Search results for: evolutionary genetic algorithm

Authors: Ibrahim A. Adeniran, Rui F. Zhu, Man S. Wong

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Owing to the insufficiency in the spatial representativeness and continuity of in situ temperature measurements from weather stations (WS), the use of temperature measurement from WS for large-range diurnal analysis in heterogenous landscapes has been limited. This has made the accurate estimation of land surface temperature (LST) from remotely sensed data more crucial. Moreover, the study of dynamic interaction between the atmosphere and the physical surface of the Earth could be enhanced at both annual and diurnal scales by using optimal LST data derived from satellite sensors. The tradeoff between the spatial and temporal resolution of LSTs from satellite’s thermal infrared sensors (TIRS) has, however, been a major challenge, especially when high spatiotemporal LST data are recommended. It is well-known from existing literature that polar satellites have the advantage of high spatial resolution, while geostationary satellites have a high temporal resolution. Hence, this study is aimed at designing a framework for the cross-comparison of LST data from polar and geostationary satellites in a heterogeneous landscape. This could help to understand the relationship between the LST estimates from the two satellites and, consequently, their integration in diurnal LST analysis. Landsat-8 satellite data will be used as the representative of the polar satellite due to the availability of its long-term series, while the Himawari-8 satellite will be used as the data source for the geostationary satellite because of its improved TIRS. For the study area, Hong Kong Special Administrative Region (HK SAR) will be selected; this is due to the heterogeneity in the landscape of the region. LST data will be retrieved from both satellites using the Split window algorithm (SWA), and the resulting data will be validated by comparing satellite-derived LST data with temperature data from automatic WS in HK SAR. The LST data from the satellite data will then be separated based on the land use classification in HK SAR using the Global Land Cover by National Mapping Organization version3 (GLCNMO 2013) data. The relationship between LST data from Landsat-8 and Himawari-8 will then be investigated based on the land-use class and over different seasons of the year in order to account for seasonal variation in their relationship. The resulting relationship will be spatially and statistically analyzed and graphically visualized for detailed interpretation. Findings from this study will reveal the relationship between the two satellite data based on the land use classification within the study area and the seasons of the year. While the information provided by this study will help in the optimal combination of LST data from Polar (Landsat-8) and geostationary (Himawari-8) satellites, it will also serve as a roadmap in the annual and diurnal urban heat (UHI) analysis in Hong Kong SAR.

Keywords: automatic weather station, Himawari-8, Landsat-8, land surface temperature, land use classification, split window algorithm, urban heat island

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Authors: Dipanshu Sur, Ratnabali Chakravorty

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Background: Striae result from rapid expansion of the underlying tissue, e.g. during puberty, pregnancy or rapid weight gain. Prior data indicate that the incidence of stretch marks in Indian women is 77%.The hormonal and genetic factors are associated with their appearance. Recently that has been found skin extensibility, elasticity and rupture were strongly influenced by the water content of dermis and epidermis cells. Objective: The objectives were to assess the effects of topical treatments applied during pregnancy on the later development of stretch marks. Materials and methods: An open, prospective, randomized study was done on 120 pregnant women in whom skin elasticity and hydration as well as striae presence or apparition were measured at baseline and periodically until delivery. Patients were randomly assigned to application in wet skin cream, or in dry skin conditions. Results: The average basal hydration was 42 ±13 IU and the final was 46 ± 6 IU (P = 0.0325; 95% CI: -7.66 to -0.34), which difference was statistically significant. By measuring the moisture in the control region (forearm) a basal reading of 40 ± 9 IU and end of study of 38 ± 6; (p = 0.1547; 95% CI: -0.77 to 4.77) and this difference was considered to be not statistically significant. It was observed that at the end of the study, 55% women without ridges; mild ridges 5%; 36% moderate, and 4%, severe ridges. The proportion of women without grooves was 54% when the cream was applied studied wet skin and 45% when the cream was applied on dry skin. Conclusion: It was shown that cream under study increased hydration and elasticity of abdominal skin consequently in all subjects. This effect is more significant (54%) when the cream is applied to damp skin.

