Search results for: normal operators

Authors: Mustafa M. Donma, Ayşen Haksayar, Bahadır Batar, Buse Tepe, Birol Topçu, Orkide Donma

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Childhood obesity is an ever-increasing health problem. The Association of obesity with severe chronic diseases such as diabetes and cardiovascular diseases makes the problem life-threatening. Aside from psychological, societal and metabolic factors, genetic polymorphisms have gained importance concerning etiology in recent years. The aim of this study was to evaluate the relationship between rs10455872 gene polymorphism in the Lipoprotein (a) locus and the development of childhood obesity. This was a prospective study carried out according to the Helsinki Declarations. The study protocol was approved by the Institutional Ethics Committee. This study was supported by Tekirdag Namik Kemal University Rectorate, Scientific Research Projects Coordination Unit. Project No: NKUBAP.02.TU.20.278. A total of 180 children (103 obese (OB) and 77 healthy), aged 6-18 years, without any acute or chronic disease, participated in the study. Two different groups were created: OB and healthy control. Each group was divided into two further groups depending on the nature of the polymorphism. Anthropometric measurements were taken during the detailed physical examination. Laboratory tests and TANITA measurements were performed. For the statistical evaluations, SPSS version 28.0 was used. A P-value smaller than 0.05 was the statistical significance degree. The distribution of lipoprotein (a) rs10455872 gene polymorphism did not differ between OB and healthy children. Children with AG genotype in both OB and control groups had lower body mass index (BMI), diagnostic obesity notation model assessment index (DONMA II), body fat ratio (BFR), C-reactive protein (CRP), and metabolic syndrome index (MetS index) values compared to children with normal AA genotype. In the OB group, serum iron, vitamin B12, hemoglobin, MCV, and MCH values were found to be higher in the AG genotype group than those of children with the normal AA genotype. A significant correlation was found between the MetS index and BFR among OB children with normal homozygous genotype. MetS index increased as BFR increased in this group. However, such a correlation was not observed in the OB group with heterozygous AG genotype. To the best of our knowledge, the association of lipoprotein (a) rs10455872 gene polymorphism with the etiology of childhood obesity has not been studied yet. Therefore, this study was the first report suggesting polymorphism with AG genotype as a good risk factor for obesity.

Keywords: child, gene polymorphism, lipoprotein (a), obesity, rs10455872

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Authors: Hemendra Singh Rathod

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Frequency is, among other factors, one of the governing parameters for maintaining electrical grid stability. The quality of an electrical transmission and supply system is mainly described by the stability of the grid frequency. Over the past few decades, energy generation by intermittent sustainable sources like wind and solar has seen a significant increase globally. Consequently, controlling the associated deviations in grid frequency within safe limits has been gaining momentum so that the balance between demand and supply can be maintained. Lithium-ion battery energy storage system (Li-Ion BESS) has been a promising technology to tackle the challenges associated with grid instability. BESS is, therefore, an effective response to the ongoing debate whether it is feasible to have an electrical grid constantly functioning on a hundred percent renewable power in the near future. In recent years, large-scale manufacturing and capital investment into battery production processes have made the Li-ion battery systems cost-effective and increasingly efficient. The Li-ion systems require very low maintenance and are also independent of geographical constraints while being easily scalable. The paper highlights the use of stationary and moving BESS for balancing electrical energy, thereby maintaining grid frequency at a rapid rate. Moving BESS technology, as implemented in the selected railway network in Germany, is here considered as an exemplary concept for demonstrating the same functionality in the electrical grid system. Further, using certain applications of Li-ion batteries, such as self-consumption of wind and solar parks or their ancillary services, wind and solar energy storage during low demand, black start, island operation, residential home storage, etc. offers a solution to effectively integrate the renewables and support Europe’s future smart grid. EMT software tool DIgSILENT PowerFactory has been utilised to model an electrical transmission system with 100% renewable energy penetration. The stability of such a transmission system has been evaluated together with BESS within a defined frequency band. The transmission system operators (TSO) have the superordinate responsibility for system stability and must also coordinate with the other European transmission system operators. Frequency control is implemented by TSO by maintaining a balance between electricity generation and consumption. Li-ion battery systems are here seen as flexible, controllable loads and flexible, controllable generation for balancing energy pools. Thus using Li-ion battery storage solution, frequency-dependent load shedding, i.e., automatic gradual disconnection of loads from the grid, and frequency-dependent electricity generation, i.e., automatic gradual connection of BESS to the grid, is used as a perfect security measure to maintain grid stability in any case scenario. The paper emphasizes the use of stationary and moving Li-ion battery storage for meeting the demands of maintaining grid frequency and stability for near future operations.

