Search results for: performance properties

Authors: Shahriar Farzam, Maryam Rastgarpour

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Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME).

Keywords: curvelet transform, CBCT, image enhancement, image denoising

Procedia PDF Downloads 294

Authors: Ayliana Dharmawan, Heng Yong Sheng, Zhang Xiaojin, Tan Thai Lian

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To facilitate discharge planning, doctors are presently required to assign an Estimated Discharge Date (EDD) for each patient admitted to the hospital. This assignment of the EDD is largely based on the doctor’s judgment. This can be difficult for cases which are complex or relatively new to the doctor. It is hypothesized that a data-driven approach would be able to facilitate the doctors to make accurate estimations of the discharge date. Making use of routinely collected data on inpatient discharges between January 2013 and May 2016, a predictive model was developed using machine learning techniques to predict the Length of Stay (and hence the EDD) of inpatients, at the point of admission. The predictive performance of the model was compared to that of the clinicians using accuracy measures. Overall, the best performing model was found to be able to predict EDD with an accuracy improvement in Average Squared Error (ASE) by -38% as compared to the first EDD determined by the present method. It was found that important predictors of the EDD include the provisional diagnosis code, patient’s age, attending doctor at admission, medical specialty at admission, accommodation type, and the mean length of stay of the patient in the past year. The predictive model can be used as a tool to accurately predict the EDD.

Keywords: inpatient, estimated discharge date, EDD, prediction, data-driven

Procedia PDF Downloads 167

Authors: Alirıza Kaleli, M. Akif Ceviz, Erdoğan Güner, Köksal Erentürk

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The cyclic variations in spark ignition engines occurring especially under specific engine operating conditions make the maximum pressure variable for successive in-cylinder pressure cycles. Minimization of cyclic variations has a great importance in effectively operating near to lean limit, or at low speed and load. The cyclic variations may reduce the power output of the engine, lead to operational instabilities, and result in undesirable engine vibrations and noise. In this study, spark timing is controlled in order to reduce the cyclic variations in spark ignition engines. Firstly, an ARMAX model has developed between spark timing and maximum pressure using system identification techniques. By using this model, the maximum pressure of the next cycle has been predicted. Then, self-tuning minimum variance controller has been designed to change the spark timing for consecutive cycles of the first cylinder of test engine to regulate the in-cylinder maximum pressure. The performance of the proposed controller is illustrated in real time and experimental results show that the controller has a reliable effect on cycle to cycle variations of maximum cylinder pressure when the engine works under low speed conditions.

Keywords: cyclic variations, cylinder pressure, SI engines, self tuning controller

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Authors: Zhijun Ren, Zhang Lin, Zhao Ye, Zuo Xiangyu, Mei Dongxing

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As a pretreatment process of ballast water treatment, the performance of high gradient magnetic separation (HGMS) technology for the removal of particulates and microorganisms was studied. The results showed that HGMS process could effectively remove suspended particles larger than 5 µm and had ability to resist impact load. Microorganism could also be effectively removed by HGMS process, and the removal effect increased with increasing magnetic field strength. The maximum removal rates for Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were 4016.1% and 9675.3% higher, respectively, than without the magnetic field. In addition, the superoxide dismutase (SOD) activity of the microbes decreased by 32.2% when the magnetic field strength was 15.4 mT for 72 min. The microstructure of the stainless steel wool was investigated, and the results showed that particle removal by HGMS has common function by the magnetic force of the high-strength, high-gradient magnetic field on weakly magnetic particles in the water, and on the stainless steel wool.

Keywords: HGMS, particulates, superoxide dismutase (SOD) activity, steel wool magnetic medium

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Authors: Sellidj Abdelaziz, Lebaili Soltane

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A cobalt-based alloy type Co-Cr-Ni-WC was deposited by plasma transferred arc projection (PTA) on a stainless steel valve. The alloy is characterized at the equilibrium by a solid solution Co (γ) mainly dendritic, and eutectic carbides M₇C₃ and ηM₆C. At the deposit/substrate interface, this microstructure is modified by the fast cooling mode of the alloy when applied in the liquid state on the relatively cold steel substrate. The structure formed in this case is heterogeneous and metastable phases can occur and evolve over temperature service. Coating properties and reliability are directly related to microstructures formed during deposition. We were interested more particularly in this microstructure formed during the solidification of the deposit in the region of the interface joining the soldered couple and its evolution during cyclic heat treatments at temperatures similar to those of the thermal environment of the valve. The characterization was carried out by SEM-EDS microprobe CAMECA, XRD, and micro hardness profiles. The deposit obtained has a linear and regular appearance that is free of cracks and with little porosity. The morphology of the microstructure represents solidification stages that are relatively fast with a temperature gradient high at the beginning of the interface by forming a plane front solid solution Co (γ). It gradually changes with the decreasing temperature gradient by getting farther from the junction towards the outer limit of the deposit. The matrix takes the forms: cellular, mixed (cells and dendrites) and dendritic. Dendritic growth is done according to primary ramifications in the direction of the heat removal which takes place in the direction perpendicular to the interface, towards the external surface of the deposit, following secondary and tertiary undeveloped arms. The eutectic carbides M₇C₃ and ηM₆C formed are very thin and are located in the intercellular and interdendritic spaces of the solid solution Co (γ).

