Search results for: Signal Processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5008

Search results for: Signal Processing

2758 A Data-Driven Approach for Studying the Washout Effects of Rain on Air Pollution

Authors: N. David, H. O. Gao

Abstract:

Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.

Keywords: air pollution, commercial microwave links, rainfall, washout

Procedia PDF Downloads 111
2757 Metal-Organic Chemical Vapor Deposition (MOCVD) Process Investigation for Co Thin Film as a TSV Alternative Seed Layer

Authors: Sajjad Esmaeili, Robert Krause, Lukas Gerlich, Alireza Mohammadian Kia, Benjamin Uhlig

Abstract:

This investigation aims to develop the feasible and qualitative process parameters for the thin films fabrication into ultra-large through-silicon-vias (TSVs) as vertical interconnections. The focus of the study is on TSV metallization and its challenges employing new materials for the purpose of rapid signal propagation in the microsystems technology. Cobalt metal-organic chemical vapor deposition (Co-MOCVD) process enables manufacturing an adhesive and excellent conformal ultra-thin film all the way through TSVs in comparison with the conventional non-conformal physical vapor deposition (PVD) process of copper (Cu) seed layer. Therefore, this process provides a Cu seed-free layer which is capable of direct Cu electrochemical deposition (Cu-ECD) on top of it. The main challenge of this metallization module is to achieve the proper alternative seed layer with less roughness, sheet resistance and granular organic contamination (e.g. carbon) which intensify the Co corrosion under the influence of Cu electrolyte.

Keywords: Cobalt MOCVD, direct Cu electrochemical deposition (ECD), metallization technology, through-silicon-via (TSV)

Procedia PDF Downloads 158
2756 Thermoplastic Composites with Reduced Discoloration and Enhanced Fire-Retardant Property

Authors: Peng Cheng, Liqing Wei, Hongyu Chen, Ruomiao Wang

Abstract:

This paper discusses a light-weight reinforced thermoplastic (LWRT) composite with superior fire retardancy. This porous LWRT composite is manufactured using polyolefin, fiberglass, and fire retardant additives via a wet-lay process. However, discoloration of the LWRT can be induced by various mechanisms, which may be a concern in the building and construction industry. It is commonly understood that discoloration is strongly associated with the presence of phenolic antioxidant(s) and NOx. The over-oxidation of phenolic antioxidant(s) is probably the root-cause of the discoloration (pinking/yellowing). Hanwha Azdel, Inc. developed a LWRT with fire-retardant property of ASTM E84-Class A specification, as well as negligible discoloration even under harsh conditions. In addition, this thermoplastic material is suitable for secondary processing (e.g. compression molding) if necessary.

Keywords: discoloration, fire-retardant, thermoplastic composites, wet-lay process

Procedia PDF Downloads 126
2755 The Classification of Parkinson Tremor and Essential Tremor Based on Frequency Alteration of Different Activities

Authors: Chusak Thanawattano, Roongroj Bhidayasiri

Abstract:

This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

Procedia PDF Downloads 443
2754 Production of Ferroboron by SHS-Metallurgy from Iron-Containing Rolled Production Wastes for Alloying of Cast Iron

Authors: G. Zakharov, Z. Aslamazashvili, M. Chikhradze, D. Kvaskhvadze, N. Khidasheli, S. Gvazava

Abstract:

Traditional technologies for processing iron-containing industrial waste, including steel-rolling production, are associated with significant energy costs, the long duration of processes, and the need to use complex and expensive equipment. Waste generated during the industrial process negatively affects the environment, but at the same time, it is a valuable raw material and can be used to produce new marketable products. The study of the effectiveness of self-propagating high-temperature synthesis (SHS) methods, which are characterized by the simplicity of the necessary equipment, the purity of the final product, and the high processing speed, is under the wide scientific and practical interest to solve the set problem. The work presents technological aspects of the production of Ferro boron by the method of SHS - metallurgy from iron-containing wastes of rolled production for alloying of cast iron and results of the effect of alloying element on the degree of boron assimilation with liquid cast iron. Features of Fe-B system combustion have been investigated, and the main parameters to control the phase composition of synthesis products have been experimentally established. Effect of overloads on patterns of cast ligatures formation and mechanisms structure formation of SHS products was studied. It has been shown that an increase in the content of hematite Fe₂O₃ in iron-containing waste leads to an increase in the content of phase FeB and, accordingly, the amount of boron in the ligature. Boron content in ligature is within 3-14%, and the phase composition of obtained ligatures consists of Fe₂B and FeB phases. Depending on the initial composition of the wastes, the yield of the end product reaches 91 - 94%, and the extraction of boron is 70 - 88%. Combustion processes of high exothermic mixtures allow to obtain a wide range of boron-containing ligatures from industrial wastes. In view of the relatively low melting point of the obtained SHS-ligature, the positive dynamics of boron absorption by liquid iron is established. According to the obtained data, the degree of absorption of the ligature by alloying gray cast iron at 1450°C is 80-85%. When combined with the treatment of liquid cast iron with magnesium, followed by alloying with the developed ligature, boron losses are reduced by 5-7%. At that, uniform distribution of boron micro-additives in the volume of treated liquid metal is provided. Acknowledgment: This work was supported by Shota Rustaveli Georgian National Science Foundation of Georgia (SRGNSFG) under the GENIE project (grant number № CARYS-19-802).

Keywords: self-propagating high-temperature synthesis, cast iron, industrial waste, ductile iron, structure formation

Procedia PDF Downloads 123
2753 Determinants of Service Quality on Thai Passengers’ Repeated Purchase of Domestic Flight Service with Thai Airways International

Authors: Nattapong Techarattanased

Abstract:

This research paper aimed to identify determinants of airline service quality on passengers’ repeated purchase of service. The population of this study was Thai passengers flying domestic flights with Thai Airways, making a total of 300 samples. These 300 samples participated in this research by answering a collection of questions by means of a questionnaire. An analysis of means score and multiple regression revealed that perceived service quality for tangible elements, reliability, responsiveness, assurance and empathy had determined repeated purchase of flight service of the passengers at a high level. Moreover, reliability and responsiveness factors could predict the passengers’ repeated purchase of flight service at the percentage of 30.6. The findings gave a signal that Thai Airways may consider a development of route network and fleet strategy as well as an establishment of aircraft and seat qualification to meet passengers’ needs and requirements. Passengers’ level of satisfaction could also be maximized by offering service value through various kinds of special deals and programs, whereas value- added pricing strategy should be considered in order to differentiate from and beat other leading airline competitors.

Keywords: repeated purchase, service quality, domestic flight, Thai Airways

Procedia PDF Downloads 283
2752 Optimized Electron Diffraction Detection and Data Acquisition in Diffraction Tomography: A Complete Solution by Gatan

Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

Abstract:

Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

Procedia PDF Downloads 107
2751 Humeral Head and Scapula Detection in Proton Density Weighted Magnetic Resonance Images Using YOLOv8

Authors: Aysun Sezer

Abstract:

Magnetic Resonance Imaging (MRI) is one of the advanced diagnostic tools for evaluating shoulder pathologies. Proton Density (PD)-weighted MRI sequences prove highly effective in detecting edema. However, they are deficient in the anatomical identification of bones due to a trauma-induced decrease in signal-to-noise ratio and blur in the traumatized cortices. Computer-based diagnostic systems require precise segmentation, identification, and localization of anatomical regions in medical imagery. Deep learning-based object detection algorithms exhibit remarkable proficiency in real-time object identification and localization. In this study, the YOLOv8 model was employed to detect humeral head and scapular regions in 665 axial PD-weighted MR images. The YOLOv8 configuration achieved an overall success rate of 99.60% and 89.90% for detecting the humeral head and scapula, respectively, with an intersection over union (IoU) of 0.5. Our findings indicate a significant promise of employing YOLOv8-based detection for the humerus and scapula regions, particularly in the context of PD-weighted images affected by both noise and intensity inhomogeneity.

