Search results for: detecting of envelope modulation on noise

Authors: Bessy Thuranira

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Buildings, as they are designed and used, may contribute to serious environmental problems because of excessive consumption of energy and other natural resources. Buildings in the informal settlements particularly, due to their unplanned physical structure and design, have significantly contributed the global energy problematic scenario typified by high-level inefficiencies. Energy used in buildings in Africa is estimated to be the highest of the total national electricity consumption. Over the last decade, assessments of energy consumption and efficiency/inefficiency has focused on formal and modern buildings. This study seeks to go off the beaten path, by focusing on energy use in informal settlements. Operationally, it sought to establish the contribution of informal buildings in the overall energy consumption in the city and the country at large. This study was carried out in Mukuru kwa Reuben informal settlement where there is distinct manifestation of different settlement morphologies within a small locality. The research narrowed down to three villages (Mombasa, Kosovo and Railway villages) within the settlement, that were representative of the different slum housing typologies. Due to the unpredictability nature and informality in slums, this study takes a multi-methodology approach. Detailed energy audits and measurements are carried out to predict total building consumption, and document building design and envelope, typology, materials and occupancy levels. Moreover, the study uses semi-structured interviews and to access energy supply, cost, access and consumption patterns. Observations and photographs are also used to shed more light on these parameters. The study reveals the high energy inefficiencies in slum buildings mainly related to sub-standard equipment and appliances, building design and settlement layout, poor access and utilization/consumption patterns of energy. The impacts of this inefficiency are high economic burden to the poor, high levels of pollution, lack of thermal comfort and emissions to the environment. The study highlights a set of urban planning and building design principles that can be used to retrofit slums into more energy efficient settlements. The study explores principles of responsive settlement layouts/plans and appropriate building designs that use the beneficial elements of nature to achieve natural lighting, natural ventilation, and solar control to create thermally comfortable, energy efficient, and environmentally responsive buildings/settlements. As energy efficiency in informal settlements is a relatively less explored area of efficiency, it requires further research and policy recommendations, for which this paper will set a background.

Keywords: energy efficiency, informal settlements, renewable energy, settlement layout

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Authors: Gyo Woo Lee, Man Young Kim

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Emission regulations for diesel engines are being strengthened and it is impossible to meet the standards without exhaust after-treatment systems. Lack of the space in many diesel vehicles, however, make it difficult to design and install stand-alone catalytic converters such as DOC, DPF, and SCR in the vehicle exhaust systems. Accordingly, those have been installed inside the muffler to save the space, and referred to the catalytic muffler. However, that has complex internal structure with perforated plate and pipe for noise and monolithic catalyst for emission reduction. For this reason, flow uniformity and pressure drop, which affect efficiency of catalyst and engine performance, respectively, should be examined when the catalytic muffler is designed. In this work, therefore, the flow uniformity and pressure drop to improve the performance of the catalytic converter and the engine have been numerically investigated by changing various design parameters such as inlet shape, porosity, and outlet shape of the muffler using the three-dimensional turbulent flow of the incompressible, non-reacting, and steady state inside the catalytic muffler. Finally, it can be found that the shape, in which the muffler has perforated pipe inside the inlet part, has higher uniformity index and lower pressure drop than others considered in this work.

Keywords: catalytic muffler, perforated inlet cone, catalysts, perforated pipe, flow uniformity, pressure drop

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Authors: Hu Ding, Kai Liu, Guoan Tang

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The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully features detection including gully-affected area and its two dimension parameters (length, width, area et al.), is a significant task not only for researchers but also for policy-makers. This study aims at gully-affected area detection in three catchments of Chinese Loess Plateau, which were selected in Changwu, Ansai, and Suide by using unmanned aerial vehicle (UAV). The methodology includes a sequence of UAV data generation, image segmentation, feature calculation and selection, and random forest classification. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The segmentation strategy adopted in this paper, which considers the topographic information, and optimal parameter combination can improve the segmentation results. Besides, the overall extraction accuracy in Changwu, Ansai, and Suide achieved was 84.62%, 86.46%, and 93.06%, respectively, which indicated that the proposed method for detecting gully-affected area is more objective and effective than traditional methods. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.

