Search results for: reduce undesirable incidents

Authors: Isiaka Akinwale, Tolulope Babatunde, Oladepo Sowemimo

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A cross-sectional study was conducted between March and April, 2016 among pre-school and school-aged children in two peri-urban communities in Osun State, Southwest Nigeria. Urine samples were collected from the pre-school and school-aged children, tested for microhaematuria using reagent strips, processed and examined for Schistosoma haematobium ova. Out of 274 pupils examined, 132 (48.2%) had infection, with no statistically significant difference (P > 0.05) in infection between male (48.6%) and female pupils (47.6%). The prevalence of infection increases significantly with age (P < 0.05), with the peak (93.3%) of infection recorded in pupils aged 15 to 16 years and the lowest infection (10.0%) in pupils aged 3 to 4 years. There was no statistically significant association (P > 0.05) between intensity in male pupils (156.0 ± 34.5/10 ml) and female pupils (141.7 ± 29.5/10 ml). The prevalence of pupils with microhaematuria was 65.0% and it increased significantly with age (P < 0.001). The conclusion drawn from the study is that to reduce the transmission of S. haematobium in endemic communities, health education and provision of potable water are advocated.

Keywords: Schistosoma haematobium, microhaeamturia, prevalence, urinary schistosomiasis, school aged children, Nigeria

Procedia PDF Downloads 425

Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

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A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: bistatic radar cross section, passive radar, propagation losses, radar coverage

Procedia PDF Downloads 336

Authors: Gholamreza Momenzadeh, Forough Nematolahi

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The Extended Enterprise Resource Planning (ERPII) system usually requires massive amounts of storage space, powerful servers, and large upfront and ongoing investments to purchase and manage the software and the related hardware which are not affordable for organizations. In recent decades, organizations prefer to adapt their business structures with new technologies for remaining competitive in the world economy. Therefore, cloud computing (which is one of the tools of information technology (IT)) is a modern system that reveals the next-generation application architecture. Also, cloud computing has had some advantages that reduce costs in many ways such as: lower upfront costs for all computing infrastructure and lower cost of maintaining and supporting. On the other hand, traditional ERPII is not responding for huge amounts of data and relations between the organizations. In this study, based on a literature study, ERPII is investigated in the context of cloud computing where the organizations operate more efficiently. Also, ERPII conditions have a response to needs of organizations in large amounts of data and relations between the organizations.

Keywords: extended enterprise resource planning, cloud computing, business process, enterprise information integration

Procedia PDF Downloads 222

Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

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With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation, pressure drop

Procedia PDF Downloads 171

Authors: Ali Abdullah Albezaghi

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This article aims to introduce a conceptual framework that can facilitate investigations concerning the role of risk management practices in the relationship between construction risks and the construction project's performance. This article is structured based on the extant literature; it reviews theoretical perspectives, highlights the gaps, and illustrates the significance of developing a framework of suggested relationships. Despite growing interest in the role of risks in construction project performance, previous studies have paid little attention to investigating the moderating role of risk management practices on the risk-performance link. This has left researchers and construction project managers with minimal information to explain the conditions under which risk management practices can reduce the impact of project-related risks and improve performance. In this context, this article suggests a viable research model with propositions that assess risk-performance relationships and discusses the potential moderating effects on the domain relationship. This paper adds to the risk management literature by focusing on risk variables that directly impact performance. Further, it also considers the moderating role of risk management practices in such relationships.

Keywords: risk management practices, external risks, internal risks, project risks, project performance

Procedia PDF Downloads 137

Authors: Yen-Ting Chiu, Chia-Ying Lin, Pei-Hsuan Ho

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New technologies can help solve the problem of labor shortage and the decline of birthrate. Technologies can improve human’s life and reduce the burden on the staff and bring convenience to people. That’s why unmanned retail store X-Store was established in Taiwan to create more valuable services and shopping experiences based on smart retailing. The purpose of this study is to examine the impact of unmanned stores, X-Store, on customers’ behavioral intentions. It uses the Unified theory of acceptance and use of technology (UTAUT) model as a basis and adds a perceived value factor to explain customer willingness to use the X-Store. In addition, the study further divided the sample into gender and age groups to compare behavioral differences between different groups. The study collected 214 valid questionnaires through online questionnaires. Using SPSS as a statistical analysis tool, the results of the study show that effort expectancy, social influence, facilitating conditions, and perceived value have a significant impact on behavioral intention to use X-Store. However, performance expectancy is not significant. This research concludes with managerial implications and suggestions for retail practitioners.

