Search results for: learning through movement

Authors: Serdal Pamuk, Irem Cay

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Our model is based on the theory of reinforced random walks coupled with Michealis-Menten mechanisms which view endothelial cell receptors as the catalysts for transforming both tumor and macrophage derived tumor angiogenesis factor (TAF) into proteolytic enzyme which in turn degrade the basal lamina. The model consists of two main parts. First part has seven differential equations (DE’s) in one space dimension over the capillary, whereas the second part has the same number of DE’s in two space dimensions in the extra cellular matrix (ECM). We connect these two parts via some boundary conditions to move the cells into the ECM in order to initiate capillary formation. But, when does this movement begin? To address this question we estimate the thresholds that activate the transport equations in the capillary. We do this by using steady-state analysis of TAF equation under some assumptions. Once these equations are activated endothelial, pericyte and macrophage cells begin to move into the ECM for the initiation of angiogenesis. We do believe that our results play an important role for the mechanisms of cell migration which are crucial for tumor angiogenesis. Furthermore, we estimate the long time tendency of these three cells, and find that they tend to the transition probability functions as time evolves. We provide our numerical solutions which are in good agreement with our theoretical results.

Keywords: angiogenesis, capillary formation, mathematical analysis, steady-state, transition probability function

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Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

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Authors: Sandor Levai, Valentin Juhasz, Miklos Gasz

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Rising damp is an extremely complex phenomenon that is of great practical interest to the field of building conservation due to the irreversible damages it can make to old and historic structures. The electrical effects occurring in damp masonry have been scarcely researched and are a largely unknown aspect of rising damp. Present paper describes the typical electrical patterns occurring in porous brickwork during a wetting and drying cycle. It has been found that in contrast with dry masonry, where electrical phenomena are virtually non-existent, damp masonry exhibits a wide array of electrical effects. Long-term real-time measurements performed in the lab on small-scale brick structures, using an array of embedded micro-sensors, revealed significant voltage, current, capacitance and resistance variations which can be linked to the movement of moisture inside porous materials. The same measurements performed on actual old buildings revealed a similar behaviour, the electrical effects being more significant in areas of the brickwork affected by rising damp. Understanding these electrical phenomena contributes to a better understanding of the driving mechanisms of rising damp, potentially opening new avenues of dealing with it in a less invasive manner.

Keywords: brick masonry, electrical phenomena in damp brickwork, porous building materials, rising damp, spontaneous electrical potential, wetting-drying cycle

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Authors: Aizreena Azaman, Mai Ishibashi, Masanori Ishizawa, Shin-Ichiroh Yamamoto

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Sensory input plays an important role to human posture control system to initiate strategy in order to counterpart any unbalance condition and thus, prevent fall. In previous study, joint stiffness was observed able to describe certain issues regarding to movement performance. But, correlation between balance ability and joint stiffness is still remains unknown. In this study, joint stiffening strategy at ankle and hip were observed under different sensory manipulations and its correlation with conventional clinical test (Functional Reach Test) for balance ability was investigated. In order to create unstable condition, two different surface perturbations (tilt up-tilt (TT) down and forward-backward (FB)) at four different frequencies (0.2, 0.4, 0.6 and 0.8 Hz) were introduced. Furthermore, four different sensory manipulation conditions (include vision and vestibular system) were applied to the subject and they were asked to maintain their position as possible. The results suggested that joint stiffness were high during difficult balance situation. Less balance people generated high average joint stiffness compared to balance people. Besides, adaptation of posture control system under repetitive external perturbation also suggested less during sensory limited condition. Overall, analysis of joint stiffening response possible to predict unbalance situation faced by human.

Keywords: balance ability, joint stiffness, sensory, adaptation, dynamic

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Authors: David A. Harness

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Natural evolution of ATP cognitive systems is to meet AI peer review standards. ATP process of axiom selection from Mizar to prove a conjecture would be further refined, as in all human and machine learning, by solving the real world problem of the proposed AI peer review challenge: Determine which conjecture forms the higher confidence level constructive proof between Standard Model of Physics SU(n) lattice gauge group operation vs. present non-standard 4D GEM EOS SU(n) lattice gauge group spatially extended operation in which the photon and electron are the first two trace angular momentum invariants of a gravitoelectromagnetic (GEM) energy momentum density tensor wavetrain integration spin-stress pressure-volume equation of state (EOS), initiated via 32 lines of Mathematica code. Resulting gravitoelectromagnetic spectrum ranges from compressive through rarefactive of the central cosmological constant vacuum energy density in units of pascals. Said self-adjoint group operation exclusively operates on the stress energy momentum tensor of the Einstein field equations, introducing quantization directly on the 4D spacetime level, essentially reformulating the Yang-Mills virtual superpositioned particle compounded lattice gauge groups quantization of the vacuum—into a single hyper-complex multi-valued GEM U(1) × SU(1,3) lattice gauge group Planck spacetime mesh quantization of the vacuum. Thus the Mizar corpus already contains all of the axioms required for relevant DeepMath premise selection and unambiguous formal natural language parsing in context deep learning.