Keywords: unmanned aerial vehicle (UAV), object-analysis image analysis, gully erosion, gully-affected area, Loess Plateau, random forest

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Authors: Abdelkrim Khadir, Sina Kavalakatt, Preethi Cherian, Ali Tiss

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Soluble epoxide hydrolase (sEH) is an emerging therapeutic target in several chronic states that have inflammation as a common underlying cause such as immunometabolic diseases. Indeed, sEH is known to play a pro-inflammatory role by metabolizing anti-inflammatory, epoxyeicosatrienoic acids (EETs) to pro-inflammatory diols. Recently, it was shown sEH to be linked to diet and microbiota interaction in rat models of obesity. Nevertheless, the functional contribution of sEH and its anti-inflammatory substrates EETs in obesity remain poorly understood. In the current study, we compared the expression pattern of sEH between lean and obese nondiabetic human subjects using subcutaneous adipose tissue (SAT) and peripheral blood mononuclear cells (PBMCs). Using RT-PCR, western blot and immunofluorescence confocal microscopy, we show here that the level of sEH mRNA and protein to be significantly increased in obese subjects with concomitant increase in endoplasmic reticulum (ER) stress components (GRP78 and ATF6α) and inflammatory markers (TNF-α, IL-6) when compared to lean controls. The observation that sEH was overexpressed in obese subjects’ prompt us to investigate whether physical exercise could reduce its expression. In this study, we report here 3-months supervised physical exercise significantly attenuated the expression of sEH in both the SAT and PBMCs, with a parallel decrease in the expression of ER stress markers along with attenuated inflammatory response. On the other hand, homocysteine, a sulfur containing amino acid deriving from the essential amino acid methionine was shown to be directly associated with insulin resistance. When 3T3-L1 preadipocytes cells were treated with homocysteine our results show increased sEH levels along with ER stress markers. Collectively, our data suggest that sEH upregulation is strongly linked to ER stress in adiposity and that physical exercise modulates its expression. This gives further evidence that exercise might be useful as a strategy for managing obesity and preventing its associated complications.

Keywords: obesity, adipose tissue, epoxide hydrolase, ER stress

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Authors: Jacky Liu, Dulani Jayasuriya, Ryan Elmore

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Match fixing and anomalous sports events have increasingly threatened the integrity of professional sports, prompting concerns about existing detection methods. This study addresses prior research limitations in match fixing detection, improving the identification of potential fraudulent matches by incorporating advanced anomaly detection techniques. We develop a novel method to identify anomalous matches and player performances by examining series of matches, such as playoffs. Additionally, we investigate bettors' potential profits when avoiding anomaly matches and explore factors behind unusual player performances. Our literature review covers match fixing detection, match outcome forecasting models, and anomaly detection methods, underscoring current limitations and proposing a new sports anomaly detection method. Our findings reveal anomalous series in the 2022 NBA playoffs, with the Phoenix Suns vs Dallas Mavericks series having the lowest natural occurrence probability. We identify abnormal player performances and bettors' profits significantly decrease when post-season matches are included. This study contributes by developing a new approach to detect anomalous matches and player performances, and assisting investigators in identifying responsible parties. While we cannot conclusively establish reasons behind unusual player performances, our findings suggest factors such as team financial difficulties, executive mismanagement, and individual player contract issues.

Keywords: anomaly match detection, match fixing, match outcome forecasting, problematic players identification

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Authors: Nor Mazlin Zahari, Lian Gan, Xuerui Mao

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The power production in wind farms and the mechanical loads on the turbines are strongly impacted by the wake of the wind turbine. Thus, there is a need for understanding and modelling the turbine wake dynamic in the wind farm and the layout optimization. Having a good wake model is important in predicting plant performance and understanding fatigue loads. In this paper, the Dynamic Mode Decomposition (DMD) was applied to the simulation data generated by a Direct Numerical Simulation (DNS) of flow around a turbine, perturbed by upstream inflow noise. This technique is useful in analyzing the wake flow, to predict its future states and to reflect flow dynamics associated with the coherent structures behind wind turbine wake flow. DMD was employed to describe the dynamic of the flow around turbine from the DNS data. Since the DNS data comes with the unstructured meshes and non-uniform grid, the interpolation of each occurring within each element in the data to obtain an evenly spaced mesh was performed before the DMD was applied. DMD analyses were able to tell us characteristics of the travelling waves behind the turbine, e.g. the dominant helical flow structures and the corresponding frequencies. As the result, the dominant frequency will be detected, and the associated spatial structure will be identified. The dynamic mode which represented the coherent structure will be presented.

