Search results for: RGB channel extraction

Authors: Hasna Soli

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The main objective of this work is the extraction of sulfur from gypsum here is industrial waste. Indeed the sulfuric acid production, passing through the following process; melting sulfur, filtration of the liquid sulfur, sulfur combustion to produce SO₂, conversion of SO₂ to SO₃ and SO₃ absorption in water to produce H₂SO₄ product as waste CaSO₄ the anhydrous calcium sulfate. The main objectives of this work are improving the industrial practices and to find other ways to manage these solid wastes. It should also assess the consequences of treatment in terms of training and become byproducts. Firstly there will be a characterization of this type of waste by an X-ray diffraction; to obtain phase solid compositions and chemical analysis; gravimetrically and atomic absorption spectrometry or by ICP. The samples are mineralized in suitable acidic or basic solutions. The elements analyzed are CaO, Sulfide (SO₃), Al₂O₃, Fe₂O₃, MgO, SiO₂. Then an analysis by EDS energy dispersive spectrometry using an Oxford EDX probe and differential thermal and gravimetric analyzes. Gypsum’s valuation will be performed. Indeed, the CaSO₄ will be reused to produce sulfuric acid, which will be reintroduced into the production line. The second approach explored in this work is the thermal utilization of solid waste to remove sulfur as a dilute sulfuric acid solution.

Keywords: environment, gypsum, sulfur, waste

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Authors: K. Thakkar, C. Ghenai

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An integrated modeling approach was used in this study to (1) track energy consumption, production, and resource extraction, (2) track greenhouse gases emissions and (3) analyze emissions for local and regional air pollutions. The model was used in this study for short and long term energy and GHG emissions reduction analysis for the state of Florida. The integrated modeling methodology will help to evaluate the alternative energy scenarios and examine emissions-reduction strategies. The mitigation scenarios have been designed to describe the future energy strategies. They consist of various demand and supply side scenarios. One of the GHG mitigation scenarios is crafted by taking into account the available renewable resources potential for power generation in the state of Florida to compare and analyze the GHG reduction measure against ‘Business As Usual’ and ‘Florida State Policy’ scenario. Two more ‘integrated’ scenarios, (‘Electrification’ and ‘Efficiency and Lifestyle’) are crafted through combination of various mitigation scenarios to assess the cumulative impact of the reduction measures such as technological changes and energy efficiency and conservation.

Keywords: energy planning, climate change mitigation assessment, integrated modeling approach, energy alternatives, and GHG emission reductions

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Authors: P. Saee, Baiju Gopal

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YouTube has seen a surge in the recent years in the number of creators opening up about their mental illness on the video-sharing platform. In documenting their mental health, YouTubers perform an identity of their mental illness in the online world. Identity performance is a theory under identity research that has been readily applied to illness narratives and internet studies. Furthermore, in India, suffering from mental illnesses is regarded with stigma, making the act of taking mental health from a personal to a public space on YouTube a phenomenon worth exploring. Thus, the aim of this paper is to analyse the mental illness narratives of Indian YouTubers for understanding its performance in the virtual world. For this purpose, thematic narrative analysis on the interviews of four Indian YouTubers was conducted. This data was synthesized with analysis of the videos the YouTubers had uploaded on their channel sharing about their mental illness. The narratives of the participants shed light on two significant presentations that they engage in: (a) the identity of a survivor/fighter and (b) the identity of a silent sufferer. Further, the participants used metaphors to describe their illness, thereby co-constructing a corresponding identity based on their particular metaphors. Lastly, the process of bringing mental illness from back stage to front stage on YouTube involves a shift in the audience, from being rejecting and invalidating in real life to being supportive and encouraging in the virtual space. Limitations and implications for future research were outlined.

Keywords: cyber-psychology, internet, media, mental health, mental illness, technology

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Authors: Jiajia Yao, Guanlin Wu, Fang Liu, Junshuai Xue, Yue Hao