Keywords: frequency control, grid stability, li-ion battery storage, smart grid

Procedia PDF Downloads 127

Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Nadjet Brahmia

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The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transportation (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria (organizational, technical, geographical, etc.). As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems (such as GIS, RDBMS…), so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: ODT, geomatics, GIS, transport systems

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Authors: Dong-ping Yuan, Lin Gu, Jun Long, Jie Chen, Ni Jie, Ying-Li Shi

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Endometriosis is a common disease in women of reproductive age, whose classic characteristic is mononuclear cell infiltration into lesions. Shikonin is an anti-inflammatory phytocompound from Lithospermum erythrorhizon, whose potential therapeutic effects for the endometriosis remain unclear. The working hypothesis was that shikonin can inhibit the development of endometriosis by the inhibition of chemotactic effect. Shikonin significantly inhibited the growth of human endometrial tissue implanted into mice (P<0.05). No observable adverse effects were found. The mouse regulated upon activation normal T-cell expressed and secreted (mRANTES) level in peritoneal fluid of animal endometriosis model was higher than that in normal SCID mice (P<0.05), and decreased dramatically after shikonin treatment in a dose-dependent manner (P<0.05). Peritoneal fluid from NOD/SCID mice treated with shikonin inhibited monocytes chemotaxis, which could be abolished by mRANTES antibody. In vitro, shikonin significantly inhibited RANTES expression of U937 cells cultured alone or co-cultured with human methothelail cells and endometrial stromal cells, and inhibited RANTES-induced chemotaxis of U937 cells (P<0.05). The present results suggest that shikonin can inhibit the development of endometriosis by mechanisms that at least include the inhibition of RANTES expression and decreased migration of mononuclear cells to lesions. Shikonin may be a useful and safe new approach for treating endometriosis.

Keywords: endometriosis, shikonin, RANTES chemotaxis

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Authors: Fariborz Ahmadi, Reza Tati

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Genetic algorithm is a soft computing method that works on set of solutions. These solutions are called chromosome and the best one is the absolute solution of the problem. The main problem of this algorithm is that after passing through some generations, it may be produced some chromosomes that had been produced in some generations ago that causes reducing the convergence speed. From another respective, most of the genetic algorithms are implemented in software and less works have been done on hardware implementation. Our work implements genetic algorithm in hardware that doesn’t produce chromosome that have been produced in previous generations. In this work, most of genetic operators are implemented without producing iterative chromosomes and genetic diversity is preserved. Genetic diversity causes that not only do not this algorithm converge to local optimum but also reaching to global optimum. Without any doubts, proposed approach is so faster than software implementations. Evaluation results also show the proposed approach is faster than hardware ones.

Keywords: hardware, genetic algorithm, computer science, engineering

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Authors: Pegah Farshadmanesh, Jamshid Mohammadi, Mehdi Modares

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In nearly all earthquakes of the past century that resulted in moderate to significant damage, the occurrence of postearthquake fire ignition (PEFI) has imposed a serious hazard and caused severe damage, especially in urban areas. In order to reduce the loss of life and property caused by post-earthquake fires, there is a crucial need for predictive models to estimate the PEFI risk. The parameters affecting PEFI risk can be categorized as: 1) factors influencing fire ignition in normal (non-earthquake) condition, including floor area, building category, ignitability, type of appliance, and prevention devices, and 2) earthquake related factors contributing to the PEFI risk, including building vulnerability and earthquake characteristics such as intensity, peak ground acceleration, and peak ground velocity. State-of-the-art statistical PEFI risk models are solely based on limited available earthquake data, and therefore they cannot predict the PEFI risk for areas with insufficient earthquake records since such records are needed in estimating the PEFI model parameters. In this paper, the correlation between normal condition ignition risk, peak ground acceleration, and PEFI risk is examined in an effort to offer a means for predicting post-earthquake ignition events. An illustrative example is presented to demonstrate how such correlation can be employed in a seismic area to predict PEFI hazard.

