Search results for: depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices

Authors: Ying Han, Weirong Chen, Qi Li

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An energy management method based on equivalent hydrogen consumption minimum strategy is proposed in this paper aiming at the direct-current (DC) microgrid consisting of photovoltaic cells, fuel cells, energy storage devices, converters and DC loads. The rational allocation of fuel cells and battery devices is achieved by adopting equivalent minimum hydrogen consumption strategy with the full use of power generated by photovoltaic cells. Considering the balance of the battery’s state of charge (SOC), the optimal power of the battery under different SOC conditions is obtained and the reference output power of the fuel cell is calculated. And then a droop control method based on time-varying droop coefficient is proposed to realize the automatic charge and discharge control of the battery, balance the system power and maintain the bus voltage. The proposed control strategy is verified by RT-LAB hardware-in-the-loop simulation platform. The simulation results show that the designed control algorithm can realize the rational allocation of DC micro-grid energy and improve the stability of system.

Keywords: DC microgrid, equivalent minimum hydrogen consumption strategy, energy management, time-varying droop coefficient, droop control

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Authors: Deborah Weidner, Melissa Morgera

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The model of care delivery in the Behavioral Health Network (BHN) is integrated across all five regions of Hartford Healthcare and thus spans the entirety of the state of Connecticut, with care provided in seven inpatient settings and over 30 ambulatory outpatient locations. While safety has been a core priority of the BHN in alignment with High Reliability practices, safety initiatives have historically been facilitated locally in each region or within each entity, with interventions implemented locally as opposed to throughout the network. To address this, the BHN introduced a network wide Safety Huddle during 2022. Launched in January, the BHN Safety Huddle brought together internal stakeholders, including medical and administrative leaders, along with executive institute leadership, quality, and risk management. By bringing leaders together and introducing a network-wide safety huddle into the way we work, the benefit has been an increase in awareness of safety events occurring in behavioral health areas as well as increased systemization of countermeasures to prevent future events. One significant discussion topic presented in huddles has pertained to environmental design and patient access to potentially dangerous items, addressing some of the most relevant factors resulting in harm to patients in inpatient and emergency settings for behavioral health patients. The safety huddle has improved visibility of potential environmental safety risks through the generation of over 15 safety alerts cascaded throughout the BHN and also spurred a rapid improvement project focused on standardization of patient belonging searches to reduce patient access to potentially dangerous items on inpatient units. Safety events pertaining to potentially dangerous items decreased by 31% as a result of standardized interventions implemented across the network and as a result of increased awareness. A second positive outcome originating from the BHN Safety Huddle was implementation of a recommendation to increase the emergency Narcan®(naloxone) supply on hand in ambulatory settings of the BHN after incidents involving accidental overdose resulted in higher doses of naloxone administration. By increasing the emergency supply of naloxone on hand in all ambulatory and residential settings, colleagues are better prepared to respond in an emergency situation should a patient experience an overdose while on site. Lastly, discussions in safety huddle spurred a new initiative within the BHN to improve responsiveness to assaultive incidents through a consultation service. This consult service, aligned with one of the network’s improvement priorities to reduce harm events related to assaultive incidents, was borne out of discussion in huddle in which it was identified that additional interventions may be needed in providing clinical care to patients who are experiencing multiple and/ or frequent safety events.

Keywords: quality, safety, behavioral health, risk management

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Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

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Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

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Authors: Kelemewerk Destalem, Joongjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo

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Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of a histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Keywords: background subtraction, background updating, real time, light weight algorithm, temporal difference

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Authors: H. El-Kamchouchi, Heba Gaber, Fatma Ahmed, Dalia H. El-Kamchouchi

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A digital signature is an electronic signature form used by an original signer to sign a specific document. When the original signer is not in his office or when he/she travels outside, he/she delegates his signing capability to a proxy signer and then the proxy signer generates a signing message on behalf of the original signer. The two parties must be able to authenticate one another and agree on a secret encryption key, in order to communicate securely over an unreliable public network. Authenticated key agreement protocols have an important role in building a secure communications network between the two parties. In this paper, we present a secure proxy signature scheme over an efficient and secure authenticated key agreement protocol based on factoring and discrete logarithm problem.

