Search results for: tree detection

Authors: Howard Chitimira

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The European Union (EU) was probably the first body to establish multinational anti-market abuse laws aimed at enhancing the detection and curbing of cross-border market abuse activities in its member states. Put differently, the EU Insider Dealing Directive was adopted in 1989 and was the first law that harmonised the insider trading ban among the EU member states. Thereafter, the European Union Directive on Insider Dealing and Market Manipulation (EU Market Abuse Directive) was adopted in a bid to improve and effectively discourage all the forms of market abuse in the EU’s securities and financial markets. However, the EU Market Abuse Directive had its own gaps and flaws. In light of this, the Market Abuse Regulation and the Criminal Sanctions for Market Abuse Directive were enacted to repeal and replace the EU Market Abuse Directive in 2016. The article examines the adequacy of the EU Market Abuse Directive and its implementation in the United Kingdom (UK) prior to the British exit (Brexit). This is done to investigate the possible implications of the Brexit referendum outcome of 23 June 2016 on the future regulation of market abuse in the UK.

Keywords: market abuse, insider trading, market manipulation, European Union, United Kingdom

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Authors: Analen Malnegro, Gina Malacas

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Dominating sets and related topics have been studied extensively in the past few decades. A dominating set of a graph G is a subset D of V such that every vertex not in D is adjacent to at least one member of D. The domination number γ(G) is the number of vertices in a smallest dominating set for G. Some problems involving detection devices can be modeled with graphs. Finding the minimum number of devices needed according to the type of devices and the necessity of locating the object gives rise to locating-dominating sets. A subset S of vertices of a graph G is called locating-dominating set, LD-set for short, if it is a dominating set and if every vertex v not in S is uniquely determined by the set of neighbors of v belonging to S. The location-domination number λ(G) is the minimum cardinality of an LD-set for G. The complement of a graph G is a graph Ḡ on same vertices such that two distinct vertices of Ḡ are adjacent if and only if they are not adjacent in G. An LD-set of a graph G is global if it is an LD-set of both G and its complement Ḡ. The global location-domination number λg(G) is defined as the minimum cardinality of a global LD-set of G. In this paper, global LD-sets on the join of two graphs are characterized. Global location-domination numbers of these graphs are also determined.

Keywords: dominating set, global locating-dominating set, global location-domination number, locating-dominating set, location-domination number

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Authors: Japhet N. Mwambusi

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High tropical forests deforestation for solid wood furniture industry is among of climate change contributing agents. This pressure indirectly is caused by furniture joints failure due to poor gluing technology based on improper use of different glues to different wood species which lead to low quality and weak wood-glue joints. This study was carried in order to run performance tests of wood glues on different wood species used in wood workshops: Morogoro Tanzania whereby three popular wood species of C. lusitanica, T. glandis and E. maidenii were tested against five glues of Woodfix, Bullbond, Ponal, Fevicol and Coral found in the market. The findings were necessary on developing a guideline for proper glue selection for a particular wood species joining. Random sampling was employed to interview carpenters while conducting a survey on the background of carpenters like their education level and to determine factors that influence their glues choice. Monsanto Tensiometer was used to determine bonding strength of identified wood glues to different wood species in use under British Standard of testing wood shear strength (BS EN 205) procedures. Data obtained from interviewing carpenters were analyzed through Statistical Package of Social Science software (SPSS) to allow the comparison of different data while laboratory data were compiled, related and compared by the use of MS Excel worksheet software as well as Analysis of Variance (ANOVA). Results revealed that among all five wood glues tested in the laboratory to three different wood species, Coral performed much better with the average shear strength 4.18 N/mm², 3.23 N/mm² and 5.42 N/mm² for Cypress, Teak and Eucalyptus respectively. This displays that for a strong joint to be formed to all tree wood species for soft wood and hard wood, Coral has a first priority in use. The developed table of guideline from this research can be useful to carpenters on proper glue selection to a particular wood species so as to meet glue-bond strength. This will secure furniture market as well as reduce pressure to the forests for furniture production because of the strong existing furniture due to their strong joints. Indeed, this can be a good strategy on reducing climate change speed in tropics which result from high deforestation of trees for furniture production.

