Search results for: feature detection

Authors: A. Pietro Rimoldi, B. Anilkumar Gopinath, C. Minimol Korulla

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Coastal engineering structure is conventionally designed for a shorter planning horizon usually 20 years. These structures are subjected to different offshore climatic externalities like waves, tides, tsunamis etc. during the design life period. The probability of occurrence of these different offshore climatic externalities varies. The impact frequently caused by these externalities on the structures is of concern because it has a significant bearing on the capital /operating cost of the project. There can also be repeated short time occurrence of these externalities in the assumed planning horizon which can cause heavy damage to the conventional coastal structure which are mainly made of rock. A replacement of the damaged portion to prevent complete collapse is time consuming and expensive when dealing with hard rock structures. But if coastal structures are made of Geo-synthetic containment systems such replacement is quickly possible in the time period between two successive occurrences. In order to have a better knowledge and to enhance the predictive capacity of these occurrences, this study estimates risk of encounter within the design life period of various externalities based on the concept of exponential distribution. This gives an idea of the frequency of occurrences which in turn gives an indication of whether replacement is necessary and if so at what time interval such replacements have to be effected. To validate this theoretical finding, a pilot project has been taken up in the field so that the impact of the externalities can be studied both for a hard rock and a Geosynthetic tube structure. The paper brings out the salient feature of a case study which pertains to a project in which Geosynthetic tubes have been used for reformation of a seawall adjacent to a conventional rock structure in Alappuzha coast, Kerala, India. The effectiveness of the Geosystem in combatting the impact of the short-term externalities has been brought out.

Keywords: climatic externalities, exponential distribution, geosystems, planning horizon

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Authors: Nathalia Florencia Barros Azeredo, Josué Martins Gonçalves, Pamela De Oliveira Rossini, Koiti Araki, Lucio Angnes

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This work demonstrates the electroanalysis of uric acid (UA) at very low working potential (0 V vs Ag/AgCl) directly in body fluids such as saliva and sweat using electrodes modified with mixed -Ni0.75Zn0.25(OH)2 nanoparticles exhibiting stable electrocatalytic responses from alkaline down to weakly acidic media (pH 14 to 3 range). These materials were prepared for the first time and fully characterized by TEM, XRD, and spectroscopic techniques. The electrochemical properties of the modified electrodes were evaluated in a fast and simple procedure for uric acid analyses based on cyclic voltammetry and chronoamperometry, pushing down the detection and quantification limits (respectively of 2.3*10-8 and 7.6*10-8 mol L-1) with good repeatability (RSD = 3.2% for 30 successive analyses pH 14). Finally, the possibility of real application was demonstrated upon realization of unexpectedly robust and sensitive modified FTO (fluorine doped tin oxide) glass and screen-printed sensors for measurement of uric acid directly in real saliva and sweat samples, with no significant interference of usual concentrations of ascorbic acid, acetaminophen, lactate and glucose present in those body fluids (Fig. 1).

Keywords: nickel hydroxide, mixed catalyst, uric acid sensors, biofluids

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Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma

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The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.

Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.

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Authors: Puntarikorn Rungrattanakasin

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Objectives: To develop the trigger tool to warn about the risk of bleeding as an adverse event from warfarin drug usage during admission in Medical Wards of Chumphae Hospital. Methods: A retrospective study was performed by reviewing the medical records for the patients admitted between June 1st,2020- May 31st, 2021. ADEs were evaluated by Naranjo’s algorithm. The international normalized ratio (INR) and events of bleeding during admissions were collected. Statistical analyses, including Chi-square test and Reciever Operating Characteristic (ROC) curve for optimal INR threshold, were used for the study. Results: Among the 139 admissions, the INR range was found to vary between 0.86-14.91, there was a total of 15 bleeding events, out of which 9 were mild, and 6 were severe. The occurrence of bleeding started whenever the INR was greater than 2.5 and reached the statistical significance (p <0.05), which was in concordance with the ROC curve and yielded 100 % sensitivity and 60% specificity in the detection of a bleeding event. In this regard, the INR greater than 2.5 was considered to be an optimal threshold to alert promptly for bleeding tendency. Conclusions: The INR value of greater than 2.5 (>2.5) would be an appropriate trigger tool to warn of the risk of bleeding for patients taking warfarin in Chumphae Hospital.

