Search results for: vision substitution systems

Authors: Naim Izet Kajtazi

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Context: Frequently, the cause of raised intracranial pressure remains unresolved and rarely is related to spinal tumors, moreover less to spinal medulloblastoma without primary brain focus. Process: An 18-year-old woman had a 3-month history of headaches and impaired vision. Neurological examination revealed bilateral sixth cranial nerve palsies with bilateral papilloedema of grade III. No focal brain or spine lesion was found on imaging. Consecutive lumbar punctures showed high opening pressure and subsequent increasing protein level. The meningeal biopsy was negative. At one point, she developed an increasing headache, vomiting and back pain. Spine MRI showed diffuse nodular leptomeningeal enhancement with the largest nodule at T6–T7. Malignant cells were detected in cerebrospinal fluid. She underwent laminectomy with excisional biopsy, and pathology showed medulloblastoma WHO grade IV. Outcome: She was treated with chemotherapy and craniospinal irradiation and made a good recovery. Relevance: Primary spinal leptomeningeal medulloblastoma is extremely rare, especially without primary brain focus, but may cause increased intracranial pressure, even in the early microscopic phases, and it should be considered in the differential diagnosis if conventional and aggressive treatment of idiopathic intracranial hypertension fails. We assume that arachnoiditis from tumor seeding caused increased intracranial pressure. Appropriate neurosurgical intervention and surgical biopsy are mandated if a suspicious lesion is detected. Consider proper rescreening of the whole neuroaxis in refractory cases of intracranial hypertension.

Keywords: CNS infection, IIH, headache, primary spinal leptomeningeal medulloblastoma

Procedia PDF Downloads 67

Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

Procedia PDF Downloads 114

Authors: Antonella Regueiro Fernandez

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This paper examines the issue of period poverty and the innovative approaches – or lack thereof – that national systems are using to tackle the issue. Through a systems-thinking and economical approach, the paper analyzes the intricate relationship between proper systemic change and sustainable innovations for this global problem. The first part of the research introduces period poverty and the lack of sustainable options currently in place to resolve the issue. The second part delves into a comparison of existing technologies – single-use and reusable period products -- and their benefits and deficiencies. It also provides a comparison of two countries and their existing solutions landscape (Scotland and the United States), arguing that while Scotland has provided an innovative national solution to the problem, it still lacks a proper assessment of the issue of sustainability, while the United States continues to lag in offering any holistic solution at all. The last part provides a conclusion to the research and affirms the importance of holistic policymaking approaches to issues of period poverty, which have the potential to truly benefit half of the world’s population while also encouraging environmental preservation.

Keywords: gender equity, sustainability, period poverty, SDGs, sustainable development

Procedia PDF Downloads 122

Authors: Thierno Diop, Michel Fortin, Jean Deteix

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Since the precise formulation of the elastic part is irrelevant for the description of the algorithm, we shall consider a generic case. In practice, however, we will have to deal with a non linear material (for instance a Mooney-Rivlin model). We are interested in solving a finite element approximation of the problem, leading to large-scale non linear discrete problems and, after linearization, to large linear systems and ultimately to calculations needing iterative methods. This also implies that penalty method, and therefore augmented Lagrangian method, are to be banned because of their negative effect on the condition number of the underlying discrete systems and thus on the convergence of iterative methods. This is in rupture to the mainstream of methods for contact in which augmented Lagrangian is the principal tool. We shall first present the problem and its discretization; this will lead us to describe a general solution algorithm relying on a preconditioner for saddle-point problems which we shall describe in some detail as it is not entirely standard. We will propose an iterative approach for solving three-dimensional frictional contact problems between elastic bodies, including contact with a rigid body, contact between two or more bodies and also self-contact.

Keywords: frictional contact, three-dimensional, large-scale, iterative method

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Authors: Heba M. Wagih, Hoda M. O. Mokhtar

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Social Network has recently played a significant role in both scientific and social communities. The growing adoption of social network applications has been a relevant source of information nowadays. Due to its popularity, several research trends are emerged to service the huge volume of users including, Location-Based Social Networks (LBSN), Recommendation Systems, Sentiment Analysis Applications, and many others. LBSNs applications are among the highly demanded applications that do not focus only on analyzing the spatiotemporal positions in a given raw trajectory but also on understanding the semantics behind the dynamics of the moving object. LBSNs are possible means of predicting human mobility based on users social ties as well as their spatial preferences. LBSNs rely on the efficient representation of users’ trajectories. Hence, traditional raw trajectory information is no longer convenient. In our research, we focus on studying human behavior trajectory which is the major pillar in location recommendation systems. In this paper, we propose an ontology design patterns with their underlying description logics to efficiently annotate human behavior trajectories.