Keywords: climate change, deforestation, gluing technology, joint failure, wood-glue, wood species

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Authors: B. G. Sheeparamatti, J. S. Kadadevarmath

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Microcantilevers are the basic MEMS devices, which can be used as sensors, actuators, and electronics can be easily built into them. The detection principle of microcantilever sensors is based on the measurement of change in cantilever deflection or change in its resonance frequency. The objective of this work is to explore the analogies between the mechanical and electrical equivalent of microcantilever beams. Normally scientists and engineers working in MEMS use expensive software like CoventorWare, IntelliSuite, ANSYS/Multiphysics, etc. This paper indicates the need of developing the electrical equivalent of the MEMS structure and with that, one can have a better insight on important parameters, and their interrelation of the MEMS structure. In this work, considering the mechanical model of the microcantilever, the equivalent electrical circuit is drawn and using a force-voltage analogy, it is analyzed with circuit simulation software. By doing so, one can gain access to a powerful set of intellectual tools that have been developed for understanding electrical circuits. Later the analysis is performed using ANSYS/Multiphysics - software based on finite element method (FEM). It is observed that both mechanical and electrical domain results for a rectangular microcantilevers are in agreement with each other.

Keywords: electrical equivalent circuit analogy, FEM analysis, micro cantilevers, micro sensors

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Authors: Maxime Farin, Emmanuel Moulin, Lynda Chehami, Farouk Benmeddour, Pierre Campistron

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Assessing corrosion is crucial in the petrochemical and marine industry. Usual ultrasonic methods based on guided waves to detect corrosion can inspect large areas but lack precision. We propose a complementary and sensitive ultrasonic method (~ 10 MHz) based on coda wave interferometry to detect and quantify corrosion at the surface of a steel sample. The method relies on a single piezoelectric transducer, exciting the sample and measuring the scattered coda signals at different instants in time. A laboratory experiment is conducted with a steel sample immersed in salted water for 60~h with parallel coda and temperature measurements to correct coda dependence to temperature variations. Micrometric changes to the sample surface caused by corrosion are detected in the late coda signals, allowing precise corrosion detection. Moreover, a good correlation is found between a parameter quantifying the temperature-corrected stretching of the coda over time with respect to a reference without corrosion and the corrosion surface over the sample recorded with a camera.

Keywords: coda wave interferometry, nondestructive evaluation, corrosion, ultrasonics

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Authors: Noraishah Othman, Siti K. Kamarudin, Norinsan K. Othman, Mohd S. Takriff, Masli I. Rosli, Engku M. Fahmi, Mior A. Khusaini

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The present work describes hydrodynamics of mixing characteristics of two dual hybrid impeller consisting of, radial and axial impeller using radiotracer technique. Type A mixer, a Rushton turbine is mounted above a Pitched Blade Turbine (PBT) at common shaft and Type B mixer, a Rushton turbine is mounted below PBT. The objectives of this paper are to investigate the residence time distribution (RTD) of two hybrid mixers and to represent the respective mixers by RTD model. Each type of mixer will experience five radiotracer experiments using Tc99m as source of tracer and scintillation detectors NaI(Tl) are used for tracer detection. The results showed that mixer in parallel model and mixers in series with exchange can represent the flow model in mixer A whereas only mixer in parallel model can represent Type B mixer well than other models. In conclusion, Type A impeller, Rushton impeller above PBT, reduced the presence of dead zone in the mixer significantly rather than Type B.

Keywords: hybrid impeller, residence time distribution (RTD), radiotracer experiments, RTD model

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Authors: B. X. Tchomeni, A. A. Alugongo, L. M. Masu

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This paper presents a 4-DOF nonlinear model of a cracked of Laval rotor established based on Energy Principles. The model has been used to simulate coupled torsional-lateral response of the cracked rotor stator-system with multiple parametric excitations, namely, rotor-stator-rub, a breathing transverse crack, unbalanced mass, and an axial force. Nonlinearity due to a “breathing” crack is incorporated by considering a simple hinge model which is suitable for small breathing crack. The vibration response of a cracked rotor passing through its critical speed with rotor-stator interaction is analyzed, and an attempt for crack detection and monitoring explored. Effects of unbalanced eccentricity with phase and acceleration are investigated. By solving the motion equations, steady-state vibration response is obtained in presence of several rotor faults. The presence of a crack is observable in the power spectrum despite the excitation by the axial force and rotor-stator rub impact. Presented results are consistent with existing literature and could be adopted into rotor condition monitoring strategies

