Search results for: remote detection chemical warfare agents

Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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The assessment variables of the accessibility and the sustainability of access infrastructure for remote regions may vary significant by location and a wide range of factors may affect the decision process. In this paper, the environmental disturbance implications of transportation system to key demand and supply variables impact the economic system in remote destination are descripted. According to a systemic approach, the key sustainability variables deals with decision making process that have to be included in strategic plan for the critical transport infrastructure development and their relationship to regional socioeconomic system are presented. The application deals with the development of railway in remote destinations, where the traditional CBA not include the external cost generated by the environmental impacts that may have a range of diverse impacts on transport infrastructure and services. The analysis output provides key messages to decision and policy makers towards sustainable development of transport infrastructure, especially for remote destinations where accessibility is a key factor of regional economic development and social stability. The key conclusion could be essential useful for relevant applications in remote regions in the same latitude.

Keywords: sustainable development in remote regions, transport infrastructure, strategic planning, sustainability variables

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Ismail Elkhrachy

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Determination of land use changing is an important component of regional planning for applications ranging from urban fringe change detection to monitoring change detection of land use. This data are very useful for natural resources management.On the other hand, the technologies and methods of change detection also have evolved dramatically during past 20 years. So it has been well recognized that the change detection had become the best methods for researching dynamic change of land use by multi-temporal remotely-sensed data. The objective of this paper is to assess, evaluate and monitor land use change surrounding the area of Najran city, Kingdom of Saudi Arabia (KSA) using Landsat images (June 23, 2009) and ETM+ image(June. 21, 2014). The post-classification change detection technique was applied. At last,two-time subset images of Najran city are compared on a pixel-by-pixel basis using the post-classification comparison method and the from-to change matrix is produced, the land use change information obtained.Three classes were obtained, urban, bare land and agricultural land from unsupervised classification method by using Erdas Imagine and ArcGIS software. Accuracy assessment of classification has been performed before calculating change detection for study area. The obtained accuracy is between 61% to 87% percent for all the classes. Change detection analysis shows that rapid growth in urban area has been increased by 73.2%, the agricultural area has been decreased by 10.5 % and barren area reduced by 7% between 2009 and 2014. The quantitative study indicated that the area of urban class has unchanged by 58.2 km〗^2, gained 70.3 〖km〗^2 and lost 16 〖km〗^2. For bare land class 586.4〖km〗^2 has unchanged, 53.2〖km〗^2 has gained and 101.5〖km〗^2 has lost. While agriculture area class, 20.2〖km〗^2 has unchanged, 31.2〖km〗^2 has gained and 37.2〖km〗^2 has lost.

Keywords: land use, remote sensing, change detection, satellite images, image classification

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Authors: Georgios Linardatos, Miltiadis Zamparas, Vlasoula Bekiari, Georgios Bokias, Georgios Hotos

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Hydrogels are three-dimensional, hydrophilic, polymeric networks composed of homopolymers or copolymers and are insoluble in water due to the presence of chemical or physical cross-links. When hydrogels come in contact with aqueous solutions, they can effectively sorb and retain the dissolved substances, depending on the nature of the monomeric units comprising the hydrogel. For this reason, hydrogels have been proposed in several studies as water purification agents. At the present work anionic hydrogels bearing negatively charged –COO- groups were prepared and investigated. These gels are based on sodium acrylate (ANa), either homopolymerized (poly(sodiumacrylate), PANa) or copolymerized (P(DMAM-co-ANa)) with N,N Dimethylacrylamide (DMAM). The hydrogels were used to extract some model organic dyes from water. It is found that cationic dyes are strongly sorbed and retained by the hydrogels, while sorption of anionic dyes was negligible. In all cases it was found that both maximum sorption capacity and equilibrium binding constant varied from one dye to the other depending on the chemical structure of the dye, the presence of functional chemical groups and the hydrophobic-hydrophilic balance. Finally, the nonionic hydrogel of the homopolymer poly(N,N-dimethylacrylamide), PDMAM, was also used for reasons of comparison.

