Search results for: project progress prediction

Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

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Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

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Authors: K. S. Al-Mugren, A. Yahya, S. Alodah, R. Alharbi, S. H. Almsaid , A. Alqahtani, H. Jaber, A. Basaqer, N. Alajra, N. Almoghati, A. Alsalman, Khalid Alharbi

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Context: The production of biofertilizers from naturally occurring microorganisms is an area of research that aims to enhance agricultural practices by utilizing local resources. This research project focuses on isolating and screening indigenous microorganisms with PK-fixing and phosphate solubilizing characteristics from local sources. Research Aim: The aim of this project is to develop a biofertilizer product using indigenous microorganisms and composted agro waste as a carrier. The objective is to enhance crop productivity and soil fertility through the application of biofertilizers. Methodology: The research methodology includes several key steps. Firstly, indigenous microorganisms will be isolated from local resources using the ten-fold serial dilutions technique. Screening assays will be conducted to identify microorganisms with phosphate solubilizing and PK-fixing activities. Agro-waste materials will be collected from local agricultural sources, and composting experiments will be conducted to convert them into organic matter-rich compost. Physicochemical analysis will be performed to assess the composition of the composted agro-waste. Gamma and X-ray irradiation will be used to sterilize the carrier material. The sterilized carrier will be tested for sterility using the ten-fold serial dilutions technique. Finally, selected indigenous microorganisms will be developed into biofertilizer products. Findings: The research aims to find suitable indigenous microorganisms with phosphate solubilizing and PK-fixing characteristics for biofertilizer production. Additionally, the research aims to assess the suitability of composted agro waste as a carrier for biofertilizers. The impact of gamma irradiation sterilization on pathogen elimination will also be investigated. Theoretical Importance: This research contributes to the understanding of utilizing indigenous microorganisms and composted agro waste for biofertilizer production. It expands knowledge on the potential benefits of biofertilizers in enhancing crop productivity and soil fertility. Data Collection and Analysis Procedures: The data collection process involves isolating indigenous microorganisms, conducting screening assays, collecting and composting agro waste, analyzing the physicochemical composition of composted agro waste, and testing carrier sterilization. The analysis procedures include assessing the abilities of indigenous microorganisms, evaluating the composition of composted agro waste, and determining the sterility of the carrier material. Conclusion: The research project aims to develop biofertilizer products using indigenous microorganisms and composted agro waste as a carrier. Through the isolation and screening of indigenous microorganisms, the project aims to enhance crop productivity and soil fertility by utilizing local resources. The research findings will contribute to the understanding of the suitability of composted agro waste as a carrier and the efficacy of gamma irradiation sterilization. The research outcomes will have theoretical importance in the field of biofertilizer production and agricultural practices.

Keywords: biofertilizer, microorganisms, agro waste, nuclear technologies

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Authors: Sandra Cardoso, Gaspar Pais, Judite Neves, Sandra Cavaca, Fernando Araújo

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In 2021, Portugal has 63 emergency department (ED) visits per 100 people annually, the highest numbers in Europe. While EDs provide a critical service, high use is indicative of inappropriate and inefficient healthcare. In Portugal, all ED have the Manchester Triage System (MTS), a clinical risk management tool to enable that patients are seen in order of clinical priority. In 2023, more than 40% of the ED visits were of non-urgent conditions (blue and green), that could be better managed in primary health care (PHC), meaning wrong use of resources and lack of health literacy. From 2017, the country has a phone line, SNS24 (Contact Centre of the National Health Service), for triage, counseling, and referral service, 24 hours/7 days a week. The pilot project ‘Call before, save lives’ was implemented in the municipalities of Póvoa de Varzim and Vila do Conde (around 150.000 residents), in May 2023, by the executive board of the Portuguese Health Service, with the support of the Shared Services of the Ministry of Health, and local authorities. This geographical area has short travel times, 99% of the population a family doctor and the region is organized in a health local unit (HLU), integrating PHC and the local hospital. The purposes of this project included to increase awareness to contact SNS 24, before going to an ED, and non-urgent conditions oriented to a family doctor, reducing ED visits. The implementation of the project involved two phases, beginning with: i) development of campaigns using local influencers (fishmonger, model, fireman) through local institutions and media; ii) provision of telephone installed on site to contact SNS24; iii) establishment of open consultation in PHC; iv) promotion of the use of SNS24; v) creation of acute consultations at the hospital for complex chronic patients; and vi) direct referral for home hospitalization by PHC. The results of this project showed an excellent level of access to SNS24, an increase in the number of users referred to ED, with great satisfaction of users and professionals. The second phase, initiated in January 2024, for access to the ED, the need for prior referral was established as an admission rule, except for certain situations, as trauma patients. If the patient refuses, their registration in the ED and subsequent screening in accordance with the MTS must be ensured. When the patient is non-urgent, shall not be observed in the ED, provided that, according to his clinical condition, is guaranteed to be referred to PHC or to consultation/day hospital, through effective scheduling of an appointment for the same or the following day. In terms of results, 8 weeks after beginning of phase 2, we assist of a decrease in self-reported patients to ED from 59% to 15%, and a reduction of around 7% of ED visits. The key for this success was an effective public campaign that increases the knowledge of the right use of the health system, and capable of changing behaviors.