Keywords: striae gravidarum, skin moisturizer, skin hydration, skin elasticity

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Authors: Begum Koru, Isik Aybay, Demet Celik Ulusoy

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The discipline of law is quite complex and has its own terminology. Apart from written legal rules, there is also living law, which refers to legal practice. Basic legal rules aim at the happiness of individuals in social life and have different characteristics in different branches such as public or private law. On the other hand, law is a national phenomenon. The law of one nation and the legal system applied on the territory of another nation may be completely different. People who are experts in a particular field of law in one country may have insufficient expertise in the law of another country. Today, in addition to the local nature of law, international and even supranational law rules are applied in order to protect basic human values and ensure the protection of human rights around the world. Systems that offer algorithmic solutions to legal problems using artificial intelligence (AI) tools will perhaps serve to produce very meaningful results in terms of human rights. However, algorithms to be used should not be developed by only computer experts, but also need the contribution of people who are familiar with law, values, judicial decisions, and even the social and political culture of the society to which it will provide solutions. Otherwise, even if the algorithm works perfectly, it may not be compatible with the values of the society in which it is applied. The latest developments involving the use of AI techniques in legal systems indicate that artificial law will emerge as a new field in the discipline of law. More AI systems are already being applied in the field of law, with examples such as predicting judicial decisions, text summarization, decision support systems, and classification of documents. Algorithms for legal systems employing AI tools, especially in the field of prediction of judicial decisions and decision support systems, have the capacity to create automatic decisions instead of judges. When the judge is removed from this equation, artificial intelligence-made law created by an intelligent algorithm on its own emerges, whether the domain is national or international law. In this work, the aim is to make a general analysis of this new topic. Such an analysis needs both a literature survey and a perspective from computer experts' and lawyers' point of view. In some societies, the use of prediction or decision support systems may be useful to integrate international human rights safeguards. In this case, artificial law can serve to produce more comprehensive and human rights-protective results than written or living law. In non-democratic countries, it may even be thought that direct decisions and artificial intelligence-made law would be more protective instead of a decision "support" system. Since the values of law are directed towards "human happiness or well-being", it requires that the AI algorithms should always be capable of serving this purpose and based on the rule of law, the principle of justice and equality, and the protection of human rights.

Keywords: AI and law, artificial law, protection of human rights, AI tools for legal systems

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Authors: Farhad Nouparast

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For more production we need more capital formation. Capital formation in each country should be based on comparative advantages in different economic sectors due to the different production possibility curves. In regional planning, recognizing the relative advantages and consequently investing in more production requires identifying areas with the necessary capabilities and location of each region compared to other regions. In this article, ranking of Iran's provinces is done according to the specific and given variables as the best investment position in agricultural activity. So we can provide the necessary background for investment analysis in different regions of the country to formulate national and regional planning and execute investment projects. It is used factor analysis technique and numerical taxonomy analysis to do this in thisarticle. At first, the provinces are homogenized and graded according to the variables using cross-sectional data obtained from the agricultural census and population and housing census of Iran as data matrix. The results show that which provinces have the most potential for capital formation in agronomy sub-sector. Taxonomy classifies organisms based on similar genetic traits in biology and botany. Numerical taxonomy using quantitative methods controls large amounts of information and get the number of samples and categories and take them based on inherent characteristics and differences indirectly accommodates. Numerical taxonomy is related to multivariate statistics.

Keywords: Capital Formation, Factor Analysis, Multivariate statistics, Numerical Taxonomy Analysis, Production, Ranking, Spatial Planning

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Authors: Andrew Lock, Alastair Allen

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Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance of investigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: biometrics, iris recognition, reversible watermarking, vision engineering

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Authors: Ahmed O. Apampa, Yinusa A. Jimoh