Keywords: automated theorem proving, constructive quantum field theory, information theory, neural networks

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Authors: A. Martins, I. Martins, O. Pereira

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The purpose of this research is to focus on the importance of distributed leadership in universities and Higher Education Institutions (HEIs). The research question is whether there a significant finding in self-reported ratings of leadership styles of those respondents that are studying management. The study aims to further discover whether students are encouraged to become responsible and proactive citizens, to develop their skills set, specifically shared leadership and higher-level skills to inspire creation knowledge, sharing and distribution thereof. Contemporary organizations need active and responsible individuals who are capable to make decisions swiftly and responsibly. Leadership influences innovative results and education play a dynamic role in preparing graduates. Critical reflection of extant literature indicates a need for a culture of leadership and innovation to promote organizational sustainability in the globalised world. This study debates the need for HEIs to prepare the graduate for both organizations and society as a whole. This active collaboration should be the very essence of both universities and the industry in order for these to achieve responsible sustainability. Learning and innovation further depend on leadership efficacy. This study follows the pragmatic paradigm methodology. Primary data collection is currently being gathered via the web-based questionnaire link which was made available on the UKZN notice system. The questionnaire has 35 items with a Likert scale of five response options. The purposeful sample method was used, and the population entails the undergraduate and postgraduate students in the College of Law and Business, University of KwaZulu-Natal, South Africa. Limitations include the design of the study and the reliance on the quantitative data as the only method of primary data collection. This study is of added value for scholars and organizations in the innovation economy.

Keywords: knowledge creation, learning, performance, sustainability

Procedia PDF Downloads 278

Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: Surendra Choudhary, Sapan Tiwari

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The driver has two fundamental duties i) controlling the position of the vehicle along the longitudinal and lateral direction of movement ii) roadway width. Both of these duties are interdependent and are concurrently referred to as two-dimensional driver behavior. One of the main problems facing driver behavior modeling is to identify the parameters for describing the exemplary driving conduct and car maneuver under distinct traffic circumstances. Still, to date, there is no well-accepted theory that can comprehensively model the 2-D driver conduct (longitudinal and lateral). The primary objective of this research is to explore the vehicle's lateral longitudinal behavior in the heterogeneous condition of traffic on horizontal curves as well as the effect of road geometry on dynamic traffic parameters, i.e., car velocity and lateral placement. In this research, with their interrelationship, a thorough assessment of dynamic car parameters, i.e., speed, lateral acceleration, and turn radius. Also, horizontal curve road parameters, i.e., curvature radius, pavement friction, are performed. The dynamic parameters of the various types of car drivers are gathered using a VBOX GPS-based tool with high precision. The connection between dynamic car parameters and curve geometry is created after the removal of noise from the GPS trajectories. The major findings of the research are that car maneuvers with higher than the design limits of speed, acceleration, and lateral deviation on the studied curves of the highway. It can become lethal if the weather changes from dry to wet.

Keywords: geometry, maneuverability, terrain, trajectory, VBOX

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Authors: A. I. O. Zaid

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Deep drawing is considered to be the most widely used sheet metal forming processes among the particularly in automobile and aircraft industries. It is widely used for manufacturing a large number of the body and spare parts. In its simplest form it may be defined as a secondary forming process by which a sheet metal is formed into a cylinder or alike by subjecting the sheet to compressive force through a punch with a flat end of the same geometry as the required shape of the cylinder end while it is held by a blank holder which hinders its movement but does not stop it. The punch and die profile radii play In this paper, the effects of punch and die profile radii on the autographic record, the minimum thickness strain location where the cracks normally start and cause the fracture, the maximum deep drawing force and the total consumed work in the drawing flat ended cylindrical brass cups are investigated. Five punches and five dies each having different profile radii were manufactured for this investigation. Furthermore, their effect on the quality of the drawn cups is also presented and discussed. It was found that the die profile radius has more effect on the maximum drawing force and the total consumed work than the punch profile radius.

