Search results for: extra tree classifier

Authors: Davies Obaromi, Qin Yongsong, James Ndege, Azeez Adeboye, Akinwumi Odeyemi

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The basic model usually used in disease mapping, is the Besag, York and Mollie (BYM) model and which combines the spatially structured and spatially unstructured priors as random effects. Bayesian Conditional Autoregressive (CAR) model is a disease mapping method that is commonly used for smoothening the relative risk of any disease as used in the Besag, York and Mollie (BYM) model. This model (CAR), which is also usually assigned as a prior to one of the spatial random effects in the BYM model, successfully uses information from adjacent sites to improve estimates for individual sites. To our knowledge, there are some unrealistic or counter-intuitive consequences on the posterior covariance matrix of the CAR prior for the spatial random effects. In the conventional BYM (Besag, York and Mollie) model, the spatially structured and the unstructured random components cannot be seen independently, and which challenges the prior definitions for the hyperparameters of the two random effects. Therefore, the main objective of this study is to construct and utilize an extended Bayesian spatial CAR model for studying tuberculosis patterns in the Eastern Cape Province of South Africa, and then compare for flexibility with some existing CAR models. The results of the study revealed the flexibility and robustness of this alternative extended CAR to the commonly used CAR models by comparison, using the deviance information criteria. The extended Bayesian spatial CAR model is proved to be a useful and robust tool for disease modeling and as a prior for the structured spatial random effects because of the inclusion of an extra hyperparameter.

Keywords: Besag2, CAR models, disease mapping, INLA, spatial models

Procedia PDF Downloads 256

Authors: Kouorsh Zarea, Fatemeh Hassani, Samira Beiranvand, Akram Mohamadi

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Background and Objectives: Medication error in hospitals is a major cause of the errors which disrupt the health care system. The aim of this study was to assess the nurses’ medication errors and related factors. Material and methods: This was a descriptive study on 225 nurses in various hospitals, selected through multistage random sampling. Data was collected by three researcher made tools; demographic, medication error and related factors questionnaires. Data was analyzed by descriptive statistics, Chi-square, Kruskal-Wallis, One-way analysis of variance. Results: Based on the results obtained, the type of medication errors giving drugs to patients later or earlier (55.6%), multiple oral medication together regardless of their interactions (36%) and the postoperative analgesic without a prescription (34.2%), respectively. In addition, factors such as the shortage of nurses to patients’ ratio (57.3%), high load functions (51.1%) and fatigue caused by the extra work (40.4%), were the most important factors affecting the incidence of medication errors. The fear of legal issues (40%) are the most important factor is the lack of reported medication errors. Conclusions: Based on the results, effective management and promotion motivate nurses. Therefore, increasing scientific and clinical expertise in the field of nursing medication orders is recommended to prevent medication errors in various states of nursing intervention. Employing experienced staff in areas with high risk of medication errors and also supervising less-experienced staff through competent personnel are also suggested.

Keywords: medication error, nurse, clinical care, drug errors

Procedia PDF Downloads 252

Authors: Anandita Mitro, Archana Srivastava, Bidisha Banerjee

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The present paper attempts to analyze the hierarchy and interconnection of factors responsible for the uptake of BCG vaccination in India. The study uses National Family Health Survey (NFHS-5) data which was conducted during 2019-21. The univariate logistic regression method is used to understand the univariate effects while the interconnection effects have been studied using the Categorical Inference Tree (CIT) which is a non-parametric Machine Learning (ML) model. The hierarchy of the factors is further established using Conditional Inference Forest which is an extension of the CIT approach. The results suggest that BCG vaccination coverage was influenced more by system-level factors and awareness than education or socio-economic status. Factors such as place of delivery, antenatal care, and postnatal care were crucial, with variations based on delivery location. Region-specific differences were also observed which could be explained by the factors. Awareness of the disease was less impactful along with the factor of wealth and urban or rural residence, although awareness did appear to substitute for inadequate ANC. Thus, from the policy point of view, it is revealed that certain subpopulations have less prevalence of vaccination which implies that there is a need for population-specific policy action to achieve a hundred percent coverage.

