Search results for: premises selection

Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng

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Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.

Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm

Procedia PDF Downloads 180

Authors: Doo Ki Lee, Kumaresh Selvakumar, Man Young Kim, In Jae Song

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The widespread utilization of mixer in selective catalytic reduction (SCR) system marks a remarkable advantage in diesel engines. In the automotive selective catalytic reduction (SCR) system, the de-NOX efficiency can be improved by highly uniform flow with effective turbulent mixing. In this paper, the exhaust pipe is complemented with the swirling mixers of three different vane angles installed at the upstream of the SCR reactor. The attributes of the mixer are established by the variation in flow behavior followed by the drawback owing to the absence of mixer. In particular, the information pertaining to the selection of proper static mixer is provided based on the correlation between the uniformity index (UI) and the pressure drop. The uniform distribution of the flow at the entrance of the SCR reactor aids to determine the configuration which gives high mixing performance and comprehend the function of the mixer.

Keywords: pressure drop, selective catalytic reduction, static mixer, turbulent mixing, uniformity index

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Authors: Kenichiro Hida, Shin-Ichi Kuribayashi

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NFV-based network implements a variety of network functions with software on general-purpose servers, and this allows the network operator to select any capabilities and locations of network functions without any physical constraints. In this paper, we evaluate the influence of the maximum tolerable network delay on the virtual routing function deployment guidelines which the authors proposed previously. Our evaluation results have revealed the following: (1) the more the maximum tolerable network delay condition becomes severe, the more the number of areas where the route selection function is installed increases and the total network cost increases, (2) the higher the routing function cost relative to the circuit bandwidth cost, the increase ratio of total network cost becomes larger according to the maximum tolerable network delay condition.

Keywords: NFV (Network Functions Virtualization), resource allocation, virtual routing function, minimum total network cost

Procedia PDF Downloads 237

Authors: Fakhreddin El Wali Elalaoui, Maatouk Mustapha

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The problem of global climate change isbecoming more and more serious. Therefore, there is a growing interest in renewable energy sources to minimize the impact of this phenomenon. Environmental policies are changing in different countries, including Morocco, with a greater focus on the integration and development of renewable energy projects. The purpose of this paper is to evaluate the potential of solar power plants in Morocco based on two technologies: concentrated solar power (CSP) and photovoltaics (PV). In order to perform an accurate search, we must follow a certain method to select the correct criteria. Four selection criteria were retained: climate, topography, location, and water resources. AnalyticHierarchy Process (AHP) was used to calculate the weight/importance of each criterion. Once obtained, weights are applied to the map for each criterion to produce a final ranking that ranks regions according to their potential. The results show that Morocco has strong potential for both technologies, especially in the southern region. Finally, this work is the first in the field to include the whole of Morocco in the study area.

Keywords: PV, Csp, solar energy, GIS

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Authors: Angelina Anani, Ignacio Ortiz Flores, Haitao Li

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The use of underground mining methods have increased significantly over the past decades. This increase has also been spared on by several mines transitioning from surface to underground mining. However, determining the transition depth can be a challenging task, especially when coupled with production schedule optimization. Several researchers have simplified the problem by excluding operational features relevant to production schedule optimization. Our research objective is to investigate the extent to which operational features of transition mines accounted for affect the optimal production schedule. We also provide a framework for factors to consider in production schedule optimization for transition mines. An integrated mixed-integer linear programming (MILP) model is developed that maximizes the NPV as a function of production schedule and transition depth. A case study is performed to validate the model, with a comparative sensitivity analysis to obtain operational insights.