Keywords: human behavior trajectory, location-based social network, ontology, social network

Procedia PDF Downloads 452

Authors: I. Valdez, J. Perdomo, M. Colindres, N. Castro

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Today, digital servo systems are extensively used in industrial manufacturing processes, robotic applications, vehicles and other areas. In such control systems, control action is provided by digital controllers with different compensation algorithms, which are designed to meet specific requirements for a given application. Due to the constant search for optimization in industrial processes, it is of interest to design digital controllers that offer ease of realization, improved computational efficiency, affordable return rates, and ease of tuning that ultimately improve the performance of the controlled actuators. There is a vast range of options of compensation algorithms that could be used, although in the industry, most controllers used are based on a PID structure. This research article compares different types of digital compensators implemented in a servo system for DC motor position control. PID compensation is evaluated on its two most common architectures: PID position form (1 DOF), and PID speed form (2 DOF). State feedback algorithms are also evaluated, testing two modern control theory techniques: discrete state observer for non-measurable variables tracking, and a linear quadratic method which allows a compromise between the theoretical optimal control and the realization that most closely matches it. The compared control systems’ performance is evaluated through simulations in the Simulink platform, in which it is attempted to model accurately each of the system’s hardware components. The criteria by which the control systems are compared are reference tracking and disturbance rejection. In this investigation, it is considered that the accurate tracking of the reference signal for a position control system is particularly important because of the frequency and the suddenness in which the control signal could change in position control applications, while disturbance rejection is considered essential because the torque applied to the motor shaft due to sudden load changes can be modeled as a disturbance that must be rejected, ensuring reference tracking. Results show that 2 DOF PID controllers exhibit high performance in terms of the benchmarks mentioned, as long as they are properly tuned. As for controllers based on state feedback, due to the nature and the advantage which state space provides for modelling MIMO, it is expected that such controllers evince ease of tuning for disturbance rejection, assuming that the designer of such controllers is experienced. An in-depth multi-dimensional analysis of preliminary research results indicate that state feedback control method is more satisfactory, but PID control method exhibits easier implementation in most control applications.

Keywords: control, DC motor, discrete PID, discrete state feedback

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Authors: Siah Koka, Rony Swennen

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Arumeru district is located in Arusha region in Upper Pangani basin in Tanzania. Economically it is dominated with agricultural activities. Banana, coffee, maize, beans, tomatoes, and cassava are the most important food and cash crops. This paper characterized the banana-based farming system of Arumeru district, evaluates its sustainability as well as research needs. The household questionnaire was performed on-site and on farm observation. Transect walk also involved to identify different agro- ecological zones. Results show that farm holdings (home gardens) are smaller than a hectare (0.7 ha) and continue to fragment as population continues to grow. Banana cultivation is the backbone of the farming systems present both in the upland and plains. In the upper belt banana found their place in the forest, which form the home garden structure typical to East African highland banana production systems. However, in the plains, cultivation is done in monoculture and depends heavily on irrigation. We found slightly less cultivars present and hypothetically more pest and disease pressure. This was mainly seen for Fusarium oxysporum species, which eradicates susceptible cultivars such as Mchare cultivars rapidly given the method of irrigation. The smaller permanent upland home garden plots provide thus a more suitable environment where banana perform better. It should be noted that findings indicated good performance to occur in the less suitable plains too. Good management is believed to be the most influencing factor, although our survey failed in identifying them. Population pressure is currently pushing the sustainable system in the uplands to its boundaries. Nutrient mining, deforestation and changing rain patterns threat production not only on Mt. Meru but on a global scale.

