Search results for: bayesian parameter identification

Authors: El Miloudi Djelloul

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Based on analysis on applications by perception control technology in computer network security status and security protection measures, from the angles of network physical environment and network software system environmental security, this paper provides network security system perception control solution using Internet of Things (IOT), telecom and other perception technologies. Security Perception Control System is in the computer network environment, utilizing Radio Frequency Identification (RFID) of IOT and telecom integration technology to carry out integration design for systems. In the network physical security environment, RFID temperature, humidity, gas and perception technologies are used to do surveillance on environmental data, dynamic perception technology is used for network system security environment, user-defined security parameters, security log are used for quick data analysis, extends control on I/O interface, by development of API and AT command, Computer Network Security Perception Control based on Internet and GSM/GPRS is achieved, which enables users to carry out interactive perception and control for network security environment by WEB, E-MAIL as well as PDA, mobile phone short message and Internet. In the system testing, through middle ware server, security information data perception in real time with deviation of 3-5% was achieved; it proves the feasibility of Computer Network Security Perception Control System.

Keywords: computer network, perception control system security strategy, Radio Frequency Identification (RFID)

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Authors: Rudi Ryacudu, Edi Artono, Gema Wahyudi Purnama

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Oil and gas consumption in Indonesia is currently on the rise due to its nation economic improvement. Unfortunately, Indonesia’s domestic oil production cannot meet it’s own consumption and Indonesia has lost its status as Oil and Gas exporter. Even worse, our conventional oil and gas reserve is declining. Unwilling to give up, the government of Indonesia has taken measures to invite investors to invest in domestic oil and gas exploration to find new potential reserve and ultimately increase production. Yet, it has not bear any fruit. Indonesia has taken steps now to explore new unconventional oil and gas play including Shale Gas, Shale Oil and Tight Sands to increase domestic production. These new plays require definite parameters to differentiate each concept. The purpose of this paper is to provide ways in defining unconventional hydrocarbon reservoir parameters in Shale Gas, Shale Oil and Tight Sands. The parameters would serve as an initial baseline for users to perform analysis of unconventional hydrocarbon plays. Some of the on going concerns or question to be answered in regards to unconventional hydrocarbon plays includes: 1. The TOC number, 2. Has it been well “cooked” and become a hydrocarbon, 3. What are the permeability and the porosity values, 4. Does it need a stimulation, 5. Does it has pores, and 6. Does it have sufficient thickness. In contrast with the common oil and gas conventional play, Shale Play assumes that hydrocarbon is retained and trapped in area with very low permeability. In most places in Indonesia, hydrocarbon migrates from source rock to reservoir. From this case, we could derive a theory that Kitchen and Source Rock are located right below the reservoir. It is the starting point for user or engineer to construct basin definition in relation with the tectonic play and depositional environment. Shale Play concept requires definition of characteristic, description and reservoir identification to discover reservoir that is technically and economically possible to develop. These are the steps users and engineers has to do to perform Shale Play: a. Calculate TOC and perform mineralogy analysis using water saturation and porosity value. b. Reconstruct basin that accumulate hydrocarbon c. Brittlenes Index calculated form petrophysical and distributed based on seismic multi attributes d. Integrated natural fracture analysis e. Best location to place a well.

Keywords: unconventional hydrocarbon, shale gas, shale oil tight sand reservoir parameters, shale play

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Authors: Jae Ni Jang, SoYoon Park, Sukhee Park, Yumin Song, Jae Won Kim, Keum Nae Kang, Young Uk Kim

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Objectives: Patellofemoral pain syndrome (PFPS) is a common clinical condition characterized by anterior knee pain. Here, we investigated the quadriceps tendon cross-sectional area (QTCSA) as a novel predictor for the diagnosis of PFPS. By examining the association between the QTCSA and PFPS, we aimed to provide a more valuable diagnostic parameter and more equivocal assessment of the diagnostic potential of PFPS by comparing the QTCSA with the quadriceps tendon thickness (QTT), a traditional measure of quadriceps tendon hypertrophy. Patients and Methods: This retrospective study included 30 patients with PFPS and 30 healthy participants who underwent knee magnetic resonance imaging. T1-weighted turbo spin echo transverse magnetic resonance images were obtained. The QTCSA was measured on the axial-angled phases of the images by drawing outlines, and the QTT was measured at the most hypertrophied quadriceps tendon. Results: The average QTT and QTCSA for patients with PFPS (6.33±0.80 mm and 155.77±36.60 mm², respectively) were significantly greater than those for healthy participants (5.77±0.36 mm and 111.90±24.10 mm2, respectively; both P<0.001). We used a receiver operating characteristic curve to confirm the sensitivities and specificities for both the QTT and QTCSA as predictors of PFPS. The optimal diagnostic cutoff value for QTT was 5.98 mm, with a sensitivity of 66.7%, a specificity of 70.0%, and an area under the curve of 0.75 (0.62–0.88). The optimal diagnostic cutoff value for QTCSA was 121.04 mm², with a sensitivity of 73.3%, a specificity of 70.0%, and an area under the curve of 0.83 (0.74–0.93). Conclusion: The QTCSA was found to be a more reliable diagnostic indicator for PFPS than QTT.

