Search results for: array signal processing
3027 Analysis of Automotive Sensor for Engine Knock System
Authors: Miroslav Gutten, Jozef Jurcik, Daniel Korenciak, Milan Sebok, Matej Kuceraa
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This paper deals with the phenomenon of the undesirable detonation combustion in internal combustion engines. A control unit of the engine monitors these detonations using piezoelectric knock sensors. With the control of these sensors the detonations can be objectively measured just outside the car. If this component provides small amplitude of the output voltage it could happen that there would have been in the areas of the engine ignition combustion. The paper deals with the design of a simple device for the detection of this disorder. A construction of the testing device for the knock sensor suitable for diagnostics of knock combustion in internal combustion engines will be presented. The output signal of presented sensor will be described by Bessel functions. Using the first voltage extremes on the characteristics it is possible to create a reference for the evaluation of the polynomial residue. It should be taken into account that the velocity of sound in air is 330 m/s. This sound impinges on the walls of the combustion chamber and is detected by the sensor. The resonant frequency of the clicking of the motor is usually in the range from 5 kHz to 15 kHz. The sensor worked in the field to 37 kHz, which shall be taken into account on an own sensor resonance.Keywords: diagnostics, knock sensor, measurement, testing device
Procedia PDF Downloads 4473026 Objective Evaluation on Medical Image Compression Using Wavelet Transformation
Authors: Amhimmid Mohammed Saffour, Mustafa Mohamed Abdullah
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The use of computers for handling image data in the healthcare is growing. However, the amount of data produced by modern image generating techniques is vast. This data might be a problem from a storage point of view or when the data is sent over a network. This paper using wavelet transform technique for medical images compression. MATLAB program, are designed to evaluate medical images storage and transmission time problem at Sebha Medical Center Libya. In this paper, three different Computed Tomography images which are abdomen, brain and chest have been selected and compressed using wavelet transform. Objective evaluation has been performed to measure the quality of the compressed images. For this evaluation, the results show that the Peak Signal to Noise Ratio (PSNR) which indicates the quality of the compressed image is ranging from (25.89db to 34.35db for abdomen images, 23.26db to 33.3db for brain images and 25.5db to 36.11db for chest images. These values shows that the compression ratio is nearly to 30:1 is acceptable.Keywords: medical image, Matlab, image compression, wavelet's, objective evaluation
Procedia PDF Downloads 2853025 Impact of Hard Limited Clipping Crest Factor Reduction Technique on Bit Error Rate in OFDM Based Systems
Authors: Theodore Grosch, Felipe Koji Godinho Hoshino
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In wireless communications, 3GPP LTE is one of the solutions to meet the greater transmission data rate demand. One issue inherent to this technology is the PAPR (Peak-to-Average Power Ratio) of OFDM (Orthogonal Frequency Division Multiplexing) modulation. This high PAPR affects the efficiency of power amplifiers. One approach to mitigate this effect is the Crest Factor Reduction (CFR) technique. In this work, we simulate the impact of Hard Limited Clipping Crest Factor Reduction technique on BER (Bit Error Rate) in OFDM based Systems. In general, the results showed that CFR has more effects on higher digital modulation schemes, as expected. More importantly, we show the worst-case degradation due to CFR on QPSK, 16QAM, and 64QAM signals in a linear system. For example, hard clipping of 9 dB results in a 2 dB increase in signal to noise energy at a 1% BER for 64-QAM modulation.Keywords: bit error rate, crest factor reduction, OFDM, physical layer simulation
Procedia PDF Downloads 3663024 [Keynote Speech]: Curiosity, Innovation and Technological Advancements Shaping the Future of Science, Technology, Engineering and Mathematics Education
Authors: Ana Hol
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We live in a constantly changing environment where technology has become an integral component of our day to day life. We rely heavily on mobile devices, we search for data via web, we utilise smart home sensors to create the most suited ambiences and we utilise applications to shop, research, communicate and share data. Heavy reliance on technology therefore is creating new connections between STEM (Science, Technology, Engineering and Mathematics) fields which in turn rises a question of what the STEM education of the future should be like? This study was based on the reviews of the six Australian Information Systems students who undertook an international study tour to India where they were given an opportunity to network, communicate and meet local students, staff and business representatives and from them learn about the local business implementations, local customs and regulations. Research identifies that if we are to continue to implement and utilise electronic devices on the global scale, such as for example implement smart cars that can smoothly cross borders, we will need the workforce that will have the knowledge about the cars themselves, their parts, roads and transport networks, road rules, road sensors, road monitoring technologies, graphical user interfaces, movement detection systems as well as day to day operations, legal rules and regulations of each region and country, insurance policies, policing and processes so that the wide array of sensors can be controlled across country’s borders. In conclusion, it can be noted that allowing students to learn about the local conditions, roads, operations, business processes, customs and values in different countries is giving students a cutting edge advantage as such knowledge cannot be transferred via electronic sources alone. However once understanding of each problem or project is established, multidisciplinary innovative STEM projects can be smoothly conducted.Keywords: STEM, curiosity, innovation, advancements