Keywords: perceived value, smart retailing, unmanned store, UTAUT, X-Store

Procedia PDF Downloads 90

Authors: Mohammad Y. Badiee, Saeed Golestani, Mir Saman Pishvaee

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In recent years consumers and governments have been pushing companies to design their activities in such a way as to reduce negative environmental impacts by producing renewable product or threat free disposal policy more and more. It is therefore important to focus more accurate to the optimization of various aspect of total supply chain. Modeling a supply chain can be a challenging process due to the fact that there are a large number of factors that need to be considered in the model. The use of multi-objective optimization can lead to overcome those problems since more information is used when designing the model. Uncertainty is inevitable in real world. Considering uncertainty on parameters in addition to use multi-objectives are ways to give more flexibility to the decision making process since the process can take into account much more constraints and requirements. In this paper we demonstrate a stochastic scenario based robust model to cope with uncertainty in a closed-loop multi-objective supply chain. By applying the proposed model in a real world case, the power of proposed model in handling data uncertainty is shown.

Keywords: supply chain management, closed-loop supply chain, multi-objective optimization, goal programming, uncertainty, robust optimization

Procedia PDF Downloads 416

Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

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The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

Procedia PDF Downloads 307

Authors: Mahshid Hatamzad, Geanette Polanco

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Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.

Keywords: environmental impacts, DEA, risk and safety, WRM

Procedia PDF Downloads 118

Authors: Rute Faria, Digo Moraes, Amanda Santos, Dione Morais, Maria Sartori

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Seed vigor is a fundamental component for the good performance of the entire soybean production process. Seeds with mechanical damage at harvest time will be more susceptible to fungal and insect attack during storage, which will invariably reduce their vigor to the field, compromising uniformity and final stand performance. Harvesters, even the most modern ones, when not properly regulated or operated, can cause irreversible damages to the seeds, compromising even their commercialization. Therefore, the control of an efficient harvest is necessary in order to guarantee a good quality final product. In this work, the damage caused by two different harvesters (one rented, and another one) was evaluated, traveling in two speeds (4 and 8 km / h). The design was completely randomized in 2 x 2 factorial, with four replications. To evaluate the physiological quality seed germination and vigor tests were carried out over a period of six months. A multivariate analysis of Principal Components (PCA) and clustering allowed us to verify that the leased machine had better performance in the incidence of immediate damages in the seeds, but after a storage period of 6 months the vigor of these seeds reduced more than own machine evidencing that such a machine would bring more damages to the seeds.

Keywords: Glycine max (L.), cluster analysis, PCA, vigor

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Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

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Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

Procedia PDF Downloads 93

Authors: Kouzi Katia

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This paper proposes a Direct Torque Control (DTC) algorithm of dual Stator Induction Motor (DSIM) drive using two approach intelligent techniques: Artificial Neural Network (ANN) approach replaces the switching table selector block of conventional DTC and Mamdani Fuzzy Logic controller (FLC) is used for stator resistance estimation. The fuzzy estimation method is based on an online stator resistance correction through the variations of stator current estimation error and its variation. The fuzzy logic controller gives the future stator resistance increment at the output. The main advantage of suggested algorithm control is to reduce the hardware complexity of conventional selectors, to avoid the drive instability that may occur in certain situation and ensure the tracking of the actual of the stator resistance. The effectiveness of the technique and the improvement of the whole system performance are proved by results.

