Search results for: machine translation

Authors: Mohamed Moustafa Mahmoud Sedky

Abstract:

In line start permanent magnet synchronous motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. This paper presents an FEM that identifies different models, static eccentricity, dynamic eccentricity, and mixed eccentricity, at no load and full load. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates motor speed, torque and flux density distribution along the air gap for SE, DE, and ME. This paper represents the various effects of different eccentricities types on the transient performance.

Keywords: line start permanent magnet, synchronous machine, static eccentricity, dynamic eccentricity, mixed eccentricity

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Authors: Jaskirat Singh, Roshan Lal Virdi, Khushdeep Goyal

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The purpose of this paper is to perform a microstructural analysis of Friction Stir Welded joints of aluminum alloys 6063 and 5083, also to check the properties of the weld zone by SEM analysis. FSW experiments were carried on CNC Vertical milling machine. The tools used for welding were the round cylindrical pin shape and square pin shape. It is found that Microstructure shows the uniformly distributed material with minimum heat affected zone and dense welded zone without any defect. Microstructures indicate that the weld material is defect free. The SEM shows the diffusion of material with base metal with proper bonding without any defect.

Keywords: friction stir welding, aluminum alloy, microstructure, SEM analysis

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Authors: T. Thein, S. Kalyar Myo

Abstract:

Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Hyung Jun Ahn

Abstract:

With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Rupan Preet Kaur

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This article reviewed the potential of artificial intelligence in the field of identity and access management (IAM) and identity governance and administration (IGA), the most critical pillars of any organization. The power of leveraging AI in the most complex and huge user base environment was outlined by simplifying and streamlining the user access approvals and re-certifications without any impact on the user productivity and at the same time strengthening the overall compliance of IAM landscape. Certain challenges encountered in the current state were detailed where majority of organizations are still lacking maturity in the data integrity aspect. Finally, this paper concluded that within the realm of possibility, users and application owners can reap the benefits of unified approach provided by AI to improve the user experience, improve overall efficiency, and strengthen the risk posture.

Keywords: artificial intelligence, machine learning, user access review, access approval

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Authors: Aida Raissi, Holly Wong, Elma Raissi

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Background: Connection is a primal need established during infancy and reiterated in many forms of social interaction. When we make connections with others we experience growth, continuity, and gain an understanding of the other’s sense of the world. Feeling socially connected to another individual or community has been shown to increase self-esteem, happiness, and meaning. However, feeling connected to another individual or a specific community may also decrease the motivation to seek connection with more distant individuals or communities. Furthermore, we allow ourselves to interact with those in other communities as apart from us, and in some cases, to dehumanize their existence. Objective: The aim of this project is to bridge the gap between different communities, specifically religious communities and foster feelings of connection as one with all members through the medium of art, specifically photography. Method: Members of all major faiths including Agnosticism, Atheism, Buddhism, Catholicism, Christianity, Ismaili, Jewish, Ja’far Shia, Sunni will be interviewed. Participants will be asked to partake in a brief interview of two parts: A. Answering two questions: 1. What are you most looking forward to in the future, and why? 2. What does religion mean to you? B. Having their picture taken. Our questions aim to elicit individual stories that together, show that we have more in common, than differences, despite our faiths. With the completion of the interviews, the responses will be compiled together and major themes will be identified. Impact: The resulting stories and corresponding individual pictures provide an excellent opportunity to encourage and inspire people to get to know those of other beliefs and values, participate in each other’s communities and develop a sense of oneness within our shared humanity. Knowledge translation: The personal stories, and the common themes they illustrate, will be shared with various audiences, including the general public, academia and targeted groups such as students. This will be done through displaying the photographs and responses at art galleries, conferences, in print and online.

Keywords: social justice, religion, connection, understanding, community

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Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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Authors: Santhosh Kumat T., Priya E.

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The control of a doubly fed induction generator by fuzzy is described. The active and reactive power can be controlled by rotor and grid side converters with fuzzy controller. The main objective is to maintain constant voltage and frequency at the output of the generator. However the Line Side Converter (LSC) can be controlled to supply up to 50% of the required reactive current. When the crowbar is not activated the DFIG can supply reactive power from the rotor side through the machine as well as through the LSC.