Keywords: patellofemoral pain syndrome, quadriceps muscle, hypertrophy, magnetic resonance imaging

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Authors: Natapol Pumipuntu

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Staphylococcus argenteus is the emerging species of S. aureus complex. It was generally misidentified as S. aureus by standard techniques and their features. S. argenteus is possibly emerging in both humans and animals, as well as increasing worldwide distribution. The objective of this study was to differentiate and identify S. argenteus from S. aureus, which has been collected and isolated from milk samples of subclinical bovine mastitis cases in Maha Sarakham province, Northeastern of Thailand. Twenty-one isolates of S. aureus, which confirmed by conventional methods and immune-agglutination method were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and multilocus sequence typing (MLST). The result from MALDI-TOF MS and MLST showed 6 from 42 isolates were confirmed as S. argenteus, and 36 isolates were S. aureus, respectively. This study indicated that the identification and classification method by using MALDI-TOF MS and MLST could accurately differentiate the emerging species, S. argenteus, from S. aureus complex which usually misdiagnosed. In addition, the identification of S. argenteus seems to be very limited despite the fact that it may be the important causative pathogen in bovine mastitis as well as pathogenic bacteria in food and milk. Therefore, it is very necessary for both bovine medicine and veterinary public health to emphasize and recognize this bacterial pathogen as the emerging disease of Staphylococcal bacteria and need further study about S. argenteus infection.

Keywords: Staphylococcus argenteus, subclinical bovine mastitis, Staphylococcus aureus complex, mass spectrometry, MLST

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Authors: Yeliz Sarı Nayim, B. Niyami Nayim

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Biotopes such as forest areas rich in biodiversity, wetlands, hedgerows and woodlands play important ecological roles in agricultural landscapes. Of these semi-natural areas and features, hedgerows are the most common landscape elements. Their most significant features are that they serve as a barrier between the agricultural lands, serve as shelter, add aesthetical value to the landscape and contribute significantly to the wildlife and biodiversity. Hedgerows surrounding agricultural landscapes also provide an important habitat for pollinators which are important for agricultural production. This study looks into the identification of hedgerows in agricultural lands in the Mugada rural area within Bartın province, Turkey. From field data and-and satellite images, it is clear that in this area, especially around rural settlements, large forest areas have been cleared for settlement and agriculture. A network of hedgerows is also apparent, which might potentially play an important role in the otherwise open agricultural landscape. We found that these hedgerows serve as an ecological and biological corridor, linking forest ecosystems. Forest patches of different sizes and creating a habitat network across the landscape. Some examples of this will be presented. The overall conclusion from the study is that ecologically, biologically and aesthetically important hedge biotopes should be maintained in the long term in agricultural landscapes such as this. Some suggestions are given for how they could be managed sustainably into the future.

Keywords: agricultural biotopes, Hedgerows, landscape ecology, Turkey

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Authors: Fahad Abbasi

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Flow of electrically conducting nanofluids is of pivotal importance in countless industrial and medical appliances. Fluctuations in thermophysical properties of such fluids due to variations in temperature have not received due attention in the available literature. Present investigation aims to fill this void by analyzing the flow of copper-water nanofluid with temperature dependent viscosity past a Riga plate. Strong wall suction and viscous dissipation have also been taken into account. Numerical solutions for the resulting nonlinear system have been obtained. Results are presented in the graphical and tabular format in order to facilitate the physical analysis. An estimated expression for skin friction coefficient and Nusselt number are obtained by performing linear regression on numerical data for embedded parameters. Results indicate that the temperature dependent viscosity alters the velocity, as well as the temperature of the nanofluid and, is of considerable importance in the processes where high accuracy is desired. Addition of copper nanoparticles makes the momentum boundary layer thinner whereas viscosity parameter does not affect the boundary layer thickness. Moreover, the regression expressions indicate that magnitude of rate of change in effective skin friction coefficient and Nusselt number with respect to nanoparticles volume fraction is prominent when compared with the rate of change with variable viscosity parameter and modified Hartmann number.