Keywords: punch and die profile radii, deep drawing process, maximum drawing force, total consumed work, quality of produced parts, flat ended cylindrical brass cups

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Authors: Mian Adnan Kakakhel, NIshita Narwal, Majid Rasta, Shi Xiaotao

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The widespread use of nanoparticles means that they are significantly increasing in the aquatic ecosystem, where they are likely to pose threat to aquatic organism. In particular, the influence of nanoparticles exposure combined with varying water velocities on fish behavior remain poorly understood. Emerging evidences suggested a probable correlation between fish swimming behavior and gut bacterial dysbiosis. Therefore, the current study aimed to investigate the effects of nanomaterials in different water velocities on fish gut bacterial composition, which in results change in fish swimming behavior. The obtained findings showed that the contamination of nanoparticles was reduced as the velocity increased. However, the synergetic effects of nanoparticles and water velocity significantly (p < 0.05) decreased the bacterial composition, which plays a critical role in fish development, metabolism, digestion, enzymes production, and energy production such as Bacteroidetes and Firmicutes. This group of bacterial also support fish in swimming behavior by providing them a significant energy during movement. The obtained findings of this study suggested that the presence of nanoparticles in different water velocities have had a significant correlation with fish gut bacterial dysbiosis, as results the gut dysbiosis had been linked to the change in fish behavior. The study provides an important insight into the mechanisms by which the nanoparticles possibly affect the fish behavior.

Keywords: water velocities, fish behavior, gut bacteria, secondary metabolites, regulation

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Authors: Lynn Mcquarrie, Charlotte Enns

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The goal of this project was to develop a visually-based, signed language phonological awareness training program and to pilot the intervention with signing deaf children (ages 6 -10 years/ grades 1 - 4) who were beginning readers to assess the effects of systematic explicit American Sign Language (ASL) phonological instruction on both ASL vocabulary and English print vocabulary learning. Growing evidence that signing learners utilize visually-based signed language phonological knowledge (homologous to the sound-based phonological level of spoken language processing) when reading underscore the critical need for further research on the innovation of reading instructional practices for visual language learners. Multiple single-case studies using a multiple probe design across content (i.e., sign and print targets incorporating specific ASL phonological parameters – handshapes) was implemented to examine if a functional relationship existed between instruction and acquisition of these skills. The results indicated that for all cases, representing a variety of language abilities, the visually-based phonological teaching approach was exceptionally powerful in helping children to build their sign and print vocabularies. Although intervention/teaching studies have been essential in testing hypotheses about spoken language phonological processes supporting non-deaf children’s reading development, there are no parallel intervention/teaching studies exploring hypotheses about signed language phonological processes in supporting deaf children’s reading development. This study begins to provide the needed evidence to pursue innovative teaching strategies that incorporate the strengths of visual learners.

Keywords: American sign language phonological awareness, dual language strategies, vocabulary learning, word reading

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Authors: Berkant Coşkuner, Rahmi Aksoy

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The aim of this study is to present some preliminary stratigraphic and structural evidence for the Fethiye-Burdur fault zone between Kozluca and Burdur. The Fethiye-Burdur fault zone, the easternmost extension of the west Anatolian extensional province, extends from the Gulf of Fethiye northeastward through Burdur, a distance of about 300 km. The research area is located in the Burdur segment of the fault zone. Here, the fault zone includes several parallel to subparallel fault branching and en-echelon faults that lie within a linear belt, as much as 20 km in width. The direction of movement in the fault zone has been oblique-slip in the left lateral sense. The basement of the study area consists of the Triassic-Eocene Lycian Nappes, the Eocene-Oligocene molasse sediments and the lower Miocene marine rocks. The Burdur basin contains two basin infills. The ancient and deformed basin fill is composed of lacustrine sediments of the upper Miocene-lower Pliocene age. The younger and undeformed basin fill comprises Plio-Quaternary alluvial fan and recent basin-floor deposits and unconformably overlies the ancient basin infill. The Burdur basin is bounded by the NE-SW trending, left lateral oblique-slip normal faults, the Karakent fault on the northwest and the Burdur fault on the southeast. These faults played a key role in the development of the Burdur basin as a pull-apart basin.