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The potential economic viability and environmental benefits of using a biomass waste, such as corn cob ash (CCA) as pozzolan in stabilizing soils for road pavement construction in a sub-tropical region was investigated. Corn cob was obtained from Maya in South West Nigeria and processed to ash of characteristics similar to Class C Fly Ash pozzolan as specified in ASTM C618-12. This was then blended with ordinary Portland cement in the CCA:OPC ratios of 1:1, 1:2 and 2:1. Each of these blends was then mixed with lateritic soil of ASHTO classification A-2-6(3) in varying percentages from 0 – 7.5% at 1.5% intervals. The soil-CCA-Cement mixtures were thereafter tested for geotechnical index properties including the BS Proctor Compaction, California Bearing Ratio (CBR) and the Unconfined Compression Strength Test. The tests were repeated for soil-cement mix without any CCA blending. The cost of the binder inputs and optimal blends of CCA:OPC in the stabilized soil were thereafter analyzed by developing algorithms that relate the experimental data on strength parameters (Unconfined Compression Strength, UCS and California Bearing Ratio, CBR) with the bivariate independent variables CCA and OPC content, using Matlab R2011b. An optimization problem was then set up minimizing the cost of chemical stabilization of laterite with CCA and OPC, subject to the constraints of minimum strength specifications. The Evolutionary Engine as well as the Generalized Reduced Gradient option of the Solver of MS Excel 2010 were used separately on the cells to obtain the optimal blend of CCA:OPC. The optimal blend attaining the required strength of 1800 kN/m2 was determined for the 1:2 CCA:OPC as 5.4% mix (OPC content 3.6%) compared with 4.2% for the OPC only option; and as 6.2% mix for the 1:1 blend (OPC content 3%). The 2:1 blend did not attain the required strength, though over a 100% gain in UCS value was obtained over the control sample with 0% binder. Upon the fact that 0.97 tonne of CO2 is released for every tonne of cement used (OEE, 2001), the reduced OPC requirement to attain the same result indicates the possibility of reducing the net CO2 contribution of the construction industry to the environment ranging from 14 – 28.5% if CCA:OPC blends are widely used in soil stabilization, going by the results of this study. The paper concludes by recommending that Nigeria and other developing countries in the sub-tropics with abundant stock of biomass waste should look in the direction of intensifying the use of biomass waste as fuel and the derived ash for the production of pozzolans for road-works, thereby reducing overall green house gas emissions and in compliance with the objectives of the United Nations Framework on Climate Change.

Keywords: corn cob ash, biomass waste, lateritic soil, unconfined compression strength, CO2 emission

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Authors: Ahmed Emad Ahmed

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This paper aims to address the concept of human resources information systems (HRIS) and how to link it to new technologies such as artificial intelligence (AI) to be implemented in two human resources processes. A literature view has been collected to cover the main points related to HRIS, AI, and BC. A study case has been presented by generating a random HRIS to apply some AI operations to it. Then, an algorithm was applied to the database to complete some human resources processes, including training and performance appraisal, using a pre-trained AI model. After that, outputs and results have been presented and discussed briefly. Finally, a conclusion has been introduced to show the ability of new technologies such as AI and ML to be applied to the human resources management processes.

Keywords: human resources new technologies, HR artificial intelligence, HRIS AI models, construction AI HRIS

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Authors: Fathi Kallel, Saida Khachira, Mohamed Ben Slima, Ahmed Ben Hamida

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Speckle noise is a main characteristic of cardiac ultrasound images, it corresponding to grainy appearance that degrades the image quality. For this reason, the ultrasound images are difficult to use automatically in clinical use, then treatments are required for this type of images. Then a filtering procedure of these images is necessary to eliminate the speckle noise and to improve the quality of ultrasound images which will be then segmented to extract the necessary forms that exist. In this paper, we present the importance of the pre-treatment step for segmentation. This work is applied to cardiac ultrasound images. In a first step, a comparative study of speckle filtering method will be presented and then we use a segmentation algorithm to locate and extract cardiac structures.

Keywords: medical image processing, ultrasound images, Speckle noise, image enhancement, speckle filtering, segmentation, snakes

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Authors: Medina Muñoz Lina Rocio

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The purpose of this paper is to examine the debates related to the harmonization of intellectual property rights on plant material, the corporate governance of the seed market in Colombia and the political economy of seeds defended by indigenous communities. In recent years, the commodification of seeds through genetic engineering and political intellectual property, codified as a result of the implementation of the Free Trade Agreement with the United States, has come into conflict with the traditional production of seeds carried out by small farmers and indigenous populations. Agricultural and food practices. In order to understand the ontological dimension of conflicts over seeds, it is necessary to analyze the conceptions that indigenous communities have about good, which they consider a common element of their social organization and define them as sentient beings. Therefore, through a multiple approach, in which the intellectual property policy, the ecological aspects of seed production and the political ontology of indigenous communities are interwoven, I intend to present the discussions held by the actors involved and present the strategies of small producers to protect their interests. It demonstrates that communities have begun to organize social movements to protect such interests and have questioned the philosophy of GM corporate agriculture as a pro-life movement. Finally, it is argued that the conservation of 'traditional' seeds of the communities is an effective strategy to support their struggles for territory, identity, food sovereignty and self-determination.

