Search results for: flood features

Authors: Lauren Dixon, David Galvani

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Objective: Sharing devastating news with patients is often considered the most difficult task of doctors. This study aimed to explore patients’ perceptions of receiving bad news including which features improve the experience and which areas need refining. Methods: A questionnaire was written based on the steps of the SPIKES model for breaking bad news. 20 patients receiving treatment for a haematological malignancy completed the questionnaire. Results: Overall, the results are promising as most patients praised their consultation. ‘Poor’ was more commonly rated by women and participants aged 45-64. The main differences between the ‘excellent’ and ‘poor’ consultations include the doctor’s sensitivity and checking the patients’ understanding. Only 35% of patients were asked their existing knowledge and 85% of consultations failed to discuss the impact of the diagnosis on daily life. Conclusion: This study agreed with the consensus of existing literature. The commended aspects include consultation set-up and information given. Areas patients felt needed improvement include doctors determining the patient’s existing knowledge and exploring how the diagnosis will affect the patient’s life. With a poorer prognosis, doctors should work on conveying appropriate hope. The study was limited by a small sample size and potential recall bias.

Keywords: cancer, diagnosis, haematology, patients

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Authors: Muhammad Munir, Moazzam, Attia Saddique, Muhammad Waheed

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This study examines the complex interactions between entertainment, interaction, and authenticity aspects in the context of live streaming tourism e-commerce and how they affect tourists' intent to purchase. In the context of e-commerce live streaming, the goal of this study is to offer a thorough understanding of how these factors work together to influence consumers' intents to make purchases related to tourism. A sample of 250 respondents' information was gathered, and it was analyzed through Smart PLS 4. To ensure reliable measurement constructs, convergent and discriminant validity were evaluated. Discriminant validity was evaluated using the HTMT ratio approach, and the structural model was evaluated using structural equation modeling (SEM) with bootstrapping. Results showed that entertainment had a strong beneficial impact on social presence, highlighting the value of compelling content in raising users' sense of presence on live streaming platforms for tourism-related e-commerce. The lack of a direct relationship between Interactivity and Authenticity and Social Presence emphasizes the need for more research into certain characteristics of these dimensions that appeal to consumers in this situation.

Keywords: entertainment, interactivity, authenticity, tourism consumer’s purchase intention, social presence

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Authors: Mark Shiu-kee Shum, Dan Shi

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The paper aims to introduce the ‘Reading to Learn, Learning to Write’ (R2L) pedagogy and its application in teaching reading and writing to non-Chinese speaking (NCS) students in Hong Kong. Guided by the teaching and learning cycles accentuated in R2L pedagogy, sufficient scaffolding was provided for students with an explicit teaching method in literacy education. To understand the influence of using R2L pedagogy on students’ reading and writing abilities across different genres, quantitative data were collected by pre- and post-test of reading and writing tasks in the two different genres of narration and explanation. The pre-test and post-test were used to assess students’ writing performance based on the three textual components of context, discourse, and graphic features, while the reading abilities were assessed at the literal, inferred and interpretive levels of reading comprehension to measure the effectiveness of R2L pedagogy on their literacy improvement. The findings show the use of R2L pedagogy has been proven more effective in improving NCS students’ writing abilities than developing their reading capacity. It is hoped that the R2L-based pedagogic practices can serve as teaching references and pedagogic rationale for L1 language teachers and raise their metalinguistic awareness in teaching Chinese to non-Chinese speaking students in Hong Kong and beyond.

Keywords: pedagogical inclusiveness, literacy education, ethnic minority, reading and writing

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Authors: Shinoy Vengaramkode Bhaskaran, Kaushik Sathupadi, Sandesh Achar

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Human locomotion recognition is important in a variety of sectors, such as robotics, security, healthcare, fitness tracking and cloud computing. With the increasing pervasiveness of peripheral devices, particularly Inertial Measurement Units (IMUs) sensors, researchers have attempted to exploit these advancements in order to precisely and efficiently identify and categorize human activities. This research paper introduces a state-of-the-art methodology for the recognition of human locomotion patterns in a cloud environment. The methodology is based on a publicly available benchmark dataset. The investigation implements a denoising and windowing strategy to deal with the unprocessed data. Next, feature extraction is adopted to abstract the main cues from the data. The SelectKBest strategy is used to abstract optimal features from the data. Furthermore, state-of-the-art ML classifiers are used to evaluate the performance of the system, including logistic regression, random forest, gradient boosting and SVM have been investigated to accomplish precise locomotion classification. Finally, a detailed comparative analysis of results is presented to reveal the performance of recognition models.