Keywords: coherent structure, Direct Numerical Simulation (DNS), dominant frequency, Dynamic Mode Decomposition (DMD)

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Mona T. Kashef, Omneya M. Helmy

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Multidrug resistant (MDR) bacteria have become a significant public health threat. The prevalence rates, of Gram negative MDR bacteria, are in continuous increase. However, few data are available about these resistant strains. Since, third generation cephalosporins are one of the most commonly used antimicrobials, we set out to investigate the prevalence, different mechanisms and clonal relatedness of multidrug resistance among third generation resistant Gram negative clinical isolates. A total of 114 Gram negative clinical isolates, previously characterized as being resistant to at least one of 3rd generation cephalosporins, were included in this study. Each isolate was tested, using Kirby Bauer disk diffusion method, against its assigned categories of antimicrobials. The role of efflux pump in resistance development was tested by the efflux pump inhibitor-based microplate assay using chloropromazine as an inhibitor. Detecting different aminoglycosides, β-lactams and quinolones resistance genes was done using polymerase chain reaction. The genetic diversity of MDR isolates was investigated using Random Amplification of Polymorphic DNA technique. MDR phenotype was detected in 101 isolates (89%). Efflux pump mediated resistance was detected in 49/101 isolates. Aminoglycosides resistance genes; armA and aac(6)-Ib were detected in one and 53 isolates, respectively. The aac(6)-Ib-cr allele, that also confers resistance to floroquinolones, was detected in 28/53 isolates. β-lactam resistance genes; blaTEM, blaSHV, blaCTX-M group 1 and group 9 were detected in 52, 29, 61 and 35 isolates, respectively. Quinolone resistance genes; qnrA, qnrB and qnrS were detectable in 2, 14, 8 isolates respectively, while qepA was not detectable at all. High diversity was observed among tested MDR isolates. MDR is common among 3rd generation cephalosporins resistant Gram negative bacteria, in Egypt. In most cases, resistance was caused by different mechanisms. Therefore, new treatment strategies should be implemented.

Keywords: gram negative, multidrug resistance, RAPD typing, resistance genes

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Authors: Hafiz Muhammad Tayyab Bhatti, Munazza Usmani

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One of nature's most destructive occurrences, floods do immense damage to communities and economic losses. Nigeria country, specifically southern Nigeria, is known for being prone to flooding. Even though periodic flooding occurs in Nigeria frequently, the floods of 2022 were the worst since those in 2012. Flood vulnerability analysis and mapping are still lacking in this region due to the very limited historical hydrological measurements and surveys on the effects of floods, which makes it difficult to develop and put into practice efficient flood protection measures. Remote sensing and Geographic Information Systems (GIS) are useful approaches to detecting, determining, and estimating the flood extent and its impacts. In this study, NOAA VIIR has been used to extract the flood extent using the flood water fraction data and afterward fused with GIS data for some zonal statistical analysis. The estimated possible flooding areas are validated using satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). The goal is to map and studied flood extent, flood hazards, and their effects on the population, schools, and health facilities for each state of Nigeria. The resulting flood hazard maps show areas with high-risk levels clearly and serve as an important reference for planning and implementing future flood mitigation and control strategies. Overall, the study demonstrated the viability of using the chosen GIS and remote sensing approaches to detect possible risk regions to secure local populations and enhance disaster response capabilities during natural disasters.