Keywords: vaccination, NFHS, machine learning, public health

Procedia PDF Downloads 36

Authors: Telesphore Tiendrebeogo, Oumarou Sié

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Cloud computing technologies have attracted considerable interest in recent years. Thus, these latters have become more important for many existing database applications. It provides a new mode of use and of offer of IT resources in general. Such resources can be used “on demand” by anybody who has access to the internet. Particularly, the Cloud platform provides an ease to use interface between providers and users, allow providers to develop and provide software and databases for users over locations. Currently, there are many Cloud platform providers support large scale database services. However, most of these only support simple keyword-based queries and can’t response complex query efficiently due to lack of efficient in multi-attribute index techniques. Existing Cloud platform providers seek to improve performance of indexing techniques for complex queries. In this paper, we define a new cloud computing architecture based on a Distributed Hash Table (DHT) and design a prototype system. Next, we perform and evaluate our cloud computing indexing structure based on a hyperbolic tree using virtual coordinates taken in the hyperbolic plane. We show through our experimental results that we compare with others clouds systems to show our solution ensures consistence and scalability for Cloud platform.

Keywords: virtual coordinates, cloud, hyperbolic plane, storage, scalability, consistency

Procedia PDF Downloads 408

Authors: Jing Ren, Guifeng Han

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The mental health of most college students in China is negative due to the multiple pressures of academics, life, and employment. The problem of psychological stress has been widely discussed and needs to be resolved immediately. Therefore, six typical green spaces in Chongqing University, China, were selected to explore the relationship between eight environmental characteristics and students' stress relief. A path analysis model is established using Amos26.0 to explain the paths for environmental characteristics influencing psychological stress relief. The results show that (1) tree species diversity (TSD) has a positive effect on stress relief, thus green coverage ratio (GCR), the proportion of water area (WAP), visual green index (VGI), and color richness (CR) have both positive and negative effects; (2) CR could reduce stress directly and indirectly, while GCR, TSD, WAP, and VGI could only reduce stress indirectly, and the most effective path is TSD→extent→stress relief; (3) CR can reduce stress more greatly for males than females, CR and VGI have better effects for art students than science students. The study can provide a theoretical reference for planning and designing campus living environments to improve students' mental health.

Keywords: public health, residential environment, space planning and management, mental health, path analysis

Procedia PDF Downloads 47

Authors: Shivani Kuttuva, James Sampson, Timothy Simmons, Vinayak Thattaruparambil, Holly Burton, Peter Coyne

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Anogenital mammary-like glands were established to be embryological remnants of breast tissue due to failed resolution of the ectodermal mammary ridge. However, recent studies are now considering this to represent normal constituents of the anogenital area with histological resemblance to the orthotopic breast tissue with multiple benign and malignant lesions arising from it. The incidence of the above has been predominant in females in the vulval region. Due to the paucity of cases reported in men, this poses a diagnostic and therapeutic challenge resulting in a delay in treatment and, thereby, poor outcomes. Our patient presented to the dermatology clinic with an itchy, purplish lesion in the peri-anal region which, on punch biopsy, was diagnosed to be Extra-mammary Paget’s disease and taken up for Wide local excision. Immunochemically, staining was positive for HER2, ER and Cytokeratin 7, keeping with the presence of actual breast tissue with no primary breast carcinoma. Due to the invasive nature of the disease, he required Abdominoperineal resection with flap reconstruction. Despite complete surgical clearance and adjuvant radiotherapy, the disease progressed to adjacent inguinal and obturator lymph nodes with origin resembling anogenital type mammary glands but histology negative for hormonal receptors of the breast.