Keywords: artificial intelligence, cloud computing, IoT, human locomotion, gradient boosting, random forest, neural networks, body-worn sensors

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Authors: Beatriz Suárez López, Gabriela Forman

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Kombucha (a symbiotic culture of bacteria and yeast) produces material capable of acquiring multiple shapes and textures that change significantly under different environment or temperature variations (e.g., when it is exposed to wet conditions), properties that may be explored in the scenic industry. This paper presents an analysis of its specific characteristics, exploring them as a non-conventional material for arts and performance. Costume Design uses surfaces as a powerful way of expression to represent concepts and stories; it may apply the unique features of nano bacterial cellulose (NBC) as assets in this artistic context. A mix of qualitative and quantitative (interventionist) methodology approaches were used -review of relevant literature to deepen knowledge on the research topic (crossing bibliography from different fields of studies: Biology, Art, Costume Design, etc.); as well as descriptive methods: laboratorial experiments, document quantities, observation to identify material properties and possibilities used to express a multiple narrative ideas, concepts and feelings. The results confirmed that NBC is an interactive and versatile material viable to be used in an alternative scenic context; its unique aesthetic and performative qualities, which change in contact to moisture, is a resource that can be used to show a visual and poetic impact on stage.

Keywords: biotechnological materials, contemporary dance, costume design, nano bacterial cellulose, performing arts

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: Khizir Mohd Ismail, Yu Jun Lim, Tshun Howe Yong

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The study of flow behavior in an enclosed volume using Computational Fluid Dynamics (CFD) has been around for decades. However, due to the knowledge limitation of adaptive grid methods, the flow in an enclosed volume near the moving wall using CFD is less explored. A CFD simulation of flow in an enclosed volume near a moving wall was demonstrated and studied by introducing a moving mesh method and was modeled with Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach. A static enclosed volume with controlled opening size in the bottom was positioned against a moving, translational wall with sliding mesh features. Controlled variables such as smoothed, crevices and corrugated wall characteristics, the distance between the enclosed volume to the wall and the moving wall speed against the enclosed chamber were varied to understand how the flow behaves and reacts in between these two geometries. These model simulations were validated against experimental results and provided result confidence when the simulation had shown good agreement with the experimental data. This study had provided better insight into the flow behaving in an enclosed volume when various wall types in motion were introduced within the various distance between each other and create a potential opportunity of application which involves adaptive grid methods in CFD.

Keywords: moving wall, adaptive grid methods, CFD, moving mesh method

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Authors: F. Boukazouha, G. Poulin-Vittrant, M. Rguiti, M. Lethiecq

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Since its invention, by virtue of its remarkable features, the piezoelectric transformer (PT) has drawn the attention of the scientific community. In past years, it has been extensively studied and its performances have been continuously improved. Nowadays, such devices are designed in more and more sophisticated architectures with associated models describing their behavior quite accurately. However, the different studies usually carried out on such devices mainly focus on their electrical characteristics induced by direct piezoelectric effects such as voltage gain, efficiency or supplied power. In this work, we are particularly interested in the characterization of mechanical displacements induced by the inverse piezoelectric effect in a PT in vibration. For this purpose, a detailed three-dimensional finite element analysis is proposed to examine the mechanical behavior of a Rosen-type transformer made of a single bar of soft PZT (P191) and with dimensions 22mm×2.35mm×2.5mm. At the first three modes of vibration, output voltage and mechanical displacements ux, uy and uz along the length, the width and the thickness, respectively, are calculated. The amplitude of displacements varies in a range from a few nanometers to a few hundred nanometers. The validity of the simulations was successfully confirmed by experiments carried out on a prototype using a laser interferometer. A good match was observed between simulation and experimental results, especially for us at the second mode. Such 3D simulations thus appear as a helpful tool for a better understanding of mechanical phenomena in Rosen-type PT.