Keywords: Doubly Fed Induction Generator (DFIG), Rotor Side Converter (RSC), Grid Side Converter (GSC), Wind Energy Conversion Systems (WECS)

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Authors: Khenenou Tarek, Mohamed Amine Fares, Djallal Eddine Rahmoun

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The study intends to evaluate the morphological changes in the mesenteric lymph nodes of dromedaries in different rearing systems. we aimed to evaluate the adaptative behavior of the animal’s immune system with environmental variations, and to conduct a comparative analysis on the morphological features of the mesenteric lymph node of the one-humped camel (Camelus dromedarius) in the region of El Oued, with two different rearing systems, with different practices and different purposes. The study was conducted using histo-morphometric techniques to analyze the morphological features of the mesenteric lymph node of the one-humped camel (Camelus dromedarius) in the region of El Oued. Two groups of dromedaries were used in the study, one group raised in a free-roaming housing system and another group raised in a restricted-roaming housing system. The results revealed that there were significant differences between the two groups in terms of active follicle ratio and size and also the cellular population of functional zones. Animals living and roaming outside the farm barriers were more exposed to pathogens, which leads to the installation of an adaptative process, whereas the animals living under restricted-roaming housing system were not exposed to pathogens. This study indicated that the adaptative behavior of the animal’s immune system with environmental variations is the functional translation of morphological changes. The obtained findings revealed that the morphological features of the mesenteric lymph node of the one-humped camel (Camelus dromedarius) in the region of El Oued are directly linked to the rearing system practices

Keywords: adaptative behavior, dromedary, lymph node, morphology, rearing systems

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Authors: Shiva Abdoli, Daniel T.Semere

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Several researches have been conducted to study consumption of energy in cutting process. Most of these researches are focusing to measure the consumption and propose consumption reduction methods. In this work, the relation between the cutting parameters and the consumption is investigated in order to establish a generalized energy consumption model that can be used for process and production planning in real production lines. Using the generalized model, the process planning will be carried out by taking into account the energy as a function of the selected process parameters. Similarly, the generalized model can be used in production planning to select the right operational parameters like batch sizes, routing, buffer size, etc. in a production line. The description and derivation of the model as well as a case study are given in this paper to illustrate the applicability and validity of the model.

Keywords: process parameters, cutting process, energy efficiency, Material Removal Rate (MRR)

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Authors: Amira Yousef Mahrous Yousef

Abstract:

This paper includes fast fashion verses sustainable fashion or slow fashion Indian based consumers. The expression ‘Fast fashion’ is generally referred to low-cost clothing collections that considered first hand copy of luxury brands, sometime interchangeably used with ‘mass fashion’. Whereas slow fashion or limited fashion which are consider to be more organic or eco-friendly. "Sustainable fashion is ethical fashion and here the consumer is just not design conscious but also social-environment conscious". Paper will deal with desire of young Indian consumer towards such luxury brands present in India, and their understanding of sustainable fashion, how to maintain the equilibrium between never newer fashion, style, and fashion sustainability. The green fashion market is growing rapidly as eco-friendly consumers are willing to expand their organic lifestyle to include clothing. With an increasing share of fashion consumers globally, Indian consumers are observed to consider the social and environmental ethics while making purchasing decisions. While some research clearly identifies the efforts of responsible consumers towards green fashion, some argue that fashion-orientated consumers who are sensitive towards environment do not actively participate towards supporting green fashion. This study aims to analyze the current perception of green fashion among Indian consumers. A small-scale exploratory study is conducted where consumers’ perception of green fashion is examined followed by an analysis of translation of this perception into purchase decision making. This research paper gives insight into consumer awareness on green fashion and provides scope towards the expansion of ethical fashion consumption .