Keywords: fire risk, post-earthquake fire ignition (PEFI), risk management, seismicity

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Authors: Maryam Zahedifard, Fadhil Lafta Faraj, Maryam Hajrezaie, Nazia Abdul Majid, Mahmood Ameen Abdulla, Hapipah Mohd Ali

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In the current study, we prepared two new quinazoline schiff bases through condensation reaction of 2-aminobenzhydrazide with 5-bromosalicylaldehyde and 3-methoxy-5-bromosalicylaldehyde. The chemical structures of both newly synthesized compounds (1 and 2) were confirmed by FT-IR and X-ray crystallography studies. The cytotoxic effect of compounds was investigated against MCF-7 human breast cancer cells. MTT results showed that (1) and (2) decreased the viability of MCF-7 cells in a time-dependent manner, exhibiting an IC50 value of 3.23 ± 0.28 µg/mL and 3.41 ± 0.34 µg/mL, respectively, after a 72-hours treatment period. In contrast, they did not show significant anti-proliferative effect towards MCF-10A normal breast cells and WRL-68 normal liver cells. We found a perturbation in mitochondrial membrane potential and increased cytochrome c release from the mitochondria to the cytosol, suggesting an activation of apoptosis by compounds, which was confirmed by activation of the initiator caspase-9 and the executioner caspases-3/7. (1) was also able to trigger extrinsic pathway via activation of caspase-8 and inhibition of NF-κB translocation. The acute toxicity test showed no toxicity effect of the compounds in rats. Our results showed that the selected synthesized compounds are highly potent to induce apoptosis in MCF-7 cells via either intrinsic or extrinsic mitochondrial pathway.

Keywords: Quinazoline Schiff base, apoptosis, MCF-7 human breast cancer cell line, caspase, NF-κB translocation

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Authors: Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, Léo Fréchier, Barthélémy Hermenault

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Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.

Keywords: deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering

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Authors: Bagul Abhijeet

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Background: Client-Server model is the backbone of today’s internet communication. In which normal user can not have control over particular website or server? By using the same processing model one can have unauthorized access to particular server. In this paper, we discussed about application scenario of hacking for simple website or server consist of unauthorized way to access the server database. This application emerges to autonomously take direct access of simple website or server and retrieve all essential information maintain by administrator. In this system, IP address of server given as input to retrieve user-id and password of server. This leads to breaking administrative security of server and acquires the control of server database. Whereas virus helps to escape from server security by crashing the whole server. Objective: To control malicious attack and preventing all government website, and also find out illegal work to do hackers activity. Results: After implementing different hacking as well as non-hacking techniques, this system hacks simple web sites with normal security credentials. It provides access to server database and allow attacker to perform database operations from client machine. Above Figure shows the experimental result of this application upon different servers and provides satisfactory results as required. Conclusion: In this paper, we have presented a to view to hack the server which include some hacking as well as non-hacking methods. These algorithms and methods provide efficient way to hack server database. By breaking the network security allow to introduce new and better security framework. The terms “Hacking” not only consider for its illegal activities but also it should be use for strengthen our global network.