Keywords: heat transfer, peristaltic flows, radially varying magnetic field, curved channel

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Authors: Haifeng Zhou, Tsungyang Liow, Xiaoguang Tu, Eujin Lim, Chao Li, Junfeng Song, Xianshu Luo, Ying Huang, Lianxi Jia, Lianwee Luo, Qing Fang, Mingbin Yu, Guoqiang Lo

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With the development of technology, countries gradually allocated more and more frequency spectrums for civilization and commercial usage, especially those high radio frequency bands indicating high information capacity. The field effect becomes more and more prominent in microwave components as frequency increases, which invalidates the transmission line theory and complicate the design of microwave components. Here a modeling approach based on numerical search algorithm is proposed to design various building blocks for microwave circuits to avoid complicated impedance matching and equivalent electrical circuit approximation. Concretely, a microwave component is discretized to a set of segments along the microwave propagation path. Each of the segment is initialized with random dimensions, which constructs a multiple-dimension parameter space. Then numerical searching algorithms (e.g. Pattern search algorithm) are used to find out the ideal geometrical parameters. The optimal parameter set is achieved by evaluating the fitness of S parameters after a number of iterations. We had adopted this approach in our current projects and designed many microwave components including sharp bends, T-branches, Y-branches, microstrip-to-stripline converters and etc. For example, a stripline 90° bend was designed in 2.54 mm x 2.54 mm space for dual-band operation (Ka band and Ku band) with < 0.18 dB insertion loss and < -55 dB reflection. We expect that this approach can enrich the tool kits for microwave designers.

Keywords: microwave component, microstrip and stripline, bend, power division, the numerical search algorithm.

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Authors: Mai M. Farid, Mona El-Shabrawy, Sameh R. Hussein, Ahmed Elkhateeb, El-Said S. Abdel-Hameed, Mona M. Marzouk

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Asphodelus aestivus Brot. Is a wild plant distributed in Egypt and is considered one of the five Asphodelus spp. from the family Asphodelaceae; it grows in dry grasslands and on rocky or sandy soil. The chemical components of A. aestivus flowers extract were analyzed using different chromatographic and spectral techniques and led to the isolation of two anthraquinones identified as emodin and emodin-O-glucoside. In addition to, five flavonoid compounds;kaempferol,Kaempferol-3-O-glucoside,Apigenin-6-C-glucoside-7-O-glucoside (Saponarine), luteolin 7-O-β-glucopyranoside, Isoorientin-O-malic acid which is a new compound in nature. The LC-ESI-MS/MS analysis of the flower extract of A. aestivus led to the identification of twenty- two compounds characterized by the presence of flavones, flavonols, and flavone C-glycosides. While GC/MS analysis led to the identification of 24 compounds comprising 98.32% of the oil, the major components of the oil were 9, 12, 15-Octadecatrieoic acid methyl ester 28.72%, and 9, 12-Octadecadieroic acid (Z, Z)-methyl ester 19.96%. In vitro cytotoxic activity of the aqueous methanol extract of A. aestivus flowers against HEPG2, HCT-116, MCF-7, and A549 culture was examined and showed moderate inhibition (62.3±1.1)% on HEPG2 cell line followed by (36.8±0.2)% inhibition on HCT-116 and a weak inhibition (5.7± 0.0.2) on MCF-7 cell line followed by (4.5± 0.4) % inhibition on A549 cell line and this is considered the first cytotoxic report of A. aestivus flowers.

Keywords: Anthraquinones, Asphodelus aestivus, Cytotoxic activity, Flavonoids, LC-ESI-MS/MS

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

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This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

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Authors: Katharina Fellnhofer

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The more information and knowledge that technology provides, the more important are profoundly human skills like intuition, the skill of using nonconscious information. As our world becomes more complex, shaken by crises, and characterized by uncertainty, time pressure, ambiguity, and rapidly changing conditions, intuition is increasingly recognized as a key human asset. However, due to methodological limitations of sample size or time frame or a lack of real-world or cross-cultural scope, precisely how to measure intuition when facing risks on a nonconscious level remains unclear. In light of the measurement challenge related to intuition’s nonconscious nature, a technique is introduced to measure intuition via hidden images as nonconscious additional information to trigger intuition. This technique has been tested in a within-subject fully online design with 62,721 real-world investment decisions made by 657 subjects in Europe and the United States. Bayesian models highlight the technique’s potential to measure skill at using nonconscious information for conscious decision making. Over the long term, solving the mysteries of intuition and mastering its use could be of immense value in personal and organizational decision-making contexts.

