Search results for: neural signal recording

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

Procedia PDF Downloads 227

Authors: Abdulaziz Alakeel, Abdulrahman Alomair, Mohammed Fouda

Abstract:

Introduction: Methotrexate (MTX) is an antimetabolite used to treat multiple conditions, including neoplastic diseases, severe psoriasis, and rheumatoid arthritis. Skin cancer is the out-of-control growth of abnormal cells in the epidermis, the outermost skin layer, caused by unrepaired DNA damage that triggers mutations. These mutations lead the skin cells to multiply rapidly and form malignant tumors. The aim of this review is to evaluate the risk of skin cancer associated with the use of methotrexate and to suggest regulatory recommendations if required. Methodology: Signal Detection team at Saudi Food and Drug Authority (SFDA) performed a safety review using National Pharmacovigilance Center (NPC) database as well as the World Health Organization (WHO) VigiBase, alongside with literature screening to retrieve related information for assessing the causality between skin cancer and methotrexate. The search conducted in July 2020. Results: Four published articles support the association seen while searching in literature, a recent randomized control trial published in 2020 revealed a statistically significant increase in skin cancer among MTX users. Another study mentioned methotrexate increases the risk of non-melanoma skin cancer when used in combination with immunosuppressant and biologic agents. In addition, the incidence of melanoma for methotrexate users was 3-fold more than the general population in a cohort study of rheumatoid arthritis patients. The last article estimated the risk of cutaneous malignant melanoma (CMM) in a cohort study shows a statistically significant risk increase for CMM was observed in MTX exposed patients. The WHO database (VigiBase) searched for individual case safety reports (ICSRs) reported for “Skin Cancer” and 'Methotrexate' use, which yielded 121 ICSRs. The initial review revealed that 106 cases are insufficiently documented for proper medical assessment. However, the remaining fifteen cases have extensively evaluated by applying the WHO criteria of causality assessment. As a result, 30 percent of the cases showed that MTX could possibly cause skin cancer; five cases provide unlikely association and five un-assessable cases due to lack of information. The Saudi NPC database searched to retrieve any reported cases for the combined terms methotrexate/skin cancer; however, no local cases reported up to date. The data mining of the observed and the expected reporting rate for drug/adverse drug reaction pair is estimated using information component (IC), a tool developed by the WHO Uppsala Monitoring Centre to measure the reporting ratio. Positive IC reflects higher statistical association, while negative values translated as a less statistical association, considering the null value equal to zero. Results showed that a combination of 'Methotrexate' and 'Skin cancer' observed more than expected when compared to other medications in the WHO database (IC value is 1.2). Conclusion: The weighted cumulative pieces of evidence identified from global cases, data mining, and published literature are sufficient to support a causal association between the risk of skin cancer and methotrexate. Therefore, health care professionals should be aware of this possible risk and may consider monitoring any signs or symptoms of skin cancer in patients treated with methotrexate.

Keywords: methotrexate, skin cancer, signal detection, pharmacovigilance

Procedia PDF Downloads 103

Authors: Vahid Tabrizi, Reza GHasemi, Ahmadreza Vali

Abstract:

This paper presents robust nonlinear control law for a quadrotor UAV using fast terminal sliding mode control. Fast terminal sliding mode idea is used for introducing a nonlinear sliding variable that guarantees the finite time convergence in sliding phase. Then, in reaching phase for removing chattering and producing smooth control signal, continuous approximation idea is used. Simulation results show that the proposed algorithm is robust against parameter uncertainty and has better performance than conventional sliding mode for controlling a quadrotor UAV.

Keywords: quadrotor UAV, fast terminal sliding mode, second order sliding mode t

Procedia PDF Downloads 527

Authors: J. Y. Tan, L. C. Lum, M. G. Lee, S. Mansouri, K. Hapgood, X. D. Chen, M. W. Woo

Abstract:

Folic acid (FA) is known to be an important supplement to prevent neural tube defect (NTD) in pregnant women. Similar to some commercial formulations, sodium bicarbonate solution is used as a solvent for FA. This work uses the antisolvent vapor precipitation (AVP), incorporating ethanol vapor as the convective drying medium in place of air to produce branch-like micro-structure FA particles. Interestingly, the dissolution rate of the resultant particle is 2-3 times better than the particle produce from conventional air drying due to the higher surface area of particles produced. The higher dissolution rate could possibly improve the delivery and absorption of FA in human body. This application could potentially be extended to other commercial products, particularly in less soluble drugs to improve its solubility.