Keywords: Hacking, Vulnerabilities, Dummy request, Virus, Server monitoring

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Authors: B. A. Adeniyi, S. A. Daud, O. Amao

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The study investigates consumer demand for meat products in Oyo West Local Government using linear approximate almost ideal demand system (LA/AIDS). Questions that were addressed by the study include: first, what is the type and quantity of meat products available to the household and their demand pattern? Second is the investigation of the factors that affect meat products demand pattern and proportion of income that is spent on them. For the above purpose cross-sectional data were collected from 156 households of the study area and analyzed to reveal the functional relationship between meat products consumption and some socio-economic variables of the household. Results indicated that per capita meat consumption increased as household income and education increased but decreased with age. It was also found that male tend to consume more meat products than their female counterparts and that increase in household size will first increased per caput meat consumption but later decreased it. Price also tends to greatly influence the demand pattern of meat products. The results of elasticity computed from the results of regression analysis revealed that own price elasticity for all meat products were negative which indicated that they were normal products while cross and expenditure elasticity were positive which further confirmed that meat products were normal and substitute products. This study therefore concludes that the relevance of these variables imposed a great challenge to the policy makers and the government, in the sense that more cost effective methods of meat production technology have to be devised in other to make consumption of meat products more affordable.

Keywords: meat products, consumption, animal production, technology

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Ayad Salih Sabbar, Amin Chegenizadeh, Hamid Nikraz

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Utilizing waste materials in civil engineering applications has a positive influence on the environment by reducing carbon dioxide emissions and issues associated with waste disposal. Granulated blast furnace slag (GBFS) is a by-product of the iron and steel industry, with millions of tons of slag being annually produced worldwide. Slag has been widely used in structural engineering and for stabilizing clay soils; however, studies on the effect of slag on sandy soils are scarce. This article investigates the effect of slag content on shear strength parameters through direct shear tests and unconsolidated undrained triaxial tests on mixtures of Perth sand and slag. For this purpose, sand-slag mixtures, with slag contents of 2%, 4%, and 6% by weight of samples, were tested with direct shear tests under three normal stress values, namely 100 kPa, 150 kPa, and 200 kPa. Unconsolidated undrained triaxial tests were performed under a single confining pressure of 100 kPa and relative density of 80%. The internal friction angles and shear stresses of the mixtures were determined via the direct shear tests, demonstrating that shear stresses increased with increasing normal stress and the internal friction angles and cohesion increased with increasing slag. There were no significant differences in shear stresses parameters when slag content rose from 4% to 6%. The unconsolidated undrained triaxial tests demonstrated that shear strength increased with increasing slag content.

Keywords: direct shear, shear strength, slag, UU test

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Authors: Mohadeseh Shojaei Shahrokhabadi, Ding-Geng (Din) Chen

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Positive continuous outcomes with a substantial number of zero values and incomplete longitudinal follow-up are quite common in medical cost data. To jointly model semi-continuous longitudinal cost data and survival data and to provide marginalized covariate effect estimates, a marginalized two-part joint model (MTJM) has been developed for outcome variables with lognormal distributions. In this paper, we propose MTJM models for outcome variables from a generalized gamma (GG) family of distributions. The GG distribution constitutes a general family that includes approximately all of the most frequently used distributions like the Gamma, Exponential, Weibull, and Log Normal. In the proposed MTJM-GG model, the conditional mean from a conventional two-part model with a three-parameter GG distribution is parameterized to provide the marginal interpretation for regression coefficients. In addition, MTJM-gamma and MTJM-Weibull are developed as special cases of MTJM-GG. To illustrate the applicability of the MTJM-GG, we applied the model to a set of real electronic health record data recently collected in Iran, and we provided SAS code for application. The simulation results showed that when the outcome distribution is unknown or misspecified, which is usually the case in real data sets, the MTJM-GG consistently outperforms other models. The GG family of distribution facilitates estimating a model with improved fit over the MTJM-gamma, standard Weibull, or Log-Normal distributions.

Keywords: marginalized two-part model, zero-inflated, right-skewed, semi-continuous, generalized gamma

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: V. R. Ahire, A. Kumar, B. N. Pandey, K. P. Mishra, G. R. Kulkarni

