Search results for: images processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5650

Search results for: images processing

3520 To Smile or Not to Smile: How Engendered Facial Cues affect Hiring Decisions

Authors: Sabrina S. W. Chan, Emily Schwartzman, Nicholas O. Rule

Abstract:

Past literature showed mixed findings on how smiling affects a person’s chance of getting hired. On one hand, smiling suggests enthusiasm, cooperativeness, and enthusiasm, which can elicit positive impressions. On the other hand, smiling can suggest weaker professionalism or a filler to hide nervousness, which can lower a candidate’s perceived competence. Emotion expressions can also be perceived differently depending on the person’s gender and can activate certain gender stereotypes. Women especially face a double bind with respect to hiring decisions and smiling. Because women are socially expected to smile more, those who do not smile will be considered stereotype incongruent. This becomes a noisy signal to employers and may lower their chance of being hired. However, women’s smiling as a formality may also be an obstacle. They are more likely to put on fake smiles; but if they do, they are also likely to be perceived as inauthentic and over-expressive. This paper sought to investigate how smiling affects hiring decisions, and whether this relationship is moderated by gender. In Study 1, participants were shown a series of smiling and emotionally neutral face images, incorporated into fabricated LinkedIn profiles. Participants were asked to rate how hireable they thought that candidate was. Results showed that participants rated smiling candidates as more hireable than nonsmiling candidates, and that there was no difference in gender. Moreover, individuals who did not study business were more biased in their perceptions than those who did. Since results showed a trending favoritism over female targets, in suspect of desirability bias, a second study was conducted to collect implicit measures behind the decision-making process. In Study 2, a mouse-tracking design was adopted to explore whether participants’ implicit attitudes were different from their explicit responses on hiring. Participants asked to respond whether they would offer an interview to a candidate. Findings from Study 1 was replicated in that smiling candidates received more offers than neutral-faced candidates. Results also showed that female candidates received significantly more offers than male candidates but was associated with higher attractiveness ratings. There were no significant findings in reaction time or change of decisions. However, stronger hesitation was detected for responses made towards neutral targets when participants perceived the given position as masculine, implying a conscious attempt of making situational judgments (e.g., considering candidate’s personality and job fit) to override automatic processing (evaluations based on attractiveness). Future studies would look at how these findings differ for positions which are stereotypically masculine (e.g., surgeons) and stereotypically feminine (e.g., kindergarten teachers). Current findings have strong implications for developing bias-free hiring policies in workplace, especially for organizations who maintain online/hybrid working arrangements in the post-pandemic era. This also bridges the literature gap between face perception and gender discrimination, highlighting how engendered facial cues can affect individual’s career development and organization’s success in diversity and inclusion.

Keywords: engendered facial cues, face perception, gender stereotypes, hiring decisions, smiling, workplace discrimination

Procedia PDF Downloads 133
3519 Synthesize of Cobalt Oxide Nanoballs/Carbon Aerogel Nanostructures: Towards High-Performance Materials for Supercapacitors

Authors: A. Bahadoran, M. Zomorodian

Abstract:

The synthesizer of cobalt oxide nanoballs (length 3−4 μm, width 250−400 nm) was achieved by a simple high-temperature supercritical solution method. Multiwalled carbon aerogels are a step towards high-density nanometer-scale nanostructures. Cobalt oxide nanoballs were prepared by supercritical solution method. Synthesis in an aqueous solution containing cobalt hydroxide at ∼80 °C without any further heat treatment at high temperature. The formation of cobalt oxide nanoballs on carbon aerogel was confirmed by X-ray diffraction and Raman spectroscopy. The FE-SEM images showed the presence of cobalt oxide nanoballs. The reaction mechanism of the ultrasound-assisted synthesis of cobalt oxide nanostructures was proposed on the basis of the XRD, X-ray absorption spectroscopy analysis and FE-SEM observation of the reaction products taken during the course of the synthesis.