Keywords: Arumeru district, banana-based farming system, Tanzania, Arumeru district

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Authors: Ashkan Asgari, Korous Khoshbakht, Saeid Soufizadeh

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Various factors including land lots can affect biodiversity indices in Agricultural systems. Field study conducted to evaluate factors affecting crop diversity in Sarpolzahab in 2012. Required data were collected through direct observation of farms and filling questionnaires. Total numbers of 140 questionnaires were filled, SAS Software was used to analyse data and Ecological Methodology Program was applied to calculate Shannon-Winner index, subsequently. Results of study indicated that average number of land lots for each farmer was 2.78 and various from 2.2 in Rikhak Olia Village to 4.31 in Golam Kaboud Olia Village which shows small size of land lots due to separating larger lots by children of deceased farmers. The correlation between number of land lots and species biodiversity (0.308**) was significant and Shannon-Winner index was (0.262**). Therefore, according to the mentioned results one can assume that increase in number of land lots results in improving of the target index. Multiple land lots allow farmers to cultivate various crops which results in increasing biodiversity of crops in agro ecosystem. Subsequently, this increase will facilitate economic sustainability of the farmers and distribution of work force in the region throughout the year. The correlation of seasonal workers with biodiversity of crop species (0.256**) and Shannon-Winner (0.286**) was statistically significant and increasing number of seasonal work forces had resulted in improving crop biodiversity and decreasing dominant species or single crop farming systems. Vegetable farms which have a significant diversity, require a significant number of work forces which describes correlation between number of workers and diversity of species.

Keywords: agricultural systems, biodiversity indices, Shannon-Winner index, sustainability, rural

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Authors: M. Rahimnejad, B. Vahidi, B. Ebrahimi Hoseinzadeh, F. Yazdian, P. Motamed Fath, R. Jamjah

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In this study, we developed and simulated nano-drug delivery systems efficacy in compare to free drug prescription. Computational models can be utilized to accelerate experimental steps and control the experiments high cost. Molecular dynamics simulation (MDS), in particular NAMD was utilized to better understand the anti-cancer drug interaction with cell membrane model. Paclitaxel (PTX) and dipalmitoylphosphatidylcholine (DPPC) were selected for the drug molecule and as a natural phospholipid nanocarrier, respectively. This work focused on two important interaction parameters between molecules in terms of center of mass (COM) and van der Waals interaction energy. Furthermore, we compared the simulation results of the PTX interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane. The molecular dynamic analysis resulted in low energy between the nanocarrier and the cell membrane as well as significant decrease of COM amount in the nanocarrier and the cell membrane system during the interaction. Thus, the drug vehicle showed notably better interaction with the cell membrane in compared to free drug interaction with the cell membrane.

Keywords: anti-cancer drug, center of mass, interaction energy, molecular dynamics simulation, nanocarrier

Procedia PDF Downloads 341

Authors: Gunasekaran Raja, Kottilingam Kottursamy, Rajakumar Arul, Ramkumar Jayaraman, Krithika Sairam, Lakshmi Ravi

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The synchronization server maintains a dynamically changing cache, which contains the data items which were requested and collected by the mobile node from the server. The order and presence of tuples in the cache changes dynamically according to the frequency of updates performed on the data, by the server and client. To synchronize, the data which has been modified by client and the server at an instant are collected, batched together by the type of modification (insert/ update/ delete), and sorted according to their update frequencies. This ensures that the DCASH (Dynamic Cache Synchronization Algorithm for Heterogeneous Reverse Y synchronizing Mobile Database Systems) gives priority to the frequently accessed data with high usage. The optimal memory management algorithm is proposed to manage data items according to their frequency, theorems were written to show the current mobile data activity is reverse Y in nature and the experiments were tested with 2g and 3g networks for various mobile devices to show the reduced response time and energy consumption.

Keywords: mobile databases, synchronization, cache, response time

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Khaled Own Mohaisen, Md. Hasan Zahir, Salah U. Al-Dulaijan, Shamsad Ahmad, Mohammed Maslehuddin

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Shape-stabilized phase change materials (ss-PCMs) for energy storage systems were developed using perlite, scoria, and oil ash as a carrier, with polyethylene glycol (PEG) with a molecular weight of 6000 as phase change material (PCM). Physical mixing using simple impregnation of ethanol evaporation technique method was carried out to fabricate the form stabilized PCM. The fabricated PCMs prevent leakage, reduce the supercooling effect and minimize recalescence problems of the PCM. The differential scanning calorimetry (DSC) results show that perlite composite (ExPP) has the highest latent heat of melting and freezing values of (141.6 J/g and 143.7 J/g) respectively, compared with oil ash (OAP) and scoria (SCP) composites. Moreover, ExPP has the highest impregnation ratio, energy storage efficiency, and energy storage capacity compared with OAP and SCP. However, OAP and SCP have higher thermal conductivity values compared to ExPP composites which accelerate the thermal storage response in the composite. These results were confirmed with DSC, and the characteristic of the PCMs was investigated by using XRD and FE-SEM techniques.