Procedia PDF Downloads 1993023 Dynamic Model for Forecasting Rainfall Induced Landslides
Authors: R. Premasiri, W. A. H. A. Abeygunasekara, S. M. Hewavidana, T. Jananthan, R. M. S. Madawala, K. Vaheeshan
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Forecasting the potential for disastrous events such as landslides has become one of the major necessities in the current world. Most of all, the landslides occurred in Sri Lanka are found to be triggered mostly by intense rainfall events. The study area is the landslide near Gerandiella waterfall which is located by the 41st kilometer post on Nuwara Eliya-Gampala main road in Kotmale Division in Sri Lanka. The landslide endangers the entire Kotmale town beneath the slope. Geographic Information System (GIS) platform is very much useful when it comes to the need of emulating the real-world processes. The models are used in a wide array of applications ranging from simple evaluations to the levels of forecast future events. This project investigates the possibility of developing a dynamic model to map the spatial distribution of the slope stability. The model incorporates several theoretical models including the infinite slope model, Green Ampt infiltration model and Perched ground water flow model. A series of rainfall values can be fed to the model as the main input to simulate the dynamics of slope stability. Hydrological model developed using GIS is used to quantify the perched water table height, which is one of the most critical parameters affecting the slope stability. Infinite slope stability model is used to quantify the degree of slope stability in terms of factor of safety. DEM was built with the use of digitized contour data. Stratigraphy was modeled in Surfer using borehole data and resistivity images. Data available from rainfall gauges and piezometers were used in calibrating the model. During the calibration, the parameters were adjusted until a good fit between the simulated ground water levels and the piezometer readings was obtained. This model equipped with the predicted rainfall values can be used to forecast of the slope dynamics of the area of interest. Therefore it can be investigated the slope stability of rainfall induced landslides by adjusting temporal dimensions.Keywords: factor of safety, geographic information system, hydrological model, slope stability
Procedia PDF Downloads 4233022 Increased Circularity in Metals Production Using the Ausmelt TSL Process
Authors: Jacob Wood, David Wilson, Stephen Hughes
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The Ausmelt Top Submerged Lance (TSL) Process has been widely applied for the processing of both primary and secondary copper, nickel, lead, tin, and zinc-bearing feed materials. Continual development and evolution of the technology over more than 30 years has resulted in a more intense smelting process with higher energy efficiency, improved metal recoveries, lower operating costs, and reduced fossil fuel consumption. This paper covers a number of recent advances to the technology, highlighting their positive impacts on smelter operating costs, environmental performance, and contribution towards increased circularity in metals production.Keywords: ausmelt TSL, smelting, circular economy, energy efficiency
Procedia PDF Downloads 2443021 Seismic Refraction and Resistivity Survey of Ini Local Government Area, South-South Nigeria: Assessing Structural Setting and Groundwater Potential
Authors: Mfoniso Udofia Aka
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A seismic refraction and resistivity survey was conducted in Ini Local Government Area, South-South Nigeria, to evaluate the structural setting and groundwater potential. The study involved 20 Vertical Electrical Soundings (VES) using an ABEM Terrameter with a Schlumberger array and a 400-meter electrode spread, analyzed with WinResist software. Concurrently, 20 seismic refraction surveys were performed with a Geometric ES 3000 12-Channel seismograph, employing a 60-meter slant interval. The survey identified three distinct geological layers: top, middle, and lower. Seismic velocities (Vp) ranged from 209 to 500 m/s in the top layer, 221 to 1210 m/s in the middle layer, and 510 to 1700 m/s in the lower layer. Secondary seismic velocities (Vs) ranged from 170 to 410 m/s in the topsoil, 205 to 880 m/s in the middle layer, and 480 to 1120 m/s in the lower layer. Poisson’s ratios varied from -0.029 to -7.709 for the top layer, -0.027 to -6.963 for the middle layer, and -0.144 to -6.324 for the lower layer. The depths of these layers were approximately 1.0 to 3.0 meters for the top layer, 4.0 to 12.0 meters for the middle layer, and 8.0 to 14.5 meters for the lower layer. The topsoil consists of a surficial layer overlaid by reddish/clayey laterite and