Search results for: covering machine

Authors: Karolin Bauer, Anna Brinkmann

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Vulnerabilities in critical infrastructure can cause significant difficulties for the affected population during crises. Securing the food supply as part of the critical infrastructure in crisis situations is an essential part of public services and a ground stone for a successful concept of civil protection. In most industrialized countries, there are currently no comparative studies regarding the food supply of the population during crisis and disaster events. In order to mitigate the potential impact in case of major disasters in Germany, it is absolutely necessary to investigate how the food supply can be secured. The research project aims to provide in-depth research on the experiences gathered during past large-scale disasters in the 34 OECD member countries in order to discover alternatives for an updated civil protection system in Germany. The basic research question is: "Which international approaches and structures of civil protection have been proven and would be useful to modernize the German civil protection with regards to the critical infrastructure and food supply?" Research findings should be extracted from an extensive literature review covering the entire research period as well as from personal and online-based interviews with experts and responsible persons from involved institutions. The capability of the research project insists on the deliberate choice to investigate previous large-scale disasters to formulate important and practical approaches to modernize civil protection in Germany.

Keywords: food supply, vulnerabilty, critical infratstructure, large-scale disaster

Procedia PDF Downloads 338

Authors: Luo Jiaoyang, Yu Hongyang

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In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: Habib Alehossein, M. S. K. Fernando

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Soil density depends on the volume of the voids and the proportion of the water and air in the voids. However, there is a limit to the contraction of the voids at any given compaction energy, whereby additional water is used to reduce the void volume further by lubricating the particles' frictional contacts. Hence, at an optimum moisture content and specific compaction energy, the density of unsaturated soil can be maximized where the void volume is minimum. However, when considering a full compaction curve and permutations and variations of all these components (soil, air, water, and energy), laboratory soil compaction tests can become expensive, time-consuming, and exhausting. Therefore, analytical methods constructed on a few test data can be developed and used to reduce such unnecessary efforts significantly. Concentrating on the compaction testing results, this study discusses the analytical modelling method developed for some fine-grained and coarse-grained soils of Queensland. Soil properties and characteristics, such as full functional compaction curves under various compaction energy conditions, were studied and developed for a few soil types. Using MATLAB, several generic analytical codes were created for this study, covering all possible compaction parameters and results as they occur in a soil mechanics lab. These MATLAB codes produce a family of curves to determine the relationships between the density, moisture content, void ratio, saturation, and compaction energy.

Keywords: analytical, MATLAB, modelling, compaction curve, void ratio, saturation, moisture content

Procedia PDF Downloads 95

Authors: Kevin William Taylor

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This work used industry-standard practices and technologies as a foundation to explore current and future advancements in modularity for 3D environmental production. Covering environmental generation, and AI-assisted generation, this study investigated how these areas will shape the industries goal to achieve full immersion within augmented reality environments. This study will explore modular environmental construction techniques utilized in large scale 3D productions. This will include the reasoning behind this approach to production, the principles in the successful development, potential pitfalls, and different methodologies for successful implementation of practice in commercial and proprietary interactive engines. A focus will be on the role of the 3D artists in the future of environmental development, requiring adaptability to new approaches, as the field evolves in response to tandem technological advancements. Industry findings and projections theorize how these factors will impact the widespread utilization of augmented reality in daily life. This will continue to inform the direction of technology towards expansive interactive environments. It will change the tools and techniques utilized in the development of environments for game, film, and VFX. This study concludes that this technology will be the cornerstone for the creation of AI-driven AR that is able to fully theme our world, change how we see and engage with one another. This will impact the concept of a virtual self-identity that will be as prevalent as real-world identity. While this progression scares or even threaten some, it is safe to say that we are seeing the beginnings of a technological revolution that will surpass the impact that the smartphone had on modern society.

Keywords: virtual reality, augmented reality, training, 3D environments

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Authors: A. Sopharak, B. Uyyanonvara, S. Barman

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Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists’ hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.