Keywords: discrete logarithm, factoring, proxy signature, key agreement

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Authors: Nassim Ourabia, Malika Ourabia

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A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The technique obtains closed form expressions for the equivalent circuits which are used to model these discontinuities. Then it would be easy to handle and to characterize complicated structures like T and Y junctions, truncated junctions, arbitrarily shaped junctions, cascading junctions, and more generally planar multiport junctions. Another advantage of this method is that the edge line concept for arbitrary shape junctions operates with real parameters circuits. The validity of the method was further confirmed by comparing our results for various discontinuities (bend, filters) with those from HFSS as well as from other published sources.

Keywords: CAD analysis, contour integral approach, microwave circuits, s-parameters

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Authors: Lizmol Mathew, Divya Thomas, Shiney Rajan

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Educational paradigm all over the globe is undergoing significant reform today. Because of this, so-called flipped classroom model is becoming increasingly popular in higher education. Flipped classroom has proved to be more effective than traditional lecture based model as flipped classroom model promotes active learning by encouraging students to work on in collaborative tasks and peer-led learning during the class-time. However, success of flipped classrooms relies on students’ ability and their attitudes towards collaboration and group work. This paper examines: 1) Students’ attitudes towards collaborative learning; 2) Main challenges to successful collaboration from students’ experience and 3) Students’ perception of criteria for successful team work. 4) Recommendations for enhancing collaborative learning. This study’s methodology involves quantitative analysis of surveys collected from students enrolled in undergraduate Architecture program at Qatar University. Analysis indicates that in general students enrolled in the program do not have positive perceptions or experiences associated with group work. Positive and negative factors that influence collaborative learning in higher education have been identified. Recommendations for improving collaborative work experience have been proposed.

Keywords: architecture, collaborative learning, female, group work, higher education, Middle East, Qatar, student experience

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Authors: Ratnadip Natwarbhai Bhoi

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The objective of this research paper is to study waste tire crumb rubber granules as a partial concrete replacement by the different percentages of facing layer thickness and without facing layer in the production of rubber cement composite paver block. The physical properties of RCCRP compressive strength, flexural strength, abrasion strength density, and water absorption testing by the IS 15658:2006 method. All these physical properties depend upon the ratio of crumb rubber uses. The result showed that the with facing layer at 15 mm, 25 mm, totally rubberized and without facing layer had little effect on compressive strength, flexural strength and abrasion resistance properties. Water absorption is also important for the service life of the product. The crumb rubber paver block also performed quite well in both compressive strength and abrasion resistance. The rubber cement composite rubber paver block is suitable for nonstructural purposes, such as being lightweight and easy installation for the walkway, sidewalks, and playing area applications.

Keywords: rubber cement, crumb rubber, composite, layer

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Authors: M. Benachour, N. Benachour, M. Benguediab

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In this investigation an empirical study was made on fatigue crack initiation on 7075 T6 and 7075 T71 al-alloys under constant amplitude loading. At initiation stage, local strain approach at the notch was applied. Single Edge Notch Tensile specimen with semi circular notch is used. Based on experimental results, effect of mean stress, is highlights on fatigue initiation life. Results show that fatigue life initiation is affected by notch geometry and mean stress.

Keywords: fatigue crack initiation, al-alloy, mean stress, heat treatment state

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Authors: Adebowale Olukayode Efunnowo

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This study was carried out to assess the awareness and utilization of Social Network Tools (SNTs) among agricultural science students in Colleges of Education in Ogun State, Nigeria. Simple random sampling techniques were used to select 280 respondents from the study area. Descriptive statistics was used to describe the objectives while Pearson Product Moment Correlation was used to test the hypothesis. The result showed that the majority (71.8%) of the respondents were single, with a mean age of 20 years. Almost all (95.7%) the respondents were aware of Facebook and 2go as a Social Network Tools (SNTs) while 85.0% of the respondents were not aware of Blackplanet, LinkedIn, MyHeritage and Bebo. Many (41.1%) of the respondents had views that using SNTs can enhance extensive literature survey, increase internet browsing potential, promote teaching proficiency, and update on outcomes of researches. However, 51.4% of the respondents perceived that SNTs usage as what is meant for the lecturers/adults only while 16.1% considered it as mainly used by internet fraudsters. Findings revealed that about 50.0% of the respondents browsed Facebook and 2go daily while more than 80% of the respondents used Blackplanet, MyHeritage, Skyrock, Bebo, LinkedIn and My YearBook as the need arise. Major constraints to the awareness and utilization of SNTs were high cost and poor quality of ICTs facilities (77.1%), epileptic power supply (75.0%), inadequate telecommunication infrastructure (71.1%), low technical know-how (62.9%) and inadequate computer knowledge (61.1%). The result of PPMC analysis showed that there was an inverse relationship between constraints and utilization of SNTs at p < 0.05. It can be concluded that constraints affect efficient and effective utilization of SNTs in the study area. It is hereby recommended that management of colleges of education and agricultural institutes should provide good internet connectivity, computer facilities, and alternative power supply in order to increase the awareness and utilization of SNTs among students.

