Search results for: contextual toxicity detection

Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi

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In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.

Keywords: cardiac anomalies, ECG, HTM, real time anomaly detection

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Authors: Elena G. Salina, Vadim A. Makarov

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With the emergence of primary resistance to the current drugs and wide distribution of latent tuberculosis infection, a need for new compounds with a novel mode of action is growing steadily. Copper-mediated innate immunity and antibacterial toxicity propose novel strategies in TB drug discovery and development. Transcriptome of M. tuberculosis was obtained by RNA-seq, intracellular copper content was measured by ISP MS and complexes of 1-hydroxy-2-thiopyridines with copper were detected by HPLC.1-hydroxy-2-thiopyridine derivatives were found to be highly active in vitro against both actively growing and dormant non-culturable M. tuberculosis. Transcriptome response to 1-hydroxy-2-thiopyridines revealed signs of copper toxicity in M. tuberculosis bacilli. Indeed, Cu was found to accumulate inside cells treated with 1-hydroxy-2-thiopyridines. These compounds were found to form stable charged lipophylic complexes with Cu²⁺ ions which transport into mycobacterial cell. Subsequent metabolic destruction of the complex led to transformation of 1-hydroxy-2-thiopyridines into 2-methylmercapto-2-ethoxycarbonylpyridines, which did not possess antitubercular activity and releasing of free Cu²⁺ in the cytoplasm. 1-hydroxy-2-thiopyridines are a potent class of Cu-dependent inhibitors of M. tuberculosis which may control M. tuberculosis infection by impairment of copper homeostasis. Acknowledgment: This work was financially supported by the Ministry of Education and Science of the RussianFederation (Agreement No 14.616.21.0065; unique identifier RFMEFI61616X0065).

Keywords: copper toxicity, drug discovery, M. tuberculosis inhibitors, 2-thiopyridines

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security.In this paper we present different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection).

Keywords: intrusion detection, architectures, characteristic, tools, security

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Authors: Wafa' Slaibi Alsharafat

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Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

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Authors: Tatsuya Takino, Izuru Nomura, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

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We propose a method of detecting the craters from the image of the lunar surface. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) working group aiming at the pinpoint landing on the lunar surface and investigating scientific research. It is difficult to equip and use high-performance computers for the small space probe. So, it is necessary to use a small computer with an exclusive hardware such as FPGA. We have studied the crater detection using principal component analysis (PCA), In this paper, We implement detection algorithm into the FPGA, and the detection is performed on the data that was captured from the CMOS camera.

Keywords: crater detection, PCA, FPGA, image processing

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Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

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Authors: Rakhyun Kim, Sungho Tae

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Global environmental issues such as abnormal weathers due to global warming, resource depletion, and ecosystem distortions have been escalating due to rapid increase of population growth, and expansion of industrial and economic development. Accordingly, initiatives have been implemented by many countries to protect the environment through indirect regulation methods such as Environmental Product Declaration (EPD), in addition to direct regulations such as various emission standards. Following this trend, life cycle assessment (LCA) techniques that provide quantitative environmental information, such as Human Toxicity Potential (HTP), for buildings are being developed in the construction industry. However, at present, the studies on the environmental database of building materials are not sufficient to provide this support adequately. The purpose of this study is to analysis human toxicity potential of major building material production stage using life cycle assessment. For this purpose, the theoretical consideration of the life cycle assessment and environmental impact category was performed and the direction of the study was set up. That is, the major material in the global warming potential view was drawn against the building and life cycle inventory database was selected. The classification was performed about 17 kinds of substance and impact index, such as human toxicity potential, that it specifies in CML2001. The environmental impact of analysis human toxicity potential for the building material production stage was calculated through the characterization. Meanwhile, the environmental impact of building material in the same category was analyze based on the characterization impact which was calculated in this study. In this study, establishment of environmental impact coefficients of major building material by complying with ISO 14040. Through this, it is believed to effectively support the decisions of stakeholders to improve the environmental performance of buildings and provide a basis for voluntary participation of architects in environment consideration activities.