Keywords: anionic organic hydrogels, sorption, organic dyes, water purification agents

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Authors: Mohammad Soliman, Mohamed A. Abou-Shouk

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Knowledge management focuses on the development, storage, retrieval, and dissemination of information and expertise. It has become an important tool to improve performance in tourism enterprises. This includes improving decision-making, developing customer services, and increasing sales and profits. Knowledge management adoption depends on human, organizational and technological factors. This study aims to explore the concept of knowledge management in travel agents in Egypt. It explores the requirements of adoption and its impact on performance in these agencies. The study targets Category A travel agents in Egypt. The population of the study encompasses Category A travel agents having online presence. An online questionnaire is used to collect data from managers of travel agents. This study is useful for travel agents who are in urgent need to restructure their intermediary role and support their survival in the global travel market. The study sheds light on the requirements of adoption and the expected impact on performance. This could help travel agents identify their situation and the determine the extent to which they are ready to adopt knowledge management. This study is contributing to knowledge by providing insights from the tourism sector in a developing country where the concept of knowledge management is still in its infancy stages.

Keywords: knowledge management, knowledge management adoption, performance, travel agents

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Authors: Shuen-Tai Wang, Yu-Ching Lin, Hsi-Ya Chang

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With the development of virtualization technologies, a new type of service named cloud computing service is produced. Cloud users usually encounter the problem of how to use the virtualized platform easily over the web without requiring the plug-in or installation of special software. The object of this paper is to develop a system and a method enabling process interfacing within an automation scenario for accessing remote application by using the web browser. To meet this challenge, we have devised a web-based interface that system has allowed to shift the GUI application from the traditional local environment to the cloud platform, which is stored on the remote virtual machine. We designed the sketch of web interface following the cloud virtualization concept that sought to enable communication and collaboration among users. We describe the design requirements of remote application technology and present implementation details of the web application and its associated components. We conclude that this effort has the potential to provide an elastic and resilience environment for several application services. Users no longer have to burden the system maintenances and reduce the overall cost of software licenses and hardware. Moreover, this remote application service represents the next step to the mobile workplace, and it lets user to use the remote application virtually from anywhere.

Keywords: virtualization technology, virtualized platform, web interface, remote application

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Authors: Ariel Barel, Rotem Manor, Alfred M. Bruckstein

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We present a probabilistic gathering algorithm for agents that can only detect the presence of other agents in front of or behind them. The agents act in the plane and are identical and indistinguishable, oblivious, and lack any means of direct communication. They do not have a common frame of reference in the plane and choose their orientation (direction of possible motion) at random. The analysis of the gathering process assumes that the agents act synchronously in selecting random orientations that remain fixed during each unit time-interval. Two algorithms are discussed. The first one assumes discrete jumps based on the sensing results given the randomly selected motion direction, and in this case, extensive experimental results exhibit probabilistic clustering into a circular region with radius equal to the step-size in time proportional to the number of agents. The second algorithm assumes agents with continuous sensing and motion, and in this case, we can prove gathering into a very small circular region in finite expected time.

Keywords: control, decentralized, gathering, multi-agent, simple sensors

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Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

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Authors: Li Hui, Riyadh Hindi

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Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

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Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

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Authors: W. Mazari, K. Boucherit, Z. Boucherit-Otmani, M. N. Rahmoun, M. Benabdallah

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The hospital or any other establishment of care can be considered as an ecosystem where the patient comes into contact with a frightening microbial universe and a risk to contract infection that is referred to as nosocomial or health care-associated. In these last years, the incidence of these infections has risen sharply. Several microorganisms are the cause of these nosocomial infections and the emergence of resistance of the microbial strains against antibiotics creates a danger to public health. The search for new antimicrobial agents to overcome this problem has produced interesting compounds through chemical synthesis, which plays a very important role in the research and discovery of new drugs. It is in this framework that our study was conducted at our laboratory and it involves evaluating the antibacterial activity of thirteen 2-pyridone derivatives synthesized by two methods, the diffusion disc method and the dilution method against eight Gram negative bacterial strains. The results seem interesting especially for two products that have shown the best activities against Escherichia coli ATCC 25922 and Enterobacter cloacae ATCC 13047 with CMI of 512µg/ml.

