Search results for: virtual environments computer auditing

Authors: Abdul Mannan Akhtar

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In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Ivana Cestar, Ivica Stančerić, Saša Ahac, Vesna Dragčević, Tamara Džambas

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On special paved areas, such as road intersections, vehicles are usually moving through horizontal curves with smaller radii and occupy considerably greater area compared to open road segments. Planning procedure of these areas is mainly an iterative process that consists of designing project elements, assembling those elements to a design project, and analyzing swept paths for the design vehicle. If applied elements do not fulfill the swept path requirements for the design vehicle, the process must be carried out again. Application of specialized computer software for swept path analysis significantly facilitates planning procedure of special paved areas. There are various software of this kind available on the global market, and each of them has different specifications. In this paper, comparison of two software commonly used in Croatia (Auto TURN and Vehicle Tracking) is presented, their advantages and disadvantages are described, and their applicability on a particular paved area is discussed. In order to reveal which one of the analyszed software is more favorable in terms of swept paths widths, which one includes input parameters that are more relevant for this kind of analysis, and which one is more suitable for the application on a certain special paved area, the analysis shown in this paper was conducted on a number of different intersection types.

Keywords: software comparison, special paved areas, swept path analysis, swept path input parameters

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Authors: Stephanie Guerra-Arias, Stephani Nevarez, Calvin Stewart, Rachel Grodsky, Denis Eichorst

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The objective of this study is to describe the framework for optimizing the heat treatment of alkali silicate glasses, to enhance the performance of hermetic seals in extreme environments. When connectors are exposed to elevated temperatures, residual stresses develop due to the mismatch of thermal expansions between the glass, metal pin, and metal shell. Excessive thermal expansion mismatch compromises the reliability of hermetic seals. In this study, a series of heat treatment schedules will be performed on two commercial sealing glasses (one conventional sealing glass and one crystallizable sealing glass) using a design of experiments (DOE) approach. The coefficient of thermal expansion (CTE) will be measured pre- and post-heat treatment using thermomechanical analysis (TMA). Afterwards, the flexural strength of the specimen will be measured using a four-point bend fixture mounted in a static universal testing machine. The measured material properties will be statistically analyzed using MiniTab software to determine which factors of the heat treatment process have a strong correlation to the coefficient of thermal expansion and/or flexural strength. Finally, a heat-treatment will be designed and tested to ensure the optimal performance of the hermetic seals in connectors.

Keywords: glass-ceramics, design of experiment, hermetic connectors, material characterization

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: R. Malathy

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High performance concrete is not only characterized by its high strength, workability, and durability but also by its smartness in performance without human care since the first day. If the concrete can cure on its own without external curing without compromising its strength and durability, then it is said to be high performance self-curing concrete. In this paper, an attempt is made on the performance study of internally cured concrete using biomaterials, namely Spinacea pleracea and Calatropis gigantea as self-curing agents, and it is compared with the performance of concrete with existing self-cure chemical, namely polyethylene glycol. The present paper focuses on workability, strength, and durability study on M20, M30, and M40 grade concretes replacing 30% of fly ash for cement. The optimum dosage of Spinacea pleracea, Calatropis gigantea, and polyethylene glycol was taken as 0.6%, 0.24%, and 0.3% by weight of cement from the earlier research studies. From the slump tests performed, it was found that there is a minimum variation between conventional concrete and self-cured concrete. The strength activity index is determined by keeping compressive strength of conventionally cured concrete for 28 days as unity and observed that, for self-cured concrete, it is more than 1 after 28 days and more than 1.15 after 56 days because of secondary reaction of fly ash. The performance study of concretes in aggressive environment like acid attack, sea water attack, and chloride attack was made, and the results are positive and encouraging in bio-self-cured concretes which are ecofriendly, cost effective, and high performance materials.