Keywords: human toxicity potential, major building material, life cycle assessment, production stage

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Authors: Emine G. Cansu Ergun

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Conjugated system based sensors for selective detection of metal ions have been taking attention during last two decades. Fluorescent sensors are the promising candidates for ion detection due to their high selectivity towards metal ions, and rapid response times. Detection of mercury in an environmenet is important since mercury is a toxic element for human. Beyond the maximum allowable limit, mercury may cause serious problems in human health by spreading into the atmosphere, water and the food chain. In this study, a quinoxaline and 3,4-ethylenedioxy thiophene based donor-acceptor-donor type conjugated molecule used as a fluorescent sensor for detecting the mercury ion in aqueous medium. Among other various cations, existence of mercury resulted in a full quenching of the fluorescence signal. Then, a paper based sensor is constructed and used for mercury detection. As a result it is concluded that the offering sensor is a good candidate for selective mercury detection in aqueous media both in solution and paper based forms.

Keywords: Conjugated molecules , fluorescence quenching, metal ion detection , sensors

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Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

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Potholes are a severe threat to road safety and a major contributing factor towards road distress. In the Indian context, they are a major road hazard. Timely detection of potholes and subsequent repair can prevent the roads from deteriorating. To facilitate the roadway authorities in the timely detection and repair of potholes, we propose a pothole detection methodology using convolutional neural networks. The YOLOv3 model is used as it is fast and accurate in comparison to other state-of-the-art models. You only look once v3 (YOLOv3) is a state-of-the-art, real-time object detection system that features multi-scale detection. A mean average precision(mAP) of 73% was obtained on a training dataset of 200 images. The dataset was then increased to 500 images, resulting in an increase in mAP. We further calculated the depth of the potholes using stereoscopic vision by reconstruction of 3D potholes. This enables calculating pothole volume, its extent, which can then be used to evaluate the pothole severity as low, moderate, high.

Keywords: CNN, pothole detection, pothole severity, YOLO, stereovision

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Authors: Tao Feng, Wei-Wei Zhang, Chang-Ming Ding

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Cross-site scripting (XSS) is one of the most popular WEB Attacking methods at present, and also one of the most risky web attacks. Because of the population of JavaScript, the scene of the cross site scripting attack is also gradually expanded. However, since the web application developers tend to only focus on functional testing and lack the awareness of the XSS, which has made the on-line web projects exist many XSS vulnerabilities. In this paper, different various techniques of XSS attack are analyzed, and a method automatically to detect it is proposed. It is easy to check the results of vulnerability detection when running it as a plug-in.

Keywords: XSS, no target attack platform, automatic detection，XSS detection

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

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Authors: Muhammad Ammar, Talha Ali, Abdul Basit, Bakhtawar Rajput, Zobia Sohail

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Music note detection is an area of study for the past few years and has its own influence in music file generation from sheet music. We proposed a method to detect music notes on sheet music using basic thresholding and blob detection. Subsequently, we created a notes dictionary using a semi-supervised learning approach. After notes detection, for each test image, the new symbols are added to the dictionary. This makes the notes detection semi-automatic. The experiments are done on images from a dataset and also on the captured images. The developed approach showed almost 100% accuracy on the dataset images, whereas varying results have been seen on captured images.

Keywords: music note, sheet music, optical music recognition, blob detection, thresholding, dictionary generation

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Authors: Hwan-Jun Choi, Sung-Bok Choi, Hyoung-Kyu Song

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Recently, among the MIMO-OFDM detection techniques, a lot of papers suggested V-BLAST scheme which can achieve high data rate. Therefore, the signal detection of MIMOOFDM system is important issue. In this paper, efficient iterative VBLAST detection technique is proposed in wireless communication system. The proposed scheme adjusts the number of candidate symbol and iterative scheme based on channel state. According to the simulation result, the proposed scheme has better BER performance than conventional schemes and similar BER performance of the QRD-M with iterative scheme. Moreover complexity of proposed scheme has 50.6 % less than complexity of QRD-M detection with iterative scheme. Therefore the proposed detection scheme can be efficiently used in wireless communication.

