Search results for: health monitoring systems

Authors: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

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Authors: Bruno Vilić Belina, Ivan Župan

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Smart industry concepts and digital transformation are very popular in many industries. They develop their own digital platforms, which have an important role in innovations and transactions. The main idea of smart industry digital platforms is central data collection, industrial data integration, and data usage for smart applications and services. This paper presents the development of a digital platform for building critical infrastructure protection systems in smart industries. Different service contraction modalities in service level agreements (SLAs), customer relationship management (CRM) relations, trends, and changes in business architectures (especially process business architecture) for the purpose of developing infrastructural production and distribution networks, information infrastructure meta-models and generic processes by critical infrastructure owner demanded by critical infrastructure law, satisfying cybersecurity requirements and taking into account hybrid threats are researched.

Keywords: cybersecurity, critical infrastructure, smart industries, digital platform

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Authors: Neeley Current, Fatih Demir, Kenneth Haggerty, Blake Naughton, Isa Jahnke

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Educational systems seek reform using data-intensive continuous improvement processes known as strategic improvement plans (SIPs). Schools turn to digital systems to monitor, analyze and report SIPs. One technical challenge of these digital systems focuses on integrating a highly diverse set of data sources. Another challenge is to create a learnable sociotechnical system to help administrators, principals and teachers add, manipulate and interpret data. This study explores to what extent one particular system is usable and useful for strategic planning activities and whether intended users see the benefit of the system achieve the goal of improving workflow related to strategic planning in schools. In a three-phase study, researchers used sociotechnical design methods to understand the current workflow, technology use, and processes of teachers and principals surrounding their strategic improvement planning. Additionally, design review and task analysis usability methods were used to evaluate task completion, usability, and user satisfaction of the system. The resulting socio-technical models illustrate the existing work processes and indicate how and at which places in the workflow the newly developed system could have an impact. The results point to the potential of the system but also indicate that it was initially too complicated for use. However, the diverse users see the potential benefits, especially to overcome the diverse set of data sources, and that the system could fill a gap for schools in planning and conducting strategic improvement plans.

Keywords: continuous improvement process, education reform, strategic improvement planning, sociotechnical design, software development, usability

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: A. Nabhan, Mohamed R. El-Sharkawy, A. Rashed

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The main aim of this paper is to dedicate the belt drive system faults like cogs missing, misalignment and belt worm using vibration analysis technique. Experimentally, the belt drive test-rig is equipped to measure vibrations signals under different operating conditions. Finite element 3D model of belt drive system is created and vibration response analyzed using commercial finite element software ABAQUS/CAE.  Root mean square (RMS) and Crest Factor will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern obtained from the simulation model and experimental data have the same characteristics. It can be concluded that each case of the RMS is more effective in detecting the defect for acceleration response. While Crest Factor parameter has a response with the displacement and velocity of vibration signals. Also it can be noticed that the model has difficulty in completing the solution when the misalignment angle is higher than 1 degree.

Keywords: simulation model, misalignment, cogs missing, vibration analysis

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Authors: Kalkidan Worku, Eniyew Tegegne, Menichil Amsalu, Samuel Derbie Habtegiorgis

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Introduction: Because of the seasonal nature of the work, day laborers are exposed to risky sexual practices. Since the majority of them are living far away from their birthplace and family, they engage in unplanned and multiple sexual practices. These unplanned and unprotected sexual experiences are a risk for different types of sexual-related health crises. This study aimed to assess the pooled prevalence of risky sexual practices and its determinants among day laborers in Ethiopia. Methods: Online databases, including PubMed, Google Scholar, Science Direct, African Journal of Online, Academia Edu, Semantic Scholar, and university repository sites, were searched from database inception until March 2023. PRISMA 2020 guideline was used to conduct the review. Among 851 extracted studies, ten articles were retained for the final quantitative analysis. To identify the source of heterogeneity, a sub-group analysis and I² test were performed. Publication bias was assessed by using a funnel plot and the Egger and Beg test. The pooled prevalence of risky sexual practices was calculated. Besides, the association between determinant factors and risky sexual practice was determined using a pooled odds ratio (OR) with a 95% confidence interval. Result: The pooled prevalence of risky sexual practices among day laborers was 46.00% (95% CI: 32.96, 59.03). Being single (OR: 2.49; 95% CI: 1.29 to 4.83), substance use (OR: 1.79; 95% CI: 1.40 to 2.29), alcohol intake (OR: 4.19; 95% CI: 2.19 to 8.04), watching pornographic (OR: 5.49; 95% CI: 2.99 to 10.09), discussion about SRH (OR: 4.21; 95% CI: 1.34 to 13.21), visiting night clubs (OR: 2.86 95% CI: 1.79 to 4.57) and risk perception (OR: 0.37 95% CI: 0.20 to 0.70) were the possible factors for risky sexual practice of day laborers in Ethiopia. Conclusions: A large proportion of day laborers engaged in risky sexual practices. Interventions targeting creating awareness of sexual and reproductive health for day laborers should be implemented. Continuous peer education on sexual health should be given to day laborers. Sexual and reproductive health services should be accessible in their workplaces to maximize condom utilization and to facilitate sexual health education for all day laborers.