Keywords: cobalt oxide nano balls, carbon aerogel, synthesize, nanostructure

Procedia PDF Downloads 358
3518 Suitability of Class F Flyash for Construction Industry: An Indian Scenario

Authors: M. N. Akhtar, J. N. Akhtar

Abstract:

The present study evaluates the properties of class F fly ash as a replacement of natural materials in civil engineering construction industry. The low-lime flash similar to class F is the prime variety generated in India, although it has significantly smaller volumes of high-lime fly ash as compared to class C. The chemical and physical characterization of the sample is carried out with the number of experimental approaches in order to investigate all relevant features present in the samples. For chemical analysis, elementary quantitative results from point analysis and scanning electron microscopy (SEM)/dispersive spectroscopy (EDS) techniques were used to identify the element images of different fractions. The physical properties found very close to the range of common soils. Furthermore, the fly ash-based bricks were prepared by the same sample of class F fly ash and the results of compressive strength similar to that of Standard Clay Brick Grade 1 available in the local market of India.

Keywords: fly ash, class F, class C, chemical, physical, SEM, EDS

Procedia PDF Downloads 181
3517 Effect of Ti, Nb, and Zr Additives on Biocompatibility of Injection Molded 316L Stainless Steel for Biomedical Applications

Authors: Busra Gundede, Ozal Mutlu, Nagihan Gulsoy

Abstract:

Background: Over the years, material research has led to the development of numerous metals and alloys for using in biomedical applications. One of the major tasks of biomaterial research is the functionalization of the material surface to improve the biocompatibility according to a specific application. 316L and 316L alloys are excellent for various bio-applications. This research was investigated the effect of titanium (Ti), niobium (Nb), and zirconium (Zr) additives on injection molded austenitic grade 316L stainless steels in vitro biocompatibility. For this purpose, cytotoxic tests were performed to evaluate the potential biocompatibility of the specimens. Materials and Methods: 3T3 fibroblast were cultivated in DMEM supplemented with 10% fetal bovine serum and %1 penicillin-streptomycin at 37°C with 5% CO2 and 95%humidity. Trypsin/EDTA solution was used to remove cells from the culture flask. Cells were reseeded at a density of 1×105cell in 25T flasks. The medium change took place every 3 days. The trypan blue assay was used to determine cell viability. Cell viability is calculated as the number of viable cells divided by the total number of cells within the grids on the cell counter machine counted the number of blue staining cells and the number of total cells. Cell viability should be at least 95% for healthy log-phase cultures. MTT assay was assessed for 96-hours. Cells were cultivated in 6-well flask within 5 ml DMEM and incubated as same conditions. 0,5mg/ml MTT was added for 4-hours and then acid-isoprohanol was added for solubilize to formazan crystals. Cell morphology after 96h was investigated by SEM. The medium was removed, samples were washed with 0.15 M PBS buffer and fixed for 12h at 4- 8°C with %2,5 gluteraldehyte. Samples were treated with 1% osmium tetroxide. Samples were then dehydrated and dried, mounted on appropriate stubs with colloidal silver and sputter-coated with gold. Images were collected using a scanning electron microscope. ROS assay is a cell viability test for in vitro studies. Cells were grown for 96h, ROS solution added on cells in 6 well plate flask and incubated for 1h. Fluorescence signal indicates ROS generation by cells. Results: Trypan Blue exclusion assay results were 96%, 92%, 95%, 90%, 91% for negative control group, 316L, 316L-Ti, 316L-Nb and 316L-Zr, respectively. Results were found nearly similar to each other when compared with control group. Cell viability from MTT analysis was found to be 100%, 108%, 103%, 107%, and 105% for the control group, 316L, 316L-Ti, 316L-Nb and 316L-Zr, respectively. Fluorescence microscopy analysis indicated that all test groups were same as the control group in ROS assay. SEM images demonstrated that the attachment of 3T3 cells on biomaterials. Conclusion: We, therefore, concluded that Ti, Nb and Zr additives improved physical properties of 316L stainless. In our in vitro experiments showed that these new additives did not modify the cytocompatibility of stainless steel and these additives on 316L might be useful for biomedical applications.