Keywords: anogenital mammary-like glands, abdominoperineal resection, ectopic breast tissue, ectopic male breast carcinoma, peri-anal skin lesion

Procedia PDF Downloads 64

Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

Procedia PDF Downloads 164

Authors: Yuhong Li, Luyu Mao

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Globalization has led to an increasingly interconnected international community and transmitted risks to every corner of the world through the chain of globalization. Security risks arising from international conflicts seem inescapable. Some countries have begun to build their capacity to deal with the globalization of security risks. They establish disembedding security mechanisms that transcend spatial or temporal boundaries and promote security cooperation with countries or regions that are not geographically close. This paper proposes four hypotheses of the phenomenon of "risks and security disembedding" in the post-Cold War international society and uses them to explain The United Kingdom’s behavior in the Bosnian War and the Russo-Ukrainian War. In the Bosnian War, confident in its own security and focused on maintaining European stability, The UK has therefore chosen to be cautious in its use of force in international frameworks such as the EU and to maintain a very limited intervention in Bosnia and Herzegovina's affairs. In contrast, the failure of the EU and NATO’s security mechanism in the Russo-Ukrainian war heightened Britain's anxiety, and the volatile international situation led it to show a strong tendency towards security disembedding, choosing to conclude security communities with extra-territorial states. Analysis suggests that security mechanisms are also the starting point of conflict and that countries will rely more on disembedding mechanisms to counteract the global security risks. The current mechanism of security disembedding occurs as a result of the global proliferation of security perceptions as a symbolic token and the recognition of an expert system of security mechanisms formed by states with similar security perceptions.

Keywords: disembedding mechanism, bosnia war, the russian-ukrainian war, british security strategy

Procedia PDF Downloads 66

Authors: Zuoji Huang, Haiming Qian, Chunlin Wang, Jinyan Sun, Nan Xu

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In this paper, the strategy to extract double road edge lines from acquired road stripe image was explored. The workflow is as follows: the road stripes are acquired by probabilistic boosting tree algorithm and morphological algorithm immediately, and road centerlines are detected by thinning algorithm, so the initial road edge lines can be acquired along the road centerlines. Then we refine the results with big variation of local curvature of centerlines. Specifically, the energy function of edge line is constructed by gradient feature and spectral information, and Dijkstra algorithm is used to optimize the initial road edge lines. The Snake model is constructed to solve the fracture problem of intersection, and the discrete dynamic programming algorithm is used to solve the model. After that, we could get the final road network. Experiment results show that the strategy proposed in this paper can be used to extract the continuous and smooth road edge lines from high-resolution remote sensing images with an accuracy of 88% in our study area.

Keywords: road edge lines extraction, energy function, intersection fracture, Snake model

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Authors: K. Raja Rajan, D. Nagarajan

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

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

Procedia PDF Downloads 239

Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

Procedia PDF Downloads 377

Authors: Sabah El-Sawalhi, Elie Fayad, Roula M. Abdel-Massih

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Ilex paraguariensis (Yerba Mate) is a medium to large tree commonly consumed by South Americans. Its leaves and stems are associated with different biological activities. The purpose of this study was to evaluate the antibacterial activity of Yerba Mate against Gram-positive and Gram-negative bacterial strains and its action against some resistant bacteria with different resistance profiles. Yerba Mate aqueous extracts were prepared at 70°C for 2 hrs, and the microdilution method was used to determine the minimum inhibitory concentration (MIC). Gram-positive bacteria exhibited a stronger antibacterial activity (MIC ranged between 0.468 mg/mL and 15 mg/mL) than Gram-negative bacteria. Yerba Mate was also extracted with acetone: water (1:1) and then further sub-fractionated with hexane, chloroform, and ethyl acetate. MIC values against Staphylococcus aureus ranged from 0.78 to 2.5 mg/ml for the chloroform fraction, from 1.56 to 3.75 mg/ml for the ethyl acetate fraction, and 0.78 to 1.87 mg/ml for the water fraction. The water fraction also exhibited antibacterial activity against Salmonella species (MIC ranged from 1.56 mg/ml to 3.12 mg/ml). The water fraction exhibited the highest antibacterial activity among all the fractions obtained. More studies are needed to determine the molecule or molecules responsible for this activity.