Keywords: Co-Ni-Cr-W-C alloy, solid deposit, microstructure, carbides, cyclic heat treatment

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Authors: Ajish K. Abraham

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Hearing aid is the most fundamental technology employed towards rehabilitation of persons with sensory neural hearing impairment. Hearing in noise is still a matter of major concern for many hearing aid users and thus continues to be a challenging issue for the hearing aid designers. Several techniques are being currently used to enhance the speech at the hearing aid output. Most of these techniques, when implemented, result in reduction of intelligibility of the speech signal. Thus the dissatisfaction of the hearing aid user towards comprehending the desired speech amidst noise is prevailing. Multichannel Wiener Filter is widely implemented in binaural hearing aid technology for noise reduction. In this study, Wiener filter based noise reduction approach is experimented for a single microphone based hearing aid set up. This method checks the status of the input speech signal in each frequency band and then selects the relevant noise reduction procedure. Results showed that the Wiener filter based algorithm is capable of enhancing speech even when the input acoustic signal has a very low Signal to Noise Ratio (SNR). Performance of the algorithm was compared with other similar algorithms on the basis of improvement in intelligibility and SNR of the output, at different SNR levels of the input speech. Wiener filter based algorithm provided significant improvement in SNR and intelligibility compared to other techniques.

Keywords: hearing aid output speech, noise reduction, SNR improvement, Wiener filter, speech enhancement

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Authors: Ana Serafimovic, Karthik Devarajan

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Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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Authors: Federica Floridi

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The long tradition of contrastive idiom research has essentially been focusing on three domains: the comparison of structural types of idioms (e.g. verbal idioms, idioms with noun-phrase structure, etc.), the description of idioms belonging to the same thematic groups (Sachgruppen), the identification of different types of cross-linguistic equivalents (i.e. full equivalents, partial equivalents, phraseological parallels, non-equivalents). The diastratic, diachronic and diatopic aspects of the compared idioms, as well as their syntactic, pragmatic and semantic properties, have been rather ignored. Corpora (both monolingual and parallel) give the opportunity to investigate the actual use of correlating idioms in authentic texts of L1 and L2. Adopting the corpus-based approach, it is possible to draw attention to the frequency of occurrence of idioms, their syntactic embedding, their potential syntactic transformations (e.g., nominalization, passivization, relativization, etc.), their combinatorial possibilities, the variations of their lexical structure, their connotations in terms of stylistic markedness or register. This paper aims to present the results of a contrastive analysis of Russian and Italian idioms referring to the concepts of ‘beginning’ and ‘end’, that has been carried out by using the Russian National Corpus and the ‘La Repubblica’ corpus. Beyond the digital corpora, bilingual dictionaries, like Skvorcova - Majzel’, Dobrovol’skaja, Kovalev, Čerdanceva, as well as monolingual resources, have been consulted. The study has shown that many of the idioms that have been traditionally indicated as cross-linguistic equivalents on bilingual dictionaries cannot be considered correspondents. The findings demonstrate that even those idioms, that are formally identical in Russian and Italian and are presumably derived from the same source (e.g., conceptual metaphor, Bible, classical mythology, World literature), exhibit differences regarding usage. The ultimate purpose of this article is to highlight that it is necessary to review and improve the existing bilingual dictionaries considering the empirical data collected in corpora. The materials gathered in this research can contribute to this sense.