Keywords: 316L stainles steel, biocompatibility, cell culture, Ti, Nb, Zr

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3516 Automatic Extraction of Water Bodies Using Whole-R Method

Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

Abstract:

Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R-colour component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: feature extraction, remote sensing, image retrieval, chromaticity, water index, spectral library, integrated method

Procedia PDF Downloads 386
3515 Time Temperature Dependence of Long Fiber Reinforced Polypropylene Manufactured by Direct Long Fiber Thermoplastic Process

Authors: K. A. Weidenmann, M. Grigo, B. Brylka, P. Elsner, T. Böhlke

Abstract:

In order to reduce fuel consumption, the weight of automobiles has to be reduced. Fiber reinforced polymers offer the potential to reach this aim because of their high stiffness to weight ratio. Additionally, the use of fiber reinforced polymers in automotive applications has to allow for an economic large-scale production. In this regard, long fiber reinforced thermoplastics made by direct processing offer both mechanical performance and processability in injection moulding and compression moulding. The work presented in this contribution deals with long glass fiber reinforced polypropylene directly processed in compression moulding (D-LFT). For the use in automotive applications both the temperature and the time dependency of the materials properties have to be investigated to fulfill performance requirements during crash or the demands of service temperatures ranging from -40 °C to 80 °C. To consider both the influence of temperature and time, quasistatic tensile tests have been carried out at different temperatures. These tests have been complemented by high speed tensile tests at different strain rates. As expected, the increase in strain rate results in an increase of the elastic modulus which correlates to an increase of the stiffness with decreasing service temperature. The results are in good accordance with results determined by dynamic mechanical analysis within the range of 0.1 to 100 Hz. The experimental results from different testing methods were grouped and interpreted by using different time temperature shift approaches. In this regard, Williams-Landel-Ferry and Arrhenius approach based on kinetics have been used. As the theoretical shift factor follows an arctan function, an empirical approach was also taken into consideration. It could be shown that this approach describes best the time and temperature superposition for glass fiber reinforced polypropylene manufactured by D-LFT processing.

Keywords: composite, dynamic mechanical analysis, long fibre reinforced thermoplastics, mechanical properties, time temperature superposition

Procedia PDF Downloads 199
3514 Wetting Induced Collapse Behavior of Loosely Compacted Kaolin Soil: A Microstructural Study

Authors: Dhanesh Sing Das, Bharat Tadikonda Venkata

Abstract:

Collapsible soils undergo significant volume reduction upon wetting under the pre-existing mechanically applied normal stress (inundation pressure). These soils exhibit a very high strength in air-dried conditions and can carry up to a considerable magnitude of normal stress without undergoing significant volume change. The soil strength is, however, lost upon saturation and results in a sudden collapse of the soil structure under the existing mechanical stress condition. The intrusion of water into the dry deposits of such soil causes ground subsidence leading to damages in the overlying buildings/structures. A study on the wetting-induced volume change behavior of collapsible soils is essential in dealing with the ground subsidence problems in various geotechnical engineering practices. The collapse of loosely compacted Kaolin soil upon wetting under various inundation pressures has been reported in recent studies. The collapse in the Kaolin soil is attributed to the alteration in the soil particle-particle association (fabric) resulting due to the changes in the various inter-particle (microscale) forces induced by the water saturation. The inundation pressure plays a significant role in the fabric evolution during the wetting process, thus controls the collapse potential of the compacted soil. A microstructural study is useful to understand the collapse mechanisms at various pore-fabric levels under different inundation pressure. Kaolin soil compacted to a dry density of 1.25 g/cc was used in this work to study the wetting-induced volume change behavior under different inundation pressures in the range of 10-1600 kPa. The compacted specimen of Kaolin soil exhibited a consistent collapse under all the studied inundation pressure. The collapse potential was observed to be increasing with an increase in the inundation pressure up to a maximum value of 13.85% under 800 kPa and then decreased to 11.7% under 1600 kPa. Microstructural analysis was carried out based on the fabric images and the pore size distributions (PSDs) obtained from FESEM analysis and mercury intrusion porosimetry (MIP), respectively. The PSDs and the soil fabric images of ‘as-compacted’ specimen and post-collapse specimen under 400 kPa were analyzed to understand the changes in the soil fabric and pores due to wetting. The pore size density curve for the post-collapse specimen was found to be on the finer side with respect to the ‘as-compacted’ specimen, indicating the reduction of the larger pores during the collapse. The inter-aggregate pores in the range of 0.1-0.5μm were identified as the major contributing pore size classes to the macroscopic volume change. Wetting under an inundation pressure results in the reduction of these pore sizes and lead to an increase in the finer pore sizes. The magnitude of inundation pressure influences the amount of reduction of these pores during the wetting process. The collapse potential was directly related to the degree of reduction in the pore volume contributed by these pore sizes.