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Radiation therapy is an effective vital strategy used globally in the treatment of cervical cancer. However, radiation efficacy principally depends on the radiosensitivity of the tumor, and not all patient exhibit significant response to irradiation. A radiosensitive tumor is easier to cure than a radioresistant tumor which later advances to local recurrence and metastasis. Herbal polyphenols are gaining attention for exhibiting radiosensitization through various signaling. Current work focuses to study the radiosensitization effect of ellagic acid (EA), on HeLa cells. EA intermediated radiosensitization of HeLa cells was due to the induction γ-H2AX foci formation, G1 phase cell cycle arrest, and loss of reproductive potential, growth inhibition, drop in the mitochondrial membrane potential and protein expression studies that eventually induced apoptosis. Irradiation of HeLa in presence of EA (10 μM) to doses of 2 and 4 Gy γ-radiation produced marked tumor cytotoxicity. EA also demonstrated radio-protective effect on normal cell, NIH3T3 and aided recovery from the radiation damage. Our results advocate EA to be an effective adjuvant for improving cancer radiotherapy as it displays striking tumor cytotoxicity and reduced normal cell damage instigated by irradiation.

Keywords: apoptotic radiosensitivity, ellagic acid, mitochondrial potential, cell-cycle arrest

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Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

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This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: hit-or-miss operator transform, HMT, binary morphological operation, shape detection, binary images processing

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Authors: Tais Silva Lopes, Danilo Caneppele, Elizabeth Romagosa

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Surubim-do-Paraíba, Steindachneridion parahybae is a species of South American fish in critical conditions of extinction. Researches have been developed with the objective of conserving the biological material of this species. We evaluated the cooling of mature oocytes in the cryoprotective solutions containing the following alcohols: methanol, Propylene glycol and DMSO, each at concentrations of 1M, 2M and 4M, totaling nine treatments. After being submitted to treatments, the oocytes were maintained for 120 minutes in cooling to -5.52±2.58⁰C. A sample of oocytes was submitted to negative control (NC), kept in 90% L-15 solution, and positive control (PC), fertilized and taken directly to the incubator. Fertilization and hatching rates were evaluated. In order to compare the sensitivity of oocytes to embryos of the same species, the embryos maintained as CP in the previous assay were used in the free-flow stage (about 22 hours post fertilization) and submitted to the same treatments (prepared in distilled water) and also cooled for 120 min. The evaluation was done by the hatch rate. There was no fertilization rate of the oocytes submitted to the cooling with propylene glycol; the other cryoprotectants presented values of at most 3.7% of fertilization (Methanol 1M), and no treatment completed development until hatching. The cooled embryos had a significant percentage of normal larvae in all treatments, but inversely proportional to the increase in the concentration of the alcohols. DMSO 1M was the most promising treatment for embryo cooling, with 41.7% ± 20.2 of normal larvae, while mature oocytes were highly sensitive to cold.

Keywords: cryoconservation, cooling, embryos, freezing, oocytes, south American fish

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Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

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Background: The negative consequences of intimate partner violence (IPV) on children have not been studied extensively. This study aimed to determine the prevalence of different types of IPV and its association with children’s growth and developmental problems. Methods: In a descriptive-analytical study, 596 mothers of one-year-old children referred to the primary health centers in Gonbad-e- Kavoos city were recruited (2018). The data were collected using the World Health Organization Domestic Violence, Ages and Stages Questionnaire-12 and the socio-economic, obstetrics, demographic and anthropometric characteristics related questionnaire. BMI Z-Score was categorized into three grades; thin (Z<-2), normal (-2≤Z<1), and overweight-obese (Z≥1). The data were analyzed using descriptive analysis, chi-square test, and regression. Results: The prevalence of physical, psychological, and sexual IPV was 7.4%, 29.5%, and 2.4%, respectively. Most of the children were of normal weight at one-year-old (91.7%). Similarly, the prevalence of overweight and obese was 13.3% and 8%, respectively. 2% of children had developmental problems at age one. There was a significant relationship between the father’s education and occupation and IPV and children’s delay in growth, respectively. There was no significant difference between BMI Z-Score and developmental disabilities in the children in women exposed and not exposed to all types of IPV. Conclusions: The prevalence of psychological IPV was common. IPV and children’s growth problems were influenced by the father’s socio-economic status. Preventing psychological IPV as a forerunner of other types of IPV and improving the economic situation may help in the reduction of these difficulties.