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As the production process of self-standing GaN substrates evolves, the commercialization of low dislocation density, large-scale, semi-insulating self-standing GaN substrates is gradually becoming a reality. This advancement has given rise to increased interest in GaN materials' homoepitaxial technology. However, at the homoepitaxial interface, there are considerable concentrations of impurity elements, including C, Si, and O, which generate parasitic leakage channels at the re-growth junction. This phenomenon results in leaked HEMTs that prove difficult to switch off, rendering them effectively non-functional. The emergence of leakage channels can also degrade the high-frequency properties and lower the power devices' breakdown voltage. In this study, the uniform epitaxy of AlGaN/GaN heterojunction with high electron mobility was accomplished through the surface treatment of the GaN substrates prior to growth and the design of the AlN isolation layer structure. By employing a procedure combining gallium atom in-situ cleaning and plasma nitridation, the C and O impurity concentrations at the homoepitaxial interface were diminished to the scale of 10¹⁷ cm-³. Additionally, the 1.5 nm nitrogen-rich AlN isolation layer successfully prevented the diffusion of Si impurities into the GaN channel layer. The result was an AlGaN/GaN heterojunction with an electron mobility of 1552 cm²/Vs and an electron density of 1.1 × 10¹³ cm-² at room temperature, obtained on a Fe-doped semi-insulating GaN substrate.

Keywords: MBE, AlGaN/GaN, homogenerous epitaxy, HEMT

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Authors: Khaled Suleiman Mohammed Al-Mashrafi

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A compositional plume is a fluid flow in a directional channel of finite width in another fluid of different material composition. The study of the dynamics of compositional plumes plays an essential role in many real-life applications like industrial applications (e.g., iron casting), environmental applications (e.g., salt fingers and sea ice), and geophysical applications (e.g., solidification at the inner core boundary (ICB) of the Earth, and mantle plumes). The dynamics of compositional plumes have been investigated experimentally and theoretically. The experimental works observed that the plume flow seems to be stable, although some experiments showed that it can be unstable. At the same time, the theoretical investigations showed that the plume flow is unstable. This is found to be true even if the plume is subject to rotation or/and in the presence of a magnetic field and even if another plume of different composition is also present. It is noticeable that all the theoretical studies on the dynamics of compositional plumes are conducted in unbounded domains. The present work is to investigate theoretically the influence of vertical walls (boundaries) on the dynamics of compositional plumes in the absence/presence of a rotation field. The mathematical model of the dynamics of compositional plumes used the equations of continuity, motion, heat, concentration of light material, and state. It is found that the presence of boundaries has a strong influence on the basic state solution as well as the stability of the plume, particularly when the plume is close to the boundary, but the compositional plume remains unstable.

Keywords: compositional plumes, stability, bounded domain, vertical boundaries

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Authors: Farramae Francisco, Rhoda Mae Simora, Sharon Nunal

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Deproteination and demineralization efficiencies of shrimp waste using two Lactobacillus species treated with different carbohydrate sources for chitin production, its chemical conversion to chitosan and the quality of chitin and chitosan produced were determined. Using 5% glucose and 5% cassava starch as carbohydrate sources, pH slightly increased from the initial pH of 6.0 to 6.8 and 7.2, respectively after 24 h and maintained their pH at 6.7 to 7.3 throughout the treatment period. Demineralization (%) in 5 % glucose and 5 % cassava was highest during the first day of treatment which was 82% and 83%, respectively. Deproteination (%) was highest in 5% cassava starch on the 3rd day of treatment at 84.4%. The obtained chitin from 5% cassava and 5% glucose had a residual ash and protein below 1% and solubility of 59% and 44.3%, respectively. Chitosan produced from 5% cassava and 5% glucose had protein content below 0.05%; residual ash was 1.1% and 0.8%, respectively. Chitosan solubility and degree of deacetylation were 56% and 33% in 5% glucose and 48% and 29% in 5% cassava, respectively. The advantage this alternative technology offers over that of chemical extraction is large reduction in chemicals needed thus less effluent production and generation of a protein-rich liquor, although the demineralization process should be improved to achieve greater degree of deacetylation.

Keywords: alternative carbon source, bioprocessing, lactic acid bacteria, waste utilization

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Authors: Diego De Castro Rodrigues, Marcelo B. Nery, Sergio Adorno

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The project aims to develop a framework for social data analysis, particularly by mobilizing criminal records and applying descriptive computational techniques, such as associative algorithms and extraction of tree decision rules, among others. The methods and instruments discussed in this work will enable the discovery of patterns, providing a guided means to identify similarities between recurring situations in the social sphere using descriptive techniques and data visualization. The study area has been defined as the city of São Paulo, with the structuring of social data as the central idea, with a particular focus on the quality of the information. Given this, a set of tools will be validated, including the use of a database and tools for visualizing the results. Among the main deliverables related to products and the development of articles are the discoveries made during the research phase. The effectiveness and utility of the results will depend on studies involving real data, validated both by domain experts and by identifying and comparing the patterns found in this study with other phenomena described in the literature. The intention is to contribute to evidence-based understanding and decision-making in the social field.