Keywords: inclusions, temperature gradient, HPHT synthetic fibers, polyamide fibers, fiber volume, compressive strength. gold nano clusters, copper ions, wool keratin, fluorescence

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Authors: Qiuyue Peng, Vladimir Zachar

Abstract:

The application of adipose-derived stromal/stem cells (ASCs) in regenerative medicine is gaining more awareness due to their advanced translational potential and abundant source preparations. However, ASC-based translation has been confounded by high subpopulation heterogeneity, causing ambiguity about its precise therapeutic value. Some phenotypes defined by a unique combination of positive and negative surface markers have been found beneficial to the required roles. Therefore, the immunophenotypic repertoires of cultured ASCs and temporal changes of distinct subsets were investigated in this study. ASCs from three donors undergoing cosmetic liposuction were cultured in standard culturing methods, and the co-expression patterns based on the combination of selected markers at passages 1, 4, and 8 were analyzed by multi-chromatic flow cytometry. The results showed that the level of heterogeneity of subpopulations of ASCs became lower by in vitro expansion. After a few passages, most of the CD166⁺/CD274⁺/CD271⁺ based subpopulations converged to CD166 single positive cells. Meanwhile, these CD29⁺CD201⁺ double-positive cells, in combination with CD36/Stro-1 expression or without, feathered only the major epitopes and maintained prevailing throughout the whole process. This study suggested that, upon in vitro expansion, the phenotype repertoire of ASCs redistributed and stabilized in a way that cells co-expressing exclusively the strong markers remained dominant. These preliminary findings provide a general overview of the distribution of heterogeneous subsets residents within human ASCs during expansion in vitro. It is a critical step to fully characterize ASCs before clinical application, although the biological effects of heterogeneous subpopulations still need to be clarified.

Keywords: adipose-derived stromal/stem cells, heterogeneity, immunophenotype, subpopulations

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Authors: S. Kherchaoui, A. Houacine

Abstract:

This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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Authors: Felib Ayman Shawky Salem

Abstract:

This paper includes fast fashion verses sustainable fashion or slow fashion Indian based consumers. The expression ‘Fast fashion’ is generally referred to low-cost clothing collections that considered first hand copy of luxury brands, sometime interchangeably used with ‘mass fashion’. Whereas slow fashion or limited fashion which are consider to be more organic or eco-friendly. "Sustainable fashion is ethical fashion and here the consumer is just not design conscious but also social-environment conscious". Paper will deal with desire of young Indian consumer towards such luxury brands present in India, and their understanding of sustainable fashion, how to maintain the equilibrium between never newer fashion, style, and fashion sustainability. The green fashion market is growing rapidly as eco-friendly consumers are willing to expand their organic lifestyle to include clothing. With an increasing share of fashion consumers globally, Indian consumers are observed to consider the social and environmental ethics while making purchasing decisions. While some research clearly identifies the efforts of responsible consumers towards green fashion, some argue that fashion-orientated consumers who are sensitive towards environment do not actively participate towards supporting green fashion. This study aims to analyze the current perception of green fashion among Indian consumers. A small-scale exploratory study is conducted where consumers’ perception of green fashion is examined followed by an analysis of translation of this perception into purchase decision making. This research paper gives insight into consumer awareness on green fashion and provides scope towards the expansion of ethical fashion consumption

Keywords: diamond, inclusions, temperature gradient, HPHT synthetic fibers, polyamide fibers, fiber volume, compressive strength. gold nano clusters, copper ions, wool keratin, fluorescence

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Authors: Hassina Gheribi, Salim Boukebbab

Abstract:

The measurement of the parts manufactured on CMM (coordinate measuring machine) is based on the association of a surface of perfect geometry to the group of dots palpated via a mathematical calculation of the distances between the palpated points and itself surfaces. Surfaces not being never perfect, they are measured by a number of points higher than the minimal number necessary to define them mathematically. However, the central problems of three-dimensional metrology are the estimate of, the orientation parameters, location and intrinsic of this surface. Including the numerical uncertainties attached to these parameters help the metrologist to make decisions to be able to declare the conformity of the part to specifications fixed on the design drawing. During this paper, we will present a data-processing model in Visual Basic-6 which makes it possible automatically to determine the whole of these parameters, and their uncertainties.

