Search results for: emotion detection in the text

Authors: Sardorbek Numonov, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Dongeun Choi, Byung-Woo Hong

Abstract:

The detection of curvilinear structures often plays an important role in the analysis of images. In particular, it is considered as a crucial step for the diagnosis of chronic respiratory diseases to localize the fissures in chest CT imagery where the lung is divided into five lobes by the fissures that are characterized by linear features in appearance. However, the characteristic linear features for the fissures are often shown to be subtle due to the high intensity variability, pathological deformation or image noise involved in the imaging procedure, which leads to the uncertainty in the quantification of anatomical or functional properties of the lung. Thus, it is desired to enhance the linear features present in the chest CT images so that the distinctiveness in the delineation of the lobe is improved. We propose a recursive diffusion process that prefers coherent features based on the analysis of structure tensor in an anisotropic manner. The local image features associated with certain scales and directions can be characterized by the eigenanalysis of the structure tensor that is often regularized via isotropic diffusion filters. However, the isotropic diffusion filters involved in the computation of the structure tensor generally blur geometrically significant structure of the features leading to the degradation of the characteristic power in the feature space. Thus, it is required to take into consideration of local structure of the feature in scale and direction when computing the structure tensor. We apply an anisotropic diffusion in consideration of scale and direction of the features in the computation of the structure tensor that subsequently provides the geometrical structure of the features by its eigenanalysis that determines the shape of the anisotropic diffusion kernel. The recursive application of the anisotropic diffusion with the kernel the shape of which is derived from the structure tensor leading to the anisotropic scale-space where the geometrical features are preserved via the eigenanalysis of the structure tensor computed from the diffused image. The recursive interaction between the anisotropic diffusion based on the geometry-driven kernels and the computation of the structure tensor that determines the shape of the diffusion kernels yields a scale-space where geometrical properties of the image structure are effectively characterized. We apply our recursive anisotropic diffusion algorithm to the detection of curvilinear structure in the chest CT imagery where the fissures present curvilinear features and define the boundary of lobes. It is shown that our algorithm yields precise detection of the fissures while overcoming the subtlety in defining the characteristic linear features. The quantitative evaluation demonstrates the robustness and effectiveness of the proposed algorithm for the detection of fissures in the chest CT in terms of the false positive and the true positive measures. The receiver operating characteristic curves indicate the potential of our algorithm as a segmentation tool in the clinical environment. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: anisotropic diffusion, chest CT imagery, chronic respiratory disease, curvilinear structure, fissure detection, structure tensor

Procedia PDF Downloads 229

Authors: Yuan-Jye Tseng, Ching-Yen Chen

Abstract:

In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

Procedia PDF Downloads 183

Authors: Martina Kaufmann, Thomas Goetz, Anastasiya A. Lipnevich, Reinhard Pekrun

Abstract:

Positive emotions have been shown to benefit from optimistic perceptions, even if these perceptions are illusory. The current research investigated the impact of illusions of control on positive emotions. There is empirical evidence showing that people are more emotionally attentive to losses than to gains. Hence, we expected that, compared to gains, losses in illusory control would have a stronger impact on positive emotions. The results of two experimental studies support this assumption: Participants who experienced gains in illusory control showed no substantial change in positive emotions. However, positive emotions decreased when they perceived a loss in illusory control. These results suggest that a loss of illusory control (but not a gain thereof) mediates the impact of the situation on individuals’ positive emotions. Implications for emotion theory and practice are discussed.

Keywords: cognitive appraisal, control, illusions, optimism, positive emotions

Procedia PDF Downloads 637

Authors: Eva Savy, Anthony Ruiz

Abstract:

In extrusion blow molding, there is great variability in product quality due to the sensitivity of the machine settings. These variations lead to unnecessary rejects and loss of time. Yet production control is a major challenge for companies in this sector to remain competitive within their market. Current quality control methods only apply to finished products (vision control, leak test...). It has been shown that material melt temperature, blowing pressure, and ambient temperature have a significant impact on the variability of product quality. Since blowing is a key step in the process, we have studied this parameter in this paper. The objective is to determine if airflow analysis allows the identification of quality problems before the full completion of the manufacturing process. We conducted tests to determine if it was possible to identify a leakage defect and an obstructed defect, two common defects on products. The results showed that it was possible to identify a leakage defect by airflow analysis.

