Search results for: feature fusion

Authors: Sonam Kumari

Abstract:

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, possesses a remarkable feature of entering into and emerging from a persistent state. The mechanism by which Mtb switches from the dormant state to the replicative form is still poorly characterized. Proteome studies have given us an insight into the role of certain proteins in giving stupendous virulence to Mtb, but numerous dotsremain unconnected and unaccounted. The WhiB family of proteins is one such protein that is associated with developmental processes in actinomycetes.Mtb has seven such proteins (WhiB1 to WhiB7).WhiB proteins are transcriptional regulators; their conserved C-terminal HTH motif is involved in DNA binding. They regulate various essential genes of Mtbby binding to their promoter DNA. Biophysical Analysis of the effect of DNA binding on WhiB proteins has not yet been appropriately characterized. Interaction with DNA induces conformational changes in the WhiB proteins, confirmed by steady-state fluorescence and circular dichroism spectroscopy. ITC has deduced thermodynamic parameters and the binding affinity of the interaction. Since these transcription factors are highly unstable in vitro, their stability and solubility were enhanced by the co-expression of molecular chaperones. The present study findings help determine the conditions under which the WhiB proteins interact with their interacting partner and the factors that influence their binding affinity. This is crucial in understanding their role in regulating gene expression in Mtbandin targeting WhiB proteins as a drug target to cure TB.

Keywords: tuberculosis, WhiB proteins, mycobacterium tuberculosis, nucleic acid binding

Procedia PDF Downloads 101

Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

Abstract:

With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation

Procedia PDF Downloads 351

Authors: Misagh Irandoost Shahrestani, Mehdi Ashjaee, Shahrokh Zandieh Vakili

Abstract:

In this paper, partially premixed laminar methane/air co-flow flame is studied experimentally. Methane-air flame was established on an axisymmetric coannular burner. The fuel-air jet flows from the central tube while the secondary air flows from the region between the inner and the outer tube. The aim is to investigate the flame features and to develop a nonintrusive method for temperature measurement of methane/air partially premixed flame using Mach-Zehnder interferometry method. Different equivalence ratios and Reynolds numbers are considered. Flame generic visible appearance was also investigated and its various structures were studied. Three distinguished flame regimes were seen based on its appearance. A double flame structure can be seen for the equivalence ratio in the range of 1<Φ<2.1. By adding air to the mixture up to Φ=4 the flame has the characteristics of both premixed and non-premixed flames. Finally for 4<Φ<∞ the flame mainly becomes non-premixed like and the luminous sooting region on its tip is the obvious feature of this type of flames. The Mach-Zehnder method is used to obtain temperature field of a transparent fluid by means of index of refraction. Temperature obtained from optical techniques was compared with that of obtained from thermocouples in order to validate the results. Good agreement was observed for these two methods.

Keywords: flame structure, Mach-Zehnder interferometry, partially premixed flame, temperature field

Procedia PDF Downloads 480

Authors: Nursel Koyuncu, Nihal Ata Tutkun

Abstract:

Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

Procedia PDF Downloads 209

Authors: R. Noorani, K. Peerless, J. Mandrell, A. Lopez, R. Dalberto, M. Alzebaq

Abstract:

Rapid prototyping (RP) is an additive manufacturing technology used in industry that works by systematically depositing layers of working material to construct larger, computer-modeled parts. A key challenge associated with this technology is that RP parts often feature undesirable levels of surface roughness for certain applications. To combat this phenomenon, an experimental technique called Design of Experiments (DOE) can be employed during the growth procedure to statistically analyze which RP growth parameters are most influential to part surface roughness. Utilizing DOE to identify such factors is important because it is a technique that can be used to optimize a manufacturing process, which saves time, money, and increases product quality. In this study, a four-factor/two level DOE experiment was performed to investigate the effect of temperature, layer thickness, infill percentage, and infill speed on the surface roughness of RP prototypes. Samples were grown using the sixteen different possible growth combinations associated with a four-factor/two level study, and then the surface roughness data was gathered for each set of factors. After applying DOE statistical analysis to these data, it was determined that layer thickness played the most significant role in the prototype surface roughness.