Keywords: cognition, intuition, investment decisions, methodology

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Authors: Babatunde James Falaye, Shi Hai Dong, Kayode John Oyewumi

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We study the effects of oblateness up to J4 of the primaries and power-law density profile (PDP) on the linear stability of libration location of an innitesimal mass within the framework of restricted three body problem (R3BP), by using a more realistic model in which a disc with PDP is rotating around the common center of the system mass with perturbed mean motion. The existence and stability of triangular equilibrium points have been explored. It has been shown that triangular equilibrium points are stable for 0 < μ < μc and unstable for μc ≤ μ ≤ 1/2, where c denotes the critical mass parameter. We find that, the oblateness up to J2 of the primaries and the radiation reduces the stability range while the oblateness up to J4 of the primaries increases the size of stability both in the context where PDP is considered and ignored. The PDP has an eect of about ≈0:01 reduction on the application of c to Earth-Moon and Jupiter-Moons systems. We find that the comprehensive effects of the perturbations have a stabilizing proclivity. However, the oblateness up to J2 of the primaries and the radiation of the primaries have tendency for instability, while coecients up to J4 of the primaries have stability predisposition. In the limiting case c = 0, and also by setting appropriate parameter(s) to zero, our results are in excellent agreement with the ones obtained previously. Libration points play a very important role in space mission and as a consequence, our results have a practical application in space dynamics and related areas. The model may be applied to study the navigation and station-keeping operations of spacecraft (innitesimal mass) around the Jupiter (more massive) -Callisto (less massive) system, where PDP accounts for the circumsolar ring of asteroidal dust, which has a cloud of dust permanently in its wake.

Keywords: libration points, oblateness, power-law density profile, restricted three-body problem

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Authors: Saci Abdelhakim Ferkous, Khedoudja Soudani, Smail Haddadi

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This paper presents the results of a laboratory experimental study that explores the skid resistance of asphalt concrete mixtures made of local low-performance aggregates by partially replacing sand with olive mill waste (OMW). OMW was mixed with aggregates using a dry process by replacing sand with contents of 5%, 7%, 10% and 15%. The mechanical performances of the mixtures were evaluated using the Marshall and Duriez tests. A modified accelerated polishing machine was used as polishing equipment, and a British pendulum tester (BPT) was used to test the skid resistance of the samples. Finally, texture parameter analysis was performed using scanning electron microscopy (SEM) and Mountains Map software to assess the effect of OMW on the friction coefficient evolution. Using a distinct road wheel for a modified version of an accelerated polishing machine, which is normally used to determine the polished stone value of aggregates, the results showed that the addition of OMW up to 10% conferred a better skid resistance in comparison to normal asphalt concrete. The presence of olive mill waste in the mixture until 15% guarantees a gain of 22%-29% in skid resistance after polishing compared with the reference mix. Indeed, from texture parameter analysis, it was observed that there was differential wear of the lightweight aggregates (OMW) compared to the other aggregates during the polishing process, which created a new surface microtexture that had new peaks and led to a good level of friction compared to the mixtures without OMW. In general, it was found that OMW is a promising modifier for asphalt mixtures with both engineering and economic merits.

Keywords: skid resistance, olive mill waste, polishing resistance, accelerated polishing machine, local materials, sustainable development.

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Authors: V. Baweja, K. K. Gupta, V. Dubey, C. Keshavam

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Antimicrobial activity of six indigenous plants such as Tulsi Ocimum sanctum, Neem Azadirachta indica, Aloe vera, Turmeric Curcuma longa, Lantana Lantana camara, and Clove Syzygium aromaticum was assessed against the gut microbiota of the dengue fever mosquito Aedes aegypti, keeping in view that the presence of midgut bacteria may affect the ability of the vector to transmit pathogens. Eleven different types of bacterial clones were isolated from the midgut of lab-reared fourth instar larvae of Aedes aegypti and were grown on LB agar medium at an optimum temperature of 25 ºC. Identification of these bacteria was done on the basis of their colony characteristic such as colony size, shape, opacity, elevation, consistency, and growth. Light microscopic studies of the gut microbiota revealed dominance of Gram-negative cocci over gram positive cocci and bacilli and Gram-negative bacilli. Identification of species was done by chemical characterization of the colonies. Crude extracts of all test plants were screened for their antimicrobial activities against gut microbiota by disc diffusion assay. The zone of exclusion seen after 24 hr of incubation in different assays revealed the most potent antibacterial activities in neem followed by clove and turmeric. Lantana and Aloe vera were least effective.

Keywords: plant extract, aedes, dengue, antimicrobial activity

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Takashi Yamaguchi, Ichio Asanuma, Jong G. Park, Kenneth J. Mackin, John Mittleman

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In this paper, vessel detection using the artificial neural network is proposed in order to automatically construct the vessel detection model from the satellite imagery of day/night band (DNB) in visible infrared in the products of Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (Suomi-NPP).The goal of our research is the establishment of vessel detection method using the satellite imagery of DNB in order to monitor the change of vessel activity over the wide region. The temporal vessel monitoring is very important to detect the events and understand the circumstances within the maritime environment. For the vessel locating and detection techniques, Automatic Identification System (AIS) and remote sensing using Synthetic aperture radar (SAR) imagery have been researched. However, each data has some lack of information due to uncertain operation or limitation of continuous observation. Therefore, the fusion of effective data and methods is important to monitor the maritime environment for the future. DNB is one of the effective data to detect the small vessels such as fishery ships that is difficult to observe in AIS. DNB is the satellite sensor data of VIIRS on Suomi-NPP. In contrast to SAR images, DNB images are moderate resolution and gave influence to the cloud but can observe the same regions in each day. DNB sensor can observe the lights produced from various artifact such as vehicles and buildings in the night and can detect the small vessels from the fishing light on the open water. However, the modeling of vessel detection using DNB is very difficult since complex atmosphere and lunar condition should be considered due to the strong influence of lunar reflection from cloud on DNB. Therefore, artificial neural network was applied to learn the vessel detection model. For the feature of vessel detection, Brightness Temperature at the 3.7 μm (BT3.7) was additionally used because BT3.7 can be used for the parameter of atmospheric conditions.