Keywords: contact centre of the national health service, emergency department visits, public campaign, health literacy, SNS24

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Authors: Ahmed Abdulfatah Yusuf, Collins Oduor Ondiek

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The automation of farming activities can have a transformational impact on the agricultural sector, especially from the emerging new technologies such as the Internet of Things (IoT). The system uses water level sensors and soil moisture sensors that measure the content of water in the soil as the values generated from the sensors enable the system to use an appropriate quantity of water, which avoids over or under irrigation. Due to the increase in the world’s population, there is a need to increase food production. With this demand in place, it is difficult to increase crop yield using the traditional manual approaches that lead to the wastage of water, thus affecting crop production. Food insecurity has become a scourge greatly affecting the developing countries and agriculture is an essential part of human life and tends to be the mainstay of the economy in most developing nations. Thus, without the provision of adequate food supplies, the population of those living in poverty is likely to multiply. The project’s main objective is to design and develop an IoT (Internet of Things) microcontroller-based Smart Irrigation System. In addition, the specific research objectives are to find out the challenges with traditional irrigation approaches and to determine the benefits of IoT-based smart irrigation systems. Furthermore, the system includes Arduino, a website and a database that works simultaneously in collecting and storing the data. The system is designed to pave the way in attaining the Sustainable Development Goal (SDG 1), which aims to end extreme poverty in all forms by 2030. The research design aimed at this project is a descriptive research design. Data was gathered through online questionnaires that used both quantitative and qualitative in order to triangulate the data. Out of the 32 questionnaires sent, there were 32 responses leading to a 100% response rate. In terms of sampling, the target group of this project is urban farmers, which account for about 25% of the population of Nairobi. From the findings of the research carried out, it is evident that there is a need to move away from manual irrigation approaches due to the high wastage of water to the use of smart irrigation systems that propose a better way of conserving water while maintaining the quality and moisture of the soil. The research also found out that urban farmers are willing to adopt this system to better their farming practices. However, this system can be improved in the future by incorporating it with other features and deploying it to a larger geographical area.

Keywords: crop production, food security, smart irrigation system, sustainable development goal

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Authors: YuLung Wu, YuTien Wu, ShuMey Yu

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Game-based learning can enhance the learning motivation of students and provide a means for them to learn through playing games. This study used augmented reality technology to develop an interactive card game as a game-based teaching aid for delivering elementary school science course content with the aim of enhancing student learning processes and outcomes. Through playing the proposed card game, students can familiarize themselves with appearance, features, and foraging behaviors of insects. The system records the actions of students, enabling teachers to determine their students’ learning progress. In this study, 37 students participated in an assessment experiment and provided feedback through questionnaires. Their responses indicated that they were significantly more motivated to learn after playing the game, and their feedback was mostly positive.

Keywords: game-based learning, learning motivation, teaching aid, augmented reality

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Authors: K. Raja Rajan, D. Nagarajan

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Bored cast in-situ pile is a popular choice amongst consultant and contractor due to the ability to adjust the pile length suitably in case if any variation found in the actual geological strata. Bangladesh geological strata are dominated by silt content. Design is normally based on field test such as Standard Penetration test N-values. Initially, pile capacity estimated through static formula with co-relation of N-value and angle of internal friction. Initial pile load test was conducted in order to validate the geotechnical parameters assumed in design. Initial pile load test was conducted on 1.5m diameter bored cast in-situ pile. Kentledge method is used to load the pile for 2.5 times of its working load. Initially, safe working load of pile has been estimated as 570T, so test load is fixed to 1425T. Max load applied is 777T for which the settlement reached around 155mm which is more than 10% of diameter of piles. Pile load test results was not satisfactory and compelled to increase the pile length approximately 20% of its total length. Due to unpredictable geotechnical parameters, length of each pile has been increased which is having a major impact on the project cost and as well as in project schedule. Extra bore holes have been planned along with lab test results in order to redefine the assumed geotechnical parameters. This article presents detailed design assumptions of geotechnical parameters in the design stage and the results of pile load test which made to redefine the assumed geotechnical properties.