Keywords: Burdur basin, Fethiye-Burdur fault zone, left lateral oblique-slip fault, Western Anatolia

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Authors: Monjurul Hasan, Golam Kibria, Abdus Salam

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Pervious concrete is a form of lightweight porous concrete, obtained by eliminating the fine aggregate from the normal concrete mix. The advantages of this type of concrete are lower density, lower cost due to lower cement content, lower thermal conductivity, relatively low drying shrinkage, no segregation and capillary movement of water. In this paper an investigation is made on the mechanical response of the pervious concrete at zero fine level (zero fine concrete) made with local brick aggregate. Effect of aggregate size variation on the strength, void ratio and permeability of the zero fine concrete is studied. Finally, a comparison is also presented between the stone aggregate made pervious concrete and brick aggregate made pervious concrete. In total 75 concrete cylinder were tested for compressive strength, 15 cylinder were tested for void ratio and 15 cylinder were tested for permeability test. Mix proportion (cement: Coarse aggregate) was kept fixed at 1:6 (by weights), where water cement ratio was valued 0.35 for preparing the sample specimens. The brick aggregate size varied among 25mm, 19mm, 12mm. It has been found that the compressive strength decreased with the increment of aggregate size but permeability increases and concrete made with 19mm maximum aggregate size yields the optimum value. No significant differences on the strength and permeability test are observed between the brick aggregate made zero fine concrete and stone aggregate made zero fine concrete.

Keywords: pervious concrete, brick aggregate concrete, zero fine concrete, permeability, porosity

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Authors: June Tay, Ivy Chia

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There are numerous changes, both mental and physical, taking place when people age. We need to understand the different aspects required for healthy living, including meeting nutritional needs, regular physical activities to keep agility, sufficient rest and sleep to have physical and mental well-being, social engagement to avoid the risk of social isolation and depression, and access to healthcare to detect and manage chronic conditions. Promoting physical activities for an ageing population is necessary as many may have enjoyed sedentary lifestyles for some time. In our study, we evaluate the considerations when designing a computer vision video game for the elderly. We need to design some low-impact activities, such as stretching and gentle movements, because some elderly individuals may have joint pains or mobility issues. The exercise game should consist of simple movements that are easy to follow and remember. It should be fun and enjoyable so that they can be motivated to do some exercise. Social engagement can keep the elderly motivated and competitive, and they are more willing to engage in game exercises. Elderly citizens can compare their game scores and try to improve them. We propose a computer vision-based video game for the elderly that will capture and track the movement of the elderly hand pushing a ball on the screen into a circle. It can be easily set up using a PC laptop with a webcam. Our video game adhered to the design framework we employed, and it encompassed ease of use, a simple graphical interface, easy-to-play game exercise, and fun gameplay.

Keywords: about computer vision, video games, gerontology technology, caregiving

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Authors: Donald Wright

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The ultimate goal of this study is to reinvigorate the philosophical underpinnings the study of urbanization with scientific data with the goal of circumventing what seems an inevitable future clash between rural and urban populations. To that end urban infrastructure must be sustainable economically, politically and ecologically over the course of several generations as cities continue to grow with the incorporation of climate refugees. Our research will provide data concerning the projected increase in population over the coming two decades in Morocco, and the population will shift from rural areas to urban centers during that period of time. As a result, urban infrastructure will need to be adapted, developed or built to fit the demand of future internal migrations from rural to urban centers in Morocco. This paper will also examine how past experiences of internally displaced people give insight into the challenges faced by future migrants and, beyond the gathering of data, how people react to internal migration. This study employs four different sets of research tools. First, a large part of this study is archival, which involves compiling the relevant literature on the topic and its complex history. This step also includes gathering data bout migrations in Morocco from public data sources. Once the datasets are collected, the next part of the project involves populating the attribute fields and preprocessing the data to make it understandable and usable by machine learning algorithms. In tandem with the mathematical interpretation of data and projected migrations, this study benefits from a theoretical understanding of the critical apparatus existing around urban development of the 20th and 21st centuries that give us insight into past infrastructure development and the rationale behind it. Once the data is ready to be analyzed, different machine learning algorithms will be experimented (k-clustering, support vector regression, random forest analysis) and the results compared for visualization of the data. The final computational part of this study involves analyzing the data and determining what we can learn from it. This paper helps us to understand future trends of population movements within and between regions of North Africa, which will have an impact on various sectors such as urban development, food distribution and water purification, not to mention the creation of public policy in the countries of this region. One of the strengths of this project is the multi-pronged and cross-disciplinary methodology to the research question, which enables an interchange of knowledge and experiences to facilitate innovative solutions to this complex problem. Multiple and diverse intersecting viewpoints allow an exchange of methodological models that provide fresh and informed interpretations of otherwise objective data.