Keywords: MIMO-OFDM, V-BLAST, QR-decomposition, QRDM, DFE, iterative scheme, channel condition

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Authors: Majed Sanan, Mohammad Rammal, Wassim Rammal

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Today, security is a major concern. Intrusion Detection, Prevention Systems and Honeypot can be used to moderate attacks. Many researchers have proposed to use many IDSs ((Intrusion Detection System) time to time. Some of these IDS’s combine their features of two or more IDSs which are called Hybrid Intrusion Detection Systems. Most of the researchers combine the features of Signature based detection methodology and Anomaly based detection methodology. For a signature based IDS, if an attacker attacks slowly and in organized way, the attack may go undetected through the IDS, as signatures include factors based on duration of the events but the actions of attacker do not match. Sometimes, for an unknown attack there is no signature updated or an attacker attack in the mean time when the database is updating. Thus, signature-based IDS fail to detect unknown attacks. Anomaly based IDS suffer from many false-positive readings. So there is a need to hybridize those IDS which can overcome the shortcomings of each other. In this paper we propose a new approach to IDS (Intrusion Detection System) which is more efficient than the traditional IDS (Intrusion Detection System). The IDS is based on Honeypot Technology and Anomaly based Detection Methodology. We have designed Architecture for the IDS in a packet tracer and then implemented it in real time. We have discussed experimental results performed: both the Honeypot and Anomaly based IDS have some shortcomings but if we hybridized these two technologies, the newly proposed Hybrid Intrusion Detection System (HIDS) is capable enough to overcome these shortcomings with much enhanced performance. In this paper, we present a modified Hybrid Intrusion Detection System (HIDS) that combines the positive features of two different detection methodologies - Honeypot methodology and anomaly based intrusion detection methodology. In the experiment, we ran both the Intrusion Detection System individually first and then together and recorded the data from time to time. From the data we can conclude that the resulting IDS are much better in detecting intrusions from the existing IDSs.

Keywords: security, intrusion detection, intrusion prevention, honeypot, anomaly-based detection, signature-based detection, cloud computing, kfsensor

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Authors: Sheraz Gul

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The requirements for progressing a compound to clinical trials is well established and relies on the results from in-vitro and in-vivo animal tests to indicate that it is likely to be safe and efficacious when testing in humans. The typical data package required will include demonstrating compound safety, toxicity, bioavailability, pharmacodynamics (potential effects of the compound on body systems) and pharmacokinetics (how the compound is potentially absorbed, distributed, metabolised and eliminated after dosing in humans). If the desired criteria are met and the compound meets the clinical Candidate criteria and is deemed worthy of further development, a submission to regulatory bodies such as the US Food & Drug Administration for an exploratory Investigational New Drug Study can be made. The purpose of this study is to collect data to establish that the compound will not expose humans to unreasonable risks when used in limited, early-stage clinical studies in patients or normal volunteer subjects (Phase I). These studies are also designed to determine the metabolism and pharmacologic actions of the drug in humans, the side effects associated with increasing doses, and, if possible, to gain early evidence on their effectiveness. In order to reach the above goals, we have developed a pre-clinical high throughput Absorption, Distribution, Metabolism and Excretion–Toxicity (ADME–Toxicity) panel of assays to identify compounds that are likely to meet the Lead and Candidate compound acceptance criteria. This panel includes solubility studies in a range of biological fluids, cell viability studies in cancer and primary cell-lines, mitochondrial toxicity, off-target effects (across the kinase, protease, histone deacetylase, phosphodiesterase and GPCR protein families), CYP450 inhibition (5 different CYP450 enzymes), CYP450 induction, cardio-toxicity (hERG) and gene-toxicity. This panel of assays has been applied to multiple compound series developed in a number of projects delivering Lead and clinical Candidates and examples from these will be presented.