Keywords: day laborers, sexual health, risky sexual practice, unsafe sex, multiple sexual partners

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Authors: Lassaad Smirani

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In this paper we propose a Neurosymbolic Learning System (NLS) as a channel estimator for Long Term Evolution Advanced (LTE-A) uplink. The proposed system main idea based on Neural Network has modules capable of performing bidirectional information transfer between symbolic module and connectionist module. We demonstrate various strengths of the NLS especially the ability to integrate theoretical knowledge (rules) and experiential knowledge (examples), and to make an initial knowledge base (rules) converted into a connectionist network. Also to use empirical knowledge witch by learning will have the ability to revise the theoretical knowledge and acquire new one and explain it, and finally the ability to improve the performance of symbolic or connectionist systems. Compared with conventional SC-FDMA channel estimation systems, The performance of NLS in terms of complexity and quality is confirmed by theoretical analysis and simulation and shows that this system can make the channel estimation accuracy improved and bit error rate decreased.

Keywords: channel estimation, SC-FDMA, neural network, hybrid system, BER, LTE-A

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Authors: Ju-young Hwang, Hyo-Gyoung Kwak, Hong Jae Yim

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical non-linearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, Prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC structures, heat transfer analysis, nonlinear analysis, after-cooling concrete model

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Authors: Khet Raj Dahal, Dhruva Dhital, Chhatra Mani Sharma

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A study was conducted during 2012 to 2013 in the selected reach of Tinau River, Nepal. The main objective of the study was to quantify employment and income generation from the extraction of construction materials from the river. A 10 km stretch of the river was selected for the study. Sample survey with a semi-structured questionnaire and field observation were the main tools used during field investigation. Extraction of riverbed materials from the banks, beds and floodplain areas of the river has provided many kinds of job opportunities for the people living in the vicinity of the river. It has also generated an adequate amount of revenues. The collected revenue has been invested for many kinds of social and infrastructures development for years. Though extraction of riverbed materials is beneficial for income and employment generation, it has also negative environmental impacts in and around the river. Furthermore, the study concluded that river bed extraction should be continued with special monitoring and evaluation in the areas where there is still room for extraction.

Keywords: extraction, crusher plants, economic activities, Tinau River

Procedia PDF Downloads 683

Authors: Ho Yeon Park, Kyoung-Jae Kim

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The purpose of this study is to investigate whether friendship in social media can be an important factor in recommender system through social scientific analysis of friendship in popular social media such as Facebook and Twitter. For this purpose, this study analyzes data on friendship in real social media using component analysis and clique analysis among sub-group analysis in social network analysis. In this study, we propose an algorithm to reflect the results of sub-group analysis on the recommender system. The key to this algorithm is to ensure that recommendations from users in friendships are more likely to be reflected in recommendations from users. As a result of this study, outcomes of various subgroup analyzes were derived, and it was confirmed that the results were different from the results of the existing recommender system. Therefore, it is considered that the results of the subgroup analysis affect the recommendation performance of the system. Future research will attempt to generalize the results of the research through further analysis of various social data.

Keywords: sub-group analysis, social media, social network analysis, recommender systems

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Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu

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A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.

Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation

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Authors: Charles Anthony S. Santillan, Jude Noel P. Jarina, Patricia Mae A. Cuevas, Julito B. Añora Jr.