Keywords: antibacterial activity, bacterial resistance, minimum inhibitory concentration, yerba mate

Procedia PDF Downloads 118

Authors: Felicia Segeth, Florian G. Klein, Lea Berger, Andreas Kolk, Per S. Holm

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The entry of oncolytic viruses (OVs) into clinical application opens groundbreaking changes in current and future treatment regimens. However, despite their potent anti-cancer activity in vitro, clinical studies revealed limitations of OVs as monotherapy. The same applies to CDK 4/6 inhibitors (CDK4/6i) targeting cell cycle as well as bromodomain and extra-terminal domain inhibitors (BETi) targeting gene expression. In this study, the anti-tumoral effect of XVir-N-31, an YB-1 dependent oncolytic adenovirus, was evaluated in combination with Ribociclib, a CDK4/6i, and JQ1, a BETi. The head and neck squamous cell carcinoma (HNSCC) cell lines Fadu, SAS, and Cal-33 were used. DNA replication and gene expression of XVir-N-31 was measured by RT-qPCR, protein expression by western blotting, and cell lysis by SRB assays. Treatment with CDK4/6i and BETi increased viral gene expression, viral DNA replication, and viral particle formation. The data show that the combination of oncolytic adenovirus XVir-N-31 with CDK4/6i & BETi acts highly synergistic in cancer cell lysis. Furthermore, additional molecular analyses on this subject demonstrate that the positive transcription elongation factor P-TEFb plays a decisive role in this regard, indicating an influence of the combinational therapy on gene transcription control. The combination of CDK4/6i & BETi and XVir-N-31 is an attractive strategy to achieve substantial cancer cell killing and is highly suitable for clinical testing.

Keywords: adenovirus, BET, CDK4/6, HNSCC, P-TEFb, YB-1

Procedia PDF Downloads 101

Authors: Nima Pirhadi, Shao Yong Bo, Xusheng Wan, Jianguo Lu, Jilei Hu

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Although gravels and gravelly soils are assumed to be non-liquefiable because of high conductivity and small modulus; however, the occurrence of this phenomenon in some historical earthquakes, especially recently earthquakes during 2008 Wenchuan, Mw= 7.9, 2014 Cephalonia, Greece, Mw= 6.1 and 2016, Kaikoura, New Zealand, Mw = 7.8, has been promoted the essential consideration to evaluate risk assessment and hazard analysis of seismic gravelly soil liquefaction. Due to the limitation in sampling and laboratory testing of this type of soil, in situ tests and site exploration of case histories are the most accepted procedures. Of all in situ tests, dynamic penetration test (DPT), Which is well known as the Chinese dynamic penetration test, and shear wave velocity (Vs) test, have been demonstrated high performance to evaluate seismic gravelly soil liquefaction. However, the lack of a sufficient number of case histories provides an essential limitation for developing new models. This study at first investigates recent earthquakes that caused liquefaction in gravelly soils to collect new data. Then, it adds these data to the available literature’s dataset to extend them and finally develops new models to assess seismic gravelly soil liquefaction. To validate the presented models, their results are compared to extra available models. The results show the reasonable performance of the proposed models and the critical effect of gravel content (GC)% on the assessment.

Keywords: liquefaction, gravel, dynamic penetration test, shear wave velocity

Procedia PDF Downloads 191

Authors: Farah Jafarpisheh, John Hutson, Howard Fallowfield

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Growing Sorghum varieties, with the potential of the animal food source, by using the treated wastewater from High Rate Algae Ponds (HRAPs) is an attractive subject. For the first time, in South Australia, Sorghum Earthnote variety one (SE1) has been grown using the wastewater from HRAPs. In this study, after the first harvest, the roots left in the soil. After a short period of time, sorghum started to regrow again, which can increase the value of planting sorghum by using the wastewater. This study demonstrates the higher amount of green biomass with the potential of animal food source after the second harvest. Different parameters, including height(mm), number of leaves and tiller, Brix percentage, fresh and dry leaf weight(g), total top fresh weight(g), stem and seed dry and fresh weight(g) have been measured in the field after first and second harvest. The results demonstrated the higher height, number of tiller, and diameter after the second harvest. Number of leaves and leaves fresh weight and total top weight increased by 6 and 10 times, respectively. Brix percentage increased by 2 times. In the first harvest, no seeds harvested, while in the second harvest, 134 g seeds harvested. This sorghum variety (SE1) showed the acceptable green biomass, especially after the second harvest. This property will add to the value of sorghum in this condition, as it will not need extra fertilizer and labor work for seed planting.