Keywords: artificial neural network, direct torque control, dual stator induction motor, fuzzy logic estimator, switching table

Procedia PDF Downloads 345

Authors: Obasi Igwe Oscar, Udokure Ubong James, Echebiri Raphael Ndubuisi

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The study examined the determinants of the welfare of itinerant palm oil marketers in Akwa Ibom State, Nigeria. Multistage sampling techniques were adopted to select 120 itinerant palm oil marketers for the study. Primary data were obtained using a structured questionnaire. Data were analyzed using the cost and returns formula and multiple regression model. Results showed that itinerant palm oil marketing was profitable and 57.39% efficient. The respondents' monthly expenditure of N111,787.90 on food and non-food items indicated that they live above the extreme poverty threshold of $2.15 per person per day, with a daily spending of over $2. Net income (P<0.05), age (P<0.01), educational level (P<0.01), household size (P<0.01), credit amount (P<0.01), market information (P<0.05), amount of tax paid (P<0.01) and the level of market participation (P<0.05) were the significant determinants of the welfare of itinerant traders in the study area. The study recommended that government and non-governmental organizations should make available marketing facilities and enhance transportation networks to reduce inefficiencies and lower transaction costs for itinerant palm oil traders in Akwa Ibom state.

Keywords: determinants, welfare, itinerant, palm oil, marketers

Procedia PDF Downloads 30

Authors: Okay Gunes

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Unsatisfactory experiences due to an information shortage regarding the future pay-offs of actual choices, yield satisficing decision-making. This research will examine, for the first time in the literature, the motivation behind suboptimal decisions due to uncertainty by subjecting Adam Smith’s and Jeremy Bentham’s assumptions about the nature of the actions that lead to satisficing behavior, in order to clarify the theoretical background of a “consumption-based satisfactory time” concept. The contribution of this paper with respect to the existing literature is threefold: Firstly, it is showed in this paper that Adam Smith’s uncertainty is related to the problem of the constancy of ideas and not related directly to beliefs. Secondly, possessions, as in Jeremy Bentham’s oeuvre, are assumed to be just as pleasing, as protecting and improving the actual or expected quality of life, so long as they reduce any displeasure due to the undesired outcomes of uncertainty. Finally, each consumption decision incurs its own satisfactory time period, owed to not feeling hungry, being healthy, not having transportation…etc. This reveals that the level of satisfaction is indeed a behavioral phenomenon where its value would depend on the simultaneous satisfaction derived from all activities.

Keywords: decision-making, idea and belief, satisficing, uncertainty

Procedia PDF Downloads 286

Authors: Nidhin Dani Abraham, T. K. Sri Shilpa

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Asset liability management is an important aspect in banking business. Moreover, the today’s banking is based on BASEL III which strictly regulates on the counterparty default. This paper focuses on prediction and analysis of counter party default risk, which is a type of risk occurs when the customers fail to repay the amount back to the lender (bank or any financial institutions). This paper proposes an approach to reduce the counterparty risk occurring in the financial institutions using an appropriate data mining technique and thus predicts the occurrence of NPA. It also helps in asset building and restructuring quality. Liability management is very important to carry out banking business. To know and analyze the depth of liability of bank, a suitable technique is required. For that a data mining technique is being used to predict the dormant behaviour of various deposit bank customers. Various models are implemented and the results are analyzed of saving bank deposit customers. All these data are cleaned using data cleansing approach from the bank data warehouse.

Keywords: data mining, asset liability management, BASEL III, banking

Procedia PDF Downloads 553

Authors: Ming-Hwi Yao, Su-Szu Yang

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Typhoons are one of the major types of disasters that affect Taiwan each year and that cause severe damage to agriculture. Indeed, the damage exacted during a typical typhoon season can be up to $1 billion, and is responsible for nearly 75% of yearly agricultural losses. However, there is no consensus on how to reduce the damage caused by the strong winds and heavy precipitation engendered by typhoons. One suggestion is the use of windbreak nets, which are a low-cost and easy-to-use disaster mitigation strategy for crop production. In the present study, we conducted an evaluation to determine the optimal conditions of a windbreak net by using a computational fluid dynamics (CFD) model. This model may be used as a reference for crop protection. The results showed that CFD simulation validated windbreak nets of different mesh sizes and heights in the experimental area; thus, CFD is an efficient tool for evaluating the effectiveness of windbreak nets. Specifically, the effective wind protection length and height were found to be 6 and 1.3 times the length and height of the windbreak net, respectively. During a real typhoon, maximum wind gusts of 18 m s-1 can be reduced to 4 m s-1 by using a windbreak net that has a 70% blocking rate. In short, windbreak nets are significantly effective in protecting typhoon-affected areas.