Keywords: YOLOv8, object detection, humerus, scapula, IRM

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2750 A Review on Big Data Movement with Different Approaches

Authors: Nay Myo Sandar

Abstract:

With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

Procedia PDF Downloads 86
2749 Reduction of Speckle Noise in Echocardiographic Images: A Survey

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

Abstract:

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

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

Procedia PDF Downloads 530
2748 Digital Recording System Identification Based on Audio File

Authors: Michel Kulhandjian, Dimitris A. Pados

Abstract:

The objective of this work is to develop a theoretical framework for reliable digital recording system identification from digital audio files alone, for forensic purposes. A digital recording system consists of a microphone and a digital sound processing card. We view the cascade as a system of unknown transfer function. We expect same manufacturer and model microphone-sound card combinations to have very similar/near identical transfer functions, bar any unique manufacturing defect. Input voice (or other) signals are modeled as non-stationary processes. The technical problem under consideration becomes blind deconvolution with non-stationary inputs as it manifests itself in the specific application of digital audio recording equipment classification.

Keywords: blind system identification, audio fingerprinting, blind deconvolution, blind dereverberation

Procedia PDF Downloads 304
2747 Effects of Oxytocin on Neural Response to Facial Emotion Recognition in Schizophrenia

Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

Abstract:

Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

Procedia PDF Downloads 220
2746 Optimized Approach for Secure Data Sharing in Distributed Database

Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

Abstract:

In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation

Procedia PDF Downloads 333
2745 Evaluation of Long Term Evolution Mobile Signal Propagation Models and Vegetation Attenuation in the Livestock Department at Escuela Superior Politécnica de Chimborazo

Authors: Cinthia Campoverde, Mateo Benavidez, Victor Arias, Milton Torres

Abstract:

This article evaluates and compares three propagation models: the Okumura-Hata model, the Ericsson 9999 model, and the SUI model. The inclusion of vegetation attenuation in the area is also taken into account. These mathematical models aim to predict the power loss between a transmitting antenna (Tx) and a receiving antenna (Rx). The study was conducted in the open areas of the Livestock Department at the Escuela Superior Politécnica de Chimborazo (ESPOCH) University, located in the city of Riobamba, Ecuador. The necessary parameters for each model were calculated, considering LTE technology. The transmitting antenna belongs to the mobile phone company ”TUENTI” in Band 2, operating at a frequency of 1940 MHz. The reception power data in the area were empirically measured using the ”Network Cell Info” application. A total of 170 samples were collected, distributed across 19 radius, forming concentric circles around the transmitting antenna. The results demonstrate that the Okumura Hata urban model provides the best fit to the measured data.

Keywords: propagation models, reception power, LTE, power losses, correction factor

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2744 Agrowastes to Edible Hydrogels through Bio Nanotechnology Interventions: Bioactive from Mandarin Peels

Authors: Niharika Kaushal, Minni Singh

Abstract:

Citrus fruits contain an abundance of phytochemicals that can promote health. A substantial amount of agrowaste is produced from the juice processing industries, primarily peels and seeds. This leftover agrowaste is a reservoir of nutraceuticals, particularly bioflavonoids which render it antioxidant and potentially anticancerous. It is, therefore, favorable to utilize this biomass and contribute towards sustainability in a manner that value-added products may be derived from them, nutraceuticals, in this study. However, the pre-systemic metabolism of flavonoids in the gastric phase limits the effectiveness of these bioflavonoids derived from mandarin biomass. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was explored for its flavonoid profile. This work entails supercritical fluid extraction and identification of bioflavonoids from mandarin biomass. Furthermore, to overcome the limitations of these flavonoids in the gastrointestinal tract, a double-layered vehicular mechanism comprising the fabrication of nanoconjugates and edible hydrogels was adopted. Total flavonoids in the mandarin peel extract were estimated by the aluminum chloride complexation method and were found to be 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the abundance of polymethoxyflavones (PMFs), nobiletin and tangeretin as the major flavonoids in the extract, followed by hesperetin and naringenin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which showed an IC50 of 0.55μg/ml. Nanoconjugates were fabricated via the solvent evaporation method, which was further impregnated into hydrogels. Additionally, the release characteristics of nanoconjugate-laden hydrogels in a simulated gastrointestinal environment were studied. The PLGA-PMFs nanoconjugates exhibited a particle size between 200-250nm having a smooth and spherical shape as revealed by FE-SEM. The impregnated alginate hydrogels offered a dense network that ensured the holding of PLGA-PMF nanoconjugates, as confirmed by Cryo-SEM images. Rheological studies revealed the shear-thinning behavior of hydrogels and their high resistance to deformation. Gastrointestinal studies showed a negligible 4.0% release of flavonoids in the gastric phase, followed by a sustained release over the next hours in the intestinal environment. Therefore, based on the enormous potential of recovering nutraceuticals from agro-processing wastes, further augmented by nanotechnological interventions for enhancing the bioefficacy of these compounds, lays the foundation for exploring the path towards the development of value-added products, thereby contributing towards the sustainable use of agrowaste.