Keywords: underground mining, transition mines, mixed-integer linear programming, production schedule

Procedia PDF Downloads 155

Authors: Shosh Shahrabani, Sharon Teitler-Regev, Helena Desivilya Syna, Fotini Voulgaris, Evangelos Tsoukatos, Vitor Ambrosio, Sandra M. Correia Loureiro

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International crises that affect tourism, such as terror attacks, political unrest, and economic crises have become more frequent, and their influence has become broader. The influence of such extreme events depends on their salience in the tourists' awareness. Hence, it is important to understand the mechanisms underlying tourists' selection of travel destinations, especially their perceptions of crisis-related events and the impact of the sociopolitical and economic context in their countries of origin. The current study examined how the socio-political and economic context in the home countries of potential young tourists affected their selection of travel destinations. The objective was to elucidate how the salience of various crises (economic and political) in the tourists' perceptions, due to their experiences at home, color their construal of destinations affected by similar hazards and influence their travel intentions. The study focused on student tourists from Israel, Greece, and Portugal. Today about a fifth of international tourism is based on young people, especially students. These countries were chosen since Greece and Portugal are in the midst of economic crises. In addition, Greece and Portugal have experienced political instability, while Israel has security-related problems (including terrorist incidents). In 2013, a total of 648 students, responded to a questionnaire that included questions concerning attitudes and risk perceptions regarding travel to destinations with various risk hazards as well as socio-demographic details. The results indicate that over half of the Israelis intend to visit Greece or Portugal. The majority of the Portuguese intend to visit Greece, while less than a third of them intend to visit Israel. About half of the Greeks intend to visit Portugal, and most of them do not intend to visit Israel. The results indicate that greater perceived importance of economic crises mitigates the intention to travel to destinations with economic crises for tourists from origin countries that are also marked by economic crises, such as Greece and Portugal. However, for tourists from Israel, a country with a relatively stable economy, issues related to the economy barely affect their intention to travel to the other two countries. The findings also suggest that Greeks and Portuguese who are highly concerned about political unrest are unlikely to select Israel as a tourist destination. In addition, strong apprehension regarding terrorism impedes the intention to travel to destinations marked by terrorist incidents, such as Israel. The current research contributes to the existing literature by highlighting the impact of travelers' personal previous experience with crisis on their risk perceptions and in turn on their intentions to travel to countries with similar risks. Therefore, in a world where such incidents are on the rise, understanding tourists' risk perceptions and behavior and the factors influencing their destination-related decisions are crucial for countries that wish to increase the numbers of incoming tourists.

Keywords: economic crises, political instability, risk perception, young tourists

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Authors: Manoj Kumar, Preeti Goel

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National Capital Region of India is one of the most populous urban agglomerations in the world. This region has residents from all the parts of India, and their shopping behaviors are quite different. The region also has the substantial population of people from other countries. Due to high purchasing power of a large number of people, NCR is one the major markets for luxury fashion brands. Marketers of luxury fashion brands keep on adding innovative features to their products to attract the buyers. This research is an attempt to understand the major factors which impact the brand selection for these brands and other buying decisions like purchasing time and location. The research is based on primary data collected from potential buyers of luxury fashion brands and the people involved in the marketing of these brands in various roles. The research has tried to identify the relative strength of various factors on the shopping behavior for these brands.

Keywords: luxury brands, fashion, shopping, National Capital Region (NCR)

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Authors: Manvender Singh

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Temperature is one of the most important climatic parameter for explaining the geographic distribution of ectothermic species. Empirical investigations on norms of the reaction according to developmental temperatures are helpful in analyzing the adapture capacity of a species which may be related to its ecological niche. In the present investigation, we have compared the effects of developmental temperatures on fecundity, hatchability, viability, and duration of development in five natural populations of Drosophila bipectinata along the latitudinal range. The clinal patterns for fecundity, as well as ovariole number, were observed which showed significant positive correlation (r=0.97). Similarly, hatchability and duration of development also revealed a positive correlation with latitude. Hence, suggesting the role of natural selection in maintaining the genetic divergence for life history traits along the north-south transect of the Indian Subcontinent.