Keywords: rotor, crack, rubbing, axial force, non linear

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Authors: Sh. Najari Moghadam, M. Qomi, F. Raofie, J. Khadiv

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In this study, a liquid phase microextraction by hollow fiber (HF-LPME) combined with high performance liquid chromatography-UV detector was applied to preconcentrate and determine trace levels of Cyproheptadine in human urine and plasma samples. Cyproheptadine was extracted from 10 mL alkaline aqueous solution (pH: 9.81) into an organic solvent (n-octnol) which was immobilized in the wall pores of a hollow fiber. Then, it was back-extracted into an acidified aqueous solution (pH: 2.59) located inside the lumen of the hollow fiber. This method is simple, efficient and cost-effective. It is based on pH gradient and differences between two aqueous phases. In order to optimize the HF-LPME, some affecting parameters including the pH of donor and acceptor phases, the type of organic solvent, ionic strength, stirring rate, extraction time and temperature were studied and optimized. Under optimal conditions enrichment factor, limit of detection (LOD) and relative standard deviation (RSD(%), n=3) were up to 112, 15 μg.L−1 and 2.7, respectively.

Keywords: biological samples, cyproheptadine, hollow fiber, liquid phase microextraction

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

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Authors: Lee Suan Chua

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This study investigated the effects of thermal treatment on Tualang honey sample in terms of honey colour and heat-induced small metabolites. The heating process was carried out in a temperature controlled water batch at 90 °C for 4 hours. The honey samples were put in cylinder tubes with the dimension of 1 cm diameter and 10 cm length for homogenous heat transfer. The results found that the thermal treatment produced not only hydroxylmethylfurfural, but also other harmful substances such as phthalic anhydride and radiolytic byproducts. The degradation of honey protein was reported due to the detection of free amino acids such as cysteine and phenylalanine in heat-treated honey samples. Sugar dehydration also occurred because fragmented di-galactose was identified based on the presence of characteristic ions in the mass fragmentation pattern. The honey colour was found getting darker as the heating duration was increased up to 4 hours. Approximately, 60 mm PFund of increment was noticed for the honey colour with the colour change rate of 14.8 mm PFund per hour. Based on the principal component analysis, the chemical profile of Tualang honey was significantly altered after 2 hours of heating at 90 °C.

Keywords: honey colour, hydroxylmethylfurfural, thermal treatment, tualang honey

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Authors: İmren Öztürk Yılmaz, Abdullah Yasin Bilici, Yasin Atalay Candemir

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The system consists of 4 main elements: motion system, image acquisition system, image processing software, and control interface. The parts coming out of the production line to enter the image processing system with the conveyor belt at the end of the line. The 3D scanning of the produced part is performed with the laser scanning system integrated into the system entry side. With the 3D scanning method, it is determined at what position and angle the parts enter the system, and according to the data obtained, parameters such as part origin and conveyor speed are calculated with the designed software, and the robot is informed about the position where it will take part. The robot, which receives the information, takes the produced part on the belt conveyor and shows it to high-resolution cameras for quality control. Measurement processes are carried out with a maximum error of 20 microns determined by the experiments.