Keywords: coordinate measuring machines (CMM), associated surface, uncertainties of measurement, acquisition and modeling

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Authors: Xiao-Yin Liu, Liang-Xue Zhou

Abstract:

Traumatic brain injury (TBI), as a kind of nerve trauma caused by an external force, affects people all over the world and is a global public health problem. Although there are various clinical treatments for brain injury, including surgery, drug therapy, and rehabilitation therapy, the therapeutic effect is very limited. To improve the therapeutic effect of TBI, scaffolds combined with exosomes are a promising but challenging method for TBI repair. In this study, we examined whether a novel 3D-printed collagen/chitosan scaffold/exosomes derived from neural stem cells (NSCs) pretreated with insulin growth factor-1 (IGF-I) scaffolds (3D-CC-INExos) could be used to improve TBI repair and functional recovery after TBI. Our results showed that composite scaffolds of collagen-, chitosan- and exosomes derived from NSCs pretreated with IGF-I (INExos) could continuously release the exosomes for two weeks. In the rat TBI model, 3D-CC-INExos scaffold transplantation significantly improved motor and cognitive function after TBI, as assessed by the Morris water maze test and modified neurological severity scores. In addition, immunofluorescence staining and transmission electron microscopy showed that the recovery of damaged nerve tissue in the injured area was significantly improved by 3D-CC-INExos implantation. In conclusion, our data suggest that 3D-CC-INExos might provide a potential strategy for the treatment of TBI and lay a solid foundation for clinical translation.

Keywords: traumatic brain injury, exosomes, insulin growth factor-1, neural stem cells, collagen, chitosan, 3D printing, neural regeneration, angiogenesis, functional recovery

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Authors: R. Naveen, E. Vanitha, S. Gayathri

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The use of Sandwich composite materials in aerospace and civil infrastructure application has been increasing especially due to their enormously low weight that leads to a reduction in the total weight and fuel consumption, high flexural and transverse shear stiffness, and corrosion resistance. The essential properties of sandwich materials vary according to the application area of the structure. The objectives of this study are to identify the mechanical behaviour and failure mechanisms of sandwich structures made of bamboo, V- board and metal (Aluminium as face sheet and Foam as Core material). The three-point bending test and UTM (Universal testing machine) experimental tests are done for three specimens for each type of sandwich composites. From the experiment results of three sandwich composites, bamboo shows high Young’s modulus of elasticity and low density.

Keywords: bamboo sandwich composite, metal sandwich composite, sandwich composite, v-board sandwich composite

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Authors: Tim Farrelly

Abstract:

In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Misarah Abdelaziz, L Djenidi, Mergen H. Ghayesh, Rey Chin

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Measurements of a turbulent boundary layer over 3D sinusoidal roughness are performed for friction Reynolds numbers ranging from 650 < Reτ < 2700. This surface was fabricated by a Multicam CNC Router machine of an acrylic sheet to have an amplitude of k/2 = 0.8 mm and an equal wavelength of 8k in both streamwise and spanwise directions, a 0.6 mm stepover and 12 mm ball nose cutter was used. Single hotwire anemometry measurements are done at one location x=1.5 m downstream at different freestream velocities under zero-pressure gradient conditions. As expected, the roughness causes a downward shift on the wall-unit normalised streamwise mean velocity profile when compared to the smooth wall profile. The shift is increasing with increasing Reτ, 1.8 < ∆U+ < 6.2. The coefficient of friction is almost constant at all cases Cf = 0.0042 ± 0.0002. The results show a gradual reduction in the inner peak of profiles with increasing Reτ until fully destruction at Reτ of 2700.

Keywords: hotwire, roughness, TBL, ZPG

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Authors: Sun-Ki Hong, Ki-Seok Kim, Yong-Ho Jo

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Lots of motors have been being used in industry. Therefore many researchers have studied about the failure diagnosis of motors. In this paper, the effect of measuring environment for diagnosis of gear fault connected to a motor shaft is studied. The fault diagnosis is executed through the comparison of normal gear and abnormal gear. The measured FFT data are compared with the normal data and analyzed for q-axis current, noise and vibration. For bad and good environment, the diagnosis results are compared. From these, it is shown that the bad measuring environment may not be able to detect exactly the motor gear fault. Therefore it is emphasized that the measuring environment should be carefully prepared.