Keywords: heterocyclic derivatives, chemical synthesis, antimicrobial activity, biotechnology

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Authors: Feng Yin

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Clouds are inevitable contaminants in optical satellite imagery, and prevent the satellite imaging systems from acquiring clear view of the earth surface. The presence of clouds in satellite imagery bring negative influences for remote sensing land resources investigation. As a consequence, detecting the locations of clouds in satellite imagery is an essential preprocessing step, and further remove the existing clouds is crucial for the application of imagery. In this paper, a multi-temporal based satellite imagery cloud detection and removal method is proposed, which will be used for large-scale land resource investigation. The proposed method is mainly composed of four steps. First, cloud masks are generated for cloud contaminated images by single temporal cloud detection based on multiple spectral features. Then, a cloud-free reference image of target areas is synthesized by weighted averaging time-series images in which cloud pixels are ignored. Thirdly, the refined cloud detection results are acquired by multi-temporal analysis based on the reference image. Finally, detected clouds are removed via multi-temporal linear regression. The results of a case application in Hubei province indicate that the proposed multi-temporal cloud detection and removal method is effective and promising for large-scale land resource investigation.

Keywords: cloud detection, cloud remove, multi-temporal imagery, land resources investigation

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Authors: Hossam E. Emam

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The functional textiles development history in the military field could be ascribed as a uniquely interesting research topic. Soldiers are like a high-performance athletes, where monitoring their physical and physiological capabilities is a vital requirement. Functional clothes represent a “second skin” that has a close, “intimate” relationship with the human body. For the application of textiles in military purposes, which is normally required in difficult weather and environmental conditions, several functions are required. The requirements for designing functional military textiles for soldier's protection can be categorized into three categories; i) battle field (protection from chemical warfare agents, flames, and thermal radiation), ii) environmental (water proof, air permeable, UV-protection, antibacterial), iii) physiological (minimize heat stress, low weight, insulative, durability). All of these requirements are important, but the means to fulfill these requirements are not simple and straight forward. Additionally, the combination of more than one function is reported to be very expensive and requires many complicated steps, and the final product is found to be low durability. Not only do all of these requirements are overlapping, but they are also contradicting each other at various levels. Thus, we plan to produce multi-functional textiles (e.g., anti-microbial, UV-protection, fire retardant, photoluminescent) to be applied in military clothes. The current project aims to use quite a simple and applicable technique through the modification of textiles with different coordination polymers and functionalized coordination polymers.

Keywords: functional textiles, military clothes, coordination polymers, antimicrobial, fire retardant, photolumenscent

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Authors: Spoorthi Srupad

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Environmental Impact Assessment (EIA) stands as a critical engineering application facilitated by Earth Resources and Environmental Remote Sensing. Employing advanced technologies, this process enables a systematic evaluation of potential environmental impacts arising from engineering projects. Remote sensing techniques, including satellite imagery and geographic information systems (GIS), play a pivotal role in providing comprehensive data for assessing changes in land cover, vegetation, water bodies, and air quality. This abstract delves into the significance of EIA in engineering, emphasizing its role in ensuring sustainable and environmentally responsible practices. The integration of remote sensing technologies enhances the accuracy and efficiency of impact assessments, contributing to informed decision-making and the mitigation of adverse environmental consequences associated with engineering endeavors.

Keywords: environmental impact assessment, engineering applications, sustainability, environmental monitoring, remote sensing, geographic information systems, environmental management

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Authors: Cem Ozatalay, Senem Ornek

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The Artprice Contemporary Art Market Annual Report 2014 notices that Istanbul, with its art market volume of $3.6 million has become the first city of the Middle East and North Africa region and the 14th city of the World. Indeed, the period 2004–2014 has been significant in terms of the growth of the art market, during which the majority of contemporary art galleries and museums in Istanbul was inaugurated. This boom means that with the joining of new agents, the structure of the art market has dramatically changed. To use Nathalie Heinich’s terminology, in the current art field, three art genres – namely classical art, modern art and contemporary art – coexist, but in the case of Istanbul, such as many art cities in the world, the latter genre has become increasingly dominant. This presentation aims to show how the power shifts away from the classical art agents to contemporary art agents, and the effects produced by the conflicts between the old and new agents of current art field. Based on the data obtained from an ongoing field research in Istanbul among the art market agents such as art dealers, curators, art critics and artists, it will be shown that even if the agents of different art genres are in conflict with each other, there is, at the same time, a continuum between the three art worlds.