Keywords: piezoelectricity, gain, dispalcement, simulations

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Authors: A. Elbaz, K. Spang

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Infrastructure projects are often subjected to delays and cost overruns and mistakenly described as unsuccessful projects. These projects have many peculiarities such as public attention, impact on the environment, subjected to special regulations, etc. They also deal with several stakeholders with different motivations and face unique risks. With this in mind we need to reconsider our approach to manage them, define their success factors and implement these success factors. Infrastructure projects are not only lacking a unified meaning of project success or a definition of success factors, but also a clear method to implement these factors. This paper investigates this gap and introduces a concept to implement success factors in an efficient way, taking into consideration the specific characteristics of infrastructure projects. This concept consists of six enablers such as project organization, project team, project management workflow, contract management, communication and knowledge transfer and project documentations. These enablers allow other success factors to be efficiently implemented in projects. In conclusion, this paper provides project managers as well as company managers with a tool to define and implement success factors efficiently in their projects, along with upgrading their assets for the coming projects. This tool consists of processes and validated checklists to ensure the best use of company resources and knowledge. Due to the special features of infrastructure projects this tool will be tested in the German infrastructure market. However, it is meant to be adaptable to other markets and industries.

Keywords: infrastructure projects, operative success factors, project success, success factors, transportation projects

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Authors: Misagh Irandoost Shahrestani, Mehdi Ashjaee, Shahrokh Zandieh Vakili

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In this paper, partially premixed laminar methane/air co-flow flame is studied experimentally. Methane-air flame was established on an axisymmetric coannular burner. The fuel-air jet flows from the central tube while the secondary air flows from the region between the inner and the outer tube. The aim is to investigate the flame features and to develop a nonintrusive method for temperature measurement of methane/air partially premixed flame using Mach-Zehnder interferometry method. Different equivalence ratios and Reynolds numbers are considered. Flame generic visible appearance was also investigated and its various structures were studied. Three distinguished flame regimes were seen based on its appearance. A double flame structure can be seen for the equivalence ratio in the range of 1<Φ<2.1. By adding air to the mixture up to Φ=4 the flame has the characteristics of both premixed and non-premixed flames. Finally for 4<Φ<∞ the flame mainly becomes non-premixed like and the luminous sooting region on its tip is the obvious feature of this type of flames. The Mach-Zehnder method is used to obtain temperature field of a transparent fluid by means of index of refraction. Temperature obtained from optical techniques was compared with that of obtained from thermocouples in order to validate the results. Good agreement was observed for these two methods.

Keywords: flame structure, Mach-Zehnder interferometry, partially premixed flame, temperature field

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Authors: Amine.Harbia, Hicham. Moutaabbidb, Yann. Le Godecb, Said. Benmokhtara, Mouhammed. Moutaabbida

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This study explores the structural and magnetic characteristics of newly synthesized double perovskite oxides, La₂NiₓCo1-xMnO₆, with x ranging from 0.2 to 0.8. Utilizing X-ray powder diffraction and SQUID magnetometry, we analyzed the compounds that consistently exhibit a monoclinic structure with the P21/n space group at ambient temperature. it findings reveal that as Ni2+ is progressively substituted by Co2+, there is a corresponding decrease in cell parameters, attributable to the smaller ionic radius of Ni2+ (0.69 Å) compared to Co2+ (0.74 Å). The crystal structure features octahedrally coordinated (Co/Ni)2+ and Mn4+ cations with oxygen, forming (Co/Ni)O6 and MnO6 octahedra linked via oxygen atoms along different crystallographic axes. Magnetic characterization conducted over a temperature range of 2 to 300 K in both DC and AC magnetic fields, showed a predominant paramagnetic to ferromagnetic transition between 232 K and 260 K, with the Curie temperature notably increasing with higher x values. Samples with x=0.2, 0.25, and 0.5 exhibited a secondary PM-FM transition between 200 K and 208 K. Cation ordering was quantitatively assessed, indicating a higher ordering in Ni2+-rich samples (x=0.75 and 0.8) at over 96%, whereas the sample with x=0.25 showed minimal ordering. Furthermore, the out-of-phase component of the AC susceptibility displayed frequency-dependent transitions between 65 K and 110 K, suggesting the presence of superparamagnetic domains across all samples.