Keywords: absorption, distribution, metabolism and excretion–toxicity , drug discovery, food and drug administration , pharmacodynamics

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Authors: Olivia A. Kjorlien, Maryam Asghari, Farshid Alizadeh-Shabdiz

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The goal of this paper is to investigate the impact of mosaic augmentation on the performance of object detection solutions. To carry out the study, YOLOv4 and YOLOv4-Tiny models have been selected, which are popular, advanced object detection models. These models are also representatives of two classes of complex and simple models. The study also has been carried out on two categories of objects, simple and complex. For this study, YOLOv4 and YOLOv4 Tiny are trained with and without mosaic augmentation for two sets of objects. While mosaic augmentation improves the performance of simple object detection, it deteriorates the performance of complex object detection, specifically having the largest negative impact on the false positive rate in a complex object detection case.

Keywords: accuracy, false positives, mosaic augmentation, object detection, YOLOV4, YOLOV4-Tiny

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Authors: Nasser AlShawaaf

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While previous researchers have attempted to explain art museums commercialisation with reference to cultural policies, they have overlooked the phenomenon of globalisation. This study examines the causes and effects of globalisation of art museums in France. Building on arts literature, we show that the cultural policies of the French government since 1980s of cultural democratisation, cultural decentralisation, and implementing market principles on the cultural sector are leading to arts globalisation. Although globalisation is producing economic benefits and enhancing cultural reach, however, the damages include artistic values and creativity, cultural heritage and representation, and the museum itself. Art museums and host cities could overcome negative consequences through a hybrid collection display and develop local collections gradually.

Keywords: cultural policy, cultural decentralisation, cultural globalisation, art museums, contextual analysis, France

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Authors: Iva Blazkova, Amitava Moulick, Vedran Milosavljevic, Pavel Kopel, Marketa Vaculovicova, Vojtech Adam, Rene Kizek

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Doxorubicin is one of the most commonly used and the most effective chemotherapeutic drugs. This antracycline drug isolated from the bacteria Streptomyces peuceticus var. caesius is sold under the trade name Adriamycin (hydroxydaunomycin, hydroxydaunorubicin). Doxorubicin is used in single therapy to treat hematological malignancies (blood cancers, leukaemia, lymphoma), many types of carcinoma (solid tumors) and soft tissue sarcomas. It has many serious side effects like nausea and vomiting, hair lost, myelosupression, oral mucositis, skin reactions and redness, but the most serious one is the cardiotoxicity. Because of the risk of heart attack and congestive heart failure, the total dose administered to patients has to be accurately monitored. With the aim to lower the side effects and to targeted delivery of doxorubicin into the tumor tissue, the different nanoparticles are studied. The drug can be bound on a surface of nanoparticle, encapsulated in the inner cavity, or incorporated into the structure of nanoparticle. Among others, carbon nanoparticles (graphene, carbon nanotubes, fullerenes) are highly studied. Besides the number of inorganic nanoparticles, a great potential exhibit also organic ones mainly lipid-based and polymeric nanoparticle. The aim of this work was to perform a toxicity study of free doxorubicin compared to doxorubicin conjugated with various nanotransporters. The effect of liposomes, fullerenes, graphene, and carbon nanotubes on the toxicity was analyzed. As a first step, the binding efficacy of between doxorubicin and the nanotransporter was determined. The highest efficacy was detected in case of liposomes (85% of applied drug was encapsulated) followed by graphene, carbon nanotubes and fullerenes. For the toxicological studies, the chicken embryos incubated under controlled conditions (37.5 °C, 45% rH, rotation every 2 hours) were used. In 7th developmental day of chicken embryos doxorubicin or doxorubicin-nanotransporter complex was applied on the chorioallantoic membrane of the eggs and the viability was analyzed every day till the 17th developmental day. Then the embryos were extracted from the shell and the distribution of doxorubicin in the body was analyzed by measurement of organs extracts using laser induce fluorescence detection. The chicken embryo mortality caused by free doxorubicin (30%) was significantly lowered by using the conjugation with nanomaterials. The highest accumulation of doxorubicin and doxorubicin nanotransporter complexes was observed in the liver tissue