Keywords: end bearing, pile load test, settlement, shaft friction

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Authors: Sukhvinder Kaur, Ashok Agarwal

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Background: For the first time in 2009, India was able to generate estimates of HIV incidence (the number of new HIV infections per year). Analysis of epidemic projections helped in revealing that the number of new annual HIV infections in India had declined by more than 50% during the last decade (GOI Ministry of Health and Family Welfare, 2010). Then, National AIDS Control Organisation (NACO) planned to scale up its efforts in generating projections through epidemiological analysis and modelling by taking recent available sources of evidence such as HIV Sentinel Surveillance (HSS), India Census data and other critical data sets. Recently, NACO generated current round of HIV estimates-2012 through globally recommended tool “Spectrum Software” and came out with the estimates for adult HIV prevalence, annual new infections, number of people living with HIV, AIDS-related deaths and treatment needs. State level prevalence and incidence projections produced were used to project consequences of the epidemic in spectrum. In presence of HIV estimates generated at state level in India by NACO, USIAD funded PIPPSE project under the leadership of NACO undertook the estimations and projections to district level using same Spectrum software. In 2011, adult HIV prevalence in one of the high prevalent States, Maharashtra was 0.42% ahead of the national average of 0.27%. Considering the heterogeneity of HIV epidemic between districts, two districts of Maharashtra – Thane and Mumbai were selected to estimate and project the number of People-Living-with-HIV/AIDS (PLHIV), HIV-prevalence among adults and annual new HIV infections till 2017. Methodology: Inputs in spectrum included demographic data from Census of India since 1980 and sample registration system, programmatic data on ‘Alive and on ART (adult and children)’,‘Mother-Baby pairs under PPTCT’ and ‘High Risk Group (HRG)-size mapping estimates’, surveillance data from various rounds of HSS, National Family Health Survey–III, Integrated Biological and Behavioural Assessment and Behavioural Sentinel Surveillance. Major Findings: Assuming current programmatic interventions in these districts, an estimated decrease of 12% points in Thane and 31% points in Mumbai among new infections in HRGs and migrants is observed from 2011 by 2017. Conclusions: Project also validated decrease in HIV new infection among one of the high risk groups-FSWs using program cohort data since 2012 to 2016. Though there is a decrease in HIV prevalence and new infections in Thane and Mumbai, further decrease is possible if appropriate programme response, strategies and interventions are envisaged for specific target groups based on this evidence. Moreover, evidence need to be validated by other estimation/modelling techniques; and evidence can be generated for other districts of the state, where HIV prevalence is high and reliable data sources are available, to understand the epidemic within the local context.

Keywords: HIV sentinel surveillance, high risk groups, projections, new infections

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Authors: Hailemariam Getachew, John Sandi, Isata Dumbuya, Patricia Efe.Azikiwe, Evaline Nginge, Moses Mugisha, Eseoghene Dase, Foday Mandaray, Grace Moore

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Enhanced recovery after cesarean section (ERAC) is a standardized peri- operative care program that comprises the multidisciplinary team's collective efforts working in collaboration throughout the peri-operative period with the principal goal to improve quality of surgical care, decrease surgical related complications, and increasing patient satisfaction. Objective: The main objective of this project is to improve the implementation of enhanced recovery after cesarean section at Koidu Government hospital. Identified gap: Even though the hospital is providing comprehensive maternal and child care service, there are gaps in the implementation of ERAC. According to our survey, we found that there is low (13.3%) utilization of WHO surgical safety checklist, only limited (15.9%) patients get opioid free analgesia, pain was not recorded as a vital sign, there is no standardized checklist for hand over to and from Post Anesthesia care Unit(PACU). Furthermore, there is inconsistent evidence based post-operative care and there is no local consensus protocol and guideline as well. Implementation plan: we aimed at designing standardized protocol, checklist and guideline, provide training, build staff capacity, document pain as vital sign, perform regional analgesia, and provide evidence based post-operative care, monitoring and evaluation. Result: Data from 389 cesarean mothers showed that, Utilization of the WHO surgical safety check list found to be 95%, and pain assessment and documentation was done for all surgical patients. Oral feeding, ambulation and catheter removal was performed as per the ERAC standard for all patients. Postoperative complications drastically decreased from 13.6% to 8.1%. While, the rate of readmission was kept below 1%. Furthermore, the duration of hospital stay decreased from 4.64 days to 3.12 days. Conclusion The successful implementation of ERAC protocols demonstrates through this Quality Improvement Project that, the effectiveness of the protocols in improving recovery and patient outcome following cesarean section.