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The research examines the effectiveness of Two-Position and Tuned PID controllers in magnetic levitation systems. Magnetic levitation, a crucial technology in diverse industries, depends on meticulous control mechanisms for stability and performance. The study seeks to compare these two control strategies to ascertain their efficacy in practical applications. The paper explores the theoretical foundations of the controllers, presents an experimental methodology emphasizing setup and installation, and examines the results about stability, response time, and susceptibility to disturbances. By interpreting and discussing the findings, the research provides valuable perspectives on the practical ramifications of utilizing Two-Position and Tuned PID controllers in magnetic levitation systems. The conclusion encapsulates significant outcomes and proposes avenues for future research, thereby contributing to the progress of control strategies in magnetic levitation technology.

Keywords: arduino, comparative analysis, magnetic levitation, tuned PID controller, two-position controller

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Authors: Ruth Goldschmidt, Vyacheslav Kalchenko, Lilah Agemy, Rachel Elmoalem, Avigdor Scherz

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Vascular Targeted Photodynamic therapy (VTP) is a new modality for selective cancer treatment that leads to the complete tumor ablation. A photosensitizer, a bacteriochlorophyll derivative in our case, is first administered to the patient and followed by the illumination of the tumor area, by a near-IR laser for its photoactivation. The photoactivated drug releases reactive oxygen species (ROS) in the circulation, which reacts with blood cells and the endothelium leading to the occlusion of the blood vasculature. If the blood vessels are only partially closed, the tumor may recover, and cancer cells could survive. On the other hand, excessive treatment may lead to toxicity of healthy tissues nearby. Simultaneous VTP monitoring and image processing independent of the photoexcitation laser has not yet been reported, to our knowledge. Here we present a method for blood flow monitoring, using a real-time laser speckle imaging (RTLSI) in the tumor during VTP. We have synthesized over the years a library of bacteriochlorophyll derivatives, among them WST11 and STL-6014. Both are water soluble derivatives that are retained in the blood vasculature through their partial binding to HSA. WST11 has been approved in Mexico for VTP treatment of prostate cancer at a certain drug dose, and time/intensity of illumination. Application to other bacteriochlorophyll derivatives or other cancers may require different treatment parameters (such as light/drug administration). VTP parameters for STL-6014 are still under study. This new derivative mainly differs from WST11 by its lack of the central Palladium, and its conjugation to an Arg-Gly-Asp (RGD) sequence. RGD is a tumor-specific ligand that is used for targeting the necrotic tumor domains through its affinity to αVβ3 integrin receptors. This enables the study of cell-targeted VTP. We developed a special RTLSI module, based on Labview software environment for data processing. The new module enables to acquire raw laser speckle images and calculate the values of the laser temporal statistics of time-integrated speckles in real time, without additional off-line processing. Using RTLSI, we could monitor the tumor’s blood flow following VTP in a CT26 colon carcinoma ear model. VTP with WST11 induced an immediate slow down of the blood flow within the tumor and a complete final flow arrest, after some sporadic reperfusions. If the irradiation continued further, the blood flow stopped also in the blood vessels of the surrounding healthy tissue. This emphasizes the significance of light dose control. Using our RTLSI system, we could prevent any additional healthy tissue damage by controlling the illumination time and restrict blood flow arrest within the tumor only. In addition, we found that VTP with STL-6014 was the most effective when the photoactivation was conducted 4h post-injection, in terms of tumor ablation success in-vivo and blood vessel flow arrest. In conclusion, RTSLI application should allow to optimize VTP efficacy vs. toxicity in both the preclinical and clinical arenas.

Keywords: blood vessel occlusion, cancer treatment, photodynamic therapy, real time imaging