fine to medium coarse-grained sandy material, identified as the auriferous zone. Resistivity values were 1300 to 3215 Ωm for the topsoil, 720 to 1600 Ωm for the laterite, and 100 to 1350 Ωm for the sandy zone. Aquifer thickness and depth varied, with shallow aquifers ranging from 4.5 to 15.2 meters, medium-depth aquifers from 15.5 to 70.0 meters, and deep aquifers from 4.0 to 70.0 meters. Locations 1, 15, and 13 exhibited favorable water potential with shallow formations, while locations 5, 11, 9, and 14 showed less potential due to the lack of fractured or weathered zones. The auriferous sandy zone indicated significant potential for industrial development. Future surveys should consider using a more robust energy source to enhance data acquisition and accuracy.Keywords: hydrogeological, aquifer, seismic section geo-electric section, stratigraphy
Procedia PDF Downloads 293020 SQL Generator Based on MVC Pattern
Authors: Chanchai Supaartagorn
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Structured Query Language (SQL) is the standard de facto language to access and manipulate data in a relational database. Although SQL is a language that is simple and powerful, most novice users will have trouble with SQL syntax. Thus, we are presenting SQL generator tool which is capable of translating actions and displaying SQL commands and data sets simultaneously. The tool was developed based on Model-View-Controller (MVC) pattern. The MVC pattern is a widely used software design pattern that enforces the separation between the input, processing, and output of an application. Developers take full advantage of it to reduce the complexity in architectural design and to increase flexibility and reuse of code. In addition, we use White-Box testing for the code verification in the Model module.Keywords: MVC, relational database, SQL, White-Box testing
Procedia PDF Downloads 4223019 Human Thinking Explained with Basic Drives
Authors: Peter Pfeifer, Julian Pfeifer, Niko Pfeifer
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Information processing is the focus of brain and cognition research. This work has a different perspective; it starts with behaviors. The detailed analysis of behaviors leads to the discovery that a significant proportion of them are based on only five basic drives. These basic drives are combinable, and the combinations result in the diversity of human behavior and thinking. The key elements are drive memories. They collect memories of drive-related situations and feelings. They contain variations of basic drives in numerous areas of life and build combinations with different meanings depending on the area. Human thinking could be explained with variations on these nested combinations of basic drives.Keywords: cognition, psycholinguistics, psychology, psychophysiology of cognition
Procedia PDF Downloads 1613018 A Constructivist and Strategic Approach to School Learning: A Study in a Tunisian Primary School
Authors: Slah Eddine Ben Fadhel
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Despite the development of new pedagogic methods, current teaching practices put more emphasis on the learning products than on the processes learners deploy. In school syllabi, for instance, very little time is devoted to both the explanation and analysis of strategies aimed at resolving problems by means of targeting students’ metacognitive procedures. Within a cognitive framework, teaching/learning contexts are conceived of in terms of cognitive, metacognitive and affective activities intended for the treatment of information. During these activities, learners come to develop an array of knowledge and strategies which can be subsumed within an active and constructive process. Through the investigation of strategies and metacognition concepts, the purpose is to reflect upon the modalities at the heart of the learning process and to demonstrate, similarly, the inherent significance of a cognitive approach to learning. The scope of this paper is predicated on a study where the population is a group of 76 primary school pupils who experienced difficulty with learning French. The population was divided into two groups: the first group was submitted during three months to a strategy-based training to learn French. All through this phase, the teachers centred class activities round making learners aware of the strategies the latter deployed and geared them towards appraising the steps these learners had themselves taken by means of a variety of tools, most prominent among which is the logbook. The second group was submitted to the usual learning context with no recourse whatsoever to any strategy-oriented tasks. The results of both groups point out the improvement of linguistic competences in the French language in the case of those pupils who were trained by means of strategic procedures. Furthermore, this improvement was noted in relation with the native language (Arabic), a fact that tends to highlight the importance of the interdisciplinary investigation of (meta-)cognitive strategies. These results show that strategic learning promotes in pupils the development of a better awareness of their own processes, which contributes to improving their general linguistic competences.Keywords: constructive approach, cognitive strategies, metacognition, learning
Procedia PDF Downloads 2113017 High Secure Data Hiding Using Cropping Image and Least Significant Bit Steganography
Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway
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This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.Keywords: steganography, stego, LSB, crop