Keywords: cesarean delivery, enhanced recovery, quality improvement, patient outcome

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Authors: Rui Liu, Klaus Greve

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The navigation information is a kind of dynamic geographic information, and the navigation information system is a kind of special geographic information system. At present, there are many researches on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing is not deeply applied into the research of navigation information service. And the imperfection of navigation target coordination and navigation information sharing mechanism under certain navigation tasks has greatly affected the reliability and scientificity of navigation service such as path planning. Considering this, the project intends to study the multi-source information fusion and multi-objective united navigation information interaction mechanism: first of all, investigate the actual needs of navigation users in different areas, and establish the preliminary navigation information classification and importance level model; and then analyze the characteristics of the remote sensing and GIS vector data, and design the fusion algorithm from the aspect of improving the positioning accuracy and extracting the navigation environment data. At last, the project intends to analyze the feature of navigation information of the land, sea and air navigation targets, and design the united navigation data standard and navigation information sharing model under certain navigation tasks, and establish a test navigation system for united navigation simulation experiment. The aim of this study is to explore the theory of united navigation service and optimize the navigation information service model, which will lay the theory and technology foundation for the united navigation of land, sea and air targets.

Keywords: information fusion, united navigation, dynamic path planning, navigation information visualization

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Authors: Ridha Zgolli, Ahmed Belhaj, Maroua Ennouri

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This study presents a new method to predict cavitation area that may be eroded. It is based on the post-treatment of URANS simulations in cavitant flows. The most RANS calculations with incompressible consideration are based on cavitation model using mixture fluid with density (ρm) calculated as a function of liquid density (ρliq), vapour or gas density (ρvap) and vapour or gas volume fraction α (ρm = αρvap + (1-α) ρliq). The calculations are performed on hydrofoil geometries and compared with experimental works concerning flows characteristics (size of pocket, pressure, velocity). We present here the used cavitation model and the approach followed to evaluate the value of α fixing the shape of pocket around wall before collapsing.

Keywords: flows, CFD, cavitation, erosion

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Authors: Orod Zarrin, Mohsen Ramezan Shirazi

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Rehabilitation of dam components such as foundations, buttresses, spillways and overtopping protection require a wide range of construction and design methodologies. Geotechnical Engineering considerations play an important role in the design and construction of foundations of new dams. Much investigation is required to assess and evaluate the existing dams. The application of roller compacting concrete (RCC) has been accepted as a new method for constructing new dams or rehabilitating old ones. In the past 40 years there have been so many changes in the usage of RCC and now it is one of most satisfactory solutions of water and hydropower resource throughout the world. The considerations of rehabilitation and construction of dams might differ due to upstream reservoir and its influence on penetrating and dewatering of downstream, operations requirements and plant layout. One of the advantages of RCC is its rapid placement which allows the dam to be operated quickly. Unlike ordinary concrete it is a drier mix, and stiffs enough for compacting by vibratory rollers. This paper evaluates some different aspects of RCC and focuses on its preparation progress.

Keywords: spillway, vibrating consistency, fly ash, water tightness, foundation

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Authors: Mohammad Ghahramani, Fahimeh Saei Manesh

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Winning a soccer game is based on thorough and deep analysis of the ongoing match. On the other hand, giant gambling companies are in vital need of such analysis to reduce their loss against their customers. In this research work, we perform deep, real-time analysis on every soccer match around the world that distinguishes our work from others by focusing on particular seasons, teams and partial analytics. Our contributions are presented in the platform called “Analyst Masters.” First, we introduce various sources of information available for soccer analysis for teams around the world that helped us record live statistical data and information from more than 50,000 soccer matches a year. Our second and main contribution is to introduce our proposed in-play performance evaluation. The third contribution is developing new features from stable soccer matches. The statistics of soccer matches and their odds before and in-play are considered in the image format versus time including the halftime. Local Binary patterns, (LBP) is then employed to extract features from the image. Our analyses reveal incredibly interesting features and rules if a soccer match has reached enough stability. For example, our “8-minute rule” implies if 'Team A' scores a goal and can maintain the result for at least 8 minutes then the match would end in their favor in a stable match. We could also make accurate predictions before the match of scoring less/more than 2.5 goals. We benefit from the Gradient Boosting Trees, GBT, to extract highly related features. Once the features are selected from this pool of data, the Decision trees decide if the match is stable. A stable match is then passed to a post-processing stage to check its properties such as betters’ and punters’ behavior and its statistical data to issue the prediction. The proposed method was trained using 140,000 soccer matches and tested on more than 100,000 samples achieving 98% accuracy to select stable matches. Our database from 240,000 matches shows that one can get over 20% betting profit per month using Analyst Masters. Such consistent profit outperforms human experts and shows the inefficiency of the betting market. Top soccer tipsters achieve 50% accuracy and 8% monthly profit in average only on regional matches. Both our collected database of more than 240,000 soccer matches from 2012 and our algorithm would greatly benefit coaches and punters to get accurate analysis.