Keywords: awareness, utilization, social network tools, constraints, students

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Authors: Adriana Martínez-Arias, John Josephraj Selvaraj, Luis Octavio González-Salcedo

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In the Colombian Pacific, Dorado fish (Coryphaena hippurus L.) fisheries is of great commercial interest. However, its habitat and fisheries may be affected by climatic change especially by the actual increase in sea surface temperature. Hence, it is of interest to study the dynamics of these species fishing zones. In this study, we developed Artificial Neural Networks (ANN) models to predict Catch per Unit Effort (CPUE) as an indicator of species abundance. The model was based on four oceanographic variables (Chlorophyll a, Sea Surface Temperature, Sea Level Anomaly and Bathymetry) derived from satellite data. CPUE datasets for model training and cross-validation were obtained from logbooks of commercial fishing vessel. Sea surface Temperature for Colombian Pacific were projected under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 using Coupled Model Intercomparison Project Phase 5 (CMIP5) and CPUE maps were created. Our results indicated that an increase in sea surface temperature reduces the potential fishing zones of this species in the Colombian Pacific. We conclude that ANN is a reliable tool for simulation of climate change effects on the potential fishing zones. This research opens a future agenda for other species that have been affected by climate change.

Keywords: climatic change, artificial neural networks, dorado fish, CPUE

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Authors: Aina Barcelona, Carolyn Oldham, Jordi Colomer, Teresa Serra

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The loss of seagrass meadows worldwide is being tackled by formulating coastal restoration strategies. Seagrass loss results in a network of vegetated patches which are barely interconnected, and consequently, the ecological services they provide may be highly compromised. Hence, there is a need to optimize coastal management efforts in order to implement successful restoration strategies, not only through modifying the architecture of the canopies but also by gathering together information on the hydrodynamic conditions of the seabeds. To obtain information on the hydrodynamics within the patches of vegetation, this study deals with the scale analysis of the minimum lengths of patch management strategies that can be effectively used on. To this aim, a set of laboratory experiments were conducted in a laboratory flume where the plant densities, patch lengths, and hydrodynamic conditions were varied to discern the vegetated patch lengths that can provide optimal ecosystem services for canopy development. Two possible patch behaviours based on the turbulent kinetic energy (TKE) production were determined: one where plants do not interact with the flow and the other where plants interact with waves and produce TKE. Furthermore, this study determines the minimum patch lengths that can provide successful management restoration. A canopy will produce TKE, depending on its density, the length of the vegetated patch, and the wave velocities. Therefore, a vegetated patch will produce plant-wave interaction under high wave velocities when it presents large lengths and high canopy densities.

Keywords: seagrass, minimum patch size, turbulent kinetic energy, oscillatory flow

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Authors: Parth Gupta, Ujjawal Singh, Shashank Kumar, Mansi Chandra, Arnab Sarkar

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Microfluidic devices have emerged as indispensable tools across various scientific disciplines, offering precise control and manipulation of fluids at the microscale. Their efficacy in flow-based research, spanning engineering, chemistry, and biology, relies heavily on the geometric design of microfluidic channels. This work introduces a novel approach to optimise these channels through Response Surface Methodology (RSM), departing from the conventional practice of addressing one parameter at a time. Traditionally, optimising microfluidic channels involved isolated adjustments to individual parameters, limiting the comprehensive understanding of their combined effects. In contrast, our approach considers the simultaneous impact of multiple parameters, employing RSM to efficiently explore the complex design space. The outcome is an innovative microfluidic channel that consumes an optimal sample volume and minimises flow time, enhancing overall efficiency. The relevance of geometric parameter optimization in microfluidic channels extends significantly in biomedical engineering. The flow characteristics of porous materials within these channels depend on many factors, including fluid viscosity, environmental conditions (such as temperature and humidity), and specific design parameters like sample volume, channel width, channel length, and substrate porosity. This intricate interplay directly influences the performance and efficacy of microfluidic devices, which, if not optimized, can lead to increased costs and errors in disease testing and analysis. In the context of biomedical applications, the proposed approach addresses the critical need for precision in fluid flow. it mitigate manufacturing costs associated with trial-and-error methodologies by optimising multiple geometric parameters concurrently. The resulting microfluidic channels offer enhanced performance and contribute to a streamlined, cost-effective process for testing and analyzing diseases. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing.