Procedia PDF Downloads 2693016 The Immunology Evolutionary Relationship between Signal Transducer and Activator of Transcription Genes from Three Different Shrimp Species in Response to White Spot Syndrome Virus Infection
Authors: T. C. C. Soo, S. Bhassu
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Unlike the common presence of both innate and adaptive immunity in vertebrates, crustaceans, in particular, shrimps, have been discovered to possess only innate immunity. This further emphasizes the importance of innate immunity within shrimps in pathogenic resistance. Under the study of pathogenic immune challenge, different shrimp species actually exhibit varying degrees of immune resistance towards the same pathogen. Furthermore, even within the same shrimp species, different batches of challenged shrimps can have different strengths of immune defence. Several important pathways are activated within shrimps during pathogenic infection. One of them is JAK-STAT pathway that is activated during bacterial, viral and fungal infections by which STAT(Signal Transducer and Activator of Transcription) gene is the core element of the pathway. Based on theory of Central Dogma, the genomic information is transmitted in the order of DNA, RNA and protein. This study is focused in uncovering the important evolutionary patterns present within the DNA (non-coding region) and RNA (coding region). The three shrimp species involved are Macrobrachium rosenbergii, Penaeus monodon and Litopenaeus vannamei which all possess commercial significance. The shrimp species were challenged with a famous penaeid shrimp virus called white spot syndrome virus (WSSV) which can cause serious lethality. Tissue samples were collected during time intervals of 0h, 3h, 6h, 12h, 24h, 36h and 48h. The DNA and RNA samples were then extracted using conventional kits from the hepatopancreas tissue samples. PCR technique together with designed STAT gene conserved primers were utilized for identification of the STAT coding sequences using RNA-converted cDNA samples and subsequent characterization using various bioinformatics approaches including Ramachandran plot, ProtParam and SWISS-MODEL. The varying levels of immune STAT gene activation for the three shrimp species during WSSV infection were confirmed using qRT-PCR technique. For one sample, three biological replicates with three technical replicates each were used for qRT-PCR. On the other hand, DNA samples were important for uncovering the structural variations within the genomic region of STAT gene which would greatly assist in understanding the STAT protein functional variations. The partially-overlapping primers technique was used for the genomic region sequencing. The evolutionary inferences and event predictions were then conducted through the Bayesian Inference method using all the acquired coding and non-coding sequences. This was supplemented by the construction of conventional phylogenetic trees using Maximum likelihood method. The results showed that adaptive evolution caused STAT gene sequence mutations between different shrimp species which led to evolutionary divergence event. Subsequently, the divergent sites were correlated to the differing expressions of STAT gene. Ultimately, this study assists in knowing the shrimp species innate immune variability and selection of disease resistant shrimps for breeding purpose. The deeper understanding of STAT gene evolution from the perspective of both purifying and adaptive approaches not only can provide better immunological insight among shrimp species, but also can be used as a good reference for immunological studies in humans or other model organisms.Keywords: gene evolution, JAK-STAT pathway, immunology, STAT gene
Procedia PDF Downloads 1503015 Bit Error Rate Performance of MIMO Systems for Wireless Communications
Authors: E. Ghayoula, M. Haj Taieb, A. Bouallegue, J. Y. Chouinard, R. Ghayoula
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This paper evaluates the bit error rate (BER) performance of MIMO systems for wireless communication. MIMO uses multiple transmitting antennas, multiple receiving antennas and the space-time block codes to provide diversity. MIMO transmits signal encoded by space-time block (STBC) encoder through different transmitting antennas. These signals arrive at the receiver at slightly different times. Spatially separated multiple receiving antennas are employed to provide diversity reception to combat the effect of fading in the channel. This paper presents a detailed study of diversity coding for MIMO systems. STBC techniques are implemented and simulation results in terms of the BER performance with varying number of MIMO transmitting and receiving antennas are presented. Our results show how increasing the number of both transmit and receive antenna improves system performance and reduces the bit error rate.Keywords: MIMO systems, diversity, BER, MRRC, SIMO, MISO, STBC, alamouti, SNR
Procedia PDF Downloads 4903014 Automatic Classification of Periodic Heart Sounds Using Convolutional Neural Network
Authors: Jia Xin Low, Keng Wah Choo
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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification
Procedia PDF Downloads 3483013 Covid-19 Lockdown Experience of Elderly Female as Reflected in Their Artwork
Authors: Liat Shamri-Zeevi, Neta Ram-Vlasov