Keywords: artificial neural network, day/night band, remote sensing, Suomi National Polar-orbiting Partnership, vessel detection, Visible Infrared Imaging Radiometer Suite

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Authors: Maria C. Almario, Pam Remer, Jeff Resse, Kathy Moran, Linda Theander Adam

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The identification of victims of human trafficking and consequential service provision is characterized by a significant disconnection between the estimated prevalence of this issue and the number of cases identified. This poses as tremendous problem for human rights advocates as it prevents data collection, information sharing, allocation of resources and opportunities for international dialogues. The current paper introduces the Inclusive Human Trafficking Checklist (IHTC) as a measurement methodology with theoretical underpinnings derived from dialectic theory. The presence of human trafficking in a person’s life is conceptualized as a dynamic and dialectic interaction between vulnerability and exploitation. The current papers explores the operationalization of exploitation and vulnerability, evaluates the metric qualities of the instrument, evaluates whether there are differences in assessment based on the participant’s profession, level of knowledge, and training, and assesses if users of the instrument perceive it as useful. A total of 201 participants were asked to rate three vignettes predetermined by experts to qualify as a either human trafficking case or not. The participants were placed in three conditions: business as usual, utilization of the IHTC with and without training. The results revealed a statistically significant level of agreement between the expert’s diagnostic and the application of the IHTC with an improvement of 40% on identification when compared with the business as usual condition While there was an improvement in identification in the group with training, the difference was found to have a small effect size. Participants who utilized the IHTC showed an increased ability to identify elements of identity-based vulnerabilities as well as elements of fraud, which according to the results, are distinctive variables in cases of human trafficking. In terms of the perceived utility, the results revealed higher mean scores for the groups utilizing the IHTC when compared to the business as usual condition. These findings suggest that the IHTC improves appropriate identification of cases and that it is perceived as a useful instrument. The application of the IHTC as a multidisciplinary instrumentation that can be utilized in legal and human services settings is discussed as a pivotal piece of helping victims restore their sense of dignity, and advocate for legal, physical and psychological reparations. It is noteworthy that this study was conducted with a sample in the United States and later re-tested in Colombia. The implications of the instrument for treatment conceptualization and intervention in human trafficking cases are discussed as opportunities for enhancement of victim well-being, restoration engagement and activism. With the idea that what is personal is also political, we believe that the careful observation and data collection in specific cases can inform new areas of human rights activism.

Keywords: exploitation, human trafficking, measurement, vulnerability, screening

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Authors: Ebissa Gadissa Kedir, C. S. P. Ojha, K. S. Hari Prasad

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In the present study, the depth-averaged velocity and boundary shear stress in non-prismatic compound channels with three different converging floodplain angles ranging from 1.43ᶱ to 7.59ᶱ have been studied. The analytical solutions were derived by considering acting forces on the channel beds and walls. In the present study, five key parameters, i.e., non-dimensional coefficient, secondary flow term, secondary flow coefficient, friction factor, and dimensionless eddy viscosity, were considered and discussed. An expression for non-dimensional coefficient and integration constants was derived based on the boundary conditions. The model was applied to different data sets of the present experiments and experiments from other sources, respectively, to examine and analyse the influence of floodplain converging angles on depth-averaged velocity and boundary shear stress distributions. The results show that the non-dimensional parameter plays important in portraying the variation of depth-averaged velocity and boundary shear stress distributions with different floodplain converging angles. Thus, the variation of the non-dimensional coefficient needs attention since it affects the secondary flow term and secondary flow coefficient in both the main channel and floodplains. The analysis shows that the depth-averaged velocities are sensitive to a shear stress-dependent model parameter non-dimensional coefficient, and the analytical solutions are well agreed with experimental data when five parameters are included. It is inferred that the developed model may facilitate the interest of others in complex flow modeling.