Keywords: social data analysis, criminal records, computational techniques, data mining, big data

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Authors: Krasimir Ivanov, Elitsa Kolentsova, Dimitar Dimitrov, Petya Petrova, Tatyana Tabakova

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This work studies the effect of chemical composition on the activity and selectivity of γ–alumina supported CuO/ MnO2/Cr2O3 catalysts toward deep oxidation of CO, dimethyl ether (DME) and methanol. The catalysts were prepared by impregnation of the support with an aqueous solution of copper nitrate, manganese nitrate and CrO3 under different conditions. Thermal, XRD and TPR analysis were performed. The catalytic measurements of single compounds oxidation were carried out on continuous flow equipment with a four-channel isothermal stainless steel reactor. Flow-line equipment with an adiabatic reactor for simultaneous oxidation of all compounds under the conditions that mimic closely the industrial ones was used. The reactant and product gases were analyzed by means of on-line gas chromatographs. On the basis of XRD analysis it can be concluded that the active component of the mixed Cu-Mn-Cr/γ–alumina catalysts consists of at least six compounds – CuO, Cr2O3, MnO2, Cu1.5Mn1.5O4, Cu1.5Cr1.5O4 and CuCr2O4, depending on the Cu/Mn/Cr molar ratio. Chemical composition strongly influences catalytic properties, this influence being quite variable with regards to the different processes. The rate of CO oxidation rapidly decrease with increasing of chromium content in the active component while for the DME was observed the reverse trend. It was concluded that the best compromise are the catalysts with Cu/(Mn + Cr) molar ratio 1:5 and Mn/Cr molar ratio from 1:3 to 1:4.

Keywords: Cu-Mn-Cr oxide catalysts, volatile organic compounds, deep oxidation, dimethyl ether (DME)

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Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

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Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment

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Authors: Salah Hassab Elnaby, Omnia Hamdy, Aziza Ahmed Hassan, Salwa Abdelkawi, Ibrahim Abdelhalim

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Laser corneal reshaping has been proposed as a successful treatment of many refraction disorders. However, some physical and chemical demonstrations of the laser effect upon interaction with the corneal tissue are still not fully explained. Therefore, different computational and mathematical models have been implemented to predict the depth of the ablated channel and calculate the ablation threshold and the local temperature rise. In the current paper, we present a modified model that aims to answer some of the open questions about the ablation threshold, the ablation rate, and the physical and chemical mechanisms of that action. The proposed model consists of three parts. The first part deals with possible photochemical reactions between the incident photons and various components of the cornea (collagen, water, etc.). Such photochemical reactions may end by photo-ablation or just the electronic excitation of molecules. Then a chemical reaction is responsible for the ablation threshold. Finally, another chemical reaction produces fragments that can be cleared out. The model takes into account all processes at the same time with different probabilities. Moreover, the effect of applying different laser wavelengths that have been studied before, namely the common excimer laser (193-nm) and the solid state lasers (213-nm & 266-nm), has been investigated. Despite the success and ubiquity of the ArF laser, the presented results reveal that a carefully designed 213-nm laser gives the same results with lower operational drawbacks. Moreover, the use of mode locked laser could also decrease the risk of heat generation and diffusion.

Keywords: UV lasers, mathematical model, corneal ablation, photochemical ablation

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Authors: Robert Joseph M. Licup

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The deployment of the fifth-generation (5G) mobile system through mmWave frequencies is the new solution in the requirement to provide higher bandwidth readily available for all users. The usage pattern of the mobile users has moved towards either the work from home or online classes set-up because of the pandemic. Previous mobile technologies can no longer meet the high speed, and bandwidth requirement needed, given the drastic shift of transactions to the home. The millimeter-wave (mmWave) underutilized frequency is utilized by the fifth-generation (5G) cellular networks that support multi-gigabit-per-second (Gbps) transmission. However, due to its short wavelengths, high path loss, directivity, blockage sensitivity, and narrow beamwidth are some of the technical challenges that need to be addressed. Different tools, technologies, and scenarios are explored to support network design, accurate channel modeling, implementation, and deployment effectively. However, there is a big challenge on how the consumer will adopt this solution and maximize the benefits offered by the 5G Technology. This research proposes to study the intricacies of technology diffusion, individual attitude, behaviors, and how technology adoption will be attained. The agent based simulation model shaped by the actual applications, technology solution, and related literature was used to arrive at a computational model. The research examines the different attributes, factors, and intricacies that can affect each identified agent towards technology adoption.