Keywords: rapid prototyping, surface roughness, design of experiments, statistical analysis, factors and levels

Procedia PDF Downloads 261

Authors: Aoqi Zhang, Changgil Lee Lee, Seunghee Park

Abstract:

A non-contact nondestructive technique using laser-induced ultrasonic wave generation method was applied to visualize corrosion damage at aluminum alloy plate structures. The ultrasonic waves were generated by a Nd:YAG pulse laser, and a galvanometer-based laser scanner was used to scan specific area at a target structure. At the same time, wave responses were measured at a piezoelectric sensor which was attached on the target structure. The visualization of structural damage was achieved by calculating logarithmic values of root mean square (RMS). Damage-sensitive feature was defined as the scattering characteristics of the waves that encounter corrosion damage. The corroded damage was artificially formed by hydrochloric acid. To observe the effect of the location where the corrosion was formed, the both sides of the plate were scanned with same scanning area. Also, the effect on the depth of the corrosion was considered as well as the effect on the size of the corrosion. The results indicated that the damages were successfully visualized for almost cases, whether the damages were formed at the front or back side. However, the damage could not be clearly detected because the depth of the corrosion was shallow. In the future works, it needs to develop signal processing algorithm to more clearly visualize the damage by improving signal-to-noise ratio.

Keywords: non-destructive testing, corrosion, pulsed laser scanning, ultrasonic waves, plate structure

Procedia PDF Downloads 299

Authors: Wenhao Lan, Ning Li, Qiang Tong

Abstract:

To improve the registration accuracy of a source point cloud and template point cloud when the initial relative deflection angle is too large, a PointNetLK algorithm combined with an oriented bounding box (PointNetLK-OBB) is proposed. In this algorithm, the OBB of a 3D point cloud is used to represent the macro feature of source and template point clouds. Under the guidance of the iterative closest point algorithm, the OBB of the source and template point clouds is aligned, and a mirror symmetry effect is produced between them. According to the fitting degree of the source and template point clouds, the mirror symmetry plane is detected, and the optimal rotation and translation of the source point cloud is obtained to complete the 3D point cloud registration task. To verify the effectiveness of the proposed algorithm, a comparative experiment was performed using the publicly available ModelNet40 dataset. The experimental results demonstrate that, compared with PointNetLK, PointNetLK-OBB improves the registration accuracy of the source and template point clouds when the initial relative deflection angle is too large, and the sensitivity of the initial relative position between the source point cloud and template point cloud is reduced. The primary contribution of this paper is the use of PointNetLK to avoid the non-convex problem of traditional point cloud registration and leveraging the regularity of the OBB to avoid the local optimization problem in the PointNetLK context.

Keywords: mirror symmetry, oriented bounding box, point cloud registration, PointNetLK-OBB

Procedia PDF Downloads 148

Authors: Jyh-Cherng Gu, Ming-Ta Yang, Chao-Fong Yan, Hsin-Yung Chung, Yung-Ruei Chang, Yih-Der Lee, Chen-Min Chan, Chia-Hao Hsu

Abstract:

There are a number of distributed generations (DGs) installed in microgrid, which may have diverse path and direction of power flow or fault current. The overcurrent protection scheme for the traditional radial type distribution system will no longer meet the needs of microgrid protection. Integrating the intelligent electronic device (IED) and a supervisory control and data acquisition (SCADA) with IEC 61850 communication protocol, the paper proposes a microgrid protection management system (MPMS) to protect power system from the fault. In the proposed method, the MPMS performs logic programming of each IED to coordinate their tripping sequence. The GOOSE message defined in IEC 61850 is used as the transmission information medium among IEDs. Moreover, to cope with the difference in fault current of microgrid between grid-connected mode and islanded mode, the proposed MPMS applies the group setting feature of IED to protect system and robust adaptability. Once the microgrid topology varies, the MPMS will recalculate the fault current and update the group setting of IED. Provided there is a fault, IEDs will isolate the fault at once. Finally, the Matlab/Simulink and Elipse Power Studio software are used to simulate and demonstrate the feasibility of the proposed method.

