98% and by the specific activity of 39.6 TBq/mmol. 37 MBq of the complex was injected intravenously into the BULB/c mice with adenocarcinoma breast cancer. PET/CT images were acquired after 30, 60 and 90 min post injection demonstrated significant accumulation in the tumour sites. Also, considerable activity was observed in the kidney and bladder as the main routs of excretion. Generally, the results showed that 68Ga-DOTATOC can be considered as a suitable complex for diagnosis of the adenocarcinoma breast cancer using PET procedure.

Keywords: adenocarcinoma breast cancer, 68Ga, octreotide, imaging

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Authors: Eseldin Keleb

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In the pharmaceutical industry particle size distribution is an important parameter for the characterization of pharmaceutical powders. The powder flowability, reactivity and compatibility, which have a decisive impact on the final product, are determined by particle size and size distribution. Therefore, the aim of this study was to evaluate the influence of processing parameters on the particle size distribution measurements. Different Size fractions of α-lactose monohydrate and 5% polyvinylpyrrolidone were prepared by wet granulation and were used for the preparation of samples. The influence of sieve load (50, 100, 150, 200, 250, 300, and 350 g), processing time (5, 10, and 15 min), sample size ratios (high percentage of small and large particles), type of disturbances (vibration and shaking) and process reproducibility have been investigated. Results obtained showed that a sieve load of 50 g produce the best separation, a further increase in sample weight resulted in incomplete separation even after the extension of the processing time for 15 min. Performing sieving using vibration was rapider and more efficient than shaking. Meanwhile between day reproducibility showed that particle size distribution measurements are reproducible. However, for samples containing 70% fines or 70% large particles, which processed at optimized parameters, the incomplete separation was always observed. These results indicated that sieving reliability is highly influenced by the particle size distribution of the sample and care must be taken for samples with particle size distribution skewness.

Keywords: sieving, reliability, particle size distribution, processing parameters

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Authors: Feng Guolin, Gong Zhiqiang

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In order to study the spatial structure and dynamical mechanism of extreme precipitation in East Asia, a corresponding climate network is constructed by employing the method of event synchronization. It is found that the area of East Asian summer extreme precipitation can be separated into two regions: one with high area weighted connectivity receiving heavy precipitation mostly during the active phase of the East Asian Summer Monsoon (EASM), and another one with low area weighted connectivity receiving heavy precipitation during both the active and the retreat phase of the EASM. Besides，a way for the prediction of extreme precipitation is also developed by constructing a directed climate networks. The simulation accuracy in East Asia is 58% with a 0-day lead, and the prediction accuracy is 21% and average 12% with a 1-day and an n-day (2≤n≤10) lead, respectively. Compare to the normal EASM year, the prediction accuracy is lower in a weak year and higher in a strong year, which is relevant to the differences in correlations and extreme precipitation rates in different EASM situations. Recognizing and identifying these effects is good for understanding and predicting extreme precipitation in East Asia.

Keywords: synchronization, climate network, prediction, rainfall

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Authors: Farah Al Zaabi, Sarah Amrani

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Complex regional pain syndrome (CRPS) is a chronic pain condition that develops in an extremity following a fracture, soft tissue injury, or surgery. It is a neuropathic pain disorder that is accompanied by the characteristic skin manifestations that are needed for the diagnosis. We report the case of a 30 year old male, who has findings consistent with CRPS and has been followed for over two years by multiple specialties within the healthcare system without obtaining a diagnosis. The symptoms he presented with were treated based on the specialty he was seeing, rather than unified and recognized as a single disease process. Our case highlights the complexity of chronic pain, which can sometimes present with skin manifestations, and the importance of involving a pain specialist early for both the medical and physical recovery of CRPS patients.