Keywords: corpora, cross-linguistic equivalence, idioms, Italian, Russian

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Wang Shuen-Tai, Lin Yu-Ching, Chang Hsi-Ya

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Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML 5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Keywords: web-based, workflow, HTML5, Cloud Computing, Queuing System

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Authors: Sodamade Abiodun, Adeboye Olubunmi Omolara

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Problems associated with protein malnutrition are still prevalent in third-world countries, leading to the constant search for plants that can serve as nutrients and medicinal purposes. Huckleberry is one of the plants that has been proven useful locally in the treatment of numerous ailments and diseases. A fresh sample of Huckleberry was collected from a vegetable garden situated near the Erelu dam of the Emmanuel Alayande College of Education campus, Oyo. The sample was authenticated at the forestry research institute of Nigeria (FRIN) Ibadan. The leaves of the plant were plucked and processed for leaf protein concentrates before proximate composition; mineral analysis phytochemical and antimicrobial properties of the leaf protein concentrates were determined using a standard method of analysis. The results of proximate constituents showed; moisture content; 9.89±0.051g/100g, Ash; 3.23±0.12g/100g, crude fat; 3.96±0.11g/100g and 61.27±0.56g/100g of Nitrogen free extractive results of the mineral analysis showed that the sample contains Mg; 0.081±0.00mg/100g, Ca; 42.30±0.05mg/100g, Na; 27.57±0.09mg/100g, K; 6.81±0.01mg/100g, P; 8.90±0.03mg/100g Fe; 0.51±0.00mg/100g, Zn; 0.021±0.00mg/100g, Cd; 0.04±0.04mg/100g, Pb; 0.002±0.00mg/100g, Cr; 0.041±0.00mg/100g while cadmium was not detected in the sample. The result of phytochemical analysis of leaf protein concentrates of the Huckleberry showed the presence of Alkaloid, Saponin, Flavonoid, Tanin, Coumarin, steroid, Terpenoid, cordial glycosides, Glycosides, Quinones, Anthocyanin, phytosterols, and phenols. Ethanolic extracts of the Huckleberry leaf protein concentrates showed that it contains bioactive compounds that are capable of eradicating some tested microorganisms; Staphylococcus aureus, Streptococcus pyogenes, Streptococcus faecalis, Pseudomonas aeruginosa, Klebisidlae pneumonia and Proteus merabilis. The results of the analysis of leaf protein concentrates of Huckleberry showed that the sample contains high nutrient and mineral constituents and phytochemical compounds that could make the sample useful for medicinal activities.

Keywords: huckleberry, mentha piperita, phytochemical, leaf protein concentrates, nutritional characteristics

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Authors: Mahsa Tavakoli, Seyed Mohammad Hojjati, Yahya Kooch

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In this study, the effect of coal mining activities on lead and cadmium concentrations and distribution in soil was investigated in Hyrcanian forest, North Iran. 16 plots (20×20 m²) were established by systematic-randomly (60×60 m²) in an area of 4 ha (200×200 m²-mine entrance placed at center). An area adjacent to the mine was not affected by the mining activity; considered as the controlled area. In order to investigate soil lead and cadmium concentration, one sample was taken from the 0-10 cm in each plot. To study the spatial pattern of soil properties and lead and cadmium concentrations in the mining area, an area of 80×80m² (the mine as the center) was considered and 80 soil samples were systematic-randomly taken (10 m intervals). Geostatistical analysis was performed via Kriging method and GS⁺ software (version 5.1). In order to estimate the impact of coal mining activities on soil quality, pollution index was measured. Lead and cadmium concentrations were significantly higher in mine area (Pb: 10.97±0.30, Cd: 184.47±6.26 mg.kg^-1) in comparison to control area (Pb: 9.42±0.17, Cd: 131.71±15.77 mg.kg^-1). The mean values of the PI index indicate that Pb (1.16) and Cd (1.77) presented slightly polluted. Results of the NIPI index showed that Pb (1.44) and Cd (2.52) presented slight pollution and moderate pollution respectively. Results of variography and kriging method showed that it is possible to prepare interpolation maps of lead and cadmium around the mining areas in Hyrcanian forest. According to results of pollution and risk assessments, forest soil was contaminated by heavy metals (lead and cadmium); therefore, using reclamation and remediation techniques in these areas is necessary.

Keywords: traditional coal mining, heavy metals, pollution indicators, geostatistics, Caspian forest

Procedia PDF Downloads 173

Authors: Yasir M. Alyazichi, Brian G. Jones, Errol McLean, Hamd N. Altalyan, Ali K. M. Al-Nasrawi