Keywords: expanded perlite, oil ash, scoria, energy storage material

Procedia PDF Downloads 90

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Janaki Rama Raju Patchamatla, Emani Pavan Kumar

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The idea of increasing the existing train speeds and introduction of the high-speed trains in India as a part of Vision-2020 is really challenging from both economic viability and technical feasibility. More than economic viability, technical feasibility has to be thoroughly checked for safe operation and execution. Trains moving at high speeds need a well-established firm and safe track thoroughly tested against vibration effects. With increased speeds of trains, the track structure and layered soil-structure interaction have to be critically assessed for vibration and displacements. Physical establishment of track, testing and experimentation is a costly and time taking process. Software-based modelling and simulation give relatively reliable, cost-effective means of testing effects of critical parameters like sleeper design and density, properties of track and sub-grade, etc. The present paper reports the applicability of infinite elements in reducing the unrealistic stress-wave reflections from so-called soil-structure interface. The influence of the infinite elements is quantified in terms of the displacement time histories of adjoining soil and the deformation pattern in general. In addition, the railhead response histories at various locations show that the numerical model is realistic without any aberrations at the boundaries. The numerical model is quite promising in its ability to simulate the critical parameters of track design.

Keywords: high speed railway track, finite element method, Infinite elements, vibration analysis, soil-structure interface

Procedia PDF Downloads 272

Authors: Maria Nabakooza

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Efficient agricultural production is very significant in attaining food sufficiency and security in the world. Many methods are employed by the farmers while attending to their gardens, from manual to mechanized, with Farmers range from subsistence to commercial depending on the motive. This creates a lacuna in the modes of operation in this field as different farmers will take different approaches. This has led to many e-Learning courses being introduced to address this gap. Many e-learning systems use advanced network technologies like Web services, grid computing to promote learning at any time and any place. Many of the existing systems have not inculcated the applicability of the modules in them, the tools to be used and further access whether they are the right tools for the right job. A thorough investigation into the applicability of adaptive eLearning in the agricultural sector has not been taken into account; enabling the assumption that eLearning is the right tool for boosting productivity in this sector. This study comes in to provide an insight and thorough analysis as to whether adaptive eLearning is the right tool for boosting agricultural productivity. The Simulation will adopt a system dynamics modeling approach as a way of examining causality and effect relationship. This study will provide teachers with an insight into which tools they should adopt in designing, and provide students the opportunities to achieve an orderly learning experience through adaptive navigating e-learning services.

Keywords: agriculture, adaptive, e-learning, technology

Procedia PDF Downloads 251

Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

Procedia PDF Downloads 478

Authors: Emile Niringiyimana, LI Ji Qing, Giovanni Dushimimana, Virginie Umwere

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The development and utilization of renewable energy (RE) can not only effectively reduce carbon dioxide (CO2) emissions, but also became a solution to electricity shortage mitigation in rural areas. Hybrid RE systems are promising ways to provide consistent and continuous power for isolated areas. This work investigated the prospect and cost effectiveness of hybrid system complementarity between a 100kW solar PV system and a small-scale 200kW hydropower station in the South of Rwanda. In order to establish the optimal size of a RE system with adequate sizing of system components, electricity demand, solar radiation, hydrology, climate data are utilized as system input. The average daily solar radiation in Rukarara is 5.6 kWh/m2 and average wind speed is 3.5 m/s. The ideal integrated RE system, according to Homer optimization, consists of 91.21kW PV, 146kW hydropower, 12 x 24V li-ion batteries with a 20kW converter. The method of enhancing such hybrid systems control, sizing and choice of components is to reduce the Net present cost (NPC) of the system, unmet load, the cost of energy and reduction of CO2. The power consumption varies according to dominant source of energy in the system by controlling the energy compensation depending on the generation capacity of each power source. The initial investment of the RE system is $977,689.25, and its operation and maintenance expenses is $142,769.39 over a 25-year period. Although the investment is very high, the targeted profits in future are huge, taking into consideration of high investment in rural electrification structure implementations, tied with an increase of electricity cost and the 5 years payback period. The study outcomes suggest that the standalone hybrid PV-Hydropower system is feasible with zero pollution in Rukara community.