Keywords: extrusion blow molding, signal, sensor, defects, detection

Procedia PDF Downloads 144

Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

Abstract:

Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

Procedia PDF Downloads 688

Authors: Rupesh K. Mishra, Gaëlle Catanante, Akhtar Hayat, Jean-Louis Marty

Abstract:

Ochratoxins (OTA) are secondary metabolites present in a wide variety of food stuff. They are dangerous by-products mainly produced by several species of storage fungi including the Aspergillus and Penicillium genera. OTA is known to have nephrotoxic, immunotoxic, teratogenic and carcinogenic effects. Thus, needs a special attention for a highly sensitive and selective detection system that can quantify these organic toxins in various matrices such as cocoa beans. This work presents a folding based aptasensors by employing an aptamer conjugated redox probe (methylene blue) specifically designed for OTA. The aptamers were covalently attached to the screen printed carbon electrodes using diazonium grafting. Upon sensing the OTA, it binds with the immobilized aptamer on the electrode surface, which induces the conformational changes of the aptamer, consequently increased in the signal. This conformational change of the aptamer before and after biosensing of target OTA could produce the distinguishable electrochemical signal. The obtained limit of detection was 0.01 ng/ml for OTA samples with recovery of up to 88% in contaminated cocoa samples.

Keywords: ochratoxin A, cocoa, DNA aptamer, labelled probe

Procedia PDF Downloads 280

Authors: Amani Abdallah, Isam Shahrour

Abstract:

The quality of drinking water is a major concern of public health. The control of this quality is generally performed in the laboratory, which requires a long time. This type of control is not adapted for accidental pollution from sudden events, which can have serious consequences on population health. Therefore, it is of major interest to develop real-time innovative solutions for the detection of accidental contamination in drinking water systems This paper presents researches conducted within the SunRise Demonstrator for ‘Smart and Sustainable Cities’ with a particular focus on the supervision of the water quality. This work aims at (i) implementing a smart water system in a large water network (Campus of the University Lille1) including innovative equipment for real-time detection of abnormal events, such as those related to the contamination of drinking water and (ii) develop a numerical modeling of the contamination diffusion in the water distribution system. The first step included verification of the water quality sensors and their effectiveness on a network prototype of 50m length. This part included the evaluation of the efficiency of these sensors in the detection both bacterial and chemical contamination events in drinking water distribution systems. An on-line optical sensor integral with a laboratory-scale distribution system (LDS) was shown to respond rapidly to changes in refractive index induced by injected loads of chemical (cadmium, mercury) and biological contaminations (Escherichia coli). All injected substances were detected by the sensor; the magnitude of the response depends on the type of contaminant introduced and it is proportional to the injected substance concentration.

Keywords: distribution system, drinking water, refraction index, sensor, real-time

Procedia PDF Downloads 348

Authors: Nahla Elsherbiny, Ahmed Ahmed, Hamada Mohammed, Mohamed Ali

Abstract:

Background: The enterococci may be considered as opportunistic agents particularly in immunocompromised patients. It is one of the top three pathogens causing many healthcare associated infections (HAIs). Resistance to several commonly used antimicrobial agents is a remarkable characteristic of most species which may carry various genes contributing to virulence. Objectives: to determine the prevalence of enterococci species in different intensive care units (ICUs) causing health care-associated infections (HAIs), intestinal carriage and environmental contamination. Also, to study the antimicrobial susceptibility pattern of the isolates with special reference to vancomycin resistance. In addition to phenotypic and genotypic detection of gelatinase, cytolysin and biofilm formation among isolates. Patients and Methods: This study was carried out in the infection control laboratory at Assiut University Hospitals over a period of one year. Clinical samples were collected from 285 patients with various (HAIs) acquired after admission to different ICUs. Rectal swabs were taken from 14 cases for detection of enterococci carriage. In addition, 1377 environmental samples were collected from the surroundings of the patients. Identification was done by conventional bacteriological methods and confirmed by analytical profile index (API). Antimicrobial sensitivity testing was performed by Kirby Bauer disc diffusion method and detection of vancomycin resistance was done by agar screen method. For the isolates, phenotypic detection of cytolysin, gelatinase production and detection of biofilm by tube method, Congo red method and microtiter plate. We performed polymerase chain reaction (PCR) for detection of some virulence genes (gelE, cylA, vanA, vanB and esp). Results: Enterococci caused 10.5% of the HAIs. Respiratory tract infection was the predominant type (86.7%). The commonest species were E.gallinarum (36.7%), E.casseliflavus (30%), E.faecalis (30%), and E.durans (3.4 %). Vancomycin resistance was detected in a total of 40% (12/30) of those isolates. The risk factors associated with acquiring vancomycin resistant enterococci (VRE) were immune suppression (P= 0.031) and artificial feeding (P= 0.008). For the rectal swabs, enterococci species were detected in 71.4% of samples with the predominance of E. casseliflavus (50%). Most of the isolates were vancomycin resistant (70%). Out of a total 1377 environmental samples, 577 (42%) samples were contaminated with different microorganisms. Enterococci were detected in 1.7% (10/577) of total contaminated samples, 50% of which were vancomycin resistant. All isolates were resistant to penicillin, ampicillin, oxacillin, ciprofloxacin, amikacin, erythromycin, clindamycin and trimethoprim-sulfamethaxazole. For the remaining antibiotics, variable percentages of resistance were reported. Cytolysin and gelatinase were detected phenotypically in 16% and 48 % of the isolates respectively. The microtiter plate method showed the highest percentages of detection of biofilm among all isolated species (100%). The studied virulence genes gelE, esp, vanA and vanB were detected in 62%, 12%, 2% and 12% respectively, while cylA gene was not detected in any isolates. Conclusions: A significant percentage of enterococci was isolated from patients and environments in the ICUs. Many virulence factors were detected phenotypically and genotypically among isolates. The high percentage of resistance, coupled with the risk of cross transmission to other patients make enterococci infections a significant infection control issue in hospitals.