Keywords: agent-based model, AnyLogic, 5G O21, 5G mmWave solutions, technology adoption

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Authors: Laurentiu Moruz, Jens Kitzhofer, Mircea Dinulescu

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The paper aims to extend the knowledge about jet behavior and jet interaction between five plane unventilated jets with large aspect ratio (AR). The distance between the single plane jets is two times the channel height. The experimental investigation applies 2D Particle Image Velocimetry (PIV) and static pressure measurements. Our study focuses on the influence of two different outlet nozzle geometries (triangular shape with 2 x 7.5° and blunt geometry) with respect to variation of Reynolds number from 5500 - 12000. It is shown that the outlet geometry has a major influence on the jet formation in terms of uniformity of velocity profiles downstream of the sudden expansion. Furthermore, we describe characteristic regions like converging region, merging region and combined region. The triangular outlet geometry generates most uniform velocity distributions in comparison to a blunt outlet nozzle geometry. The blunt outlet geometry shows an unstable behavior where the jets tend to attach to one side of the walls (ceiling) generating a large recirculation region on the opposite side. Static pressure measurements confirm the observation and indicate that the recirculation region is connected to larger pressure drop.

Keywords: 2D particle image velocimetry, parallel jet interaction, pressure drop, sudden expansion

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Authors: Devarakonda Ramadevi, Dasari Rambabu, K. Suresh Babu, Battu Ganga Rao, Lakshmi Sirisha Kotikalapudi

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The phytochemical and biological evaluation of the whole plant of Derris scandens is belonging to the family fabaceae. The dried plant of D.scandens was procured from the tirumala. The completely dried powder of the whole plant was taken and ground to a coarse powder which was then subjected to Soxhlet extraction with hexane and chloroform successively for 36 hrs. Chloroform extract was filtered and concentrated by using rotary evaporator an about 100g extract was obtained. The chloroform extract was subjected to column chromatographed over silicagel. From the column chromatography seven compounds were isolated named as osajin, scandinone, scandenone, 4,5,7-tri hydroxy biprenyl isoflavone, derris isoflavone-A, scandenin and isoscandinone. D.scandens resulting in the isolation of seven compounds in the plant was confirmed by spectral data (1H NMR, 13C NMR, ESI-MS and FTIR). The isolated compounds were screened for antioxidant activity, antidiabetic activity, α-glucosidase (inhibitory activity) and anti-bacterial activity. The isolated seven compounds were tested for α-glucosidase inhibitory activity and antioxidant activity. All the seven compounds showed good α-glucosidase inhibitory activity and moderate antioxidant activity.

Keywords: Derris scandens, phytochemical, antioxident, antidiabetic, antibacterial activity

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Authors: N. Saki, S. Nalbantoglu, M. Akin, G. Arabaci

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Walnut has a great range of phenolic profile and it is used in Asia and Africa for treatment of many diseases and cancer. Phenolic compounds play a number of crucial roles in complex metabolism of plants and of also fruit trees. Consumption of certain phenolics in the food is considered beneficial for human nutrition. Phenolic compounds known as anti-radical inactivators with their high antioxidant activities and these activities play an important role in inhibition of multi-metal corrosion. Many common corrosion inhibitors that are still in use today are health hazards. Therefore, there is still an increased attention directed towards the development of environmentally compatible, nonpolluting corrosion inhibitors. The present study reports the total phenols content, antioxidant potentials and tyrosinase inhibitory activity of the walnut (Juglans regia L.) produced in Turkey. The anti-tyrosinase activity was investigated for walnut at 2 h extraction time and all extracts exhibited tyrosinase activity. The results of this study suggested that walnut can be used as an excellent, easily accessible source of natural antioxidant.