Keywords: collapse behavior, inundation pressure, kaolin, microstructure

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3513 A CORDIC Based Design Technique for Efficient Computation of DCT

Authors: Deboraj Muchahary, Amlan Deep Borah Abir J. Mondal, Alak Majumder

Abstract:

A discrete cosine transform (DCT) is described and a technique to compute it using fast Fourier transform (FFT) is developed. In this work, DCT of a finite length sequence is obtained by incorporating CORDIC methodology in radix-2 FFT algorithm. The proposed methodology is simple to comprehend and maintains a regular structure, thereby reducing computational complexity. DCTs are used extensively in the area of digital processing for the purpose of pattern recognition. So the efficient computation of DCT maintaining a transparent design flow is highly solicited.

Keywords: DCT, DFT, CORDIC, FFT

Procedia PDF Downloads 478
3512 Study of Land Use Land Cover Change of Bhimbetka with Temporal Satellite Data and Information Systems

Authors: Pranita Shivankar, Devashree Hardas, Prabodhachandra Deshmukh, Arun Suryavanshi

Abstract:

Bhimbetka Rock Shelters is the UNESCO World Heritage Site located about 45 kilometers south of Bhopal in the state of Madhya Pradesh, India. Rapid changes in land use land cover (LULC) adversely affect the environment. In recent past, significant changes are found in the cultural landscape over a period of time. The objective of the paper was to study the changes in land use land cover (LULC) of Bhimbetka and its peripheral region. For this purpose, the supervised classification was carried out by using satellite images of Landsat and IRS LISS III for the year 2000 and 2013. Use of remote sensing in combination with geographic information system is one of the effective information technology tools to generate land use land cover (LULC) change information.

Keywords: IRS LISS III, Landsat, LULC, UNESCO, World Heritage Site

Procedia PDF Downloads 351
3511 Operating Parameters and Costs Assessments of a Real Fishery Wastewater Effluent Treated by Electrocoagulation Process

Authors: Mirian Graciella Dalla Porta, Humberto Jorge José, Danielle de Bem Luiz, Regina de F. P. M.Moreira

Abstract:

Similar to most processing industries, fish processing produces large volumes of wastewater, which contains especially organic contaminants, salts and oils dispersed therein. Different processes have been used for the treatment of fishery wastewaters, but the most commonly used are chemical coagulation and flotation. These techniques are well known but sometimes the characteristics of the treated effluent do not comply with legal standards for discharge. Electrocoagulation (EC) is an electrochemical process that can be used to treat wastewaters in terms of both organic matter and nutrient removal. The process is based on the use of sacrificial electrodes such as aluminum, iron or zinc, that are oxidized to produce metal ions that can be used to coagulate and react with organic matter and nutrients in the wastewater. While EC processes are effective to treatment of several types of wastewaters, applications have been limited due to the high energy demands and high current densities. Generally, the for EC process can be performed without additional chemicals or pre-treatment, but the costs should be reduced for EC processes to become more applicable. In this work, we studied the treatment of a real wastewater from fishmeal industry by electrocoagulation process. Removal efficiencies for chemical oxygen demand (COD), total organic carbon (TOC) turbidity, phosphorous and nitrogen concentration were determined as a function of the operating conditions, such as pH, current density and operating time. The optimum operating conditions were determined to be operating time of 10 minutes, current density 100 A.m-2, and initial pH 4.0. COD, TOC, phosphorous concentration, and turbidity removal efficiencies at the optimum operating conditions were higher than 90% for aluminum electrode. Operating costs at the optimum conditions were calculated as US$ 0.37/m3 (US$ 0.038/kg COD) for Al electrode. These results demonstrate that the EC process is a promising technology to remove nutrients from fishery wastewaters, as the process has both a high efficiency of nutrient removal, and low energy requirements.