Keywords: quality control, industry 4.0, image processing, automated fault detection, digital visual inspection

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Authors: Ramesh Joshi, Nisha Khatik

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Murraya koenigii (L.) Spreng locally known as “Curry patta” or “Meetha neem” belonging to the family Rutaceae that grows wildly in Southern Asia. Its aromatic leaves are commonly used as the raw material for traditional medicinal formulations in India. The leaves contain essential oil and also used as a condiment. Several monomeric and binary carbazol alkaloids present in the various plant parts. These alkaloids have been reported to possess anti-microbial, mosquitocidal, topo-isomerase inhibition and antioxidant properties. Some of the alkaloids reported in this plant have showed anti carcinogenic and anti-diabetic properties. The conventional method of propagation of this tree is limited to seeds only, which retain their viability for only a short period. Hence, a biotechnological approach might have an advantage edging over traditional breeding as well as the genetic improvement of M. koenigii within a short period. The development of a reproducible regeneration protocol is the prerequisite for ex situ conservation and micropropagation. An efficient protocol for high frequency regeneration of in vitro plants of Murraya koenigii via different explants such as- nodal segments, intermodal segments, leaf, root segments, hypocotyle, cotyledons and cotyledonary node explants is described. In the present investigation, assessment of clonal fidelity in the micropropagated plantlets of Murraya koenigii was attempted using RAPD and ISSR markers at different pathways of plant tissue culture technique. About 20 ISSR and 40 RAPD primers were used for all the samples. Genomic DNA was extracted by CTAB method. ISSR primer were found to be more suitable as compared to RAPD for the analysis of clonal fidelity of M. koenigii. The amplifications however, were finally performed using RAPD, ISSR markers owing to their better performance in terms of generation of amplification products. In RAPD primer maximum 75% polymorphism was recorded in OPU-2 series which exhibited out of 04 scorable bands, three bands were polymorphic with a band range of size 600-1500 bp. In ISSR primers the UBC 857 showed 50% polymorphism with 02 band were polymorphic of band range size between 400-1000 bp.

Keywords: genetic fidelity, Murraya koenigii, aromatic plants, ISSR primers

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Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

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Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, condition monitoring, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Kaan Karaoglu, Raif Bayir

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In this study, a cartesian robot is developed to improve the performance and efficiency of wireless charging of electric vehicles. The cartesian robot has three axes, each of which moves linearly. Magnetic positioning is used to align the cartesian robot transmitter charging pad. There are two different wireless charging methods, static and dynamic, for charging electric vehicles. The current state of charge information (SOC State of Charge) and location information are received wirelessly from the electric vehicle. Based on this information, the power to be transmitted is determined, and the transmitter and receiver charging pads are aligned for maximum efficiency. With this study, a fully automated cartesian robot structure will be used to charge electric vehicles with the highest possible efficiency. With the wireless communication established between the electric vehicle and the charging station, the charging status will be monitored in real-time. The cartesian robot developed in this study is a fully automatic system that can be easily used in static wireless charging systems with vehicle-machine communication.

Keywords: electric vehicle, wireless charging systems, energy efficiency, cartesian robot, location detection, trajectory planning

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Authors: Tianyang Xu

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Small underwater targets generally have a non-centrosymmetric geometry, and the acoustic scattering field of the target has spatial inhomogeneity under active sonar detection conditions. In view of the above problems, this paper takes the hemispherical cylindrical shell as the research object, and considers the angle continuity implied in the echo characteristics, and proposes a cluster-driven research method for the non-uniform characteristics of target echo angle. First, the target echo features are extracted, and feature vectors are constructed. Secondly, the t-SNE algorithm is used to improve the internal connection of the feature vector in the low-dimensional feature space and to construct the visual feature space. Finally, the implicit angular relationship between echo features is extracted under unsupervised condition by cluster analysis. The reconstruction results of the local geometric structure of the target corresponding to different categories show that the method can effectively divide the angle interval of the local structure of the target according to the natural acoustic scattering characteristics of the target.

Keywords: underwater target;, non-uniform characteristics;, cluster-driven method;, acoustic scattering characteristics

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Authors: Alemayehu Hailemicael Mezgebe, A. J. Solomon Raju