Keywords: contemporary art market, economic sociology of art, Istanbul art market, structure of the art field in Istanbul

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Authors: Wei Li, Tuo Yang

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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Sikander Nawaz Khan

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Natural disasters like flood, earthquake, cyclone, volcanic eruption and others are causing immense losses to the property and lives every year. Current status and actual loss information of natural hazards can be determined and also prediction for next probable disasters can be made using different remote sensing and mapping technologies. Global Positioning System (GPS) calculates the exact position of damage. It can also communicate with wireless sensor nodes embedded in potentially dangerous places. GPS provide precise and accurate locations and other related information like speed, track, direction and distance of target object to emergency responders. Remote Sensing facilitates to map damages without having physical contact with target area. Now with the addition of more remote sensing satellites and other advancements, early warning system is used very efficiently. Remote sensing is being used both at local and global scale. High Resolution Satellite Imagery (HRSI), airborne remote sensing and space-borne remote sensing is playing vital role in disaster management. Early on Geographic Information System (GIS) was used to collect, arrange, and map the spatial information but now it has capability to analyze spatial data. This analytical ability of GIS is the main cause of its adaption by different emergency services providers like police and ambulance service. Full potential of these so called 3S technologies cannot be used in alone. Integration of GPS and other remote sensing techniques with GIS has pointed new horizons in modeling of earth science activities. Many remote sensing cases including Asian Ocean Tsunami in 2004, Mount Mangart landslides and Pakistan-India earthquake in 2005 are described in this paper.

Keywords: disaster mitigation, GIS, GPS, remote sensing

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Authors: Shyaka Eugene

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The efficient and safe demolition of structures is a critical challenge in civil engineering and construction. This study focuses on the development of optimal demolition strategies by investigating the crack propagation behavior in beams induced by soundless cracking agents. It is commonly used in controlled demolition and has gained prominence due to its non-explosive and environmentally friendly nature. This research employs a comprehensive experimental and computational approach to analyze the crack initiation, propagation, and eventual failure in beams subjected to soundless cracking agents. Experimental testing involves the application of various cracking agents under controlled conditions to understand their effects on the structural integrity of beams. High-resolution imaging and strain measurements are used to capture the crack propagation process. In parallel, numerical simulations are conducted using advanced finite element analysis (FEA) techniques to model crack propagation in beams, considering various parameters such as cracking agent composition, loading conditions, and beam properties. The FEA models are validated against experimental results, ensuring their accuracy in predicting crack propagation patterns. The findings of this study provide valuable insights into optimizing demolition strategies, allowing engineers and demolition experts to make informed decisions regarding the selection of cracking agents, their application techniques, and structural reinforcement methods. Ultimately, this research contributes to enhancing the safety, efficiency, and sustainability of demolition practices in the construction industry, reducing environmental impact and ensuring the protection of adjacent structures and the surrounding environment.

Keywords: expansion pressure, energy release rate, soundless chemical demolition agent, crack propagation

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Authors: Mahdi Rahaie

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MicroRNAs are a novel class of small RNAs which regulate gene expression by translational repression or degradation of messenger RNAs. To produce sensitive, simple and cost-effective assays for microRNAs, detection is in urgent demand due to important role of these biomolecules in progression of human disease such as Alzheimer’s, Multiple sclerosis, and some other neurodegenerative diseases. Herein, we report several novel, sensitive and specific microRNA nanobiosensors which were designed based on colorimetric and fluorescence detection of nanoparticles and hybridization chain reaction amplification as an enzyme-free amplification. These new strategies eliminate the need for enzymatic reactions, chemical changes, separation processes and sophisticated equipment whereas less limit of detection with most specify are acceptable. The important features of these methods are high sensitivity and specificity to differentiate between perfectly matched, mismatched and non-complementary target microRNAs and also decent response in the real sample analysis with blood plasma. These nanobiosensors can clinically be used not only for the early detection of neuro diseases but also for every sickness related to miRNAs by direct detection of the plasma microRNAs in real clinical samples, without a need for sample preparation, RNA extraction and/or amplification.