Keywords: diabetic retinopathy, microaneurysm, naive Bayes classifier, SVM classifier

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Authors: John Ayisi, Gideon M. Kivengea, George A. Ombakho

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In this emerging era of knowledge economy, universities, as major centres of learning and research, are becoming increasingly important as sources of ideas, knowledge, skills, innovation and technological advances. These ideas can be turned into new products, processes and systems needed to drive their respective national economies, and thus placing universities at the centre of the national innovation systems. Thus, commercialization of research outputs from universities to industry has become an area of strong policy interest in African countries. To assess the level of commercialization of research outputs in Kenyan universities, a standardized questionnaire covering seven sub-sections, namely: University Commercialization Environment, Management of Commercialization Activities, Commercialization Office, Intellectual Property Rights (IPRs), Early Stage Financing and Venture Capital; Industrial Linkages; and Technology Parks and Incubators was administered among a few selected public and private universities. Results show that all the universities have a strategic plan; though not all have innovation and commercialization as part of it. Half the nineteen surveyed universities indicated they have created designated offices for fostering commercialization. Majority have guidelines on IPRs which advocate IP to be co-owned by researcher/university. University-industry linkages are weak. Most universities are taking precursory steps to incentivise and encourage entrepreneurial activities among their academic staff and students, even though the level of resources devoted to them is low. It is recommended that building capacity in entrepreneurship among staff and students and committing more resources to R&D activities hold potential to increased commercialization of university research outputs.

Keywords: commercialization, knowledge, R&D, university

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Authors: Timiebi Aganaba-Jeanty

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Accurate and transparent monitoring, reporting and verification of Greenhouse Gas (GHG) emissions and removals is a requirement of the United Nations Framework Convention on Climate Change (UNFCCC). Several countries are obligated to prepare and submit an annual national greenhouse gas inventory covering anthropogenic emissions by sources and removals by sinks, subject to a review conducted by an international team of experts. However, the process is not without flaws. The self-reporting varies enormously in thoroughness, frequency and accuracy including inconsistency in the way such reporting occurs. The world’s space agencies are calling for a new generation of satellites that would be precise enough to map greenhouse gas emissions from individual nations. The plan is delicate politically because the global system could verify or cast doubt on emission reports from the member states of the UNFCCC. A level playing field is required and an idea that an international system should be perceived as an instrument to facilitate fairness and equality rather than to spy on or punish. This change of perspective is required to get buy in for an international verification system. The research proposes the viability of a satellite system that provides independent access to data regarding greenhouse gas emissions and the policy and governance implications of its potential use as a monitoring and verification system for the Paris Agreement. It assesses the foundations of the reporting monitoring and verification system as proposed in Paris and analyzes this in light of a proposed satellite system. The use of remote sensing technology has been debated for verification purposes and as evidence in courts but this is not without controversy. Lessons can be learned from its use in this context.

Keywords: greenhouse gas emissions, reporting, monitoring and verification, satellite, UNFCCC

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Authors: Nidhi Gopal

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Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

Procedia PDF Downloads 815

Authors: Lou J. Pino, Mark Campbell, Matthew J. Kennedy, Ashleigh C. Kennedy

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A concussion is complex and nuanced, with cognitive rest being a key component of recovery. Cognitive overexertion during rehabilitation from a concussion is associated with delayed recovery. However, daily living imposes cognitive demands that may be unavoidable and difficult to quantify. Therefore, a portable tool capable of alerting patients before cognitive overexertion occurs could allow patients to maintain their quality of life while preventing symptoms and recovery setbacks. EEG allows for a sensitive measure of cognitive exertion. Clinical 32-lead EEG headsets are not practical for day-to-day concussion rehabilitation management. However, there are now commercially available and affordable portable EEG headsets. Thus, these headsets can potentially be used to continuously monitor cognitive exertion during mental tasks to alert the wearer of overexertion, with the aim of preventing the occurrence of symptoms to speed recovery times. The objective of this study was to test an algorithm for predicting cognitive exertion from EEG data collected from a portable headset. EEG data were acquired from 10 participants (5 males, 5 females). Each participant wore a portable 4 channel EEG headband while completing 10 tasks: rest (eyes closed), rest (eyes open), three levels of the increasing difficulty of logic puzzles, three levels of increasing difficulty in multiplication questions, rest (eyes open), and rest (eyes closed). After each task, the participant was asked to report their perceived level of cognitive exertion using the NASA Task Load Index (TLX). Each participant then completed a second session on a different day. A customized machine learning model was created using data from the first session. The performance of each model was then tested using data from the second session. The mean correlation coefficient between TLX scores and predicted cognitive exertion was 0.75 ± 0.16. The results support the efficacy of the algorithm for predicting cognitive exertion. This demonstrates that the algorithms developed in this study used with portable EEG devices have the potential to aid in the concussion recovery process by monitoring and warning patients of cognitive overexertion. Preventing cognitive overexertion during recovery may reduce the number of symptoms a patient experiences and may help speed the recovery process.