Keywords: double perovskite oxides, magnetic transitions, cation ordering, squid magnetometry

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Authors: Collins Ogbu, Godwin Johnny Akpan, James NDA Jacob

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The debilitating outcomes of violent conflict, consummated by rural armed banditry have nonetheless, occasioned the need for the mapping of crime zones in Nigeria. As a step towards understanding the scourge of armed bandits, ungoverned spaces have been uncovered as the most dominant excuse for rural crimes and fierce confrontations. From the creeks of the Niger Delta to the forest of Sambisa, Small Arms and Light Weapons (SALW) have proliferated to the vagaries of national insecurity. While the trends present indications of State fragility, the paucity of governance in these so-called ungoverned spaces has persistently reflected a Hobbesian state of nature, where the fittest survives. This study, therefore, interrogates the demographic implications of these ungoverned spaces by specifically identifying the most immediate features of the characters in the areas under investigation. The Farmers-Herders Crises, Niger-Delta Militancy, Boko-Haram Insurgency, Armed Robbery, Kidnapping and Cattle Rustling all define the major focus. In undertaking this study, anecdotal sources will be relied on, while extant information on the concept of ungoverned spaces will be content-analyzed. It is hoped that the knowledge gathered, as a result, will ultimately aid in proffering a dependable panacea to the crises of rural armed banditry in Nigeria.

Keywords: ungoverned spaces, rural armed banditry, state fragility, conflicts

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Authors: Dalia Elleuch

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Narcissistic Personality Disorder (NPD) manifests as a personality disorder marked by inflated self-importance, heightened sensitivity to criticism, a lack of empathy, a preoccupation with appearance over substance, and features such as arrogance, grandiosity, a constant need for admiration, a tendency to exploit others, and an inclination towards demanding special treatment due to a sense of excessive entitlement (APA, 2013). This interdisciplinary study delves into NPD through the systematic synthesis of psycholinguistic analysis and neuroscientific correlates. The cognitive and emotional dimensions of NPD reveal linguistic patterns, including grandiosity, entitlement, and manipulative communication. Neuroscientific investigations reveal structural brain differences and alterations in functional connectivity, further explaining the neural underpinnings of social cognition deficits observed in individuals with NPD. Genetic predispositions and neurotransmitter imbalances add a layer of complexity to the understanding of NPD. The necessity for linguistic intervention in diagnosing and treating Narcissistic Personality Disorder is underscored by an interdisciplinary study that intricately synthesizes psycholinguistic analysis and neuroscientific correlates, offering a comprehensive understanding of NPD’s cognitive, emotional, and neural dimensions and paving the way for future practical, theoretical, and pedagogical approaches to address the complexities of this personality disorder.

Keywords: Narcissistic Personality Disorder (NPD), psycholinguistic analysis, neuroscientific correlates, interpersonal dysfunction, cognitive empathy

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Authors: Hiba Alkhalaf

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Historic cities and places of cultural significance is continuously under the pressure of economic development and social change that threaten its natural and cultural environment. The challenge here is to find a balance between preserving the cultural character while ensuring the socio-economic gains and continuity of its uniqueness. That is by sustaining the use, character, meaning and social interaction associated with the place, in other words the sense of place. The main argument here is what we attempt to conserve is the cultural physical and non-physical dimensions of the historic city. It is based on the proposition that what give the historic city its character is its strong sense of place- whether it is historic or current. When properly identified, its various dimensions (use, meaning and form) would help determine what to sustain and what not by making the development meaningfully related to the uniqueness of the historic place. Accordingly, those socio-economic features within the context of a changing historic environment needed to be clarified. This paper, thus, explores the various perspectives of the role of sense of place within the historic city and its connection to cultural heritage. It also reviews urban conservation practice as it is currently understood in the context of historic city development. It concludes that sense of place lies in complex interrelated relationships between various users of the place and the physical, economic, cultural, political, and environmental contexts in which they interact. This calls for the need to sustain the sense of place as part of the overall urban development and conservation strategies.

Keywords: cultural heritage, historic urban areas, urban development, sense of place

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Authors: M. Abbasi Layegh, S. Haghipour, K. Athari, R. Khosravi, M. Tafkikialamdari

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An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study.

Keywords: radif of Mirzâ Ábdollâh, Gushe, mel frequency cepstral coefficients, fuzzy c-mean clustering algorithm, k-nearest neighbors (KNN), gaussian mixture model (GMM), hidden markov model (HMM), support vector machine (SVM)