Keywords: trigger tool, warfarin, risk of bleeding, medical wards

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Authors: Ali Berkan Ural

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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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Authors: N. Adjlane, N. Haddad

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The American foulbrood is one of the most serious diseases that may affect brood of larvae and pupae stages. The causative organism is a gram positive bacterium Paaenibacillus larvae. American foulbrood infected apiaries suffer from severe economic losses, resulting from significant decreases in honeybee populations and honey production. The aim of this study was to detect Paenibacillus larvae in the remains collected at the bottom of the hive from the suspected hives by direct PCR and culture growth. A total of 56 suspected beehive wax debris samples collected in 40 different apiaries located in the central region of Algeria. MYPGP the culture medium is used during all the identifications of the bacterium. After positive results on samples, biochemical confirmation tests (test of catalase, presence hydrolysis of casein) and microscopic (gram stain) are used in order to verify the accuracy of the initial results. The QIAamp DNA Mini Kit is used to identify the DNA of Paaenibacillus larvae. Paaenibacillus larvae were identified in 14 samples out of 16 by the PCR. A suspected culture-negative sample was found positive through evaluation with PCR. This research is for the bacterium Paaenibacillus larvae in the debris of the colony is an effective method for diagnosis of the pathology of American foulbrood.

Keywords: Paenibacillus larvae, honeybee, PCR, microbiological method

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Authors: Kin On Kwok, Vivian Wei, Benjamin Cowling, Steven Riley, Jonathan Read

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Background: The role of social contact behavior measured in different contact constructs in the transmission of respiratory pathogens with acute respiratory illness (ARI) remains unclear. We, therefore, aim to depict the individual pattern of ARI in the community and investigate the association between different contact dimensions and ARI in Hong Kong. Methods: Between June 2013 and September 2013, 620 subjects participated in the last two waves of recruitment of the population based longitudinal phone social contact survey. Some of the subjects in this study are from the same household. They are also provided with the symptom diaries to self-report any acute respiratory illness related symptoms between the two days of phone recruitment. Data from 491 individuals who were not infected on the day of phone recruitment and returned the symptom diaries after the last phone recruitment were used for analysis. Results: After adjusting different follow-up periods among individuals, the overall incidence rate of ARI was 1.77 per 100 person-weeks. Over 75% ARI episodes involve running nose, cough, sore throat, which are followed by headache (55%), malagia (35%) and fever (18%). Using a generalized estimating equation framework accounting for the cluster effect of subjects living in the same household, we showed that both daily number of locations visited with contacts and the number of contacts, explained the ARI incidence rate better than only one single contact construct. Conclusion: Our result suggests that it is the intertwining property of contact quantity (number of contacts) and contact intensity (ratio of subject-to-contact) that governs the infection risk by a collective set of respiratory pathogens. Our results provide empirical evidence that multiple contact constructs should be incorporated in the mathematical transmission models to feature a more realistic dynamics of respiratory disease.

Keywords: acute respiratory illness, longitudinal study, social contact, symptom diaries

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Authors: Toufik Bensana, Medkour Mihoub, Slimane Mekhilef

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally nonstationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA), and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

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

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Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

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The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

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Authors: Reira Kinoshita, Shin'ichi Ishimaru

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Vapochromism is a type of chromism in which the color of a substance changes when it is exposed to the vapor of volatile materials, and has been investigated for the application of chemical sensors for volatile organic compounds causing sick building syndrome and health hazards in workspaces. We synthesized intercalation compounds of 3,3',5,5'-tetramethylbenzidine (TMB), and tetrasilisicfluormica (TSFM) by the commonly used cation-exchange method with the cation ratio TMB²⁺/CEC of TSFM = 1.0, 2.0, 2.7 and 5.4 to investigate the vapochromism of these materials. The obtained samples were characterized by powder XRD, XRF, TG-DTA, N₂ adsorption, and SEM. Vapochromism was measured for each sample under a controlled atmosphere by a handy reflectance spectrometer directly from the outside of the glass sample tubes. The color was yellow for all specimens vacuum-dried at 50 °C, but it turned green under H₂O vapor exposure for the samples with TMB²⁺/CEC = 2.0, 2.7, and 5.4 and blue under acetonitrile vapor for all cation ratios. Especially the sample TMB²⁺/CEC = 2.0 showed clear chromism both for water and acetonitrile. On the other hand, no clear color change was observed for vapors of alcohols, acetone, and non-polar solvents. From these results, this material can be expected to apply for easy detection of humidity and acetonitrile vapor in the environment.