Keywords: growth temperature, fecundity, hatchability, viability, duration of development, Drosophila

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Stephanie Wall, Guido Wimmers

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The construction and operation of buildings greatly contribute to environmental degradation through resource and energy consumption and greenhouse gas emissions. The design of the envelope system affects the environmental impact of a building in two major ways; 1) high thermal performance and air tightness can significantly reduce the operational energy of the building and 2) the material selection for the envelope largely impacts the embodied energy of the building. Life cycle assessment (LCA) is a scientific methodology that is used to systematically analyze the environmental load of processes or products, such as buildings, over their life. The paper will discuss the results of a comparative LCA of different envelope designs and the long-term monitoring of the Wood Innovation Research Lab (WIRL); a Passive House (PH), industrial building under construction in Prince George, Canada. The WIRL has a footprint of 30m x 30m on a concrete raft slab foundation and consists of shop space as well as a portion of the building that includes a two-story office/classroom space. The lab building goes beyond what was previously thought possible in regards to energy efficiency of industrial buildings in cold climates due to their large volume to surface ratio, small floor area, and high air change rate, and will be the first PH certified industrial building in Canada. These challenges were mitigated through the envelope design which utilizes solar gains while minimizing overheating, reduces thermal bridges with thick (570mm) prefabricated truss walls filled with blown in mineral wool insulation and a concrete slab and roof insulated with EPS rigid insulation. The envelope design results in lower operational and embodied energy when compared to buildings built to local codes or with steel. The LCA conducted using Athena Impact Estimator for Buildings identifies project specific hot spots as well illustrates that for high-efficiency buildings where the operational energy is relatively low; the embodied energy of the material selection becomes a significant design decision as it greatly impacts the overall environmental footprint of the building. The results of the LCA will be reinforced by long-term monitoring of the buildings envelope performance through the installation of temperature and humidity sensors throughout the floor slab, wall and roof panels and through detailed metering of the energy consumption. The data collected from the sensors will also be used to reinforce the results of hygrothermal analysis using WUFI®, a program used to verify the durability of the wall and roof panels. The WIRL provides an opportunity to showcase the use of wood in a high performance envelope of an industrial building and to emphasize the importance of considering the embodied energy of a material in the early stages of design. The results of the LCA will be of interest to leading researchers and scientists committed to finding sustainable solutions for new construction and high-performance buildings.

Keywords: high performance envelope, life cycle assessment, long term monitoring, passive house, prefabricated panels

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Authors: Danilo López, Edwin Rivas, Leyla López

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This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.

Keywords: cognitive radio, base station, best effort, MLPNN, prediction, real time

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Yahya Ibrahim Harande

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The purpose of this study was to identify the journals that published articles on malaria disease in Africa and to determine the core of productive journals from the identified journals. The data for the study were culled out from African Index Medicus (AIM) database. A total of 529 articles was gathered from 115 journal titles from 1979-2011. In order to obtain the core of productive journals, Bradford`s law was applied to the collected data. Five journal titles were identified and determined as core journals. The data used for the study was analyzed and that, the subject matter used, Malaria was in conformity with the Bradford`s law. On the aspect dispersion of the literature, English was found to be the dominant language of the journals. (80.9%) followed by French (16.5%). Followed by Portuguese (1.7%) and German (0.9%). Recommendation is hereby proposed for the medical libraries to acquire these five journals that constitute the core in malaria literature for the use of their clients. It could also help in streamlining their acquision and selection exercises. More researches in the subject area using Bibliometrics approaches are hereby recommended.

Keywords: productive journals, malaria disease literature, Bradford`s law, core journals, African scholars

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Authors: Gelila Tamyalew, Asres Abitie

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Community Pharmacists (CPs) have a significant part in consumer choice in the rational use of LMPPs. The opinion of pharmacists regarding branded and generic medications can offer a perception of the potential obstacles that might have to be overcome to advance generic medicine utilization. Many factors affect CPs' attitudes negatively toward LMPPs. Therefore, the current study assessed factors that can affect CPs' attitudes toward LMPPs. In the regression analysis of variables, three variables were associated with CPs' attitudes toward LMPPs. These are; maximum educational status, professional status, and year of experience in community pharmacy practice. Moreover, lack of belief in LMPPs, substitution agreement with the prescriber, cost-effectiveness of LMPPs, and consumer preference/demand were the most influencing reasons for the selection of LMPPs. In conclusion, the attitude of CPs seems suboptimal that requires an intervention to optimize LMPP utilization.

