Search results for: advanced gastric cancer
2448 Modeling SET Effect on Charge Pump Phase Locked Loop
Authors: Varsha Prasad, S. Sandya
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Cosmic Ray effects in microelectronics such as single event effect (SET) and total dose ionization (TID) have been of major concern in space electronics since 1970. Advanced CMOS technologies have demonstrated reduced sensitivity to TID effect. However, charge pump Phase Locked Loop is very much vulnerable to single event transient effect. This paper presents an SET analysis model, where the SET is modeled as a double exponential pulse. The time domain analysis reveals that the settling time of the voltage controlled oscillator (VCO) depends on the SET pulse strength, setting the time constant and the damping factor. The analysis of the proposed SET analysis model is confirmed by the simulation results.Keywords: charge pump, phase locked loop, SET, VCO
Procedia PDF Downloads 4332447 Modeling of Bed Level Changes in Larak Island
Authors: Saeed Zeinali, Nasser Talebbeydokhti, Mehdi Saeidian, Shahrad Vosough
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In this article, bathymetry changes have been studied as a case study for Larak Island, located in The South of Iran. The advanced 2D model of Mike21 has been used for this purpose. A simple procedure has been utilized in this model. First, the hydrodynamic (HD) module of Mike21 has been used to obtain the required output for sediment transport model (ST module). The ST module modeled the area for tidal currents only. Bed level changes are resulted by series of modeling for both HD and ST module in 3 months time step. The final bathymetry in each time step is used as the primary bathymetry for next time step. This consecutive procedure been continued until bathymetry for the year 2020 is obtained.Keywords: bed level changes, Larak Island, hydrodynamic, sediment transport
Procedia PDF Downloads 2672446 Cutting Tools in Finishing Operations for CNC Rapid Manufacturing Processes: Experimental Studies
Authors: M. N. Osman Zahid, K. Case, D. Watts
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This paper reports an advanced approach in the application of CNC machining for rapid manufacturing processes (CNC-RM). The aim of this study is to improve the quality of machined parts by introducing different cutting tools during finishing operations. As the cutting is performed in different directions, the surfaces presented on part can be classified into several categories. Therefore, suitable cutting tools are assigned to machine particular surfaces and to improve the quality. Experimental studies have been carried out by fabricating several parts based on the suggested approach. The results provide further support for implementing this approach in rapid machining processes.Keywords: CNC machining, end mill tool, finishing operation, rapid manufacturing
Procedia PDF Downloads 3462445 Design and Development of Novel Anion Selective Chemosensors Derived from Vitamin B6 Cofactors
Authors: Darshna Sharma, Suban K. Sahoo
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The detection of intracellular fluoride in human cancer cell HeLa was achieved by chemosensors derived from vitamin B6 cofactors using fluorescence imaging technique. These sensors were first synthesized by condensation of pyridoxal/pyridoxal phosphate with 2-amino(thio)phenol. The anion recognition ability was explored by experimental (UV-VIS, fluorescence and 1H NMR) and theoretical DFT [(B3LYP/6-31G(d,p)] methods in DMSO and mixed DMSO-H2O system. All the developed sensors showed both naked-eye detectable color change and remarkable fluorescence enhancement in the presence of F- and AcO-. The anion recognition was occurred through the formation of hydrogen bonded complexes between these anions and sensor, followed by the partial deprotonation of sensor. The detection limit of these sensors were down to micro(nano) molar level of F- and AcO-.Keywords: chemosensors, fluoride, acetate, turn-on, live cells imaging, DFT
Procedia PDF Downloads 4002444 A Review on Aluminium Metal Matric Composites
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
Procedia PDF Downloads 4652443 Detergent Removal from Rinsing Water by Peroxi Electrocoagulation Process
Authors: A. Benhadji, M. Taleb Ahmed
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Among the various methods of treatment, advanced oxidation processes (AOP) are the most promising ones. In this study, Peroxi Electrocoagulation Process (PEP) was investigated for the treatment of detergent wastewater. The process was compared with electrooxidation treatment. The results showed that chemical oxygen demand (COD) was high 7584 mgO2.L-1, while the biochemical oxygen demand was low (250 mgO2.L-1). This wastewater was hardly biodegradable. Electrochemical process was carried out for the removal of detergent using a glass reactor with a volume of 1 L and fitted with three electrodes. A direct current (DC) supply was used. Samples were taken at various current density (0.0227 A/cm2 to 0.0378 A/cm2) and reaction time (1-2-3-4 and 5 hour). Finally, the COD was determined. The results indicated that COD removal efficiency of PEP was observed to increase with current intensity and reached to 77% after 5 h. The highest removal efficiency was observed after 5 h of treatment.Keywords: AOP, COD, detergent, PEP, wastewater