Keywords: cognitive activity, EEG, machine learning, personalized recovery

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Authors: Javed Iqbal, R. Ahmed, M. A. Baig

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We present new data on the optical emission spectra of the laser produced lead plasma using a pulsed Nd:YAG laser at 1064 nm (pulse energy 400 mJ, pulse width 5 ns, 10 Hz repetition rate) in conjunction with a set of miniature spectrometers covering the spectral range from 200 nm to 720 nm. Well resolved structure due to the 6p7s → 6p2 transition array of neutral lead and a few multiplets of singly ionized lead have been observed. The electron temperatures have been calculated in the range (9000 - 10800) ± 500 K using four methods; two line ratio, Boltzmann plot, Saha-Boltzmann plot and Morrata method whereas, the electron number densities have been determined in the range (2.0 – 8.0) ± 0.6 ×1016 cm-3 using the Stark broadened line profiles of neutral lead lines, singly ionized lead lines and hydrogen Hα-line. Full width at half maximum (FWHM) of a number of neutral and singly ionized lead lines have been extracted by the Lorentzian fit to the experimentally observed line profiles. Furthermore, branching fractions have been deduced for eleven lines of the 6p7s → 6p2 transition array in lead whereas the absolute values of the transition probabilities have been calculated by combining the experimental branching fractions with the life times of the excited levels The new results are compared with the existing data showing a good agreement.

Keywords: LIBS, plasma parameters, transition probabilities, branching fractions, stark width

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Authors: P. Pötters, A. Marquet, B. Leyendecker

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The objective of this paper is to investigate different implementation approaches for the implementation of Lean production in companies. Furthermore, a structured overview of those different approaches is to be made. Therefore, the present work is intended to answer the following research question: What differences and similarities exist between the various systematic approaches and phase models for the implementation of Lean Production? To present various approaches for the implementation of Lean Production discussed in the literature, a qualitative content analysis was conducted. Within the framework of a qualitative survey, a selection of texts dealing with lean production and its introduction was examined. The analysis presents different implementation approaches from the literature, covering the descriptive aspect of the study. The study also provides insights into similarities and differences among the implementation approaches, which are drawn from the analysis of latent text contents and author interpretations. In this study, the focus is on identifying differences and similarities among systemic approaches for implementing Lean Production. The research question takes into account the main object of consideration, objectives pursued, starting point, procedure, and endpoint of the implementation approach. The study defines the concept of Lean Production and presents various approaches described in literature that companies can use to implement Lean Production successfully. The study distinguishes between five systemic implementation approaches and seven phase models to help companies choose the most suitable approach for their implementation project. The findings of this study can contribute to enhancing transparency regarding the existing approaches for implementing Lean Production. This can enable companies to compare and contrast the available implementation approaches and choose the most suitable one for their specific project.

Keywords: implementation, lean production, phase models, systematic approaches

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Authors: Farah Al-Fityani, Aljohara Alsowail, Shatha Bindawood, Heba Balrbeah

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Locket is a popular app that lets users share spontaneous photos with a close circle of friends. The app offers a unique way to stay connected with loved ones by allowing users to see glimpses of their day through photos displayed on a widget on their home screen. This summary outlines the process of developing an app like Locket, highlighting the importance of user privacy and security. It also details the findings of a study on user engagement with the Locket app, revealing positive sentiment towards its features and concept but also identifying areas for improvement. Overall, the summary portrays Locket as a successful app that is changing the way people connect on social media.