Keywords: complex regional pain syndrome, chronic pain, skin changes of CRPS, dermatological manifestions of CRPS

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Authors: Velimir "monty" Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: Wanbao Chen, Qianqian Yao, Zhenming Zhou

Abstract:

Whole grains with intact pericarp are largely resistant to digestion by ruminants because entire kernels are not conducive to bacterial attachment. But processing methods makes the starch more accessible to microbes, and increases the rate and extent of starch degradation in the rumen. To estimate the feasibility of applying a steam-flaking as the processing technique of grains for ruminants, cereal grains (maize, wheat, barley and sorghum) were processed by steam-flaking (steam temperature 105°C, heating time, 45 min). And chemical analysis, in vitro gas production, volatile fatty acid concentrations, and energetic values were adopted to evaluate the effects of steam-flaking. In vitro cultivation was conducted for 48h with the rumen fluid collected from steers fed a total mixed ration consisted of 40% hay and 60% concentrates. The results showed that steam-flaking processing had a significant effect on the contents of neutral detergent fiber and acid detergent fiber (P < 0.01). The concentration of starch gelatinization degree in all grains was also great improved in steam-flaking grains, as steam-flaking processing disintegrates the crystal structure of cereal starch, which may subsequently facilitate absorption of moisture and swelling. Theoretical maximum gas production after steam-flaking processing showed no great difference. However, compared with intact grains, total gas production at 48 h and the rate of gas production were significantly (P < 0.01) increased in all types of grain. Furthermore, there was no effect of steam-flaking processing on total volatile fatty acid, but a decrease in the ratio between acetate and propionate was observed in the current in vitro fermentation. The present study also found that steam-flaking processing increased (P < 0.05) organic matter digestibility and energy concentration of the grains. The collective findings of the present study suggest that steam-flaking processing of grains could improve their rumen fermentation and energy utilization by ruminants. In conclusion, the utilization of steam-flaking would be practical to improve the quality of common cereal grains.

Keywords: cereal grains, gas production, in vitro rumen fermentation, steam-flaking processing

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Authors: Sehur Sibel Ozkaynak, Zakir Koc, Ebru Barcın

Abstract:

Essential tremor (ET) is one of the most common movement disorders and has long been considered a monosymptomatic disorder. While ET has traditionally been categorized as a pure motor disease, cross-sectional and longitudinal studies of cognition in ET have been demonstrated that these patients may have cognitive dysfunction. We investigated the neuro physiological aspects of cognition in ET, using event-related potentials (ERPs).Twenty patients with ET and 20 age-education and sex matched healthy controls underwent a neuro physiological evaluation. P300 components and Contingent Negative Variation (CNV) were recorded. The latencies and amplitudes of the P300 and CNV were evaluated. P200-N200 amplitude was significantly smaller in the ET group, while no differences emerged between patients and controls in P300 latencies. CNV amplitude was significantly smaller at Cz electrode site in the ET group. No differences were observed between in the two groups in CNV latencies. As a result, P300 and CNV parameters did not show significant differences between in the two groups, does not mean that there aren't mild cognitive changes in ET patients. In this regard, there is a need to further studies using electro physiological tests related to cognitive changes in ET patients.

Keywords: cognition, essential tremor, event related potentials

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Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua

Abstract:

The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.

Keywords: complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT

Procedia PDF Downloads 229

Authors: Carlos Escobar-del Pozo, César Ahumada-Monroy, Azael García-Rebolledo, Alberto Brambila-Solórzano, Gregorio Martínez-Sánchez, Luis Ortiz-Rincón

Abstract:

Numerical simulations of flow in complex biological structures have gained considerable attention in the last years. However, the major issue is the validation of the results. The present work shows a Particle Image Velocimetry PIV flow visualization technique in complex biological structures, particularly in intracranial aneurysms. A methodology to reconstruct and generate a transparent model has been developed, as well as visualization and particle tracking techniques. The generated transparent models allow visualizing the flow patterns with a regular camera using the visualization techniques. The final goal is to use visualization as a tool to provide more information on the treatment and surgery decisions in aneurysms.

Keywords: aneurysms, PIV, flow visualization, particle tracking

Procedia PDF Downloads 76