Procedia PDF Downloads 1192442 Investigating the Relationship between Bank and Cloud Provider
Authors: Hatim Elhag
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Banking and Financial Service Institutions are possibly the most advanced in terms of technology adoption and use it as a key differentiator. With high levels of business process automation, maturity in the functional portfolio, straight through processing and proven technology outsourcing benefits, Banking sector stand to benefit significantly from Cloud computing capabilities. Additionally, with complex Compliance and Regulatory policies, combined with expansive products and geography coverage, the business impact is even greater. While the benefits are exponential, there are also significant challenges in adopting this model– including Legal, Security, Performance, Reliability, Transformation complexity, Operating control and Governance and most importantly proof for the promised cost benefits. However, new architecture designed should be implemented to align this approach.Keywords: security, cloud, banking sector, cloud computing
Procedia PDF Downloads 4992441 Modern Information Security Management and Digital Technologies: A Comprehensive Approach to Data Protection
Authors: Mahshid Arabi
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With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.Keywords: data protection, digital technologies, information security, modern management
Procedia PDF Downloads 292440 Comparing the ‘Urgent Community Care Team’ Clinical Referrals in the Community with Suggestions from the Clinical Decision Support Software Dem DX
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Background: Additional demands placed on senior clinical teams with ongoing COVID-19 management has accelerated the need to harness the wider healthcare professional resources and upskill them to take on greater clinical responsibility safely. The UK NHS Long Term Plan (2019)¹ emphasises the importance of expanding Advanced Practitioners’ (APs) roles to take on more clinical diagnostic responsibilities to cope with increased demand. In acute settings, APs are often the first point of care for patients and require training to take on initial triage responsibilities efficiently and safely. Critically, their roles include determining which onward services the patients may require, and assessing whether they can be treated at home, avoiding unnecessary admissions to the hospital. Dem Dx is a Clinical Reasoning Platform (CRP) that claims to help frontline healthcare professionals independently assess and triage patients. It guides the clinician from presenting complaints through associated symptoms to a running list of differential diagnoses, media, national and institutional guidelines. The objective of this study was to compare the clinical referral rates and guidelines adherence registered by the HMR Urgent Community Care Team (UCCT)² and Dem Dx recommendations using retrospective cases. Methodology: 192 cases seen by the UCCT were anonymised and reassessed using Dem Dx clinical pathways. We compared the UCCT’s performance with Dem Dx regarding the appropriateness of onward referrals. We also compared the clinical assessment regarding adherence to NICE guidelines recorded on the clinical notes and the presence of suitable guidance in each case. The cases were audited by two medical doctors. Results: Dem Dx demonstrated appropriate referrals in 85% of cases, compared to 47% in the UCCT team (p<0.001). Of particular note, Dem Dx demonstrated an almost 65% (p<0.001) improvement in the efficacy and appropriateness of referrals in a highly experienced clinical team. The effectiveness of Dem Dx is in part attributable to the relevant NICE and local guidelines found within the platform's pathways and was found to be suitable in 86% of cases. Conclusion: This study highlights the potential of clinical decision support, as Dem Dx, to improve the quality of onward clinical referrals delivered by a multidisciplinary team in primary care. It demonstrated that it could support healthcare professionals in making appropriate referrals, especially those that may be overlooked by providing suitable clinical guidelines directly embedded into cases and clear referral pathways. Further evaluation in the clinical setting has been planned to confirm those assumptions in a prospective study.Keywords: advanced practitioner, clinical reasoning, clinical decision-making, management, multidisciplinary team, referrals, triage
Procedia PDF Downloads 1492439 Metagenomics, Urinary Microbiome, and Chronic Prostatitis
Authors: Elmira Davasaz Tabrizi, Mushteba Sevil, Ercan Arican