Keywords: climate change, machine learning, migration, Morocco, urban development

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Authors: Animish Jain

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This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

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Authors: Hozaifa Zaki, Ghada Soliman

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In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

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Authors: Farshad Amini, Kejun Wen

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The formation of reflective cracking of pavement overlays has confronted highway engineers for many years. Stress-relieving interlayers, such as paving fabrics, have been used in an attempt to reduce or delay reflective cracking. The effectiveness of paving fabrics in reducing reflection cracking is related to joint or crack movement in the underlying pavement, crack width, overlay thickness, subgrade conditions, climate, and traffic volume. The nonwoven geotextiles are installed between the old and new asphalt layers. Paving fabrics enhance performance through two mechanisms: stress relief and waterproofing. Several factors including proper installation, remedial work performed before overlay, overlay thickness, variability of pavement strength, existing pavement condition, base/subgrade support condition, and traffic volume affect the performance. The primary objective of this study was to conduct a long-term monitoring of the paving fabric interlayer systems to evaluate its effectiveness and performance. A comprehensive testing, monitoring, and analysis program were undertaken, where twelve 500-ft pavement sections of a four-lane highway were rehabilitated, and then monitored for seven years. A comparison between the performance of paving fabric treatment systems and control sections is reported. Lessons learned, and the various factors are discussed.

Keywords: monitoring, paving fabrics, performance, reflective cracking

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Authors: Habibi Said Mustafa, Hiroko Ono

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Since 2006, Afghanistan is dealing with one of the most dramatic trend of urban movement in its history, cities and towns are expanding in size and number. Kabul is the capital of Afghanistan and as well as the fast-growing city in the Asia. The influx of the returnees from neighbor countries and other provinces of Afghanistan caused high rate of artificial growth which slums increased. As an unwanted consequence of this growth, today informal settlements have covered a vast portion of the city. Land Readjustment (LR) has proved to be an important tool for developing informal settlements and reorganizing urban areas but its implementation always varies from country to country and region to region within the countries. Consequently, to successfully develop the informal settlements in Kabul, we need to define an Afghan model of LR specifically for Afghanistan which needs to incorporate all those factors related to the socio-economic condition of the country. For this purpose, a part of the old city of Kabul has selected as a study area which is located near the Central Business District (CBD). After the further analysis and incorporating all needed factors, the result shows a positive potential for the implementation of an adaptable Land Readjustment model for Kabul city which is more sustainable and socio-economically friendly. It will enhance quality of life and provide better urban services for the residents. Moreover, it will set a vision and criteria by which sustainable developments shall proceed in other similar informal settlements of Kabul.

Keywords: adaptation, informal settlements, Kabul, land readjustment, preservation

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Authors: Tahsin Toma Sabbagh, Ihsan Al-Abboodi, Ali Al-Jazaairry

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Allowable-bearing capacity is the competency of soil to safely carries the pressure from the superstructure without experiencing a shear failure with accompanying excessive settlements. Ensuring a safe bearing pressure with respect to failure does not tolerate settlement of the foundation will be within acceptable limits. Therefore, settlement analysis should always be performed since most structures are settlement sensitive. When visualising the movement of a soil wedge in the bearing capacity criterion, both vertically and horizontally, it becomes clear that by confining the soil surrounding the foundation, both the bearing capacity and settlement values improve. In this study, two sizes of spread foundation were considered; (2×4) m and (3×5) m. These represent two real problem case studies of an existing building. The foundations were analysed in terms of dimension as well as position with respect to a confining wall (i.e., sheet piles on both sides). Assuming B is the least foundation dimension, the study comprised the analyses of three distances; (0.1 B), (0.5 B), and (0.75 B) between the sheet piles and foundations alongside three depths of confinement (0.5 B), (1 B), and (1.5 B). Nonlinear three-dimensional finite element analysis (ANSYS) was adopted to perform an analytical investigation on the behaviour of the two foundations contained by the case study. Results showed that confinement of foundations reduced the overall stresses near the foundation by 65% and reduced the vertical displacement by 90%. Moreover, the most effective distance between the confinement wall and the foundation was found to be 0.5 B.