Keywords: doxorubicin, chicken embryos, nanotransporters, toxicity

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Authors: Luísa P. Cruz-Lopes, Artur Figueirinha, Isabel Brás, Bruno Esteves

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Portugal is an important wine and olive oil producer, activities which generate a high quantity of residues commonly called grape stalks and olive cake, respectively. In this work grape stalks and olive cake were used as lignocellulosic adsorbents for wastewater containing lead treatment. To attain a better knowledge of the factors that could influence the quality of the treated wastewater, a chemical characterization of the materials used in the treatment was done. To access the ecotoxicological safety of the treated wastewater, several tests were performed. The results of the toxicity test show that the samples leachate has a mild effect on the living models tested. The tests performed in lemna and bacteria were the most sensible to toxicity effects of the samples. The results obtained in this work evidenced the importance of use of simple and fast toxicity tests to predict impacts in the environment.

Keywords: chemical composition, lignocellulosic residues, ecotoxicological safety, wastewater

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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

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Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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Authors: Avijit Sengupta, Klarissa Ting Ting Cheng, Maffee Peng-Hui Wan

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This study investigates the influence of user factors and referent characteristics on representation types generated using the stereotype production method for designing icons. Sixty-eight participants of farming communities were asked to draw images based on sixteen feature referents. Significant statistical differences were found between the types of representations generated for contextual and context-independent referents. Strong correlations were observed between years of formal education and total number of abstract representations produced for both contextual and context-independent referents. However, representation characteristics were not influenced by other user factors such as participants’ experience with mobile phone and years of farming experience. A statistically significant tendency of making concrete representations was observed for both contextual and context-independent referents. These findings provide insights on community members’ involvement in icon design and suggest a consolidated icon design strategy based on population stereotype, particularly for under-served rural communities of India.

Keywords: abstract representation, concrete representation, participatory design, population stereotype

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Authors: Carlos Alberto Riveros, Edwin Fabián García, Javier Enrique Rivero

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The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structures

Keywords: optimum sensor placement, structural damage detection, modal identification, beam-like structures.

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Authors: Jie Yang, Jian-Min Meng

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A GPU-based floating object detection scheme is presented in this paper which is designed for floating mine detection tasks. This system uses contrast and motion information to eliminate as many false positives as possible while avoiding false negatives. The GPU computation platform is deployed to allow detecting objects in real-time. From the experimental results, it is shown that with certain configuration, the GPU-based scheme can speed up the computation up to one thousand times compared to the CPU-based scheme.

Keywords: object detection, GPU, motion estimation, parallel processing

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Authors: Awad G. Abdellatif, Huda M. Gargoum, Abdelkader A. Debani, Mudafara Bengleil, Salmin Alshalmani, N. El Zuki, Omran El Fitouri

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In this study, the administration of 660 mg/kg of the ethanolic extract of the Alhgigraecorum (camel thorn) to mice, showed a significant decrease in the level of transaminases in animals treated with a combination of CTE plus carbon tetrachloride (CCl4) or acetaminophen as compared to animals receiving CCl4 or acetaminophen alone. The histopathological investigation also confirmed that camel thorn extract protects the liver against damage-induced either by carbon tetrachloride or acetaminophen. On the other hand, the cardiac toxicity produced by adriamycin was significantly increased in the presence of the ethanolic extract of camel thorn. Our study suggested that camel thorn can protect the liver against the injury produced by carbon tetrachloride or acetaminophen, with an unexpected increase in the cardiac toxicity–induced by adriamycin in rodents.

