Search results for: causal realtion extraction

Authors: S. Vasailor, C. Rattanakawin

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Electro-winning of copper metal from dilute sulfate solution (13.7 g/L) was performed in a lab electrolytic cell with stainless-steel cathode and lead-alloy anode. The effects of various parameters including cell voltage, electro-winning temperature and time were studied in order to acquire an appropriate current efficiency of copper deposition. The highest efficiency is about 95% obtaining from electro-winning condition of 3V, 55°C and 3,600 s correspondingly. The cathode copper with 95.5% Cu analyzed using atomic absorption spectrometry can be obtained from this single-winning condition. In order to increase the copper grade, solvent extraction should be used to increase the sulfate concentration, say 50 g/L, prior to winning the cathode copper effectively.

Keywords: copper metal, current efficiency, dilute sulfate solution, electro-winning

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Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore

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In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.

Keywords: CDSS, EHR, business intelliegence, tools

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Authors: Guanghua Lu, Zhenhua Yan

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To investigate the estrogenic contamination and potential risk of Taihu Lake, eight active biomonitoring points in the northern section of Taihu Lake were set up and located in Wangyuhe River outlet (P1), Gonghu Bay (P2 and P3), Meiliang Bay (P4 and P5), Zhushan Bay (P6 and P7) and Lake Centre (P8). A suite of biomarkers in caged fish after in situ exposure for 28 days, coupled with six selected exogenous estrogens in water, were determined in May and December 2011. Six target estrogens, namely estrone (E1), 17b-estradiol (E2), ethinylestradiol (EE2), estriol (E3), diethylstilbestrol (DES) and bisphenol A (BPA), were quantified using UPLC/MS/MS. The concentrations of E1, E2, E3, EE2, DES and BPA ranged from ND to 3.61 ng/L, ND to 17.3 ng/L, ND to 1.65 ng/L, ND to 10.2 ng/L, ND to 34.6 ng/L, and 3.95 to 207 ng/L, respectively. BPA was detected at all sampling points at all test periods, E2 was detected at 95% of samples, E1 and EE2 was detected at 75% of samples, and E3 was detected only in December 2011 with quite low concentrations. Each individual estrogen concentration measured at each sampling point was multiplied by its relative potency to gain the estradiol equivalent (EEQ). The total EEQ values in all the monitoring points ranged from 5.69 to 17.8 ng/L in May 2011, and from 4.46 to 21.1 ng/L in December 2011. E2 and EE2 were thought to be the major causal agents responsible for the estrogenic activities. Serum vitellogenin and E2 levels, gonadal DNA damage, and gonadosomatic index were measured in the in situ exposed fish. An enhanced integrated biomarker response (EIBR) was calculated and used to evaluate potential feminization risk of fish in the polluted area of Taihu Lake. EIBR index showed good agreement with the observed total EEQ levels in water. Our results indicated that Gong bay and the lake center had a low estrogenic risk, whereas Wangyuhe River, Meiliang Bay, and Zhushan Bay might present a higher risk to fish.

Keywords: active biomonitoring, estrogen, feminization risk, Taihu Lake

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Authors: F. Fernandes, C. Poleto

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This paper aims at assessing the concentrations of heavy metals and the isotopic composition of lead ²¹⁰Pb in different fractions of sediment produced in the watershed that makes up the Mãe d'água dam and thus characterizing the distribution of metals along the sedimentary column and inferencing in the urbanization of the same process. Sample collection was carried out in June 2014; eight sediment cores were sampled in the lake of the dam. For extraction of the sediments core, a core sampler “Piston Core” was used. The trace metal concentrations were determined by conventional atomic absorption spectrophotometric methods. The samples were subjected to radiochemical analysis of ²¹⁰Po. ²¹⁰Pb activity was obtained by measuring ²¹⁰Po activity. The chronology was calculated using the constant rate of supply (CRS). ²¹⁰Pb is used to estimate the sedimentation rate.

Keywords: ²¹⁰Pb dating method, heavy metal, lakes urban, pollution history

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

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China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.

Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron

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Authors: Nizar Ghali, Bernard Fortin, Guy Lacroix

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In Quebec, colonoscopies volumes have continued to rise in recent years in the absence of effective monitoring mechanism for the appropriateness and the quality of these exams. In 2010, November, Quebec Government introduced the colorectal cancer-screening program in the objective to control for volume and cost imperfection. This program is based on clinical standards and was initiated for first group of institutions. One year later, Government adds financial incentives for participants institutions. In this analysis, we want to assess for the causal effect of the two components of this program: clinical pathways and financial incentives. Especially we assess for the reform effect on healthcare quality and population health in the context that medical remuneration is not directly dependent on this additional funding offered by the program. We have data on admissions episodes and deaths for 8 years. We use multistate model analog to difference in difference approach to estimate reform effect on the transition probability between different states for each patient. Our results show that the reform reduced length of stay without deterioration in hospital mortality or readmission rate. In the other hand, the program contributed to decrease the hospitalization rate and a less invasive treatment approach for colorectal surgeries. This is a sign of healthcare quality and population health improvement. We demonstrate in this analysis that physicians’ behavior can be affected by both clinical standards and financial incentives even if offered to facilities.