Keywords: agrowaste, gastrointestinal, hydrogel, nutraceuticals

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2743 Unsupervised Neural Architecture for Saliency Detection

Authors: Natalia Efremova, Sergey Tarasenko

Abstract:

We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

Procedia PDF Downloads 348
2742 Neuron-Based Control Mechanisms for a Robotic Arm and Hand

Authors: Nishant Singh, Christian Huyck, Vaibhav Gandhi, Alexander Jones

Abstract:

A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors, and outputs to effectors. The robot performs a simple pick-and-place task. This work is a proof of concept study for a longer term approach. It is hoped that further work will lead to more effective and flexible robots. As another benefit, it is hoped that further work will also lead to a better understanding of human and other animal neural processing, particularly for physical motion. This is a multidisciplinary approach combining cognitive neuroscience, robotics, and psychology.

Keywords: cell assembly, force sensitive resistor, robot, spiking neuron

Procedia PDF Downloads 349
2741 Language Activation Theory: Unlocking Bilingual Language Processing

Authors: Leorisyl D. Siarot

Abstract:

It is conventional to see and hear Filipinos, in general, speak two or more languages. This phenomenon brings us to a closer look on how our minds process the input and produce an output with a specific chosen language. This study aimed to generate a theoretical model which explained the interaction of the first and the second languages in the human mind. After a careful analysis of the gathered data, a theoretical prototype called Language Activation Model was generated. For every string, there are three specialized banks: lexico-semantics, morphono-syntax, and pragmatics. These banks are interrelated to other banks of other language strings. As the bilingual learns more languages, a new string is replicated and is filled up with the information of the new language learned. The principles of the first and second languages' interaction are drawn; these are expressed in laws, namely: law of dominance, law of availability, law of usuality and law of preference. Furthermore, difficulties encountered in the learning of second languages were also determined.

Keywords: bilingualism, psycholinguistics, second language learning, languages

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2740 Accuracy Improvement of Traffic Participant Classification Using Millimeter-Wave Radar by Leveraging Simulator Based on Domain Adaptation

Authors: Tokihiko Akita, Seiichi Mita

Abstract:

A millimeter-wave radar is the most robust against adverse environments, making it an essential environment recognition sensor for automated driving. However, the reflection signal is sparse and unstable, so it is difficult to obtain the high recognition accuracy. Deep learning provides high accuracy even for them in recognition, but requires large scale datasets with ground truth. Specially, it takes a lot of cost to annotate for a millimeter-wave radar. For the solution, utilizing a simulator that can generate an annotated huge dataset is effective. Simulation of the radar is more difficult to match with real world data than camera image, and recognition by deep learning with higher-order features using the simulator causes further deviation. We have challenged to improve the accuracy of traffic participant classification by fusing simulator and real-world data with domain adaptation technique. Experimental results with the domain adaptation network created by us show that classification accuracy can be improved even with a few real-world data.