Keywords: chemical sensor, intercalation compound, tetramethylbenzidine, tetrasilisicfluormica, vapochromism, volatile organic compounds

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

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In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Rohith J. K., Amir Nazemi, Abbas S. Milani

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In Paralympic sports, athletes often depend on some form of equipment to enable competitive sporting, where most of this equipment would only allow passive physiological supports and discrete physiological measurements. Active feedback physiological support and continuous detection of performance indicators, without time or space constraints, would be beneficial in more effective training and performance measures of Paralympic athletes. Moreover, occasionally the athletes suffer from fatigue and muscular stains due to improper monitoring systems. The latter challenges can be overcome by using Smart Composites technology when manufacturing, e.g., knee brace and other sports wearables utilities, where the sensors can be fused together into the fabric and an assisted system actively support the athlete. This paper shows how different sensing functionality may be created by intrinsic and extrinsic modifications onto different types of composite fabrics, depending on the level of integration and the employed functional elements. Results demonstrate that fabric sensors can be well-tailored to measure muscular strain and be used in the fabrication of a smart knee brace as a sample potential application. Materials, connectors, fabric circuits, interconnects, encapsulation and fabrication methods associated with such smart fabric technologies prove to be customizable and versatile.

Keywords: smart composites, sensors, smart fabrics, knee brace

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Authors: Sanjay Saraf

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The oral cavity can be the site for early manifestations of mucocutaneous disorders (MD) or the only site for occurrence of these disorders. It can also exhibit oral lesions with simultaneous associated skin lesions. The MD involving the oral mucosa commonly presents with signs such as ulcers, vesicles and bullae. The unique environment of the oral cavity may modify these signs of the disease, thereby making the clinical diagnosis an arduous task. In addition to the unique environment of oral cavity, the overlapping of the signs of various mucocutaneous disorders, also makes the clinical diagnosis more intricate. The aim of this review is to present the oral signs of dermatological disorders having common oral involvement and emphasize their importance in early detection of the systemic disorders. The aim is also to highlight the necessity of oral examination by a dermatologist while examining the skin lesions. Prior to the oral examination, it must be imperative for the dermatologists and the dental clinicians to have the knowledge of oral anatomy. It is also important to know the impact of various diseases on oral mucosa, and the characteristic features of various oral mucocutaneous lesions. An initial clinical oral examination is may help in the early diagnosis of the MD. Failure to identify the oral manifestations may reduce the likelihood of early treatment and lead to more serious problems. This paper reviews the oral manifestations of immune mediated dermatological disorders with common oral manifestations.

Keywords: dermatological investigations, genodermatosis, histological features, oral examination

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Authors: Augustine Okolie, Johannes Müller, Mirjam Kretzchmar

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We adopt a maximum-likelihood framework to estimate parameters of a stochastic susceptible-infected-recovered (SIR) model with contact tracing on a rooted random tree. Given the number of detectees per index case, our estimator allows to determine the degree distribution of the random tree as well as the tracing probability. Since we do not discover all infectees via contact tracing, this estimation is non-trivial. To keep things simple and stable, we develop an approximation suited for realistic situations (contract tracing probability small, or the probability for the detection of index cases small). In this approximation, the only epidemiological parameter entering the estimator is the basic reproduction number R0. The estimator is tested in a simulation study and applied to covid-19 contact tracing data from India. The simulation study underlines the efficiency of the method. For the empirical covid-19 data, we are able to compare different degree distributions and perform a sensitivity analysis. We find that particularly a power-law and a negative binomial degree distribution meet the data well and that the tracing probability is rather large. The sensitivity analysis shows no strong dependency on the reproduction number.