Keywords: IEC 61850, IED, group Setting, microgrid

Procedia PDF Downloads 458

Authors: Ahmet Ozcan, Onder Alparslan, Anil Sezgin, Omer Cetin

Abstract:

The use of unmanned systems for different purposes has become very popular over the past decade. Expectations from these systems have also shown an incredible increase in this parallel. But meeting the demands of the tasks are often not possible with the usage of a single unmanned vehicle in a mission, so it is necessary to use multiple autonomous vehicles with different abilities together in coordination. Therefore the usage of the same type of vehicles together as a swarm is helped especially to satisfy the time constraints of the missions effectively. In other words, it allows sharing the workload by the various numbers of homogenous platforms together. Besides, it is possible to say there are many kinds of problems that require the usage of the different capabilities of the heterogeneous platforms together cooperatively to achieve successful results. In this case, cooperative working brings additional problems beyond the homogeneous clusters. In the scenario presented as an example problem, it is expected that an autonomous ground vehicle, which is lack of its position information, manage to perform point-to-point navigation without losing its way in a previously unknown labyrinth. Furthermore, the ground vehicle is equipped with very limited sensors such as ultrasonic sensors that can detect obstacles. It is very hard to plan or complete the mission for the ground vehicle by self without lost its way in the unknown labyrinth. Thus, in order to assist the ground vehicle, the autonomous air drone is also used to solve the problem cooperatively. The autonomous drone also has limited sensors like downward looking camera and IMU, and it also lacks computing its global position. In this context, it is aimed to solve the problem effectively without taking additional support or input from the outside, just benefiting capabilities of two autonomous vehicles. To manage the point-to-point navigation in a previously unknown labyrinth, the platforms have to work together coordinated. In this paper, cooperative work of heterogeneous unmanned systems is handled in an applied sample scenario, and it is mentioned that how to work together with an autonomous ground vehicle and the autonomous flying platform together in a harmony to take advantage of different platform-specific capabilities. The difficulties of using heterogeneous multiple autonomous platforms in a mission are put forward, and the successful solutions are defined and implemented against the problems like spatially distributed tasks planning, simultaneous coordinated motion, effective communication, and sensor fusion.

Keywords: unmanned systems, heterogeneous autonomous vehicles, coordination, task planning

Procedia PDF Downloads 126

Authors: Mojtaba Heydarizad

Abstract:

Andarokh basin is one of the main karstic regions in Khorasan Razavi province NE Iran. This basin is part of Kopeh-Dagh mega zone extending from Caspian Sea in the east to northern Afghanistan in the west. This basin is covered by Mozdooran Formation, Ngr evaporative formation and quaternary alluvium deposits in descending order of age. Mozdooran carbonate formation is notably karstified. The main surface karstic features in Mozdooran formation are Groove karren, Cleft karren, Rain pit, Rill karren, Tritt karren, Kamintza, Domes, and Table karren. In addition to surface features, deep karstic feature Andarokh Cave also exists in the region. Studying Ca, Mg, Mn, Sr, Fe concentration and Sr/Mn ratio in Mozdooran formation samples with distance to main faults and joints system using PCA analyses demonstrates intense meteoric digenesis role in controlling carbonate rock geochemistry. The karst evaluation in Andarokh basin varies from early stages 'deep seated karst' in Mesozoic to mature karstic system 'Exhumed karst' in quaternary period. Andarokh cave (the main cave in Andarokh basin) is rudimentary branch work consists of three passages of A, B and C and two entrances Andarokh and Sky.