Keywords: depth-average velocity, converging floodplain angles, non-dimensional coefficient, non-prismatic compound channels

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Authors: W. Ling, Mohamed Saufi Bin Awang

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Introduction: Mycobacterium tuberculosis post a major health problem worldwide. Central nervous system (CNS) infection by mycobacterium tuberculosis is one of the most devastating complications of tuberculosis. Although with advancement in medical fields, we are yet to understand the pathophysiology of how mycobacterium tuberculosis was able to cross the blood-brain barrier (BBB) and infect the CNS. CNS TB may present with nonspecific clinical symptoms which can mimic other diseases/conditions; this is what makes the diagnosis relatively difficult and challenging. Public health has to be informed and educated about the spread of TB, and early identification of TB is important as it is a curable disease. Case Report: A young 21-year-old Malay gentleman was initially presented to us with symptoms of ear discharge, tinnitus, and right-sided headache for the past one year. Further history reveals that the symptoms have been mismanaged and neglected over the period of 1 year. Initial investigation reveals features of inflammation of the ear. Further imaging showed the feature of chronic inflammation of the otitis media and atypical right cerebral abscess, which has the same characteristic features and consistency. He further underwent a biopsy, and results reveal positive Mycobacterium tuberculosis of the otitis media. With the results and the available imaging, we were certain that this is likely a case of disseminated tuberculosis causing CNS TB. Conclusion: We aim to highlight the challenge and difficult face in our health care system and public health in early identification and treatment.

Keywords: central nervous system tuberculosis, intracranial tuberculosis, tuberculous encephalopathy, tuberculous meningitis

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Authors: Lintang Nur Fadlillah, Muh Aris Marfai, M. Widyastuti

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Delta is dynamics area which is influenced by marine and river. Increasing human population in coastal area and the need of life exert pressure in delta that provides various resources. Wulan Delta is one of active Delta in Central Java, Indonesia. It has been experienced multiple pressures because of natural factors and human factors. In order to provide scientific solution and to analyze the main driving force in river delta, we collected several evidences based on news, papers, and publications related to Wulan Delta. This paper presents a review and problems identification in Wulan Delta, based on hydrodynamic approach, land use, and human activities which influenced water quality in the delta. A comprehensive overview is needed to address best policies under local communities and government. The analysis based on driving forces which affect delta estuary and river mouth. Natural factor in particular hydrodynamic influenced by tides, waves, runoff, and sediment transport. However, hydrodynamic affecting mixing process in river estuaries. The main problem is human intervention in land which is land use exchange leads to several problems such us decreasing water quality. Almost 90% of delta has been transformed into fish pond by local communities. Yet, they have not apply any water management to treat waste water before flush it to the sea and estuary. To understand the environmental condition, we need to assess water quality of river delta. The assessment based on land use as non-point source pollution. In Wulan Delta there are no industries. The land use in Wulan Delta consist of fish pond, settlement, and agriculture. The samples must represent the land use, to estimate which land use are most influence in river delta pollution. The hydrodynamic condition such as high tides and runoff must be considered, because it will affect the mixing process and water quality as well. To determine the samples site, we need to involve local community, in order to give insight into them. Furthermore, based on this review and problem identification, recommendations and strategies for water management are formulated.

Keywords: delta, land use, water quality, management, hydrodynamics

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Authors: Chien-Kuo Chang, Yu-Hsiang Lin, Yi-Yun Tang, Min-Chiu Wu

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With the trend of technological advancement, the harm caused by power outages is substantial, mostly due to problems in the power grid. This highlights the necessity for further improvement in the reliability of the power system. In the power system, gas-insulated switches (GIS) and power cables play a crucial role. Long-term operation under high voltage can cause insulation materials in the equipment to crack, potentially leading to partial discharges. If these partial discharges (PD) can be analyzed, preventative maintenance and replacement of equipment can be carried out, there by improving the reliability of the power grid. This research will diagnose defects by identifying three different defects in GIS and three different defects in straight cable joints, for a total of six types of defects. The partial discharge data measured will be converted through phase analysis diagrams and pulse sequence analysis. Discharge features will be extracted using convolutional image processing, and three different deep learning models, CNN, ResNet18, and MobileNet, will be used for training and evaluation. Class Activation Mapping will be utilized to interpret the black-box problem of deep learning models, with each model achieving an accuracy rate of over 95%. Lastly, the overall model performance will be enhanced through an ensemble learning voting method.