Keywords: stochastic SIR model on graph, contact tracing, branching process, parameter inference

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Authors: Keyao Li, Sai On Cheung

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Incorporation of alternative dispute resolution (ADR) mechanism has been the main feature of current trend of construction project dispute resolution (CPDR). ADR approaches have been identified as efficient mechanisms and are suitable alternatives to litigation and arbitration. Moreover, the use of ADR in this multi-tiered dispute resolution process often leads to repeated evaluations of a same dispute. Multi-tiered CPDR may become a breeding ground for cognitive biases. When completed knowledge is not available at the early tier of construction dispute resolution, disputing parties may form preconception of the dispute matter or the counterpart. This preconception would influence their information processing in the subsequent tier. Disputing parties tend to search and interpret further information in a self-defensive way to confirm their early positions. Their imbalanced information collection would boost their confidence in the held assessments. Their attitudes would be hardened and difficult to compromise. The occurrence of cognitive bias, therefore, impedes efficient dispute settlement. This study aims to explore ways to minimize bias in CPDR. Based on a comprehensive literature review, three types of bias minimizing approaches were collected: strategy-based, attitude-based and process-based. These approaches were further operationalized into bias minimizing measures. To verify the usefulness and practicability of these bias minimizing measures, semi-structured interviews were conducted with ten CPDR third party neutral professionals. All of the interviewees have at least twenty years of experience in facilitating settlement of construction dispute. The usefulness, as well as the implications of the bias minimizing measures, were validated and suggested by these experts. There are few studies on cognitive bias in construction management in general and in CPDR in particular. This study would be the first of its type to enhance the efficiency of construction dispute resolution by highlighting strategies to minimize the biases therein.

Keywords: bias, construction project dispute resolution, minimization, multi-tiered, semi-structured interview

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Authors: Muhammad Farooq Baig

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Objective: The purpose of this study was to compare results obtained using a single fecal specimen for O&P examination, direct immunofluorescence assay (DFA), and two conventional staining methods. Design: Hundred and fifty children fecal specimens were collected and examined by each method. The O&P and the DFA were used as the reference method. Setting: The study was performed at the laboratory in the Basic Medical Science Institute JPMC Karachi. Patients or Other Participants: The fecal specimens were collected from children with a suspected Giardia lamblia infection. Main Outcome Measures: The amount of agreement and disagreement between methods.1) Presence of giardiasis in our population. 2) The sensitivity and specificity of each method. Results: There was 45(30%) positive 105 (70%) negative on DFA, 41 (27.4%) positive 109 (72.6%) negative on iodine and 34 (22.6%) positive 116(77.4%) on saline method. The sensitivity and specificity of DFA in comparision to iodine were 92.2%, 92.7% respectively. The sensitivity and specificity of DFA in comparisoin to saline method were 91.2%, 87.9% respectively. The sensitivity of iodine method and saline method in compariosn to DFA were 82.2%, 68.8% respectively. There is mark diffrence in sensitivity of DFA to conventional method. Conclusion: The study supported findings of other investigators who concluded that DFA method have the greater sensitivity. The immunologic methods were more efficient and quicker than the conventional O&P method.

Keywords: direct immunofluorescence assay (DFA), ova and parasite (O&P), Giardia lamblia, children, medical science