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The main purpose of this study is to assess the sediment quality and potential ecological risk in marine sediments in Gymea Bay located in south Sydney, Australia. A total of 32 surface sediment samples were collected from the bay. Current track trajectories and velocities have also been measured in the bay. The resultant trace elements were compared with the adverse biological effect values Effect Range Low (ERL) and Effect Range Median (ERM) classifications. The results indicate that the average values of chromium, arsenic, copper, zinc, and lead in surface sediments all reveal low pollution levels and are below ERL and ERM values. The highest concentrations of trace elements were found close to discharge points and in the inner bay, and were linked with high percentages of clay minerals, pyrite and organic matter, which can play a significant role in trapping and accumulating these elements. The lowest concentrations of trace elements were found to be on the shoreline of the bay, which contained high percentages of sand fractions. It is postulated that the fine particles and trace elements are disturbed by currents and tides, then transported and deposited in deeper areas. The current track velocities recorded in Gymea Bay had the capability to transport fine particles and trace element pollution within the bay. As a result, hydrodynamic measurements were able to provide useful information and to help explain the distribution of sedimentary particles and geochemical properties. This may lead to knowledge transfer to other bay systems, including those in remote areas. These activities can be conducted at a low cost, and are therefore also transferrable to developing countries. The advent of portable instruments to measure trace elements in the field has also contributed to the development of these lower cost and easily applied methodologies available for use in remote locations and low-cost economies.

Keywords: current track velocities, gymea bay, surface sediments, trace elements

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Authors: Soheil Heydari, Ailar Hajimohammadi, Nasser Khalili

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The application of plastic waste for asphalt modification is a sustainable strategy to deal with the enormous plastic waste generated each year and enhance the properties of asphalt. The modification is either practiced by the dry process or the wet process. In the dry process, plastics are added straight into the asphalt mixture, and in the wet process, they are mixed and digested into bitumen. In this article, the effects of plastic inclusion in asphalt mixture, through the dry process, on the permanent deformation of the asphalt are investigated. The main waste plastics that are usually used in asphalt modification are taken into account, which is linear, low-density polyethylene, low-density polyethylene, high-density polyethylene, and polypropylene. Also, to simulate a plastic waste stream, different grades of each virgin plastic are mixed and used. For instance, four different grades of polypropylene are mixed and used as representative of polypropylene. A precisely designed mixing condition is considered to dry-mix the plastics into the mixture such that the polymer was melted and modified by the later introduced binder. In this mixing process, plastics are first added to the hot aggregates and mixed three times in different time intervals, then bitumen is introduced, and the whole mixture is mixed three times in fifteen minutes intervals. Marshall specimens were manufactured, and dynamic creep tests were conducted to evaluate the effects of modification on the permanent deformation of the asphalt mixture. Dynamic creep is a common repeated loading test conducted at different stress levels and temperatures. Loading cycles are applied to the AC specimen until failure occurs; with the amount of deformation constantly recorded, the cumulative, permanent strain is determined and reported as a function of the number of cycles. The results of this study showed that the dry inclusion of the waste plastics is very effective in enhancing the resistance against permanent deformation of the mixture. However, the mixing process must be precisely engineered to melt the plastics, and a homogenous mixture is achieved.

Keywords: permanent deformation, waste plastics, low-density polyethene, high-density polyethene, polypropylene, linear low-density polyethene, dry process

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Authors: Musawira Iftikhar

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The field of membrane materials is the most dynamic due to the constantly evolving requirements advancement of materials, to address challenges such as biocompatibility, protein-bound uremic toxins, blood coagulation, auto-immune responses, oxidative stress, and poor clearance of uremic toxins. Hemodialysis is a membrane filtration processes that is currently necessary for daily living of the patients with ESRD. Tens of millions of people with ESRD have benefited from hemodialysis over the past 60–70 years, both in terms of safeguarding life and a longer lifespan. Beyond challenges associated with the efficiency and separative properties of the membranes, ensuring hemocompatibility, or the safe circulation of blood outside the body for four hours every two days, remains a persistent challenge. This review explores the ongoing field of metal–Organic Frameworks (MOFs) and their applications in hemodialysis, offering a comprehensive examination of various MOFs employed to address challenges inherent in traditional hemodialysis methodologies. this This review included includes the experimental work done with various MOFs as a filler such as UiO-66, HKUST-1, MIL-101, and ZIF-8, which together lead to improved adsorption capacities for a range of uremic toxins and proteins. Furthermore, this review highlights how effectively MOF-based hemodialysis membranes remove a variety of uremic toxins, including p-cresol, urea, creatinine, and indoxyl sulfate and potential filler choices for the future. Future research efforts should focus on refining synthesis techniques, enhancing toxin selectivity, and investigating the long-term durability of MOF-based membranes. With these considerations, MOFs emerge as transformative materials in the quest to develop advanced and efficient hemodialysis technologies, holding the promise to significantly enhance patient outcomes and redefine the landscape of renal therapy.