Keywords: hybridization chain reaction, microRNA, nanobiosensor, neurodegenerative diseases

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Authors: Yaner Yan, Ning Li, Yajun Qiao, Shuqing An

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Although most studies have focused on assessing and mapping terrestrial ecosystem services, there is still a knowledge gap on coastal ecosystem services and an urgent need to assess them. Lau (2013) clearly defined five types of costal ecosystem services: carbon sequestration, shoreline protection, fish nursery, biodiversity, and water quality. While high-resolution remote sensing can provide the more direct, spatially estimates of biophysical parameters, such as species distribution relating to biodiversity service, and Fluorescence information derived from remote sensing direct relate to photosynthesis, availing in estimation of carbon sequestration and the response to environmental changes in coastal wetland. Here, we review the capabilities of high-resolution and fluorescence remote sesing for describing biodiversity, vegetation condition, ecological processes and highlight how these prodicts may contribute to costal ecosystem service assessment. In so doing, we anticipate rapid progress to combine the high-resolution and fluorescence remote sesing to estimate the spatial pattern of costal ecosystem services.

Keywords: ecosystem services, high resolution, remote sensing, chlorophyll fluorescence

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Francielle A. Vargas, Thiago A. S. Pardo

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According to the standard philosophical definition, lying is saying something that you believe to be false with the intent to deceive. For deception detection, the FBI trains its agents in a technique named statement analysis, which attempts to detect deception based on parts of speech (i.e., linguistics style). This method is employed in interrogations, where the suspects are first asked to make a written statement. In this poster, we model false statements using linguistics style. In order to achieve this, we methodically analyze linguistic features in a corpus of fake news in the Portuguese language. The results show that they present substantial lexical, syntactic and semantic variations, as well as punctuation and emotion distinctions.

Keywords: deception detection, linguistics style, computational linguistics, natural language processing

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Authors: Omair Ghori, Anton Stadler, Stefan Wilk, Wolfgang Effelsberg

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Fire-related incidents account for extensive loss of life and material damage. Quick and reliable detection of occurring fires has high real world implications. Whereas a major research focus lies on the detection of outdoor fires, indoor camera-based fire detection is still an open issue. Cameras in combination with computer vision helps to detect flames and smoke more quickly than conventional fire detectors. In this work, we present a computer vision-based smoke detection algorithm based on contrast changes and a multi-step classification. This work accelerates computer vision-based fire detection considerably in comparison with classical indoor-fire detection.

Keywords: contrast analysis, early fire detection, video smoke detection, video surveillance

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Authors: Shashank Gupta, Shiva Garg

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The purpose of the present paper is to study the changes in the strength characteristics of autoclaved aerated concrete (AAC) and also the density when different expansion agents are used. The expansion agent so used releases air in the concrete thereby making it lighter by reducing its density. It also increases the workability of the concrete. The various air entraining agents used for this study are hydrogen peroxide, oleic acid, and olive oil. The addition of these agents causes the concrete to rise like cake but it reduces the strength of concrete due to the formation of air voids. The amount of agents chosen for concrete production are 0.5%, 1%, 1.5% by weight of cement.

Keywords: AAC, olive oil, hydrogen peroxide, oleic acid, steam curing

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Authors: Radka Obořilová, Hana Šimečková, Matěj Pastucha, Jan Přibyl, Petr Skládal, Ivana Mašlaňová, Zdeněk Farka

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Due to the spreading of antimicrobial resistance, alternative approaches to combat superinfections are being sought, both in the field of lysing agents and methods for studying bacterial lysis. A suitable alternative to antibiotics is phage therapy and enzybiotics, for which it is also necessary to study the mechanism of their action. Biosensor-based techniques allow rapid detection of pathogens in real time, verification of sensitivity to commonly used antimicrobial agents, and selection of suitable lysis agents. The detection of lysis takes place on the surface of the biosensor with immobilized bacteria, which has the potential to be used to study biofilms. An example of such a biosensor is surface plasmon resonance (SPR), which records the kinetics of bacterial lysis based on a change in the resonance angle. The bacteria are immobilized on the surface of the SPR chip, and the action of phage as the mass loss is monitored after a typical lytic cycle delay. Atomic force microscopy (AFM) is a technique for imaging of samples on the surface. In contrast to electron microscopy, it has the advantage of real-time imaging in the native conditions of the nutrient medium. In our case, Staphylococcus aureus was lysed using the enzyme lysostaphin and phage P68 from the familyPodoviridae at 37 ° C. In addition to visualization, AFM was used to study changes in mechanical properties during lysis, which resulted in a reduction of Young’s modulus (E) after disruption of the bacterial wall. Changes in E reflect the stiffness of the bacterium. These advanced methods provide deeper insight into bacterial lysis and can help to fight against bacterial diseases.