Keywords: soccer, analytics, machine learning, database

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Authors: Elena Filova, Ondrej Kaplan, Marie Markova, Helena Dragounova, Roman Matejka, Eduard Brynda, Lucie Bacakova

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Decellularized vessels have been evaluated as small-diameter vascular prostheses. Reseeding autologous cells onto decellularized tissue prior implantation should prolong prostheses function and make them living tissues. Suitable cell types for reseeding are both endothelial cells and bone marrow-derived stem cells, with a capacity for differentiation into smooth muscle cells upon mechanical loading. Endothelial cells assure antithrombogenicity of the vessels and MSCs produce growth factors and, after their differentiation into smooth muscle cells, they are contractile and produce extracellular matrix proteins as well. Fibrin is a natural scaffold, which allows direct cell adhesion based on integrin receptors. It can be prepared autologous. Fibrin can be modified with bound growth factors, such as basic fibroblast growth factor (FGF-2) and vascular endothelial growth factor (VEGF). These modifications in turn make the scaffold more attractive for cells ingrowth into the biological scaffold. The aim of the study was to prepare thin surface-attached fibrin assemblies with bound FGF-2 and VEGF, and to evaluate growth and differentiation of bone marrow-derived mesenchymal stem cells on the fibrin (Fb) assemblies. Following thin surface-attached fibrin assemblies were prepared: Fb, Fb+VEGF, Fb+FGF2, Fb+heparin, Fb+heparin+VEGF, Fb+heparin+FGF2, Fb+heparin+FGF2+VEGF. Cell culture poly-styrene and glass coverslips were used as controls. Human MSCs (passage 3) were seeded at the density of 8800 cells/1.5 mL alpha-MEM medium with 2.5% FS and 200 U/mL aprotinin per well of a 24-well cell culture. The cells have been cultured on the samples for 6 days. Cell densities on day 1, 3, and 6 were analyzed after staining with LIVE/DEAD cytotoxicity/viability assay kit. The differentiation of MSCs is being analyzed using qPCR. On day 1, the highest density of MSCs was observed on Fb+VEGF and Fb+FGF2. On days 3 and 6, there were similar densities on all samples. On day 1, cell morphology was polygonal and spread on all sample. On day 3 and 6, MSCs growing on Fb assemblies with FGF2 became apparently elongated. The evaluation of expression of genes for von Willebrand factor and CD31 (endothelial cells), for alpha-actin (smooth muscle cells), and for alkaline phosphatase (osteoblasts) is in progress. We prepared fibrin assemblies with bound VEGF and FGF-2 that supported attachment and growth of mesenchymal stem cells. The layers are promising for improving the ingrowth of MSCs into the biological scaffold. Supported by the Technology Agency of the Czech Republic TA04011345, and Ministry of Health NT11270-4/2010, and BIOCEV – Biotechnology and Biomedicine Centre of the Academy of Sciences and Charles University” project (CZ.1.05/1.1.00/02.0109), funded by the European Regional Development Fund for their financial supports.

Keywords: fibrin assemblies, FGF-2, mesenchymal stem cells, VEGF

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Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: Jaci Marie Mastrandrea, Rosario Haro

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Background: The National Comprehensive Cancer Network (NCCN) recommends that healthcare institutions have established processes for integrating palliative care (PC) into cancer treatment and that all cancer patients be screened for PC needs upon initial diagnosis as well as throughout the entire continuum of care (National Comprehensive Cancer Network, 2021). Early PC screening and intervention is directly associated with improved patient outcomes. The Sky Lakes Cancer Treatment Center (SLCTC) is an institution that has access to PC services yet does not have protocols in place for identifying patients with palliative needs or a standardized referral process. The aim of this quality improvement project was to improve early access to PC services by establishing a standardized screening and referral process for outpatient oncology patients. Method: The sample population included all adult patients with an oncology diagnosis who presented to the SLCTC for treatment during the project timeline. The “Palliative and Supportive Needs Assessment'' (PSNA) screening tool was developed from validated, evidence-based PC referral criteria. The tool was initially implemented using paper forms, and data was collected over a period of eight weeks. Patients were screened by nurses on the SLCTC oncology treatment team. Nurses responsible for screening patients received an educational inservice prior to implementation. Patients with a PSNA score of three or higher received an educational handout on the topic of PC and education about PC and symptom management. A score of five or higher indicates that PC referral is strongly recommended, and the patient’s EHR is flagged for the oncology provider to review orders for PC referral. The PSNA tool was approved by Sky Lakes administration for full integration into Epic-Beacon. The project lead collaborated with the Sky Lakes’ information systems team and representatives from Epic on the tool’s aesthetic and functionality within the Epic system. SLCTC nurses and physicians were educated on how to document the PSNA within Epic and where to view results. Results: Prior to the implementation of the PSNA screening tool, the SLCTC had zero referrals to PC in the past year, excluding referrals to hospice. Data was collected from the completed screening assessments of 100 patients under active treatment at the SLCTC. Seventy-three percent of patients met criteria for PC referral with a score greater than or equal to three. Of those patients who met referral criteria, 53.4% (39 patients) were referred for a palliative and supportive care consultation. Patients that were not referred to PC upon meeting criteria were flagged in EPIC for re-screening within one to three months. Patients with lung cancer, chronic hematologic malignancies, breast cancer, and gastrointestinal malignancy most frequently met the criteria for PC referral and scored highest overall on the scale of 0-12. Conclusion: The implementation of a standardized PC screening tool at the SLCTC significantly increased awareness of PC needs among cancer patients in the outpatient setting. Additionally, data derived from this quality improvement project supports the national recommendation for PC to be an integral component of cancer treatment across the entire continuum of care.