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Authors: Akhad Ibrokhimov

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Update of preventive medicine has exacerbated the problem of cause-and-effect relationship between the presence of herpetic stomatitis (HS) and periodontal disease. Comprehensive survey of children with herpetic stomatitis, according to WHO equirements, on the territory of Tashkent years was conducted. Objective: To analyze the prevalence and intensity of periodontal tissue diseases in children with herpetic stomatitis. Materials and methods. Dental disease in Tashkent was studied in 156 children with herpetic stomatitis, as a control, the incidence of dental studied in 153 children of comparable age and sex never without a history of herpetic stomatitis. Results and discussion. The study revealed that 42,86 ± 13,23% of children with Herpetic stomatitis in the age group 6 years, 1 month - 10 years suffered from periodontal disease, the incidence of periodontal disease in the control group was 14,29 ± 9,35% (R≥0 05) corresponding to the frequency of detection of sextants with bleeding and tartar was equal to 35,71 ± 12,80% vs. 7,14 ± 6,88% (R≥0,05) and 14,29 ± 9,35% against 7 14 ± 6,88% (R≥0,05). Status of periodontal tissues was assessed in age groups 6 years, 1 month - 10 years and 10 years, 1 month - 15 years. The intensity of periodontal lesions observed at the level of 1,79 ± 0,06 vs. 0,66 ± 0,03 (P ≤ 0,05) affected sextant, including sextants with bleeding 1,62 ± 0,07 vs. 0.65 ± 0 , 03 (P ≤ 0,05) and sextants tartar - 0,17 ± 0,008 vs. 0,10 ± 0,008 (P ≤ 0,05). At age 10 years, 1 month - 15 years, a higher prevalence of signs of periodontal lesion was identified in patients with table of contents in 80,00 ± 12,65% of cases versus 30,00 ± 14,49% (P ≤ 0,05), and prevailed bleeding gums 70,00 ± 14,49% against 20,00 ± 11,83% (p ≤ 0.05), tartar was diagnosed respectively in 30,00 ± 14,49% against 10,00 ± 9,48% (R≥0,05) surveyed.

Keywords: vestibular surface, abnormal abrasion, composites, prosthesis

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Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang

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Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.

Keywords: air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF

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Authors: Amanpreet Kaur, Ravinder Agarwal, Amod Kumar

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Surface electromyography is a strategy to measure the muscle activity of the skin. Sensors placed on the skin recognize the electrical current or signal generated by active muscles. A lot of the research has focussed on the detection of signal from upper limb amputee with activity of triceps and biceps muscles. The purpose of this study was to correlate phantom movement and sEMG activity in residual stump muscles of transhumeral amputee from the shoulder muscles. Eight non- amputee and seven right hand amputees were recruited for this study. sEMG data were collected for the trapezius, pectoralis and teres muscles for elevation, protraction and retraction of shoulder. Contrast between the amputees and non-amputees muscles action have been investigated. Subsequently, to investigate the impact of class separability for different motions of shoulder, analysis of variance for experimental recorded data was carried out. Results were analyzed to recognize different shoulder movements and represent a step towards the surface electromyography controlled system for amputees. Difference in F ratio (p < 0.05) values indicates the distinction in mean therefore these analysis helps to determine the independent motion. The identified signal would be used to design more accurate and efficient controllers for the upper-limb amputee for researchers.

Keywords: around shoulder amputation, surface electromyography, analysis of variance, features

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Authors: Hadi Ardiny, Amir Mohammad Beigzadeh

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Through the utilization of a combination of various sensors and data fusion methods, the detection of potential nuclear threats can be significantly enhanced by extracting more information from different data. In this research, an experimental and modeling approach was employed to track a radioactive source by combining a surveillance camera and a radiation detector (NaI). To run this experiment, three mobile robots were utilized, with one of them equipped with a radioactive source. An algorithm was developed in identifying the contaminated robot through correlation between camera images and camera data. The computer vision method extracts the movements of all robots in the XY plane coordinate system, and the detector system records the gamma-ray count. The position of the robots and the corresponding count of the moving source were modeled using the MCNPX simulation code while considering the experimental geometry. The results demonstrated a high level of accuracy in finding and locating the target in both the simulation model and experimental measurement. The modeling techniques prove to be valuable in designing different scenarios and intelligent systems before initiating any experiments.