Keywords: energy, high rate algae ponds, HRAPs, Sorghum, waste water

Procedia PDF Downloads 90

Authors: Victor Romanov, Daria Efimenko

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The focus on innovation in modern economy is the main factor in surviving business in a competitive environment. The innovations are based on the search and use of knowledge in a global context. Nowadays consumers and market demand are the main innovation drivers. This leads to build a business as a system with feedback, promptly restructuring production and innovation implementation in response to market demands. In modern knowledge economy, because of speed of technical progress, the product's lifecycle became much shorter, what makes more stringent requirements for innovation implementation on the enterprises of and therefore the possibility for enterprise for receiving extra income is decreasing. This circumstance imposes additional requirements for the replacement of obsolete products and the prompt release of innovative products to the market. The development of information technologies has led to the fact that only in the conditions of partnership and knowledge sharing with partners it is possible to update products quickly for innovative products. Many companies pay attention to updating innovations through the search for new partners, but the task of finding new partners presents some difficulties. The search for a suitable one includes several stages such as: determining the moment of innovation-critical, introducing a search, identifying search criteria, justifying and deciding on the choice of a partner. No less important is the question of how to manage an innovative product in response to a changing market. The article considers the problems of information support for the search for the source of innovation and partnership to decrease the time for implementation of novelty products.

Keywords: partnership, novelty, market feedback, alliance

Procedia PDF Downloads 178

Authors: Peter James C. Icalia, Agapita J. Salces, Loida Valenzuela, Kangseok Seo, Geronima Ludan

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This study evaluated polymorphism of 11 microsatellite markers in four local genetic groups of cattle. Batanes cattle which has never been studied using microsatellites is evaluated for its genetic distance from the Ilocos cattle while Brahman and Holstein-Sahiwal are also included as there were insemination programs by the government using these two breeds. PCR products that were genotyped for each marker were analyzed using POPGENEv32. Results showed that 55% (Fst=0.5501) of the genetic variation is due to the differences between populations while the remaining 45% is due to individual variation. The Fst value also indicates that there were very great differences from population to population using the range proposed by Sewall and Wright. The constructed phylogenetic tree based on Nei’s genetic distance using the modified neighboor joining procedure of PHYLIPv3.5 showed the admixture of Brahman and Holstein-Sahiwal having them grouped in the same clade. Batanes and Ilocos cattle were grouped in a different cluster showing that they have descended from a single parental population. This would presumably address the claim that Batanes and Ilocos cattle are genetically distant from other groups and still exist despite the artificial insemination program of the government using Brahman and other imported breeds. The knowledge about the genetic structure of this population supports the development of conservation programs for the smallholder farmers.

Keywords: microsatellites, cattle, Philippines, populations, genetic structure

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Authors: Aderonke Oluseun Akinwumi, Olusola A. Komolaf

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This paper gives information about the wide array of challenges facing both the electric utilities and consumers in the distribution system in developing countries, using Obafemi Awolowo University, Ile-Ife Nigeria as a case study. It also proffers cost-effective solution through remote monitoring, diagnostic and operation of distribution networks without compromising the system reliability. As utilities move from manned and unintelligent networks to completely unmanned smart grids, switching activities at substations and feeders will be managed and controlled remotely by dedicated systems hence this design. The Substation Remote Diagnostic and Operation Solution (sRDOs) would remotely monitor the load on Medium Voltage (MV) and Low Voltage (LV) feeders as well as distribution transformers and allow the utility disconnect non-paying customers with absolutely no extra resource deployment and without interrupting supply to paying customers. The aftermath of the implementation of this design improved the lifetime of key distribution infrastructure by automatically isolating feeders during overload conditions and more importantly erring consumers. This increased the ratio of revenue generated on electricity bills to total network load.