Keywords: absorption, antisolvent vapor precipitation, dissolution rate, folic acid

Procedia PDF Downloads 432

Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

Abstract:

This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

Procedia PDF Downloads 124

Authors: C. U. Om Kumar, S. Kishore, A. Geetha

Abstract:

An Operating system (OS) is software that manages computer hardware and software resources by providing services to computer programs. One of the important user expectations of the operating system is to provide the practice of defending information from unauthorized access, disclosure, modification, inspection, recording or destruction. Operating system is always vulnerable to the attacks of malwares such as computer virus, worm, Trojan horse, backdoors, ransomware, spyware, adware, scareware and more. And so the anti-virus software were created for ensuring security against the prominent computer viruses by applying a dictionary based approach. The anti-virus programs are not always guaranteed to provide security against the new viruses proliferating every day. To clarify this issue and to secure the computer system, our proposed expert system concentrates on authorizing the processes as wanted and unwanted by the administrator for execution. The Expert system maintains a database which consists of hash code of the processes which are to be allowed. These hash codes are generated using MD5 message-digest algorithm which is a widely used cryptographic hash function. The administrator approves the wanted processes that are to be executed in the client in a Local Area Network by implementing Client-Server architecture and only the processes that match with the processes in the database table will be executed by which many malicious processes are restricted from infecting the operating system. The add-on advantage of this proposed Expert system is that it limits CPU usage and minimizes resource utilization. Thus data and information security is ensured by our system along with increased performance of the operating system.

Keywords: virus, worm, Trojan horse, back doors, Ransomware, Spyware, Adware, Scareware, sticky software, process table, MD5, CPU usage and resource utilization

Procedia PDF Downloads 409

Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Ítalo de Pontes Oliveira

Abstract:

This paper presents a analysis of performance the Received Strength Signal Indicator (RSSI) to Wireless Sensor Networks, with a finality of investigate a behavior of ZigBee devices operating into real environments. The test of performance was realize using two Series 1 ZigBee Module and two modules of development Arduino Uno R3, evaluating in this form a measurements of RSSI into environments like places of sports, preservation forests and water reservoir.

Keywords: wireless sensor networks, RSSI, Arduino, environments

Procedia PDF Downloads 602

Authors: Ima Rahmawati, Nur Hafizul Kalam

Abstract:

Development of industrial and economic sectors in various countries very rapidly caused raising the greenhouse gas (GHG) emissions. Greenhouse gases are dominated by carbon dioxide (CO2) and methane (CH4) in the atmosphere that make the surface temperature of the earth always increase. The increasing gases caused by incomplete combustion of fossil fuels such as petroleum and coals and also high rate of deforestation. Yogyakarta Special Province which every year always become tourist destination, has a great potency in increasing of greenhouse gas emissions mainly from the incomplete combustion. One of effort to reduce the concentration of gases in the atmosphere is keeping and empowering the existing forests in the Province of Yogyakarta, especially forest in Kulonprogro is to be maintained the greenness so that it can absorb and store carbon maximally. Remote sensing technology can be used to determine the ability of forests to absorb carbon and it is connected to the density of vegetation. The purpose of this study is to determine the density of the biomass of forest vegetation and determine the ability of forests to store carbon through Photo-interpretation and Geographic Information System approach. Remote sensing imagery that used in this study is LANDSAT 8 OLI year 2015 recording. LANDSAT 8 OLI imagery has 30 meters spatial resolution for multispectral bands and it can give general overview the condition of the carbon stored from every density of existing vegetation. The method is the transformation of vegetation index combined with allometric calculation of field data then doing regression analysis. The results are model maps of density and capability level of forest vegetation in Kulonprogro, Yogyakarta in storing carbon.