Keywords: millimeter-wave radar, object classification, deep learning, simulation, domain adaptation

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2739 The Internet of Things Ecosystem: Survey of the Current Landscape, Identity Relationship Management, Multifactor Authentication Mechanisms, and Underlying Protocols

Authors: Nazli W. Hardy

Abstract:

A critical component in the Internet of Things (IoT) ecosystem is the need for secure and appropriate transmission, processing, and storage of the data. Our current forms of authentication, and identity and access management do not suffice because they are not designed to service cohesive, integrated, interconnected devices, and service applications. The seemingly endless opportunities of IoT are in fact circumscribed on multiple levels by concerns such as trust, privacy, security, loss of control, and related issues. This paper considers multi-factor authentication (MFA) mechanisms and cohesive identity relationship management (IRM) standards. It also surveys messaging protocols that are appropriate for the IoT ecosystem.

Keywords: identity relation management, multifactor authentication, protocols, survey of internet of things ecosystem

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2738 Programmed Speech to Text Summarization Using Graph-Based Algorithm

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

Abstract:

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

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

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2737 The Role of Estradiol-17β and Type IV Collagen on the Regulation and Expression Level Of C-Erbb2 RNA and Protein in SKOV-3 Ovarian Cancer Cell Line

Authors: Merry Meryam Martgrita, Marselina Irasonia Tan

Abstract:

One of several aggresive cancer is cancer that overexpress c-erbB2 receptor along with the expression of estrogen receptor. Components of extracellular matrix play an important role to increase cancer cells proliferation, migration and invasion. Both components can affect cancer development by regulating the signal transduction pathways in cancer cells. In recent research, SKOV-3 ovarian cancer cell line, that overexpress c-erbB2 receptor was cultured on type IV collagen and treated with estradiol-17β, to reveal the role of both components on RNA and protein level of c-erbB2 receptor. In this research we found a modulation phenomena of increasing and decreasing of c-erbB2 RNA level and a stabilisation phenomena of c-erbB2 protein expression due to estradiol-17β and type IV collagen. It seemed that estradiol-17β has an important role to increase c-erbB2 transcription and the stability of c-erbB2 protein expression. Type IV collagen has an opposite role. It blocked c-erbB2 transcription when it bound to integrin receptor in SKOV-3 cells.

Keywords: c-erbB2, estradiol-17β, SKOV-3, type IV collagen

Procedia PDF Downloads 284
2736 The Challenges of Business Incubations: A Case of Malaysian Incubators

Authors: Logaiswari Indiran, Zainab Khalifah, Kamariah Ismail

Abstract:

Business incubators have now been recognized as effective tools in providing business assistance to start-up firms. In both developed and developing countries, the number of incubators is growing tremendously. As the birth rate of incubators increases, so do its challenges. Malaysia, as one of the developing countries in the Asian continent, has also established a number of business incubators to breed and foster the growth and survival of start-up firms. Thus, this study discusses the incubation model applied in Malaysia and the challenges faced by these incubators using secondary data including policies, previous literature, and reports related to Malaysian incubators. The findings of this study call the government to rethink the key role of incubator managers and staffs, internal structure of the incubator concept and process, intellectual properties management, strategic alliances with universities-industries and funding supports in enhancing the support provided by the business incubators in Malaysia. The key challenges highlighted in this study signal important policy lessons for other developing countries that aim to create and map an effective business incubator ecosystem.

Keywords: business incubators, incubation challenges, funding support, incubator managers, internal structure, start-up firms

Procedia PDF Downloads 275
2735 Acoustic Room Impulse Response Computation with Image Sources and Frequency Dependent Boundary Reflection Coefficients

Authors: Pratik Gandhi, Kavitha Chandra, Charles Thompson

Abstract:

A computational model of the acoustic room impulse response between transmitters and receivers located in an enclosed cavity under the influence of frequency-dependent reflection coefficients of the walls is presented. The characteristic features of the impulse responses that differentiate these results from frequency-independent reflecting surfaces are discussed. The image-source model is derived from the first principle solution to Green's function of the acoustic wave equation. The post-processing of the computed impulse response with a band-pass filter to better represents the response of a loud-speaker is demonstrated.