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Context: Lake Chamo is a significant lake in the Ethiopian Rift Valley, known for its diversity of wildlife and vegetation. However, the lake is facing various threats due to human activities and global effects. The poor management of resources could lead to food insecurity, ecological degradation, and loss of biodiversity. Research Aim: The aim of this study is to analyze the environmental implications of lake level changes using GIS and remote sensing. The research also aims to examine the floristic composition of the lakeside vegetation and propose spatially oriented environmental planning for the sustainable utilization of the biodiversity resources. Methodology: The study utilizes multi-temporal satellite images and aerial photographs to analyze the changes in the lake area over the past 45 years. Geospatial analysis techniques are employed to assess land use and land cover changes and change detection matrix. The composition and role of the lakeside vegetation in the ecological and hydrological functions are also examined. Findings: The analysis reveals that the lake has shrunk by 14.42% over the years, with significant modifications to its upstream segment. The study identifies various threats to the lake-wetland ecosystem, including changes in water chemistry, overfishing, and poor waste management. The study also highlights the impact of human activities on the lake's limnology, with an increase in conductivity, salinity, and alkalinity. Floristic composition analysis of the lake-wetland ecosystem showed definite pattern of the vegetation distribution. The vegetation composition can be generally categorized into three belts namely, the herbaceous belt, the legume belt and the bush-shrub-small trees belt. The vegetation belts collectively act as different-sized sieve screen system and calm down the pace of incoming foreign matter. This stratified vegetation provides vital information to decide the management interventions for the sustainability of lake-wetland ecosystem.Theoretical Importance: The study contributes to the understanding of the environmental changes and threats faced by Lake Chamo. It provides insights into the impact of human activities on the lake-wetland ecosystem and emphasizes the need for sustainable resource management. Data Collection and Analysis Procedures: The study utilizes aerial photographs, satellite imagery, and field observations to collect data. Geospatial analysis techniques are employed to process and analyze the data, including land use/land cover changes and change detection matrices. Floristic composition analysis is conducted to assess the vegetation patterns Question Addressed: The study addresses the question of how lake level changes and human activities impact the environmental health and biodiversity of Lake Chamo. It also explores the potential opportunities and threats related to water utilization and waste management. Conclusion: The study recommends the implementation of spatially oriented environmental planning to ensure the sustainable utilization and maintenance of Lake Chamo's biodiversity resources. It emphasizes the need for proper waste management, improved irrigation facilities, and a buffer zone with specific vegetation patterns to restore and protect the lake outskirt.

Keywords: buffer zone, geo-spatial, lake chamo, lake level changes, sustainable utilization

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Authors: Sutida Maneeanakekul, Dusit Wechakit, Somsak Piriyayota

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Coastal erosion is a major problem in Thailand, in both the Gulf of Thailand and the Andaman Sea coasts. According to the Department of Marine and Coastal Resources, land erosion occurred along the 200 km coastline with an average rate of 5 meters/year. Coastal erosion affects public and government properties, as well as the socio-economy of the country, including emigration in coastal communities, loss of habitats, and decline in fishery production. To combat the problem of coastal erosion, projects utilizing bamboo sticks for coastal defense against erosion were carried out in 5 areas beginning in November, 2010, including: Pak Klong Munharn- Samut Songkhram Province; Ban Khun Samutmaneerat, Pak Klong Pramong and Chao Matchu Shrine-Samut Sakhon Province,and Pak Klong Hongthong – Chachoengsao Province by Marine and Coastal Resources Department. In 2012, an evaluation of the effectiveness of solving the problem of coastal erosion by using bamboo stick was carried out, with a focus on three aspects. Firstly, the change in physical and biological features after using the bamboo stick technique was assessed. Secondly, participation of people in the community in the way of managing the problem of coastal erosion were these aspects evaluated as part of the study. The last aspect that was evaluated is the satisfaction of the community toward this technique. The results of evaluation showed that the amounts of sediment have dramatically changed behind the bamboo sticks lines. The increase of sediment was found to be about 23.50-56.20 centimeters (during 2012-2013). In terms of biological aspect, there has been an increase in mangrove forest areas, especially at Bang Ya Prak, Samut Sakhon Province. Average tree density was found to be about 4,167 trees per square meter. Additionally, an increase in production of fisheries was observed. Presently, the change in the evaluated physical features tends to increase in every aspect, including the satisfaction of people in community toward the process of solving the erosion problem. People in the community are involved in the preparatory, operation, monitoring and evaluation process to resolve the problem in the medium levels.