Keywords: bearing capacity, cohesionless soils, soil confinement, soil modelling, spread footings

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Authors: Kasi Jockeil-Ojike

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The study of signage and wayfinding design guidelines is to provide consistent, coherent, and comprehensive guidelines for all type of signage design that may be applied to guide persons from the freeway into campus, and to specific building. As the world becomes more complex and the population increases, people increasingly rely on signage and wayfinding systems to navigate their way in built environment such as university campus. This paper will demonstrate and discuss signage and wayfinding, and the importance of visual literacy in university campuses. It discusses the process of wayfinding and signage, how poor signage and wayfinding systems affect people when navigating, and why wayfinding is more than just signage. Hence, this paper tries to examine the design guideline that primarily addresses the signage and wayfinding system that improves visual literacy within University of Port Harcourt multi-campuses. In doing this, the paper explore the environmental graphic design senori-emotional values and communicative information theories that takes the subjectivity of the observer in account. By making these connections, the paper will also determine what University of Port Harcourt need to focus on to be counted in the global trends, using developed visual communication guidelines based on previous studies or concept from professional. In conclusion, information about why physical structures (buildings and waypaths) on University of Port Harcourt multiple campuses need to be branded in self-communicative manner using signage and wayfinding design as integral part of its physical planning policy is recommended.

Keywords: campus-signage, movement, visual-literacy, wayfinding-guidelines

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Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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Authors: Anna-Maria Saarela

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At the Savonia University of Applied Sciences (UAS), curriculum and studies have been improved by applying an Open Innovation Space approach (OIS). It is based on multidisciplinary action learning. The key elements of OIS-ideology are work-life orientation, and student-centric communal learning. In this approach, every participant can learn from each other and innovations will be created. In this social innovation educational approach, all practices are carried out in close collaboration with enterprises in real-life settings, not in classrooms. As an example, in this paper, Savonia UAS’s Future Food RDI hub (FF) shows how OIS practices are implemented by providing food product development and consumer research services for enterprises in close collaboration with academicians, students and consumers. In particular one example of OIS experimentation in the field is provided by a consumer research carried out utilizing verbal analysis protocol combined with audio-visual observation (VAP-WAVO). In this case, all co-learners were acting together in supermarket settings to collect the relevant data for a product development and the marketing department of a company. The company benefitted from the results obtained, students were more satisfied with their studies, educators and academicians were able to obtain good evidence for further collaboration as well as renewing curriculum contents based on the requirements of working life. In addition, society will benefit over time as young university adults find careers more easily through their OIS related food science studies. Also this knowledge interaction model re-news education practices and brings working-life closer to educational research institutes.

Keywords: collaboration, education, food science, industry, knowledge transfer, RDI, student

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Authors: Palak Sadhwani, Susie Pryor

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This paper investigates interprofessional collaboration (IPC) in the context of entrepreneurship education. Collaboration has been found to enhance problem solving, leverage expertise, improve resource allocation, and create organizational efficiencies. However, research suggests that successful collaboration is hampered by individual and organizational characteristics. IPC occurs when two or more professionals work together to solve a problem or achieve a common objective. The necessity for this form of collaboration is particularly prevalent in cross-disciplinary fields. In this study, we utilize social exchange theory (SET) to examine IPC in the context of an entrepreneurship living learning community (LLC) at a large university in the Western United States. Specifically, we explore these research questions: How are rules or norms established that govern the collaboration process? How are resources valued and distributed? How are relationships developed and managed among and between parties? LLCs are defined as groups of students who live together in on-campus housing and share similar academic or special interests. In 2007, the Association of American Colleges and Universities named living communities a high impact practice (HIP) because of their capacity to enhance and give coherence to undergraduate education. The entrepreneurship LLC in this study was designed to offer first year college students the opportunity to live and learn with like-minded students from diverse backgrounds. While the university offers other LLC environments, the target residents for this LLC are less easily identified and are less apparently homogenous than residents of other LLCs on campus (e.g., Black Scholars, LatinX, Women in Science and Education), creating unique challenges. The LLC is a collaboration between the university’s College of Business & Public Administration and the Department of Housing and Residential Education (DHRE). Both parties are contributing staff, technology, living and learning spaces, and other student resources. This paper reports the results an ethnographic case study which chronicles the start-up challenges associated with the co-creation of the LLC. SET provides a general framework for examining how resources are valued and exchanged. In this study, SET offers insights into the processes through which parties negotiate tensions resulting from approaching this shared project from very different perspectives and cultures in a novel project environment. These tensions occur due to a variety of factors, including team formation and management, allocation of resources, and differing output expectations. The results are useful to both scholars and practitioners of entrepreneurship education and organizational management. They suggest probably points of conflict and potential paths towards reconciliation.