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Authors: Alexandra Steed

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Alexandra Steed URBAN was commissioned to undertake the South Essex Green and Blue Infrastructure Study (SEGBI) on behalf of the Association of South Essex Local Authorities (ASELA): a partnership of seven neighboring councils within the Thames Estuary. Located on London’s doorstep, the 70,000-hectare region is under extraordinary pressure for regeneration, further development, and economic expansion, yet faces extreme challenges: sea-level rise and inadequate flood defenses, stormwater flooding and threatened infrastructure, loss of internationally important habitats, significant existing community deprivation, and lack of connectivity and access to green space. The brief was to embrace these challenges in the creation of a document that would form a key part of ASELA’s Joint Strategic Framework and feed into local plans and master plans. Thus, helping to tackle climate change, ecological collapse, and social inequity at a regional scale whilst creating a relationship and awareness between urban communities and the surrounding landscapes and nature. The SEGBI project applied a ‘land-based’ methodology, combined with a co-design approach involving numerous stakeholders, to explore how living infrastructure can address these significant issues, reshape future planning and development, and create thriving places for the whole community of life. It comprised three key stages, including Baseline Review; Green and Blue Infrastructure Assessment; and the final Green and Blue Infrastructure Report. The resulting proposals frame an ambitious vision for the delivery of a new regional South Essex Estuary (SEE) Park – 24,000 hectares of protected and connected landscapes. This unified parkland system will drive effective place-shaping and “leveling up” for the most deprived communities while providing large-scale nature recovery and biodiversity net gain. Comprehensive analysis and policy recommendations ensure best practices will be embedded within planning documents and decisions guiding future development. Furthermore, a Natural Capital Account was undertaken as part of the strategy showing the tremendous economic value of the natural assets. This strategy sets a pioneering precedent that demonstrates how the prioritisation of living infrastructure has the capacity to address climate change and ecological collapse, while also supporting sustainable housing, healthier communities, and resilient infrastructures. It was only achievable through a collaborative and cross-boundary approach to strategic planning and growth, with a shared vision of place, and a strong commitment to delivery. With joined-up thinking and a joined-up region, a more impactful plan for South Essex was developed that will lead to numerous environmental, social, and economic benefits across the region, and enhancing the landscape and natural environs on the periphery of one of the largest cities in the world.

Keywords: climate change, green and blue infrastructure, landscape architecture, master planning, regional planning, social equity

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Authors: Kirti, Samanta Sekhar Khora

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Inflation serves different purposes in different organisms and adds beauty to their behavioral attributes. Pufferfishes are also known as blowfish, swellfish, and globefish due to their remarkable ability to puff themselves up like a balloon when threatened. This ability to inflate can be correlated with anatomical features that are unique to pufferfishes. Pufferfish skin provides a rigid framework to support the body contents and a flexible covering to allow whatever changes are necessary for remarkable inflation mechanism. Skin, the outer covering of animals is made up of collagen fibers arranged in more or less ordered arrays. The ventral skin of pufferfish stretches more than dorsal skin during inflation. So, this study is of much of the interest in comparing the structure and mechanical properties of these two skin regions. The collagen fibers were found to be arranged in different ordered arrays for ventral and dorsal skin and concentration of fibers were also found to be different for these two skin parts. Scanning electron microscopy studies of the ventral skin showed a unidirectional arrangement of the collagen fibers, which provide more stretching capacity. Dorsal skin, on the other hand, has an orthogonal arrangement of fibers. This provides more stiffness to the ventral skin at the time of inflation. In this study, the possible role of collagen fibers was determined which significantly contributed to the remarkable inflation mechanism of pufferfishes.

Keywords: collagen, histology, inflation, pufferfish, scanning electron microscopy, Small-Angle X-Ray Scattering (SAXS), transmission electron microscopy

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

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Authors: Jeffrey Cacho, Sherwin Reyes

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The research targeted enhancing energy utilization and reducing waste in roasting processes, particularly in Camarines Norte, where Bounty Agro Ventures Incorporated dominates through brands such as Chooks-to-Go, Uling Roaster, and Reyal. Competitors like Andok’s and Baliwag Lechon Manok also share the market. A staggering 90% of these businesses use traditional glass-type roasting furnaces fueled by wood charcoal, leading to significant energy loss and inefficiency due to suboptimal heat conservation. Only a mere 10% employ electric ovens. Many available furnaces, typically constructed from industrial materials through welding and other metal joining techniques, are not energy-efficient. Cost-prohibitive commercial options compel some micro-enterprises to fabricate their furnaces. The study proposed developing an eco-friendly, cost-effective roasting furnace with excellent heat retention. The distinct design aimed to reduce cooks' heat exposure and overall fuel consumption. The furnace features an angle bar frame, a combustion chute for fuel burning, a heat-retaining clay-walled chamber, and a top cover, all contributing to improved energy savings and user safety.