Keywords: antimicrobial resistance, enterococci, ICUs, virulence factors

Procedia PDF Downloads 279

Authors: Hemalatha Rallapalli, K. Lal Kishore

Abstract:

In comparison to systems that are typically designed to provide capabilities over a narrow frequency range through hardware elements, the next generation cognitive radios are intended to implement a broader range of capabilities through efficient spectrum exploitation. This offers the user the promise of greater flexibility, seamless roaming possible on different networks, countries, frequencies, etc. It requires true paradigm shift i.e., liberalization over a wide band of spectrum as well as a growth path to more and greater capability. This work contributes towards the design and implementation of an open spectrum access (OSA) feature to unlicensed users thus offering a frequency agile radio platform that is capable of performing spectrum sensing over a wideband. Thus, an ultra-wideband (UWB) radio, which has the intelligence of spectrum sensing only, unlike the cognitive radio with complete intelligence, is named as a Smart Software Radio (SSR). The spectrum sensing mechanism is implemented based on energy detection. Simulation results show the accuracy and validity of this method.

Keywords: cognitive radio, energy detection, software radio, spectrum sensing

Procedia PDF Downloads 415

Authors: Vithaya Intaraphimol

Abstract:

This study investigates the relationship between employee’s job satisfaction and job performance of hotel’s employees in five-star hotels in Bangkok. This study used self-administration data collection from a sample of 400 employees of five-star hotels in Bangkok. The results indicated that there was a relationship between job satisfaction and job performance. In addition, dysfunctional conflict was related negatively to job satisfaction; meanwhile, functional conflict was related positively to job satisfaction. Moreover, there was a positive relationship between integrating, obliging, avoiding and compromising style and job satisfaction; however; dominating style had a negative relationship with job satisfaction and proved that job satisfaction tend to increase the positive emotion on job satisfaction in the service setting, consequently, employee has ability to deal with problems with more effectively and predictor of job satisfaction due to employee who satisfied with the job seems to remain in the organization and appearing to gain rewarding beneficial.

Keywords: conflict management, job satisfaction, job performance, service sector

Procedia PDF Downloads 268

Authors: Sneha Leslie

Abstract:

The current situation in the cyber world is that crimes performed by Botnets are increasing and the masterminds (botmaster) are not detectable easily. The botmaster in the botnet compromises the legitimate host machines in the network and make them bots or zombies to initiate the cyber-attacks. This paper will focus on the live detection of the botmaster in the network by using the strong framework 'metasploit', when distributed denial of service (DDOS) attack is performed by the botnet. The affected victim machine will be continuously monitoring its incoming packets. Once the victim machine gets to know about the excessive count of packets from any IP, that particular IP is noted and details of the noted systems are gathered. Using the vulnerabilities present in the zombie machines (already compromised by botmaster), the victim machine will compromise them. By gaining access to the compromised systems, applications are run remotely. By analyzing the incoming packets of the zombies, the victim comes to know the address of the botmaster. This is an effective and a simple system where no specific features of communication protocol are considered.