Keywords: ethanolic, alhgigraecorum, tetrachloride, acetaminophen

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Authors: Vedant Subhash

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This paper discusses the physics of the detection of thermal neutrons using thin-film coated semiconductor detectors. The thermal neutron detection efficiency as a function of film thickness is calculated for the front and back irradiation detector devices coated with ¹⁰B, ⁶LiF, and pure Li thin films. The detection efficiency for back irradiation devices is 4.15% that is slightly higher than that for front irradiation detectors, 4.0% for ¹⁰B films of thickness 2.4μm. The theoretically calculated thermal neutron detection efficiency using ¹⁰B film thickness of 1.1 μm for the back irradiation device is 3.0367%, which has an offset of 0.0367% from the experimental value of 3.0%. The detection efficiency values are compared and proved consistent with the given calculations.

Keywords: detection efficiency, neutron detection, semiconductor detectors, thermal neutrons

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Authors: Gabrielle Peck, Ryan Hayes

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Four façade systems were tested using a reduced height BS 8414-2 (5 m) test rig. An L-shaped masonry test wall was clad with three types of insulation and an aluminum composite panel with a non-combustible filling (meeting Euroclass A2). A large (3 MW) wooden crib was ignited in a recess at the base of the L, and the fire was allowed to burn for 30 minutes. Air velocity measurements and gas samples were taken from the main ventilation duct and also a small additional ventilation duct, like those in an apartment bathroom or kitchen. This provided a direct route of travel for smoke from the building façade to a theoretical room using a similar design to many high-rise buildings where the vent is connected to (approximately) 30 m³ rooms. The times to incapacitation and lethality of the effluent were calculated for both the main exhaust vent and for a vent connected to a theoretical 30 m³ room. The rainscreen façade systems tested were the common combinations seen in many tower blocks across the UK. Three tests using ACM A2 with Stonewool, Phenolic foam, and Polyisocyanurate (PIR) foam. A fourth test was conducted with PIR and ACM-PE (polyethylene core). Measurements in the main exhaust duct were representative of the effluent from the burning wood crib. FEDs showed incapacitation could occur up to 30 times quicker with combustible insulation than non-combustible insulation, with lethal gas concentrations accumulating up to 2.7 times faster than other combinations. The PE-cored ACM/PIR combination produced a ferocious fire, resulting in the termination of the test after 13.5 minutes for safety reasons. Occupants of the theoretical room in the PIR/ACM A2 test reached a FED of 1 after 22 minutes; for PF/ACM A2, this took 25 minutes, and for stone wool, a lethal dose measurement of 0.6 was reached at the end of the 30-minute test. In conclusion, when measuring smoke toxicity in the exhaust duct, there is little difference between smoke toxicity measurements between façade systems. Toxicity measured in the main exhaust is largely a result of the wood crib used to ignite the façade system. The addition of a vent allowed smoke toxicity to be quantified in the cavity of the façade, providing a realistic way of measuring the toxicity of smoke that could enter an apartment from a façade fire.

Keywords: smoke toxicity, large-scale testing, BS8414, FED

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Authors: Elsayed Elmiligy, Dzolkhifili Omar, Norhayu Asib

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Sitophilus oryzae is a primary destructive insect pest. A study on nanoemulsion formulation of C. hystrix peel oil and evaluation of its insecticidal effect on the adults of S. oryzae was held in toxicology laboratory at Faculty of Agriculture, Universiti Putra Malaysia (UPM). Three nanoemulsion formulations (F1, F2, and F3) were prepared using C. hystrix peel oil (a.i), Tween 80 (surfactant), AMD 810 (carrier) and deionized water. The selected formulations have undergone stability tests, surface tension, zeta potential and particle size measurements. The formulations were tested for their contact and fumigant activity against the adults of S. oryzae. LC₅₀ values were obtained from Probit regressions using the Polo-PC program. All the formulations showed stability under storage temperature and centrifugation. They were characterized as nanoemulsions as they remained in the range of nanoscale 200 nm. The formulations revealed lower surface tension in the range of 29.5 to 30.4 mN/m. They showed stable of zeta potential values. The formulations showed the highest toxicity against the adults of S. oryzae. The order of decreasing toxicity was F1 > F2 > F3 with LC₅₀ values of 52.1, 58.5, and 61.7 µl/l for contact toxicity, and 71, 75.5, and 76.7 µl/l air for fumigant bioassay after 72 hours. Formulation of C. hystrix peel oil in a nanoemulsion enhance its effectiveness and reduce the amount of applied essential oil.