Keywords: membrane, hemodailysis, metal organic frameworks, seperation, protein adsorbtion

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Authors: Mourad Makhlouf Sabrina Bouriche, Zoubir Benmaamar, Didier Villemin

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Background: The increasing presence of electromagnetic interference (EMI) requires the development of effective protection solutions. Intelligent textiles offer a promising approach due to their wear ability and the possibility of integration into everyday clothing. In this study, the use of graphene and polyaniline for EMI shielding on cotton fabrics was examined. Methods: In this study, the continuous dyeing of recycled graphite-derived graphene and polyaniline was examined. Bottom-reforming technology was adopted to improve adhesion and achieve uniform distribution of conductive material on the fiber surface. The effect of material weight ratio on fabric performance and X-band EMI shielding effectiveness (SE) was evaluated. Significant Findings: The dyed cotton fabrics incorporating graphene, polyaniline, and their combination exhibited improved conductivity. Notably, these fabrics achieved EMI SE values ranging from 9 to 16 dB within the X-band frequency range (8-9 GHz). These findings demonstrate the potential of this approach for developing intelligent textiles with effective EMI shielding capabilities. Additionally, the utilization of recycled materials contributes to a more sustainable shielding solution.

Keywords: Intelligent textiles, graphene, polyaniline, electromagnetic shielding, conductivity, recycling

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Authors: Mohsen Adabi, Mahdi Adabi, Reza Saber

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The recent advancements in nanomaterials have provided a platform to develop efficient transduction matrices for sensors. Modified electrodes allow to electrochemists to enhance the property of electrode surface and provide desired properties such as improved sensing capabilities, higher electron transfer rate and prevention of undesirable reactions competing kinetically with desired electrode process. Nanostructured electrodes including arrays of carbon nanotubes have demonstrated great potential for the development of electrochemical sensors and biosensors. The aim of this work is to evaluate the concentration of multi-walled carbon nanotubes (MWCNTs) on the conductivity of gold electrode. For this work, raw MWCNTs was functionalized and shortened. Raw and shorten MWCNTs were characterized using transfer electron microscopy (TEM). Next, 0.5, 2 and 3.5 mg of Shortened and functionalized MWCNTs were dispersed in 2 mL Dimethyl formamide (DMF) and cysteamine modified gold electrodes were incubated in the different concentrations of MWCNTs for 8 hours. Then, the immobilization of MWCNTs on cysteamine modified gold electrode was characterized by scanning electron microscopy (SEM) and the effect of MWCNT concentrations on electron transfer of modified electrodes was investigated by cyclic voltammetry (CV). The results demonstrated that CV response of ferricyanide redox at modified gold electrodes increased as concentration of MWCNTs enhanced from 0.5 to 2 mg in 2 mL DMF. This increase can be attributed to the number of MWCNTs which enhance on the surface of cysteamine modified gold electrode as the MWCNTs concentration increased whereas CV response of ferricyanide redox at modified gold electrodes did not changed significantly as the MWCNTs concentration increased from 2 to 3.5 mg in 2 mL DMF. The reason may be that amine groups of cysteamine modified gold electrodes are limited to a given number which can interact with the given number of carboxylic groups of MWCNTs and CV response of ferricyanide redox at modified gold do not enhance after amine groups of cysteamine are saturated with carboxylic groups of MWCNTs.

Keywords: carbon nanotube, cysteamine, electrochemical sensor, gold electrode

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Authors: Mohd Moiz Khan, S. M. Mahajani, G. N. Jadhav

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Waste foundry sand (total clay content 15%) contains toxic heavy metals and particulate matter which make dumping of waste sand an environmental and health hazard. Disposal of waste foundry sand (WFS) remains one of the substantial challenges faced by Indian foundries nowadays. To cope up with this issue, the chemical method was used to reclaim WFS. A stirrer tank reactor was used for chemical reclamation. Experiments were performed to reduce the total clay content from 15% to as low as 0.9% in chemical reclamation. This method, although found to be effective for WFS reclamation, it may face a challenge due to the possibly high operating cost. Reclaimed sand was found to be satisfactory in terms of sand qualities such as total clay (0.9%), active clay (0.3%), acid demand value (ADV) (2.6%), loss on igniting (LOI) (3 %), grain fineness number (GFN) (56), and compressive strength (60 kPa). The experimental data generated on chemical reactor under different conditions is further used to optimize the design and operating parameters (rotation speed, sand to acidic solution ratio, acid concentration, temperature and time) for the best performance. The use of reclaimed sand within the foundry would improve the economics and efficiency of the process and reduce environmental concerns.