Keywords: bio materials, Calatropis gigantea, self curing concrete, Spinacea oleracea

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Authors: Nanjiang Chen

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In the backdrop of expanding urban landscapes, accurately assessing spatial openness is critical. Traditional visibility analysis methods grapple with discretization errors and inefficiencies, creating a gap in truly capturing the human experi-ence of space. Addressing these gaps, this paper introduces a distinct continuous visibility algorithm, a leap in measuring urban spaces from a human-centric per-spective. This study presents a methodological breakthrough by applying this algorithm to urban visibility analysis. Unlike conventional approaches, this tech-nique allows for a continuous range of visibility assessment, closely mirroring hu-man visual perception. By eliminating the need for predefined subdivisions in ray casting, it offers a more accurate and efficient tool for urban planners and architects. The proposed algorithm not only reduces computational errors but also demonstrates faster processing capabilities, validated through a case study in Bei-jing's urban setting. Its key distinction lies in its potential to benefit a broad spec-trum of stakeholders, ranging from urban developers to public policymakers, aid-ing in the creation of urban spaces that prioritize visual openness and quality of life. This advancement in urban analysis methods could lead to more inclusive, comfortable, and well-integrated urban environments, enhancing the spatial experience for communities worldwide.

Keywords: visual openness, spatial continuity, ray-tracing algorithms, urban computation

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security

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Authors: Qiang Wang, Hongyang Yu

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Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

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Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

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The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

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Authors: Qiong Li

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This study investigated in which condition computer-mediated communication (CMC) could promote pragmatic development. The focal feature included four Chinese sentence final particles (SFPs), a, ya, ba, and ne. They occur frequently in Chinese, and function as mitigators to soften the tone of speech. However, L2 acquisition of SFPs is difficult, suggesting the necessity of additional exposure to or explicit instruction on Chinese SFPs. This study follows this line and aims to explore two research questions: (1) Is CMC combined with data-driven instruction more effective than CMC alone in promoting L2 Chinese learners’ SFP use? (2) How does L2 Chinese learners’ SFP use change over time, as compared to the production of native Chinese speakers? The study involved 19 intermediate-level learners of Chinese enrolled at a private American university. They were randomly assigned to two groups: (1) the control group (N = 10), which was exposed to SFPs through CMC alone, (2) the treatment group (N = 9), which was exposed to SFPs via CMC and data-driven instruction. Learners interacted with native speakers on given topics through text-based CMC over Skype. Both groups went through six 30-minute CMC sessions on a weekly basis, with a one-week interval after the first two CMC sessions and a two-week interval after the second two CMC sessions (nine weeks in total). The treatment group additionally received a data-driven instruction after the first two sessions. Data analysis focused on three indices: token frequency, type frequency, and acceptability of SFP use. Token frequency was operationalized as the raw occurrence of SFPs per clause. Type frequency was the range of SFPs. Acceptability was rated by two native speakers using a rating rubric. The results showed that the treatment group made noticeable progress over time on the three indices. The production of SFPs approximated the native-like level. In contrast, the control group only slightly improved on token frequency. Only certain SFPs (a and ya) reached the native-like use. Potential explanations for the group differences were discussed in two aspects: the property of Chinese SFPs and the role of CMC and data-driven instruction. Though CMC provided the learners with opportunities to notice and observe SFP use, as a feature with low saliency, SFPs were not easily noticed in input. Data-driven instruction in the treatment group directed the learners’ attention to these particles, which facilitated the development.

Keywords: computer-mediated communication, data-driven instruction, pragmatic development, second language Chinese, sentence final particles

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Authors: Mohammad Jamalabadi, Noemi Zabari, Lukasz Bratasz