Keywords: remote sensing, carbon, kulonprogo, forest vegetation, vegetation index

Procedia PDF Downloads 383

Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

Abstract:

Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

Procedia PDF Downloads 501

Authors: Pierre Tize Mha, Mohammad Jahazi, Amèvi Togne, Olivier Pantalé

Abstract:

Large-size forged blocks made of medium carbon high-strength steels are extensively used in the automotive industry as dies for the production of bumpers and dashboards through the plastic injection process. The manufacturing process of the large blocks starts with ingot casting, followed by open die forging and a quench and temper heat treatment process to achieve the desired mechanical properties and numerical simulation is widely used nowadays to predict these properties before the experiment. But the temperature gradient inside the specimen remains challenging in the sense that the temperature before loading inside the material is not the same, but during the simulation, constant temperature is used to simulate the experiment because it is assumed that temperature is homogenized after some holding time. Therefore to be close to the experiment, real distribution of the temperature through the specimen is needed before the mechanical loading. Thus, We present here a robust algorithm that allows the calculation of the temperature gradient within the specimen, thus representing a real temperature distribution within the specimen before deformation. Indeed, most numerical simulations consider a uniform temperature gradient which is not really the case because the surface and core temperatures of the specimen are not identical. Another feature that influences the mechanical properties of the specimen is recrystallization which strongly depends on the deformation conditions and the type of deformation like Upsetting, Cogging...etc. Indeed, Upsetting and Cogging are the stages where the greatest deformations are observed, and a lot of microstructural phenomena can be observed, like recrystallization, which requires in-depth characterization. Complete dynamic recrystallization plays an important role in the final grain size during the process and therefore helps to increase the mechanical properties of the final product. Thus, the identification of the conditions for the initiation of dynamic recrystallization is still relevant. Also, the temperature distribution within the sample and strain rate influence the recrystallization initiation. So the development of a technique allowing to predict the initiation of this recrystallization remains challenging. In this perspective, we propose here, in addition to the algorithm allowing to get the temperature distribution before the loading stage, an analytical model leading to determine the initiation of this recrystallization. These two techniques are implemented into the Abaqus finite element software via the UAMP and VUHARD subroutines for comparison with a simulation where an isothermal temperature is imposed. The Artificial Neural Network (ANN) model to describe the plastic behavior of the material is also implemented via the VUHARD subroutine. From the simulation, the temperature distribution inside the material and recrystallization initiation is properly predicted and compared to the literature models.

Keywords: dynamic recrystallization, finite element modeling, artificial neural network, numerical implementation

Procedia PDF Downloads 70

Authors: Aishrith Rao

Abstract:

Human activity recognition is an important aspect of video analytics, and many approaches have been recommended to enable action recognition. In this approach, the model is used to identify the action of the multiple people in the frame and classify them accordingly. A few approaches use RNNs and 3D CNNs, which are computationally expensive and cannot be trained with the small datasets which are currently available. Multi-person action recognition has been performed in order to understand the positions and action of people present in the video frame. The size of the video frame can be adjusted as a hyper-parameter depending on the hardware resources available. OpenPose has been used to calculate pose estimate using CNN to produce heap-maps, one of which provides skeleton features, which are basically joint features. The features are then extracted, and a classification algorithm can be applied to classify the action.

Keywords: human activity recognition, computer vision, pose estimates, convolutional neural networks

Procedia PDF Downloads 123

Authors: Samhita Bharadwaj

Abstract:

This is an empirical study of classifiers in Assamese and Bodo, two genetically unrelated languages of India. The objective of the paper is to address the language contact between Assamese and Bodo as reflected in classifiers. The data has been collected through fieldwork in Bodo recording narratives and folk tales and eliciting specific data from the speakers. The data for Assamese is self-produced as native speaker of the language. Assamese is the easternmost New-Indo-Aryan (henceforth NIA) language mainly spoken in the Brahmaputra valley of Assam and some other north-eastern states of India. It is the lingua franca of Assam and is creolised in the neighbouring state of Nagaland. Bodo, on the other hand, is a Tibeto-Burman (henceforth TB) language of the Bodo-Garo group. It has the highest number of speakers among the TB languages of Assam. However, compared to Assamese, it is still a lesser documented language and due to the prestige of Assamese, all the Bodo speakers are fluent bi-lingual in Assamese, though the opposite isn’t the case. With this context, classifiers, a characteristic phenomenon of TB languages, but not so much of NIA languages, presents an interesting case study on language contact caused by bilingualism. Assamese, as a result of its language contact with the TB languages which are rich in classifiers; has developed the richest classifier system among the IA languages in India. Yet, as a part of rampant borrowing of Assamese words and patterns into Bodo; Bodo is seen to borrow even Assamese classifiers into its system. This paper analyses the borrowed classifiers of Bodo and finds the route of this borrowing phenomenon in the number system of the languages. As the Bodo speakers start replacing the higher numbers from five with Assamese ones, they also choose the Assamese classifiers to attach to these numbers. Thus, the partial loss of number in Bodo as a result of language contact and bilingualism in Assamese is found to be the reason behind the borrowing of classifiers in Bodo. The significance of the study lies in exploring an interesting aspect of language contact in Assam. It is hoped that this will attract further research on bilingualism and classifiers in Assam.

Keywords: Assamese, bi-lingual, Bodo, borrowing, classifier, language contact

Procedia PDF Downloads 204

Authors: László Schmidt

Abstract:

In the context of artificial intelligence, we need to pay primary and particular attention to ethical principles not only in the design process but also during the application process. According to the European Commission's Ethical Guidelines, AI must have three main characteristics: it must be legal, ethical and stabil. We must never lose sight of the ethical principles because we risk that this new technology will not help democratic decision-making under the rule of law, but will, on the contrary, destroy it. The rapid spread and use of artificial intelligence poses an enormous challenge to both lawmaking and law enforcement. On legislation because AI permeates many areas of our daily lives that the legislator must regulate. We can see how challenging it is to regulate e.g., selfdriving cars/taxis/vans etc. Not to mention, more recently, cryptocurrencies and Chat GPT, the use of which also requires legislative intervention, from copyright to scientific use and even law of succession. Artificial intelligence also poses an extraordinary challenge to law enforcement. In criminal cases, police and prosecutors can make great use of AI in investigations, e.g. in forensics, DNA samples, reconstruction, identification, etc. But it can also be of great help in the detection of crimes committed in cyberspace. In criminal or civil court proceedings, AI can also play a major role in the evaluation of evidence and proof. For example, a photo or video or audio recording could be immediately revealed as genuine or fake. Likewise, the authenticity or falsification of a document could be determined much more quickly and cheaply than with current procedure (expert witnesses). Neither the current Hungarian Civil Procedure Act nor the Criminal Procedure Act allows the use of artificial intelligence in the evidentiary process. However, this should be changed. To use this technology in court proceedings would be very useful. The procedures would be faster, simpler, and therefore cheaper. Artificial intelligence could also replace much of the work of expert witnesses. Its introduction into judicial procedures would certainly be justified, but with due respect for human rights, the right to a fair trial and other democratic and rule of law guarantees.

Keywords: artificial intelligence, judiciary, Hungarian, court practice

Procedia PDF Downloads 62

Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza

Abstract:

There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Keywords: face recognition, labeled faces in the wild (LFW) database, random local descriptor (RLD), random features

Procedia PDF Downloads 341

Authors: Fabiano Araujo Soares, Sauro Emerick Salomoni, Joao Paulo Lima da Silva, Igor Luiz Moura, Adson Ferreira da Rocha

Abstract:

This paper presents a tool developed in the Matlab platform. It was developed to simplify the analysis of surface electromyography signals (S-EMG) in a way accessible to users that are not familiarized with signal processing procedures. The tool receives data by commands in window fields and generates results as graphics and excel tables. The underlying math of each S-EMG estimator is presented. Setup window and result graphics are presented. The tool was presented to four non-engineer users and all of them managed to appropriately use it after a 5 minutes instruction period.

Keywords: S-EMG estimators, electromyography, surface electromyography, ARV, RMS, MDF, MNF, CV

Procedia PDF Downloads 536

Authors: A. Manallah, C. Meier

Abstract:

Confocal spectral interferometry (CSI) is an innovative optical method for determining microtopography of surfaces and thickness of transparent layers, based on the combination of two optical principles: confocal imaging, and spectral interferometry. Confocal optical system images at each instant a single point of the sample. The whole surface is reconstructed by plan scanning. The interference signal generated by mixing two white-light beams is analyzed using a spectrometer. In this work, five ‘rugotests’ of known standard roughnesses are investigated. The topography is then measured and illustrated, and the equivalent roughness is determined and compared with the standard values.