Keywords: electrocoagulation, fish, food industry, wastewater

Procedia PDF Downloads 249
3510 Deep Learning Approach for Colorectal Cancer’s Automatic Tumor Grading on Whole Slide Images

Authors: Shenlun Chen, Leonard Wee

Abstract:

Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

Procedia PDF Downloads 134
3509 Artificial Intelligence Based Analysis of Magnetic Resonance Signals for the Diagnosis of Tissue Abnormalities

Authors: Kapila Warnakulasuriya, Walimuni Janaka Mendis

Abstract:

In this study, an artificial intelligence-based approach is developed to diagnose abnormal tissues in human or animal bodies by analyzing magnetic resonance signals. As opposed to the conventional method of generating an image from the magnetic resonance signals, which are then evaluated by a radiologist for the diagnosis of abnormalities, in the discussed approach, the magnetic resonance signals are analyzed by an artificial intelligence algorithm without having to generate or analyze an image. The AI-based program compares magnetic resonance signals with millions of possible magnetic resonance waveforms which can be generated from various types of normal tissues. Waveforms generated by abnormal tissues are then identified, and images of the abnormal tissues are generated with the possible location of them in the body for further diagnostic tests.

Keywords: magnetic resonance, artificial intelligence, magnetic waveform analysis, abnormal tissues

Procedia PDF Downloads 91
3508 Sorting Fish by Hu Moments

Authors: J. M. Hernández-Ontiveros, E. E. García-Guerrero, E. Inzunza-González, O. R. López-Bonilla

Abstract:

This paper presents the implementation of an algorithm that identifies and accounts different fish species: Catfish, Sea bream, Sawfish, Tilapia, and Totoaba. The main contribution of the method is the fusion of the characteristics of invariance to the position, rotation and scale of the Hu moments, with the proper counting of fish. The identification and counting is performed, from an image under different noise conditions. From the experimental results obtained, it is inferred the potentiality of the proposed algorithm to be applied in different scenarios of aquaculture production.

Keywords: counting fish, digital image processing, invariant moments, pattern recognition

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3507 Comparison of Flow and Mixing Characteristics between Non-Oscillating and Transversely Oscillating Jet

Authors: Dinku Seyoum Zeleke, Rong Fung Huang, Ching Min Hsu

Abstract:

Comparison of flow and mixing characteristics between non-oscillating jet and transversely oscillating jet was investigated experimentally. Flow evolution process was detected by using high-speed digital camera, and jet spread width was calculated using binary edge detection techniques by using the long-exposure images. The velocity characteristics of transversely oscillating jet induced by a V-shaped fluidic oscillator were measured using single component hot-wire anemometer. The jet spread width of non-oscillating jet was much smaller than the jet exit gap because of behaving natural jet behaviors. However, the transversely oscillating jet has a larger jet spread width, which was associated with the excitation of the flow by self-induced oscillation. As a result, the flow mixing characteristics desperately improved both near-field and far-field. Therefore, this transversely oscillating jet has a better turbulence intensity, entrainment, and spreading width so that it augments flow-mixing characteristics desperately.

