Search results for: deep composite kernel

Authors: Jafar Razmi

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Integral abutment bridges are bridges that do not have joints. If these bridges are subject to large seasonal and daily temperature variations, the expansion and contraction of the bridge slab is transferred to the piles. Since the piles are deep into the soil, displacement induced by slab can cause bending and stresses in piles. These stresses cause fatigue and failure of piles. A complex mechanical interaction exists between the slab, pile, soil and abutment. This complex interaction needs to be understood in order to calculate the stresses in piles. This paper uses a mechanical approach in developing analytical equations for the complex structure to determine the stresses in piles. The solution to these analytical solutions is developed and compared with finite element analysis results and experimental data. Our comparison shows that using analytical approach can accurately predict the displacement in piles. This approach offers a simplified technique that can be utilized without the need for computationally extensive finite element model.

Keywords: integral abutment bridges, piles, thermo-mechanical stress, stress and strains

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Authors: Seyfullah Madakbas, Hatice Birtane, Memet Vezir Kahraman

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In this study, we aimed to synthesize and characterize polyhedral oligomeric silsesquioxanes containing polyimide nanocomposite. Polyimide nanocomposites widely have been used in membranes in fuel cell, solar cell, gas filtration, sensors, aerospace components, printed circuit boards. Firstly, polyamic acid was synthesized and characterized by Fourier Transform Infrared. Then, polyhedral oligomeric silsesquioxanes containing polyimide nanocomposite was prepared with thermal imidization method. The obtained polyimide nanocomposite was characterized by Fourier Transform Infrared, Scanning Electron Microscope, Thermal Gravimetric Analysis and Differential Scanning Calorimetry. Thermal stability of polyimide nanocomposite was evaluated by thermal gravimetric analysis and differential scanning calorimetry. Surface morphology of composite samples was investigated by scanning electron microscope. The obtained results prove that successfully prepared polyhedral oligomeric silsesquioxanes are containing polyimide nanocomposite. The obtained nanocomposite can be used in many industries such as electronics, automotive, aerospace, etc.

Keywords: polyimide, nanocomposite, polyhedral oligomeric silsesquioxanes

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Authors: Anushree S. Panikkassery

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The paper analyses the pattern and trend of maternal health care in south Indian states. It studies the interstate disparities in terms of maternal health care. It also compares the trends in terms of achieving the target of sustainable development Goal is related to maternal health. The maternal health care (MHC) development is one of the key indicators for the development of health sector in the country and assumes significance from the socioeconomic and developmental perspectives. Maternal health care mainly consists of composite care during pregnancy, child birth as well as postpartum period. Antenatal care, identification, referral and management of high risk pregnancies, safe and healthy child birth and early postnatal care are some of the important issues pertaining to maternal health. Data is collected from national family health survey 1992-93, 1998-99, 2005-06, and 2015-16. A concentration index is used to study the disparities in equity of maternal health among south Indian states. The study shows that there has been an improvement in maternal health care in south Indian states with Kerala topping among the states. But there exist disparities among the south Indian states.

Keywords: antenatal care, disparities, equity, maternal health

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Authors: Jiahui Song, Ravindra P. Joshi

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One of the biggest obstacles to human space exploration of the solar system is the risk posed by prolonged exposure to space radiation. It is generally agreed that particles with energies around 1-2 GeV per nucleon are the most damaging to humans. Passive shielding techniques entail using solid material to create a shield that prevents particles from penetrating a given region by absorbing the energy of incident particles. Previous techniques resulted in adding ‘dead mass’ to spacecraft, which is not an economically viable solution. Additionally, collisions of the incoming ionized particles with traditional passive protective material lead to secondary radiation. This study develops an enhanced hybrid active space radiation bio-shielding concept, a combination of the electrostatic and magnetostatic shielding, by varying the size of the magnetic ring, and by having multiple current-carrying rings, to mitigate the biohazards of severe space radiation for the success of deep-space explorations. The simulation results show an unprecedented reduction of 1GeV GCR (Galactic Cosmic Rays) proton transmission to about 15%.