Keywords: biomass roasting furnace, heat storage, combustion chute, start-up roasting business

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Authors: Leila Goosen

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The research problem reported on in this paper relates to improving success in Computer Science and Information Technology subjects where students are learning applications, especially when teaching occurs in a distance education context. An investigation was launched in order to address students’ struggles with applications, and improve their assessment in such subjects. Some of the main arguments presented centre on formulating and situating significant concepts within an appropriate conceptual framework. The paper explores the experiences and perceptions of computing instructors, teaching assistants, students and higher education institutions on how they are empowered by using technologies such as myITLab. They also share how they are working with the available features to successfully teach applications to their students. The data collection methodology used is then described. The paper includes discussions on how myITLab empowers instructors, teaching assistants, students and higher education institutions. Conclusions are presented on the way in which this paper could make an original and significant contribution to the promotion and development of knowledge in fields related to successfully teaching applications for student learning, including in a distance education context. The paper thus provides a forum for practitioners to highlight and discuss insights and successes, as well as identify new technical and organisational challenges, lessons and concerns regarding practical activities related to myITLab as an implementation instance of distance education technologies.

Keywords: distance, education, myITLab, technologies

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Authors: J. Lu, H. Li, F. Cole

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This paper proposes a high-frequency rotary transformer (HFRT) for a separately excited synchronous machine (SESM) used in a flywheel energy storage system. The SESM can eliminate and reduce rare earth permanent magnet (REPM) usage and provide a better performance in renewable energy systems. However, the major drawback of such SESM is the necessity of brushes and slip rings to supply the field current, which increases the maintenance cost and operation reliability. To overcome these problems, an HFRT integrated with SiC semiconductor devices can replace brushes and slip rings in the SESM. The proposed HFRT features a high-frequency magnetic ferrite for both the stationary part as the transformer primary and the rotating part as the transformer secondary, as well as an air gap, allowing safe operation at high rotational speeds. Hence, this rotary transformer can enable the adoption of a wound rotor synchronous machine (WRSM). The HFRT, working at over 100kHz operating frequency, exhibits excellent performance of power efficiency and significant size reduction. The experimental validations to support the theoretical findings have been provided.

Keywords: brushes and slip rings, flywheel energy storage, high frequency rotary transformer, separately excited synchronous machine

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Authors: Changzhi Jiang, Chunyu Ding, Yan Su, Jiawei Li, Ravi Sharma, Yuanzhou Liu, Jiangwan Xu

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Early Mars is believed to have had extensive liquid water activity, which has now predominantly transitioned to a frozen state, with the majority of water stored in polar ice caps. It has long been deemed that the shallow subsurface of Mars' mid-to-low latitudes is devoid of liquid water. However, geological features observed at the Tianwen-1 landing site hint potential subsurface water. Our research indicates that the shallow subsurface at the Tianwen-1 landing site consists primarily of diluvium deposits containing liquid brine and brine ice, which exhibits diurnal thermal convection processes. Here we report the relationship between the loss tangent and temperature of materials within 5 meters depth of the subsurface at the Tianwen-1 landing site, as in-situ detected by high-frequency radar and climate station onboard the Zhurong rover. When the strata temperature exceeds ~ 240 K, the mixed brine ice transitions to liquid brine, significantly increasing the loss tangent from an average of ~ 0.0167 to a maximum of ~ 0.0448. This finding indicates the presence of substantial subsurface water in Mars' mid-to-low latitudes, influencing the shallow subsurface heat distribution and contributing to the current Martian hydrological cycle.

Keywords: water on mars, mars exploration, in-situ radar detection, tianwen-1 mission

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Authors: Hadjadj Abdechafik, Kious Mecheri, Ameur Aissa

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The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the Root Mean Square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an online monitoring system. Although we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal, this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored.

Keywords: flank wear, vibration, milling, signal processing, monitoring

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Authors: Georgii Emelianov, Mikhail Polikarpov, Fabian Hübner, Jochen Deuse, Jochen Schiemann

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Recycling refrigerating appliances plays a major role in protecting the Earth's atmosphere from ozone depletion and emissions of greenhouse gases. The performance of refrigerator recycling plants in terms of material retention is the subject of strict environmental certifications and is reviewed periodically through specialized audits. The continuous collection of Refrigerator data required for the input-output analysis is still mostly manual, error-prone, and not digitalized. In this paper, we propose an automated data collection system for recycling plants in order to deduce expected material contents in individual end-of-life refrigerating appliances. The system utilizes laser scanner measurements and optical data to extract attributes of individual refrigerators by applying transfer learning with pre-trained vision models and optical character recognition. Based on Recognized features, the system automatically provides material categories and target values of contained material masses, especially foaming and cooling agents. The presented data collection system paves the way for continuous performance monitoring and efficient control of refrigerator recycling plants.