Keywords: acoustic room impulse response, frequency dependent reflection coefficients, Green's function, image model

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2734 Optimizing Power in Sequential Circuits by Reducing Leakage Current Using Enhanced Multi Threshold CMOS

Authors: Patikineti Sreenivasulu, K. srinivasa Rao, A. Vinaya Babu

Abstract:

The demand for portability, performance and high functional integration density of digital devices leads to the scaling of complementary metal oxide semiconductor (CMOS) devices inevitable. The increase in power consumption, coupled with the increasing demand for portable/hand-held electronics, has made power consumption a dominant concern in the design of VLSI circuits today. MTCMOS technology provides low leakage and high performance operation by utilizing high speed, low Vt (LVT) transistors for logic cells and low leakage, high Vt (HVT) devices as sleep transistors. Sleep transistors disconnect logic cells from the supply and/or ground to reduce the leakage in the sleep mode. In this technology, energy consumption while doing the mode transition and minimum time required to turn ON the circuit upon receiving the wake up signal are issues to be considered because these can adversely impact the performance of VLSI circuit. In this paper we are introducing an enhancing method of MTCMOS technology to optimize the power in MTCMOS sequential circuits.

Keywords: power consumption, ultra-low power, leakage, sub threshold, MTCMOS

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2733 Facial Recognition of University Entrance Exam Candidates using FaceMatch Software in Iran

Authors: Mahshid Arabi

Abstract:

In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

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2732 Assessing the Adoption of Health Information Systems in a Resource-Constrained Country: A Case of Uganda

Authors: Lubowa Samuel

Abstract:

Health information systems, often known as HIS, are critical components of the healthcare system to improve health policies and promote global health development. In a broader sense, HIS as a system integrates data collecting, processing, reporting, and making use of various types of data to improve healthcare efficacy and efficiency through better management at all levels of healthcare delivery. The aim of this study is to assess the adoption of health information systems (HIS) in a resource-constrained country drawing from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. The results indicate that the user's perception of the technology and the poor information technology infrastructures contribute a lot to the low adoption of HIS in resource-constrained countries.

Keywords: health information systems, resource-constrained countries, health information systems

Procedia PDF Downloads 121
2731 Sperm Flagellum Center-Line Tracing in 4D Stacks Using an Iterative Minimal Path Method

Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

Abstract:

Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

Procedia PDF Downloads 284
2730 Construction of Green Aggregates from Waste Processing

Authors: Fahad K. Alqahtani

Abstract:

Nowadays construction industry is developing means to incorporate waste products in concrete to ensure sustainability. To meet the need of construction industry, a synthetic aggregate was developed using optimized technique called compression moulding press technique. The manufactured aggregate comprises mixture of plastic, waste which acts as binder, together with by-product waste which acts as fillers. The physical properties and microstructures of the inert materials and the manufactured aggregate were examined and compared with the conventional available aggregates. The outcomes suggest that the developed aggregate has potential to be used as substitution of conventional aggregate due to its less weight and water absorption. The microstructure analysis confirmed the efficiency of the manufacturing process where the final product has the same mixture of binder and filler.

Keywords: fly ash, plastic waste, quarry fine, red sand, synthetic aggregate

Procedia PDF Downloads 230
2729 Augmented Reality as Enhancer of the Lean Philosophy: An Exploratory Study

Authors: P. Gil, F. Charrua-Santos, A. A. Baptista, S. Azevedo, A. Espirito-Santo, J. Páscoa

Abstract:

Lean manufacturing is a philosophy of industrial management that aims to identify and eliminate any waste that exists in the companies. The augmented reality is a new technology that stills being developed in terms of software and hardware. This technology consists of an image capture device, a device for data processing and an image visualization equipment to visualize collected and processed images. It is characterized by being a technology that merges the reality with the virtual environment, so there is an instantaneous interaction between the two environments. The present work intends to demonstrate that the use of the augmented reality will contribute to improve some tools and methods used in Lean manufacturing philosophy. Through several examples of application in industry it will be demonstrated that the technological impact of the augmented reality on the Lean Manufacturing philosophy contribute to added value improvements.

Keywords: lean manufacturing, augmented reality, case studies, value

Procedia PDF Downloads 624