Keywords: intellectual property rights, intellectual property, traditional knowledge, food safety

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Authors: Enock E. Goler, Emmanuel H. Kwon-Ndung, Gbenga F. Akomolafe, Terna T. Paul, Markus Musa, Joshua I. Waya, James H. Okogbaa

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An ethno-medicinal survey of plants used in treating various diseases and ailments was carried out in the study area of Nasarawa State, North Central Nigeria to obtain information on their uses and potentials. The ethno-medicinal survey was administered through structured questionnaires among local inhabitants from areas with high plant density and diversity within the various Local Government Areas of the State. A total of 84 (Eighty four) plant species belonging to 45 (Forty five) families were found to be useful in treatment of various ailments such as diabetes, measles, fever, asthma, jaundice, pneumonia, sexually transmitted diseases (STDs), aches, diarrhea, cough, arthritis, yellow fever, typhoid, erectile dysfunction and excessive bleeding. Different parts of the plant such as the roots, leaves and stems are used in preparing herbal remedies which could be from dry or freshly collected plants. The main methods of preparation are decoction or infusion, while in some cases the plant parts used are consumed directly. Residents in the study areas find the herbal remedy cheaper and more accessible and claimed that there are no side effects compared to orthodox medicine. This study has confirmed the need towards the conscious conservation of plant genetic resources in order to ensure sustained access to these ethno-medicinal plant materials.

Keywords: ethno-medicinal, Nasarawa, plants, survey

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Authors: Elabed Saud

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This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

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Authors: A. Djahbar, E. Bounadja, A. Zegaoui, H. Allouache

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In this paper, vector control of a series-connected two-machine drive system fed by a single inverter (CSI/VSI) is presented. The two stator windings of both machines are connected in series while the rotors may be connected to different loads, are called series-connected two-machine drive. Appropriate phase transposition is introduced while connecting the series stator winding to obtain decoupled control the two-machines. The dynamic decoupling of each machine from the group is obtained using the vector control algorithm. The independent control is demonstrated by analyzing the characteristics of torque and speed of each machine obtained via simulation under vector control scheme. The viability of the control techniques is proved using analytically and simulation approach.

Keywords: drives, inverter, multi-phase induction machine, vector control

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Authors: Diana A. Pazmino, Lynne vanHerwerden, Colin A. Simpfendorfer, Claudia Junge, Stephen C. Donnellan, Mauricio Hoyos-Padilla, Clinton A. J. Duffy, Charlie Huveneers, Bronwyn Gillanders, Paul A. Butcher, Gregory E. Maes

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With just a handful of documented cases of hybridisation in cartilaginous fishes, shark hybridisation remains poorly investigated. Small amounts of admixture have been detected between Galapagos (Carcharhinus galapagensis) and dusky (Carcharhinus obscurus) sharks previously, generating a hypothesis of ongoing hybridisation. We sampled a large number of individuals from areas where both species co-occur (contact zones) across the Pacific Ocean and used both mitochondrial and nuclear-encoded SNPs to examine genetic admixture and introgression between the two species. Using empirical, analytical approaches and simulations, we first developed a set of 1,873 highly informative and reliable diagnostic SNPs for these two species to evaluate the degree of admixture between them. Overall, results indicate a high discriminatory power of nuclear SNPs (FST=0.47, p < 0.05) between the two species, unlike mitochondrial DNA (ΦST = 0.00 p > 0.05), which failed to differentiate between these species. We identified four hybrid individuals (~1%) and detected bi-directional introgression between C. galapagensis and C. obscurus in the Gulf of California along the eastern Pacific coast of the Americas. We emphasize the importance of including a combination of mtDNA and diagnostic nuclear markers to properly assess species identification, detect patterns of hybridisation, and better inform management and conservation of these sharks, especially given the morphological similarities within the genus Carcharhinus.

Keywords: elasmobranchs, single nucleotide polymorphisms, hybridisation, introgression, misidentification

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Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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Authors: Alexander P. Vazhenin, Mikhail M. Lavrentiev, Alexey A. Romanenko, Pavel V. Tatarintsev

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One of the problems obstructing effective tsunami modelling is the lack of information about initial wave shape at source. The existing methods; geological, sea radars, satellite images, contain an important part of uncertainty. Therefore, direct measurement of tsunami waves obtained at the deep water bottom peruse recorders is also used. In this paper we propose a new method to reconstruct the initial sea surface displacement at tsunami source by the measured signal (marigram) approximation with the help of linear combination of synthetic marigrams from the selected set of unit sources, calculated in advance. This method has demonstrated good precision and very high performance. The mathematical model and results of numerical tests are here described.