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Panel paintings -complex multi-layer structures consisting of wood support and a paint layer composed of a preparatory layer of gesso, paints, and varnishes- are among the category of cultural objects most vulnerable to relative humidity fluctuations and frequently found in museum collections. The current environmental specifications in museums have been derived using the criterion of crack initiation in an undamaged, usually new gesso layer laid on wood. In reality, historical paintings exhibit complex crack patterns called craquelures. The present paper analyses the structural response of a paint layer with a virtual network of rectangular cracks under environmental loadings using a three-dimensional model of a panel painting. Two modes of loading are considered -one induced by one-dimensional moisture response of wood support, termed the tangential loading, and the other isotropic induced by drying shrinkage of the gesso layer. The superposition of the two modes is also analysed. The modelling showed that minimum distances between cracks parallel to the wood grain depended on the gesso stiffness under the tangential loading. In spite of a non-zero Poisson’s ratio, gesso cracks perpendicular to the wood grain could not be generated by the moisture response of wood support. The isotropic drying shrinkage of gesso produced cracks that were almost evenly spaced in both directions. The modelling results were cross-checked with crack patterns obtained on a mock-up of a panel painting exposed to a number of extreme environmental variations in an environmental chamber.

Keywords: fracture saturation, surface cracking, paintings on wood, wood panels

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Authors: Nguyen-Tri Phuong, Triki Ennouri, Gauvin Chantal, Tuduri Ludovic, Vu-Khanh Toan

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Hand injuries due to mechanical hazards such as cuts and punctures are major risks and concerns for several occupational groups, particularly for workers in the metal manufacturing sector and mechanical automotive services. Personal protective equipment such as gloves or clothing is necessary for many professionals to protect against a variety of occupational hazards, which arise daily in their work environments. In many working places such as metal manufacturing or automotive services, mechanical hazards often occur together with industrial contaminants, particularly metalworking fluids (MWFs). The presence of these contaminants could modify the properties of gloves made from polymeric materials and thus increase the risk of hand injuries for workers. The focus of this study is to determine the swelling characteristics and the resistance of six polymer membranes when they are contaminated with several industrial metalworking fluids. These polymer membranes, commonly used in protective gloves, are nitrile, neoprene, vinyl, butyl, polyurethane and latex rubbers. Changes swelling index were continuously followed during the contamination procedure to compare the performance of each polymer under different conditions. The modification of the samples surface, tensile properties during the contamination process was also investigated. The effect of temperature on mechanical properties and morphology of material was also examined.

Keywords: metalworking fluid, swelling behavior, protective glove materials, elastomers

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Authors: G. Gnanachandrasamy, Y. Zhou, S. Venkatramanan, T. Ramkumar, S. Wang

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The natural resources of groundwater are the most precious resources around the world that balances are shrinking day by day. In connection, there is an urgency need for demarcation of potential groundwater zone. For these rationale integration of geographical information system (GIS) and remote sensing techniques (RS) for the hydrological studies have become a dramatic change in the field of hydrological research. These techniques are provided to locate the potential zone of groundwater. This research has been made to indent groundwater potential zone in Ariyalur of the southern part of India with help of GIS and remote sensing techniques. To identify the groundwater potential zone used by different thematic layers of geology, geomorphology, drainage, drainage density, lineaments, lineaments density, soil and slope with inverse distance weighting (IDW) methods. From the overall result reveals that the potential zone of groundwater in the study area classified into five classes named as very good (12.18 %), good (22.74 %), moderate (32.28 %), poor (27.7 %) and very poor (5.08 %). This technique suggested that very good potential zone of groundwater occurred in patches of northern and central parts of Jayamkondam, Andimadam and Palur regions in Ariyalur district. The result exhibited that inverse distance weighting method offered in this research is an effective tool for interpreting groundwater potential zones for suitable development and management of groundwater resources in different hydrogeological environments.

Keywords: GIS, groundwater potential zone, hydrology, remote sensing

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Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

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Authors: Michal Urzynicok, Krzysztof Kwiecinski