Keywords: case study, ethnography, interprofessional collaboration, social exchange theory

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Authors: Sarah Amodeo

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Drawing on the author’s research about the experiences of female immigrant students in academic Adult Education, in Montreal, Quebec, this paper deconstructs the benefits of autoethnography as a methodology for educators in Adult Education. Autoethnography is an advantageous methodology for teachers in Adult Education as it allows for deep engagement, allowing for educators to reflect on student experiences and their day-to-day realities, and in turn, allowing for professional development, improved andragogy, and changes to classroom practices. Autoethnography is a qualitative research methodology that cultivates strategies for improving adult learning. The paper begins by outlining the context that inspired autoethnography for the author’s work, highlighting the emergence of autoethnography as a method, while examining how it is evolving and drawing on foundational work that continues to inspire research. The basic autoethnographic methodologies that are explored in this paper include the use of memory work in episode formation, the use of personal photographs, and textual readings of artworks. Memory work allows for the researcher to use their professional experience and the lived/shared experiences of their students in their research, drawing on episodes from their past. Personal photographs and descriptions of artwork allow researchers to explore images of learning environments/realities in ways that compliment student experiences. Major findings of the text are examined through the analysis of categories of autoethnography. Specific categories include realism, impressionism, and conceptualism which aid in orientating the analysis and emergent themes that develop through self-study. Finally, the text presents a discussion surrounding the limitations of autoethnography, with attention to the trustworthiness and ethical issues. The paper concludes with a consideration of the implications of autoethnography for adult educators in juxtaposition with youth sector work.

Keywords: artwork, autoethnography, conceptualism, episode formation, impressionism, memory work, personal photographs, and realism, realism

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Authors: Sophie Whittle

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Prior to present day, English syntax historically exhibited an inconsistent verb-second (V2) rule, which saw the verb move to the second position in the sentence following the fronting of a type of phrase. There was a high amount of variation throughout the history of English with regard to the ordering of subject and verb, and many explanations attempting to account for this variation have been documented in previous literature. However, these attempts have been contradictory, with many accounts positing the effect of previous syntactic changes as the main motivations behind the decline of V2. For instance, morphosyntactic changes, such as the loss of clitics and the loss of empty expletives, have been loosely connected to changes in frequency for the loss of V2. The questions surrounding the development of non-V2 in English have, therefore, yet to be answered. The current paper aims to bring together a number of explanations from different linguistic fields to determine the factors driving the changes in English V2. Using historical corpus-based methods, the study analyses both quantitatively and qualitatively the changes in frequency for the history of V2 in the Old, Middle, and Modern English periods to account for the variation in a range of sentential environments. These methods delve into the study of information structure, prosody and language contact to explain variation within different contexts. The analysis concludes that these factors, in addition to changes within the syntax, are responsible for the position of verb movement. The loss of V2 serves as an exemplar study within the field of historical linguistics, which combines a number of factors in explaining language change in general.

Keywords: corpora, English, language change, mixed-methods, syntax, verb-second

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Authors: Shervin Khazaeli, Shahab Haj-zamani

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Recently, advanced geotechnical engineering problems related to soil movement, particle loss, and modeling of local failure (i.e. discontinua) as well as modeling the in-contact structures (i.e. continua) are of the great interest among researchers. The aim of this research is to meet the requirements with respect to the modeling of the above-mentioned two different domains simultaneously. To this end, a coupled numerical method is introduced based on Discrete Element Method (DEM) and eXtended-Finite Element Method (X-FEM). In the coupled procedure, DEM is employed to capture the interactions and relative movements of soil particles as discontinua, while X-FEM is utilized to model in-contact structures as continua, which may consist of different types of discontinuities. For verification purposes, the new coupled approach is utilized to examine benchmark problems including different contacts between/within continua and discontinua. Results are validated by comparison with those of existing analytical and numerical solutions. This study proves that extended-finite-discrete element method can be used to robustly analyze not only contact problems, but also other types of discontinuities in continua such as (i) crack formations and propagations, (ii) voids and bimaterial interfaces, and (iii) combination of previous cases. In essence, the proposed method can be used vastly in advanced soil-structure interaction problems to investigate the micro and macro behaviour of the surrounding soil and the response of the embedded structure that contains discontinuities.