Keywords: confocal spectral interferometry, nondestructive testing, optical metrology, surface topography, roughness

Procedia PDF Downloads 257

Authors: Bernd Kiefer, Abraham Gebru Tesfay, Dietrich Klakow

Abstract:

The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. We achieve precision and recall values between 87% and 100% per class, and an average accuracy at 95.2%. We also study the effect of varying audio chunk size in the application phase of the models and find only a mild impact on performance.

Keywords: acoustic features, autonomous robots, feature extraction, terrain classification

Procedia PDF Downloads 349

Authors: Tae Jin Choi, Jong Ok Kim, Sang Min Jin, Gilwon Yoon

Abstract:

Analysis of EEG brainwave provides information on mental or emotional states. One of the particular states that can have various applications in human machine interface (HMI) is concentration. 8-channel EEG signals were measured and analyzed. The concentration index was compared during resting and concentrating periods. Among eight channels, locations the frontal lobe (Fp1 and Fp2) showed a clear increase of the concentration index during concentration regardless of subjects. The rest six channels produced conflicting observations depending on subjects. At this time, it is not clear whether individual difference or how to concentrate made these results for the rest six channels. Nevertheless, it is expected that Fp1 and Fp2 are promising locations for extracting control signal for HMI applications.

Keywords: concentration, EEG, human machine interface, biophysical

Procedia PDF Downloads 468

Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

Abstract:

This paper deals with a stabilization problem for multi-agent systems, when all agents in a multi-agent system receive the same broadcasting control signal and the controller can measure not each agent output but the sum of all agent outputs. It is analytically shown that when the sum of all agent outputs is bounded with a certain broadcasting controller for a given reference, each agent output is separately bounded:stabilization of the sum of agent outputs always results in the stability of every agent output. A numerical example is presented to illustrate our theoretic findings in this paper.

Keywords: broadcasting control, multi-agent system, transfer function, stabilization

Procedia PDF Downloads 365

Authors: Dhanashree Moghe, Roberta Bullingham, Rizwan Ahmed, Tarun Singhal

Abstract:

Aim: The NHS Bowel Screening Programme recommends the use of endoscopic tattooing for suspected malignant lesions that later require surgical or endoscopic localisation, using local protocols as guidance. This is in accordance with guidance from the BSG (The British Society of Gastroenterologists). We used a well-recognised local protocol as a standard to audit current tattooing practice in a large district general hospital with no current local guidelines. Method: A retrospective quantitative analysis of 50 patients who underwent segmental colonic resection for cancer over a 6-month period in 2021. We reviewed historic electronic endoscopy reports recording relevant data on tattoo indication and placement. Secondly, we carried out an anonymous survey of 16 independent lower GI endoscopists on self-reported details of their practice. Results: In our study, 28 patients (56%) had a tattoo placed at the time of their colonoscopy. Of these, only 53% (n=15) had the tattoo distal to the lesion, with the measured distance of the tattoo from the lesion only being documented in 8 reports. Only seven patients (25%) had a circumferential (4 quadrant) placement of the tattoo. 13 patients had lesions either in the caecum or rectum, locations deemed unnecessary as per BSG guidelines. Of the survey responses collected, there were four different protocols being used to guide practice. Only 50% of respondents placed tattoos at the correct distance from the lesion, and 83% placed the correct number of tattoos. Conclusion: There is a lack of standardisation of practices in colonic tattooing demonstrated in our study with incomplete compliance to our standard. The inadequate documentation of tattoo location can contribute to confusion and inaccuracy in the intraoperative localisation of lesions. This has the potential to increase operation length and morbidity. There is a need to standardise both technique and documentation in colonoscopic tattooing practice.