Keywords: flow mixing, transversely oscillating, spreading width, velocity characteristics

Procedia PDF Downloads 249
3506 An Approach to Autonomous Drones Using Deep Reinforcement Learning and Object Detection

Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

Abstract:

Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

Procedia PDF Downloads 251
3505 Discussion on Microstructural Changes Caused by Deposition Temperature of LZO Doped Mg Piezoelectric Films

Authors: Cheng-Ying Li, Sheng-Yuan Chu

Abstract:

This article deposited LZO-doped Mg piezoelectric thin films via RF sputtering and observed microstructure and electrical characteristics by varying the deposition temperature. The XRD analysis results indicate that LZO-doped Mg exhibits excellent (002) orientation, and there is no presence of ZnO(100), Influenced by the temperature's effect on the lattice constant, the (002) peak intensity increases with rising temperature. Finally, we conducted deformation intensity analysis on the films, revealing an over fourfold increase in deformation at a processing temperature of 500°C.

Keywords: RF sputtering, piezoelectricity, ZnO, Mg

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3504 Improving Subjective Bias Detection Using Bidirectional Encoder Representations from Transformers and Bidirectional Long Short-Term Memory

Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

Abstract:

Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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3503 Enabling Non-invasive Diagnosis of Thyroid Nodules with High Specificity and Sensitivity

Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

Abstract:

Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

Procedia PDF Downloads 58
3502 Effect of Roasting Treatment on Milling Quality, Physicochemical, and Bioactive Compounds of Dough Stage Rice Grains

Authors: Chularat Leewuttanakul, Khanitta Ruttarattanamongkol, Sasivimon Chittrakorn

Abstract:

Rice during grain development stage is a rich source of many bioactive compounds. Dough stage rice contains high amounts of photochemical and can be used for rice milling industries. However, rice grain at dough stage had low milling quality due to high moisture content. Thermal processing can be applied to rice grain for improving milled rice yield. This experiment was conducted to study the chemical and physic properties of dough stage rice grain after roasting treatment. Rice were roasted with two different methods including traditional pan roasting at 140 °C for 60 minutes and using the electrical roasting machine at 140 °C for 30, 40, and 50 minutes. The chemical, physical properties, and bioactive compounds of brown rice and milled rice were evaluated. The result of this experiment showed that moisture content of brown and milled rice was less than 10 % and amylose contents were in the range of 26-28 %. Rice grains roasting for 30 min using electrical roasting machine had high head rice yield and length and breadth of grain after milling were close to traditional pan roasting (p > 0.05). The lightness (L*) of rice did not affect by roasting treatment (p > 0.05) and the a* indicated the yellowness of milled rice was lower than brown rice. The bioactive compounds of brown and milled rice significantly decreased with increasing of drying time. Brown rice roasted for 30 minutes had the highest of total phenolic content, antioxidant activity, α-tocopherol, and ɤ-oryzanol content. Volume expansion and elongation of cooked rice decreased as roasting time increased and quality of cooked rice roasted for 30 min was comparable to traditional pan roasting. Hardness of cooked rice as measured by texture analyzer increased with increasing roasting time. The results indicated that rice grains at dough stage, containing a high amount of bioactive compounds, have a great potential for rice milling industries and the electrical roasting machine can be used as an alternative to pan roasting which decreases processing time and labor costs.

Keywords: bioactive compounds, cooked rice, dough stage rice grain, grain development, roasting

Procedia PDF Downloads 164
3501 Representation of Women in TV Commercials

Authors: Elmira Fotoohi

Abstract:

Representation of women in commercials and the place of sex in advertising is a part of communication studies and all of them are subset of advertising sociology. In this context, a lot of national and international studies have been done from different aspects. But in the meantime, and in connection with women issues, researchers in Communication Science and Sociology are interested in two topics “use of pornographic images of women” and “repeated representations of women in traditional roles and gender stereotypes by emphasizing the differences between men and women”, more than any other topics. Considering a number of changes that have occurred in social institutions and at different levels, the main research question currently are, what is the role of women in our TV ads and how are they represented in them? Do the local television ads represent women in the same issues as the researchers on this topic has proposed or new changes have occurred? Many scholars and thinkers in the field of media outlet that, today, media not just focus on women as gender issues or sex objects, but also seeks to strengthen the gender division of labor in the family and emphasize on the traditional muliebrity and masculinity stereotype.