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Authors: Baba Mbaye

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In collaborative filtering recommendation systems, a user receives suggested items based on the opinions and evaluations of a community of users. This type of recommendation system uses only the information (notes in numerical values) contained in a usage matrix as input data. This matrix can be constructed based on users' behaviors or by offering users to declare their opinions on the items they know. The cold start problem leads to very poor performance for new users. It is a phenomenon that occurs at the beginning of use, in the situation where the system lacks data to make recommendations. There are three types of cold start problems: cold start for a new item, a new system, and a new user. We are interested in this article at the cold start for a new user. When the system welcomes a new user, the profile exists but does not have enough data, and its communities with other users profiles are still unknown. This leads to recommendations not adapted to the profile of the new user. In this paper, we propose an approach that improves cold start by using the notions of similarity and semantic proximity between users profiles during cold start. We will use the cold-metadata available (metadata extracted from the new user's data) useful in positioning the new user within a community. The aim is to look for similarities and semantic proximities with the old and current user profiles of the system. Proximity is represented by close concepts considered to belong to the same group, while similarity groups together elements that appear similar. Similarity and proximity are two close but not similar concepts. This similarity leads us to the construction of similarity which is based on: a) the concepts (properties, terms, instances) independent of ontology structure and, b) the simultaneous representation of the two concepts (relations, presence of terms in a document, simultaneous presence of the authorities). We propose an ontology, OIVCSRS (Ontology of Improvement Visitor Cold Start in Recommender Systems), in order to structure the terms and concepts representing the meaning of an information field, whether by the metadata of a namespace, or the elements of a knowledge domain. This approach allows us to automatically attach the new user to a user community, partially compensate for the data that was not initially provided and ultimately to associate a better first profile with the cold start. Thus, the aim of this paper is to propose an approach to improving cold start using semantic technologies.

Keywords: visitor cold start, recommender systems, collaborative filtering, semantic filtering

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Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.

Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software

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Authors: Deddi Nordiawan

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Effective public policy creation required a strong budget system, both in terms of design and implementation. Performance-based Budget is an evolutionary approach with two substantial characteristics; first, the strong integration between budgeting and planning, and second, its existence as guidance so that all activities and expenditures refer to measurable performance targets. There are four processes in the government that should be followed in order to make the budget become performance-based. These four processes consist of the preparation of a vision according to the bold aspiration, the formulation of outcome, the determination of output based on the analysis of organizational resources, and the formulation of Value Creation Map that contains a series of programs and activities. This is consistent with the concept of logic model which revealed that the budget performance should be placed within a relational framework of resources, activities, outputs, outcomes and impacts. Through the issuance of Law 17/2003 regarding State Finance, local governments in Indonesia have to implement performance-based budget. Central Government then issued Government Regulation 58/2005 which contains the detail guidelines how to prepare local governments budget. After a decade, implementation of performance budgeting in local government is still not fully meet expectations, though the guidance is completed, socialization routinely performed, and trainings have also been carried out at all levels. Accordingly, this study views the practice of performance-based budget at local governments as a problematic situation. This condition must be approached with a system approach that allows the solutions from many point of views. Based on the fact that the infrastructure of budgeting has already settled, the study then considering the situation as complexity. Therefore, the intervention needs to be done in the area of human activity system. Using Soft Systems Methodology, this research will reconstruct the process of performance-based budget at local governments is area of human activity system. Through conceptual models, this study will invite all actors (central government, local government, and the parliament) for dialogue and formulate interventions in human activity systems that systematically desirable and culturally feasible. The result will direct central government in revise the guidance to local government budgeting process as well as a reference to build the capacity building strategy.

Keywords: soft systems methodology, performance-based budgeting, Indonesia, public policy

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Authors: Mohamed Bualhamam

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Due to the complex nature of tourism resources of the Northern part of the United Arab Emirates (UAE), the potential of Geographical Information Systems (GIS) and Remote Sensing (RS) in resolving these issues was used. The study was an attempt to use existing GIS data layers to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth and give some specific recommendations to protect the area. By identifying sensitive natural environment and archaeological heritage resources, public agencies and citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas. The paper concludes that applications of GIS and RS in study of urban growth impact in tourism resources are a strong and effective tool that can aid in tourism planning and decision-making. The study area is one of the fastest growing regions in the country. The increase in population along the region, as well as rapid growth of towns, has increased the threat to natural resources and archeological sites. Satellite remote sensing data have been proven useful in assessing the natural resources and in monitoring the changes. The study used GIS and RS to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth. The result of GIS analyses shows that the Northern part of the UAE has variety for tourism resources, which can use for future tourism development. Rapid urban development in the form of small towns and different economic activities are showing in different places in the study area. The urban development extended out of old towns and have negative affected of sensitive tourism resources in some areas. Tourism resources for the Northern part of the UAE is a highly complex resources, and thus requires tools that aid in effective decision making to come to terms with the competing economic, social, and environmental demands of sustainable development. The UAE government should prepare a tourism databases and a GIS system, so that planners can be accessed for archaeological heritage information as part of development planning processes. Applications of GIS in urban planning, tourism and recreation planning illustrate that GIS is a strong and effective tool that can aid in tourism planning and decision- making. The power of GIS lies not only in the ability to visualize spatial relationships, but also beyond the space to a holistic view of the world with its many interconnected components and complex relationships. The worst of the damage could have been avoided by recognizing suitable limits and adhering to some simple environmental guidelines and standards will successfully develop tourism in sustainable manner. By identifying sensitive natural environment and archaeological heritage resources of the Northern part of the UAE, public agencies and private citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas.