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Today the world as a whole is attempting to cope with the COVID-19, which has affected all facets of personal and social life from country-wide confinement to maintaining social distance and taking protective measures to maintain hygiene. One of the populations faced with the most severe restrictions is seniors. Various studies have shown that creativity plays a crucial role in dealing with crisis events. Painting - regardless of media - allows for emotional and cognitive processing of these situations, and enables the expression of experiences in a tangible creative way that conveys and endows meaning to the artwork. The current study was conducted in Israel immediately after a 6-week lockdown. It was designed to specifically examine the impact of the COVID-19 pandemic on the quality of life of elderly women as reflected in their artworks. The sample was composed of 21 Israeli women aged 60-90, in good mental health (without diagnosed dementia or Alzheimer's), all of whom were Hebrew-speaking, and retired with an extended family, who indicated that they painted and had engaged in artwork on an ongoing basis throughout the lockdown (from March 12 to May 30, 2020). The participants' artworks were collected, and a semi-structured in-depth interview was conducted that lasted one to two hours. The participants were asked about their feelings during the pandemic and the artworks they produced during this time, and completed a questionnaire on well-being and mental health. The initial analysis of the interviews and artworks revealed themes related to the specific role of each piece of artwork. The first theme included notions that the artwork was an activity and a framework for doing, which supported positive emotions, and provided a sense of vitality during the closure. Most of the participants painted images of nature and growth which were ascribed concrete and symbolic meaning. The second theme was that the artwork enabled the processing of difficult and /or conflicting emotions related to the situation, including anxiety about death and loneliness that were symbolically expressed in the artworks, such as images of the Corona virus and the respiratory machines. The third theme suggested that the time and space prompted by the lockdown gave the participants time for a gathering together of the self, and freed up time for creative activities. Many participants stated that they painted more and more frequently during the Corona lockdown. At the conference, additional themes and findings will be presented.Keywords: Corona virus, artwork, quality of life of elderly
Procedia PDF Downloads 1433012 Non-Signaling Chemokine Receptor CCRL1 and Its Active Counterpart CCR7 in Prostate Cancer
Authors: Yiding Qu, Svetlana V. Komarova
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Chemokines acting through their cognate chemokine receptors guide the directional migration of the cell along the chemokine gradient. Several chemokine receptors were recently identified as non-signaling (decoy), based on their ability to bind the chemokine but produce no measurable signal in the cell. The function of these decoy receptors is not well understood. We examined the expression of a decoy receptor CCRL1 and a signaling receptor that binds to the same ligands, CCR7, in prostate cancer using publically available microarray data (www.oncomine.org). The expression of both CCRL1 and CCR7 increased in an approximately half of prostate carcinoma samples and the majority of metastatic cancer samples compared to normal prostate. Moreover, the expression of CCRL1 positively correlated with the expression of CCR7. These data suggest that CCR7 and CCRL1 can be used as clinical markers for the early detection of transformation from carcinoma to metastatic cancer. In addition, these data support our hypothesis that the non-signaling chemokine receptors actively stimulate cell migration.Keywords: bioinformatics, cell migration, decoy receptor, meta-analysis, prostate cancer
Procedia PDF Downloads 4693011 Compressive Strength and Microstructure of Hybrid Alkaline Cements
Authors: Z. Abdollahnejad, P. Torgal, J. Barroso Aguiar
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Publications on the field of alkali-activated binders, state that this new material is likely to have high potential to become an alternative to Portland cement. Classical alkali-activated cements could be made more eco-efficient if the use of sodium silicate is avoided. Besides, most alkali-activated cements suffer from severe efflorescence originated by the fact that alkaline and/or soluble silicates that are added during processing cannot be totally consumed. This paper presents experimental results on hybrid alkaline cements. Compressive strength results and efflorescence’s observations show that the new mixes already analyzed are promising. SEM results show that no traditional porous ITZ was detected in these binders.Keywords: hybrid alkaline cements, compressive strength, efflorescence, SEM, ITZ
Procedia PDF Downloads 2933010 Surface-Enhanced Raman Detection in Chip-Based Chromatography via a Droplet Interface
Authors: Renata Gerhardt, Detlev Belder