Keywords: antioxidant activity, Juglans Regia, total phenols, tyrosinase activity

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Authors: Pratham Madnur, Prathamkumar Shetty, Sneha Varur, Gouri Parashetti

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In order to overcome conventional obstacles, this research paper investigates novel approaches for cricket pitch and ball detection that make use of cutting-edge technologies. The research integrates OpenCV for pitch inspection and modifies the YOLOv8 model for cricket ball detection in order to overcome the shortcomings of manual pitch assessment and traditional ball detection techniques. To ensure flexibility in a range of pitch environments, the pitch detection method leverages OpenCV’s color space transformation, contour extraction, and accurate color range defining features. Regarding ball detection, the YOLOv8 model emphasizes the preservation of minor object details to improve accuracy and is specifically trained to the unique properties of cricket balls. The methods are more reliable because of the careful preparation of the datasets, which include novel ball and pitch information. These cutting-edge methods not only improve cricket analytics but also set the stage for flexible methods in more general sports technology applications.

Keywords: OpenCV, YOLOv8, cricket, custom dataset, computer vision, sports

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Authors: Shymaa S. Zaher, Howayda Abd El-Hady, Nehad Khalifa

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Lake Nasser is vital to Egypt as it is the main Nile water reservoir. One of the major challenges in ecological flood is to establish how environmental enrichment in nutrients availability may affect both the biochemical composition of phytoplankton and the species communities. Samples were collected from twenty sites representing different lake sectors along the main channel of the lake during 2017. Generally, phytoplankton distribution during flood season in Lake Nasser indicates the predominance of Cyanophyceae at all lake sectors. Increases in NO₂ (9.31 µg/l) and PO₄ (7.11µg/l) at the Abu-Simble sector are associated with changes in community structure and biochemical composition of phytoplankton, where Cyanophyceae blooming occur associated with retardation in biopolymeric particulate organic carbon. The maximum total biochemical contents (91.29 mg/l) and biopolymeric particulate organic carbon (37.15 mg/l) was found at El-Madiq sector where there was optimum nutrients (NO₂ 0.479 µg/l and PO₄ 5.149µg/l), a highly positive correlation was found between Cyanophyceae and NO₂ in the lake (r = 0.956). A highly positive correlation was detected between carbohydrates and both transparency and pH in the lake (r = 0.974 and 0.787). Also carbohydrates had a positive relation with Bacillariophyceae (r = 0.610). Flood positively alter the water quality of the lake by increasing dissolved oxygen and nutrients enrichment to the aquatic ecosystem, affecting other aquatic organisms of higher trophic levels as economic fishes inhabiting the lake.

Keywords: aquatic microalgae, Aswan high dam lake, biochemical composition, fresh water

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Authors: Zahia Aliche, Fatiha Boudjema, Benyoucef Khelidj, Selma Mettai, Zohra Bouriahi, Saliha Mohammed Belkebir, Ridha Mazouz

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The purpose of this work is the study of the viscoelastic behaviour formulating gels based plant extractions. The extracts of Zingibar officinale and Cinnamomum cassia were included in the gel at different concentrations of these plants in order to be applied in anti-inflammatory drugs. The yield of ethanolic extraction of Zingibar o. is 3.98% and for Cinnamomum c., essential oil by hydrodistillation is 1.67 %. The ethanolic extract of Zingibar.o, the essential oil of Cinnamomum c. and the mixture showed an anti-DPPH radicals’ activity, presented by EC50 values of 11.32, 13.48 and 14.39 mg/ml respectively. A gel based on different concentrations of these extracts was prepared. Microbiological tests conducted against Staphylococcus aureus and Escherichia colishowed moderate inhibition of Cinnamomum c. gel and less the gel based on Cinnamomum c./ Zingibar o. (20/80). The yeast Candida albicansis resistant to gels. The viscoelastic formulation property was carried out in dynamic and creep and modeled with the Kelvin-Voigt model. The influence of some parameters on the stability of the gel (time, temperature and applied stress) has been studied.

Keywords: Cinnamomum cassia, Zingibar officinale, antioxidant activity, antimicrobien activity, gel, viscoelastic behaviour

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: A. Asgharzadeh, M. Maroufi

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5G mobile communication system has drawn more and more attention. The 5G system needs to provide three different types of services, including enhanced Mobile BroadBand (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communication (URLLC). Universal Filtered Multi-Carrier (UFMC), Filter Bank Multicarrier (FBMC), and Filtered Orthogonal Frequency Division Multiplexing (f-OFDM) are suggested as a well-known candidate waveform for the coming 5G system. Themachine-to-machine (M2M) communications are one of the essential applications in 5G, and it involves exchanging of concise messages with a very short latency. However, in UFMC systems, the subcarriers are grouped into subbands but f-OFDM only one subband covers the entire band. Furthermore, in FBMC, a subband includes only one subcarrier, and the number of subbands is the same as the number of subcarriers. This paper mainly discusses the performance of UFMC with different parameters for the UFMC system. Also, paper shows that UFMC is the best choice outperforming OFDM in any case and FBMC in case of very short packets while performing similarly for long sequences with channel estimation techniques for Interleave Division Multiple Access (IDMA) systems.