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Directly or indirectly, the human microbiome, or the population of bacteria and other microorganisms living in the human body, has been linked with human health. Various research has examined the connection with both illness status and the composition of the human microbiome, even though current studies indicate that the gut microbiome influences the mucosa and immune system. A significant amount of effort is being put into understanding the human microbiome's natural history in terms of health outcomes while also expanding our comprehension of the molecular connections between the microbiome and the host. To maintain health and avoid disease, these efforts ultimately seek to find efficient methods for recovering human microbial communities. This review article describes how the human microbiome leads to chronic diseases and discusses evidence for an important significant disorder that is related to the microbiome and linked to prostate cancer: chronic prostatitis (CP).Keywords: urobiome, chronic prostatitis, metagenomic, urinary microbiome
Procedia PDF Downloads 762438 Latest Advances in the Management of Liver Diseases
Authors: Rabab Makki, Deputy Chief Dietitian
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Malnutrition is commonly seen in Liver Disease patients. Prevalence of malnutrition in cirrhosis, is as high as 65-90%. Protein depletion and reduced muscle function are common. There are many mechanisms of malnutrition in liver cirrhosis e.g. insulin resistance, low respiratory quotient, increased glucogenesis etc. Nutrition support improves outcome in patients unable to maintain an intake of 35-40 Kcal/kg and 1.2-1.5 gm/kg/day. Simple methods of assessment such as subjective global assessment, calorie counting, MMC are useful. The value of BCAAs remains uncertain despite a considerable number of studies. Normal protein diets have been given safely to patients with hepatic encephalopathy. Restriction of protein not more than 48 hours pre- and pro-biotic, glutamine, fish oil etc are all part of the latest advanced techniques used.Keywords: liver cirrhosis, omega 3 for liver disease, nutrition management, malnutrition
Procedia PDF Downloads 2562437 Design and 3D-Printout of The Stack-Corrugate-Sheel Core Sandwiched Decks for The Bridging System
Authors: K. Kamal
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Structural sandwich panels with core of Advanced Composites Laminates l Honeycombs / PU-foams are used in aerospace applications and are also fabricated for use now in some civil engineering applications. An all Advanced Composites Foot Over Bridge (FOB) system, designed and developed for pedestrian traffic is one such application earlier, may be cited as an example here. During development stage of this FoB, a profile of its decks was then spurred as a single corrugate sheet core sandwiched between two Glass Fibre Reinforced Plastics(GFRP) flat laminates. Once successfully fabricated and used, these decks did prove suitable also to form other structure on assembly, such as, erecting temporary shelters. Such corrugated sheet core profile sandwiched panels were then also tried using the construction materials but any conventional method of construction only posed certain difficulties in achieving the required core profile monolithically within the sandwiched slabs and hence it was then abended. Such monolithic construction was, however, subsequently eased out on demonstration by dispensing building materials mix through a suitably designed multi-dispenser system attached to a 3D Printer. This study conducted at lab level was thus reported earlier and it did include the fabrication of a 3D printer in-house first as ‘3DcMP’ as well as on its functional operation, some required sandwich core profiles also been 3D-printed out producing panels hardware. Once a number of these sandwich panels in single corrugated sheet core monolithically printed out, panels were subjected to load test in an experimental set up as also their structural behavior was studied analytically, and subsequently, these results were correlated as reported in the literature. In achieving the required more depths and also to exhibit further the stronger and creating sandwiched decks of better structural and mechanical behavior, further more complex core configuration such as stack corrugate sheets core with a flat mid plane was felt to be the better sandwiched core. Such profile remained as an outcome that turns out merely on stacking of two separately printed out monolithic units of single corrugated sheet core developed earlier as above and bonded them together initially, maintaining a different orientation. For any required sequential understanding of the structural behavior of any such complex profile core sandwiched decks with special emphasis to study of the effect in the variation of corrugation orientation in each distinct tire in this core, it obviously calls for an analytical study first. The rectangular,simply supported decks have therefore been considered for analysis adopting the ‘Advanced Composite Technology(ACT), some numerical results along with some fruitful findings were obtained and these are all presented here in this paper. From this numerical result, it has been observed that