Keywords: Andarokh basin, Andarokh cave, geochemical analyses, karst evaluation

Procedia PDF Downloads 153

Authors: Bipasha Sen, Aditya Agarwal

Abstract:

Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

Procedia PDF Downloads 122

Authors: Nasrin Hosseinzad

Abstract:

Troxerutin, a trihydroxyethylated derived of rutin, is a flavonoid existing in tea, coffee, cereal grains, various fruits and vegetables have been conveyed to display radioprotective, antithrombotic, nephron-protective and hepato-protective possessions. Troxerutin, has been well-proved to utilize hepatoprotective assets. Troxerutin could upturn the resistance of hippocampal neurons alongside apoptosis by lessening the action of AChE and oxidative stress. Consequently, troxerutin may have advantageous properties in the administration of Alzheimer's disease and cancer. Troxerutin has been testified to have several welfares and medicinal stuffs. It could shelter the mouse kidney against d-gal-induced damage by refining renal utility, decreasing histopathologic changes, dropping ROS construction, reintroducing the activities of antioxidant enzymes and reducing DNA oxidative destruction. The DNA cleavage study clarifies that troxerutin showed DNA protection against hydroxyl radical persuaded DNA mutilation. Troxerutin uses anti-cancer effect in HuH-7 hepatocarcinoma cells conceivably through synchronized regulation of the molecular signalling pathways, Nrf2 and NF-κB. DNA binding at slight channel by troxerutin may have donated to feature breaks leading to improved radiation brought cell death. Furthermore, the mechanism principal the observed variance in the antioxidant activities of troxerutin and its esters was qualified to equally their free radical scavenging capabilities and dissemination on the cell membrane outward.

Keywords: troxerutin, DNA, oxidative stress, antioxidant, free radical

Procedia PDF Downloads 159

Authors: Jay Ananth

Abstract:

The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

Procedia PDF Downloads 108

Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

Procedia PDF Downloads 486

Authors: David A. Swanson, Lucky M. Tedrow

Abstract:

Taylor’s Law is a widely observed empirical pattern that relates variances to means in sets of non-negative measurements via an approximate power function, which has found application to human mortality. This study adds to this research by showing that Taylor’s Law leads to a model that reasonably describes the relationship between life expectancy at birth (e0, which also is equal to mean age at death in a life table) and variance at age of death in seven World Bank regional life tables measured at two points in time, 1970 and 2000. Using as a benchmark a non-random sample of four Japanese female life tables covering the period from 1950 to 2004, the study finds that the simple linear model provides reasonably accurate estimates of variance in age at death in a life table from e0, where the latter range from 60.9 to 85.59 years. Employing 2017 life tables from the Human Mortality Database, the simple linear model is used to provide estimates of variance at age in death for six countries, three of which have high e0 values and three of which have lower e0 values. The paper provides a substantive interpretation of Taylor’s Law relative to e0 and concludes by arguing that reasonably accurate estimates of variance in age at death in a period life table can be calculated using this approach, which also can be used where e0 itself is estimated rather than generated through the construction of a life table, a useful feature of the model.

Keywords: empirical pattern, mean age at death in a life table, mean age of a stationary population, stationary population

Procedia PDF Downloads 328

Authors: Abdullah Bal, Sevdenur Bal

Abstract:

This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.

Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware

Procedia PDF Downloads 506

Authors: Bin Wang, Yong Xu, Honggang Qu, Rongmei Liu, Zhenji Gao

Abstract:

Based on the geodynamic environment, basic geological characteristics of minerals and so on, gold deposits in China are divided into 11 categories, of which tectonic fracture altered rock, mid-intrudes and contact zone, micro-fine disseminated and continental volcanic types are the main prospecting kinds. The metallogenic age of gold deposits in China is dominated by the Mesozoic and Cenozoic. According to the geotectonic units, geological evolution, geological conditions, spatial distribution, gold deposits types, metallogenic factors etc., 42 gold concentration areas are initially determined and have a concentrated distribution feature. On the basis of the gold exploration density, gold concentration areas are divided into high, medium and low level areas. High ones are mainly distributed in the central and eastern regions. 93.04% of the gold exploration drillings are within 500 meters, but there are some problems, such as less and shallower of drilling verification etc.. The paper discusses the resource potentials of gold deposits and proposes the future prospecting directions and suggestions. The deep and periphery of old mines in the central and eastern regions and western area, especially in Xinjiang and Qinghai, will be the future key prospecting one and have huge potential gold reserves. If the exploration depth is extended to 2,000 meters shallow, the gold resources will double.

Keywords: gold deposits, gold deposits types, gold concentration areas, prospecting, resource potentiality

Procedia PDF Downloads 75

Authors: Sanchali Das, Swapan Debbarma

Abstract:

Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

Procedia PDF Downloads 218

Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

Abstract:

Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

Procedia PDF Downloads 371

Authors: Pei Yi Lin

Abstract:

Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

Procedia PDF Downloads 73

Authors: Ahmed. Abdel Bary, Omneya. Khowessah, Mojahed. al-jamrah

Abstract:

Introduction: The major challenge with the design of oral dosage forms lies with their poor bioavailability. The most frequent causes of low oral bioavailability are attributed to poor solubility and low permeability. The aim of this study was to develop solid nanodispersed tablet formulation of Glimepiride for the enhancement of the solubility and bioavailability. Methodology: Solid nanodispersions of Glimepiride (GMP) were prepared using two different ratios of 2 different carriers, namely; PEG6000, pluronic F127, and by adopting two different techniques, namely; solvent evaporation technique and fusion technique. A full factorial design of 2 3 was adopted to investigate the influence of formulation variables on the prepared nanodispersion properties. The best chosen formula of nanodispersed powder was formulated into tablets by direct compression. The Differential Scanning Calorimetry (DSC) analysis and Fourier Transform Infra-Red (FTIR) analysis were conducted for the thermal behavior and surface structure characterization, respectively. The zeta potential and particle size analysis of the prepared glimepiride nanodispersions was determined. The prepared solid nanodispersions and solid nanodispersed tablets of GMP were evaluated in terms of pre-compression and post-compression parameters, respectively. Results: The DSC and FTIR studies revealed that there was no interaction between GMP and all the excipients used. Based on the resulted values of different pre-compression parameters, the prepared solid nanodispersions powder blends showed poor to excellent flow properties. The resulted values of the other evaluated pre-compression parameters of the prepared solid nanodispersion were within the limits of pharmacopoeia. The drug content of the prepared nanodispersions ranged from 89.6 ± 0.3 % to 99.9± 0.5% with particle size ranged from 111.5 nm to 492.3 nm and the resulted zeta potential (ζ ) values of the prepared GMP-solid nanodispersion formulae (F1-F8) ranged from -8.28±3.62 mV to -78±11.4 mV. The in-vitro dissolution studies of the prepared solid nanodispersed tablets of GMP concluded that GMP- pluronic F127 combinations (F8), exhibited the best extent of drug release, compared to other formulations, and to the marketed product. One way ANOVA for the percent of drug released from the prepared GMP-nanodispersion formulae (F1- F8) after 20 and 60 minutes showed significant differences between the percent of drug released from different GMP-nanodispersed tablet formulae (F1- F8), (P<0.05). Conclusion: Preparation of glimepiride as nanodispersed particles proven to be a promising tool for enhancing the poor solubility of glimepiride.