Keywords: computational fluid dynamics, disaster, typhoon, windbreak net

Procedia PDF Downloads 191

Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

Procedia PDF Downloads 97

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 204

Authors: Didem Can

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Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

Procedia PDF Downloads 237

Authors: Shih-Hao Chen, Chi-Wai Chow

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Multiple-input and multiple-output (MIMO) scheme can extend the transmission capacity for the light-emitting-diode (LED) visible light communication (VLC) system. The MIMO VLC system using the popular mobile-phone camera as the optical receiver (Rx) to receive MIMO signal from n x n Red-Green-Blue (RGB) LED array is desirable. The key step of decoding the received RGB LED array signals is detecting the direction of received array signals. If the LED transmitter (Tx) is rotated, the signal may not be received correctly and cause an error in the received signal. In this work, we propose and demonstrate a novel hierarchical transmission scheme which can reduce the computation complexity of rotation detection in LED array VLC system. We use the n x n RGB LED array as the MIMO Tx. A novel two dimension Hadamard coding scheme is proposed and demonstrated. The detection correction rate is above 95% in the indoor usage distance. Experimental results confirm the feasibility of the proposed scheme.

Keywords: Visible Light Communication (VLC), Multiple-input and multiple-output (MIMO), Red-Green-Blue (RGB), Hadamard coding scheme

Procedia PDF Downloads 419

Authors: A. M. Attalla, A. F. lbrahim, Laila Y. Mostaffa

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This study was conducted during three seasons 2010, 2011 and 2012 on Zahhloul date palm cultivar grown in calcareous soil, Alexandria governorate, Egypt. The palms received recommended dose of mineral N only or plus different rates of organic N with or without bio fertilizer to study the effect of such treatments on date palm yield and fruit nitrate and nitrite content due to its negative influence on human, animal and environment. The obtained results clarified that all used treatments of organic and bio fertilizers were effective in improving date palm yield and decreased fruit content of NO2 and NO3 in comparison with 100 % mineral N. It was also noticed that combined treatments of 50 % mineral N + 50 % organic manure with bio fertilizer is the superior treatments for increasing the values of yield and decreasing its content of NO2 and NO3. Hence, it could be concluded that, minimizing the use of chemical nitrogen fertilizer to half of recommended dose through addition of 50 % mineral N + 50 % organic manure with bio fertilizer and also, the utilization of organic and bio fertilizers is considered as a promising alternative for chemical fertilizers to avoid pollution and reduce the costs of mineral fertilizers.

Keywords: organic and bio fertilizers, mineral fertilizer, nitrate, nitrite, zaghloul date palm cv