Keywords: bamboo sticks, coastal erosion, rehabilitate, Thailand sustainable development approach

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Authors: Emma R. Arakelova, Stepan G. Grigoryan, Flora G. Arsenyan, Nelli S. Babayan, Ruzanna M. Grigoryan, Natalia K. Sarkisyan

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Novel nanosize zinc oxide composites of doxorubicin obtained by deposition of 180 nm thick zinc oxide film on the drug surface using DC-magnetron sputtering of a zinc target in the form of gels (PEO+Dox+ZnO and Starch+NaCMC+Dox+ZnO) were studied for drug delivery applications. The cancer specificity was revealed both in in vitro and in vivo models. The cytotoxicity of the test compounds was analyzed against human cancer (HeLa) and normal (MRC5) cell lines using MTT colorimetric cell viability assay. IC50 values were determined and compared to reveal the cancer specificity of the test samples. The mechanistic study of the most active compound was investigated using Flow cytometry analyzing of the DNA content after PI (propidium iodide) staining. Data were analyzed with Tree Star FlowJo software using cell cycle analysis Dean-Jett-Fox module. The in vivo anticancer activity estimation experiments were carried out on mice with inoculated ascitic Ehrlich’s carcinoma at intraperitoneal introduction of doxorubicin and its zinc oxide compositions. It was shown that the nanosize zinc oxide film deposition on the drug surface leads to the selective anticancer activity of composites at the cellular level with the range of selectivity index (SI) from 4 (Starch+NaCMC+Dox+ZnO) to 200 (PEO(gel)+Dox+ZnO) which is higher than that of free Dox (SI = 56). The significant increase in vivo antitumor activity (by a factor of 2-2.5) and decrease of general toxicity of zinc oxide compositions of doxorubicin in the form of the above mentioned gels compared to free doxorubicin were shown on the model of inoculated Ehrlich's ascitic carcinoma. Mechanistic studies of anticancer activity revealed the cytostatic effect based on the high level of DNA biosynthesis inhibition at considerable low concentrations of zinc oxide compositions of doxorubicin. The results of studies in vitro and in vivo behavior of PEO+Dox+ZnO and Starch+NaCMC+Dox+ZnO composites confirm the high potential of the nanosize zinc oxide composites as a vector delivery system for future application in cancer chemotherapy.

Keywords: anticancer activity, cancer specificity, doxorubicin, zinc oxide

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Amira Shakila Razali, Faridah Lisa Supian, Muhammad Mat Salleh, Suriani Abu Bakar

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Water contamination by toxic compound is one of the serious environmental problems today. These toxic compounds mostly originated from industrial effluents, agriculture, natural sources and human waste. These study are focused on modification of multiwalled carbon nanotube (MWCNTs) with nanoparticle of calixarene and explore the possibility of using this nanocomposites for the remediation of cadmium in water. The nanocomposites were prepared by dissolving calixarene in chloroform solution as solvent, followed by additional multiwalled carbon nanotube (MWCNTs) then sonication process for 3 hour and fabricated the nanocomposites on substrate by spin coating method. Finally, the nanocomposites were tested on cadmium ion (10 mg/ml). The morphology of nanocomposites was investigated by FESEM showing the formation of calixarene on the outer walls of carbon nanotube and cadmium ion also clearly seen from the micrograph. This formation was supported by using energy dispersive x-ray (EDX). The presence of cadmium ions in the films, leads to some changes in the surface potential and Fourier Transform Infrared spectroscopy (FTIR).This nanocomposites have potential for development of sensor for pollutant monitoring and nanoelectronics devices applications

Keywords: calixarene, multiwalled carbon nanotubes, cadmium, surface potential

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

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Authors: Juhi Kaushik, Abhishek Agarwal, Manoj Sarda, Vatsal Sanjay, Arup Kumar Das

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Fire accidents in trains bring huge disaster to human life and property. Evacuation becomes a major challenge in such incidents owing to confined spaces, large passenger density and trains moving at high speeds. The pantry car in Indian Railways trains carry inflammable materials like cooking fuel and LPG and electrical fittings. The pantry car is therefore highly susceptible to fire accidents. Numerical simulations have been done in a pantry car of Indian locomotive train using computational fluid dynamics based software. Different scenarios of a fire outbreak have been explored by varying Heat Release Rate per Unit Area (HRRPUA) of the fire source, introduction of exhaust in the cooking area, and taking a case of an air conditioned pantry car. Temporal statures of flame and soot have been obtained for each scenario and differences have been studied and reported. Inputs from this study can be used to assess casualties in fire accidents in locomotive trains and development of smoke control/detection systems in Indian trains.