Keywords: chemical reclamation, clay content, environmental concerns, recycle, waste foundry sand

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Abir Mohamed Mohamed Ibrahim, Amina Titouche, Mohamed Hazzit

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Phytotherapy is based on use of plant natural products holding the main sources of drugs with healing properties for the treatment of human, animal or vegetable diseases. With these aims, and to replace chemical preservatives in natural products, we are interested to use essential oils from Algerian endemic plants belonging to the Asteraceae family: Artemisia herba alba Asso, which was undergoes a hydro-distillation after its irradiation by Gamma rays at frequencies: 10, 20, and 30 KGray which gave respectively the following essential oil yields: 1.087%, 1.087%, 1.085%, compared with that of the untreated sample giving a yield of 1.27 %. Evaluation of the antioxidant activity in vitro of essential oil for A. herba alba has been assessed by two different methods: inhibition of DPPH radical and measurement of reducing power. The first method has not revealed a very big difference regardless of the dose of irradiation, the IC50 is about 4000 mg/l, the maximum of inhibition was around 49.4%, likewise, the test of reducing power awarded us a maximum reducing capacity was of 0.76%; both of results were registered by the specimen irradiated at 20 KGy, it has a more better antioxidant power than no irradiated sample but slightly. To combat Fusarium culmorum, causing the wilts and rots, we are focused on the antifungal screening of this aromatic plant. The results obtained, followed by measurements of Minimal Inhibitory Concentrations (MIC); showed promising inhibitory effect against pathogen tested. With a yield superior to l%, the essential oil has shown a remarkable efficiency on the stump, mainly for sample irradiate at 30KGray (MICs= 625 µg/ml; MICc= 1250 µg/ml) with MIC of 2%. These results demonstrate a good antifungal activity, to limit and even to stop the development of the pathogenic microorganism and also the positive effect of dose of irradiation to upgrade this capacity as well, to uphold the antioxidant capacity.

Keywords: artemisia herba alba Asso, essential oil yield, gamma ray, antioxidant activity, antifungal activity

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Authors: Weihao Wang, Zhulin Zong

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Two-dimensional ordered statistical constant false alarm detection is a widely used method for detecting weak target signals in radar signal processing applications. The method is based on analyzing the statistical characteristics of the noise and clutter present in the radar signal and then using this information to set an appropriate detection threshold. In this approach, the reference cell of the unit to be detected is divided into several reference subunits. These subunits are used to estimate the noise level and adjust the detection threshold, with the aim of minimizing the false alarm rate. By using an ordered statistical approach, the method is able to effectively suppress the influence of clutter and noise, resulting in a low false alarm rate. The detection process involves a number of steps, including filtering the input radar signal to remove any noise or clutter, estimating the noise level based on the statistical characteristics of the reference subunits, and finally, setting the detection threshold based on the estimated noise level. One of the main advantages of two-dimensional ordered statistical constant false alarm detection is its ability to detect weak target signals in the presence of strong clutter and noise. This is achieved by carefully analyzing the statistical properties of the signal and using an ordered statistical approach to estimate the noise level and adjust the detection threshold. In conclusion, two-dimensional ordered statistical constant false alarm detection is a powerful technique for detecting weak target signals in radar signal processing applications. By dividing the reference cell into several subunits and using an ordered statistical approach to estimate the noise level and adjust the detection threshold, this method is able to effectively suppress the influence of clutter and noise and maintain a low false alarm rate.

Keywords: two-dimensional, ordered statistical, constant false alarm, detection, weak target signals

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Authors: Katarzyna Socha, Konrad Mielcarek, Grzegorz Kangowski, Renata Markiewicz-Zukowska, Anna Puscion-Jakubik, Jolanta Soroczynska, Maria H. Borawska

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Nuts have high nutritional value. They are a good source of polyunsaturated fatty acids, dietary fiber, vitamins (B₁, B₆, E, K) and minerals: magnesium, selenium, zinc (Zn). Zn is an essential element for proper functioning and development of human organism. Due to antioxidant and anti-inflammatory properties, Zn has an influence on immunological and central nervous system. It also affects proper functioning of reproductive organs and has beneficial impact on the condition of skin, hair, and nails. The objective of this study was estimation of Zn content in edible nuts. The research material consisted of 10 types of nuts, 12 samples of each type: almonds, brazil nuts, cashews, hazelnuts, macadamia nuts, peanuts, pecans, pine nuts, pistachios, and walnuts. The samples of nuts were digested in concentrated nitric acid using microwave mineralizer (Berghof, Germany). The concentration of Zn was determined by flame atomic absorption spectrometry method with Zeeman background correction (Hitachi, Japan). The accuracy of the method was verified on certified reference material: Simulated Diet D. The statistical analysis was performed using Statistica v. 13.0 software. For comparison between the groups, t-Student test was used. The highest content of Zn was shown in pine nuts and cashews: 78.57 ± 21.9, 70.02 ± 10,2 mg/kg, respectively, significantly higher than in other types of nuts. The lowest content of Zn was found in macadamia nuts: 16.25 ± 4.1 mg/kg. The consumption of a standard 42-gram portion of almonds, brazil nuts, cashews, peanuts, pecans, and pine nuts covers the daily requirement for Zn above 15% of recommended daily allowances (RDA) for women, while in the case of men consumption all of the above types of nuts, except peanuts. Selected types of nuts can be a good source of Zn in the diet.