Keywords: microfluidic device, minitab, statistical optimization, response surface methodology

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Authors: Karmveer Sheoran

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To make wireless communication a vast success is to use sunlight for wireless communication. We can use sunlight in upper atmosphere to encode messages to efficiently use sunlight. This use of sunlight for wireless communication will need encoders which will encode sunlight according to our message and then resultant will be spread in all atmospheres wherever sunlight goes, it will take our messages with it. With minimum requirement of cost in equipment used at the edge of atmosphere is where sunlight is being encoded. In this way a very high efficient wireless communication system can be designed. On receiver side we will need light detectors which will detect sunlight variations and will finally give the information contained i it. Sunlight can be encoded at a very high speed that nobody will be annoyed by flickering. It will be most sophisticated and efficient wireless communication ever designed. There are far more possibilities in this sunlight communication. Let us call it “Sunlight Communication".

Keywords: sunlight communication, emerging trends, wireless communication, wifi

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Authors: Ali Mohammed Ali Lmbash

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The global refugee crisis points to the vital need for sustainable and resistant solutions to different kinds of problems for displaced persons all over the world. Among the myriads of sustainable concerns, however, there are diverse considerations including energy consumption, waste management, water access, and resiliency of structures. Our research aims to develop distinct ideas for sustainable architecture given the exigent problems in disaster-threatened areas starting with the Hatay Refugee camp in Turkey where the majority of the camp dwellers are Syrian refugees. Commencing community-based participatory research which focuses on the socio-environmental issues of displaced populations, this study will apply two approaches with a specific focus on the Hatay region. The initial experiment uses Richter's predictive model and simulations to forecast earthquake outcomes in refugee campers. The result could be useful in implementing architectural design tactics that enhance structural reliability and ensure the security and safety of shelters through earthquakes. In the second experiment a model is generated which helps us in predicting the quality of the existing water sources and since we understand how greatly water is vital for the well-being of humans, we do it. This research aims to enable camp administrators to employ forward-looking practices while managing water resources and thus minimizing health risks as well as building resilience of the refugees in the Hatay area. On the other side, this research assesses other sustainability problems of Hatay Refugee Camp as well. As energy consumption becomes the major issue, housing developers are required to consider energy-efficient designs as well as feasible integration of renewable energy technologies to minimize the environmental impact and improve the long-term sustainability of housing projects. Waste management is given special attention in this case by imposing recycling initiatives and waste reduction measures to reduce the pace of environmental degradation in the camp's land area. As well, study gives an insight into the social and economic reality of the camp, investigating the contribution of initiatives such as urban agriculture or vocational training to the enhancement of livelihood and community empowerment. In a similar fashion, this study combines the latest research with practical experience in order to contribute to the continuing discussion on sustainable architecture during disaster relief, providing recommendations and info that can be adapted on every scale worldwide. Through collaborative efforts and a dedicated sustainability approach, we can jointly get to the root of the cause and work towards a far more robust and equitable society.

Keywords: smart architecture, Hatay Camp, sustainability, machine learning.

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Authors: Duaa Al Maani, Andrew Roberts

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Students in higher education are expected to learn actively and independently. Whilst quite work has been done to understand the perceptions of students’ learning transition regarding independent learning, to author’s best knowledge, it seems relatively few published research on independent learning in studio-based subjects such as architecture. Another major issue in independent learning research concerned the inconsistency in terminology; there appears to be a paucity of research on its definition, challenges, and tools within the UK university sector. It is not always clear how independent learning works in practice, or what are the challenges that face students toward being independent learners. Accordingly, this paper seeks to highlight these problems by analyzing previous and current literature of independent learning, in addition, to measure students’ independence at the very begging of their first academic year and compare it with their level of learning independence at the end of the same year. Eighty-seven student enrolled in 2017/2018 at Cardiff University completed the Autonomous Learning Questionnaire in order to measure their level of learning independence. Students’ initial responses were very positive and showed high level of learning independence. Interestingly, these responses significantly decreased at the end of the year. Time management was the most obvious challenge facing students transition into higher education, and contrary to expectations, we found no effect of student maturity on their level of independence. Moreover, we found no significant differences among students’ gender, but we did find differences among nationalities.