Keywords: flood hazards, remote sensing, damage assessment, GIS, geospatial analysis

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Authors: Zahra Rakhshan Masoudi, Sona Rostampour Yasouri

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Considering that the only way to save the lives of patients and healthy people who have suffered sudden accidents is blood transfusion, what is important is the presence of the known HCV virus as the most important cause of the disease after blood transfusion. HCV is one of the major global problems, and its transmission through blood causes life-threatening complications and extensive legal, social and economic consequences. On the one hand, unfortunately, there is still no effective vaccine available to prevent HCV. In Iran, the exact statistics of the prevalence of this disease have not yet been fully announced. The main purpose of this study is to investigate the prevalence rate and rapid diagnosis of HCV among those who refer to laboratory centers in Tehran. From spring to winter of 1401 (2022-2023), 2166 blood samples were collected from laboratory centers in Tehran. Blood samples were evaluated for the presence of HCV by Electrochemiluminescence (ECL) and PCR techniques along with specific HCV primers. In general, 36 samples (1.6%) were tested positive by the mentioned techniques. The results indicated that the ECL technique is a sensitive and specific diagnostic method for detecting HCV in the early stages of the disease and can be very helpful and provide the possibility of starting the treatment steps to prevent the exacerbation of the disease earlier. Also, the results of PCR technique showed that PCR is an accurate, sensitive and fast method for definitive diagnosis of HCV. It seems that the incidence rate of this disease is increasing in Iran, and investigating the spread of the disease throughout Iran for a longer period of time in the continuation of our research can be helpful in the future to take the necessary measures to prevent the transmission of the disease to people and the rapid onset Treatment steps for patients with HCV should be carried out.

Keywords: electrochemiluminescence, HCV, PCR, prevalence

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Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: S. Tebibel, C. Mechati, S. Messaoudi

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Algeria is currently experiencing the same rate of cancer progression as that registered these last years in the western countries. Colorectal cancer, constituting increasingly a major public health problem, is the most common form of cancer after breast and Neck-womb cancer at the woman and prostate cancer at the man. Our work is based on a retrospective study to determine the cases of colorectal cancer through eastern Algeria. Our goal is to carry out an epidemiological, histological and immune- histochemical study to investigate different techniques for the diagnosis of colorectal cancer and their interests and specific in detecting the disease. The study includes 110 patients (aged between 20 to 87 years) with colorectal cancer where the inclusions and exclusions criteria were established. In our study, colorectal cancer, expresses a male predominance, with a sex ratio of 1, 99 and the most affected age group is between 50 and 59 years. We noted that the colon cancer rate is higher than rectal cancer rate, whose frequencies are respectively 60,91 % and 39,09 %. In the series of colon cancer, the ADK lieberkunien is histological the most represented type, or 85,07 % of all cases. In contrast, the proportion of ADK mucinous (colloid mucous) is only 1,49% only. Well-differentiated ADKS, are very significant in our series, they represent 83,58 % of cases. Adenocarcinoma moderately and poorly differentiated, whose proportions are respectively 2,99 % and 0.05 %. For histological varieties of rectal ADK, we see in our workforce that ADK lieberkunien represent the most common histological form, or 76,74%, while the mucosal colloid is 13,95 %. Research of the mutation on the gene encoding K-ras, a major step in the targeted therapy of colorectal cancers, is underway in our study. Colorectal cancer is the subject of much promising research concern: the evaluation of new therapies (antiangiogenic monoclonal antibodies), the search for predictors of sensitivity to chemotherapy and new prognostic markers using techniques of molecular biology and proteomics.

Keywords: adenocarcinoma, age, colorectal cancer, epidemiology, histological section, sex

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Authors: Bhogendra Mishra, Andy Nelson, Mirco Boschetti, Lorenzo Busetto, Alice Laborte

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Rice is grown on over 100 million hectares in almost every country of Asia. It is the most important staple crop for food security and has high economic and cultural importance in Asian societies. The combination of genetic diversity and management options, coupled with the large geographic extent means that there is a large variation in seasonality (when it is grown) and cropping intensity (how often it is grown per year on the same plot of land), even over relatively small distances. Seasonality and intensity can and do change over time depending on climatic, environmental and economic factors. Detecting where and when these changes happen can provide information to better understand trends in regional and even global rice production. Remote sensing offers a unique opportunity to estimate these trends. We apply the recently published PhenoRice algorithm to 14 years of moderate resolution remote sensing (MODIS) data (utilizing 250m resolution 16 day composites from Terra and Aqua) to estimate seasonality and cropping intensity per year and changes over time. We compare the results to the surveyed data collected by International Rice Research Institute (IRRI). The study results in a unique and validated dataset on the extent and change of extent, the seasonality and change in seasonality and the cropping intensity and change in cropping intensity between 2003 and 2016 for the Philippines. Observed trends and their implications for food security and trade policies are also discussed.