Keywords: HOMER optimization, hybrid power system, renewable energy, NPC and solar pv systems

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Sweta Iyer, Nemeshwaree Behary, Vincent Nierstrasz

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Various organisms involve bioluminescence for their particular biological function. The bio-based molecules responsible for bioluminescence vary from one species to another, research has been done to identify the chemistry and different mechanisms involved in light production in living organisms. The light emitting chemical systems such as firefly and bacterial luminous mostly involves enzyme-catalyzed reactions and is widely used for ATP measurement, bioluminescence imaging, environmental biosensors etc. Our strategy is to design bioluminescent textiles using such bioluminescent systems. Hence, a detailed literature work was carried out to study on how to mimic bioluminescence effect seen in nature. Reaction mechanisms in various bioluminescent living organisms were studied and the components or molecules responsible for luminescence were identified. However, the challenge is to obtain the same effect on textiles by immobilizing enzymes responsible for light creation. Another challenge is also to regenerate substrates involved in the reaction system to create a longer lasting illumination in bioluminescent textiles. Natural film-forming polymers were used to immobilize the reactive components including enzymes on textile materials to design a biomimetic luminescent textile.

Keywords: bioluminescence, biomimetic, immobilize, luminescent textile

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Authors: Siham Rahoui, Amr Mahfouz, Amr Arisha

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In a highly competitive environment characterised by uncertainty and disruptions, such as the recent COVID-19 outbreak, supply chains (SC) face the challenge of maintaining their cost at minimum levels while continuing to provide customers with high-quality products and services. More importantly, businesses in such an economic context strive to maintain survival by keeping the cost of undertaken activities (such as logistics) low and in-house. To do so, managers need to understand the costs associated with different products and services in order to have a clear vision of the SC performance, maintain profitability levels, and make strategic decisions. In this context, SC literature explored different costing models that sought to determine the costs of undertaking supply chain-related activities. While some cost accounting techniques have been extensively explored in the SC context, more contributions are needed to explore the potential of time driven activity-based costing (TDABC). More specifically, more applications are needed in the manufacturing context of the SC, where the debate is ongoing. The aim of the study is to assess the capability of the technique to assess the operational performance of the logistics function. Through a case study methodology applied to a manufacturing company operating in the automotive industry, TDABC evaluates the efficiency of the current configuration and its logistics processes. The study shows that monitoring the process efficiency and cost efficiency leads to strategic decisions that contributed to improve the overall efficiency of the logistics processes.

Keywords: efficiency, operational performance, supply chain costing, time driven activity based costing

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Authors: Saeed M. Alshahrani

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This research integrated blockchain technology to reform medical records management in healthcare informatics. It was aimed at resolving the limitations of centralized systems by establishing a secure, decentralized, and user-centric platform. The system was architected with a sophisticated three-tiered structure, integrating advanced cryptographic methodologies, consensus algorithms, and the Fast Healthcare Interoperability Resources (HL7 FHIR) standard to ensure data security, transaction validity, and semantic interoperability. The research has profound implications for healthcare delivery, patient care, legal compliance, operational efficiency, and academic advancements in blockchain technology and healthcare IT sectors. The methodology adapted in this research comprises of Preliminary Feasibility Study, Literature Review, Design and Development, Cryptographic Algorithm Integration, Modeling the data and testing the system. The research employed a permissioned blockchain with a Practical Byzantine Fault Tolerance (PBFT) consensus algorithm and Ethereum-based smart contracts. It integrated advanced cryptographic algorithms, role-based access control, multi-factor authentication, and RESTful APIs to ensure security, regulate access, authenticate user identities, and facilitate seamless data exchange between the blockchain and legacy healthcare systems. The research contributed to the development of a secure, interoperable, and decentralized system for managing medical records, addressing the limitations of the centralized systems that were in place. Future work will delve into optimizing the system further, exploring additional blockchain use cases in healthcare, and expanding the adoption of the system globally, contributing to the evolution of global healthcare practices and policies.