Keywords: bonet, DDoS attack, network security, detection system, metasploit framework

Procedia PDF Downloads 250

Authors: Marko Batic, Nikola Tomasevic, Sanja Vranes

Abstract:

One of the strongholds in the ubiquitous efforts related to the energy conservation and energy efficiency improvement is represented by the retrofit of high energy consumers in buildings. In general, HVAC systems represent the highest energy consumers in buildings. However they usually suffer from mal-operation and/or malfunction, causing even higher energy consumption than necessary. Various Fault Detection and Diagnosis (FDD) systems can be successfully employed for this purpose, especially when it comes to the application at a single device/unit level. In the case of more complex systems, where multiple devices are operating in the context of the same building, significant energy efficiency improvements can only be achieved through application of comprehensive FDD systems relying on additional higher level knowledge, such as their geographical location, served area, their intra- and inter- system dependencies etc. This paper presents a comprehensive FDD system that relies on the utilization of common knowledge repository that stores all critical information. The discussed system is deployed as a test-bed platform at the two at Fiumicino and Malpensa airports in Italy. This paper aims at presenting advantages of implementation of the knowledge base through the utilization of ontology and offers improved functionalities of such system through examples of typical queries and reasoning that enable derivation of high level energy conservation measures (ECM). Therefore, key SPARQL queries and SWRL rules, based on the two instantiated airport ontologies, are elaborated. The detection of high level irregularities in the operation of airport heating/cooling plants is discussed and estimation of energy savings is reported.

Keywords: airport ontology, knowledge management, ontology modeling, reasoning

Procedia PDF Downloads 529

Authors: Lotfi O. Gargab, Ruichong R. Zhang

Abstract:

A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002.

Keywords: system identification, continuous-discrete mass modeling, damage detection, post-earthquake

Procedia PDF Downloads 367

Authors: Dhanuja S. Patil, Sanjay B. Waykar

Abstract:

Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

Procedia PDF Downloads 318

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 58

Authors: Raghavi C. Janaswamy

Abstract:

In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

Procedia PDF Downloads 82

Authors: Irfan Mehmood

Abstract:

The goal of this paper is to examine Toni Morrison's novels Beloved and The Bluest Eye from a cultural materialistic perspective. The history and society of African Americans provide the inspiration for the stories of Beloved and The Bluest Eye. The cultural materialist elements and characteristics of Morrison's literary text will be highlighted in this study. The topic covered in this paper will include racism, gender discrimination, social class differences, and slavery in the text. In other words, the study will focus on the underrepresented groups in society, including women, slaves, and Afro-Americans. In this aspect, Toni Morrison is a fantastic writer whose works are full of diverse races. Morrison uses her incredibly well-informed language and well-produced stories to attempt to illuminate many facets of American life. She establishes a distinctive style of writing that sharply contrasts the suffering and enslavement of Afro-Americans with the traditional writings of Euro-American authors. Morrison shows a profound understanding of the exploitation of Afro-Americans in terms of race, gender, and class conflict in Beloved and The Bluest Eye. A unique culture and the history of a typically ignored set of people whose minds and societies have been permanently changed by class, racial, and gender discrimination were introduced through the study of Morrison's chosen novels. Toni Morrison places a lot of emphasis on the marginalized members of society, particularly in terms of class, ethnicity, and gender, because the majority of the key characters in her book are black. Therefore, the purpose of this essay is to concentrate on the culturally materialistic elements of Morrison's Beloved and The Bluest Eye and to ascertain the author's position on these minorities.

Keywords: race, slavery, social class, Toni Morrison, African American culture

Procedia PDF Downloads 66

Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

Abstract:

Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

Procedia PDF Downloads 178

Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

Abstract:

In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: Haraz basin, change detection, land-use, satellite data

Procedia PDF Downloads 407

Authors: Alaa Abdullah Altaee

Abstract:

This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.

Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication

Procedia PDF Downloads 114

Authors: Brianne Nichols, John A. Parkinson

Abstract:

Positive Psychology has provided a rich understanding of the beneficial effects of positive emotions in relation to optimal functioning, and research has been devoted to promote states of positive feeling and thinking. While this is a worthwhile pursuit, positive emotions are not useful in all contexts - some situations may require the individual to make use of their negative emotions to reach a desired end state. To account for the potential value of a wider range of emotional experiences that are common to the human condition, Positive Psychology needs to expand its horizons and investigate how individuals achieve positive outcomes using varied means. The current research seeks to understand the positive psychology of fear of failure (FF), which is a commonly experienced negative emotion relevant to most life domains. On the one hand, this emotion has been linked with avoidance motivation and self-handicap behaviours, on the other; FF has been shown to act as a drive to move the individual forward. To fully capture the depth of this highly subjective emotional experience and understand the circumstances under which FF may be adaptive, this study adopted a mixed methods design using SenseMaker; a web-based tool that combines the richness of narratives with the objectivity of numerical data. Two hundred participants consisting mostly of undergraduate university students shared a story of a time in the recent past when they feared failure of achieving a valued goal. To avoid researcher bias in the interpretation of narratives, participants self-signified their stories in a tagging system that was based on researchers’ aim to explore the role of past failures, the cognitive, emotional and behavioural profile of individuals high and low in FF, and the relationship between these factors. In addition, the role of perceived personal control and self-esteem were investigated in relation to FF using self-report questionnaires. Results from quantitative analyses indicated that individuals with high levels of FF, compared to low, were strongly influenced by past failures and preoccupied with their thoughts and emotions relating to the fear. This group also reported an unwillingness to accept their internal experiences, which in turn was associated with withdrawal from goal pursuit. Furthermore, self-esteem was found to mediate the relationship between perceived control and FF, suggesting that self-esteem, with or without control beliefs, may have the potential to buffer against high FF. It is hoped that the insights provided by the current study will inspire future research to explore the ways in which ‘acceptance’ may help individuals keep moving towards a goal despite the presence of FF, and whether cultivating a non-contingent self-esteem is the key to resilience in the face of failures.

Keywords: fear of failure, goal-pursuit, negative emotions, optimal functioning, resilience

Procedia PDF Downloads 190

Authors: Zzibu Mark Brian

Abstract:

As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

Procedia PDF Downloads 24

Authors: Abid Fida Masih

Abstract:

Forced degradation study of Rifaximin was conducted to determine the stability indicating potential of HPLC testing method for detection of Rifaximin in formulated tablets to be employed for quality control and stability testing. The questioned method applied with mobile phase methanol: water (70:30), 5µm, 250 x 4.6mm, C18 column, wavelength 293nm and flow rate of 1.0 ml/min. Forced degradation study was performed under oxidative, acidic, basic, thermal and photolytic conditions. The applied method successfully determined the degradation products after acidic and basic degradation without interfering with Rifaximin detection. Therefore, the method was said to be stability indicating and can be applied for quality control and stability testing of Rifaxmin tablets during its shelf life.

Keywords: forced degradation, high-performance liquid chromatography, method validation, rifaximin, stability indicating method

Procedia PDF Downloads 300

Authors: Jahangir Ahmad Rather, Emad A. Khudaish, Ahsanulhaq Qurashi, Palanisamy Kannan

Abstract:

Chemical modification and assembling of fullerenes are fundamentally important for the application of fullerenes as functional molecules and in molecular devices and organic electronic devices. We have synthesized fullerene nanorods C60NRs conjugate via liquid-liquid interface and the synthesized C60NRs was characterized by FTIR spectroscopy, field emission electron microscopy (FESEM) and X-ray diffraction techniques. The C60NRs were immobilized on glassy carbon electrode via surface bound diazonium salts as an impact strategy. This method involves electrografting of p–nitrophenyl to give GCE–Ph–NO2 and then the terminal nitro-group was chemically reduced to GCE–Ph–NH2 in a presence of sodium borohydride/gold–polyaniline nanocomposite (NaBH4/Au–PANI). The Au–PANI composite was synthesized and characterized by FTIR, UV-vis, SEM and EDX techniques. The C60NRs were immobilized on GCE–Ph–NH2 via amination reaction which involves N-H addition across a π-bond on [60] fullerene. The immobilized C60NRs/GCE was subjected to electrochemical reduction in 1.0 M KOH to yield ERC60NRs/GCE sensor. The developed sensor shows high electrocatalytic activity for the detection of ethylparaben (EP) over a concentration range from 0.01 to 0.52 µM with a detection limit (LOD) 3.8 nM. The amount of EP present in the nourishing repair cream (OlAY®) was determined by standard addition method at the developed ERC60NRs/GCE sensor. The total concentration of EP was found to be 0.011 µM (0.1%) and is within the permissible limit of 0.19 % EP in cosmetics according to the European scientific committee (SCCS) on consumer safety on 22 March 2011 (SCCS/1348/11).