Keywords: nuclear threats, radiation detector, MCNPX simulation, modeling techniques, intelligent systems

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Authors: Mukhtar Raban

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Nelson Mandela University subscribes to a humanizing pedagogy (HP), as housed under broader critical pedagogy, that underpins and informs learning and teaching activities at the institution. The investigation sought to explore the implications of humanizing and critical pedagogical considerations for a technology-enhanced language learning (TELL) environment in a university course. The paper inquires into the design of a learning resource in an online learning environment of an English communication module, that applied HP principles. With an objective of creating agentive spaces for foregrounding identity, student voice, critical self-reflection, and recognition of others’ humanity; a flexible and open 'My Presence' feature was added to the TELL environment that allowed students and lecturers to share elements of their backgrounds in a ‘mutually vulnerable’ manner as a way of establishing digital identity and a more ‘human’ presence in the online language learning encounter, serving as a catalyst for the recognition of the ‘other’. Following a qualitative research design, the study adopted an auto-ethnographic approach, complementing the critical inquiry nature embedded into the activity’s practices. The study’s findings provide critical reflections and deductions on the possibilities of leveraging digital human expression within a humanizing pedagogical framework to advance the realization of HP-adoption in language learning and teaching encounters. It was found that the consideration of humanizing pedagogical principles in the design of online learning was more effective when the critical outcomes were explicated to students and lecturers prior to the completion of the activities. The integration of humanizing pedagogy also led to a contextual advancement of ‘affective’ language learning. Upon critical reflection and analysis, student identity and agency can flourish in a technology-enhanced learning environment when humanizing, and critical pedagogy influences the learning design.

Keywords: critical reflection, humanizing pedagogy, student identity, technology-enhanced language learning

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Authors: Aminu Abdullahi Isyaku

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Semi-arid Bornu basin in northeast Nigeria is characterised with flat topography, thick cover sediments and lack of continuous bedrock outcrops discernible for field geology. This paper presents the methodology for the characterisation of neotectonic surface structures and surface lithology in the north-eastern Bornu basin in northeast Nigeria as an alternative approach to field geological mapping using free multispectral Landsat 7 ETM+, SRTM DEM and ASAR Earth Observation datasets. Spectral lithological mapping herein developed utilised spectral discrimination of the surface features identified on Landsat 7 ETM+ images to infer on the lithology using four steps including; computations of band combination images; band ratio images; supervised image classification and inferences of the lithological compositions. Two complementary approaches to lineament mapping are carried out in this study involving manual digitization and automatic lineament extraction to validate the structural lineaments extracted from the Landsat 7 ETM+ image mosaic covering the study. A comparison between the mapped surface lineaments and lineament zones show good geospatial correlation and identified the predominant NE-SW and NW-SE structural trends in the basin. Topographic profiles across different parts of the Bama Beach Ridge palaeoshorelines in the basin appear to show different elevations across the feature. It is determined that most of the drainage systems in the northeastern Bornu basin are structurally controlled with drainage lines terminating against the paleo-lake border and emptying into the Lake Chad mainly arising from the extensive topographic high-stand Bama Beach Ridge palaeoshoreline.

Keywords: Bornu Basin, lineaments, spectral lithology, tectonics

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Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park

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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.

Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement

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Authors: S. Aouabdi, M. Taibi

Abstract:

The supervision of chemical processes is the subject of increased development because of the increasing demands on reliability and safety. An important aspect of the safe operation of chemical process is the earlier detection of (process faults or other special events) and the location and removal of the factors causing such events, than is possible by conventional limit and trend checks. With the aid of process models, estimation and decision methods it is possible to also monitor hundreds of variables in a single operating unit, and these variables may be recorded hundreds or thousands of times per day. In the absence of appropriate processing method, only limited information can be extracted from these data. Hence, a tool is required that can project the high-dimensional process space into a low-dimensional space amenable to direct visualization, and that can also identify key variables and important features of the data. Our contribution based on powerful techniques for development of a new monitoring method based on multi-scale entropy MSE in order to characterize the behaviour of the concentrations of different gases present in synthesis and soft sensor based on PCA is applied to estimate these variables.