Keywords: motor fault, diagnosis, FFT, vibration, noise, q-axis current, measuring environment

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Authors: Marc Sader, Michiel Stock, Bernard De Baets

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Considering a large amount of adsorption data of adsorbate gases on adsorbent materials in literature, it is interesting to predict such adsorption data without experimentation. A quantitative structure-activity relationship (QSAR) is developed to correlate molecular characteristics of gases and existing knowledge of materials with their respective adsorption properties. The application of Random Forest, a machine learning method, on a set of adsorption isotherms at a wide range of partial pressures and concentrations is studied. The predicted adsorption isotherms are fitted to several adsorption equations to estimate the adsorption properties. To impute the adsorption properties of desired gases on desired materials, leave-one-out cross-validation is employed. Extensive experimental results for a range of settings are reported.

Keywords: adsorption, predictive modeling, QSAR, random forest

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Authors: Debjit Ray

Abstract:

Horizontal gene transfer (HGT) and recombination leads to the emergence of bacterial antibiotic resistance and pathogenic traits. HGT events can be identified by comparing a large number of fully sequenced genomes across a species or genus, define the phylogenetic range of HGT, and find potential sources of new resistance genes. In-depth comparative phylogenomics can also identify subtle genome or plasmid structural changes or mutations associated with phenotypic changes. Comparative phylogenomics requires that accurately sequenced, complete and properly annotated genomes of the organism. Assembling closed genomes requires additional mate-pair reads or “long read” sequencing data to accompany short-read paired-end data. To bring down the cost and time required of producing assembled genomes and annotating genome features that inform drug resistance and pathogenicity, we are analyzing the performance for genome assembly of data from the Illumina NextSeq, which has faster throughput than the Illumina HiSeq (~1-2 days versus ~1 week), and shorter reads (150bp paired-end versus 300bp paired end) but higher capacity (150-400M reads per run versus ~5-15M) compared to the Illumina MiSeq. Bioinformatics improvements are also needed to make rapid, routine production of complete genomes a reality. Modern assemblers such as SPAdes 3.6.0 running on a standard Linux blade are capable in a few hours of converting mixes of reads from different library preps into high-quality assemblies with only a few gaps. Remaining breaks in scaffolds are generally due to repeats (e.g., rRNA genes) are addressed by our software for gap closure techniques, that avoid custom PCR or targeted sequencing. Our goal is to improve the understanding of emergence of pathogenesis using sequencing, comparative genomics, and machine learning analysis of ~1000 pathogen genomes. Machine learning algorithms will be used to digest the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics). Temporal data and evolutionary models can thus determine whether the origin of a particular isolate is likely to have been from the environment (could it have evolved from previous isolates). It can be useful for comparing differences in virulence along or across the tree. More intriguing, it can test whether there is a direction to virulence strength. This would open new avenues in the prediction of uncharacterized clinical bugs and multidrug resistance evolution and pathogen emergence.

Keywords: genomics, pathogens, genome assembly, superbugs

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Authors: Guofan Shao, Lina Tang, Hao Zhang

Abstract:

The values of image classification accuracy are affected by class size distributions and classification schemes, making it difficult to compare the performance of classification algorithms across different remote sensing data sources and classification systems. Based on the term efficacy from medicine and pharmacology, we have developed the metrics of image classification efficacy at the map and class levels. The novelty of this approach is that a baseline classification is involved in computing image classification efficacies so that the effects of class statistics are reduced. Furthermore, the image classification efficacies are interpretable and comparable, and thus, strengthen the assessment of image data classification methods. We use real-world and hypothetical examples to explain the use of image classification efficacies. The metrics of image classification efficacy meet the critical need to rectify the strategy for the assessment of image classification performance as image classification methods are becoming more diversified.