Keywords: rice, cropping intensity, moderate resolution remote sensing (MODIS), phenology, seasonality

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Seong-Jin Cho, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorption coefficient is considered important when designing because noise affects emotion quality of car. It is designed with lots of experiment tunings in the field because it is unreliable to predict it for multi-layer material. In this paper, we present the design of sound absorption for automotive interior material with multiple layers using estimation software of sound absorption coefficient for reverberation chamber. Additionally, we introduce the method for estimation of physical properties required to predict sound absorption coefficient of car interior materials with multiple layers too. It is calculated by inverse algorithm. It is very economical to get information about physical properties without expensive equipment. Correlation test is carried out to ensure reliability for accuracy. The data to be used for the correlation is sound absorption coefficient measured in the reverberation chamber. In this way, it is considered economical and efficient to design automotive interior materials. And design optimization for sound absorption coefficient is also easy to implement when it is designed.

Keywords: sound absorption coefficient, optimization design, inverse algorithm, automotive interior material, multiple layers nonwoven, scaled reverberation chamber, sound impedance tubes

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Authors: Yanhua Zhao, Chenli Rao, Dongdong Li, Chuanmin Tao

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The Chinese Centers for Disease Control and Prevention (CCDC) issued a new laboratory-based algorithm for HIV diagnosis on April 2016, which initially screens with a combination HIV-1/HIV-2 antigen/antibody fourth-generation immunoassay (IA) followed, when reactive, an HIV-1/HIV-2 undifferentiated antibody IA in duplicate. Reactive specimens with concordant results undergo supplemental tests with western blots, or HIV-1 nucleic acid tests (NATs) and non-reactive specimens with discordant results receive HIV-1 NATs or p24 antigen tests or 2-4 weeks follow-up tests. However, little data evaluating the application of the new algorithm have been reported to date. The study was to evaluate the performance of new laboratory-based HIV diagnostic algorithm in an inpatient population of Southwest China over the initial 6 months by compared with the old algorithm. Plasma specimens collected from inpatients from May 1, 2016, to October 31, 2016, are submitted to the laboratory for screening HIV infection performed by both the new HIV testing algorithm and the old version. The sensitivity and specificity of the algorithms and the difference of the categorized numbers of plasmas were calculated. Under the new algorithm for HIV diagnosis, 170 of the total 52 749 plasma specimens were confirmed as positively HIV-infected (0.32%). The sensitivity and specificity of the new algorithm were 100% (170/170) and 100% (52 579/52 579), respectively; while 167 HIV-1 positive specimens were identified by the old algorithm with sensitivity 98.24% (167/170) and 100% (52 579/52 579), respectively. Three acute HIV-1 infections (AHIs) and two early HIV-1 infections (EHIs) were identified by the new algorithm; the former was missed by old procedure. Compared with the old version, the new algorithm produced fewer WB-indeterminate results (2 vs. 16, p = 0.001), which led to fewer follow-up tests. Therefore, the new HIV testing algorithm is more sensitive for detecting acute HIV-1 infections with maintaining the ability to verify the established HIV-1 infections and can dramatically decrease the greater number of WB-indeterminate specimens.

Keywords: algorithm, diagnosis, HIV, laboratory

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Authors: Abdus-Samii Imam Arikewuyo

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The human rights phenomenon increasingly gains universal prominence in the contemporary age. This embraces the clamour for a just treatment of individuals in society. The human rights agitation is a global pursuit which virtually gave birth to many national and international human rights organizations. In particular, Nigeria accedes to a number of human rights covenants. Invariably, there are some provisions which are recognized as inalienable rights of man in his society by which his intrinsic worth and dignity are protected by law. Nonetheless, the constituents of human rights differ in various societies. Conversely, Islam, as a complete code of life, guarantees the rights of a man vis-à-vis the rights of others in his environment regardless of place and time. Human rights pressure in Nigeria in recent times prompted proactive steps to address the issue through various legal instruments. Amazingly, the struggle appears to be a rhetorical noise because the human rights violation subsists. This provokes the present research on a comparative study of the Nigerian legal provisions and the Islamic law perspectives on human rights. It is discovered that the first is simply theoretical, while the other contains both the theoretical framework and the practical measures for its enforcement. The study adopts analytical and descriptive methods. It concludes with the assertion that the Islamic law provisions are all-embracing, universal and more efficacious. Hence, it recommends the adoption of the Islamic law approach to human rights issues.