Keywords: GIS, natural environment, UAE, urban growth

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Authors: Jacopo Baboni Schilingi

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We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.

Keywords: algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication

Procedia PDF Downloads 143

Authors: Nandini Mukhopadhyay

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The prominence of terracotta as a building material in Bengal is well justified by its geographical location. The architectural knowledge system associated with terracotta can be comprehended in the typology of the built structures as they act as texts to interpret the knowledge. The history of Bengal has witnessed the influence of several rulers in developing the architectural vocabulary of the region. This metamorphosis of the architectural knowledge systems in the region includes the Bhakti movement, the Islamic influence, and the British rule, which led to the evolution of the use of terracotta from decorative elements to structural elements in the present-day context. This paper intends to develop an understanding of terracotta as a building material, its use in a built structure, the common problems associated with terracotta construction, and the techniques of maintenance, repair, and conservation. This paper also explores the size, shape, and geometry of the material and its varied use in temples, mosques in the region. It also takes into note that the use of terracotta was concentrated majorly to religious structures and not in the settlements of the common people. And the architectural style of temples and mosques of Bengal is hugely influenced by the houses of the common.

Keywords: terracotta, material, knowledge system, conservation

Procedia PDF Downloads 135

Authors: Taegyoo Woo, Jong Kang Park, Jong Tae Kim

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Visible Light Communication (VLC) provides wireless communication features in illumination systems. One of the key applications is to recognize the user location by indoor illuminators such as light emitting diodes. For localization of individual receivers in these systems, we usually assume that receivers and transmitters are placed in parallel. However, it is difficult to satisfy this assumption because the receivers move randomly in real case. It is necessary to analyze the case when transmitter is not placed perfectly parallel to receiver. It is also important to identify changes on optical gain by the tilted angles and distances of them against the illuminators. In this paper, we simulate optical gain for various cases where the tilt of the receiver and the distance change. Then, we identified changing patterns of optical gains according to tilted angles of a receiver and distance. These results can help many VLC applications understand the extent of the location errors with regard to optical gains of the receivers and identify the root cause.

Keywords: visible light communication, incident angle, optical gain, light emitting diode

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Authors: Orestis Κ. Efthymiou, Stavros T. Ponis

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In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.

Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics

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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: Sami M. Alshareef

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The rapid growth of smart grid technology has brought significant advancements to the power industry. However, with the increasing interconnectivity and reliance on information and communication technologies, smart grids have become vulnerable to cyber-attacks, posing significant threats to the reliable operation of power systems. Among the critical components of smart grids, the Automatic Generation Control (AGC) system plays a vital role in maintaining the balance between generation and load demand. Therefore, protecting the AGC system from cyber threats is of paramount importance to maintain grid stability and prevent disruptions. Traditional security measures often fall short in addressing sophisticated and evolving cyber threats, necessitating the exploration of innovative approaches. Machine learning, with its ability to analyze vast amounts of data and learn patterns, has emerged as a promising solution to enhance AGC system security. Therefore, this research proposal aims to address the challenges associated with detecting and mitigating cyber-attacks on AGC in smart grids by leveraging machine learning techniques on automatic generation control of two-area power systems. By utilizing historical data, the proposed system will learn the normal behavior patterns of AGC and identify deviations caused by cyber-attacks. Once an attack is detected, appropriate mitigation strategies will be employed to safeguard the AGC system. The outcomes of this research will provide power system operators and administrators with valuable insights into the vulnerabilities of AGC systems in smart grids and offer practical solutions to enhance their cyber resilience.