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Raman spectroscopy has attracted much attention as a structurally descriptive and label-free detection method. It is particularly suited for chemical analysis given as it is non-destructive and molecules can be identified via the fingerprint region of the spectra. In this work possibilities are investigated how to integrate Raman spectroscopy as a detection method for chip-based chromatography, making use of a droplet interface. A demanding task in lab-on-a-chip applications is the specific and sensitive detection of low concentrated analytes in small volumes. Fluorescence detection is frequently utilized but restricted to fluorescent molecules. Furthermore, no structural information is provided. Another often applied technique is mass spectrometry which enables the identification of molecules based on their mass to charge ratio. Additionally, the obtained fragmentation pattern gives insight into the chemical structure. However, it is only applicable as an end-of-the-line detection because analytes are destroyed during measurements. In contrast to mass spectrometry, Raman spectroscopy can be applied on-chip and substances can be processed further downstream after detection. A major drawback of Raman spectroscopy is the inherent weakness of the Raman signal, which is due to the small cross-sections associated with the scattering process. Enhancement techniques, such as surface enhanced Raman spectroscopy (SERS), are employed to overcome the poor sensitivity even allowing detection on a single molecule level. In SERS measurements, Raman signal intensity is improved by several orders of magnitude if the analyte is in close proximity to nanostructured metal surfaces or nanoparticles. The main gain of lab-on-a-chip technology is the building block-like ability to seamlessly integrate different functionalities, such as synthesis, separation, derivatization and detection on a single device. We intend to utilize this powerful toolbox to realize Raman detection in chip-based chromatography. By interfacing on-chip separations with a droplet generator, the separated analytes are encapsulated into numerous discrete containers. These droplets can then be injected with a silver nanoparticle solution and investigated via Raman spectroscopy. Droplet microfluidics is a sub-discipline of microfluidics which instead of a continuous flow operates with the segmented flow. Segmented flow is created by merging two immiscible phases (usually an aqueous phase and oil) thus forming small discrete volumes of one phase in the carrier phase. The study surveys different chip designs to realize coupling of chip-based chromatography with droplet microfluidics. With regards to maintaining a sufficient flow rate for chromatographic separation and ensuring stable eluent flow over the column different flow rates of eluent and oil phase are tested. Furthermore, the detection of analytes in droplets with surface enhanced Raman spectroscopy is examined. The compartmentalization of separated compounds preserves the analytical resolution since the continuous phase restricts dispersion between the droplets. The droplets are ideal vessels for the insertion of silver colloids thus making use of the surface enhancement effect and improving the sensitivity of the detection. The long-term goal of this work is the first realization of coupling chip based chromatography with droplets microfluidics to employ surface enhanced Raman spectroscopy as means of detection.Keywords: chip-based separation, chip LC, droplets, Raman spectroscopy, SERS
Procedia PDF Downloads 2453009 A Geometric Based Hybrid Approach for Facial Feature Localization
Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik
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Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.Keywords: biometrics, face recognition, facial landmarks, image processing
Procedia PDF Downloads 4123008 Hull Detection from Handwritten Digit Image
Authors: Sriraman Kothuri, Komal Teja Mattupalli
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In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm
Procedia PDF Downloads 4003007 An Approach to Make an Adaptive Immunoassay to Detect an Unknown Disease
Authors: Josselyn Mata Calidonio, Arianna I. Maddox, Kimberly Hamad-Schifferli
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Rapid diagnostics are critical infectious disease tools that are designed to detect a known biomarker using antibodies specific to that biomarker. However, a way to detect unknown viruses has not yet been achieved in a paper test format. We describe here a route to make an adaptable paper immunoassay that can detect an unknown biomarker, demonstrating it on SARS-CoV-2 variants. The immunoassay repurposes cross-reactive antibodies raised against the alpha variant. Gold nanoparticles of two different colors conjugated to two different antibodies create a colorimetric signal, and machine learning of the resulting colorimetric pattern is used to train the assay to discriminate between variants of alpha and Omicron BA.5. By using principal component analysis, the colorimetric test patterns can pick up and discriminate an unknown that it has not encountered before, Omicron BA.1. The test has an accuracy of 100% and a potential calculated discriminatory power of 900. We show that it can be used adaptively and that it can be used to pick up emerging variants without the need to raise new antibodies.Keywords: adaptive immunoassay, detecting unknown viruses, gold nanoparticles, paper immunoassay, repurposing antibodies
Procedia PDF Downloads 1143006 Minimizing Total Completion Time in No-Wait Flowshops with Setup Times
Authors: Ali Allahverdi
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The m-machine no-wait flowshop scheduling problem is addressed in this paper. The objective is to minimize total completion time subject to the constraint that the makespan value is not greater than a certain value. Setup times are treated as separate from processing times. Several recent algorithms are adapted and proposed for the problem. An extensive computational analysis has been conducted for the evaluation of the proposed algorithms. The computational analysis indicates that the best proposed algorithm performs significantly better than the earlier existing best algorithm.Keywords: scheduling, no-wait flowshop, algorithm, setup times, total completion time, makespan