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The development of materials used in the power generation industry for the production of boilers and their parts is characterized by high steam parameters, which present new challenges. Implementation of new combinations of alloying elements that lead to the best possible mechanical properties, including creep resistance, greatly affects new steels' weldability. All new grades have to undergo many different examinations, in regards to bending and welding, in order to enable the development of fabrication technologies, ensuring failure-free production and assembly of boiler components. 12% Cr martensitic steels like THOR™ 115 or VM-12 SHC are characterized by high oxidation resistance in high-temperature environments. At the moment, VM-12 SHC can be found in many boilers where both headers and superheater coils were produced. As this material is very difficult to obtain, a search for a proper replacement has begun. A new creep strength-enhanced ferritic steel for service in supercritical and ultra-supercritical boiler applications was developed by Tenaris in Italy and it is designated as Thor™115 (Tenaris High Oxidation Resistance). As high demand in power plants occurred to replace some parts of existing installations fabricated from VM12-SHC with other alternatives, a new development of welding procedures has begun to prepare fabricators for the challenges of joining old components with new THOR™ 115 material. This paper covers the first research of welding of dissimilar joints made out of VM12-SHC and THOR™ 115.

Keywords: thor, vm12, dissimilar welding, weldability

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Authors: Dahi Ghareab Abdelsalam Ibrahim, R. H. Bakr

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Ionizing radiation, such as gamma radiation and X-rays, has many applications in medical diagnoses and cancer treatment. In this paper, we used the windowed Fourier transform to extract the complex image of the deformed red blood cells. The real values of the complex image are used to extract the best fitting of the deformed cell boundary. Male albino rats are irradiated by γ-rays from ⁶⁰Co. The male albino rats are anesthetized with ether, and then blood samples are collected from the eye vein by heparinized capillary tubes for studying the radiation-damaging effect in-vivo by the proposed windowed Fourier transform. The peripheral blood films are prepared according to the Brown method. The peripheral blood film is photographed by using an Automatic Image Contour Analysis system (SAMICA) from ELBEK-Bildanalyse GmbH, Siegen, Germany. The SAMICA system is provided with an electronic camera connected to a computer through a built-in interface card, and the image can be magnified up to 1200 times and displayed by the computer. The images of the peripheral blood films are then analyzed by the windowed Fourier transform method to extract the precise deformation from the best fitting. Based on accurate deformation evaluation of the red blood cells, diseases can be diagnosed in their primary stages.

Keywords: windowed Fourier transform, red blood cells, phase wrapping, Image processing

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Authors: H. Fraga, J. A. Santos

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Vitiviniculture in Portugal is a key socio-economic sector, with a strong connection to local traditions and culture. Despite being a relatively small country, with prevailing Mediterranean environments, Portugal comprises an exceptionally large diversity of growth conditions (Terroirs). The vineyard area in Portugal is over 190 thousand hectares, being the eleventh wine producer and ninth wine exporter worldwide. Owing to the strong impact of weather and climate conditions on grapevine physiological development, grape berry quantity and quality show important inter-annual variability. Grapevines are also susceptible to climate change, as their responses will be unavoidably different under future climates. These impacts may change wine typicity of a given region or even its viticultural suitability. The current study reveals that the projected warming and drying trends for Portugal under the Representative Concentration Pathway (RCP) 4.5 and 8.5, are projected to 1) significantly shift current grapevine growing thermal conditions (e.g., heat and chill accumulation), 2) enhance water stress, 3) anticipate phenological timings and 4) modify yields. Moreover, the present study provides some hints regarding the effectiveness of mulching and irrigation as climate change adaptation measures. Our results show that the effectiveness of these adaptation measures will strongly rest on the strength of the climate change signal at a local scale, thus emphasizing the need for local-to-regional climate change assessments.

Keywords: viticulture, climate change, adaptation measures, Portugal

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Authors: Girlly Marchlina Listyono, Abdurrokhim Abdurrokhim, Emi Sukiyah, Pulung Arya Pranantya

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Jakarta Area is composed by deposit which has various lithology characteristics. Based on its lithology types, colors, textures, mineral dan organic content from 22 wells scattered on Jakarta, lithofacies analysis and intra-wells data correlation can be done. From the analysis, it can be interpretated that Jakarta deposit deposited in marine, transition and terrestrial depositional environments. Terrestrial deposit characterized by domination of relatively coarse clastics and content of remaining roots, woods, plants, high content of quartz, lithic fragment, calcareous and oxidated appearace. The thickness of terrestrial deposit is thickening to south. Transitional deposit characterized by fine to medium clastics with dark color, high content of organic matter, various thickness in any ways. Marine deposit characterized by finer clastics, contain remain of shells, fosil, coral, limestone fragments, glauconites, calcareous. Marine deposit relatively thickening to north. Those lateral variety caused by tectonic, subsidence and stratigraphic condition. Deposition of Jakarta deposit from the data research was started on marine depositional environment which surrounded by the event of cycle of regression and transgression then ended with regression which ongoing until form shore line in north Jakarta nowadays.