Keywords: locally manufactured pharmaceutical products, attitude, community pharmacist, Ethiopia

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Authors: Muhammad Yousaf Sadiq

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The complexity arises in defining the construction quality due to its perception, based on inherent market conditions and their requirements, the diversified stakeholders itself and their desired output. An quantitative survey based approach was adopted in this constructive study. A questionnaire-based survey was conducted for the assessment of construction Quality perception and expectations in the context of quality improvement technique. The survey feedback of professionals of the leading construction organizations/companies of Pakistan construction industry were analyzed. The financial capacity, organizational structure, and construction experience of the construction firms formed basis for their selection. The quality perception was found to be project-scope-oriented and considered as an excess cost for a construction project. Any quality improvement technique was expected to maximize the profit for the employer, by improving the productivity in a construction project. The study is beneficial for the construction professionals to assess the prevailing construction quality perception and the expectations from implementation of any quality improvement technique in construction projects.

Keywords: construction quality, expectation, improvement, perception

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Authors: Tian Lan, Yixiang Wang, Wenxin Tai, Yilan Lyu, Zufeng Wu

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The monaural speech enhancement task in the time-frequencydomain has a myriad of approaches, with the stacked con-volutional neural network (CNN) demonstrating superiorability in feature extraction and selection. However, usingstacked single convolutions method limits feature represen-tation capability and generalization ability. In order to solvethe aforementioned problem, we propose an attention-basedadaptive convolutional network that integrates the multi-scale convolutional operations into a operation-specific blockvia input dependent attention to adapt to complex auditoryscenes. In addition, we introduce a two-stage progressivelearning method to enlarge the receptive field without a dra-matic increase in computation burden. We conduct a series ofexperiments based on the TIMIT corpus, and the experimen-tal results prove that our proposed model is better than thestate-of-art models on all metrics.

Keywords: speech enhancement, adaptive convolu-tion, progressive learning, time-frequency domain

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Authors: Anastasia Tsakiridi

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Geographic information systems (GIS) have been utilized in numerous spatial problems, such as site research, land suitability, and demographic analysis. Besides, GIS has been applied in scientific fields like geography, health, and economics. In business studies, GIS has been used to provide insights and spatial perspectives in demographic trends, spending indicators, and network analysis. To date, the information regarding the available usages of GIS in supply chain management (SCM) and how these analyses can benefit businesses is limited. A systematic literature review (SLR) of the last 5-year peer-reviewed academic literature was conducted, aiming to explore the existing usages of GIS in SCM. The searches were performed in 3 databases (Web of Science, ProQuest, and Business Source Premier) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The analysis resulted in 79 papers. The results indicate that the existing GIS applications used in SCM were in the following domains: a) network/ transportation analysis (in 53 of the papers), b) location – allocation site search/ selection (multiple-criteria decision analysis) (in 45 papers), c) spatial analysis (demographic or physical) (in 34 papers), d) combination of GIS and supply chain/network optimization tools (in 32 papers), and e) visualization/ monitoring or building information modeling applications (in 8 papers). An additional categorization of the literature was conducted by examining the usage of GIS in the supply chain (SC) by the business sectors, as indicated by the volume of the papers. The results showed that GIS is mainly being applied in the SC of the biomass biofuel/wood industry (33 papers). Other industries that are currently utilizing GIS in their SC were the logistics industry (22 papers), the humanitarian/emergency/health care sector (10 papers), the food/agro-industry sector (5 papers), the petroleum/ coal/ shale gas sector (3 papers), the faecal sludge sector (2 papers), the recycle and product footprint industry (2 papers), and the construction sector (2 papers). The results were also presented by the geography of the included studies and the GIS software used to provide critical business insights and suggestions for future research. The results showed that research case studies of GIS in SCM were conducted in 26 countries (mainly in the USA) and that the most prominent GIS software provider was the Environmental Systems Research Institute’s ArcGIS (in 51 of the papers). This study is a systematic literature review of the usage of GIS in SCM. The results showed that the GIS capabilities could offer substantial benefits in SCM decision-making by providing key insights to cost minimization, supplier selection, facility location, SC network configuration, and asset management. However, as presented in the results, only eight industries/sectors are currently using GIS in their SCM activities. These findings may offer essential tools to SC managers who seek to optimize the SC activities and/or minimize logistic costs and to consultants and business owners that want to make strategic SC decisions. Furthermore, the findings may be of interest to researchers aiming to investigate unexplored research areas where GIS may improve SCM.