Keywords: colorectal cancer, endoscopic tattooing, colonoscopy, NHS BSCP

Procedia PDF Downloads 107

Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

Abstract:

Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

Procedia PDF Downloads 94

Authors: Sudeshna Chandra, Christian Gäbler, Christian Schliebe, Heinrich Lang

Abstract:

Highly branched dendrimers provide structural homogeneity, controlled composition, comparable size to biomolecules, internal porosity and multiple functional groups for conjugating reactions. Electro-active dendrimers containing multiple redox units have generated great interest in their use as electrode modifiers for development of biosensors. The electron transfer between the redox-active dendrimers and the biomolecules play a key role in developing a biosensor. Ferrocenes have multiple and electrochemically equivalent redox units that can act as electron “pool” in a system. The ferrocenyl-terminated polyamidoamine dendrimer is capable of transferring multiple numbers of electrons under the same applied potential. Therefore, they can be used for dual purposes: one in building a film over the electrode for immunosensors and the other for immobilizing biomolecules for sensing. Electrochemical immunosensor, thus developed, exhibit fast and sensitive analysis, inexpensive and involve no prior sample pre-treatment. Electrochemical amperometric immunosensors are even more promising because they can achieve a very low detection limit with high sensitivity. Detection of the cancer biomarkers at an early stage can provide crucial information for foundational research of life science, clinical diagnosis and prevention of disease. Elevated concentration of biomarkers in body fluid is an early indication of some type of cancerous disease and among all the biomarkers, IgG is the most common and extensively used clinical cancer biomarkers. We present an IgG (=immunoglobulin) electrochemical immunosensor using a newly synthesized redox-active ferrocenyl dendrimer of generation 2 (G2Fc) as glassy carbon electrode material for immobilizing the antibody. The electrochemical performance of the modified electrodes was assessed in both aqueous and non-aqueous media using varying scan rates to elucidate the reaction mechanism. The potential shift was found to be higher in an aqueous electrolyte due to presence of more H-bond which reduced the electrostatic attraction within the amido groups of the dendrimers. The cyclic voltammetric studies of the G2Fc-modified GCE in 0.1 M PBS solution of pH 7.2 showed a pair of well-defined redox peaks. The peak current decreased significantly with the immobilization of the anti-goat IgG. After the immunosensor is blocked with BSA, a further decrease in the peak current was observed due to the attachment of the protein BSA to the immunosensor. A significant decrease in the current signal of the BSA/anti-IgG/G2Fc/GCE was observed upon immobilizing IgG which may be due to the formation of immune-conjugates that blocks the tunneling of mass and electron transfer. The current signal was found to be directly related to the amount of IgG captured on the electrode surface. With increase in the concentration of IgG, there is a formation of an increasing amount of immune-conjugates that decreased the peak current. The incubation time and concentration of the antibody was optimized for better analytical performance of the immunosensor. The developed amperometric immunosensor is sensitive to IgG concentration as low as 2 ng/mL. Tailoring of redox-active dendrimers provides enhanced electroactivity to the system and enlarges the sensor surface for binding the antibodies. It may be assumed that both electron transfer and diffusion contribute to the signal transformation between the dendrimers and the antibody.

Keywords: ferrocenyl dendrimers, electrochemical immunosensors, immunoglobulin, amperometry

Procedia PDF Downloads 326

Authors: Rotondwa P. Gunununu, Mustapha Mohammed, Felix D. Dakora

Abstract:

Common bean is the most importantly high protein grain legume grown in Southern Africa for human consumption and income generation. Although common bean can associate with rhizobia to fix N₂ for bacterial use and plant growth, it is reported to be a poor nitrogen fixer when compared to other legumes. N₂ fixation can vary with legume species, genotype and rhizobial strain. Therefore, screening legume germplasm can reveal rhizobia/genotype combinations with high N₂-fixing efficiency for use by farmers. This study assessed symbiotic performance and N₂ fixation in 63 common bean genotypes under field conditions at Malkerns Station in Eswatini, using the ¹⁵N natural abundance technique. The shoots of common bean genotypes were sampled at a pod-filling stage, oven-dried (65oC for 72h), weighed, ground into a fine powder (0.50 mm sieve), and subjected to ¹⁵N/¹⁴N isotopic analysis using mass spectrometry. At maturity, plants from the inner rows were harvested for the determination of grain yield. The results revealed significantly higher modulation (p≤0.05) in genotypes MCA98 and CIM-RM01-97-8 relative to the other genotypes. Shoot N concentration was highest in genotype MCA 98, followed by KAB 10 F2.8-84, with most genotypes showing shoot N concentrations below 2%. Percent N derived from atmospheric N₂ fixation (%Ndfa) differed markedly among genotypes, with CIM-RM01-92-3 and DAB 174, respectively, recording the highest values of 66.65% and 66.22 % N derived from fixation. There were also significant differences in grain yield, with CIM-RM02-79-1 producing the highest yield (3618.75 kg/ha). These results represent an important contribution in the profiling of symbiotic functioning of common bean germplasm for improved N₂ fixation.