Keywords: universal filtered multi-carrier technique, UFMC, interleave division multiple access, IDMA, fifth-generation, subband

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Authors: Houria Hamitouche, Abdellah Khelifa

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Quaternary ammonium salts (QACs) are the most common cationic surfactants of natural or synthetic origin usually. They possess one or more hydrophobic hydrocarbon chains and hydrophilic cationic group. In fact, the hydrophobic groups are derived from three main sources: petrochemicals, vegetable oils, and animal fats. These QACs have attracted the attention of chemists for a long time, due to their general simple synthesis and their broad application in several fields. They are important as ingredients of cosmetic products and are also used as corrosion inhibitors, in emulsion polymerization and textile processing. Within biological applications, QACs show a good antimicrobial activity and can be used as medicines, gene delivery agents or in DNA extraction methods. The 2004 worldwide annual consumption of QACs was reported as 500,000 tons. The petroleum product is considered a true reservoir of a variety of chemical species, which can be used in the synthesis of quaternary ammonium salts. The purpose of the present contribution is to synthesize the quaternary ammonium salts by Menschutkin reaction, via chloromethylation/quaternization sequences, from Algerian petroleum products namely: reformate, light naphtha and kerosene and characterize.

Keywords: quaternary ammonium salts, reformate, light naphtha, kerosene

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Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

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Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Pawandeep Kaur, Prashant Garg

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Red mud is a byproduct of aluminum extraction from Bauxite industry. It is dumped in a pond which not only uses thousands of acres of land but having very high pH, it pollutes the ground water and the soil also. Leaves are yet another big waste especially during autumn when they contribute immensely to the blockage of drains and can easily catch fire, among other risks hence also needs to be utilized effectively. The use of leaf ash and red mud in highway construction as a filling material may be an efficient way to dispose of leaf ash and red mud. In this study, leaf ash and lime were used as admixtures to improve the geotechnical engineering properties of red mud. The red mud was taken from National Aluminum Company Limited, Odisha, and leaf ash was locally collected. The aim of present study is to investigate the effect of lime and leaf ash on compaction characteristics and strength characteristics of red mud. California Bearing Ratio and Unconfined Compression Strength tests were performed on red mud by varying different percentages of lime and leaf ash. Leaf ash was added in proportion 2%,4%,6%,8% and 10% whereas lime was added in proportions of 5% to 15%. Optimized value of lime was decided with respect to maximum CBR (California Bearing Ratio) of red mud mixed with different proportions of lime. An increase of 300% in California Bearing ratio of red mud and an increase of 125% in Unconfined Compression Strength values were observed. It may, therefore, be concluded that red mud may be effectively utilized in the highway industry as a filler material.

Keywords: stabilization, lime, red mud, leaf ash

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Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida

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This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatio-temporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.

Keywords: WSN, database spatio-temporal, GIS, web mapping, indicator of drought

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Authors: Fadilah Aleanizy

Abstract:

Colicins are a family of bacterial toxins that kill Escherichia coli and other closely related species. The mode of action of colicins involves binding to an outer membrane receptor and translocation across the cell envelope, leading to cytotoxicity through specific targets. The mechanism of colicin cytotoxicity includes a non-specific endonuclease activity or depolarization of the cytoplasmic membrane by pore-forming activity. For Group A colicins, translocation requires an interaction between the N-terminal domain of the colicin and a series of membrane- bound and periplasmic proteins known as the Tol system (TolB, TolR, TolA, TolQ, and Pal and the active domain must be translocated through the outer membranes. Protein-protein interactions are intrinsic to virtually every cellular process. The transient protein-protein interactions of the colicin include the interaction with much more complicated assemblies during colicin translocation across the cellular membrane to its target. The potassium release assay detects variation in the K+ content of bacterial cells (K+in). This assays is used to measure the effect of pore-forming colicins such as ColA on an indicator organism by measuring the changes of the K+ concentration in the external medium (K+out ) that are caused by cell killing with a K+ selective electrode. One of the goals of this work is to employ a quantifiable in-vivo method to spot which Tol protein are more implicated in the interaction with colicin A as it is translocated to its target.