Keywords: glimepiride, solid Nanodispersion, nanodispersed tablets, poorly water soluble drugs

Procedia PDF Downloads 485

Authors: Mina Beheshti, Vida Shams, Mojtaba Esfandiari, Farzaneh Abdollahi, Abdolreza Ohadi

Abstract:

Most of the people who survive a stroke need rehabilitation tools to regain their mobility. The core function of these devices is a brake actuator. The goal of this study is to design and control a magnetorheological brake which can be used as a rehabilitation tool. In fact, the fluid used in this brake is called magnetorheological fluid or MR that properties can change by variation of the magnetic field. The braking properties can be set as control by using this feature of the fluid. In this research, different MR brake designs are first introduced in each design, and the dimensions of the brake have been determined based on the required torque for foot movement. To calculate the brake dimensions, it is assumed that the shear stress distribution in the fluid is uniform and the fluid is in its saturated state. After designing the rehabilitation brake, the mathematical model of the healthy movement of a healthy person is extracted. Due to the nonlinear nature of the system and its variability, various adaptive controllers, neural networks, and robust have been implemented to estimate the parameters and control the system. After calculating torque and control current, the best type of controller in terms of error and control current has been selected. Finally, this controller is implemented on the experimental data of the patient's movements, and the control current is calculated to achieve the desired torque and motion.

Keywords: rehabilitation, magnetorheological fluid, knee, brake, adaptive control, robust control, neural network control, torque control

Procedia PDF Downloads 151

Authors: Avijit Sengupta, Klarissa Ting Ting Cheng, Maffee Peng-Hui Wan

Abstract:

This study investigates the influence of user factors and referent characteristics on representation types generated using the stereotype production method for designing icons. Sixty-eight participants of farming communities were asked to draw images based on sixteen feature referents. Significant statistical differences were found between the types of representations generated for contextual and context-independent referents. Strong correlations were observed between years of formal education and total number of abstract representations produced for both contextual and context-independent referents. However, representation characteristics were not influenced by other user factors such as participants’ experience with mobile phone and years of farming experience. A statistically significant tendency of making concrete representations was observed for both contextual and context-independent referents. These findings provide insights on community members’ involvement in icon design and suggest a consolidated icon design strategy based on population stereotype, particularly for under-served rural communities of India.

Keywords: abstract representation, concrete representation, participatory design, population stereotype

Procedia PDF Downloads 374

Authors: Zeljko Crljen, Predrag Lazic

Abstract:

Graphene has attracted a tremendous interest in the field of nanoelectronics and spintronics due to its exceptional electronic properties. However, pristine graphene has no band gap, a feature needed in building some of the electronic elements. Recently, a growing attention has been given to a class of carbon allotropes of graphene with honeycomb structures, in particular to graphyne and graphdiyne. They are characterized with a single and double acetylene bonding chains respectively, connecting the nearest-neighbor hexagonal rings. With an electron density comparable to that of graphene and a prominent gap in electronic band structures they appear as promising materials for nanoelectronic components. We studied the electronic structure and transport of infinite sheets of graphyne and graphdiyne and compared them with graphene. The method based on the non-equilibrium Green functions and density functional theory has been used in order to obtain a full ab initio self-consistent description of the transport current with different electrochemical bias potentials. The current/voltage (I/V) characteristics show a semi-conducting behavior with prominent nonlinearities at higher voltages. The calculated band gaps are 0.52V and 0.59V, respectively, and the effective masses are considerably smaller compared to typical semiconductors. We analyzed the results in terms of transmission eigenchannels and showed that the difference in conductance is directly related to the difference of the internal structure of the allotropes.