Keywords: healthcare informatics, blockchain, medical records management, decentralized architecture, data security, cryptographic algorithms

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Authors: Shusmita Khan, Shams El Arifeen, Kanta Jamil

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Background: Nutrition transition in Bangladesh has progressed across various relevant socio-demographic contextual issues. For a developing country like Bangladesh, its is believed that, overnutrition is less prevalent than undernutrition. However, recent evidence suggests that a rapid shift is taking place where overweight is subduing underweight. With this rapid increase, for Bangladesh, it will be challenging to achieve the global agenda on halting overweight and obesity. Methods: A secondary analysis was performed from six successive national demographic and health surveys to get the trend on undernutrition and overnutrition for women from reproductive age. In addition, national relevant policy papers were reviewed to determine the countries readiness for whole of the systems approach to tackle this epidemic. Results: Over the last decade, the proportion of women with low body mass index (BMI<18.5), an indicator of undernutrition, has decreased markedly from 34% to 19%. However, the proportion of overweight women (BMI ≥25) increased alarmingly from 9% to 24% over the same period. If the WHO cutoff for public health action (BMI ≥23) is used, the proportion of overweight women has increased from 17% in 2004 to 39% in 2014. The increasing rate of obesity among women is a major challenge to obstetric practice for both women and fetuses. In the long term, overweight women are also at risk of future obesity, diabetes, hyperlipidemia, hypertension, and heart disease. These diseases have serious impact on health care systems. Costs associated with overweight and obesity involves direct and indirect costs. Direct costs include preventive, diagnostic, and treatment services related to obesity. Indirect costs relate to morbidity and mortality costs including productivity. Looking at the Bangladesh Health Facility Survey, it is found that the country is bot prepared for providing nutrition-related health services, regarding prevention, screening, management and treatment. Therefore, if this nutrition transition is not addressed properly, Bangladesh will not be able to achieve the target of the NCD global monitoring framework of the WHO. Conclusion: Addressing this nutrition transition requires contending ‘malnutrition in all its forms’ and addressing it with integrated approaches. Whole of the systems action is required at all levels—starting from improving multi-sectoral coordination to scaling up nutrition-specific and nutrition-sensitive mainstreamed interventions keeping health system in mind.

Keywords: nutrition transition, Bangladesh, health system, undernutrition, overnutrition, obesity

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Authors: Emily Kambalame

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Water distribution networks necessitate many investments for construction, prompting researchers to seek cost reduction and efficient design solutions. Optimization techniques are employed in this regard to address these challenges. In this context, the penalty-free multi-objective evolutionary algorithm (PFMOEA) coupled with pressure-dependent analysis (PDA) was utilized to develop a multi-objective evolutionary search for the optimization of water distribution systems (WDSs). The aim of this research was to find out if the computational efficiency of the PFMOEA for WDS optimization could be enhanced. This was done by applying real coding representation and retaining different percentages of feasible and infeasible solutions close to the Pareto front in the elitism step of the optimization. Two benchmark network problems, namely the Two-looped and Hanoi networks, were utilized in the study. A comparative analysis was then conducted to assess the performance of the real-coded PFMOEA in relation to other approaches described in the literature. The algorithm demonstrated competitive performance for the two benchmark networks by implementing real coding. The real-coded PFMOEA achieved the novel best-known solutions ($419,000 and $6.081 million) and a zero-pressure deficit for the two networks, requiring fewer function evaluations than the binary-coded PFMOEA. In previous PFMOEA studies, elitism applied a default retention of 30% of the least cost-feasible solutions while excluding all infeasible solutions. It was found in this study that by replacing 10% and 15% of the feasible solutions with infeasible ones that are close to the Pareto front with minimal pressure deficit violations, the computational efficiency of the PFMOEA was significantly enhanced. The configuration of 15% feasible and 15% infeasible solutions outperformed other retention allocations by identifying the optimal solution with the fewest function evaluation

Keywords: design optimization, multi-objective evolutionary, penalty-free, water distribution systems

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Authors: Jingjue Bao, Ye Li, Yujie Qi

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The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

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Authors: Mary Cheptanui Sambu