Keywords: ammonia synthesis, concentrations of different gases, soft sensor, multi-scale entropy, multivarite statistics

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Authors: Noor Azwa Azreen Binti Abd. Aziz, Muhamad Zaim Bin Mohd Rozi

Abstract:

Moving towards the 4th Industrial Revolution, artificial intelligence (AI) is now more popular than ever. This subject is gaining significance every day and is continually expanding, often merging with other fields. Instead of merely being passive observers, there are benefits to understanding modern technology by delving into its inner workings. However, in a world teeming with digital information, the impact of AI on the spread of disinformation has garnered significant attention. The dissemination of inaccurate or misleading information is referred to as misinformation, posing a serious threat to democratic society, public debate, and individual decision-making. This article delves deep into the connection between AI and the dissemination of false information, exploring its potential, risks, and ethical issues as AI technology advances. The rise of AI has ushered in a new era in the dissemination of misinformation as AI-driven technologies are increasingly responsible for curating, recommending, and amplifying information on online platforms. While AI holds the potential to enhance the detection and mitigation of misinformation through natural language processing and machine learning, it also raises concerns about the amplification and propagation of false information. AI-powered deepfake technology, for instance, can generate hyper-realistic videos and audio recordings, making it increasingly challenging to discern fact from fiction.

Keywords: artificial intelligence, digital information, disinformation, ethical issues, misinformation

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Authors: Hee-Jae Suh, Kyung-Su Kim, Min-Ji Kim, Yeon-Seong Jeong, Ok-Hwan Lee, Jae-Wook Shin, Hyang-Sook Chun, Chan Lee

Abstract:

Canthaxanthin is keto-carotenoid produced from beta-carotene and it has been approved to be used in many countries as a food coloring agent. Canthaxanthin has been analyzed using High Performance Liquid Chromatography (HPLC) system with various ways of pretreatment methods. Four official methods for verification of canthaxanthin at FSA (UK), AOAC (US), EFSA (EU) and MHLW (Japan) were compared to improve its analytical and the pretreatment method. The Linearity, the limit of detection (LOD), the limit of quantification (LOQ), the accuracy, the precision and the recovery ratio were determined from each method with modification in pretreatment method. All HPLC methods exhibited correlation coefficients of calibration curves for canthaxanthin as 0.9999. The analysis methods from FSA, AOAC, and MLHW showed the LOD of 0.395 ppm, 0.105 ppm, and 0.084 ppm, and the LOQ of 1.196 ppm, 0.318 ppm, 0.254 ppm, respectively. Among tested methods, HPLC method of MHLW with modification in pretreatments was finally selected for the analysis of canthaxanthin in lab, because it exhibited the resolution factor of 4.0 and the selectivity of 1.30. This analysis method showed a correlation coefficients value of 0.9999 and the lowest LOD and LOQ. Furthermore, the precision ratio was lower than 1 and the accuracy was almost 100%. The method presented the recovery ratio of 90-110% with modification in pretreatment method. The cross-validation of coefficient variation was 5 or less among tested three institutions in Korea.

Keywords: analytic method, canthaxanthin, food colorants, pretreatment method

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Authors: P. Michael Preetam Raj, Souri Banerjee, Souvik Kundu

Abstract:

Oxide based memristors were fabricated in order to establish its potential applications in analog/digital electronics. BaTiO₃-BiFeO₃ (BT-BFO) was employed as an active material, whereas platinum (Pt) and Nb-doped SrTiO₃ (Nb:STO) were served as a top and bottom electrodes, respectively. Piezoelectric force microscopy (PFM) was utilized to present the ferroelectricity and repeatable polarization inversion in the BT-BFO, demonstrating its effectiveness for resistive switching. The fabricated memristors exhibited excellent electrical characteristics, such as hysteresis current-voltage (I-V), high on/off ratio, high retention time, cyclic endurance, and low operating voltages. The band-alignment between the active material BT-BFO and the substrate Nb:STO was experimentally investigated using X-Ray photoelectron spectroscopy, and it attributed to staggered heterojunction alignment. An energy band diagram was proposed in order to understand the electrical transport in BT-BFO/Nb:STO heterojunction. It was identified that the I-V curves of these memristors have several discontinuities. Curve fitting technique was utilized to analyse the I-V characteristic, and the obtained I-V equations were found to be parabolic. Utilizing this analysis, a non-linear BT-BFO memristors equivalent circuit model was developed. Interestingly, the obtained equivalent circuit of the BT-BFO memristors mimics the identical electrical performance, those obtained in the fabricated devices. Based on the developed equivalent circuit, a finite state machine (FSM) design was proposed. Efforts were devoted to fabricate the same FSM, and the results were well matched with those in the simulated FSM devices. Its multilevel noise filtering and immunity to external noise characteristics were also studied. Further, the feature of variable negative resistance was established by controlling the current through the memristor.