Keywords: supply chain management, logistics, systematic literature review, GIS

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Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

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In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, water temperature, and conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: dissolved oxygen, water quality, predication DO, support vector machine

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Authors: Shakhawan K. Mawlood, Catriona Pickard, Benjamin Pickard

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In summer 2015 the remains of 800 children are among 1,967 bodies were exhumed by archaeologists at St Peter's Burial Ground in Blackburn, Lancashire. One hundred samples from these 19th century ancient bones were selected for DNA analysis. These comprised samples biased for those which prior osteological evidence indicated a potential for microbial infection by Mycobacterium tuberculosis (causing tuberculosis, TB) or Treponema pallidum (causing Syphilis) species, as well a random selection of other bones for which visual inspection suggested good preservation (and, therefore, likely DNA retrieval).They were subject to polymerase chain reaction (PCR) assays aimed at detecting traces of DNA from infecting mycobacteria, with the purpose both of confirming the palaeopathological diagnosis of tuberculosis and determining in individual cases whether disease and death was due to M. tuberculosis or other reasons. Our secondary goal was to determine sex determination and age prediction. The results demonstrated that extraction of vast majority ancient bones DNA samples succeeded.

Keywords: ancient bone, DNA, tuberculosis, age prediction

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Authors: Jianhong Xiang, Hao Xiang, Linyu Wang

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Compressed sensing (CS) has a wide range of applications in sparse signal reconstruction. Aiming at the problems of low recovery accuracy and long reconstruction time of existing reconstruction algorithms in medical imaging, this paper proposes a corrected smoothing L0 algorithm based on compressed sensing (CSL0). First, an approximate hyperbolic tangent function (AHTF) that is more similar to the L0 norm is proposed to approximate the L0 norm. Secondly, in view of the "sawtooth phenomenon" in the steepest descent method and the problem of sensitivity to the initial value selection in the modified Newton method, the use of the steepest descent method and the modified Newton method are jointly optimized to improve the reconstruction accuracy. Finally, the CSL0 algorithm is simulated on various images. The results show that the algorithm proposed in this paper improves the reconstruction accuracy of the test image by 0-0. 98dB.

Keywords: smoothed L0, compressed sensing, image processing, sparse reconstruction

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Authors: Peyman Honarmandi, Mazen Alhirsh

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Banner towing is a major form of advertisement. It consists of a banner showing a logo or a selection of words or letters being towed by an aircraft. Traditionally bush planes have been used to tow banners given their high thrust capabilities; however, with the development of remote-controlled (RC) aircraft, they could be a good replacement as RC planes mitigate the risk of human life and can be easier to operate. This paper studies the best banner design to be towed by an RC aircraft. This is done by conducting wind tunnel testing on an array of banners with different materials and designs. A pull gauge is used to record the drag force during testing, which is then used to calculate the coefficient of drag, Cd. The testing results show that the best banner design would be a hybrid design with a solid and mesh material. The design with the lowest Cd of 0.082 was a half ripstop nylon half polyester mesh design. On the other hand, the design with the highest Cd of 0.305 involved incorporating a tail chute to decrease fluttering.

Keywords: aerodynamics of banner, banner design, banner towing, drag coefficients of banner, RC aircraft banner

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Authors: Paul Henshall, Philip Eames, Roger Moss, Stan Shire, Farid Arya, Trevor Hyde

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Encapsulating the absorber of a flat plate solar thermal collector in vacuum by an enclosure that can be evacuated can result in a significant increase in collector performance and achievable operating temperatures. This is a result of the thermal insulation effectiveness of the vacuum layer surrounding the absorber, as less heat is lost during collector operation. This work describes experimental thermal insulation characterization tests of prototype vacuum flat plate solar thermal collectors that demonstrate the improvement in absorber heat loss coefficients. Furthermore, this work describes the selection and sizing of a getter, suitable for maintaining the vacuum inside the enclosure for the lifetime of the collector, which can be activated at low temperatures.