Keywords: accuracy assessment, efficacy, image classification, machine learning, uncertainty

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Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

Abstract:

Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

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Authors: Henning Lahmann, Benjamyn I. Scott, Bart Custers

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Suboptimal adoption of AI in defence organisations carries risks for the protection of the freedom, safety, and security of society. Despite the vast opportunities that defence AI-technology presents, there are also a variety of ethical, legal, and societal concerns. To ensure the successful use of AI technology by the military, ethical, legal, and societal aspects (ELSA) need to be considered, and their concerns continuously addressed at all levels. This includes ELSA considerations during the design, manufacturing and maintenance of AI-based systems, as well as its utilisation via appropriate military doctrine and training. This raises the question how defence organisations can remain strategically competitive and at the edge of military innovation, while respecting the values of its citizens. This paper will explain the set-up and share preliminary results of a 4-year research project commissioned by the National Research Council in the Netherlands on the ethical, legal, and societal aspects of AI in defence. The project plans to develop a future-proof, independent, and consultative ecosystem for the responsible use of AI in the defence domain. In order to achieve this, the lab shall devise a context-dependent methodology that focuses on the ‘analysis’, ‘design’ and ‘evaluation’ of ELSA of AI-based applications within the military context, which include inter alia unmanned aircraft. This is bolstered as the Lab also recognises and complements the existing methods in regards to human-machine teaming, explainable algorithms, and value-sensitive design. Such methods will be modified for the military context and applied to pertinent case-studies. These case-studies include, among others, the application of autonomous robots (incl. semi- autonomous) and AI-based methods against cognitive warfare. As the perception of the application of AI in the military context, by both society and defence personnel, is important, the Lab will study how these perceptions evolve and vary in different contexts. Furthermore, the Lab will monitor – as they may influence people’s perception – developments in the global technological, military and societal spheres. Although the emphasis of the research project is on different forms of AI in defence, it focuses on several case studies. One of these case studies is on unmanned aircraft, which will also be the focus of the paper. Hence, ethical, legal, and societal aspects of unmanned aircraft in the defence domain will be discussed in detail, including but not limited to privacy issues. Typical other issues concern security (for people, objects, data or other aircraft), privacy (sensitive data, hindrance, annoyance, data collection, function creep), chilling effects, PlayStation mentality, and PTSD.

Keywords: autonomous weapon systems, unmanned aircraft, human-machine teaming, meaningful human control, value-sensitive design

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Authors: R. A. Qawasma, F. M. Haddad, H. O. Salhab

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Hemodialysis is a life-preserving treatment for a number of patients with kidney failure. The standard procedure of hemodialysis is three times a week during the hemodialysis procedure, the patient usually suffering from many inconvenient, exhausting feeling and effect on the heart and cardiovascular system are the most common signs. This paper provides a solution to reduce the previous problems by designing a wearable artificial kidney (WAK) taking in consideration a minimization the size of the dialysis machine. The WAK system consists of two circuits: blood circuit and dialysate circuit. The blood from the patient is filtered in the dialyzer before returning back to the patient. Several parameters using an advanced microcontroller and array of sensors. WAK equipped with visible and audible alarm system to aware the patients if there is any problem.

Keywords: artificial kidney, home dialysis, renal failure, wearable kidney

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Authors: Li Zhou, Yanmei Fang

Abstract:

With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

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Authors: Ssu-Han Chen, Der-Baau Perng

Abstract:

Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation

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Authors: Khaled Mohammed

Abstract:

This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

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Authors: Paul B Stone, Subhashini Ganapathy, Mary E. Fendley, Layla Akilan

Abstract:

As notifications become more common through mobile devices, it is important to understand the impact of wearable devices on the improved user experience of man-machine interfaces. This study examined the use of a wearable device for a real-time system using a computer-simulated petrochemical system. The key research question was to determine how using the information provided by the wearable device can improve human performance through measures of situational awareness and decision making. Results indicate that there was a reduction in response time when using the watch, and there was no difference in situational awareness. Perception of using the watch was positive, with 83% of users finding value in using the watch and receiving haptic feedback.

Keywords: computer applications, haptic feedback, petrochemical systems, situational awareness, wearable technology

Procedia PDF Downloads 200