Keywords: band alignment, finite state machine, polarization inversion, resistive switching

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Authors: Meareg Amare, Senait Aklog

Abstract:

Lignin film was deposited at the surface of the glassy carbon electrode potential-statically. In contrast to the unmodified glassy carbon electrode, an oxidative peak with an improved current and overpotential for caffeine at the modified electrode showed catalytic activity of the modifier towards oxidation of caffeine. Linear dependence of peak current on caffeine concentration in the range 6 × 10⁻⁶ to 100 × 10⁻⁶ mol L⁻¹ with determination coefficient and method detection limit (LoD = 3 s/slope) of 0.99925 and 8.37 × 10⁻⁷ mol L⁻¹, respectively, supplemented by recovery results of 93.79–102.17%, validated the developed method. An attempt was made to determine the caffeine content of aqueous coffee extracts of Ethiopian coffees grown in four coffee cultivating localities (Wonbera, Wolega, Finoteselam, and Zegie) and hence to evaluate the correlation between users preference and caffeine content. In agreement with reported works, caffeine contents (w/w%) of 0.164 in Wonbera coffee; 0.134 in Wolega coffee; 0.097 in Finoteselam coffee; and 0.089 in Zegie coffee were detected, confirming the applicability of the developed method for determination of caffeine in a complex matrix environment. The result indicated that users’ highest preference for Wonbera and least preference for Zegie cultivated coffees are in agreement with the caffeine content.

Keywords: electrochemical, lignin, caffeine, electrode

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Authors: Salha Abdullah Ali Al-Shamrani, Maha Muhammad Dhaher Aljuhani, Eman Ali Ahmed Aldhaheri

Abstract:

With the proliferation of Internet of Things (IoT) devices in various industries, there has been a concurrent rise in security vulnerabilities, particularly spoofing attacks. This study explores the potential of blockchain technology in enhancing the security of IoT systems and mitigating these attacks. Blockchain's decentralized and immutable ledger offers significant promise for improving data integrity, transaction transparency, and tamper-proofing. This research develops and implements a blockchain-based IoT architecture and a reference network to simulate real-world scenarios and evaluate a blockchain-integrated intrusion detection system. Performance measures including time delay, security, and resource utilization are used to assess the system's effectiveness, comparing it to conventional IoT networks without blockchain. The results provide valuable insights into the practicality and efficacy of employing blockchain as a security mechanism, shedding light on the trade-offs between speed and security in blockchain deployment for IoT. The study concludes that despite minor increases in time consumption, the security benefits of incorporating blockchain technology into IoT systems outweigh potential drawbacks, demonstrating a significant potential for blockchain in bolstering IoT security.

Keywords: internet of things, spoofing, IoT, access control, blockchain, raspberry pi

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Authors: Zohre Soleymani, Meisam Amirzadeh

Abstract:

Many products are safety critical, so proactive analysis techniques are vital for them because these techniques try to identify potential failures before the products are produced. Failure Mode and Effective Analysis (FMEA) is an effective tool in identifying probable problems of product or process and prioritizing them and planning for its elimination. The paper shows the implementation of FMEA process to identify and remove potential troubles of aero fuel pumps manufacturing process and improve the reliability of subsystems. So the different possible causes of failure and its effects along with the recommended actions are discussed. FMEA uses Risk Priority Number (RPN) to determine the risk level. RPN value is depending on Severity(S), Occurrence (O) and Detection (D) parameters, so these parameters need to be determined. After calculating the RPN for identified potential failure modes, the corrective actions are defined to reduce risk level according to assessment strategy and determined acceptable risk level. Then FMEA process is performed again and RPN revised is calculated. The represented results are applied in the format of a case study. These results show the improvement in manufacturing process and considerable reduction in aero fuel pump production risk level.

Keywords: FMEA, risk priority number, aero pump, corrective action

Procedia PDF Downloads 286