Keywords: partial discharge, gas-insulated switches, straight cable joint, defect identification, deep learning, ensemble learning

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Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

Procedia PDF Downloads 146

Authors: Sudhanshu Sharma

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Lisinopril, 1-[N-{(s)-I-carboxy-3 phenyl propyl}-L-proline dehydrate is a lysine analog of enalaprilat, the active metabolite of enalapril. It is long-acting, non-sulhydryl angiotensin-converting enzyme (ACE) inhibitor that is used for the treatment of hypertension and congestive heart failure in daily dosage 10-80 mg. Pharmacological activity of lisinopril has been proved in various experimental and clinical studies. Owing to its importance and widespread use, efforts have been made towards the development of simple and reliable analytical methods. As per our literature survey, lisinopril in pharmaceutical formulations has been determined by various analytical methodologies like polaragraphy, potentiometry, and spectrophotometry, but most of these analytical methods are not too suitable for the Identification of lisinopril from clinical samples because of the interferences caused by the amino acids and amino groups containing metabolites present in biological samples. This report is an attempt in the direction of developing a simple and reliable method for on plate identification and quantification of lisinopril in pharmaceutical formulations as well as from human urine samples using silica gel H layers developed with a new mobile phase comprising of micellar solutions of N-cetyl-N, N, N-trimethylammonium bromide (CTAB). Micellar solutions have found numerous practical applications in many areas of separation science. Micellar liquid chromatography (MLC) has gained immense popularity and wider applicability due to operational simplicity, cost effectiveness, relatively non-toxicity and enhanced separation efficiency, low aggressiveness. Incorporation of aqueous micellar solutions as mobile phase was pioneered by Armstrong and Terrill as they accentuated the importance of TLC where simultaneous separation of ionic or non-ionic species in a variety of matrices is required. A peculiarity of the micellar mobile phases (MMPs) is that they have no macroscopic analogues, as a result the typical separations can be easily achieved by using MMPs than aqueous organic mobile phases. Previously MMPs were successfully employed in TLC based critical separations of aromatic hydrocarbons, nucleotides, vitamin K1 and K5, o-, m- and p- aminophenol, amino acids, separation of penicillins. The human urine analysis for identification of selected drugs and their metabolites has emerged as an important investigation tool in forensic drug analysis. Among all chromatographic methods available only thin layer chromatography (TLC) enables a simple fast and effective separation of the complex mixtures present in various biological samples and is recommended as an approved testing for forensic drug analysis by federal Law. TLC proved its applicability during successful separation of bio-active amines, carbohydrates, enzymes, porphyrins, and their precursors, alkaloid and drugs from urine samples.

Keywords: lisnopril, surfactant, chromatography, micellar solutions

Procedia PDF Downloads 367

Authors: M. Bonopera, N. Tullini, C. C. Chen, T. K. Lin, K. C. Chang

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This paper presents the extension of a static method for the axial load identifications in prismatic beam-columns with uncertain length and unknown boundary conditions belonging to generic space structures, such as columns of space frames or struts and ties of space trusses. The non-destructive method requires the knowledge of the beam-column flexural rigidity only. Flexural displacements are measured at five cross sections along the beam-column subjected to an additional vertical load at the mid-span. Unlike analogous dynamic methods, any set of experimental data may be used in the identification procedure. The method is verified by means of many numerical and experimental tests on beam-columns having unknown boundary conditions and different slenderness belonging to three different space prototypes in small-scale. Excellent estimates of the tensile and compressive forces are obtained for the elements with higher slenderness and when the greatest possible distance between sensors is adopted. Moreover, the application of larger values of the vertical load and very accurate displacement measurements are required. The method could be an efficacious technique in-situ, considering that safety inspections will become increasingly important in the near future, especially because of the improvement of the material properties that allowed designing space structures composed of beam-columns with higher slenderness.

Keywords: force identification, in-situ test, space structure, static test

Procedia PDF Downloads 245

Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

Procedia PDF Downloads 188

Authors: T. C. C. Soo, S. Bhassu

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Unlike the common presence of both innate and adaptive immunity in vertebrates, crustaceans, in particular, shrimps, have been discovered to possess only innate immunity. This further emphasizes the importance of innate immunity within shrimps in pathogenic resistance. Under the study of pathogenic immune challenge, different shrimp species actually exhibit varying degrees of immune resistance towards the same pathogen. Furthermore, even within the same shrimp species, different batches of challenged shrimps can have different strengths of immune defence. Several important pathways are activated within shrimps during pathogenic infection. One of them is JAK-STAT pathway that is activated during bacterial, viral and fungal infections by which STAT(Signal Transducer and Activator of Transcription) gene is the core element of the pathway. Based on theory of Central Dogma, the genomic information is transmitted in the order of DNA, RNA and protein. This study is focused in uncovering the important evolutionary patterns present within the DNA (non-coding region) and RNA (coding region). The three shrimp species involved are Macrobrachium rosenbergii, Penaeus monodon and Litopenaeus vannamei which all possess commercial significance. The shrimp species were challenged with a famous penaeid shrimp virus called white spot syndrome virus (WSSV) which can cause serious lethality. Tissue samples were collected during time intervals of 0h, 3h, 6h, 12h, 24h, 36h and 48h. The DNA and RNA samples were then extracted using conventional kits from the hepatopancreas tissue samples. PCR technique together with designed STAT gene conserved primers were utilized for identification of the STAT coding sequences using RNA-converted cDNA samples and subsequent characterization using various bioinformatics approaches including Ramachandran plot, ProtParam and SWISS-MODEL. The varying levels of immune STAT gene activation for the three shrimp species during WSSV infection were confirmed using qRT-PCR technique. For one sample, three biological replicates with three technical replicates each were used for qRT-PCR. On the other hand, DNA samples were important for uncovering the structural variations within the genomic region of STAT gene which would greatly assist in understanding the STAT protein functional variations. The partially-overlapping primers technique was used for the genomic region sequencing. The evolutionary inferences and event predictions were then conducted through the Bayesian Inference method using all the acquired coding and non-coding sequences. This was supplemented by the construction of conventional phylogenetic trees using Maximum likelihood method. The results showed that adaptive evolution caused STAT gene sequence mutations between different shrimp species which led to evolutionary divergence event. Subsequently, the divergent sites were correlated to the differing expressions of STAT gene. Ultimately, this study assists in knowing the shrimp species innate immune variability and selection of disease resistant shrimps for breeding purpose. The deeper understanding of STAT gene evolution from the perspective of both purifying and adaptive approaches not only can provide better immunological insight among shrimp species, but also can be used as a good reference for immunological studies in humans or other model organisms.