a mid flat layer which eventually get created monolethically itself, in addition to eliminating the bonding process in development, has been found to offer more effective bending resistance by such decks subjected to UDL over them. This is understood to have resulted here since the existence of a required shear resistance layer at the mid of the core in this profile, unlike other bending elements. As an addendum to all such efforts made as covered above and was published earlier, this unique stack corrugate sheet core profile sandwiched structural decks, monolithically construction with ease at the site itself, has been printed out from a 3D Printer. On employing 3DcMP and using some innovative building construction materials, holds the future promises of such research & development works since all those several aspects of a 3D printing in construction are now included such as reduction in the required construction time, offering cost effective solutions with freedom in design of any such complex shapes thus can widely now be realized by the modern construction industry.Keywords: advance composite technology(ACT), corrugated laminates, 3DcMP, foot over bridge (FOB), sandwiched deck units
Procedia PDF Downloads 1722436 Review, Analysis and Simulation of Advanced Technology Solutions of Selected Components in Power Electronics Systems (PES) of More Electric Aircraft
Authors: Lucjan Setlak, Emil Ruda
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The subject of this paper is to review, comparative analysis and simulation of selected components of power electronic systems (PES), consistent with the concept of a more electric aircraft (MEA). Comparative analysis and simulation in software environment MATLAB / Simulink were carried out based on a group of representatives of civil aircraft (B-787, A-380) and military (F-22 Raptor, F-35) in the context of multi-pulse converters used in them (6- and 12-pulse, and 18- and 24-pulse), which are key components of high-tech electronics on-board power systems of autonomous power systems (ASE) of modern aircraft (airplanes of the future).Keywords: converters, electric machines, MEA (more electric aircraft), PES (power electronics systems)
Procedia PDF Downloads 4942435 Predictive Modelling of Aircraft Component Replacement Using Imbalanced Learning and Ensemble Method
Authors: Dangut Maren David, Skaf Zakwan
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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.Keywords: prognostics, data-driven, imbalance classification, deep learning
Procedia PDF Downloads 1742434 Target Training on Chinese as a Tonal Language for Better Communication
Authors: Qi Wang
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Accurate pronunciation is the first condition of communication. Compared with the alphabetic languages, Chinese is more difficult for the foreigners to study as a second language, due to the tonal language with the meaningful characters as the written system, especially speaking. This research first presents the statistics of the typical errors of the pronunciations, based on the data of our two- year program of graduate students, which shown 90% of their speaking with strong foreign accents and no obvious change of the pitches, even if they could speak Chinese fluently. Second part, analyzed the caused reasons in the learning and teaching processes. Third part, this result of this research, based the theory of Chinese prosodic words, shown that the earlier the students get trained on prosodics at the beginning and suprasegmentals at intermediate and advanced levels, the better effects for them to communicate in Chinese as a second language.Keywords: second language, prosodic word, foot, suprasegmental
Procedia PDF Downloads 4622433 Smart Structures for Cost Effective Cultural Heritage Preservation
Authors: Tamara Trček Pečak, Andrej Mohar, Denis Trček
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This article investigates the latest technological means, which deploy smart structures that are based on (advanced) wireless sensors technologies and ubiquitous computing in general in order to support the above mentioned decision making. Based on two years of in-field research experiences it gives their analysis for these kinds of purposes and provides appropriate architectures and architectural solutions. Moreover, the directions for future research are stated, because these technologies are currently the most promising ones to enable cost-effective preservation of cultural heritage not only in uncontrolled places, but also in general.Keywords: smart structures, wireless sensors, sensors networks, green computing, cultural heritage preservation, monitoring, cost effectiveness
Procedia PDF Downloads 4462432 Applying Big Data Analysis to Efficiently Exploit the Vast Unconventional Tight Oil Reserves
Authors: Shengnan Chen, Shuhua Wang
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Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves
Procedia PDF Downloads 2832431 Parallel Computing: Offloading Matrix Multiplication to GPU
Authors: Bharath R., Tharun Sai N., Bhuvan G.