Keywords: oncology, palliative and supportive care, symptom management, outpatient oncology, palliative screening tool

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Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

Procedia PDF Downloads 188

Authors: Abidin Tortum, Kubra Kocabey

Abstract:

One of the sectors where the competition is experienced at the highest level in the world is the transformer sector, and sales can be made with a limited profit margin. For this reason, manufacturers must develop cost-cutting designs to achieve higher profits. The use of rectangular cores and coils in transformer design is one of the methods that can be used to reduce costs. According to the best knowledge we have obtained, we think that we are the first company producing rectangular core power transformers in our country. BETA, to reduce the cost of this project, more compact products to reveal, as we know it to increase the alleviate and competitiveness of the product, will perform cored coil design and production rectangle for the first-time power transformers in Turkey. The transformer to be designed shall be 16 MVA, 33/11 kV voltage level. With the rectangular design of the transformer core and windings, no-load losses can be reduced. Also, the least costly transformer type is rectangular. However, short-circuit forces on rectangular windings do not affect every point of the windings in the same way. Whereas more force is applied inwards to the mid-points of the low-voltage winding, the opposite occurs in the high-voltage winding. Therefore, the windings tend to deteriorate in the event of a short circuit. While trying to reach the project objectives, the difficulties in the design should be overcome. Rectangular core transformers to be produced in our country offer a more compact structure than conventional transformers. In other words, both height and width were smaller. Thus, the reducer takes up less space in the center. Because the transformer boiler is smaller, less oil is used, and its weight is lower. Biotemp natural ester fluid is used in rectangular transformer and the cooling performance of this oil is analyzed. The cost was also reduced with the reduction of dimensions. The decrease in the amount of oil used has also increased the environmental friendliness of the developed product. Transportation costs have been reduced by reducing the total weight. The amount of carbon emissions generated during the transportation process is reduced. Since the low-voltage winding is wound with a foil winding technique, a more resistant structure is obtained against short circuit forces. No-load losses were lower due to the use of a rectangular core. The project was handled in three phases. In the first stage, preliminary research and designs were carried out. In the second stage, the prototype manufacturing of the transformer whose designs have been completed has been started. The prototype developed in the last stage has been subjected to routine, type and special tests.

Keywords: rectangular core, power transformer, transformer, productivity

Procedia PDF Downloads 121

Authors: Omil Nady Mahrous Maximous

Abstract:

The construction industry is currently experiencing a shift towards digitisation. This transformation is driven by adopting technologies like Building Information Modelling (BIM), drones, and augmented reality (AR). These advancements are revolutionizing the process of designing, constructing, and operating projects. BIM, for instance, is a new way of communicating and exploiting technology such as software and machinery. It enables the creation of a replica or virtual model of buildings or infrastructure projects. It facilitates simulating construction procedures, identifying issues beforehand, and optimizing designs accordingly. Drones are another tool in this revolution, as they can be utilized for site surveys, inspections, and even deliveries. Moreover, AR technology provides real-time information to workers involved in the project. Implementing these technologies in the construction industry has brought about improvements in efficiency, safety measures, and sustainable practices. BIM helps minimize rework and waste materials, while drones contribute to safety by reducing workers' exposure to areas. Additionally, AR plays a role in worker safety by delivering instructions and guidance during operations. Although the digital transformation within the construction industry is still in its early stages, it holds the potential to reshape project delivery methods entirely. By embracing these technologies, construction companies can boost their profitability while simultaneously reducing their environmental impact and ensuring safer practices.