Keywords: vacuum, thermal, flat-plate solar collector, insulation

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Authors: Kelsey Fortin, Susan Harvey

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The intersection between hunger and health outcomes is beginning to gain traction among the research community. With new interventions focusing on collaborations between the medical and social service sectors, this study aimed to understand the acceptability and approach of a health coaching intervention within a county-wide Midwest food pantry. Through formative research, the study used mixed methods to review secondary data and conduct surveys and semi-structured interviews with food pantry clients (n=30), staff (n=7), and volunteers (n=10). Supplemental secondary data collected and provided by pantry staff were reviewed to understand the broader pantry context of clientele health and health behaviors, annual food donations, and current pantry programming. Results from secondary data showed that the broader pantry client population reported high rates of chronic disease, low consumption of fruits and vegetables, and poor self-reported health, while annual donation data showed increases in produce availability on pantry shelves. This disconnect between produce availability, client health status, and behaviors was supported in the current study, with pantry staff and volunteers reporting lack of knowledge in produce selection and preparation being amongst the most common client inquiries and barriers to healthy food selection. Additional supports to secondary data came from pantry clients in the current study through self-reported high rates of both individual (60%, n=18) and household (43%, n=13 ) disease diagnosis, low consumption of fruits and vegetables averaging zero to one servings of vegetables (67%, n=20) and fruits (47%, n=14) per day, and low levels of physical activity averaging zero to 120 minutes per week (67%, n=20). Further, pantry clients provided health coaching programmatic recommendations through interviews with feedback such as non-judgmental coaching, accountability measures, and providing participant incentives as considerations for future program design and approach. Volunteers and staff reported the need for client education in food preparation, basic nutrition and physical activity, and the need for additional health expertise to educate and respond to diet related nutrition recommendations. All three stakeholder groups supported hosting a health coach within the pantry to focused on nutrition, physical activity, and health programming, with one client stating, 'I am hoping it really works out [the health coaching program]. I think it would be great for something like this to be offered for someone that isn’t knowledgeable like me.' In conclusion, high rates of chronic disease, partnered with low food, nutrition, and physical activity literacy among pantry clients, demonstrates the need to address health behaviors. With all three stakeholder groups showing acceptability of a health coaching program, partnered with existing literature showing health coaching success as a behavior change intervention, further research should be conducted to pilot the design and implementation of such a program in the pantry setting.

Keywords: food insecurity, formative research, food pantries, health coaching, hunger and health

Procedia PDF Downloads 124

Authors: Rugang Tian

Abstract:

In this study, we generated whole-genome sequence (WGS) data from110 native cattle. Together with whole-genome sequences from world-wide cattle populations, we estimated the genetic diversity and population genetic structure of different cattle populations. Our findings revealed clustering of cattle groups in line with their geographic locations. We identified noticeable genetic diversity between indigenous cattle breeds and commercial populations. Among all studied cattle groups, lower genetic diversity measures were found in commercial populations, however, high genetic diversity were detected in some local cattle, particularly in Rashoki and Mongolian breeds. Our search for potential genomic regions under selection in native cattle revealed several candidate genes related with immune response and cold shock protein on multiple chromosomes such as TRPM8, NMUR1, PRKAA2, SMTNL2 and OXR1 that are involved in energy metabolism and metabolic homeostasis.

Keywords: cattle, whole-genome, population structure, adaptation

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Authors: Diwei Lin, Amanda Jh. Tan

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We present a very rare case of de novo large cell neuroendocrine carcinoma of the prostate (LCNEC) in an 84-year-old male on a background of high-grade, muscle-invasive transitional cell carcinoma of the bladder. While NE tumours account for 1% to 5% of all cases of prostate cancer and scattered NE cells can be found in 10% to 100% of prostate adenocarcinomas, pure LCNEC of the prostate is extremely rare. Most LCNEC of the prostate is thought to originate by clonal progression under the selection pressure of therapy and refractory to long-term hormonal treatment for adenocarcinoma of the prostate. De novo LCNEC is only described in case reports and is thought to develop via direct malignant transformation. Limited data in the English literature makes it difficult to accurately predict the prognosis of LCNEC of the prostate. However, current evidence suggesting that increasing NE differentiation in prostate adenocarcinoma is associated with a higher stage, high-grade disease, and a worse prognosis.