Keywords: machine learning, cyber-attacks, automatic generation control, smart grid

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Authors: Liya Kalinnikova Magnusson

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The present and ongoing research investigation are focusing on special educational origins in Moldova for children with disabilities and its development towards inclusion. The research is coordinated with related research on inclusion in Ukraine and other countries. The research interest in these issues in Moldova is caused by several reasons. The first one is based upon one of the intensive processes of deconstruction of special education institutions in Moldova since 1989. A large number of children with disabilities have been dropping out of these institutions: from 11400 students in 1989 to 5800 students in 1996, corresponding to 1% of all school-age Moldovan learners. Despite the fact that a huge number of students was integrated into regular schools and the dynamics of this data across the country was uneven (the opposite, the dynamics of exclusion was raised in Trans-Dniester on the border of Moldova), the volume of the change was evident and traditional special educational provision was under stable decline. The second reason is tied to transitional challenges, which Moldova met under the force to economic liberalisation that led the country to poverty. Deinstitutionalization of the entire state system took place in the situation of economic polarization of the society. The level of social benefits was dramatically diminished, increasing inequality. The most vulnerable from the comprehensive income consideration were families with many children, children with disabilities, children with health problems, etc.: each third child belonged to the poorest population. In 2000-2001: 87,4% of all families with children had incomes below the minimum wage. The research question raised based upon these considerations has been addressed to the investigation of particular patterns of the origins of special education and its development towards inclusion in Moldova from 1980 until the present date: what is the pattern of special education origins and what are particular arrangements of special education development towards inclusion against inequality? This is a qualitative study, with relevant peer review resources connected to the research question and national documents of educational reforms towards inclusion retrospectively and contemporary, analysed by a content analysis approach. This study utilises long term statistics completed by the respective international agencies as a result of regular monitoring of the implementation of educational reforms. The main findings were composed in three big themes: adoption of the Soviet pattern of special education, ‘endemic stress’ of breaking the pattern, and ‘paradoxes of resolution’.

Keywords: special education, statistics, educational reforms, inclusion, children with disabilities, content analysis

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Authors: Yasaman Mohammadi

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Emotion regulation is a complex process that allows individuals to manage and modulate their emotional responses in order to adaptively respond to environmental demands. As individuals age, emotion regulation abilities may decline, leading to an increased vulnerability to mood disorders and other negative health outcomes. Advances in neuroimaging techniques have greatly enhanced our understanding of the neural substrates underlying emotion regulation and age-related changes in these neural systems. Additionally, genetic research has identified several candidate genes that may influence age-related changes in emotion regulation. In this paper, we review recent findings from neuroimaging and genetic research on age-related changes in the neural substrates of emotion regulation, highlighting the mechanisms and consequences of these changes. We also discuss potential interventions, including cognitive and behavioral approaches, that may be effective in mitigating age-related declines in emotion regulation. We propose that a better understanding of the mechanisms underlying age-related changes in emotion regulation may lead to the development of more targeted interventions aimed at promoting healthy emotional functioning in older adults. Overall, this paper highlights the importance of studying age-related changes in emotion regulation and provides a roadmap for future research in this field.

Keywords: emotion regulation, aging, neural substrates, neuroimaging, emotional functioning, healthy aging

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Authors: Sourabh R. Dinde, Rajshekar S. Talikoti

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According to the structural point of view Industrial Pallet rack structure can be considered typical steel framed structure. This work presents a general analysis of an industrial pallet rack structure, evaluating the influence of each of the components on the global stability. An analytical study for the sensitivity of pallet rack configuration in linear static equivalent lateral loads. The aim is to braced/unbraced frames were design and their analytical models are to be built in software. The finite element analysis is used to determine axial forces in beam and column, maximum storey displacement and buckling loads on braced/unbraced pallet rack structure. Bracing systems are mostly provided to enhance the stiffness factor of the structures with the seismic loads. Unbraced systems have mostly translational modes of failure and are very flexible due to excessive loads.

Keywords: buckling capacity, cold formed steel, finite element analysis, pallets Rrack, seismic design

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

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Nowadays, steel structures are used for not only common buildings but also high-rise construction and wide span covering. The advanced methods of construction as well as the advanced structural connections have a great effect on architecture. However a better use of steel structural systems will be achieved with the deep understanding of steel structures specifications and their substantial advantages. On the other hand, the steel structures face to the different environmental factors such as air flow which cause erosion and corrosion. With the time passing, the amount of these steel mass damages and also the imposed stress will be increased. In other words, the position of erosion in steel structures related to existing stresses indicates that effective environmental conditions will gradually decrease the structural resistance of steel components and result in decreasing the durability of steel components. In this paper, the durability of different steel structural components is evaluated and on the basis of these stress, architectural strategies for designing the system and the components of steel structures is recognized in order to achieve an optimum life cycle.