Keywords: children, development, growth, intimate partner violence

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Authors: Praveenkumar Natarajan

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A 59-year-old male with no known co-morbidities was admitted to a private hospital for complaints of fever and cough and was diagnosed to haveCOVID-19. CT of the thorax revealed the involvement of 50% of the lungs. Screening ECG and ECHO were normal. The patient was treated with oxygen therapy and drugs and was discharged after 12 days of admission. Post-discharge, the patient remained symptom-free and continued his work. After one month, the patient developed a fever for three days, for which he took antipyretics. Subsequently, the patient developed sudden onset breathlessness, which rapidly progressed to grade 4 NYHA, and developed a cough as well. Suspecting COVID-19 reinfection, the patient visited a nearby hospital, where COVID–19 rt-PCR swabs turned out to be positive, and was referred to our hospital. On receiving, the patient had diffuse lung crepitations and a diastolic murmur in the neo-aortic area. CT thorax revealed pulmonary edema with areas of consolidation. ECHO revealed vegetation on the aortic valve with severe aortic regurgitation. Blood cultures were taken, which revealed the growth of Enterococcus faecalis. The diagnosis of infective endocarditis was made, and the patient was started on appropriate treatment. COVID–19 has effects on various systems, including the cardiovascular system. Even though infective endocarditis is common in the elderly with valvular heart disease, this patient had developed infective endocarditis in an apparently normal aortic valve. Infective endocarditis and COVID–19 can have similar presentations leading to diagnostic difficulties. COVID–19, affecting the heart valves causing valvulitis and predisposing them to the development of infective endocarditis, is also an area to be explored.

Keywords: aortic regurgitation, COVID-19, infective endocarditis, valvulitis

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Authors: Aminu Hamza

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This study examines the factors that play vital role in the adoption of mobile payment system among consumers in Nigeria. Technology Acceptance Model (TAM) was used with two additional variables to form the conceptual model. The study was conducted in three Universities in Kano state, Nigeria. Convenience sampling method was used with a total valid 202 respondents which involved the students of Bayero University Kano (BUK), Northwest University, and Kano University of Science and Technology (KUST) Wudil, Kano, Nigeria. Results of the regression analysis revealed that Perceived ease of use (PEOU) and Perceived usefulness (PU) have significant and positive correlation with the behavioral intention to adopt mobile payment system. The findings of this study would be useful to the policy makers Central Bank of Nigeria (CBN), mobile network operators and providers of the services.

Keywords: mobile payment system, Nigeria, technology adoption, technology acceptance model

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Authors: William Cheng, Yuni Astria, Rini Sekartini

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Background: Prevalence of anemia among school-aged children is relatively high (25.4%). This condition can affect children’s life, including cognitive function. One of the most common factors that is associated with anemia in children is nutritional status. This simple indicator will be very helpful in identifying more population at risk. The aim of this study is to correlate the clinical implication of nutritional status to the prevalence of anemia in children, with intention to determine a more effective nutritional status indicator in detecting anemia. Method: Anthropometric and haemoglobin status were gathered from children between 5 to 7-years-old in one of the urban areas in Jakarta in 2012. We identified children with haemoglobin level under 11.5 as anemia and correlated them to their WHO z-score from each of these indicators: Body Weight for Age (normal weight and underweight), Height for Age (not stunted and stunted), and Body Mass Index for Age (not wasted and wasted). Results: A total of 195 children were included in this research and 57 of them (29,2%) were diagnosed as anemia. The majority of the children had good nutritional status, however, 30 (15,4%) of them were found to be underweight, 33 (16,9%) were stunted, and 1 children (0,5%) was wasted. There were no overweight result found in this population. From the three nutritional status indicators, none proved to be statistically significant in relation to the incidence of anemia (p>0.05). Out of 33 children who were diagnosed as stunted, 36.36 % were found to have anemia, in comparison to 27,7% of children who were not stunted. Meanwhile, among 30 children who were diagnosed as underweight, 33,3 % of them were anemic whereas only 28,4% of the normal weight group were anemic. Conclusion: In this study, there is no significant correlation between anemia with any nutritional status indicator. However, more than a third of the stunted children are proven to have low haemoglobin status. The finding of stunting in children should be given more attention to further investigate for anemia.