Keywords: diazonium salt reduction, ethylparaben (EP), endocrine disruptor, fullerene nanorods (C60NRs), gold–polyaniline nanocomposite (Au–PANI)

Procedia PDF Downloads 227

Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

Abstract:

To address the problem that the FM continuous-wave radar (FMCW) extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a new detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a BP neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise and accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal-to-noise ratio of the sign signals.

Keywords: frequency modulated continuous wave radar, ICEEMDAN, BP neural network, vital signs signal

Procedia PDF Downloads 158

Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

Abstract:

Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

Procedia PDF Downloads 319

Authors: V. Sai Geethika, Sai Snehitha Yadavalli, Swati Ghosh Acharyya

Abstract:

This study involves a single element and simultaneous electrochemical detection of heavy metal ions through square wave anodic stripping voltammetry. A glassy carbon electrode was used to detect and quantify heavy metals such as As(III), Hg(II), Cr(VI) ions in water. Under optimized conditions, peak separation was obtained by varying concentrations, scan rates, and temperatures. As (III), Hg (II), Cr (III) were simultaneously detected with GCE. Several analytical methods, such as inductively coupled plasma mass spectroscopy (ICP-MS), atomic absorption spectroscopy (AAS), were used previously to detect heavy metal ions, which are authentic but are not good enough for online monitoring due to the bulkiness of the equipment. The study provides a good alternative that is simple, more efficient, and low-cost, involving a portable potentiostat. Heavy metals having different oxidation states can be detected by anodic stripping voltammetry. This method can be easily integrated with electronics. Square wave Anodic stripping voltammetry is used with a potential range of -2.5 V – 2.5 V for single ion detection by a three-electrode cell consisting of silver/silver chloride(Ag/AgCl) as reference and platinum (Pt) counter and glassy carbon (GCE) working electrodes. All three ions are optimized by varying the parameters like concentration, scan rate, pH, temperature, and all these optimized parameters were used for studying the effects of simultaneous detection. The procedure involves preparing an electrolyte using deionized water, cleaning the surface of GCE, depositing the ions by applying the redox potentials obtained from cyclic voltammetry (CV), and then detecting by applying oxidizing potential, i.e., stripping voltage. So this includes ASV techniques such as open-circuit voltage (OCV), chronoamperometry (CA), and square wave voltammetry (SWV). Firstly, the concentration of the ions varied from 50 ppb to 5000 ppb, and an optimum concentration was determined where the three ions were detected. A concentration of 400 ppb was used while varying the temperatures in the range of 25°C – 45°C. Optimum peak intensity was obtained at a temperature of 30°C with a low scan rate of 0.005 V-s⁻¹. All the parameters were optimized, and several effects have been noticed while three ions As(II), Cr(III), Hg(II) were detected alone and simultaneously.

Keywords: Arsenic(III), Chromium(III), glassy carbon electrode, Mercury (II), square wave anodic stripping voltammetry

Procedia PDF Downloads 81

Authors: Jean-François Caron

Abstract:

The current attempts to develop what we can call 'super soldiers' are problematic in many regards. This is what this text will try to explore by concentrating primarily on the repercussions of this technology and medical research on the physical and psychological integrity of soldiers. It argues that medicines or technologies may affect soldiers’ psychological and mental features and deprive them of their capacity to reflect upon their actions as autonomous subjects and that such a possibility entails serious moral as well as judicial consequences.

Keywords: military research, super soldiers, involuntary intoxication, criminal responsibility

Procedia PDF Downloads 347

Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

Abstract:

Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

Procedia PDF Downloads 157

Authors: Retno Supriyanti, Best Leader Nababan, Yogi Ramadhani, Wahyu Siswandari

Abstract:

Blood cell morphology is an important parameter in a hematology test. Currently, in developing countries, a lot of hematology is done manually, either by physicians or laboratory staff. According to the limitation of the human eye, examination based on manual method will result in a lower precision and accuracy. In addition, the hematology test by manual will further complicate the diagnosis in some areas that do not have competent medical personnel. This research aims to develop a simple tool in the detection of blood cell morphology-based computer. In this paper, we focus on the detection of the outer contour of leukocytes. The results show that the system that we developed is promising for detecting blood cell morphology automatically. It is expected, by implementing this method, the problem of accuracy, precision and limitations of the medical staff can be solved.

Keywords: morphology operation, developing countries, hematology test, limitation of medical personnel

Procedia PDF Downloads 327