Keywords: durability, bending stress, erosion in steel structure, life cycle

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Authors: Katanku Denis Musoga

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Eat Right Campaign is an initiative that was started by the Nutrition Unit of Uganda Heart Institute with the objective of informing corporate workers in both the Government and Private sectors about how to eat to prevent Hypertension. In Uganda, according to the recent research undertaken by the Ministry of Health, 1 out of 4 adults is hypertensive and yet over 80% of those are not aware. This is attributed largely to poor eating habits influenced by a lack of knowledge. The major objective of the campaign was to demonstrate the need for effective strategic communication among the corporates by organizing workshops that involved dietary education, food demonstrations, and food preparation in an effort to prevent Hypertension. Permission from various Organizations was sought to carry out sensitization and health education while highlighting the significance of reducing financial losses to health care. The Campaign provided strategies for how to influence positive dietary changes. It involved screening for risk factors. A Pretest was given to the staff to ascertain their knowledge of how to eat right to prevent hypertension, and thereafter the campaign, a post-test was given to the same staff. This was done in all the 10 Organizations that we carried out the campaign. Over 80% of the staff had learned significantly and promised to practice what they had learned; also, the majority who had a higher Blood pressure measurement prior to the campaign returned with significantly lower blood pressure. Food demonstrations, preparations, and regular dietary education should be woven into the entire clinical and Public Health practice.

Keywords: eat right campaign initiative, corporates, prevent hypertension, dietary education

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Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

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Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

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Authors: Ana Rodrigues, Maria Cadilhe, Filipa Ferreira, Claudia Pereira, Marta Santos

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Professional paths must be understood in the multiplicity of their possible configurations. While some actors tend to represent their path as a harmonious succession of positions in the life cycle, most recognize the existence of unforeseen and uncontrollable bifurcations, caused, for example, by a work accident or by going through a period of unemployment. Considering the intensified challenges posed by the ongoing societal changes (e.g., technological and demographic), and looking at the Portuguese context, where the unemployment rate continues to be more evident in certain age groups, like in individuals aged 45 years or over, it is essential to support those adults by providing strategies capable of supporting them during professional transitions, being this a joint responsibility of governments, employers, workers, educational institutions, among others. Concerned about those issues, Porto City Council launched the challenge of designing and implementing a Lifelong Career Guidance program, which was answered with the presentation of a customized conceptual and operational model: groWing|Lifelong Career Guidance. A pilot project targeting working-age adults (35 or older) who were unemployed was carried out, aiming to support them to reconstruct their professional paths, through the recovery of their past experiences and through a reflection about dimensions such as skills, interests, constraints, and labor market. A research action approach was used to assess the proposed model, namely the perceived relevance of the theme and of the project, by adults themselves (N=44), employment professionals (N=15) and local companies (N=15), in an integrated manner. A set of activities were carried out: a train the trainer course and a monitoring session with employment professionals; collective and individual sessions with adults, including a monitoring session as well; and a workshop with local companies. Support materials for individual/collective reflection about professional paths were created and adjusted for each involved agent. An evaluation model was co-build by different stakeholders. Assessment was carried through a form created for the purpose, completed at the end of the different activities, which allowed us to collect quantitative and qualitative data. Statistical analysis was carried through SPSS software. Results showed that the participants, as well as the employment professionals and the companies involved, considered both the topic and the project as extremely relevant. Also, adults saw the project as an opportunity to reflect on their paths and become aware of the opportunities and the necessary conditions to achieve their goals; the professionals highlighted the support given by an integrated methodology and the existence of tools to assist the process; companies valued the opportunity to think about the topic and the possible initiatives they could implement within the company to diversify their recruitment pool. The results allow us to conclude that, in the local context under study, there is an alignment between different agents regarding the pertinence of supporting adults with work experience in professional transitions, seeing the project as a relevant strategy to address this issue, which justifies that it can be extended in time and to other working-age adults in the future.

Keywords: professional paths, research action, turning points, lifelong career guidance, relevance

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