Keywords: numerical tests, orthogonal decomposition, Tsunami Initial Sea Surface Displacement

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Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

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Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

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Authors: Hao-Jun Hong, Jung-Tang Huang

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The world is gradually becoming an aging society, and with the lack of laboring forces, this phenomenon is affecting the nation’s economy growth. Although nursing centers are booming in recent years, the lack of medical resources are yet to be resolved, thus creating an innovative wearable medical device could be a vital solution. This research is focused on the design and development of a wearable device which obtains a more precise heart failure measurement than products on the market. The method used by the device is based on the sensor fusion and big data algorithm. From the test result, the modified structure of wearable device can significantly decrease the MA (Motion Artifact) and provide users a more cozy and accurate physical monitor experience.

Keywords: big data, heart failure, motion artifact, sensor fusion, wearable medical device

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Authors: M. O. Oke, T. S. Workneh

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Drying behaviour of blanched sweet potato in a cabinet dryer using different five air temperatures (40-80oC) and ten sweet potato varieties sliced to 5 mm thickness were investigated. The drying data were fitted to eight models. The Modified Henderson and Pabis model gave the best fit to the experimental moisture ratio data obtained during the drying of all the varieties while Newton (Lewis) and Wang and Singh models gave the least fit. The values of Deff obtained for Bophelo variety (1.27 x 10-9 to 1.77 x 10-9 m2/s) was the least while that of S191 (1.93 x 10-9 to 2.47 x 10-9 m2/s) was the highest which indicates that moisture diffusivity in sweet potato is affected by the genetic factor. Activation energy values ranged from 0.27-6.54 kJ/mol. The lower activation energy indicates that drying of sweet potato slices requires less energy and is hence a cost and energy saving method. The drying behavior of blanched sweet potato was investigated in a cabinet dryer. Drying time decreased considerably with increase in hot air temperature. Out of the eight models fitted, the Modified Henderson and Pabis model gave the best fit to the experimental moisture ratio data on all the varieties while Newton, Wang and Singh models gave the least. The lower activation energy (0.27-6.54 kJ/mol) obtained indicates that drying of sweet potato slices requires less energy and is hence a cost and energy saving method.

Keywords: sweet potato slice, drying models, moisture ratio, moisture diffusivity, activation energy

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Authors: Vahid Changizi, Aram Rostami, Akbar Mosavi

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Purpose of study: Critical macromolecules of cells such as DNA are in exposure to damage of free radicals that induced from interaction of ionizing radiation with biological systems. Selenium and vitamin-E are natural compound that has been shown to be a direct free radical scavenger. The aim of this study was to investigate the in vivo/in vitro radioprotective effect of selenium and vitamin-E separately and synergistically against genotoxicity induced by 6MV x-rays irradiation in cultured blood lymphocytes from 15 human volunteers. Methods: Fifteen volunteers were divided in three groups include A, B and C. These groups were given slenium(800 IU), vitamin-E(100 mg) and selenium(400 IU) + vitamin-E(50 mg), respectively. Peripheral blood samples were collected from each group before(0 hr) and 1, 2 and 3 hr after selenium and vitamin-E administration (separately and synergistically). Then the blood samples were irradiated to 200 cGy of 6 Mv x-rays. After that, lymphocyte samples were cultured with mitogenic stimulation to determine the chromosomal aberrations wih micronucleus assay in cytokinesis-blocked binucleated cells. Results: The lymphocytes in the blood samples collected at 1 hr after ingestion selenium and vitamin-E, exposed in vitro to x-rays exhibited a significant decrease in the incidence of micronuclei, compared with control group at 0 hr. The maximum protection and decrease in frequency of micronuclei(50%) was observed at 1 hr after administration of selenium and vitamin-E synergistically. Conclusion: The data suggest that ingestion of selenium and vitamin-E as a radioprotector substances before exposures may reduce genetic damage caused by x-rays irradiation.