Keywords: human rights, Nigerian legal provisions, shariah law, comparative study, charter

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Authors: Chen Zhang, Bernhard Schwarz-Röhr, Alexander Härting

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To acquire accurate ship motions at the center of gravity, a single low-cost inertial sensor is utilized and applied on board to measure ship oscillating motions. As observations, the three axes accelerations and three axes rotational rates provided by the sensor are used. The mathematical model of processing the observation data includes determination of the distance vector between the sensor and the center of gravity in x, y, and z directions. After setting up the transfer matrix from sensor’s own coordinate system to the ship’s body frame, an extended Kalman filter is applied to deal with nonlinearities between the ship motion in the body frame and the observation information in the sensor’s frame. As a side effect, the method eliminates sensor noise and other unwanted errors. Results are not only roll and pitch, but also linear motions, in particular heave and surge at the center of gravity. For testing, we resort to measurements recorded on a small vessel in a well-defined sea state. With response amplitude operators computed numerically by a commercial software (Seaway), motion characteristics are estimated. These agree well with the measurements after processing with the suggested method.

Keywords: extended Kalman filter, nonlinear estimation, sea trial, ship motion estimation

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Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

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Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

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Authors: Gamze Karanfil Celep, Kevser Dincer

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The effects of polymer concentration and electrospinning process parameters on the average diameters of electrospun polyacrylonitrile (PAN) nanofibers were experimentally investigated. Besides, mechanical and thermal properties of PAN nanofibers were examined by tensile test and thermogravimetric analysis (TGA), respectively. For this purpose, the polymer concentration, solution feed rate, supply voltage and tip-to-collector distance were determined as the control factors. To succeed these aims, Taguchi’s L16 orthogonal design (4 parameters, 4 level) was employed for the experimental design. Optimal electrospinning conditions were defined using the signal-to-noise (S/N) ratio that was calculated from diameters of the electrospun PAN nanofibers according to "the-smaller-the-better" approachment. In addition, analysis of variance (ANOVA) was evaluated to conclude the statistical significance of the process parameters. The smallest diameter of PAN nanofibers was observed. According to the S/N ratio response results, the most effective parameter on finding out of nanofiber diameter was determined. Finally, the Taguchi design of experiments method has been found to be an effective method to statistically optimize the critical electrospinning parameters used in nanofiber production. After determining the optimum process parameters of nanofiber production, electrical conductivity and fuel cell performance of electrospun PAN nanofibers on the carbon papers will be evaluated.

Keywords: nanofiber, electrospinning, polyacrylonitrile, Taguchi method

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Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled DNI field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: artificial neural networks, resilient propagation, solar radiation, time series forecasting

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Authors: Yasin I. Tayem, Jamil Ahmed, Mahmood Bahzad, Abdullah Alnama, Fahad Al Asfoor, Mahmood A. Jalil, Mohammed Radhi, Ahmed Alenezi, Khalid A. J. Al-Khaja

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Drug-drug interactions (DDIs) represent a significant cause of patient’s morbidity and mortality. The rate of DDIs is rapidly increasing worldwide with the increasing proportion of ageing population and frequent requirement of polypharmacy-prescription of multiple drugs to treat comorbidities. Prescribing physicians are responsible for checking their prescriptions for the presence and severity of DDIs. However, since a large number of new drugs are approved and marketed every year, new interactions between medications are increasingly reported. Consequently, it is no longer practical for physicians to rely only upon their previous knowledge of medicine to avoid potential DDIs. The aim of this study was to explore the perceptions of physicians working at primary healthcare centers in Bahrain towards DDIs and how they manage them during their practice. Methodology: In this cross-sectional study, physicians working at all governmental primary healthcare centers in Bahrain were invited to voluntarily, privately and anonymously respond to a self-administered questionnaire. The questionnaire aims to assess their self-reported knowledge of DDIs and how they check for them in their practice. The participants were requested to provide socio demographic data and information related to their attitudes towards DDIs including strategies they employ for detecting and managing them, and their awareness of drugs which commonly cause DDIs. At the end of the questionnaire, an open-ended item was added to allow participants to further add any comment. Findings and Conclusions: The study is going on currently, and the results and conclusions will be presented at the conference.