Keywords: autonomous learning, first year, learning independence, transition

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Authors: Timothee Gidenne, Xia Pinqi

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In this paper, an investigation of the use of carbon nanotubes (CNTs) reinforced polymer as an actuator for an active flutter suppression to counter the flutter phenomena is conducted. The goal of this analysis is to establish a link between the behavior of the control surface and the actuators to demonstrate the veracity of using such a suppression system for the aeronautical field. A preliminary binary flutter model using simplified unsteady aerodynamics is developed to study the behavior of the wing while reaching the flutter speed and when the control system suppresses the flutter phenomena. The Timoshenko beam theory for bilayer materials is used to match the response of the control surface with the CNTs reinforced polymer (CNRP) actuators. According to Timoshenko theory, results show a good and realistic response for such a purpose. Even if the results are still preliminary, they show evidence of the potential use of CNRP for control surface actuation for the small-scale and lightweight system.

Keywords: actuators, aeroelastic, aeroservoelasticity, carbon nanotubes, flutter, flutter suppression

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Authors: Santosh Kumar Ketham

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Climate change creating most dramatic and destructive consequences, the result is global warming and sea-level rise, flooding coastal cities around the world forming vulnerable situations affecting in multiple ways: environment, economy, social and political. The aim and goal of the research is to develop cities on water. Taking the problem as an opportunity to bring science, engineering, policies and design together to make a resilient and sustainable floating community on water considering existing/new technologies of floating. The quest is to make sustainable habitat on water to live, work, learn and play.  To make sustainable energy generation and storage alongside maintaining balance of land and marine to conserve Ecosystem. The research would serve as a model for sustainable neighbourhoods designed in a modular way and thus can easily extend or re-arranged, to adapt for future socioeconomic realities.  This research paper studies primarily on climate change problems, effects, risks and opportunities. It does so, through analysing existing case studies, books and writings published on coastal cities and understanding its various aspects for making sustainable habitat.

Keywords: floating cities, flexible modular typologies, rising sea levels, sustainable architecture and urbanism

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Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

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In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

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Authors: Alexander Nitsche, Piotr-Robert Lazik, Harald Garrecht

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The viscosity of the concrete has a great influence on the properties of the fresh concrete. Fresh concretes with low viscosity have a good flowability, whereas high viscosity has a lower flowability. Clearly, viscosity is directly linked to other parameters such as consistency, compaction, and workability of the concrete. The above parameters also depend very much on the energy induced during the mixing process and, of course, on the installation of the mixer itself. The University of Stuttgart has decided to investigate the influence of different mixing systems on the viscosity of various types of concrete, such as road concrete, self-compacting concrete, and lightweight concrete, using a rheometer and other testing methods. Each type is tested with three different mixers, and the rheological properties, namely consistency, and viscosity are determined. The aim of the study is to show that different types of concrete mixed with different types of mixers reach completely different yield points. Therefore, a 3 step procedure will be introduced. At first, various types of concrete mixtures and their differences are introduced. Then, the chosen suspension mixer and conventional mixers, which are going to be used in this paper, will be discussed. Lastly, the influence of the mixing system on the rheological properties of each of the select mix designs, as well as on fresh concrete, in general, will be presented.

Keywords: rheological properties, flowability, suspension mixer, viscosity

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Authors: Le Fu, Rui Wu, Gang Feng Liu, Jie Zhao

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Normally, impedance control methods are based on a model that connects a spring and damper in parallel. The series connection, namely the Maxwell model, has emerged as a counterpart and draw the attention of robotics researchers. In the theoretical analysis, it turns out that the two pattern are both equivalents to some extent, but notable differences of response characteristics exist, especially in the effect of damping viscosity. However, this novel impedance control design is lack of validation on realistic robot platforms. In this study, stability analysis and experimental evaluation are achieved using a 3-fingered Barrett® robotic hand BH8-282 endowed with tactile sensing, mounted on a torque-controlled lightweight and collaborative robot KUKA® LBR iiwa 14 R820. Object handover and incoming objects catching tasks are executed for validation and analysis. Experimental results show that the series connection pattern has much better performance in natural impact or shock absorption, which indicate promising applications in robots’ safe and physical interaction with humans and objects in various environments.