Keywords: locket, app, machine learning, connect

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Authors: Lisa Snape, Andreas Lang, Tony Brown, Dan Fallu, Ben Pears

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Agricultural terraced landscapes are widespread in mountainous areas in a variety of climatic zones around the World. The most famous are those found associated with the famous Inca site of Machu Pichu in the Andes, the arid lands in upland areas of Yemen, and the abundant rice terraces covering the hilltops in tropical areas such as Thailand, Vietnam, and China and also Bali. Terraces were designed using advanced engineered techniques, requiring specialist knowledge of bedrock geology, soil cultivation and maintenance, and ecosystem management to grow a variety of crops in specific environmental conditions. These enigmatic landscapes were often overlooked in the past but have now received widespread attention to further understand their age, origins, and evolution as the landscapes and environment changed over time. By understanding the age and chronologies of agricultural terrace technology, we can enhance our understanding of these unique features considered widely as important ecosystem services in the present day. We present distinct luminescence dating evidence from a variety of terraced systems found in different European environmental settings, such as the UK, Italy and Belgium, as part of the wider ERC-funded TerrACE Project. Our research aims to better understand their history and advocate for their protection and effective management as important cultural, heritage and environmental assets, creating new avenues for future scientific research.

Keywords: terraces, agriculture, luminescence dating, heritage protection

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Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

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ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

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Authors: Sisaynew Tesfaw Admassu

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The strengthening of timber beams can be necessary for several reasons including the increase of live loads (possible in a historical building for a change of destination of use or upgrading to meet new requirements), the reduction of the resistant cross-sections following deterioration (attacks of biological agents such as fungi, and insects) or traumatic events (fires) and the excess of deflection in the members. The main purpose of strengthening an element is not merely to repair it, but also to prevent and minimize the appearance of future problems. This study did an experimental investigation on the behavior of reference and strengthened solid timber beams. The strengthening materials used in this study were CSM-450 glass fiber and steel materials for both flexural and shear strengthening techniques. Twenty-two solid timber beams of Juniperus procera (TID) species with the dimensions of 60 x 90 x 780 mm were used in the present study. The binding material to bond the strengthening materials with timber was general-purpose resin with Luperox® K10 MEKP catalyst. Three beams were used as control beams (unstrengthen beams) while the remaining nineteen beams were strengthened using the strengthening materials for flexure and shear. All the beams were tested for three points loading to failure by using a Universal Testing Machine, UTM-600kN machine. The experimental results showed that the strengthened beams performed better than the unstrengthen beams. The experimental result of flexural strengthened beams showed that the load-bearing capacity of strengthened beams increased between 16.34 – 42.55%. Four layers of Glass Fiber Reinforced polymer on the tension side of the beams was shown to be the most effective way to enhance load-bearing capacity. The strengthened beams also have an enhancement in their flexural stiffness. The stiffness of flexural strengthened beams was increased between 1.18 – 65.53% as compared to the control beams. The highest increment in stiffness has occurred on beams strengthened using 2x60 mm steel plates. The shear-strengthened beams showed a relatively small amount of performance as compared to flexural-strengthened beams; the reason is that the beams are sufficient for shear. The polyester resin used in the experimental work showed good performance in bonding agents between materials. The resin showed more effectiveness in GFRP materials than steel materials.

Keywords: heritage structures, strengthening, stiffness, adhesive, polyester resin, steel plates

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Niklas Bondesson

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Purpose: This paper attempts to examine how different facets of attitudinal brand loyalty are determined by different brand image elements in business markets. Design/Methodology/Approach: Statistical analysis is employed to data from a web survey, covering 226 professional packaging buyers in eight countries. Findings: The results reveal that different brand loyalty facets have different antecedents. Affective brand loyalties (or loyalty 'feelings') are mainly driven by customer associations to service relationships, whereas customers’ loyalty intentions (to purchase and recommend a brand) are triggered by associations to the general reputation of the company. The findings also indicate that willingness to pay a price premium is a distinct form of loyalty, with unique determinants. Research implications: Theoretically, the paper suggests that corporate B2B brand loyalty needs to be conceptualised with more refinement than has been done in extant B2B branding work. Methodologically, the paper highlights that single-item approaches can be fruitful when measuring B2B brand loyalty, and that multi-item scales can conceal important nuances in terms of understanding why customers are loyal. Practical implications: The idea of a loyalty 'silver metric' is an attractive idea, but this study indicates that firms who rely too much on one single type of brand loyalty risk to miss important building blocks. Originality/Value/Contribution: The major contribution is a more multi-faceted conceptualisation, and measurement, of corporate B2B brand loyalty and its brand image determinants than extant work has provided.