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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks
Procedia PDF Downloads 582430 Use of Segmentation and Color Adjustment for Skin Tone Classification in Dermatological Images
Authors: Fernando Duarte
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The work aims to evaluate the use of classical image processing methodologies towards skin tone classification in dermatological images. The skin tone is an important attribute when considering several factor for skin cancer diagnosis. Currently, there is a lack of clear methodologies to classify the skin tone based only on the dermatological image. In this work, a recent released dataset with the label for skin tone was used as reference for the evaluation of classical methodologies for segmentation and adjustment of color space for classification of skin tone in dermatological images. It was noticed that even though the classical methodologies can work fine for segmentation and color adjustment, classifying the skin tone without proper control of the aquisition of the sample images ended being very unreliable.Keywords: segmentation, classification, color space, skin tone, Fitzpatrick
Procedia PDF Downloads 352429 Sleep Scheduling Schemes Integrating Relay Node and User Equipment in LTE-A
Authors: Chun-Chuan Yang, Jeng-Yueng Chen, Yi-Ting Mai, Hsieh-Hua Liu
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By introduction of Relay Nodes (RNs), LTE-Advanced can provide enhanced coverage and capacity at cell edges and hot-spot areas. The authors have been researching the issue of power saving in mobile communications technology such as WiMax and LTE for some years. Based on the idea of Load-Based Power Saving (LBPS), three efficient power saving schemes for the user equipment (UE) were proposed in the authors’ previous work. In this paper, three revised schemes of the previous work in order to integrate RN and UE in power saving are proposed. Simulation study shows the proposed schemes can achieve significantly better power saving efficiency than the standard based scheme at the cost of moderately increased delay.Keywords: DRX, LTE-A, power saving, RN
Procedia PDF Downloads 5242428 A Metacognitive Strategy to Improve Saudi EFL Learners’ Lecture Comprehension
Authors: Abdul Wahed Al Zumor
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Saudi EFL Students majoring in English face difficulties in academic lectures listening comprehension in content courses like linguistics, applied linguistics or literature theories. To validate this assumption, a questionnaire assessing students' lecture comprehension experience was administered. The findings have shown that Saudi EFL learners face a great challenge in lecture comprehension at advanced levels. Literature has suggested a myriad of techniques which can enhance academic lecture comprehension. This study has used "reciprocal peer-questioning and responding technique" as an integral part of the academic lecture occupying the last ten minutes. Improvement in experimental students' scores in these courses has been noticed.Keywords: EFL learners, lecture comprehension, content courses, peer questioning
Procedia PDF Downloads 5962427 The Relevance of Smart Technologies in Learning
Authors: Rachael Olubukola Afolabi
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Immersive technologies known as X Reality or Cross Reality that include virtual reality augmented reality, and mixed reality have pervaded into the education system at different levels from elementary school to adult learning. Instructors, instructional designers, and learning experience specialists continue to find new ways to engage students in the learning process using technology. While the progression of web technologies has enhanced digital learning experiences, analytics on learning outcomes continue to be explored to determine the relevance of these technologies in learning. Digital learning has evolved from web 1.0 (static) to 4.0 (dynamic and interactive), and this evolution of technologies has also advanced teaching methods and approaches. This paper explores how these technologies are being utilized in learning and the results that educators and learners have identified as effective learning opportunities and approaches.Keywords: immersive technologoes, virtual reality, augmented reality, technology in learning
Procedia PDF Downloads 1452426 Internet of Things Professional Construction Building through the School-Enterprise Cooperation
Authors: Jumin Zhao, Na Li, Dengao Li, Yujuan Yan
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As the rapid rise of the networking industry, the shortage of Internet of Things (IoT) talented people greatly stimulates the majority of colleges to speed up the pace of professional networking reform. Caused by the construction of the original specialty, many problems appear such as the vague specialty, the mixed theoretical, the poor practical ability and the different goal. To solve the issues above, we build a ‘theory-practice-theory-improvement’ four-step model of school-enterprise integration of personnel training. Besides, we integrate the advanced teaching philosophy: flip class and Mu class, making IoT teaching more professional and the ability of students more comprehensive.Keywords: IoT, theory-practice-theory-promotion, major construction, school-enterprise cooperation