Keywords: impedance control, Maxwell model, force control, dexterous manipulation

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: Moaz H. Ali, Ahmed H. Al-Saadi

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Most of the materials used in the industry of aero-engine components generally consist of titanium alloys. Advanced materials, because of their excellent combination of high specific strength, lightweight, and general corrosion resistance. In fact, chemical wear resistance of aero-engine alloy provide a serious challenge for cutting tool material during the machining process. The reduction in cutting temperature distributions leads to an increase in tool life and a decrease in wear rate. Hence, the chip morphology and segmentation play a predominant role in determining machinability and tool wear during the machining process. The result of low thermal conductivity and diffusivity of this alloy in the concentration of high temperatures at the tool-work-piece and tool-chip interface. Consequently, the chip morphology is very important in the study of machinability of metals as well as the study of cutting tool wear. Otherwise, the result will be accelerating tool wear, increasing manufacturing cost and time consuming.

Keywords: machinability, titanium alloy (ti-6al-4v), chip formation, milling process

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Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

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Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: Mahsa Oroojeni Mohammad Javad

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Globalization of economic activity and rapid growth of information technology has resulted in shorter product lifecycles, reduced transport capacity, dynamic and changing customer behaviors, and an increased focus on supply chain design in recent years. The design of the supply chain network is one of the most important supply chain management decisions. These decisions will have a long-term impact on the efficacy and efficiency of the supply chain. In this paper, a two-objective mixed-integer linear programming (MILP) model is developed for designing and optimizing a closed-loop green supply chain network that, to the greatest extent possible, includes all real-world assumptions such as multi-level supply chain, the multiplicity of production technologies, and multiple modes of transportation, with the goals of minimizing the total cost of the chain (first objective) and minimizing total emissions of emissions (second objective). The ε-constraint and CPLEX Solver have been used to solve the problem as a single-objective problem and validate the problem. Finally, the sensitivity analysis is applied to study the effect of the real-world parameters’ changes on the objective function. The optimal management suggestions and policies are presented.

Keywords: closed-loop supply chain, multi-level green supply chain, mixed-integer programming, transportation modes

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Authors: Amer Rghei

Abstract:

The Sahara region potentially is one of the most attractive heritage areas in the world. Yet presently, the heritage of the Sahara is currently facing serious planning challenges of underdeveloped and neglected economic and physical potentials. Deterioration of heritage resources has been observed by the author during his several field tours for historic sites has discovered special heritage values such as in Ghadames which combines historic oasis, natural environment along with its exceptional urban fabric and architectural character. Despite the richness of Ghadames with historic significance, it is found that at the present time, Ghadames city, the UNESCO World Heritage site, is facing serious challenges including the abandonment by its tenants and inclusive negligence by its officials. The author believes that Ghadames can illustrate an excellent heritage example in North Africa with cultural pride and socio-economic opportunities that can contribute to overall economic development in the Sahara region. However, the paper deals with the case of Ghadames ‘The World Heritage Site’ in Libya and discusses the current challenges and possible planning for its heritage conservation strategy. The momentous resources in Ghadames with their historical, environmental, economic, social, cultural, and aesthetic values would benefit from a careful heritage planning and management program for its significant values. In this paper an attempt is made to investigate this issue seriously towards building a model of a strategy for heritage conservation planning for Ghadames is proposed.

Keywords: Ghadames, Oasis architecture, Sahara region, heritage environment

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Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

Abstract:

Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

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Authors: VojtěCh Gybas, Libor Klubal, KateřIna KostoláNyová

Abstract:

Individualized teaching process for pupils with moderate mental disabilities with the help of using mobile touch devices may be one of the forms of teaching to achieve better development of these students during the teaching process. Didactics of information and communication technology (ICT) for special primary schools, where within the Czech Republic pupils with moderate mental retardation are educated, is not precisely and clearly defined. Still, general educational program for elementary school contains a special educational area of information and communication technology, in which the work and content area are focused on work with the classic desktop, and it is not always acceptable in the case of students with moderate mental disabilities. Individualization of their schooling requires a fully elaborate content of teaching material corresponding with intellectual abilities and individuality of each pupil. After three years of daily use of mobile touch devices iPad and participant observation of 7 pupils in a class from special elementary school, we can say that these technologies can be a very useful tool, and in many ways, they even exceed, compensate and replace freely available printed educational material that is rather outdated. By working with mobile touch technology, a pupil gains responsibility, trains his will, learns to rely on himself. The first results obtained from the case studies suggest that this form of teaching may also be beneficial for pupils with moderate mental disabilities.