Keywords: women, representation, tv commercials, advertising sociology, gender stereotypes

Procedia PDF Downloads 523
3500 Content and Langauge Integrated Learning: English and Art History

Authors: Craig Mertens

Abstract:

Teaching art history or any other academic subject to EFL students can be done successfully. A course called Western Images was created to teach Japanese students art history while only using English in the classroom. An approach known as Content and Language Integrated Learning (CLIL) was used as a basis for this course. This paper’s purpose is to state the reasons why learning about art history is important, go through the process of creating content for the course, and suggest multiple tasks to help students practice the critical thinking skills used in analyzing and drawing conclusions of works of art from western culture. As a guide for this paper, Brown’s (1995) six elements of a language curriculum will be used. These stages include needs analysis, goals and objectives, assessment, materials, teaching method and tasks, and evaluation of the course. The goal here is to inspire debate and discussion regarding CLIL and its pros and cons, and to question current curriculum in university language courses.

Keywords: art history, EFL, content and language integration learning, critical thinking

Procedia PDF Downloads 597
3499 Quantitative Analysis of Camera Setup for Optical Motion Capture Systems

Authors: J. T. Pitale, S. Ghassab, H. Ay, N. Berme

Abstract:

Biomechanics researchers commonly use marker-based optical motion capture (MoCap) systems to extract human body kinematic data. These systems use cameras to detect passive or active markers placed on the subject. The cameras use triangulation methods to form images of the markers, which typically require each marker to be visible by at least two cameras simultaneously. Cameras in a conventional optical MoCap system are mounted at a distance from the subject, typically on walls, ceiling as well as fixed or adjustable frame structures. To accommodate for space constraints and as portable force measurement systems are getting popular, there is a need for smaller and smaller capture volumes. When the efficacy of a MoCap system is investigated, it is important to consider the tradeoff amongst the camera distance from subject, pixel density, and the field of view (FOV). If cameras are mounted relatively close to a subject, the area corresponding to each pixel reduces, thus increasing the image resolution. However, the cross section of the capture volume also decreases, causing reduction of the visible area. Due to this reduction, additional cameras may be required in such applications. On the other hand, mounting cameras relatively far from the subject increases the visible area but reduces the image quality. The goal of this study was to develop a quantitative methodology to investigate marker occlusions and optimize camera placement for a given capture volume and subject postures using three-dimension computer-aided design (CAD) tools. We modeled a 4.9m x 3.7m x 2.4m (LxWxH) MoCap volume and designed a mounting structure for cameras using SOLIDWORKS (Dassault Systems, MA, USA). The FOV was used to generate the capture volume for each camera placed on the structure. A human body model with configurable posture was placed at the center of the capture volume on CAD environment. We studied three postures; initial contact, mid-stance, and early swing. The human body CAD model was adjusted for each posture based on the range of joint angles. Markers were attached to the model to enable a full body capture. The cameras were placed around the capture volume at a maximum distance of 2.7m from the subject. We used the Camera View feature in SOLIDWORKS to generate images of the subject as seen by each camera and the number of markers visible to each camera was tabulated. The approach presented in this study provides a quantitative method to investigate the efficacy and efficiency of a MoCap camera setup. This approach enables optimization of a camera setup through adjusting the position and orientation of cameras on the CAD environment and quantifying marker visibility. It is also possible to compare different camera setup options on the same quantitative basis. The flexibility of the CAD environment enables accurate representation of the capture volume, including any objects that may cause obstructions between the subject and the cameras. With this approach, it is possible to compare different camera placement options to each other, as well as optimize a given camera setup based on quantitative results.