Keywords: nitrogen fixation, %Ndfa, ¹⁵N natural abundance, grain yield

Procedia PDF Downloads 205

Authors: R. Maher, D. Marchant, F. Fazel

Abstract:

Choking in sport has been defined as ‘an acute performance breakdown’, and is generally explained through a range of contributory antecedents, factors, and explanatory theories. The influence of mental antecedents on an athlete’s performance under pressure has been widely examined through numerous studies. Researchers have only recently begun to investigate the influence of physical effort and associated residual fatigue as a potential contributor to choking in sport. Consequently, the initial aim of the present study was to examine the extent to which both physical exertion and pressure affect free-throw shooting performance. It was hypothesized that the free-throw shooting scores would decline under manipulated conditions. Design and Methods: Using a within-subjects design, 50 student-athletes were assigned to four manipulated conditions: (a) higher pressure-running, (b) higher pressure-no running, (c) lower pressure-running, and (d) lower pressure-no running. The physical exertion was manipulated by including a 56 meter shuttle-run in two of the running conditions. The pressure was manipulated with the presence of an audience, video-recording, performance contingent rewards, and weighting successful shots in the higher pressure conditions. A repeated measure analysis of variance was used to analyse the data. Results: The free-throw performance significantly deteriorated under manipulated physical exertion F (1, 49) = 10.13, p = .003, ηp 2 = .17 and pressure conditions F (1, 49) = 5.25, p = .02, ηp 2 = .09. The lowest free-throw scores were observed in the higher pressure-running condition, whereas the highest free-throw scores were reported in the lower pressure-no running condition. Conclusions: Physical exertion and the associated residual fatigue were contributors to choking. The results of the present study herald a new concept in choking research and yield a practical platform for use by athletes, coaches, and sport psychologists to better manage the psychological and physiological aspects of performance under pressure.

Keywords: anxiety, basketball, choking, fatigue, free-throw shooting, physical exertion

Procedia PDF Downloads 272

Authors: Ying-Ming Su, Mei-Shu Huang

Abstract:

To mitigate the urban heat island effect has become a global issue facing the challenge of climate change. Through literature reviews, plant photosynthesis can reduce the carbon dioxide and mitigate the urban heat island effect relatively. Because there are not enough open space and park, green roof has become an important policy in Taiwan. We selected elementary school buildings in northern New Taipei City as research subjects since elementary school is asked priority to build green roof and important educational place to promote green roof concept. Testo 175-H1 recording device was used to record the temperature and humidity difference between roof surface and interior space below roof with and without green roof for the long-term. We also use questionnaire to investigate the awareness of comfort level of green roof and sensation of teachers and students of the elementary school. The results indicated the temperature of roof without greening was higher than that with greening about 2°C. But sometimes during noontime, the temperature of green roof was higher than that of non-green roof related to the character of the accumulation and dissipation of heat of greening probably. The temperature of interior space below green roof was normally lower than that without green roof about 1°C showed that green roof could lower the temperature. The humidity of the green roof was higher than the one without greening also indicated that green roof retained water better. Teachers liked to combine green roof concept in the curriculum, students wished all classes can take turns to maintain the green roof. Teachers and students that school had integrated green roof concept in the curriculum were more willing to participate in the maintenance work of green roof. Teachers and students who may access and touch the green roof can be more aware of the green roof benefit. We suggest architect to increase the accessibility and visibility of green roof, such as a part of the activity space. This idea can be a reference of the green roof curriculum design.