Keywords: multi-state and multi-episode transition model, healthcare quality, length of stay, transition probability, difference in difference

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Authors: Zineb Nougrara

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In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: satellite image, road network, nodes, image analysis and processing

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Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

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Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech.

Keywords: multiscale product, spectral centroid, speech segmentation, zero crossings rate

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Authors: Mustapha Mahmoud, Fouzia Toumi Benali, Mohamed Benyahia, Sofiane Bouazza

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This work focuses on the influences of biological and chemical parameters on the phenolic compounds such as flavonoids and tannins in different medicinal plants in western Algeria (Papaver rhoeas, Daphnegnidium, Lavandula multifida, Lavandula dentata, Lavandula stoicha, ...). Thus we look the difference between species of the same genus, difference between the different organs of the same species, the influence of environment all temperature influences, time, percentage of solvent on the extraction. Quantification of the phenolic compounds was performed by spectrophotometric method then treated with statistics tools such as variance analysis, multivariant analyzes, response surface methodology). The results show that the polyphenols are influenced by the parameters mentioned.

Keywords: polyphenols, influences, medicinal plants, west Algeria

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Authors: Hilary Rutto

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The investigation was aimed at determining the extent at which the zinc will be extracted from secondary sources generated from galvanising process using dilute sulphuric acid under controlled laboratory conditions of temperature, solid-liquid ratio, and agitation rate. The leaching experiment was conducted for a period of 2 hours and to total zinc extracted calculated in relation to the amount of zinc dissolved at a unit time in comparison to the initial zinc content of the zinc ash. Sulphuric acid was found to be an effective leaching agent with an overall extraction of 91.1% when concentration is at 2M, and solid/liquid ratio kept at 1g/200mL leaching solution and temperature set at 65ᵒC while slurry agitation is at 450rpm. The leaching mechanism of zinc ash with sulphuric acid was conformed well to the shrinking core model.

Keywords: leaching, kinetics, shrinking core model, zinc slag

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Authors: Matheus Borges Carneiro, Fabiane Leticia Lizarelli, José Carlos De Toledo

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The evolution of quality management by companies was strongly enabled by, among others, ISO 9001 certification, which is considered a crucial requirement for several customers. Likewise, performance measurement provides useful insights for companies to identify the reflection of their decision-making process on their improvement. One of the most used performance measurement models is the balanced scorecard (BSC), which uses four perspectives to address a firm’s performance: financial, internal process, customer satisfaction, and learning and growth. Studies related to ISO 9001 and business performance have mostly adopted a quantitative approach to identify the standard’s causal effect on a firm’s performance. However, to verify how this influence may occur, an in-depth analysis within a qualitative approach is required. Therefore, this paper aims to verify the impact of ISO 9001:2015 on Brazilian firms’ performance based on the balanced scorecard perspective. Hence, nine certified companies located in the Southeast region of Brazil were studied through a multiple case study approach. Within this study, it was possible to identify the positive impact of ISO 9001 on firms’ overall performance, and four Critical Success Factors (CSFs) were identified as relevant on the linkage among ISO 9001 and firms’ performance: employee involvement, top management, process management, and customer focus. Due to the COVID-19 pandemic, the number of interviews was limited to the quality manager specialist, and the sample was limited since several companies were closed during the period of the study. This study presents an in-depth analysis of how the relationship between ISO 9001 certification and firms’ performance in a developing country is.

Keywords: balanced scorecard, Brazilian firms’ performance, critical success factors, ISO 9001 certification, performance measurement

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Authors: Lamidi Lawal Aduozava

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Masquerade tradition is an indigenous culture of the Anetuno an extraction of the Ebira referred to as Ebira chao. This paper seeks to make aesthetic analysis of the masquerades in terms of their costumes and socio-cultural significance. To this end, the study examined and documented the functions and roles of Anipo and Idowo masquerades in terms of therapeutic, economic, prophetic and divination, entertainment, and funeral functions to the owner community(Eziobe group of families) in Igarra, Edo State of Nigeria, West Africa. For the purpose of data collection, focus group discussion, participatory, visual and observatory methods of data collection were used. All the data collected were aesthetically, descriptively and historically analyzed.

Keywords: Aesthetics, , Costume, , Masquerades, , Significance.