Procedia PDF Downloads 449

Authors: Nneka Nkechi Uchegbu, Temitope Omolayo Fasuan

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This study investigated how to reduce bio-compounds and amino acids in V. amygdalina leaf during processing as a functional food ingredient. Fresh V. amygdalina leaf was processed using thermal oil-aqueous mixtures (soybean oil: aqueous and palm oil: aqueous) at 1:40 and 130 (v/v), respectively. Results indicated that the hot soybean oil-aqueous mixture was the most effective in preserving the bio-compounds and amino acids with retention potentials of 80.95% of the bio-compounds at the rate of 90-100%. Hot palm oil-aqueous mixture retained 61.90% of the bio-compounds at the rate of 90-100% and hot aqueous retained 9.52% of the bio-compounds at the same rate. During the debittering process, seven new bio-compounds were formed in the leaves treated with hot soybean oil-aqueous mixture, six in palm oil-aqueous mixture, and only four in hot aqueous leaves. The bio-compounds in the treated leaves have potential functions as antitumor, antioxidants, antihistaminic, anti-ovarian cancer, anti-inflammatory, antiarthritic, hepatoprotective, antihistaminic, haemolytic 5-α reductase inhibitor, nt, immune-stimulant, diuretic, antiandrogenic, and anaemiagenic. Alkaloids and polyphenols were retained at the rate of 81.34-98.50% using oil: aqueous mixture while aqueous recorded the rate of 33.47-41.46%. Most of the essential amino acids were retained at a rate above 90% through the aid of oil. The process is scalable and could be employed for domestic and industrial applications.

Keywords: V. amygdalina leaf, bio-compounds, oil-aqueous mixture, amino acids

Procedia PDF Downloads 146

Authors: Festus Adedoyin, Nana Mbeah Otoo, Sofia Meacham

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Hypertension is one of the main health issues in Ghana, where prevalence is higher in rural than in urban areas. This is due to the challenges rural areas have in accessing technology and healthcare services for hypertension control. This study's goal is to create a digital healthcare solution to alleviate this inequality. Through an analysis of current technology and problems, using the ring onion methodology, the study determined the needs for the intervention and evaluated healthcare disparities. An online application with teleconsultation capabilities, reminder mechanisms, and clinical decision support is part of the suggested solution. In outlying areas, mobile clinics in containers with the required equipment will be established. Heuristic evaluation and think-aloud sessions were used to assess the prototype's usability and navigational problems. This study highlights the need to develop digital health interventions to help manage hypertension in rural locations and decrease healthcare disparities. To develop and improve digital healthcare solutions for rural areas worldwide and in Ghana, this study might be used as a tool for future research.

Keywords: digital health, health inequalities, hypertension management, rural areas

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Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

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Model transformation, as a pivotal aspect of Model-driven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: cross-domain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons

Procedia PDF Downloads 395

Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

Procedia PDF Downloads 85

Authors: Benny Alexander, Ikhlashia N. Fadhilah, Muhammad R. Pasha, Michelle Julia, Anne Z. Syahrial

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Brake shoe is a component that serves to reduce speed or stop the train's speed by utilizing the friction force. Generally, the material used as a brake shoe is cast iron, where cast iron itself is a heavy, expensive, and easily worn material. Aluminum matrix composites are one of candidates for the cast iron replacement material as the basic material for brake shoe. The matrix in the composite used is Aluminum AC4B. Reinforcement used in aluminum matrix composites is nano-alumina, where the use of nano-alumina of 0.25%, 0.3%, 0.35%, 0.4%, and 0.5% volume fraction will be tested. The sample is made using the stir casting method; then, it will be tested mechanically. The use of nano-alumina as a reinforcement will increase the strength of the matrix. SEM (scanning electron microscopy) testing is used to test the distribution of reinforcing particles due to stirring. Therefore, the addition of nano-alumina will improve AC4B aluminum matrix composites.

Keywords: aluminium matrix composites, brake shoe application, stir casting, nano-alumina

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Authors: Yousefali Ziari, Hamidreza Joudaki

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Humans have regularly been interacting with their environment, and have a close relation with their environment. House as a shelter which protects us against hot and cold weather and the other climatic occurrences in the environment has a close relation with climate. Before human could have access to the fossil fuels, preparing the comfort for the house was done by adjusting the building according to the climate conditions, and the help of natural resources. However after the man could access the fossil fuel, this way was forgotten, and caused much use of energy for heating & cooling. This research is trying to find some methods for designing suitable building that create comfort fitting with the zone by studying the climate condition of Arak city and as a result to find a way to reduce the use of energy and improving the design. So for the aim of this research we have used the statistics and information such as temperature, rain, wind and the approximate moisture from a period of 40 years from synoptic station of Arak. After specifying the climate of Arak by the use of effective temperature, Ulgi, Guni, Mahani and Ovenz indicator, we investigated the climate comfort conditions and the harmonious architecture with the climate and then some suggestion was given according to the climate situation of each month of the year and quality of human comfort according to this indicators.