Keywords: motion capture, cameras, biomechanics, gait analysis

Procedia PDF Downloads 310
3498 Application of Smplify-X Algorithm with Enhanced Gender Classifier in 3D Human Pose Estimation

Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian

Abstract:

The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.

Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction

Procedia PDF Downloads 100
3497 A Comparison of Image Data Representations for Local Stereo Matching

Authors: André Smith, Amr Abdel-Dayem

Abstract:

The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: colour data, local stereo matching, stereo correspondence, disparity map

Procedia PDF Downloads 370
3496 Hardware Implementation for the Contact Force Reconstruction in Tactile Sensor Arrays

Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

Abstract:

Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

Procedia PDF Downloads 195
3495 Evaluation of Three Potato Cultivars for Processing (Crisp French Fries)

Authors: Hatim Bastawi

Abstract:

Three varieties of potatoes, namely Agria, Alpha and Diamant were evaluated for their suitability for industrial production of French fries. The evaluation was under taken after testing quality parameters of specific gravity, dry matter, peeling ratio, and defect after frying and panel test. The variety Agria ranked the best followed by Alpha with regard to the parameters tested. On the other hand, Diamant showed significantly higher defect percentage than the other cultivars. Also, it was significantly judged of low acceptance by panelists.

Keywords: cultivars, crisps, French fries

Procedia PDF Downloads 261
3494 Identification of Breast Anomalies Based on Deep Convolutional Neural Networks and K-Nearest Neighbors

Authors: Ayyaz Hussain, Tariq Sadad

Abstract:

Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

Procedia PDF Downloads 136
3493 Fog Computing- Network Based Computing

Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

Abstract:

Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

Procedia PDF Downloads 388
3492 Trans-Gendered Female Characters: A Comparative Study of Two Female Characters in English and Persian Literature - Lady Macbeth and Gord Afarid

Authors: Seyedeh Azadeh Johari

Abstract:

For thousand years, the literature of the world has been mostly composed of men, and in all different forms of it, men have tried to propose their masculine desires, ideologies, and beliefs. What has been less written about or studied, however, was the role that female desire plays in the predominantly masculine society, and mostly the role of male desires was the key point in literature. Male writers have mostly shown their female characters either as stereotypes and void of dynamic characters, images of a meek person who bent to the will of her male superiors or as wicked or villains. The only exception was the kind of strong and courageous women who have mostly been masculinized by their authors, mostly male authors, as showing the valuable or important features of men, instead of women’s. These characters are transgendered by the author and have a gender identity or expression that differs from the sex to which they were assigned. This is the issue that is discussed in this project. We will refer to some examples of female characters who show masculine traits and characteristics.

Keywords: comparative literature, female, masculinized, transgendered

Procedia PDF Downloads 153
3491 Bacteria Immobilized Electrospun Fibrous Biocomposites for Cr (VI) Remediation in Water

Authors: Omer Faruk Sarioglu, Asli Celebioglu, Turgay Tekinay, Tamer Uyar

Abstract:

Fibrous biocomposites were developed by immobilization of a Cr(VI) reducing bacterial strain, morganella morganii STB5, on electrospun polystyrene (PS) and polysulfone (PSU) webs. Cr(VI) removal characteristics of STB5/PS and STB5/PSU fibrous biocomposites were determined at 25 mg L-1 of initial Cr(VI) and 70.41% and 68.27% of removal were observed within 72 h, respectively. Reusability test results indicate that both biocomposites are potentially reusable and can be used for at least 5 cycles. After storage test results suggest that the biocomposites can be stored awhile without losing their Cr(VI) bioremoval capabilities. SEM images of STB5 immobilized PS and PSU webs after the reusability test exhibit strong attachment of bacterial biofilms onto fibrous surfaces. Our results are quite promising and suggesting that reusable bacteria immobilized electrospun fibrous biocomposites might be applicable for Cr(VI) remediation in water systems.

Keywords: electrospinning, polystyrene, polysulfone, Cr(VI) bioremoval, environmental sustainability

Procedia PDF Downloads 561