Keywords: gene evolution, JAK-STAT pathway, immunology, STAT gene

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Authors: Tianyi Wang, Hieyong Jeong, An Guo, Yuko Ohno

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Healthcare robot for assisting sit-to-stand (STS) performance had aroused numerous research interests. To author’s best knowledge, knowledge about how evaluating healthcare robot is still unknown. Robot should be labeled as fault if users feel demanding during STS when they are assisted by robot. In this research, we aim to propose a method to evaluate sit-to-stand assist robot through center of pressure (CoP), then classify different STS performance. Experiments were executed five times with ten healthy subjects under four conditions: two self-performed STSs with chair heights of 62 cm and 43 cm, and two robot-assisted STSs with chair heights of 43 cm and robot end-effect speed of 2 s and 5 s. CoP was measured using a Wii Balance Board (WBB). Bayesian classification was utilized to classify STS performance. The results showed that faults occurred when decreased the chair height and slowed robot assist speed. Proposed method for fault classification showed high probability of classifying fault classes form others. It was concluded that faults for STS assist robot could be detected by inspecting center of pressure and be classified through proposed classification algorithm.

Keywords: center of pressure, fault classification, healthcare robot, sit-to-stand movement

Procedia PDF Downloads 197

Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

Procedia PDF Downloads 403

Authors: Kahsay Tadesse Mawcha, Na Zhang, Xu Yiying, Chang Jiaying, Wenxiang Yang

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Fusarium crown rot (FCR) diseased wheat seedlings were collected from different wheat-growing counties in seven different regions (Baoding, Cangzhou, Handan, Hengshui, Langfang, Shijiazhuang, and Xingtai) in Hebei province, China from 2019 to 2020. One-hundred twenty-two Fusarium isolates were isolated from crown rot diseased wheat seedlings and identified morphologically, confirmation was undertaken molecularly, and species-specific PCR was utilized to verify the morphological identification of F. psuedograminearum, F. graminearum, F. asiaticum, and F. culmorum. The predominant Fusarium species associated with wheat crown rot in the Hebei province were F. psuedograminearum, F. graminearum, F. asiaticum, and F. culmorum with isolation frequency of 85.25%, 12.30%, 1.64%, and 0.81%, respectively. All the Fusarium strains isolated from the different wheat-growing fields were qualitatively tested for toxigenic chemotypes using toxin-specific primers and chemotaxonomically classified into DON, 3-ADON, 15-ADON, and NIV. Among F. psuedograminearum identified, 84.62% were classified as DON chemotypes, 6.73% as 15-ADON chemotypes, 3.84% as 3-ADON chemotypes, and 4.81% of them had NIV as detected by the toxin-specific PCR results. Most of the F. graminearum isolates produced 15-ADON, and only two isolates had NIV chemotypes. F. asiaticum and F. culmorum produce chemotype of 15-ADON and 3-ADON, respectively. Pathogenicity test results showed that F. pseudograminearum and F. graminearum had strong pathogenicity, and F. asiaticum and F. culmorum had moderate pathogenicity to wheat in Hebei province.

Keywords: crown rot, pathogen, wheat, Fusarium species, mycotoxin

Procedia PDF Downloads 135

Authors: Yasin Akgül, Yusuf Polat, Emine Canbay, Ali Kılıç

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Electrospinning is the most common method to produce nanofibers. However, low production rate is still a big challenge for industrial applications of this method. In this study, morphology of nanofibers obtained from namely centrifugal spinning was investigated. Dominant process parameters acting on the fiber diameter and fiber orientation were discussed.

Keywords: centrifugal spinning, electrospinning, nanofiber, TPU nanofibers

Procedia PDF Downloads 449