Keywords: school-aged children, nutritional status, anemia, pediatrics

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Authors: Wafa' Alsharafat, Suhila Farhan Abu-Owida

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Genetic algorithm (GA) is a powerful evolutionary searching technique that is used successfully to solve and optimize problems in different research areas. Genetic Algorithm (GA) considered as one of optimization methods used to solve Travel salesman Problem (TSP). The feasibility of GA in finding a TSP solution is dependent on GA operators; encoding method, population size, termination criteria, in general. In specific, crossover and its probability play a significant role in finding possible solutions for Symmetric TSP (STSP). In addition, the crossover should be determined and enhanced in term reaching optimal or at least near optimal. In this paper, we spot the light on using a modified crossover method called modified sequential constructive crossover and its impact on reaching optimal solution. To justify the relevance of a parameter value in solving the TSP, a set comparative analysis conducted on different crossover methods values.

Keywords: genetic algorithm, crossover, mutation, TSP

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Authors: Binoy Chandra Sarma, S. K. Deb

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Over 85% of industrial dryers are of the convective type with hot air or direct flue gases as the drying medium. Over 99% of the applications involve removal of water. In this study, the performance of a solar air heater with the recovery of the absorbed heat by the metallic concentrator sheet itself besides the normal heat accumulated by the receiver at the focus of the concentrator for generating drying air by convection at a low to medium temperature range is discussed. The system performance through thermal analysis & the performance of a model achieving the required temperature range is also investigate in this study. Over 85% of industrial dryers are of the convective type with hot air or direct flue gases as the drying medium. Over 99% of the applications involve removal of water. In this study, the performance of a solar air heater with the recovery of the absorbed heat by the metallic concentrator sheet itself besides the normal heat accumulated by the receiver at the focus of the concentrator for generating drying air by convection at a low to medium temperature range is discussed. The system performance through thermal analysis & the performance of a model achieving the required temperature range is also investigate in this study.

Keywords: dryer, polygeneration, moisture, equilibrium, humidity

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Authors: Kannapha Amaruchkul

Abstract:

We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

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Authors: Naoya Ozaki, Takuya Watanabe, Ryosuke Matsumoto, Noriko Fukasawa

Abstract:

In the metropolitan areas in Japan, in many stations, shopping areas are set up, and escalators and elevators are installed to make the stations be barrier-free. Further, many areas around the stations are being redeveloped. Railway business operators want to know how much effect these circumstances have on attractiveness of the station or number of passengers using the station. So, we performed a questionnaire survey of the station users in the metropolitan areas for finding factors to affect the attractiveness of stations. Then, based on the analysis of the survey, we developed a method to quantitatively evaluate attractiveness of the stations. We also developed an estimation method for number of passengers based on combination of attractiveness of the station quantitatively evaluated and the residential and labor population around the station. Then, we derived precise linear regression models estimating the attractiveness of the station and number of passengers of the station.

Keywords: attractiveness of the station, estimation method, number of passengers of the station, redevelopment around the station, renovation of the station

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Authors: Michelangelo Liban, Debbie Liquete

Abstract:

A 70-year-old right-handed Filipina was seen by the Neurology service due to a new onset headache, bi-occipital in location, dull squeezing in character with a pain score of 8/10 with associated nausea and one episode of non-projectile, which provided no relief. Due to the alarming features of the headache despite the absence of risk factors and an essentially normal neurologic examination, a cranial CTA+CTV was done, which revealed a small left frontal and small right pontine hyper density with minimal perilesional edema. Findings also revealed filling defects in the straight and right transverse sinus and a consideration of hypoplastic left transverse sinus with no definite evidence of aneurysm nor A-V malformation. She had normal levels of D-Dimer, Protein C, ANA and Anti-DS DNA but had a low Protein S of 56% (N.V is 70-120%). Antithrombin, homocysteine and Factor V Leiden were not done due to unavailability of the tests. She was then treated as a case of Cerebral Venous Thrombosis with multiple hemorrhage from venous infraction and was given anticoagulants which provided relief of the headache. She did not manifest with any further cortical, bulbar or sensorimotor deficits hence was discharged improved after 15 hospital days. To our knowledge, there are no case reports of patients with CVT from Protein S deficiency and venous anomaly that presented with multiple hemorrhage from venous infarction, more so affecting the brainstem. In this paper, a rare location of CVT in a newly diagnosed Protein S deficient patient is presented together with an uneventful course and favorable outcome.