Keywords: brand equity, business-to-business branding, industrial marketing, buying behaviour

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Hasan Basaran, Emre Unal

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Formation flying of satellites is a mission that involves a relative position keeping of different satellites in the constellation. In this study, different control algorithms are compared with one another in terms of ΔV, velocity increment, and tracking error. Various control methods, covering continuous and impulsive approaches are implemented and tested for satellites flying in low Earth orbit. Feedback linearization, sliding mode control, and model predictive control are designed and compared with an impulsive feedback law, which is based on mean orbital elements. Feedback linearization and sliding mode control approaches have identical mathematical models that include second order Earth oblateness effects. The model predictive control, on the other hand, does not include any perturbations and assumes circular chief orbit. The comparison is done with 4 different initial errors and achieved with velocity increment, root mean square error, maximum steady state error, and settling time. It was observed that impulsive law consumed the least ΔV, while produced the highest maximum error in the steady state. The continuous control laws, however, consumed higher velocity increments and produced lower amounts of tracking errors. Finally, the inversely proportional relationship between tracking error and velocity increment was established.

Keywords: chief-deputy satellites, feedback linearization, follower-leader satellites, formation flight, fuel consumption, model predictive control, rendezvous, sliding mode

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Authors: Mohammed Nasser Al-Suqri

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Former information-seeking models are proposed more than two decades ago. These already existed models were given prior to the evolution of digital information era and Artificial Intelligence (AI) technologies. Lack of current information seeking models within Library and Information Studies resulted in fewer advancements for teaching students about information-seeking behaviors, design of library tools and services. In order to better facilitate the aforementioned concerns, this study aims to propose state-of-the-art model while focusing on the information seeking behavior of library users in the Sultanate of Oman. This study aims for the development, designing and contextualizing the real-time user-centric information seeking model capable of enhancing information needs and information usage along with incorporating critical insights for the digital library practices. Another aim is to establish far-sighted and state-of-the-art frame of reference covering Artificial Intelligence (AI) while synthesizing digital resources and information for optimizing information-seeking behavior. The proposed study is empirically designed based on a mix-method process flow, technical surveys, in-depth interviews, focus groups evaluations and stakeholder investigations. The study data pool is consist of users and specialist LIS staff at 4 public libraries and 26 academic libraries in Oman. The designed research model is expected to facilitate LIS by assisting multi-dimensional insights with AI integration for redefining the information-seeking process, and developing a technology rich model.

Keywords: artificial intelligence, information seeking, information behavior, information seeking models, libraries, Sultanate of Oman

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Authors: Arrate Barrenechea Garro

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Background: Bilingualism has been shown to enhance cognitive reserve and potentially delay the onset of dementia symptoms. This study investigates the impact of bilingualism on cognitive reserve and the age of diagnosis in Parkinson's Disease (PD). Methodology: The study involves 16 non-demented monolingual PD patients and 12 non-demented bilingual PD patients, matched for age, sex, and years of education. All participants are native Spanish speakers, with Spanish as their first language (L1). Cognitive performance is assessed through a neuropsychological examination covering all cognitive domains. Cognitive reserve is measured using the Cognitive Reserve Index Questionnaire (CRIq), while language proficiency is evaluated using the Bilingual Language Profile (BLP). The age at diagnosis is recorded for both monolingual and bilingual patients. Results: Bilingual PD patients demonstrate higher scores on the CRIq compared to monolingual PD patients, with significant differences between the groups. Furthermore, there is a positive correlation between cognitive reserve (CRIq) and the utilization of the second language (L2) as indicated by the BLP. Bilingual PD patients are diagnosed, on average, three years later than monolingual PD patients. Conclusion: Bilingual PD patients exhibit higher levels of cognitive reserve compared to monolingual PD patients, as indicated by the CRIq scores. The utilization of the second language (L2) is positively correlated with cognitive reserve. Bilingual PD patients are diagnosed with PD, on average, three years later than monolingual PD patients. These findings suggest that bilingualism may contribute to cognitive reserve and potentially delay the onset of clinical symptoms associated with PD. This study adds to the existing literature supporting the relationship between bilingualism and cognitive reserve. Further research in this area could provide valuable insights into the potential protective effects of bilingualism in neurodegenerative disorders.