Keywords: K+ efflux, Colicin A, Tol-proteins, E. coli

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Authors: Melba D. Horton

Abstract:

Algae are identified as an alternative source of biofuel because of their ubiquitous distribution in aquatic environments. Diatoms are unique forms of algae characterized by silicified cell walls which have gained prominence in various technological applications. Polk County is home to a multitude of ponds and lakes but has not been explored for the presence of diatoms. Considering the condition of the waters brought about by predominant phosphate mining activities in the area, this research was conducted to determine if endemic diatoms are present and explore their potential for low-cost mass production. Using custom-built photobioreactors, water samples from various lakes provided by the Polk County Parks and Recreation and from nearby ponds were used as the source of diatoms together with other algae obtained during collection. Results of the initial culture cycles were successful, but later an overgrowth of other algae crashed the diatom population. Experiments were conducted in the laboratory to tease out some factors possibly contributing to the die-off. Generally, the total biomass declines after two culture cycles and the causative factors need further investigation. The lipid yield is minimum; however, the high frustule production after die-off adds value to the overall benefit of the harvest.

Keywords: diatoms, algae, biofuel, lipid, photobioreactor, frustule

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Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

Abstract:

Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words (BOVW), classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar (PolSAR)

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Authors: Mahdi Rahaie

Abstract:

MicroRNAs are a novel class of small RNAs which regulate gene expression by translational repression or degradation of messenger RNAs. To produce sensitive, simple and cost-effective assays for microRNAs, detection is in urgent demand due to important role of these biomolecules in progression of human disease such as Alzheimer’s, Multiple sclerosis, and some other neurodegenerative diseases. Herein, we report several novel, sensitive and specific microRNA nanobiosensors which were designed based on colorimetric and fluorescence detection of nanoparticles and hybridization chain reaction amplification as an enzyme-free amplification. These new strategies eliminate the need for enzymatic reactions, chemical changes, separation processes and sophisticated equipment whereas less limit of detection with most specify are acceptable. The important features of these methods are high sensitivity and specificity to differentiate between perfectly matched, mismatched and non-complementary target microRNAs and also decent response in the real sample analysis with blood plasma. These nanobiosensors can clinically be used not only for the early detection of neuro diseases but also for every sickness related to miRNAs by direct detection of the plasma microRNAs in real clinical samples, without a need for sample preparation, RNA extraction and/or amplification.

Keywords: hybridization chain reaction, microRNA, nanobiosensor, neurodegenerative diseases

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Authors: Seda Sahin, Emin Akata

Abstract:

Obturator foramen is a specific structure in pelvic bone images and recognition of it is a new concept in medical image processing. Moreover, segmentation of bone structures such as obturator foramen plays an essential role for clinical research in orthopedics. In this paper, we present a novel method to analyze the similarity between the substructures of the imaged region and a hand drawn template, on hip radiographs to detect obturator foramen accurately with integrated usage of Marker-controlled Watershed segmentation and Zernike moment feature descriptor. Marker-controlled Watershed segmentation is applied to seperate obturator foramen from the background effectively. Zernike moment feature descriptor is used to provide matching between binary template image and the segmented binary image for obturator foramens for final extraction. The proposed method is tested on randomly selected 100 hip radiographs. The experimental results represent that our method is able to segment obturator foramens with % 96 accuracy.

Keywords: medical image analysis, segmentation of bone structures on hip radiographs, marker-controlled watershed segmentation, zernike moment feature descriptor

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Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

Abstract:

Super-resolution is the technique of intelligently upscaling images, avoiding artifacts or blurring, and deals with the recovery of a high-resolution image from one or more low-resolution images. Single-image super-resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super-resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based technique remains unknown. Super-resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. This paper aims at investigating the effects of single image super-resolution on Fourier-based and image based methods of scale-up. In this paper, first, generate a training phase of the low-resolution image and high-resolution image to obtain dictionary. In the test phase, first, generate a patch and then difference of high-resolution image and interpolation image from the low-resolution image. Next simulation of the image is obtained by applying convolution method to the dictionary creation image and patch extracted the image. Finally, super-resolution image is obtained by combining the fused image and difference of high-resolution and interpolated image. Super-resolution reduces image errors and improves the image quality.

Keywords: image dictionary creation, image super-resolution, LGE images, patch extraction

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