Procedia PDF Downloads 3403005 Comparative Analysis of Sigmoidal Feedforward Artificial Neural Networks and Radial Basis Function Networks Approach for Localization in Wireless Sensor Networks
Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy
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With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m2 grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.Keywords: localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI, GPS
Procedia PDF Downloads 3393004 Rheological Modeling for Shape-Memory Thermoplastic Polymers
Authors: H. Hosseini, B. V. Berdyshev, I. Iskopintsev
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This paper presents a rheological model for producing shape-memory thermoplastic polymers. Shape-memory occurs as a result of internal rearrangement of the structural elements of a polymer. A non-linear viscoelastic model was developed that allows qualitative and quantitative prediction of the stress-strain behavior of shape-memory polymers during heating. This research was done to develop a technique to determine the maximum possible change in size of heat-shrinkable products during heating. The rheological model used in this work was particularly suitable for defining process parameters and constructive parameters of the processing equipment.Keywords: elastic deformation, heating, shape-memory polymers, stress-strain behavior, viscoelastic model
Procedia PDF Downloads 3233003 Crater Detection Using PCA from Captured CMOS Camera Data
Authors: Tatsuya Takino, Izuru Nomura, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata
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We propose a method of detecting the craters from the image of the lunar surface. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) working group aiming at the pinpoint landing on the lunar surface and investigating scientific research. It is difficult to equip and use high-performance computers for the small space probe. So, it is necessary to use a small computer with an exclusive hardware such as FPGA. We have studied the crater detection using principal component analysis (PCA), In this paper, We implement detection algorithm into the FPGA, and the detection is performed on the data that was captured from the CMOS camera.Keywords: crater detection, PCA, FPGA, image processing
Procedia PDF Downloads 5503002 Proposal for an Inspection Tool for Damaged Structures after Disasters
Authors: Karim Akkouche, Amine Nekmouche, Leyla Bouzid
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This study focuses on the development of a multifunctional Expert System (ES) called post-seismic damage inspection tool (PSDIT), a powerful tool which allows the evaluation, the processing, and the archiving of the collected data stock after earthquakes. PSDIT can be operated by two user types; an ordinary user (ingineer, expert, or architect) for the damage visual inspection and an administrative user for updating the knowledge and / or for adding or removing the ordinary user. The knowledge acquisition is driven by a hierarchical knowledge model, the Information from investigation reports and those acquired through feedback from expert / engineer questionnaires are part.Keywords: .disaster, damaged structures, damage assessment, expert system
Procedia PDF Downloads 823001 Microfluidic Device for Real-Time Electrical Impedance Measurements of Biological Cells
Authors: Anil Koklu, Amin Mansoorifar, Ali Beskok
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Dielectric spectroscopy (DS) is a noninvasive, label free technique for a long term real-time measurements of the impedance spectra of biological cells. DS enables characterization of cellular dielectric properties such as membrane capacitance and cytoplasmic conductivity. We have developed a lab-on-a-chip device that uses an electro-activated microwells array for loading, DS measurements, and unloading of biological cells. We utilized from dielectrophoresis (DEP) to capture target cells inside the wells and release them after DS measurement. DEP is a label-free technique that exploits differences among dielectric properties of the particles. In detail, DEP is the motion of polarizable particles suspended in an ionic solution and subjected to a spatially non-uniform external electric field. To the best of our knowledge, this is the first microfluidic chip that combines DEP and DS to analyze biological cells using electro-activated wells. Device performance is tested using two different cell lines of prostate cancer cells (RV122, PC-3). Impedance measurements were conducted at 0.2 V in the 10 kHz to 40 MHz range with 6 s time resolution. An equivalent circuit model was developed to extract the cell membrane capacitance and cell cytoplasmic conductivity from the impedance spectra. We report the time course of the variations in dielectric properties of PC-3 and RV122 cells suspended in low conductivity medium (LCB), which enhances dielectrophoretic and impedance responses, and their response to sudden pH change from a pH of 7.3 to a pH of 5.8. It is shown that microfluidic chip allowed online measurements of dielectric properties of prostate cancer cells and the assessment of the cellular level variations under external stimuli such as different buffer conductivity and pH. Based on these data, we intend to deploy the current device for single cell measurements by fabricating separately addressable N × N electrode platforms. Such a device will allow time-dependent dielectric response measurements for individual cells with the ability of selectively releasing them using negative-DEP and pressure driven flow.Keywords: microfluidic, microfabrication, lab on a chip, AC electrokinetics, dielectric spectroscopy