Keywords: protein S deficiency, cerebral venous thrombosis, pontine hemorrhage from venous infarction, elderly

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Authors: Younghoon Kim, Seoung Bum Kim

Abstract:

One-class classification plays an important role in detecting outlier and abnormality from normal observations. In the previous research, several attempts were made to extend the scope of application of the one-class classification techniques to statistical process control problems. For most previous approaches, such as support vector data description (SVDD) control chart, the design of the control limits is commonly based on the assumption that the proportion of abnormal observations is approximately equal to an expected Type I error rate in Phase I process. Because of the limitation of the one-class classification techniques based on convex optimization, we cannot make the proportion of abnormal observations exactly equal to expected Type I error rate: controlling Type I error rate requires to optimize constraints with integer decision variables, but convex optimization cannot satisfy the requirement. This limitation would be undesirable in theoretical and practical perspective to construct effective control charts. In this work, to address the limitation of previous approaches, we propose the one-class classification algorithm based on the mixed integer programming technique, which can solve problems formulated with continuous and integer decision variables. The proposed method minimizes the radius of a spherically shaped boundary subject to the number of normal data to be equal to a constant value specified by users. By modifying this constant value, users can exactly control the proportion of normal data described by the spherically shaped boundary. Thus, the proportion of abnormal observations can be made theoretically equal to an expected Type I error rate in Phase I process. Moreover, analogous to SVDD, the boundary can be made to describe complex structures by using some kernel functions. New multivariate control chart applying the effectiveness of the algorithm is proposed. This chart uses a monitoring statistic to characterize the degree of being an abnormal point as obtained through the proposed one-class classification. The control limit of the proposed chart is established by the radius of the boundary. The usefulness of the proposed method was demonstrated through experiments with simulated and real process data from a thin film transistor-liquid crystal display.

Keywords: control chart, mixed integer programming, one-class classification, support vector data description

Procedia PDF Downloads 157

Authors: Fethia Zenak, Salima Benbernou, Linda Zaoui

Abstract:

Recently, many companies are based on process development from scratch to achieve their business goals. The process development is not trivial and the main objective of enterprise managing processes is to decrease the software development time. Several concepts have been proposed in the field of business process-based reused development, known as BP Mashup. This concept consists of reusing existing business processes which have been modeled in order to respond to a particular goal. To meet user process requirements, our contribution is to mix parts of processes as 'processes fragments' components to build a new process (i.e. process mashup). The main idea of our paper is to offer graphical framework tool for both creating and running processes mashup. Allow users to perform a mixture of fragments, using a simple interface with set of graphical mixture operators based on a proposed formal model. A process mashup and mixture behavior are described within a new specification of a high-level language, language for process mashup (BPML).

Keywords: business process, mashup, fragments, bp mashup

Procedia PDF Downloads 611

Authors: Ankita Dixit

Abstract:

A conference call using a mobile refers to a telephonic call in which several people talks to each other simultaneously. This is one of the most eminent features nowadays. This concept is already existing using LTE technology for mobile phones supporting SIM cards. Hence, currently, a conference call is possible only with the support of a SIM card, i.e., a Mobile operator. Bluetooth is a short-range wireless technology that is used for exchanging data between devices placed over short distances (up to 240 meters). This is a booming technology that is easily and freely available and has no dependency on network operators. Our study work proposes a smart system to enable conference calls with more than two mobile users without SIM support to communicate with each other simultaneously. The AI-based proposed solution will be self–governed, self-learned and will be intelligent enough to smartly switch between all callers connected via Bluetooth in a conference call. This proposed solution system will greatly increase the potential of using Bluetooth technology from a wider applicability perspective of conference calls, which is currently only possible over LTE mobiles.

Keywords: conference call, bluetooth, AI, frequency hopping, piconet, scatter net

Procedia PDF Downloads 60