Keywords: atomic absorption spectrometry, microelement, nuts, zinc

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Authors: Wiwin Tyas Istikowati, Futoshi Ishiguri, Haruna Aisho, Budi Sutiya, Imam Wahyudi, Kazuya Iizuka, Shinso Yokota

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The objective of this study was to investigate the anatomical characteristics of three native fast-growing species, terap (Artocarpus elasticus Reinw. ex Blume), medang (Neolitsea latifolia (Blume) S. Moore), and balik angin (Alphitonia excelsa (Fenzel) Reissek ex Benth) growing in the secondary forest in South Kalimantan, Indonesia for evaluating the possibility of tree breeding for wood quality. Cell lengths were investigated for 5 trees in each species at several different height positions (1.0, 3.0, 5.0, 7.0, 9.0, and 11.0 m above the ground). The mean values of fiber and vessel element lengths in terap, medang, and balik angin were 1.52 and 0.44, 1.16 and 0.53, and 1.02 and 0.49 mm, respectively. Fiber length in terap and balik angin gradually increased from pith to bark, whereas it increased up to 2 cm and then became nearly constant to the bark in medang. Vessel element length was almost constant from pith to bark in terap and balik angin, while slightly increased from pith to bark in medang. Fiber length in terap has a fluctuation pattern from ground level to top of the tree. It decreased up to 3 m above the ground, increased up to 5 m, and then decreased to the top of the tree. On the other hand, vessel element length slightly increased up to 5 m above the ground, and then decreased to the top of the tree. Both fiber and vessel element lengths in medang were almost constant from ground level to top of the tree, whereas decreased from ground level to top of the tree in balik angin. Significant difference at 1% level among trees was found in both fiber and vessel element length in both radial and longitudinal directions for terap and medang. Based on obtained results, it is concluded that the wood quality in fiber and vessel element lengths of terap and medang can be improved by tree breeding programs.

Keywords: anatomical properties, fiber length, vessel elements length, fast-growing species

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Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon

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In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.

Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt

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Authors: Chia-Lin Tu

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Towards the end of the 20th century, a reductive picture has dominated in philosophy of science and philosophy of mind. Reductive physicalism claims that all entities and properties in this world are eventually able to be reduced to the physical level. It means that all phenomena in the world are able to be explained by laws of physics. However, quantum physics provides another picture. It says that the world is undergoing change and the energy of change is, in fact, the most important part to constitute world phenomena. Quantum physics provides us another point of view to reconsider the reality of the world. Throughout the history of philosophy of mind, reductive physicalism tries to reduce the conscious phenomena to physical particles as well, meaning that the reality of consciousness is composed by physical particles. However, reductive physicalism is unable to explain conscious phenomena and mind-body causation. Conscious phenomena, e.g., qualia, is not composed by physical particles. The current popular theory for consciousness is emergentism. Emergentism is an ambiguous concept which has not had clear idea of how conscious phenomena are emerged by physical particles. In order to understand the emergence of conscious phenomena, it seems that quantum physics is an appropriate analogy. Quantum physics claims that physical particles and processes together construct the most fundamental field of world phenomena, and thus all natural processes, i.e., wave functions, have occurred within. The traditional space-time description of classical physics is overtaken by the wave-function story. If this methodology of quantum physics works well to explain world phenomena, then it is not necessary to describe the world by the idea of physical particles like classical physics did. Conscious phenomena are one kind of world phenomena. Scientists and philosophers have tried to explain the reality of them, but it has not come out any conclusion. Quantum physics tells us that the fundamental field of the natural world is processed metaphysics. The emergence of conscious phenomena is only possible within this process metaphysics and has clearly occurred. By the framework of quantum physics, we are able to take emergence more seriously, and thus we can account for such emergent phenomena as consciousness. By questioning the particle-mechanistic concept of the world, the new metaphysics offers an opportunity to reconsider the reality of conscious phenomena.