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Teaching practice is an integral component of students who are training to be teachers, as it provides them with an opportunity to gain experience in an actual teaching and learning environment. This study explored the experiences of trainee teachers from a local university in Kenya, undergoing a three-month teaching practice in Special Secondary schools in the country. The main aim of the study was to understand the trainees’ experiences, their expectations, and the realities encountered during the teaching practice period. The study focused on special secondary schools for learners with hearing impairment. A descriptive survey design was employed and a sample size of forty-four respondents from special secondary schools for learners with hearing impairment was purposively selected. A questionnaire was administered to the respondents and the data obtained analysed using the Statistical Package for the Social Sciences (SPSS). Preliminary analysis shows that challenges facing special secondary schools include inadequate teaching and learning facilities and resources, low academic performance among learners with hearing impairment, an overloaded curriculum and inadequate number of teachers for the learners. The study findings suggest that the Kenyan government should invest more in the education of special needs children, particularly focusing on increasing the number of trained teachers. In addition, the education curriculum offered in special secondary schools should be tailored towards the needs and interest of learners. These research findings will be useful to policymakers and curriculum developers, and will provide information that can be used to enhance the education of learners with hearing impairment; this will lead to improved academic performance, consequently resulting in better transitions and the realization of Vision 2030.

Keywords: hearing impairment, special secondary schools, trainee, teaching practice

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Authors: Youcef Sehili, Khaled Loubar, Lyes Tarabet, Mahfoudh Cerdoun, Clement Lacroix

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As emissions regulations grow more stringent and traditional fuel sources become increasingly scarce, incorporating carbon-free fuels in the transportation sector emerges as a key strategy for mitigating the impact of greenhouse gas emissions. While the utilization of hydrogen (H2) presents significant technological challenges, as evident in the engine limitation known as knocking, ammonia (NH3) provides a viable alternative that overcomes this obstacle and offers convenient transportation, storage, and distribution. Moreover, the implementation of a dual-fuel engine using ammonia as the primary gas is promising, delivering both ecological and economic benefits. However, when employing this combustion mode, the substitution of ammonia at high rates adversely affects combustion performance and leads to elevated emissions of unburnt NH3, especially under high loads, which requires special treatment of this mode of combustion. This study aims to simulate combustion in a common rail direct injection (CRDI) dual-fuel engine, considering the fundamental geometry of the combustion chamber as well as fifteen (15) alternative proposed geometries to determine the configuration that exhibits superior engine performance during high-load conditions. The research presented here focuses on improving the understanding of the equations and mechanisms involved in the combustion of finely atomized jets of liquid fuel and on mastering the CONVERGETM code, which facilitates the simulation of this combustion process. By analyzing the effect of piston bowl shape on the performance and emissions of a diesel engine operating in dual fuel mode, this work combines knowledge of combustion phenomena with proficiency in the calculation code. To select the optimal geometry, an evaluation of the Swirl, Tumble, and Squish flow patterns was conducted for the fifteen (15) studied geometries. Variations in-cylinder pressure, heat release rate, turbulence kinetic energy, turbulence dissipation rate, and emission rates were observed, while thermal efficiency and specific fuel consumption were estimated as functions of crankshaft angle. To maximize thermal efficiency, a synergistic approach involving the enrichment of intake air with oxygen (O2) and the enrichment of primary fuel with hydrogen (H2) was implemented. Based on the results obtained, it is worth noting that the proposed geometry (T8_b8_d0.6/SW_8.0) outperformed the others in terms of flow quality, reduction of pollutants emitted with a reduction of more than 90% in unburnt NH3, and an impressive improvement in engine efficiency of more than 11%.

Keywords: ammonia, hydrogen, combustion, dual-fuel engine, emissions

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Authors: Ali Etemadi, Polat H. Gulkan

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The drift spectrum derived through the continuous shear-beam and wave propagation theory is known to be useful appliance to measure of the demand of pulse like near field ground motions on building structures. As regards, many of old frame buildings with poor or non-ductile column elements, pass the elastic limits and blurt the post yielding hysteresis degradation responses when subjected to such impulsive ground motions. The drift spectrum which, is based on a linear system cannot be predicted the overestimate drift demands arising from inelasticity in an elastic plastic systems. A simple procedure to estimate the drift demands in shear-type frames which, respond over the elastic limits is described and effect of hysteresis degradation behavior on seismic demands is clarified. Whereupon the modification factors are proposed to incorporate the hysteresis degradation effects parametrically. These factors are defined with respected to the linear systems. The method can be applicable for rapid assessment of existing poor detailed, non-ductile buildings.