Keywords: electric utility, consumers, remote monitoring, diagnostic, system reliability, manned and unintelligent networks, unmanned smart grids, switching activities, medium voltage, low voltage, distribution transformer

Procedia PDF Downloads 113

Authors: Shimaa A. Higazy, Olfat E. El-Azabawy, Ahmed M. Al-Sabagh, Notaila M. Nasser, Eman A. Khamis

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In this work, two novel Schiff base polymers (PSB1 and PSB₂) with extra-high protective barrier features were facilely prepared via Polycondensation reactions. They were applied for the first time as effective corrosion inhibitors in the sour corrosive media of petroleum environments containing hydrogen sulfide (H₂S) gas. For studying the polymers' inhibitive action on the carbon steel, numerous corrosion testing methods including potentiodynamic polarization (PDP), open circuit potential, and electrochemical impedance spectroscopy (EIS) have been employed at various temperatures (298-328 K) in the oil wells formation water with H₂S concentrations of 100, 400, and 700 ppm as aggressive media. The activation energy (Ea) and other thermodynamic parameters were computed to describe the mechanism of adsorption. The corrosion morphological traits and steel samples' surfaces composition were analyzed by field emission scanning electron microscope and energy dispersive X-ray analysis. The PSB2 inhibited sour corrosion more effectively than PSB1 when subjected to electrochemical testing. The 100 ppm concentration of PSB2 exhibited 82.18 % and 81.14 % inhibition efficiencies at 298 K in PDP and EIS measurements, respectively. While at 328 K, the inhibition efficiencies were 61.85 % and 67.4 % at the same dosage and measurements. These poly Schiff bases exhibited fascinating performance as corrosion inhibitors in sour environment. They provide a great corrosion inhibition platform for the sustainable future environment.

Keywords: schiff base polymers, corrosion inhibitors, sour corrosive media, potentiodynamic polarization, H₂S concentrations

Procedia PDF Downloads 76

Authors: Tomaž Tollazzi, Matjaž Šraml, Chiara Gruden, Marko Renčelj

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Motorcycle riders are an increasing group of road users. The intrinsic characteristics of powered two-wheelers (PTW) allow them to be particularly flexible, both in urban and extra-urban environments. Nevertheless, crash statistics indicate that riders involved in road accidents are highly likely to suffer severe injuries, underlining the vulnerability of this group of road users. An element that can greatly affect the safety of PTW users is road design, as roads are usually designed for two-track vehicles (cars, buses, and lorries) and usually do not consider the needs of PTWs. Additionally, handling a motorcycle is quite different from driving a car; thus, the behavior of riders is different from that of drivers. The aim of this research was to compare how different road designs are perceived by riders and drivers and to preliminarily assess if riders’ behavior and attention allocation are related. For this research, an eye-tracking experiment was developed outdoors. Both drivers and riders travelled along a route comprising four different road designs and various road layouts, and the output was analyzed both qualitatively and quantitatively. Although it was not possible to carry out a statistical analysis due to the limited number of participants, the results demonstrate that there is a difference in the gaze behavior of drivers and riders, with the latter being far more focused on the left-hand side of the road and concentrating on defined elements of road design. Furthermore, the experiment demonstrated that a higher number of fixations is related to lower speeds. Finally, it was noted that both kinds of road users focus well on the carriageway, leading to the conclusion that the indications given through road markings may be much more effective than vertical signalization, which has rarely been observed.

Keywords: road safety, powered two-wheelers, eye-tracking, gaze behavior

Procedia PDF Downloads 63

Authors: Judit Manuel-i-Martin, Mechthild Donner, Ivana Radic, Yamna Erraach, Fatima Elhadad, Taoufik Yatribi, Feliu Lopez-i-Gelats

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This paper investigates how small olive farmers and olive oil producers implement circular economy practices to manage olive related waste and how such strategies are perceived by the farmers themselves. While there is a lot of data and research about possible uses of olive oil by-products, the perceptions and related practices of olive oil farmers is a much less investigated domain. A total of 60 semi-structured interviews were conducted in one of the most relevant olive oil producing regions in the Iberian Peninsula -the region of Terres de Ponent (Catalonia – Spain) - to examine the different by-product valorization strategies the olive oil farms develop. We test the hypothesis that the strategies conducted depend on the nature and amount of resources available by the farm. The results obtained point that access to milling infrastructure is a determining factor. We also found that olive tree pruning biomass and olive pomace are the most common by-products valorized by farmers, the first one on-farm and the latter in mills. Results indicate that high value uses for olive oil by-products are rarely implemented by farmers. We conclude that olive farmers tend to perceive by-product valorization strategies as waste management practices rather than as additional sources of value for their farm.