Keywords: quantum physics, reduction, emergence, qualia

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Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

Procedia PDF Downloads 182

Authors: Sara Patricia Ibarra-Zavaleta, Rabindranarth Romero-Lopez, Rosario Langrave, Annie Poulin, Gerald Corzo, Mathias Glaus, Ricardo Vega-Azamar, Norma Angelica Oropeza

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The progressive change in climatic conditions worldwide has increased frequency and severity of extreme hydrometeorological events (EHE). Mexico is an example; this has been affected by the presence of EHE leaving economic, social and environmental losses. The objective of this research was to apply a Canadian distributed hydrological model (DHM) to tropical conditions and to evaluate its capacity to predict flows in a basin in the central Gulf of Mexico. In addition, the DHM (once calibrated and validated) was used to calculate the theoretical hydraulic power and the performance to predict streamflow before the presence of an EHE. The results of the DHM show that the goodness of fit indicators between the observed and simulated flows in the calibration process (NSE=0.83, RSR=0.021 and BIAS=-4.3) and validation: temporal was assessed at two points: point one (NSE=0.78, RSR=0.113 and BIAS=0.054) and point two (NSE=0.825, RSR=0.103 and BIAS=0.063) are satisfactory. The DHM showed its applicability in tropical environments and its ability to characterize the rainfall-runoff relationship in the study area. This work can serve as a tool for identifying vulnerabilities before floods and for the rational and sustainable management of water resources.

Keywords: HYDROTEL, hydraulic power, extreme hydrometeorological events, streamflow

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Authors: Amir Khaleghipour, Amirhossein Moghanian, Elhamalsadat Ghaffari

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Modified bioactive glass has been considered as a promising multifunctional candidate in bone repair and regeneration due to its attractive properties. The present study mainly aims to evaluate how the individual substitution of lithium (L-BG) and magnesium (M-BG) for calcium can affect the in vitro bioactivity of sol-gel derived substituted 58S bioactive glass (BG); and to present one composition in both of the 60SiO₂–(36-x)CaO–4P₂O₅–(x)Li₂O and 60SiO₂–(36-x)CaO–4P₂O₅–(x)MgO quaternary systems (where x= 0, 5, 10 mol.%) with improved biocompatibility, enhanced alkaline phosphatase (ALP) activity, and the most efficient antibacterial activity against methicillin-resistant Staphylococcus aureus bacteria. To address these aims, and study the effect of CaO/Li₂O and CaO/MgO substitution up to 10 mol % in 58S-BGs, the samples were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, inductively coupled plasma atomic emission spectrometry and scanning electron microscopy after immersion in simulated body fluid up to 14 days. Results indicated that substitution of either CaO/ Li₂O and CaO/ MgO had a retarding effect on in vitro hydroxyapatite (HA) formation due to the lower supersaturation degree for nucleation of HA compared with 58s-BG. Meanwhile, magnesium had a more pronounced effect. The 3-(4, 5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and alkaline phosphatase (ALP) assays showed that both substitutions of CaO/ Li₂O and CaO/ MgO up to 5mol % in 58s-BGs led to increased biocompatibility and stimulated proliferation of the pre-osteoblast MC3T3 cells with respect to the control. On the other hand, substitution of either Li or Mg for Ca in the 58s BG composition resulted in improved bactericidal efficiency against MRSA bacteria. Taken together, sample 58s-BG with 5 mol % CaO/Li₂O substitution (BG-5L) was considered as a multifunctional biomaterial in bone repair/regeneration with improved biocompatibility, enhanced ALP activity as well enhanced antibacterial efficiency against methicillin-resistant Staphylococcus aureus (MRSA) bacteria among all of the synthesized L-BGs and M-BGs.

Keywords: alkaline, alkaline earth, bioactivity, biomedical applications, sol-gel processes

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Authors: A. Yongsheng Guo, B. Obedat. Abdulazeez, C. Xiaoxian Zhu

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This study aimed to identify the barriers to the development of small and medium-sized enterprises (SMEs) in China and build a theoretical framework to evaluate the support provided by the authorities and institutions. A grounded theory approach was adopted to collect and analyze data. 32 interviews were conducted with SME managers, and open, axial and selective coding was utilized to develop themes. Based on institutional theory, grounded theory models were used to present findings. The findings showed that the main barriers in the business environment were defaulting on contracts, bureaucracy in procedures, lack of financial and legal support, limited intermediaries and channels, and poor quality of products and services. This study found that many programs were provided to support SMEs. A theoretical framework was developed to evaluate the performance of the programs from the managers’ perspective. The concepts of economy, efficiency and effectiveness were used to evaluate the perceived value of the programs. This study suggests that specialized programs are needed to suit sector-specific requirements, and creative packages are helpful in supporting SMEs' growth.

Keywords: business support, public economics, public programme, SME

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

Abstract:

With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

Procedia PDF Downloads 218