Keywords: deposit, Indonesia, Jakarta, sediment, stratigraphy

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Authors: Janell Jayamohan

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A pilot project based on the Theory of Planned Behavior was completed at a single sex female international high school in order to improve the quality of comprehensive sex education in a 12th grade classroom. The student sample is representative of a growing phenomenon of “Third Culture Kids” or global nomads; often in today’s world, culture transcends any one dominant influence and blends values from multiple sources. The Objective was to improve intentions of condom use during the students’ first or next intercourse. A peer-education session which focused on condom attitudes, social norms, and self-efficacy - central tenets of the Theory of Planned Behavior - was added to an existing curriculum in order to achieve this objective. Peer educators were given liberty of creating and executing the lesson to their homeroom, a sample of 23 senior students, with minimal intervention from faculty, the desired outcome being that the students themselves would be the best judge of what is culturally relevant and important to their peers. The school nurse and school counselor acted as faculty facilitators but did not assist in the creation or delivery of the lesson, only checked for medical accuracy. The participating sample of students completed a pre and post-test with validated questions assessing changes in attitudes and overall satisfaction with the peer education lesson. As this intervention was completed during the Covid-19 pandemic, the peer education session was completed in a virtual classroom environment, limiting the modes of information delivery available to the peer educators, but is planned to be replicated in an in-person environment in subsequent cycles.

Keywords: adolescents, condoms, peer education, sex education, theory of planned behavior, third culture kids

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Authors: Minakshi Jain, I. P. Singh

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The mountain system makes the one fifth of the world’s landscape and is the home to the 600 million people. Though hills and mountains contain about 10 percent of the total population of the country, yet almost half of the country’s population living in or adjacent to the mountain areas depend directly or indirectly on the resources of the hills. Mountain environments are essential to the survival of the global ecosystems, as they sustain the economy of India through its perennial river system and precious forest wealth. Hill areas, with distinct climate, diverse vegetation and valuable flora & fauna are distinguished primarily by unique eco-system, rich both in bio-diversity and visual resources. These areas have special significance in terms of environment and economy. Still the irony is that these mountain ecosystems are fragile and highly susceptible to disturbance, with a low ability to rebound and heal after damage. Hills are home to endangered species, biological diversity and an essential part of the ecosystem. They are extremely sensitive to any human related development. Natural systems are the most ignored in the hills. The way the cities and towns have encroached them today has the serious repercussions on the climate. Amidst immense resources and constraints of nature, the town had a fantastic diversity of cultural and ethnic characteristics nurtured through ages along river basin and valley strung across the length and breadth of this Himalayan setting.

Keywords: eco-system, bio-diversity, urban sprawl, vernacular landscape

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Authors: Ahmed Azizeldein Abubaker Abdelhafez

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This review explores the application of biochar as a strategy for enhancing soil fertility in arid regions, with a focus on Arab countries. Biochar, derived from the carbonization of biomass under low-oxygen conditions, has shown promise in improving the physical and chemical properties of soil, such as increasing water retention and nutrient availability. Despite the challenging conditions of arid and semi-arid regions, characterized by poor soil fertility and severe land degradation, biochar application has emerged as a viable method to enhance agricultural productivity and mitigate environmental issues. This paper examines various aspects of biochar, including production methods, such as pyrolysis and gasification, and the effects of biochar on soil fertility. It discusses different application techniques and presents case studies from Arab countries like Egypt, the United Arab Emirates, Saudi Arabia, Qatar, Oman, and Kuwait, highlighting the successes and challenges faced in implementing biochar technology. The review also addresses the limitations of biochar use in arid regions and suggests future research directions to optimize its effectiveness. Overall, this study underscores the potential of biochar to contribute significantly to sustainable agriculture and ecological restoration in arid environments, advocating for integrated strategies that combine biochar application with other innovative agricultural practices.