Keywords: bilingualis, cogntiive reserve, diagnosis, parkinson's disease

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Authors: Reza Mehrafarin, Nafiseh Mirshekari

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The Sistan plain has always been a site for the settlement of various human societies, thanks to its favorable environmental conditions, such as abundant water from the Hirmand River and fertile sedimentary soil. Consequently, there was a need for a systematic archaeological investigation in the area. The survey had multiple objectives, with the most significant ones being the creation of an archaeological map and the identification and documentation of all ancient sites to establish their records and chronology. The survey was carried out in two phases, with each phase covering half of the area. The research method involved fieldwork, with two teams of professional archaeologists conducting a comprehensive survey of each of the 22 areas in Sistan. Once an area was identified, various recording, scientific, and field operations were executed to study the site. In the first phase (2007), an intensive field survey focused on the residential area of Sistan, including its northern and eastern regions. This phase resulted in the identification of 808 sites in eleven selected areas. In the second phase (2009), the desert area of Sistan, or its southern half, was surveyed, leading to the identification of approximately 853 sites. Overall, these surveys resulted in the identification of 1661 sites in Sistan. Among these sites, approximately 899 belong to the Bronze Age (late 4th millennium BCE to early 2nd millennium BCE). Of these sites, around 501 date back to the historical period, while nearly 590 sites pertain to the Islamic period. The archaeological investigations of both phases revealed that Sistan has consistently possessed fertile soil, abundant water, and a skilled workforce, making it capable of becoming Iran's granary and the center of the East once again if these conditions are restored.

Keywords: sistan, field surveys, archaeology, archaeological map

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Authors: Alireza Nejadmohammad Namaghi

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Investigators have reported that mulches increase production potential in arid and semi arid lands. Mulches are covering materials that are used on soil surface for efficiency irrigation, erosion control, weed control, evaporation decrease and improvement of water perpetration. Our aim and local situation determine the kind of material that we can use. In this research we used different mulches including chemical mulch (M1), Aquasorb polymer, manure mulch (M2), Residue mulch (M3) and polyethylene mulch (M4), with control treatment (M0), without usage of mulch, on germination, biomass dry matter and cottonseed yield (Varamin variety) in Kashan area. Randomized complete block (RCB) design have measured the cotton yield with 3 replications for measuring the biomass dry matter and 4 replication in tow irrigation periods as 7 and 14 days. Germination percentage for M0, M1, M2, M3 and M4 treatment were receptivity 64, 65, 76, 57 and 72% Biomass dry matter average for M0, M1, M2, M3 and M4 treatment were receptivity 276, 306, 426, 403 and 476 gram per plot. M4 treatment (polyethylene Mulch) had the most effect, M2 and M3 had no significant as well as M0 and M1. Total yield average with respect to 7 days irrigation for M0, M1, M2, M3 and M4 treatment were receptivity 700, 725, 857, 1057 and 1273 gram per plot. Dunken ne multiple showed no significant different among M0, M1, M2, and M3, but M4 ahs the most effect on yield. Total yield average with respect to 14 days irrigation for M0, M1, M2, M3 and M4 treatment were receptivity 535, 507, 690, 957 and 1047 gram per plot. These were significant difference between all treatments and control treatment. Results showed that used different mulches with water decrease in dry situation can increase the yield significantly.

Keywords: mulch, cotton, arid land management, irrigation systems

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

Abstract:

There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

Procedia PDF Downloads 178

Authors: Monapat Sasingha, Suttisak Soralump

Abstract:

This research presents the behavior of slope of the road along the canal stabilized by short piles. In this investigation, the centrifuge machine was used, modelling the condition of the water levels in the canal. The centrifuge tests were performed at 35 g. To observe the movement of the soil, visual analysis was performed to evaluate the failure behavior. Conclusively, the use of short piles to stabilize the canal slope proved to be an effective solution. However, the certain amount of settlement was found behind the short pile rows.