Keywords: x-rays, selenium, vitamin-e, lymphocyte, micronuclei

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Authors: Hamsini Pulugurtha, P. V. S. L. Jagadamba

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Programmed Speech to Text and Text Summarization Using Graph-based Algorithms can be utilized in gatherings to get the short depiction of the gathering for future reference. This gives signature check utilizing Siamese neural organization to confirm the personality of the client and convert the client gave sound record which is in English into English text utilizing the discourse acknowledgment bundle given in python. At times just the outline of the gathering is required, the answer for this text rundown. Thus, the record is then summed up utilizing the regular language preparing approaches, for example, solo extractive text outline calculations

Keywords: Siamese neural network, English speech, English text, natural language processing, unsupervised extractive text summarization

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Authors: Yonas Shuke Kitawa

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Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

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Authors: Tian Xia, Yuan Yan Tang

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In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection.

Keywords: small target detection, local contrast, human vision system, Laplacian of Gaussian

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Authors: S. Padmapriya, V. Lakshmi Prabha

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In this paper, an efficient reconfigurable fixed-point Least Mean Square Adaptive FIR filter is proposed. The proposed architecture has two methods of operation: one is area efficient design and the other is optimized power. Pipelining of the adder blocks and partial product generator are used to achieve low area and reversible logic is used to obtain low power design. Depending upon the input samples and filter coefficients, one of the techniques is chosen. Least-Mean-Square adaptation is performed to update the weights. The architecture is coded using Verilog and synthesized in cadence encounter 0.18μm technology. The synthesized results show that the area reduction ratio of the proposed when compared with conventional technique is about 1.2%.

Keywords: adaptive filter, carry select adder, least mean square algorithm, reversible logic

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Authors: Bo Yang, Christopher Monterola

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Urban intersection control without the use of the traffic light has the potential to vastly improve the efficiency of the urban traffic flow. For most proposals in the literature, such lightless intersection control depends on the mass market commercialization of highly intelligent autonomous vehicles (AV), which limits the prospects of near future implementation. We present an efficient lightless intersection traffic control scheme that only requires Level 1 AV as defined by NHTSA. The technological barriers of such lightless intersection control are thus very low. Our algorithm can also accommodate a mixture of AVs and conventional vehicles. We also carry out large scale numerical analysis to illustrate the feasibility, safety and robustness, comfort level, and control efficiency of our intersection control scheme.

Keywords: intersection control, autonomous vehicles, traffic modelling, intelligent transport system

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Authors: S. Cheng, C. Catallo

Abstract:

Introduction: Canada's healthcare and social services systems are failing high risk, vulnerable older adults. Care for vulnerable older Canadians (65 and older) is not optimal in Canada. It does not address the care needs of vulnerable, high risk adults using a holistic approach. Given the growing aging population, and the care needs for seniors with complex conditions is one of the highest in Canada's health care system, there is a sense of urgency to optimize care. Integration of health and social services is an emerging trend in Canada when compared to European countries. There is no common and universal understanding of healthcare and social services integration within the country. Consequently, a clear understanding and definition of integrated health and social services are absent in Canada. Objectives: A study was undertaken to develop a case definition for integrated health and social care initiatives that serve older adults, which was then tested against three Canadian integrated initiatives. Methodology: A limited literature review was undertaken to identify common characteristics of integrated health and social care initiatives that serve older adults, and comprised both scientific and grey literature, in order to develop a case definition. Three Canadian integrated initiatives that are located in the province of Ontario, were identified using an online search and a screening process. They were surveyed to determine if the literature-based integration definition applied to them. Results: The literature showed that there were 24 common healthcare and social services integration characteristics that could be categorized into ten themes: 1) patient-care approach; 2) program goals; 3) measurement; 4) service and care quality; 5) accountability and responsibility; 6) information sharing; 7) Decision-making and problem-solving; 8) culture; 9) leadership; and 10) staff and professional interaction. The three initiatives showed agreement on all the integration characteristics except for those characteristics associated with healthcare and social care professional interaction, collaborative leadership and shared culture. This disagreement may be due to several reasons, including the existing governance divide between the healthcare and social services sectors within the province of Ontario that has created a ripple effect in how professions in the two different sectors interact. In addition, the three initiatives may be at maturing levels of integration, which may explain disagreement on the characteristics associated with leadership and culture. Conclusions: The development of a case definition for healthcare and social services integration that incorporates common integration characteristics can act as a useful instrument in identifying integrated healthcare and social services, particularly given the emerging and evolutionary state of this phenomenon within Canada.