Procedia PDF Downloads 1513000 Natural Language Processing for the Classification of Social Media Posts in Post-Disaster Management
Authors: Ezgi Şendil
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Information extracted from social media has received great attention since it has become an effective alternative for collecting people’s opinions and emotions based on specific experiences in a faster and easier way. The paper aims to put data in a meaningful way to analyze users’ posts and get a result in terms of the experiences and opinions of the users during and after natural disasters. The posts collected from Reddit are classified into nine different categories, including injured/dead people, infrastructure and utility damage, missing/found people, donation needs/offers, caution/advice, and emotional support, identified by using labelled Twitter data and four different machine learning (ML) classifiers.Keywords: disaster, NLP, postdisaster management, sentiment analysis
Procedia PDF Downloads 752999 CMOS Positive and Negative Resistors Based on Complementary Regulated Cascode Topology with Cross-Coupled Regulated Transistors
Authors: Kittipong Tripetch, Nobuhiko Nakano
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Two types of floating active resistors based on a complementary regulated cascode topology with cross-coupled regulated transistors are presented in this paper. The first topology is a high swing complementary regulated cascode active resistor. The second topology is a complementary common gate with a regulated cross coupled transistor. The small-signal input resistances of the floating resistors are derived. Three graphs of the input current versus the input voltage for different aspect ratios are designed and plotted using the Cadence Spectre 0.18-µm Rohm Semiconductor process. The total harmonic distortion graphs are plotted for three different aspect ratios with different input-voltage amplitudes and different input frequencies. From the simulation results, it is observed that a resistance of approximately 8.52 MΩ can be obtained from supply voltage at ±0.9 V.Keywords: floating active resistor, complementary common gate, complementary regulated cascode, current mirror
Procedia PDF Downloads 2592998 The Effective Use of the Network in the Distributed Storage
Authors: Mamouni Mohammed Dhiya Eddine
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This work aims at studying the exploitation of high-speed networks of clusters for distributed storage. Parallel applications running on clusters require both high-performance communications between nodes and efficient access to the storage system. Many studies on network technologies led to the design of dedicated architectures for clusters with very fast communications between computing nodes. Efficient distributed storage in clusters has been essentially developed by adding parallelization mechanisms so that the server(s) may sustain an increased workload. In this work, we propose to improve the performance of distributed storage systems in clusters by efficiently using the underlying high-performance network to access distant storage systems. The main question we are addressing is: do high-speed networks of clusters fit the requirements of a transparent, efficient and high-performance access to remote storage? We show that storage requirements are very different from those of parallel computation. High-speed networks of clusters were designed to optimize communications between different nodes of a parallel application. We study their utilization in a very different context, storage in clusters, where client-server models are generally used to access remote storage (for instance NFS, PVFS or LUSTRE). Our experimental study based on the usage of the GM programming interface of MYRINET high-speed networks for distributed storage raised several interesting problems. Firstly, the specific memory utilization in the storage access system layers does not easily fit the traditional memory model of high-speed networks. Secondly, client-server models that are used for distributed storage have specific requirements on message control and event processing, which are not handled by existing interfaces. We propose different solutions to solve communication control problems at the filesystem level. We show that a modification of the network programming interface is required. Data transfer issues need an adaptation of the operating system. We detail several propositions for network programming interfaces which make their utilization easier in the context of distributed storage. The integration of a flexible processing of data transfer in the new programming interface MYRINET/MX is finally presented. Performance evaluations show that its usage in the context of both storage and other types of applications is easy and efficient.Keywords: distributed storage, remote file access, cluster, high-speed network, MYRINET, zero-copy, memory registration, communication control, event notification, application programming interface
Procedia PDF Downloads 219