Keywords: circular economy, discourses, Mediterranean region, olive oil by-products, farmers’ strategies, olive pomace

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Authors: Dang Thuy Binh, Truong Thi Oanh, Le Phan Khanh Hung, Luong thi Tuong Vy

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One of the greatest environmental challenges facing Asia is the management and conservation of the marine biodiversity threaten by fisheries overexploitation, pollution, habitat destruction, and climate change. To date, a few molecular taxonomical studies has been conducted on marine fauna in Vietnam. The purpose of this study was to clarify the phylogeny of economic and ecological reef fish species in Vietnam Reef fish species covering Labridae, Scaridae, Nemipteridae, Serranidae, Acanthuridae, Lutjanidae, Lethrinidae, Mullidae, Balistidae, Pseudochromidae, Pinguipedidae, Fistulariidae, Holocentridae, Synodontidae, and Pomacentridae representing 28 genera were collected from South and Center, Vietnam. Combine with Genbank sequences, a phylogenetic tree was constructed based on 16S gene of mitochondrial DNA using maximum parsimony, maximum likelihood, and Bayesian inference approaches. The phylogram showed the well-resolved clades at genus and family level. Perciformes is the major order of reef fish species in Vietnam. The monophyly of Perciformes is not strongly supported as it was clustered in the same clade with Tetraodontiformes syngnathiformes and Beryciformes. Continue sampling of commercial fish species and classification based on morphology and genetics to build DNA barcoding of fish species in Vietnam is really necessary.

Keywords: reef fish, 16s rDNA, Vietnam, phylogeny

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Authors: Maria Teresa Signes Pont, Jose Juan Cortes Plana

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Our proposal provides suitable modelling to the spread of plant pest and particularly to the propagation of Xylella fastidiosa in the almond trees. We compared the impact of temperature and humidity on the propagation of Xylella fastidiosa in various subspecies. Comparison between Balearic Islands and Alicante (Spain). Most sharpshooter and spittlebug species showed peaks in population density during the month of higher mean temperature and relative humidity (April-October), except for the splittlebug Clastoptera sp.1, whose adult population peaked from September-October (late summer and early autumn). The critical season is from when they hatch from the eggs until they are in the pre-reproductive season (January -April) to expand. We focused on winters in the egg state, which normally hatches in early March. The nymphs secrete a foam (mucilage) in which they live and that protects them from natural enemies of temperature changes and prevents dry as long as the humidity is above 75%. The interaction between the life cycles of vectors and vegetation influences the food preferences of vectors and is responsible for the general seasonal shift of the population from vegetation to trees and vice versa, In addition to the temperature maps, we have observed humidity as it affects the spread of the pest Xylella fastidiosa (Xf).

Keywords: xylella fastidiosa, almod tree, temperature, humidity, environmental model

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Authors: Anna Perrone, Federico Martinelli

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Olive fruit is well-known for the high content in secondary metabolites with high interest at nutritional, nutraceutical, antioxidant, and healthy levels. The content of secondary metabolites in olive at harvest may be affected by different water regimes, with significant effects on olive oil composition and quality and, consequently, on its healthy and nutritional features. In this work, a summary of several research studies dealing with the biosynthesis of healthy and nutraceutical metabolites of the secondary metabolism in olive fruit will be reported. The phytochemical findings have been correlated with the expression of key genes involved in polyphenol, terpenoid, and carotenoid biosynthesis and metabolism in response to different development stages and water regimes. Flavonoids were highest in immature fruits, while anthocyanins increased at ripening. In epicarp tissue, this was clearly associated with an up-regulation of the UFGT gene. Olive fruits cultivated under different water regimes were analyzed by metabolomics. This method identified several hundred metabolites in the ripe mesocarp. Among them, 46 were differentially accumulated in the comparison between rain-fed and irrigated conditions. Well-known healthy metabolites were more abundant at a higher level of water regimes. Increased content of polyphenols was observed in the rain-fed fruit; particularly, anthocyanin concentration was higher at ripening. Several secondary metabolites were differentially accumulated between different irrigation conditions. These results showed that these metabolic approaches could be efficiently used to determine the effects of agronomic treatments on olive fruit physiology and, consequently, on nutritional and healthy properties of the obtained extra-virgin olive oil.