Keywords: architectural education, construction industry, digital learning environments, immersive learning BIM, digital construction, construction technologies, digital transformation artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

Procedia PDF Downloads 58

Authors: Yulin Liang

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Under the background of protecting ecology, natural education is an effective way for people to understand nature. At the same time, it is a new means of sustainable development of eco-tourism, which can improve the functions of China 's protected areas and develop new business formats for the development of national parks. This study takes national park gateway communities as the research object and uses literature review, inductive reasoning and other research methods to sort out the development process of natural education in China and the research progress of natural education design in national park gateway communities. Finally, it discuss how gateway communities can use natural education to transform their development methods and provide theoretical and practical basis for the development of gateway communities in national parks.

Keywords: nature education, gateway communities, national park, sustainable development

Procedia PDF Downloads 61

Authors: Hae-Won Seo, Yong-Gu Lee

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Recent progress in the next generation of automobile technology is geared towards incorporating information technology into cars. Collectively called smart cars are bringing intelligence to cars that provides comfort, convenience and safety. A branch of smart cars is connected-car system. The key concept in connected-cars is the sharing of driving information among cars through decentralized manner enabling collective intelligence. This paper proposes a foundation of the information model that is necessary to define the driving information for smart-cars. Road conditions are modeled through a unique data structure that unambiguously represent the time variant traffics in the streets. Additionally, the modeled data structure is exemplified in a navigational scenario and usage using UML. Optimal driving route searching is also discussed using the proposed data structure in a dynamically changing road conditions.

Keywords: connected-car, data modeling, route planning, navigation system

Procedia PDF Downloads 374

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

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

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

Procedia PDF Downloads 104

Authors: Chijioke Oliver Nwodoh, Jonah Ikechukwu Eze, Loretta Chika Ukwuaba, Ifeoma Ndubuisi, Ada Carol Nwaneri, Ijeoma Lewechi Okoronkwo

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Presence of nursing workforce with unequal qualification and status in Nigeria has undermined the growth of nursing profession in the country. Upgrading of the existing basic and post-basic nursing schools to degree-awarding institutions in Nigeria is a way-forward to solving this inequality problem and Nigeria teaching hospitals are in vantage position for this project due to the already existing supportive structure and manpower in those hospitals. What the nurse trainers and the stakeholders of the teaching hospitals may hold for or against the upgrading is a determining factor for the upgrading project, but that is not clear and has not been investigated in Nigeria. The study investigated the perception of nurse trainers and stakeholders of teaching hospitals in Enugu State of Nigeria on the obstacles and ways-forward to upgrading nursing schools to degree-awarding institutions in Nigeria. The study specifically elicited what the subjects may view as obstacles to upgrading basic and post-basic nursing schools to degree-awarding institutions in Nigeria and ascertained their suggestions on the possible ways of overcoming the obstacles. By utilizing cross-sectional descriptive design and a purposive sampling procedure, 78 accessible subjects out of a total population of 87 were used for the study. The generated data from the subjects were analyzed using frequencies, percentages and mean for the research questions and Pearson’s chi-square for the hypotheses, with the aid of Statistical Package for Social Sciences Version 20.0. The result showed that lack of extant policy, fund, and disunity among policy makers and stakeholders of nursing profession are the main obstacles to the upgrading. However, the respondents did not see items like: stakeholders and nurse trainers of basic and post-basic schools of nursing; fear of admitting and producing poor quality nurses; and so forth, as obstacles to the upgrading project. Institution of the upgrading policy by Nursing and Midwifery Council of Nigeria, funding, awareness creation for the upgrading and unison among policy makers and stakeholders of nursing profession are the major possible ways to overcome the obstacles. The difference in the subjects’ perceptions between the two hospitals was found to be statistically insignificant (p > 0.05). It is recommended that the policy makers and stakeholders of nursing in Nigeria should unite and liaise with Federal Ministries of Health and Education for modalities and actualization of upgrading nursing schools to degree-awarding institutions in Nigeria.

Keywords: nurse trainers, obstacles, perception, stakeholders, teaching hospital, upgrading basic nursing schools, ways-forward

Procedia PDF Downloads 144

Authors: George Eduful, Ebenezer A. Jackson, Kingsford A. Atanga

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This paper investigates the impacts of cable length and capacity of transformer on ferroresonant overvoltage in cable-fed transformers. The study was conducted by simulation using the EMTP RV. Results show that ferroresonance can cause dangerous overvoltages ranging from 2 to 5 per unit. These overvoltages impose stress on insulations of transformers and cables and subsequently result in system failures. Undertaking Basic Multiple Regression Analysis (BMR) on the results obtained, a statistical model was obtained in terms of cable length and transformer capacity. The model is useful for ferroresonant prediction and control in cable-fed transformers.