Keywords: fire propagation, flame contour, pantry fire, soot flow

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

Abstract:

This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Maryam Kiani

Abstract:

The self-sensing capability opens up new possibilities for structural health monitoring, offering real-time information on the condition and performance of constructions. The synthesis and characterization of these functional 2D material geopolymers will be explored in this study. Various fabrication techniques, including mixing, dispersion, and coating methods, will be employed to ensure uniform distribution and integration of the 2D materials within the geopolymers. The resulting composite materials will be evaluated for their mechanical strength, electrical conductivity, and sensing capabilities through rigorous testing and analysis. The potential applications of these self-sensing geopolymers are vast. They can be used in infrastructure projects, such as bridges, tunnels, and buildings, to provide continuous monitoring and early detection of structural damage or degradation. This proactive approach to maintenance and safety can significantly improve the lifespan and efficiency of constructions, ultimately reducing maintenance costs and enhancing overall sustainability. In conclusion, the development of functional 2D material geopolymers as self-sensing materials presents an exciting advancement in the construction industry. By integrating these innovative materials into structures, we can create a new generation of intelligent, self-monitoring constructions that can adapt and respond to their environment.

Keywords: 2D materials, geopolymers, electrical properties, self-sensing

Procedia PDF Downloads 137

Authors: Wael Khalil, Elias Rahal, Ghassan Matar

Abstract:

Tooth related infections or commonly named dental infections have been described as the most common causes of tooth loss in adults. These pathologies were mostly periodontitis, pericoronitis, and periapical infection. The involvement of various bacteria in the pathogenesis of these pathologies has been thoroughly mentioned and approved in the literature. However, the variability in the severity and prognosis of these lesions among patients suggests the association of other pathogens, like viruses and fungi, in the pathogenesis of these lesions. Several studies in the literature investigated the association of multiple viruses and fungi with the above-mentioned lesions, yet, a vast controversy was reached concerning this subject.Aim: Our study aims to fill the gap in the literature concerning the contribution of adenovirus, HPV-16, EBV, fungi, and candida in the pathogenesis of periodontitis, pericoronitis, and periapical infection. For this purpose, we utilized the quantitative PCR for pathogen detection in saliva, gingival, and lesions samples of involved subjects. Results: Some of these pathogens appeared to have an association with the investigated dental pathologies, while others showed no contribution to the pathogenesis of these lesions. Further investigation is required in order to identify the subtype of the involved pathogens in these tooth related oral pathology.

Keywords: periodontitis, pericoronitis, dental abscess, PCR, microbiology

Procedia PDF Downloads 101

Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

Abstract:

The present study deals with the selection of the most suitable quantitative structure-retention relationship (QSRR) models which should be used in prediction of the retention behavior of basic, neutral, acidic and phenolic pesticides which belong to different classes: fungicides, herbicides, metabolites, insecticides and plant growth regulators. Sum of ranking differences (SRD) approach can give a different point of view on selection of the most consistent QSRR model. SRD approach can be applied not only for ranking of the QSRR models, but also for detection of similarity or dissimilarity among them. Applying the SRD analysis, the most similar models can be found easily. In this study, selection of the best model was carried out on the basis of the reference ranking (“golden standard”) which was defined as the row average values of logarithm of retention time (logtr) defined by high performance liquid chromatography (HPLC). Also, SRD analysis based on experimental logtr values as reference ranking revealed similar grouping of the established QSRR models already obtained by hierarchical cluster analysis (HCA).

Keywords: chemometrics, chromatography, pesticides, sum of ranking differences

Procedia PDF Downloads 375

Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

Abstract:

The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

Procedia PDF Downloads 173

Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

Abstract:

Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

Procedia PDF Downloads 265