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Authors: Maria Reichenber Arcilla

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Objective: To determine the risk factors for maternal and neonatal complications associated with operative vaginal deliveries. Methods: A retrospective chart review of 435 patients who underwent operative vaginal deliveries was done. Patient profiles – age, parity, AOG, duration of labor – and outcomes – birthweight, maternal and neonatal complications - were tabulated and multivariable analysis and logistic regression were performed using SPSS® Statistics Base. Results and Conclusion: There was no significant difference in the incidence of maternal and neonatal complications between those that underwent vacuum and forceps extraction. Among the variables analysed, parity and duration of labor reached statistical significance. The odds of maternal complications were 3 times higher among nulliparous patients. Neonatal complications were seen in those whose labor lasted more than 9 hours.

Keywords: operative vaginal deliveries, maternal, neonatal, morbidity

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Authors: A. A Warra, S. Fatima

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The experimental investigation revealed that the hexane extract of onion seed oil has acid value, iodine value, peroxide value, saponification value, relative density and refractive index of 0.03±0.01 mgKOH/g, 129.80±0.21 gI2/100g, 3.00± 0.00 meq H2O2 203.00±0.71 mgKOH/g, 0.82±0.01and 1.44±0.00 respectively. The percentage yield was 50.28±0.01%. The colour of the oil was light green. We restricted our GC-MS spectra interpretation to compounds identification, particularly fatty acids and they are identified as palmitic acid, linolelaidic acid, oleic acid, stearic acid, behenic acid, linolenic acid and eicosatetraenoic acid. The pH , foam ability (cm³), total fatty matter, total alkali and percentage chloride of the onion oil soap were 11.03± 0.02, 75.13±0.15 (cm³), 36.66 ± 0.02 %, 0.92 ± 0.02% and 0.53 ± 0.15 % respectively. The texture was soft and the colour was lighter green. The results indicated that the hexane extract of the onion seed oil has potential for cosmetic industries.

Keywords: onion seeds, soxhlet extraction, physicochemical, GC-MS, cold saponification

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Authors: Mounir Zekkaoui, Abdelhadi Fennan

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The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

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With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

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Authors: Asma Batool

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Immigrant families raising a child with developmental disabilities in Canada encounter many challenges during the process of disability care. Starting from the early screening of their child for diagnosis followed by challenges associated with treatment, access and service utilization. A substantial amount of research focuses on identifying barriers. However, the functional aspects of barriers in terms of their potential influences on parents and children with disabilities are unexplored yet. This paper presents functional analysis of barriers in disability care research by adopting a method of integrated approach. Juxtaposition of two developmental approaches, Bronfenbrenner’s ecological model and parents ‘transformational process model is generating multiple hypotheses to be considered while empirically investigating causal relationships and mediating or moderating factors among various variables related with disability care research. This functional analysis suggests that barriers have negative impacts on the physical and emotional development of children with disabilities as well as on the overall quality of family life (QOFL). While, barriers have facilitating impacts on parents, alternatively, the process of transformation in parents expedite after experiencing barriers. Consequently, parents reconstruct their philosophy of life and experience irreversible but continuous developmental change in terms of transformations simultaneously with their developing child and may buffer the expected negative impacts of barriers on disabled child and QOFL. Overall, this paper is suggesting implications for future research and parents’ transformations are suggesting potential pathways to minimize the negative influences of barriers that parents experience during disability care, hence improving satisfaction in QOFL in general.

Keywords: barriers in disability care, developmental disabilities, parents’ transformations, quality of family life

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Authors: Samarpreet Singh, Gerald Giesbrecht

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Both c-section and antibiotic exposure are linked to gut microbiota imbalance in infants. Such disturbance is associated with the Hypothalamic-Pituitary-Adrenal (HPA) axis function. However, the literature only has contradicting evidence for the association between c-sections and the HPA axis. Therefore, this study aims to test if the mode of delivery and antibiotics exposure is associated with the HPA axis. Also, whether exposure to both interacts with the HPA-axis. It was hypothesized that associations and interactions would be observed. Secondary data analysis was used for this co-relational study. Data for the mode of delivery and antibiotics exposure variables were documented from hospital records or self-questionnaires. In addition, cortisol levels (Area under the curve with respect to increasing (AUCi) and Area under the curve with respect to ground (AUCg)) were based on saliva collected from three months old during the infant’s visit to the lab and after drawing blood. One-way and between-subject ANOVA analyses were run on data. No significant association between delivery mode and infant cortisol level was found, AUCi and AUCg, p > .05. Only the infant’s AUCg was found to be significantly higher if there were antibiotics exposure at delivery (p = .001) or their mothers were exposed during pregnancy (p < .05). Infants born by c-section and exposed to antibiotics at three months had higher AUCi than those born vaginally, p < .02. These results imply that antibiotic exposure before three months is associated with an infant’s stress response. The association might increase if antibiotic exposure occurs three months after a c-section birth. However, more robust and causal evidence in future studies is needed, given a variable group’s statistically weak sample size. Nevertheless, the results of this study still highlight the unintended consequences of antibiotic exposure during delivery and pregnancy.