Keywords: climate, architecture, traditional and modern architecture, comfort indicator, Arak city

Procedia PDF Downloads 479

Authors: Norhayati Mat Wajid, Abdul Murad Zainal Abidin, Faiz Fadzil, Mohd Yusof Aizad Mukhtar

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One of the areas that present an opportunity to reduce the national carbon emission is the energy management of public buildings. To our present knowledge, there is no easy-to-use and centralized mechanism that enables the government to monitor the overall energy performance, as well as the carbon footprint, of Malaysia’s public buildings. Therefore, the Public Works Department Malaysia, or PWD, has developed a web-based energy performance reporting tool called JENOSYS (JKR Energy Online System), which incorporates a database of utility account numbers acquired from the utility service provider for analysis and reporting. For test case purposes, 23 buildings under PWD were selected and monitored for their monthly energy performance (in kWh), carbon emission reduction (in tCO₂eq) and utility cost (in MYR), against the baseline. This paper demonstrates the simplicity with which buildings without energy metering can be monitored centrally and the benefits that can be accrued by the government in terms of building energy disclosure and concludes with the recommendation of expanding the system to all the public buildings in Malaysia.

Keywords: energy-efficient buildings, energy management systems, government buildings, JENOSYS

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Authors: Prashant Dhiman, Viranshu Kumar, Pradeep Joshi

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Lot of research is going on to study the effect of cryogenic treatment on materials. Cryogenic treatment is a heat treatment process which is used widely to enhance the mechanical and metallurgical properties of various materials whether the material is ferrous or non ferrous. In almost all ferrous metals, it is found that retained austenite is converted into martensite. Generally deep cryogenic treatment is done using liquid nitrogen having temperature of -195 ℃. The austenite is unstable at this stage and converts into martensite. In non ferrous materials there presents a microcavity and under the action of stress it becomes crack. When this crack propagates, fracture takes place. As the metal contract under low temperature, by doing cryogenic treatment these microcavities will be filled hence increases the soundness of the material. Properties which are enhanced by cryogenic treatment of both ferrous and non ferrous materials are hardness, tensile strength, wear rate, electrical and thermal conductivity, and others. Also there is decrease in residual stress. A large number of manufacturing process (EDM, CNC etc.) are using cryogenic treatment on different tools or workpiece to reduce their wear. In this Review paper the use of cryogenic heat treatment in different manufacturing has been shown along with their advantages.

Keywords: cyrogenic treatment, EDM (Electrical Discharge Machining), CNC (Computer Numeric Control), Mechanical and Metallurgical Properties

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Authors: Somayeh Azizi, Mohammad Hossein Ehsani, Amir Zareidoost

Abstract:

In this research, a technique has been developed to reduce the corrosion rate of magnesium (Mg) metal by creating Zr-Nb thin film coatings. In this regard, thin-film coatings of niobium (Nb) zirconium (Zr) double alloy are applied on pure Mg specimens under different processes conditions, such as the change of the substrate temperature, substrate bias, and coating thickness using the magnetron sputtering method. Then, deposited coatings are analyzed in terms of surface features via field-emission scanning electron microscopy (FE-SEM), thin-layer X-ray diffraction (GI-XRD), energy-dispersive X-ray spectroscopy (EDS), atomic force microscopy (AFM), and corrosion tests. Also, nano-scratch tests were carried out to investigate the adhesion of the thin film. The results showed that the (Zr-Nb) thin films could control the degradation rate of Mg in the simulated body fluid (SBF). The nano-scratch studies depicted that the (Zr-Nb) thin films have a proper adhesion with the Mg substrate. Therefore, this technique could be used to enhance the corrosion resistance of bare Mg and could result in improving the performance of the biodegradable Mg implant for orthopedic applications.

Keywords: (Zr-Nb) thin film, magnetron sputtering, biodegradable Mg, degradation rate

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