Keywords: centrifuge test, slope failure, embankment, stability of slope

Procedia PDF Downloads 269

Authors: B. Kenny, M. Dixon, A. Boshell

Abstract:

The use of alcoholic surgical prep was recently introduced into the Royal Newcastle Center for elective procedures. In the past 3 months there have been a significant number of burns believed to be related to ‘pooling’ of this surgical prep in patients undergoing procedures where they are placed in the lateral position with hip bolsters. The aim of the audit was to determine the reason for the burns, analyze what pre-existing factors may contribute to the development of the burns and what can be changed to prevent further burns occurring. All patients undergoing a procedure performed on the hip who were placed in the lateral position with sacral and anterior, superior iliac spine (ASIS) support with ‘bolsters’ were included in the audit. Patients who developed a ‘burn’ were recorded, details of the surgery, demographics, surgical prep used and length of surgery were obtained as well as photographs taken to document the burn. Measures were then taken to prevent further burns and the efficacy was documented. Overall 14 patients developed burns over the ipsilateral ASIS. Of these, 13 were Total Hip Arthroplasty (THA) and 1 was a removal of femoral nail. All patients had Chlorhexidine 0.5% in Alcohol 70% Tinted Red surgical preparation or Betadine Alcoholic Skin Prep (70% etoh). Patients were set up in the standard lateral decubitus position with sacral and bilateral ASIS bolsters with a valband covering. 86% of patients were found to have pre-existing hypersensitivities to various substances. There is very little literature besides a few case reports on surgical prep-related burns. The case reports that do exist are related to the use of tourniquet-related burns and there is no mention in the literature examining ‘bolster’ related burns. The burns are hypothesized to be caused by pooling of the alcoholic solution which is amplified by the use of Valband.

Keywords: arthroplasty, chemical burns, wounds, rehabilitation

Procedia PDF Downloads 300

Authors: Sajia Islam, T. Tahsina, S. Raihana, M. M. Rahman, Q. S. Rahman, T. M. Huda, S. E. Arifeen, M. J. Dibley

Abstract:

Early neonatal sepsis accounts for more than two-thirds of all deaths in the first year of life. This study assessed the counseling during antenatal, perinatal, post natal periods and its association with possible sepsis in rural Bangladesh. Method: Data were collected from a large community-based trial in Bangladesh where pregnant women were enrolled from 2013-2015 covering 29,497 newborns. Sepsis was defined using neonatal danger signs reported by 'The Young-Infants Clinical Science Study Group. 'Result: Signs of sepsis was found among 15% of the neonates. Neonatal sepsis was higher among those who did not receive advice on TT vaccinations (15.4% vs. 11%, p < 0.05) and danger signs (14.8% vs. 12.8%, p < 0.05) during pregnancy. Advice on delivering in well-lit place was significantly associated with lower incidence of sepsis (12.7% vs. 14.8% p < 0.05). Sepsis was lower among neonates whose mothers were counseled on immediate newborn care for bathing after 3 days of delivery (13.4% vs. 15.2% p=0), breastfeeding within 1hr of birth (13.82 % vs. 15.28% p=0), apply nothing on the cord (11.54 vs. 15.06 p=0), immediate drying of child (12.62% vs. 14.89%, p=0). Neonatal sepsis was lower among children whose mothers received 2-4 advice [OR=0.91(95% CI: 0.85-0.97)] compared to neonates whose mothers received only 1 or none. Overall, children to mothers who received ≥ 5 advice had lowest incidence of sepsis [OR=0.83 (95% CI: 0.71-0.97)] Conclusion: Advice on antenatal, prenatal and post natal is significantly reduced with early newborn sepsis. Further research is required to identify specific type of counseling messages that translate into practices and reduce pathways towards early-newborn morbidities.

Keywords: ante natal care, counseling, neonatal sepsis, post natal care

Procedia PDF Downloads 279

Authors: Abdulatif Abdulsalam, Mohamed Shaban

Abstract:

This paper introduces interfacing and replication of electronic tools based on the MATLAB/ SIMULINK mock-up package. Mock-up components contain dc-dc converters, power issue rectifiers, motivation machines, dc gear, synchronous gear, and more entire systems. Power issue rectifier model includes solid state device models. The tools are the clear-cut structure and mock-up of complex energetic systems connecting with power electronic machines.

Keywords: power electronics, machine, MATLAB, simulink

Procedia PDF Downloads 358

Authors: Hoda Abugharsa

Abstract:

In this paper we propose to design a sorter circuit using insertion sorting algorithm. The circuit will be designed using Algorithmic State Machines (ASM) method. That means converting the insertion sorting flowchart into an ASM chart. Then the ASM chart will be used to design the sorter circuit and the control unit.

Keywords: insert sorting algorithm, ASM chart, sorter circuit, state machine, control unit

Procedia PDF Downloads 445