Keywords: HPA-axis, antibiotics, c-section, gut-microbiota, development, stress

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Authors: Aiman Alshare, Sahar Qaadan

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A curvature dependent force correction algorithm for planning force controlled grinding process with off-line programming flexibility is designed for ABB industrial robot, in order to avoid the manual interface during the process. The machining path utilizes a spline curve fit that is constructed from the CAD data of the workpiece. The fitted spline has a continuity of the second order to assure path smoothness. The implemented algorithm computes uniform forces normal to the grinding surface of the workpiece, by constructing a curvature path in the spatial coordinates using the spline method.

Keywords: ABB industrial robot, grinding process, offline programming, CAD data extraction, force correction algorithm

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

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Authors: Wei Li, Tuo Yang

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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Sunil Verma

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In today’s world non-renewable sources are depleting quickly, so there is a need to produce efficient and unconventional engines to minimize the use of fuel. Also, there are many fatal accidents happening every year during extraction, distillation, transportation and storage of fuel. Reason for explosions of gaseous fuel is unwanted autoignition. Autoignition characterstics of fuel are mandatory to study to build efficient engines and to avoid accidents. This report is concerned with study of autoignition delay characteristics of iso-octane by using rapid compression machine. The paper clearly explains the dependence of ignition delay characteristics on variation of equivalence ratios from lean to rich mixtures. The equivalence ratio is varied from 0.3 to 1.2.

Keywords: autoignition, iso-octane, combustion, rapid compression machine, equivalence ratio, ignition delay

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Authors: S. Da Costa, D. Páez, F. Sánchez

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We examine the causal role of positive affect on creativity, the association of creativity or innovation in the ideation phase with functional emotional regulation, successful adjustment to stress and dispositional emotional creativity, as well as the predictive role of creativity for positive emotions and social adjustment. The study examines the effects of modification of positive affect on creativity. Participants write three poems, narrate an infatuation episode, answer a scale of personal growth after this episode and perform a creativity task, answer a flow scale after creativity task and fill a dispositional emotional creativity scale. High and low positive effect was induced by asking subjects to write three poems about high and low positive connotation stimuli. In a neutral condition, tasks were performed without previous affect induction. Subjects on the condition of high positive affect report more positive and less negative emotions, more personal growth (effect size r = .24) and their last poem was rated as more original by judges (effect size r = .33). Mediational analysis showed that positive emotions explain the influence of the manipulation on personal growth - positive affect correlates r = .33 to personal growth. The emotional creativity scale correlated to creativity scores of the creative task (r = .14), to the creativity of the narration of the infatuation episode (r = .21). Emotional creativity was also associated, during performing the creativity task, with flow (r = .27) and with affect balance (r = .26). The mediational analysis showed that emotional creativity predicts flow through positive affect. Results suggest that innovation in the phase of ideation is associated with a positive affect balance and satisfactory performance, as well as dispositional emotional creativity is adaptive.

Keywords: affectivity, creativity, induction, innovation, psychological factors

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Authors: Shiming Li, Qingwang Liu, Honggan Wu, Jianbing Zhang

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Plantation forests are useful for timber production, recreation, environmental protection and social development. Stands height is an important parameter for the estimation of forest volume and carbon stocks. Although lidar is suitable technology for the vertical parameters extraction of forests, but high costs make it not suitable for operational inventory. With the development of computer vision and photogrammetry, aerial photos from unmanned aerial system can be used as an alternative solution for height mapping. Structure-from-motion (SfM) photogrammetry technique can be used to extract DSM and DEM information. Canopy height model (CHM) can be achieved by subtraction DEM from DSM. Our result shows that overlapping aerial photos is a potential solution for plantation forests height mapping.

Keywords: forest height mapping, plantation forests, structure-from-motion photogrammetry, UAS

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Authors: Syed Islam, Yiyun Huang, Sebastian Magierowski, Ebrahim Ghafar-Zadeh

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This paper presents system level CMOS solid-state nanopore techniques enhancement for speedup next generation molecular recording and high throughput channels. This discussion also considers optimum number of base-pair (bp) measurements through channel as an important role to enhance potential read accuracy. Effective power consumption estimation offered suitable rangeof multi-channel configuration. Nanopore bp extraction model in statistical method could contribute higher read accuracy with longer read-length (200 < read-length). Nanopore ionic current switching with Time Multiplexing (TM) based multichannel readout system contributed hardware savings.

Keywords: DNA, nanopore, amplifier, ADC, multichannel

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Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

Procedia PDF Downloads 164