Keywords: Canada, case definition, healthcare and social services integration, integration, seniors health, services delivery

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Authors: Jose D. Herrera, Mario A. Rios

Abstract:

This paper deals with the coordinated tuning of the Power System Stabilizer (PSS) controller and Power Oscillation Damping (POD) Controller of Flexible AC Transmission System (FACTS) in a multi-machine power systems. The coordinated tuning is based on the critical eigenvalues of the power system and a model reduction technique where the Hankel Singular Value method is applied. Through the linearized system model and the parameter-constrained nonlinear optimization algorithm, it can compute the parameters of both controllers. Moreover, the parameters are optimized simultaneously obtaining the gains of both controllers. Then, the nonlinear simulation to observe the time response of the controller is performed.

Keywords: electromechanical oscillations, power system stabilizers, power oscillation damping, hankel singular values

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Authors: Arab M., Ait Abdallah M., Zeraoulia N., Boumaza H., Aoutia M., Griene L., Ait Abdelkader B.,

Abstract:

breast and ovarian cancer are respectively the first and fourth leading causes of cancer among women in Algeria. A family story of cancer in the most important risk factor, and in most cases of families with breast and /or ovarian cancer, the pattern of cancer family can be attributed to mutation in BRCA1/2genes. objectibes: the aim of our study in to investigate the spectrum of BRCA1/2 germiline mutation in familial breast and /or ovarian cancer and to determine the prevalence and the nature of BRCA1/2mutation in Algeria methods: we deremined the prevalence of BRCA1/2 mutation within a cohort of 161 probands selected according the eisinger score double stranded sanger sequencing of all coding exons of BRCA1/2including flanking intronic region were performed results: we identified a total of 23 distinct deleterious mutations (class5) 12 differents mutations in BRCA1(52%) and 11 in BRCA2(48%). 78% (18/23) were protein truncating and 22%(5/23) missens mutations.3 novel deleterious mutations have been identified, which have not been described in public mutation database. one new mutation were found in two unrelated patients. the overall mutation detection rate in our study is 28,5%(46/161).more over, an UVS c7783 located in BRCA2 is found in two unrelated probands and segregate in the 02 families/ conclusion: our results sugget of large spectrum of BRCA1/2 mutation in Algerian breast/ovarian cancer family. The nature and prevalence of BRCA1/2mutation in algerian families are ongoing in a larger study, 80 probands are to day under investigation. This study which may therefore identify the genetic particularity of Algerian breast /ovarian cancer.

Keywords: BRCA1/2 mutations, hereditary breast cancer, algerian women, prvalence

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Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

Abstract:

Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

Abstract:

In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Akeem Akinboro, Bala Alhaj Kegun

Abstract:

Haemoglobinopathy is a genetic disorder that has the potentiality to cause death of individuals in whom both the alpha (α) and beta (β) globin chains of the haemoglobin molecule are defective due to mutations in their genes. The haemoglobin genotype variants among some residents of Niger state, Nigeria, were determined using the secondary data available at Bida, Minna and Kotangora general hospitals of the state. A total of 1,639 data, representing 434, 655 and 550, collected from the outside patients who visited the medical laboratory units of the three general hospitals, respectively, over five years period (2015-2020) were analyzed into gene frequency, sex and age to determine their haemoglobin genotypes status. More males (51.6 – 58.7%) than females (41.3 – 48.4%) visited the three hospitals during the period covered and most of the patients were between 11 - 20 years old. The frequency of HbA allele in the human population was 0.72, 0.65, 0.68 for Bida, Minna and Kotangora, respectively, while it was 0.25, 0.29 and 0.28 for HbS allele. The HbC allele was prevalent at 0.03, 0.06 and 0.05 among the human population in Bida, Minna and Kotangora cities of Niger state. In overall, the prevalence of HbA, HbS and HbC alleles in Niger state of Nigeria was 0.68, 0.28 and 0.05. Minna being the capital city of Niger state and the most populous among the three cities in the state seems to have influx of more people who are carriers of abnormal haemoglobin genotypes which has resulted to higher frequency of HbS and HbC than those of the other two cities in this study. These results show that the pattern of haemoglobin genotypes frequency of Kontagora could be a prediction for the whole of Niger state. It is therefore necessary and important to take screening of blood for haemoglobin genotype serious among intending couples to prevent and reduce the possibility of having increase in the number of people with abnormal haemoglobin genotypes in the state.

Keywords: haemoglobin, genotype, niger state, gene frequency, general hospitals

Procedia PDF Downloads 98