Procedia PDF Downloads 3812425 Targeted Delivery of Docetaxel Drug Using Cetuximab Conjugated Vitamin E TPGS Micelles Increases the Anti-Tumor Efficacy and Inhibit Migration of MDA-MB-231 Triple Negative Breast Cancer
Authors: V. K. Rajaletchumy, S. L. Chia, M. I. Setyawati, M. S. Muthu, S. S. Feng, D. T. Leong
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Triple negative breast cancers (TNBC) can be classified as one of the most aggressive with a high rate of local recurrences and systematic metastases. TNBCs are insensitive to existing hormonal therapy or targeted therapies such as the use of monoclonal antibodies, due to the lack of oestrogen receptor (ER) and progesterone receptor (PR) and the absence of overexpression of human epidermal growth factor receptor 2 (HER2) compared with other types of breast cancers. The absence of targeted therapies for selective delivery of therapeutic agents into tumours, led to the search for druggable targets in TNBC. In this study, we developed a targeted micellar system of cetuximab-conjugated micelles of D-α-tocopheryl polyethylene glycol succinate (vitamin E TPGS) for targeted delivery of docetaxel as a model anticancer drug for the treatment of TNBCs. We examined the efficacy of our micellar system in xenograft models of triple negative breast cancers and explored the effect of the micelles on post-treatment tumours in order to elucidate the mechanism underlying the nanomedicine treatment in oncology. The targeting micelles were found preferentially accumulated in tumours immediately after the administration of the micelles compare to normal tissue. The fluorescence signal gradually increased up to 12 h at the tumour site and sustained for up to 24 h, reflecting the increases in targeted micelles (TPFC) micelles in MDA-MB-231/Luc cells. In comparison, for the non-targeting micelles (TPF), the fluorescence signal was evenly distributed all over the body of the mice. Only a slight increase in fluorescence at the chest area was observed after 24 h post-injection, reflecting the moderate uptake of micelles by the tumour. The successful delivery of docetaxel into tumour by the targeted micelles (TPDC) exhibited a greater degree of tumour growth inhibition than Taxotere® after 15 days of treatment. The ex vivo study has demonstrated that tumours treated with targeting micelles exhibit enhanced cell cycle arrest and attenuated proliferation compared with the control and with those treated non-targeting micelles. Furthermore, the ex vivo investigation revealed that both the targeting and non-targeting micellar formulations shows significant inhibition of cell migration with migration indices reduced by 0.098- and 0.28-fold, respectively, relative to the control. Overall, both the in vivo and ex vivo data increased the confidence that our micellar formulations effectively targeted and inhibited EGF-overexpressing MDA-MB-231 tumours.Keywords: biodegradable polymers, cancer nanotechnology, drug targeting, molecular biomaterials, nanomedicine
Procedia PDF Downloads 2812424 Optimization of Dual Band Antenna on Silicon Substrate
Authors: Syrine lahmadi, Jamel Bel Hadj Tahar
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In this paper, a rectangular antenna with slots integrated on silicon substrate operating in 60GHz, is studied and optimized. The effect of different parameter of the antenna (width, length, the position of the microstrip-feed line...) and the parameter of the substrate (the thickness, the dielectric constant) on gain, frequency is presented. Also, the paper presents a solution to ameliorate the bandwidth. The maximum simulated radiation gain of this rectangular dual band antenna is 5, 38 dB around 60GHz. The simulation studied id developed based on advanced design system tools. It is found that the designed antenna is 19 % smaller than a rectangular antenna with the same dimensions. This antenna with dual band can function for many communication systems as automobile or radar.Keywords: dual band, enlargement of bandwidth, miniaturized antennas, printed antenna
Procedia PDF Downloads 3582423 Systematic Exploration and Modulation of Nano-Bio Interactions
Authors: Bing Yan
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Nanomaterials are widely used in various industrial sectors, biomedicine, and more than 1300 consumer products. Although there is still no standard safety regulation, their potential toxicity is a major concern worldwide. We discovered that nanoparticles target and enter human cells1, perturb cellular signaling pathways2, affect various cell functions3, and cause malfunctions in animals4,5. Because the majority of atoms in nanoparticles are on the surface, chemistry modification on their surface may change their biological properties significantly. We modified nanoparticle surface using nano-combinatorial chemistry library approach6. Novel nanoparticles were discovered to exhibit significantly reduced toxicity6,7, enhance cancer targeting ability8, or re-program cellular signaling machineries7. Using computational chemistry, quantitative nanostructure-activity relationship (QNAR) is established and predictive models have been built to predict biocompatible nanoparticles.Keywords: nanoparticle, nanotoxicity, nano-bio, nano-combinatorial chemistry, nanoparticle library
Procedia PDF Downloads 4092422 Using “Debate” in Enhancing Advanced Chinese Language Classrooms and Learning
Authors: ShuPei Wang, Yina Patterson