Keywords: awareness, drug interactions, health centres, physicians

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Authors: Denise Schrama, Claudia Raposo, Pedro Rodrigues

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Background: Food allergies are conducted by a hypersensitive response of the immune system. These allergies are a global concern for the public health. Consumption of fish is increasing worldwide as it is a healthy meat with high nutritional value. Unfortunately, fish can cause adverse immune-mediate reactions, affecting part of the population with higher incidence in children. β-parvalbumin, a small, highly conserved stable, calcium or magnesium binding muscle protein is the main fish allergen. In fish-allergic patients, cross-reactivity between different fish species exist due to recognition of highly identical protein regions. Enolases, aldolases, or fish gelatin are other identified fish allergens in some fish species. With no available cure for fish allergies, clinical management is only based on an avoidance diet aiming at the total exclusion of offending food. Methods: Mediterranean fish (S. aurata and D. labrax) were fed specifically designed diets, enriched in components that target the expression or inactivation of parvalbumin (creatine and EDTA, respectively). After 90 days fish were sampled and biological tissues were excised. Proteomics was used to access fish allergens characterization and expression in muscle while IgE assays to confirm the lower allergenic potential are conducted in patients with history of fish allergies. Fish welfare and quality of flesh were established with biochemical, texture and sensorial analysis. Results: Fish welfare shows no major impact between diets. In case of creatine supplementation in D. labrax proteomic analysis show a slight decrease in parvalbumin expression. No accumulation of this compound was found in muscle. For EDTA supplementation in S. aurata IgE assay show a slight decrease in allergenicity when using sera of fish allergic patients. Conclusion: Supplementation with these two compounds seems to change slightly the allergenicity of the two mean Mediterranean species.

Keywords: fish allergies, fish nutrition, proteomics, aquaculture

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Authors: Olaiya Folorunsho, Comfort Y. Daramola, Joel N. Ugwu, Lawrence B. Adewole, Olufisayo S. Ekundayo

Abstract:

In today world, there is a tremendous rise in the usage of internet due to the fact that almost all the communication and information sharing is done over the web. Conversely, there is a continuous growth of unauthorized access to confidential data. This has posed a challenge to information security expertise whose major goal is to curtail the menace. One of the approaches to secure the safety delivery of data/information to the rightful destination without any modification is steganography. Steganography is the art of hiding information inside an embedded information. This research paper aimed at designing a secured algorithm with the use of image steganographic technique that makes use of Least Significant Bit (LSB) algorithm for embedding the data into the bit map image (bmp) in order to enhance security and reliability. In the LSB approach, the basic idea is to replace the LSB of the pixels of the cover image with the Bits of the messages to be hidden without destroying the property of the cover image significantly. The system was implemented using C# programming language of Microsoft.NET framework. The performance evaluation of the proposed system was experimented by conducting a benchmarking test for analyzing the parameters like Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The result showed that image steganography performed considerably in securing data hiding and information transmission over the networks.

Keywords: steganography, image steganography, least significant bits, bit map image

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Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

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Authors: H. Heidari-Bafroui, B. Ribeiro, A. Charbaji, C. Anagnostopoulos, M. Faghri

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In this paper, we report the development of a portable and inexpensive infrared lightbox for improving the detection limits of paper-based phosphate devices. Commercial paper-based devices utilize the molybdenum blue protocol to detect phosphate in the environment. Although these devices are easy to use and have a long shelf life, their main deficiency is their low sensitivity based on the qualitative results obtained via a color chart. To improve the results, we constructed a compact infrared lightbox that communicates wirelessly with a smartphone. The system measures the absorbance of radiation for the molybdenum blue reaction in the infrared region of the spectrum. It consists of a lightbox illuminated by four infrared light-emitting diodes, an infrared digital camera, a Raspberry Pi microcontroller, a mini-router, and an iPhone to control the microcontroller. An iPhone application was also developed to analyze images captured by the infrared camera in order to quantify phosphate concentrations. Additionally, the app connects to an online data center to present a highly scalable worldwide system for tracking and analyzing field measurements. In this study, the detection limits for two popular commercial devices were improved by a factor of 4 for the Quantofix devices (from 1.3 ppm using visible light to 300 ppb using infrared illumination) and a factor of 6 for the Indigo units (from 9.2 ppm to 1.4 ppm) with repeatability of less than or equal to 1.2% relative standard deviation (RSD). The system also provides more granular concentration information compared to the discrete color chart used by commercial devices and it can be easily adapted for use in other applications.