Keywords: biochar, soil fertility, arid region, Arab countries, challenges and limitations

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Authors: Samuel Quashie

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PhDs in Construction Management often designs their methods based on those established in social sciences using theoretical models, to collect, gather and analysis data to answer research questions. Work aim is to apply qualitative and quantitative as a data analysis method, and as part of the theoretical framework - descriptive theory. To improve the ability to replicate the contribution to knowledge the research. Using practical triangulation approach, which covers, interviews and observations, literature review and (archival) document studies, project-based case studies, questionnaires surveys and review of integrated systems used in, construction and construction related industries. The clarification of organisational context and management delivery that influences organizational performance and quality of product and measures are achieved. Results illustrate improved reliability in this research approach when interpreting real world phenomena; cumulative results of research can be applied with confidence under similar environments. Assisted validity of the PhD research outcomes and strengthens the confidence to apply cumulative results of research under similar conditions in the Built Environment research systems, which have been criticised for the lack of reliability in approaches when interpreting real world phenomena.

Keywords: case studies, descriptive theory, theoretical framework, qualitative and quantitative research

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Authors: M. Chen, H. Lee, D. M. Weary

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China is the world’s largest egg producer, with more than 90% of production occurring in conventional cages. Cage-free housing systems offer the potential for improving hen welfare, but the growth of this system requires consumer demand, making it is important to understand consumers’ willingness to engage with cage-free eggs. Previous survey research indicates that the majority of Chinese consumers have a basic understanding of cage-free eggs and that some are willing to pay a price premium for these eggs. The aim of this research is to understand consumer behaviour, experience, and motivations when purchasing cage-free eggs in China. Purposive sampling will be used to select 20 participants from each of 2 groups: 1) consumers of cage-free eggs and 2) sales representatives who promote these eggs directly to consumers in supermarkets. This 4-month study will use methods of virtual ethnography to interact with participants repeatedly. Consumers will be asked to share their egg shopping, cooking, and eating experiences, and sales representatives will be asked to share their experiences promoting the eggs to consumers. Data collection will involve audio-recorded interviews, informal conversations (casual texts and calls), participant observation (video calling during shopping, cooking, and eating), and informant diaries (written reflections, photos, videos). All data (field notes, transcripts, diaries, photos, and videos) will be analyzed using Thematic Analysis. We expect that these will result in a nuanced understanding of consumer purchasing behaviour and motivation and will thus help identify strategies to promote higher animal welfare and cage-free egg products in China.

Keywords: animal welfare, cage-free eggs, China, consumer behaviour, ethnography

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Authors: Mojtaba Fayaz, Richard Hallal

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This study examines the various types of dangers that our virtual environment is vulnerable to, including how it can be attacked and how to avoid/secure our data. The terrain of cyberspace is never completely safe, and Covid- 19 has added to the confusion, necessitating daily periodic checks and evaluations. Cybercriminals have been able to enact with greater skill and undertake more conspicuous and sophisticated attacks while keeping a higher level of finesse by operating from home. Different types of cyberattacks, such as operation-based attacks, authentication-based attacks, and software-based attacks, are constantly evolving, but research suggests that software-based threats, such as Ransomware, are becoming more popular, with attacks expected to increase by 93 percent by 2020. The effectiveness of cyber frameworks has shifted dramatically as the pandemic has forced work and private life to become intertwined, destabilising security overall and creating a new front of cyber protection for security analysis and personal. The high-rise formats in which cybercrimes are carried out, as well as the types of cybercrimes that exist, such as phishing, identity theft, malware, and DDoS attacks, have created a new front of cyber protection for security analysis and personal safety. The overall strategy for 2022 will be the introduction of frameworks that address many of the issues associated with offsite working, as well as education that provides better information about commercialised software that does not provide the highest level of security for home users, allowing businesses to plan better security around their systems.