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This article outlines strategies for improving oral expression to advance proficiency in speaking and listening skills through structured argumentation. The objective is to empower students to effectively use the target language to express opinions and construct compelling arguments. This empowerment is achieved by honing learners' debating and questioning skills, which involves increasing their familiarity with vocabulary and phrases relevant to debates and deepening their understanding of the cultural context surrounding pertinent issues. Through this approach, students can enhance their ability to articulate complex concepts and discern critical points, surpassing superficial comprehension and enabling them to engage in the target language actively and competently.Keywords: debate, teaching and materials design, spoken expression, listening proficiency, critical thinking
Procedia PDF Downloads 692421 Synthesis and Anti-Cancer Evaluation of Uranyle Complexes
Authors: Abdol-Hassan Doulah
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In this research, some of the inorganic complexes of uranyl with N- donor ligands were synthesized. Complexes were characteriezed by FT-IR and UV spectra, ¹HNMR, ¹³CNMR and some physical properties. The uranyl unit (UO2) is composed of a center of uranium atom with the charge (+6) and two oxygen atom by forming two U=O double bonds. The structure is linear (O=U=O, 180) and usually stable. So other ligands often coordinate to the U atom in the plane perpendicularly to the O=U=O axis. The antitumor activity of some of ligand and their complexes against a panel of human tumor cell lines (HT29: Haman colon adenocarcinoma cell line T47D: human breast adenocarcinoma cell line) were determined by MTT(3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl-tetrazolium bromide) assay. These data suggest that some of these compounds provide good models for the further design of potent antitumor compounds.Keywords: inorganic, uranyl complex-donor ligands, Schiff bases, anticancer activity
Procedia PDF Downloads 4542420 Correlation Between Different Radiological Findings and Histopathological diagnosis of Breast Diseases: Retrospective Review Conducted Over Sixth Years in King Fahad University Hospital in Eastern Province, Saudi Arabia
Authors: Sadeem Aljamaan, Reem Hariri, Rahaf Alghamdi, Batool Alotaibi, Batool Alsenan, Lama Althunayyan, Areej Alnemer
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The aim of this study is to correlate between radiological findings and histopathological results in regard to the breast imaging-reporting and data system scores, size of breast masses, molecular subtypes and suspicious radiological features, as well as to assess the concordance rate in histological grade between core biopsy and surgical excision among breast cancer patients, followed by analyzing the change of concordance rate in relation to neoadjuvant chemotherapy in a Saudi population. A retrospective review was conducted over 6-year period (2017-2022) on all breast core biopsies of women preceded by radiological investigation. Chi-squared test (χ2) was performed on qualitative data, the Mann-Whitney test for quantitative non-parametric variables, and the Kappa test for grade agreement. A total of 641 cases were included. Ultrasound, mammography, and magnetic resonance imaging demonstrated diagnostic accuracies of 85%, 77.9% and 86.9%; respectively. magnetic resonance imaging manifested the highest sensitivity (72.2%), and the lowest was for ultrasound (61%). Concordance in tumor size with final excisions was best in magnetic resonance imaging, while mammography demonstrated a higher tendency of overestimation (41.9%), and ultrasound showed the highest underestimation (67.7%). The association between basal-like molecular subtypes and the breast imaging-reporting and data system score 5 classifications was statistically significant only for magnetic resonance imaging (p=0.04). Luminal subtypes demonstrated a significantly higher percentage of speculation in mammography. Breast imaging-reporting and data system score 4 manifested a substantial number of benign pathologies in all the 3 modalities. A fair concordance rate (k= 0.212 & 0.379) was demonstrated between excision and the preceding core biopsy grading with and without neoadjuvant therapy, respectively. The results demonstrated a down-grading in cases post-neoadjuvant therapy. In cases who did not receive neoadjuvant therapy, underestimation of tumor grade in biopsy was evident. In summary, magnetic resonance imaging had the highest sensitivity, specificity, positive predictive value and accuracy of both diagnosis and estimation of tumor size. Mammography demonstrated better sensitivity than ultrasound and had the highest negative predictive value, but ultrasound had better specificity, positive predictive value and accuracy. Therefore, the combination of different modalities is advantageous. The concordance rate of core biopsy grading with excision was not impacted by neoadjuvant therapy.Keywords: breast cancer, mammography, MRI, neoadjuvant, pathology, US
Procedia PDF Downloads 822419 Development of a Novel Clinical Screening Tool, Using the BSGE Pain Questionnaire, Clinical Examination and Ultrasound to Predict the Severity of Endometriosis Prior to Laparoscopic Surgery
Authors: Marlin Mubarak
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Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.
Procedia PDF Downloads 353