Keywords: biosensors, atomic force microscopy, surface plasmon resonance, bacterial lysis, staphylococcus aureus, phage P68

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Authors: Sandhya Armoogum

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In distributed systems and in open systems such as the Internet, often mobile code has to run on unknown and potentially hostile hosts. Mobile code such as a mobile agent is vulnerable when executing on remote hosts. The mobile agent may be subjected to various attacks such as tampering, inspection, and replay attack by a malicious host. Much research has been done to provide solutions for various security problems, such as authentication of mobile agent and hosts, integrity and confidentiality of the data carried by the mobile agent. Many of such proposed solutions in literature are not suitable for open systems whereby the mobile code arrives and executes on a host which is not known and trusted by the mobile agent owner. In this paper, we propose the adoption of the reference monitor by hosts in an open system for providing trust and security for mobile code execution. A secure protocol for the distribution of the reference monitor entity is described. This reference monitor entity on the remote host may also provide several security services such as authentication and integrity to the mobile code.

Keywords: security, mobile agents, reference monitor, trust

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Authors: Rashid Mahmood

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The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.

Keywords: IDS, cloud, naas, detection

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Authors: Mohamed Abd Elfattah Ibraheem Elghrbawy

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Biodeterioration of cultural heritage is a complex process which is caused by the interaction of many physical, chemical and biological agents; the growth of microorganisms can cause staining, cracking, powdering, disfigurement and displacement of monuments material, which leads to the permanent loss of monuments material. Organisms causing biodeterioration on monuments have usually been controlled by chemical products (biocides). In order to overcome the impact of biocides on the environment, human health and monument substrates, alternative tools such as antimicrobial agents from natural products can be used for monuments conservation and protection. The problem is how to formulate antibacterial agents with high efficiency and low toxicity. Various types of biodegradable metal nanoparticles (MNPs) have many applications in plant extract delivery. So, Nano-encapsulation of metal and natural antimicrobial agents using polymers such as chitosan increases their efficacy, specificity and targeting ability. Green synthesis and characterization of metal nanoparticles such as silver with natural products extracted from some plants having antimicrobial properties, using the ecofriendly method one pot synthesis. Encapsulation of the new synthesized mixture using some biopolymers such as chitosan nanoparticles. The dispersions and homogeneity of the antimicrobial heterogeneous metal nanoparticles encapsulated by biopolymers will be characterized and confirmed by Fourier Transform Infrared Spectroscopy (FTIR), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM) and Zeta seizer. The effect of the antimicrobial biopolymer metal nano-formulations on normal human cell lines will be investigated to evaluate the environmental safety of these formulations. The antimicrobial toxic activity of the biopolymeric antimicrobial metal nanoparticles formulations will be will be investigated to evaluate their efficiency towards different pathogenic bacteria and fungi.

Keywords: antimicrobial, biodeterioration, chitosan, cultural heritage, silver

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

Abstract:

Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

Procedia PDF Downloads 338

Authors: Susan Catapano, Meredith Jones, Carol McNulty

Abstract:

Analysis of one state’s collaborative effort to support teachers, in both public and private schools, as they moved from face-to-face teaching to remote teaching during the Covid pandemic to identify lessons learned and materials put into place to support teachers and families. Surveys were created, distributed, and analyzed throughout the three months of remote teaching, documents and lesson plans were developed, and training materials were created. All data collected and materials developed were analyzed to identify supports teachers used and needed for successful remote teaching. Researchers found most teachers easily moved to online teaching; however, many families did not have access to technology, so teachers needed to develop non-technology-based access and support for remote teaching. Teachers also reported the need to prepare to teach remotely as part of their teaching training, so they were prepared in the future. Finally, data indicated teachers were able to establish stronger relationships with families than usual as a result of remote teaching. The lessons learned and support developed are part of the state’s ongoing policy for online teaching in the event of disasters and pandemics in the future.

Keywords: remote learning, teacher education, pandemic, families

Procedia PDF Downloads 148