Keywords: drift spectrum, shear-type frame, stiffness and strength degradation, pinching, smooth hysteretic model, quasi static analysis

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Authors: Icaro V. Soares, Guilherme L. F. Brandao, Ursula D. C. Resende, Glaucio L. Siqueira

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Electrical energy can be wirelessly transmitted through resonant coupled coils that operate in the near-field region. Once in this region, the field has evanescent character, the efficiency of Resonant Wireless Power Transfer (RWPT) systems decreases proportionally with the inverse cube of distance between the transmitter and receiver coils. The commercially available RWPT systems are restricted to short and mid-range applications in which the distance between coils is lesser or equal to the coil size. An alternative to overcome this limitation is applying metamaterial structures to enhance the coupling between coils, thus reducing the field decay along the distance between them. Metamaterials can be conceived as composite materials with periodic or non-periodic structure whose unconventional electromagnetic behaviour is due to its unit cell disposition and chemical composition. This new kind of material has been used in frequency selective surfaces, invisibility cloaks, leaky-wave antennas, among other applications. However, for RWPT it is mainly applied as superlenses which are lenses that can overcome the optical limitation and are made of left-handed media, that is, a medium with negative magnetic permeability and electric permittivity. As RWPT systems usually operate at wavelengths of hundreds of meters, the metamaterial unit cell size is much smaller than the wavelength. In this case, electric and magnetic field are decoupled, therefore the double negative condition for superlenses are not required and the negative magnetic permeability is enough to produce an artificial magnetic medium. In this work, the influence of the magnetic permeability of a metamaterial slab inserted between two loosely coupled coils is studied in order to find the condition that leads to the maximum transmission efficiency. The metamaterial used is formed by a subwavelength unit cell that consist of a capacitor-loaded split ring with an inner spiral that is designed and optimized using the software Computer Simulation Technology. The unit cell permeability is experimentally characterized by the ratio of the transmission parameters between coils measured with and without the presence of the metamaterial slab. Early measurements results show that the transmission coefficient at the resonant frequency after the inclusion of the metamaterial is about three times higher than with just the two coils, which confirms the enhancement that this structure brings to RWPT systems.

Keywords: electromagnetic lens, loosely coupled coils, magnetic permeability, metamaterials, resonant wireless power transfer, subwavelength unit cells

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Authors: Carlos Riascos, Peter Thomson

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Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.

Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy

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Authors: Angeliki Vassila, Dimitrios Kalogeropoulos, Rania Rawashdeh, Nigel Hall, Najiha Rahman, Mark Fabian, Suresh Thulasidharan, Hossain Parwez

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Introduction: Necrotising scleritis is a severe form of scleritis and poses a significant threat to vision. It can manifest in various systemic autoimmune disorders, systemic vasculitis, or as a consequence of microbial infections. The objective of this study is to present a case of necrotizing scleritis associated with scleroderma, which was further complicated by a secondary Staphylococcus epidermidis infection. Methods: This is a retrospective analysis that examines the medical records of a patient who was hospitalised in the Eye Unit at University Hospital Southampton. Results: A 78-year-old woman presented at the eye casualty department of our unit with a two-week history of progressively worsening pain in her left eye. She received a diagnosis of necrotising scleritis and was admitted to the hospital for further treatment. It was decided to commence a three-day course of intravenous methylprednisolone followed by a tapering regimen of oral steroids. Additionally, a conjunctival swab was taken, and two days later, it revealed the presence of S. epidermidis, indicating a potential secondary infection. Given this finding, she was also prescribed topical (Ofloxacin 0.3% - four times daily) and oral (Ciprofloxacin 750mg – twice daily) antibiotics. The inflammation and symptoms gradually improved, leading to the patient being scheduled for a scleral graft and applying an amniotic membrane to cover the area of scleral thinning. Conclusions: Rheumatoid arthritis and granulomatosis with polyangiitis are the most commonly identifiable systemic diseases associated with necrotising scleritis. Although association with scleroderma is extremely rare, early identification and treatment are necessary to prevent scleritis-related complications.

Keywords: scleritis, necrotizing scleritis, scleroderma, autoimmune disease

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