Keywords: contact problems, discrete element method, extended-finite element method, soil-structure interaction

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Authors: Hidehiro Endo, Taizo Shigemichi

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Introduction & Objectives: In 2008, the revised course of study for elementary schools was published by MEXT, and from the beginning of the academic year of 2011-2012, foreign language activities (English lessons) became mandatory for 5th and 6th graders in Japanese elementary schools. Foreign language activities are currently offered once a week for approximately 50 minutes by elementary school teachers, assistant language teachers who are native speakers of English, volunteers, among others, with the purpose of helping children become accustomed to functional English. However, the new policy has disclosed a myriad of issues in conducting foreign language activities since the majority of the current elementary school teachers has neither English teaching experience nor English proficiency. Nevertheless, converting foreign language activities into English, as a subject in Japanese elementary schools (for 5th and 6th graders) from 2020 is what MEXT currently envisages with the purpose of reforming English education in Japan. According to their new proposal, foreign language activities will be mandatory for 3rd and 4th graders from 2020. Consequently, gaining better access to English learning opportunities becomes one of the primary concerns even in early childhood education. Thus, in this project, we aim to explore some nursery schools’ attempts at providing toddlers with online English lessons via Skype. The main purpose of this project is to look deeply into what roles online English lessons in the nursery schools play in guiding nursery school children to enjoy learning the English language as well as to acquire English communication skills. Research Methods: Setting; The main research site is a nursery school located in the northern part of Japan. The nursery school has been offering a 20-minute online English lesson via Skype twice a week to 7 toddlers since September 2015. The teacher of the online English lessons is a male person who lives in the Philippines. Fieldwork & Data; We have just begun collecting data by attending the Skype English lessons. Direct observations are the principal components of the fieldwork. By closely observing how the toddlers respond to what the teacher does via Skype, we examine what components stimulate the toddlers to pay attention to the English lessons. Preliminary Findings & Expected Outcomes: Although both data collection and analysis are ongoing, we found that the online English teacher remembers the first name of each toddler and calls them by their first name via Skype, a technique that is crucial in motivating the toddlers to actively participate in the lessons. In addition, when the teacher asks the toddlers the name of a plastic object such as grapes in English, the toddlers tend to respond to the teacher in Japanese. Accordingly, the effective use of Japanese in teaching English for nursery school children need to be further examined. The anticipated results of this project are an increased recognition of the significance of creating English language learning opportunities for nursery school children and a significant contribution to the field of early childhood education.

Keywords: teaching children, English education, early childhood education, nursery school

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Authors: D. Baratian, A. Cavalli, D. van den Ende, F. Mugele

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The morphology of liquid bridges inside complex geometries is the subject of interest for many years. These efforts try to find stable liquid configuration considering the boundary condition and the physical properties of the system. On the other hand precise manipulation of droplets is highly significant in many microfluidic applications. The liquid configuration in a complex geometry can be switched by means of external stimuli. We show manipulation of droplets in a wedge structure. The profile and position of a drop in a wedge geometry has been calculated analytically assuming negligible contact angle hysteresis. The characteristic length of liquid bridge and its interfacial tension inside the surrounding medium along with the geometrical parameters of the system determine the morphology and equilibrium position of drop in the system. We use electrowetting to modify one the governing parameters to manipulate the droplet. Electrowetting provides the capability to have precise control on the drop position through tuning the voltage and consequently changing the contact angle. This technique is employed to tune drop displacement and control its position inside the wedge. Experiments demonstrate precise drop movement to its predefined position inside the wedge geometry. Experimental results show promising consistency as it is compared to our geometrical model predictions. For such a drop manipulation, appealing applications in microfluidics have been considered.

Keywords: liquid bridges, microfluidics, drop manipulation, wetting, electrowetting, capillarity

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Authors: Silvia Maria Moya

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After the Great Depression, the number of admissions to psychiatric facilities saw a significant increase. This increase, coupled with the arrival of new antipsychotic drugs, prepared the ground to the psychiatric deinstitutionalization movement in North America. Community services became an essential part of care where the role of the nurse also became crucial in the management of patients. Looking through the archives of the Department of Psychiatry at the Ottawa Montfort Hospital, this project aims to assess the role of the nurse in a multidisciplinary team in a period of psychiatric deinstitutionalization. This research focuses on the different roles of the mental health nurse during the second half of the twentieth century. The case study, used as a methodological approach allows in-depth analysis of the journey of a female patient with long hospital course. The analysis of the document ‘psychiatric evaluation’ on the medical records of outpatient Montfort Hospital – where, on a regular basis, different health professionals of the multidisciplinary team write their notes – allow us to better understand the difficulties of the patient, their problems, their family and work relationships and the evolution of their self-esteem, but most importantly, it allows us to identify the importance of the different nurse`s roles in the team and in the mental health setting. This project therefore reveals that the nurse occupies a larger professional space than the other professionals in the multidisciplinary team and highlights the role of mental health nurses with patients and their families and their leadership role within a multidisciplinary team.

Keywords: mental health, nursing, deinstitutionalization, professional space

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