Keywords: electronic transport, graphene-like structures, nanoelectronics, two-dimensional materials

Procedia PDF Downloads 189

Authors: Jai Hyung Park, Eugene Kim, Jin Hun Park, Min Joon Oh

Abstract:

Introduction: Subchondral insufficiency fracture of the femoral head (SIF) is a rare complication; however, it has been recognized to cause femoral head collapse. Subchondral insufficiency fracture (SIF) is caused by normal or physiological stress without any trauma. It has been reported in osteoporotic patients after the fixation of the proximal femur with an Intramedullary nail. Case presentation: We reported 5 cases with SIF of the femoral head after proximal femur fracture fixation with Intra-medullary nail. All patients had osteoporosis as an underlying disease. Good reduction was achieved in all 5 patients. SIF was found from about 3 months to 4 years after the initial operation, and all the fractures were solidly united at the final diagnosis. We investigated retrospectively the feature of those cases and several factors that affected the occurrence of SIF. Discussion: There are a few discussions regarding the SIF of the femoral head. These discussions may include the predisposing risk factors, how to diagnose the SIF in osteoporotic patients, and the peri-operative factors to prevent SIF. Conclusion: Subchondral insufficiency fracture of the femoral head is a considerable complication after the internal fixation of the proximal femur. There are several factors that can be modified. If they could be controlled in the peri-operative period, SIF could be prevented or handled in advance. Other options related to arthroplasty can be considered in old osteoporotic patients.

Keywords: insufficiency fracture of femoral head, intra-medullary nail, osteoporosis, proximal femur fracture

Procedia PDF Downloads 126

Authors: Kevin Kellner, Nga Lao, Orla Coleman, Paula Meleady, Niall Barron

Abstract:

Chinese Hamster Ovary (CHO) cells are the prominent cell line used in biopharmaceutical production. To improve yields and find beneficial bioprocess phenotypes genetic engineering plays an essential role in recent research. The miR-23 cluster, specifically miR-24 and miR-27, was first identified as differentially expressed during hypothermic conditions suggesting a role in proliferation and productivity in CHO cells. In this study, we used sponge decoy technology to stably deplete the miRNA expression of the cluster. Furthermore, we implemented the CRISPR/Cas9 system to knockdown miRNA expression. Sponge constructs were designed for an imperfect binding of the miRNA target, protecting from RISC mediated cleavage. GuideRNAs for the CRISPR/Cas9 system were designed to target the seed region of the miRNA. The expression of mature miRNA and precursor were confirmed using RT-qPCR. For both approaches stable expressing mixed populations were generated and characterised in batch cultures. It was shown, that CRISPR/Cas9 can be implemented in CHO cells with achieving high knockdown efficacy of every single member of the cluster. Targeting of one miRNA member showed that its genomic paralog is successfully targeted as well. The stable depletion of miR-24 using CRISPR/Cas9 showed increased growth and specific productivity in a CHO-K1 mAb expressing cell line. This phenotype was further characterized using quantitative label-free LC-MS/MS showing 186 proteins differently expressed with 19 involved in proliferation and 26 involved in protein folding/translation. Targeting miR-27 in the same cell line showed increased viability in late stages of the culture compared to the control. To evaluate the phenotype in an industry relevant cell line; the miR-23 cluster, miR-24 and miR-27 were stably depleted in a Fc fusion CHO-S cell line which showed increased batch titers up to 1.5-fold. In this work, we highlighted that the stable depletion of the miR-23 cluster and its members can improve the bioprocess phenotype concerning growth and productivity in two different cell lines. Furthermore, we showed that using CRISPR/Cas9 is comparable to the traditional sponge decoy technology.

Keywords: Chinese Hamster ovary cells, CRISPR/Cas9, microRNAs, sponge decoy technology

Procedia PDF Downloads 196

Authors: Latika Choudhary

Abstract:

“The potential benefits of Artificial Intelligence are huge, So are the dangers.” - Dave Water. Artificial intelligence is one of the facet of Information technology domain which despite several attempts does not have a clear definition or ambit. However it can be understood as technology to solve problems via automated decisions and predictions. Artificial intelligence is essentially an algorithm based technology which analyses the large amounts of data and then solves problems by detecting useful patterns. Owing to its automated feature it will not be wrong to say that humans & AI have more utility than humans alone or computers alone.1 For many decades AI experienced enthusiasm as well as setbacks, yet it has today become part and parcel of our everyday life, making it convenient or at times problematic. AI and related technology encompass Intellectual Property in multiple ways, the most important being AI technology for management of Intellectual Property, IP for protecting AI and IP as a hindrance to the transparency of AI systems. Thus the relationship between the two is of reciprocity as IP influences AI and vice versa. While AI is a recent concept, the IP laws for protection or even dealing with its challenges are relatively older, raising the need for revision to keep up with the pace of technological advancements. This paper will analyze the relationship between AI and IP to determine how beneficial or conflictual the same is, address how the old concepts of IP are being stretched to its maximum limits so as to accommodate the unwanted consequences of the Artificial Intelligence and propose ways to mitigate the situation so that AI becomes the friend it is and not turn into a potential foe it appears to be.

Keywords: intellectual property rights, information technology, algorithm, artificial intelligence

Procedia PDF Downloads 85

Authors: Hamdan Arief Hanif, Rahmat Sidiq

Abstract:

Indonesia is a country of law, the legal system adopted by Indonesia is a civil law system. A major feature of the civil law is the codified legislation. Meanwhile the majority of society Indonesia are Muslims, whilst Islamic law itself having the sources written in Qur'an, Sunnah and the opinion of Muslim scholars, generally not codified in book form of legislation that is easy on the set as a reference. in Indonesia, many scholars have different opinions in decisions so that there is no legal certainty in Muslim civil cases, so the need for legal codification, which, as the source of the judges in deciding a case, especially a case in religious courts. This paper raised the topic of discussion which offers a solution to the application of the codification of the Islamic Law which became the core resources in delivering a verdict against Islamic civil related issue; codification usually called a compilation of Islamic Law. Compilation of Islamic Law is highly recommended as a core reference for the judges in religious courts in Indonesia. This compilation which includes a collection of large number of opinions scholars (book of fiqh) that existed previously and are ripened in deduce in order to unify the existing differences. This paper also discusses how the early formation of the compilation and as the right solution in order to create legal certainty and justice especially for the muslim community in Indonesia.

Keywords: Islamic law, compilation, law applied core, religious court

Procedia PDF Downloads 354

Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

Abstract:

Background modeling and subtraction in video analysis has been widely proved to be an effective method for moving objects detection in many computer vision applications. Over the past years, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are two of the most frequently occurring issues in the practical situation. This paper presents a new two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean values of RGB color channels. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block-wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the outputs of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate a very competitive performance compared to previous models.

Keywords: background subtraction, codebook model, local binary pattern, dynamic background, illumination change

Procedia PDF Downloads 216

Authors: Mudavath Raju, Bhaskar Gugulothu, B. Rajendra Naik

Abstract:

The rapid advances in Very Large Scale Integration (VLSI) technology has resulted in the reduction of minimum feature size to sub-quarter microns and switching time in tens of picoseconds or even less. As a result, the degradation of high-speed digital circuits due to signal integrity issues such as coupling effects, clock feedthrough, crosstalk noise and delay uncertainty noise. Crosstalk noise in VLSI interconnects is a major concern and reduction in VLSI interconnect has become more important for high-speed digital circuits. It is the most effectively considered in Deep Sub Micron (DSM) and Ultra Deep Sub Micron (UDSM) technology. Increasing spacing in-between aggressor and victim line is one of the technique to reduce the crosstalk. Guard trace or shield insertion in-between aggressor and victim is also one of the prominent options for the minimization of crosstalk. In this paper, far end crosstalk noise is estimated with mutual inductance and capacitance RLC interconnect model. Also investigated the extent of crosstalk in capacitive and inductively coupled interconnects to minimizes the same through shield insertion technique.

Keywords: VLSI, interconnects, signal integrity, crosstalk, shield insertion, guard trace, deep sub micron

Procedia PDF Downloads 184