Keywords: ferroresonance, cable-fed transformers, EMTP RV, regression analysis

Procedia PDF Downloads 533

Authors: Mahesh Kothari, K. D. Gharde

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The ANN and fuzzy logic (FL) models were developed to predict the runoff and sediment yield for catchment of Kal river, India using 21 years (1991 to 2011) rainfall and other hydrological data (evaporation, temperature and streamflow lag by one and two day) and 7 years data for sediment yield modelling. The ANN model performance improved with increasing the input vectors. The fuzzy logic model was performing with R value more than 0.95 during developmental stage and validation stage. The comparatively FL model found to be performing well to ANN in prediction of runoff and sediment yield for Kal river.

Keywords: transferred function, sigmoid, backpropagation, membership function, defuzzification

Procedia PDF Downloads 569

Authors: Yoshio Kurosawa, Takao Yamaguchi

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High frequency automotive interior noise above 500 Hz considerably affects automotive passenger comfort. To reduce this noise, sound insulation material is often laminated on body panels or interior trim panels. For a more effective noise reduction, the sound reduction properties of this laminated structure need to be estimated. We have developed a new calculate tool that can roughly calculate the sound absorption and insulation properties of laminate structure and handy for designers. In this report, the outline of this tool and an analysis example applied to floor mat are introduced.

Keywords: automobile, acoustics, porous material, transfer matrix method

Procedia PDF Downloads 509

Authors: Rodolfo Alfonso, David Alonso, Albin Garcia, Jose Luis Alonso

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Recently a new kilovoltage radiotherapy unit model Xstrahl 200 - donated to the INOR´s Department of Radiotherapy (DR-INOR) in the framework of a IAEA's technical cooperation project- has been commissioned. This unit is able to treat shallow and low deep laying lesions, as it provides 8 discrete beam qualities, from 40 to 200 kV. As part of the patient-specific quality assurance program established at DR-INOR for external beam radiotherapy, it has been recommended to implement in vivo dose measurements (IVD), as they allow effectively discovering eventual errors or failures in the radiotherapy process. For that purpose a radio-photoluminescence (RPL) dosimetry system, model XXX, -also donated to DR-INOR by the same IAEA project- has been studied and commissioned. Main dosimetric parameters of the RPL system, such as reproducibility, linearity, and filed size influence were assessed. In a similar way, the response of radiochromic EBT3 type film was investigated for purposes of IVD. Both systems were calibrated in terms of entrance surface dose. Results of the dosimetric commissioning of RPL and EBT3 for IVD, and their pre-clinical implementation through end-to-end test cases are presented. The RPL dosimetry seems more recommendable for hyper-fractionated schemes with larger fields and curved patient contours, as those in chest wall irradiations, where the use of more than one dosimeter could be required. The radiochromic system involves smaller corrections with field size, but it sensibility is lower; hence it is more adequate for hypo-fractionated treatments with smaller fields.

Keywords: glass dosimetry, in vivo dosimetry, kilovotage radiotherapy, radiochromic dosimetry

Procedia PDF Downloads 398

Authors: Issam Jebreen, Eman Al-Qbelat

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Outsourcing software development projects can be challenging, and there are several common challenges that organizations face. A study was conducted with a sample of 46 papers on outsourcing challenges, and the results show that there are several common challenges faced by organizations when outsourcing software development projects. Poor outsourcing relationship was identified as the most significant challenge, with 35% of the papers referencing it. Lack of quality was the second most significant challenge, with 33% of the papers referencing it. Language and cultural differences were the third most significant challenge, with 24% of the papers referencing it. Non-competitive price was another challenge faced by organizations, with 21% of the papers referencing it. Poor coordination and communication were also identified as a challenge, with 21% of the papers referencing it. Opportunistic behavior, lack of contract negotiation, inadequate user involvement, and constraints due to time zone were also challenges faced by organizations. Other challenges faced by organizations included poor project management, lack of technical capabilities, vendor employee high turnover, poor requirement specification, IPR issues, poor management of budget, schedule, and delay, geopolitical and country instability, the difference in development methodologies, failure to manage end-user expectations, and poor monitoring and control. In conclusion, outsourcing software development projects can be challenging, but organizations can mitigate these challenges by selecting the right outsourcing partner, having a well-defined contract and clear communication, having a clear understanding of the requirements, and implementing effective project management practices.

Keywords: software outsourcing, vendor, outsourcing challenges, quality model, continent, country, global outsourcing, IT workforce outsourcing.

Procedia PDF Downloads 89

Authors: John Kabuba

Abstract:

The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ion-exchange.

Keywords: clinoptilolite, loading, modeling, neural network

Procedia PDF Downloads 415