Keywords: comfort level, elementary school, green roof, heat island effect

Procedia PDF Downloads 405

Authors: Ramazan I. Kadiev, Arcady Ponosov

Abstract:

Mathematical models of gene regulatory networks can in many cases be described by ordinary differential equations with switching nonlinearities, where the initial value problem is ill-posed. Several regularization methods are known in the case of deterministic networks, but the presence of stochastic noise leads to several technical difficulties. In the presentation, it is proposed to apply the methods of the stochastic singular perturbation theory going back to Yu. Kabanov and Yu. Pergamentshchikov. This approach is used to regularize the above ill-posed problem, which, e.g., makes it possible to design stable numerical schemes. Several examples are provided in the presentation, which support the efficiency of the suggested analysis. The method can also be of interest in other fields of biomathematics, where differential equations contain switchings, e.g., in neural field models.

Keywords: ill-posed problems, singular perturbation analysis, stochastic differential equations, switching nonlinearities

Procedia PDF Downloads 181

Authors: Ioannis P. Panapakidis, Marios N. Moschakis

Abstract:

The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: deregulated energy market, forecasting, machine learning, system marginal price

Procedia PDF Downloads 198

Authors: Hamed Saremi

Abstract:

One of the challenges in manufacturing and service companies to provide a product or service is recognized Brand to consumers in target markets. They provide most of their processes under the same capacity. But the constant threat of devastating internal and external resources to prevent a rise Brands and more companies are recognizing the stages are bankrupt. This paper has tried to identify and analyze effective indicators of brand equity and focuses on indicators and presents a model of intelligent create a model to prevent possible damage. In this study identified indicators of brand equity based on literature study and according to expert opinions, set of indicators By techniques DEMATEL Then to used Multi-Step Adaptive Neural-Fuzzy Inference system (ANFIS) to design a multi-stage intelligent system for assessment of brand equity.

Keywords: anfis, dematel, brand, cosmetic product, brand value

Procedia PDF Downloads 393

Authors: Sung-Bok Choi, Hyun-Jun Shin, Hyoung-Kyu Song

Abstract:

This paper proposes a single relay selection scheme in cooperative communication. Decode and forward scheme is considered when a source node wants to cooperate with a single relay for data transmission. To use the proposed single relay selection scheme, the source node make a little different pattern signal which is not complex pattern and broadcasts it. The proposed scheme does not require the channel state information between the source node and candidates of the relay during the relay selection. Therefore, it is able to be used in many fields.

Keywords: relay selection, cooperative communication, df, channel codes

Procedia PDF Downloads 655

Authors: Scott Draper, Nat Benjanuvatra, Grant Landers, Terry Griffiths, Justin Geldard

Abstract:

Open water swimming has been an Olympic sport since 2008 and is growing in popularity world-wide as a low impact form of exercise. Unlike pool swimming, open water swimmers experience a range of different environmental conditions, including surface waves, variable water temperature, aquatic life, and ocean currents. This presentation will describe experimental research to investigate how freestyle swimming behaviour and performance is influenced by surface waves. A group of 12 swimmers were instructed to swim freestyle in the 54 m long wave flume located at The University of Western Australia’s Coastal and Offshore Engineering Laboratory. A variety of different regular waves were simulated, varying in height (up to 0.3 m), period (1.25 – 4s), and direction (with or against the swimmer). Swimmer’s velocity and acceleration, respectively, were determined from video recording and inertial sensors attached to five different parts of the swimmer’s body. The results illustrate how the swimmers stroke rate and the wave encounter frequency influence their forward speed and how particular wave conditions can benefit or hinder performance. Comparisons to simplified mathematical models provide insight into several aspects of performance, including: (i) how much faster swimmers can travel when swimming with as opposed to against the waves, and (ii) why swimmers of lesser ability are expected to be affected proportionally more by waves than elite swimmers. These findings have implications across the spectrum from elite to ‘weekend’ swimmers, including how they are coached and their ability to win (or just successfully complete) iconic open water events such as the Rottnest Channel Swim held annually in Western Australia.

Keywords: open water, surface waves, wave height/length, wave flume, stroke rate

Procedia PDF Downloads 97