Keywords: Citrus hystrix peel oil, Sitophilus oryzae, nanoemulsion, contact toxicity, Fumigant bioassay

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Authors: Abazar Ghorbani, W. M. Wishwajith W. Kandegama, Seyed Mehdi Razavi, Moxian Chen

Abstract:

The roles of hydrogen sulfide (H₂S) and melatonin (MT) as gasotransmitters in plants are widely recognised. Nevertheless, the precise nature of their involvement in defensive reactions remains uncertain. This study investigates the impact of the ML-H2S interaction on tomato plants exposed to vanadium (V) toxicity, focusing on synthesising secondary metabolites and V metal sequestration. The treatments applied in this study included a control (T1), V stress (T2), MT+V (T3), MT+H2S+V (T4), MT+hypotaurine (HT)+V (T5), and MT+H2S+HT+V (T6). These treatments were administered: MT (150 µM) as a foliar spray pre-treatment (3X), HT treatment (0.1 mM, an H2S scavenger) as root immersion for 12 hours as pre-treatments, and H2S (NaHS, 0.2 mM) and V (40 mg/L) treatments added to the Hoagland solution for 2 weeks. Results demonstrate that ML and H2S+ML treatments alleviate V toxicity by promoting the transcription of key genes (ANS, F3H, CHS, DFR, PAL, and CHI) involved in phenolic and anthocyanin biosynthesis. Moreover, they decreased V uptake and accumulation and enhanced the transcription of genes involved in glutathione and phytochelatin synthesis (GSH1, PCS, and ABC1), leading to V sequestration in roots and protection against V-induced damage. Additionally, ML and H2S+ML treatments optimize chlorophyll metabolism, and increase internal H2S levels, thereby promoting tomato growth under V stress. The combined treatment of ML+H2S shows superior effects compared to ML alone, suggesting synergistic/interactive effects between these two substances. Furthermore, inhibition of the beneficial impact of ML+H2S and ML treatments by HT, an H2S scavenger, underscores the significant involvement of H₂S in the signaling pathway activated by ML during V toxicity. Overall, these findings suggest that ML requires the presence of endogenous H₂S to mitigate V-induced adverse effects on tomato seedlings.

Keywords: vanadium toxicity, secondary metabolites, vanadium sequestration, h2s-melatonin crosstalk

Procedia PDF Downloads 18

Authors: Manuel Alves, Angelica Reis, Armindo Lobo, Valdemar Leiras

Abstract:

In industry 4.0, it is common to have a lot of sensor data. In this deluge of data, hints of possible problems are difficult to spot. The digital twin concept aims to help answer this problem, but it is mainly used as a monitoring tool to handle the visualisation of data. Failure detection is of paramount importance in any industry, and it consumes a lot of resources. Any improvement in this regard is of tangible value to the organisation. The aim of this paper is to add the ability to forecast test failures, curtailing detection times. To achieve this, several anomaly detection algorithms were compared with a symbolic regression approach. To this end, Isolation Forest, One-Class SVM and an auto-encoder have been explored. For the symbolic regression PySR library was used. The first results show that this approach is valid and can be added to the tools available in this context as a low resource anomaly detection method since, after training, the only requirement is the calculation of a polynomial, a useful feature in the digital twin context.

Keywords: anomaly detection, digital twin, industry 4.0, symbolic regression

Procedia PDF Downloads 97