Keywords: automation, data collection, performance monitoring, recycling, refrigerators

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Authors: Surendra Kumar Patel

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Disability is not just a health problem; it is a complex phenomenon, reflecting the interaction between features of a person’s age and physiology. Population ageing is a major demographic issue for India in the 21st century. Older population of India constituted 8% of total population, while 5.19% has affected by disability of older age group. Objective of the present research paper is to examine the state wise differential in disability among 60+ population and to access the health care of disabled population especially the 60+ disabled persons. The data sources of the present paper are census 2001 and 2011. For analyzing the state wise differentials by disability types and comparative advantage of data, rate, ratio, and percentage have been used. The Standardized Index of Diversity of Disability (SIDD) studies differential and diversity in disability. The results show that there are 5.19% persons have disability among 60+ population and sex differential not very significant, as it is 5.3 % of male and 5.05% in female in India but place of residence shows significant variation from 2001 to 2011 census. There is huge diversity in disability prevalence among 60+ in India, highest in Sikkim followed by Rajasthan, approximately, they comprise 11%, and the lowest found in Tamil Nadu as 2.53%. This huge gap in prevalence percentage shows the health care needs of highly prevailing states.

Keywords: disability, Standardized Index of Diversity of Disability (SIDD), differential and diversity in disability, 60+ population

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

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The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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Authors: Mohammad Besharatloo

Abstract:

Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

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Authors: Rezvan Khavari

Abstract:

The Zagros fold-thrust belt in SW Iran is a part of the Alpine-Himalayan system which consists of a variety of structures with different sizes or geometries. The study area is Chamshir Dam, which is located on the Zohreh River, 20 km southeast of Gachsaran City (southwest Iran). The satellite images are valuable means available to geologists for locating geological or geomorphological features expressing regional fault or fracture systems, therefore, the satellite images were used for structural analysis of the Chamshir dam area. As well, using the DEM and geological maps, 3D Models of the area have been constructed. Then, based on these models, all the acquired fracture traces data were integrated in Geographic Information System (GIS) environment by using Arc GIS software. Based on field investigation and DEM model, main structures in the area consist of Cham Shir syncline and two fault sets, the main thrust faults with NW-SE direction and small normal faults in NE-SW direction. There are three joint sets in the study area, both of them (J1 and J3) are the main large fractures around the Chamshir dam. These fractures indeed consist with the normal faults in NE-SW direction. The third joint set in NW-SE is normal to the others. In general, according to topography, geomorphology and structural geology evidences, Chamshir dam has a potential for sliding in some parts of Gachsaran formation.

Keywords: DEM, chamshir dam, zohreh river, satellite images

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Authors: Ruchi Makani, B. V. R. Reddy

Abstract:

Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

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Authors: Harleen Kaur, Richa

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Plants produce a large variety of secondary metabolites. Phenolics are the compounds that contain hydroxyl functional group on an aromatic ring. These are chemically heterogeneous compounds. Some are soluble only in organic solvents, some are water soluble and others are large insoluble polymers. Flavonoids are one of the largest classes of plant phenolics. The carbon skeleton of a flavonoid contains 15 carbons arranged in two aromatic rings connected by a three carbon ridge. Both phenolics and flavonoids are good natural antioxidants. Four Indian aromatic plants were selected for the study i.e, Achillea species, Jasminum primulinum, Leucas cephalotes and Leonotis nepetaefolia. All the plant species were collected from Chail region of Himachal Pradesh, India. The identifying features and anatomical studies were done of the part containing the essential oils. Phenolic cotent was estimated by Folin Ciocalteu’s method and flavonoids content by aluminium chloride method. Antioxidant property was checked by using DPPH method. Maximum antioxidant potential was found in Achillea species, followed by Leonotis nepetaefolia, Jaminum primulinum and Leucas cephalotes. Phenolics and flavonoids are important compounds that serve as defences against herbivores and pathogens. Others function in attracting pollinators and absorbing harmful radiations.

Keywords: antioxidants, DPPH, flavonoids, phenolics

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