Keywords: infrared lightbox, paper-based device, phosphate detection, smartphone colorimetric analyzer

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Authors: Jihad S. Daba, J. P. Dubois, Yvette Antar

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With the exponential growth of cellular users, a new generation of cellular networks is needed to enhance the required peak data rates. The co-channel interference between neighboring base stations inhibits peak data rate increase. To overcome this interference, multi-cell cooperation known as coordinated multipoint transmission is proposed. Such a solution makes use of multiple-input-multiple-output (MIMO) systems under two different structures: Micro- and macro-diversity. In this paper, we study the capacity and bit error rate in cellular networks using MIMO technology. We analyse both micro- and macro-diversity schemes and develop a hybrid model that switches between macro- and micro-diversity in the case of hard handoff based on a cut-off range of signal-to-noise ratio values. We conclude that our hybrid switched micro-macro MIMO system outperforms classical MIMO systems at the cost of increased hardware and software complexity.

Keywords: cooperative multipoint transmission, ergodic capacity, hard handoff, macro-diversity, micro-diversity, multiple-input-multiple output systems, orthogonal frequency division multiplexing

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Authors: ChunLoon Cha, HoYeon Lee, SangSoon Hwang

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Mild combustion is characterized with its distinguished features, such as suppressed pollutant emission, homogeneous temperature distribution, reduced noise and thermal stress. However, most studies for MILD combustion have been focused on gas phase fuel. Therefore further study on MILD combustion using liquid fuel is needed for the application to liquid fueled gas turbine especially. In this work, we will focus on numerical simulation of the effects of diluent gas velocity on the formation of liquid fuel MILD combustion used in gas turbine area. A series of numerical simulations using Ansys fluent 18.2 have been carried out in order to investigate the detail effect of the flow field in the furnace on the formation of MILD combustion. The operating conditions were fixed at relatively lower heat intensity of 1.28 MW/m³ atm and various global equivalence ratios were changed. The results show that the local high temperature region was decreased and the flame temperature was uniformly distributed due to high velocity of diluted burnt gas. The increasing of diluted burnt gas velocity can be controlled by open ratio of adapter size. It was found that the maximum temperature became lower than 1800K and the average temperature was lower than 1500K that thermal NO formation was suppressed.

Keywords: MILD combustion, spray combustion, liquid fuel, diluent gas velocity, low NOx emission

Procedia PDF Downloads 224

Authors: Malarvizhi Selvaraj, Paul Fergus, Andy Shaw

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Uterine contractions produced during labour have the potential to damage the foetus by diminishing the maternal blood flow to the placenta. In order to observe this phenomenon labour and delivery are routinely monitored using cardiotocography monitors. An obstetrician usually makes the diagnosis of foetus hypoxia by interpreting cardiotocography recordings. However, cardiotocography capture and interpretation is time-consuming and subjective, often lead to misclassification that causes damage to the foetus and unnecessary caesarean section. Both of these have a high impact on the foetus and the cost to the national healthcare services. Automatic detection of foetal heart rate may be an objective solution to help to reduce unnecessary medical interventions, as reported in several studies. This paper aim is to provide a system for better identification and interpretation of abnormalities of the fetal heart rate using RStudio. An open dataset of 552 Intrapartum recordings has been filtered with 0.034 Hz filters in an attempt to remove noise while keeping as much of the discriminative data as possible. Features were chosen following an extensive literature review, which concluded with FIGO features such as acceleration, deceleration, mean, variance and standard derivation. The five features were extracted from 552 recordings. Using these features, recordings will be classified either normal or abnormal. If the recording is abnormal, it has got more chances of hypoxia.

Keywords: cardiotocography, foetus, intrapartum, hypoxia

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Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error

Procedia PDF Downloads 313