Keywords: olea europea, anthocyanins, polyphenols, water regimes

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Md Rafiqul Islam, Ashir Ahmed, Anwaar Ulhaq, Abu Raihan M. Kamal, Yuan Miao, Hua Wang

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Mental health of people is equally important as of their physical health. Mental health and well-being are influenced not only by individual attributes but also by the social circumstances in which people find themselves and the environment in which they live. Like physical health, there is a number of internal and external factors such as biological, social and occupational factors that could influence the mental health of people. People living in poverty, suffering from chronic health conditions, minority groups, and those who exposed to/or displaced by war or conflict are generally more likely to develop mental health conditions. However, to authors’ best knowledge, there is dearth of knowledge on the impact of workplace (especially the highly stressed IT/Tech workplace) on the mental health of its workers. This study attempts to examine the factors influencing the mental health of tech workers. A publicly available dataset containing more than 65,000 cells and 100 attributes is examined for this purpose. Number of machine learning techniques such as ‘Decision Tree’, ‘K nearest neighbor’ ‘Support Vector Machine’ and ‘Ensemble’, are then applied to the selected dataset to draw the findings. It is anticipated that the analysis reported in this study would contribute in presenting useful insights on the attributes contributing in the mental health of tech workers using relevant machine learning techniques.

Keywords: mental disorder, diagnosis, occupational stress, IT workplace

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Authors: Xavier A. Conlan

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Speed of analysis is a significant limitation to current high-performance liquid chromatography/mass spectrometry (HPLC/MS) and ultra-high-pressure liquid chromatography (UHPLC)/MS systems both of which are used in many forensic investigations. The flow rate limitations of MS detection require a compromise in the chromatographic flow rate, which in turn reduces throughput, and when using modern columns, a reduction in separation efficiency. Commonly, this restriction is combated through the post-column splitting of flow prior to entry into the mass spectrometer. However, this results in a loss of sensitivity and a loss in efficiency due to the post-extra column dead volume. A new chromatographic column format known as 'parallel segmented flow' involves the splitting of eluent flow within the column outlet end fitting, and in this study we present its application in order to interrogate the provenience of methamphetamine samples with mass spectrometry detection. Using parallel segmented flow, column flow rates as high as 3 mL/min were employed in the analysis of amino acids without post-column splitting to the mass spectrometer. Furthermore, when parallel segmented flow chromatography columns were employed, the sensitivity was more than twice that of conventional systems with post-column splitting when the same volume of mobile phase was passed through the detector. These finding suggest that this type of column technology will particularly enhance the capabilities of modern LC/MS enabling both high-throughput and sensitive mass spectral detection.

Keywords: chromatography, mass spectrometry methamphetamine, parallel segmented outlet flow column, forensic sciences

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Huazhen Lin, Ruihua Xu, Zhibin Jiang

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In this real-world case, timetabling the LRT network as a whole is rather challenging for the operator: they are supposed to create a timetable to avoid various route conflicts manually while satisfying a given interval and the number of rolling stocks, but the outcome is not satisfying. Therefore, the operator adopts a computerised timetabling tool, the Train Plan Maker (TPM), to cope with this problem. However, with various constraints in the dual-line network, it is still difficult to find an adequate pairing of turnback time, interval and rolling stocks’ number, which requires extra manual intervention. Aiming at current problems, a one-off model for timetabling is presented in this paper to simplify the procedure of timetabling. Before the timetabling procedure starts, this paper presents how the dual-line system with a ring and several branches is turned into a simpler structure. Then, a non-linear programming model is presented in two stages. In the first stage, the model sets a series of constraints aiming to calculate a proper timing for coordinating two lines by adjusting the turnback time at termini. Then, based on the result of the first stage, the model introduces a series of inequality constraints to avoid various route conflicts. With this model, an analysis is conducted to reveal the relation between the ratio of trains in different directions and the possible minimum interval, observing that the more imbalance the ratio is, the less possible to provide frequent service under such strict constraints.

Keywords: light rail transit (LRT), non-linear programming, railway timetabling, timetable coordination

Procedia PDF Downloads 48