Keywords: cyber security, authentication, software, hardware, malware, COVID-19, threat actors, awareness, home users, confidentiality, integrity, availability, attacks

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Authors: Hamisu Jibril

Abstract:

The study explores changes in plant species composition along disturbance gradient in urban areas in Nigeria at Bayero University Kano campuses. The aim is to assess changes in plant species composition and distribution within a degraded dryland environment in Kano Metropolis, Nigeria. Vegetation sampling was conducted using plots quadrat and transect methods, and different plant species were identified in the three study sites. Data were analyzed using ANOVA, t-tests and conventional indices to compare species richness, evenness and diversity. The study found no significant differences in species frequency among sites or sampling methods but observed higher species richness, evenness and diversity values in grasses species compared to trees. The study addressed changes in plant species composition along a disturbance gradient in an urban environment, focusing on species richness, evenness, and diversity. The study contributes to understanding the vegetation dynamics in degraded urban environments and highlights the need for conservation efforts. The research also adds to the existing literature by confirming previous findings and suggesting re-planting efforts. The study suggests similarities in plant species composition between old and new campus areas and emphasizes the importance of further investigating factors leading to vegetation loss for conservation purposes.

Keywords: species diversity, urban kano, dryland environment, vegetation sampling

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Authors: Bo-Bin Xiaoa, Chia-Yi Liua

Abstract:

In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: Athira M., Prakasha G. S.

Abstract:

The rising prevalence of academic entitlement among school and college students necessitates a comprehensive investigation. This study focuses on discovering gender differentials in academic entitlement and their nexus with diverse grade negotiation behaviors within the undergraduate (UG) student cohort. Grade negotiation behaviors, encompassing a range from amicable discussions to more assertive tactics, are influenced by students' perceptions of their academic entitlement. The research delves into the broader significance of academic entitlement, considering its implications for student-teacher conflicts and the dynamics it introduces into the educational field. Employing a quantitative research approach, data from UG students is meticulously analyzed. Mann-Whitney U tests unveil pronounced gender difference in academic entitlement, with females demonstrating higher entitlement levels. Furthermore, the study unearths significant correlations between academic entitlement and specific negotiation styles, notably yielding and forcing strategies, albeit with minimal impact on academic performance. These findings provide a foundational understanding for educators and institutions to foster equitable learning environments and formulate effective conflict resolution strategies, ultimately elevating the quality of the educational experience. Moreover, this study opens avenues for future research, exploring interventions to enhance negotiation skills and diving deeper into the intricate dimensions of academic entitlement within academic life.

Keywords: academic entitlement, grade negotiation, negotiation styles, student-teacher conflict

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Authors: A. Degale Desta, Cheng Jian

Abstract:

Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: William J. Crowther, Conor Marsh

Abstract:

Object-based flow simulation allows fast computation of arbitrarily complex aerodynamic models made up of simple objects with limited flow interactions. The proposed approach is universally applicable to objects made from arbitrarily scaled ellipsoid primitives at arbitrary aerodynamic attitude and angular rate. The use of a component-based aerodynamic modelling approach increases efficiency by allowing selective inclusion of different physics models at run-time and allows extensibility through the development of new models. Insight into the numerical stability of the model under first order fixed-time step integration schemes is provided by stability analysis of the drag component. The compute cost of model components and functions is evaluated and compared against numerical benchmarks. Model static outputs are verified against theoretical expectations and dynamic behaviour using falling plate data from the literature. The model is applied to a range of case studies to demonstrate the efficacy of its application in extensibility, ease of use, and low computational cost. Dynamically complex multi-body systems can be implemented in a transparent and efficient manner, and we successfully demonstrate large scenes with hundreds of objects interacting with diverse flow fields.

Keywords: aerodynamics, real-time simulation, low-order model, flight dynamics

Procedia PDF Downloads 90