Keywords: large cell neuroendocrine cancer, prostate cancer, refractory cancer, medical and health sciences

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Authors: Abdar Ali, Rizwan Ullah, Zahid Ullah

Abstract:

This paper focuses on the study of DC-to-DC converters, which are suitable for low-voltage high-power applications. The output voltages generated by renewable energy sources such as photovoltaic arrays and fuel cell stacks are generally low and required to be increased to high voltage levels. Development of DC-to-DC converters, which provide high step-up voltage conversion ratios with high efficiencies and low voltage stresses is one of the main issues in the development of renewable energy systems. A procedure for three converters-conventional DC-to-DC converter, interleaved boost converter, and isolated flyback based converter, is illustrated for a given set of specifications. The selection among the converters for the given application is based on the voltage conversion ratio, efficiency, and voltage stresses.

Keywords: flyback converter, interleaved boost, photovoltaic array, fuel cell, switch stress, voltage conversion ratio, renewable energy

Procedia PDF Downloads 584

Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir

Abstract:

NSGA-II is one of the most well-known and most widely used evolutionary algorithms. In addition to its new versions, such as NSGA-III, there are several modified types of this algorithm in the literature. In this paper, a hybrid NSGA-II algorithm has been suggested for solving the multi-objective flexible job shop scheduling problem. For a better search, new neighborhood-based crossover and mutation operators are defined. To create new generations, the neighbors of the selected individuals by the tournament selection are constructed. Also, at the end of each iteration, before sorting, neighbors of a certain number of good solutions are derived, except for solutions protected by elitism. The neighbors are generated using a constraint-based neural network that uses various constructs. The non-dominated sorting and crowding distance operators are same as the classic NSGA-II. A comparison based on some multi-objective benchmarks from the literature shows the efficiency of the algorithm.

Keywords: flexible job shop scheduling problem, multi-objective optimization, NSGA-II algorithm, neighborhood structures

Procedia PDF Downloads 218

Authors: Rebiahi Sid Ahmed, Boutarfi Zakaria, Rahmoun Malika, Antonio Galvez

Abstract:

The objective of this study was to explore the possible correlation between resistance to antibiotics and tolerance to biocides in Gram-negative bacilli isolated from the University Hospital Center of Tlemcen. This study focused on 175 clinical isolates of Gram-negative bacilli, it is a question of exploring: their level and profile of resistance to antibiotics, their tolerance to biocides, as well as the identification of the genetic supports of this resistance. Enterobacter spp. was the most predominant bacterial genus, all isolates harbored at least one of the studied genes with significant resistance capacity. Our results show, in some cases, a possible positive correlation between the presence of biocide tolerance genes and those of antibiotic resistance; in fact, tolerance to biocides could be one of the co-selection factors for antibiotic resistance. The results of this study should encourage the good practice of hygiene measures as well as the rational use of antimicrobials in order to hinder the development and emergence of resistance in our hospital departments.Mots clés : Antibiotiques, Biocides, Enterobacter, Hôpital, Résistance,

Keywords: antibiotic, biocides, enterobacter, hospital, resistance

Procedia PDF Downloads 105

Authors: Cesar Hernández, Diego Giral, Ingrid Páez

Abstract:

This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics is used. These metrics are the accumulative average of failed handoffs, the accumulative average of handoffs performed, the accumulative average of transmission bandwidth, and the accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.

Keywords: cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks

Procedia PDF Downloads 525

Authors: Naci Büyükkaracığan

Abstract:

Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.

Keywords: Gediz Basin, goodness-of-fit tests, minimum flows, probability distribution

Procedia PDF Downloads 265