Keywords: individualized teaching, mobile touch technology, iPad, moderate mental disability, special education needs

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Authors: Parker Murray, Marci Johnson, Tyson S. Burnham, Alina K. Fong, Mark D. Allen, Bruce McIff

Abstract:

Purpose: Pathological dysregulation of Neurovascular Coupling (NVC) caused by mild traumatic brain injury (mTBI) is the predominant source of chronic post-concussion syndrome (PCS) symptomology. fNCI has the ability to localize dysregulation in NVC by measuring blood-oxygen-level-dependent (BOLD) signaling during the performance of fMRI-adapted neuropsychological evaluations. With fNCI, 57 brain areas consistently affected by concussion were identified as PCS neural markers, which were validated on large samples of concussion patients and healthy controls. These neuromarkers provide the basis for a computation of PCS severity which is referred to as the Severity Index Score (SIS). The SIS has proven valuable in making pre-treatment decisions, monitoring treatment efficiency, and assessing long-term stability of outcomes. Methods and Materials: After being scanned while performing various cognitive tasks, 476 concussed patients received an SIS score based on the neural dysregulation of the 57 previously identified brain regions. These scans provide an objective measurement of attentional, subcortical, visual processing, language processing, and executive functioning abilities, which were used as biomarkers for post-concussive neural dysregulation. Initial SIS scores were used to develop individualized therapy incorporating cognitive, occupational, and neuromuscular modalities. These scores were also used to establish pre-treatment benchmarks and measure post-treatment improvement. Results: Changes in SIS were calculated in percent change from pre- to post-treatment. Patients showed a mean improvement of 76.5 percent (σ= 23.3), and 75.7 percent of patients showed at least 60 percent improvement. Longitudinal reassessment of 24 of the patients, measured an average of 7.6 months post-treatment, shows that SIS improvement is maintained and improved, with an average of 90.6 percent improvement from their original scan. Conclusions: fNCI provides a reliable measurement of NVC allowing for identification of concussion pathology. Additionally, fNCI derived SIS scores direct tailored therapy to restore NVC, subsequently resolving chronic PCS resulting from mTBI.

Keywords: concussion, functional magnetic resonance imaging (fMRI), neurovascular coupling (NVC), post-concussion syndrome (PCS)

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Authors: Atitallah Sofien, Bouyahia Olfa, Romdhani Meriam, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

Abstract:

Introduction: Spondylothoracic dysostosis, also known as Jarcho-Levin syndrome, is defined by a shortened neck and thorax, a protruding abdomen, inguinal and umbilical hernias, atypical spinal structure and rib fusion, leading to restricted chest movement or difficulty in breathing, along with urinary tract abnormalities and, potentially severe scoliosis. Aim: This is the case of a patient diagnosed with Jarcho-Levin syndrome, aiming to detail the range of abnormalities observed in this syndrome, the observed complications, and the therapeutic approaches employed. Results: A three-month-old male infant, born of a consanguineous marriage, delivered at full term by cesarean section, was admitted to the pediatric department for severe acute bronchiolitis. In his prenatal history, morphological ultrasound revealed macrosomia, a shortened spine, irregular vertebrae with thickened skin, normal fetal cardiac ultrasound, and the absence of the right kidney. His perinatal history included respiratory distress, requiring ventilatory support for five days. Upon physical examination, he had stunted growth, scoliosis, a short neck and trunk, longer upper limbs compared to lower limbs, varus equinus in the right foot, a neural tube defect, a low hairline, and low-set ears. Spondylothoracic dysostosis was suspected, leading to further investigations, including a normal transfontaneous ultrasound, a spinal cord ultrasound revealing a lipomyelocele-type closed dysraphism with a low-attached cord, an abdominal ultrasound indicating a single left kidney, and a cardiac ultrasound identifying Kommerell syndrome. Due to a lack of resources, genetic testing could not be performed, and the diagnosis was based on clinical criteria. Conclusion: Jarcho-Levin syndrome can result in a mortality rate of about 50%, primarily due to respiratory complications associated with thoracic insufficiency syndrome. Other complications, like heart and neural tube defects, can also lead to premature mortality. Therefore, early diagnosis and comprehensive treatment involving various specialists are essential.

Keywords: Jarcho-Levin syndrome, congenital disorder, scoliosis, spondylothoracic dysostosis, neural tube defect

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