Keywords: bio-shielding, electrostatic, magnetostatic, radiation

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su

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Deep reinforcement learning has been applied to address various problems in robotics, such as autonomous driving and unmanned aerial vehicle. However, because of the sparse reward penalty for a collision with obstacles during the navigation mission, the agent fails to learn the optimal policy or requires a long time for convergence. Therefore, using obstacles and enemy agents, in this paper, we present a curriculum-based boost learning method to effectively train compound skills during multi-agent reinforcement learning. First, to enable the agents to solve challenging tasks, we gradually increased learning difficulties by adjusting reward shaping instead of constructing different learning environments. Then, in a benchmark environment with static obstacles and moving enemy agents, the experimental results showed that the proposed curriculum learning strategy enhanced cooperative navigation and compound collision avoidance skills in uncertain environments while improving learning efficiency.

Keywords: curriculum learning, hard exploration, multi-agent reinforcement learning, robotic navigation, sparse reward

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Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob

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Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.

Keywords: robotic vision, image processing, applications of robotics, artificial intelligent

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Authors: Ilan Tamir

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Fans’ chants in sports stadium have, over the years, become an integral part of the spectator experience. While chants add color, atmosphere, and a demonstration of fans’ support for their team, chants also play a significant role in defining fans’ perceptions of their team’s identity and its differentiation from other teams. An analysis of football chants may therefore shed light on fans’ deep-seated worldviews of their own role, their team, the sport in general, and even life itself. This study, based on an analysis of Israeli football chants over years, identifies key changing and stable perceptions of football fans. Overall 94 chants collected, over a period of five decades. After a pilot study, the chants organized in two groups (one covering 1970-1999 and the other 2000-2016). The chants analyzed through qualitative content analysis in order to understand fans values as a reflection of the society. Findings point to several values that have remained stable over years, including fans’ attitudes toward their team and its rivals, and their attitude toward God. On the other hand, recently emerging phenomena such as radicalization of hatred toward the commercialization of sport reflect social and cultural changes, both in and outside the world of sport.

Keywords: sport, fans, chants, soccer

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Authors: L. Kutateldze, T. Urushadze, R. Khvedelidze, N. Zakariashvili, I. Khokhashvili, T. Sadunishvili

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Microbial cellulase/xylanase have shown their potential application in various industries including pulp and paper, textile, laundry, biofuel production, food and feed industry, brewing, and agriculture. Extremophilic micromycetes and their enzymes that are resistant to critical values of temperature and pH, and retaining enzyme activity for a long time are of great industrial interest. Among strains of microscopic fungi from the collection of S. Durmishidze Institute of Biochemistry and Biotechnology, strains isolated from different ecological niches of Southern Caucasus-active producers of cellulase/xylanase have been selected by means of screening under deep cultivation conditions. Extremophilic micromycetes and their enzymes that are resistant to critical values of temperature and pH, and retaining enzyme activity for a long time are of great industrial interest. Among strains of microscopic fungi from the collection of S. Durmishidze Institute of Biochemistry and Biotechnology, strains isolated from different ecological niches of Southern Caucasus-active producers of cellulase/xylanase have been selected by means of screening under deep cultivation conditions. Representatives of the genera Aspergillus, Penicillium and Trichoderma are outstanding by relatively high activities of these enzymes. Among the producers were revealed thermophilic strains, representatives of the genus Aspergillus-Aspergillus terreus, Aspergillus versicolor, Aspergillus wentii, also strains of Sporotrichum pulverulentum and Chaetomium thermophile. As a result of optimization of cultivation media and conditions, activities of enzymes produced by the strains have been increased by 4 -189 %. Two strains, active producers of cellulase/xylanase – Penicillium canescence E2 (mesophile) and Aspergillus versicolor Z17 (thermophile) were chosen for further studies. Cellulase/xylanase enzyme preparations from two different genera of microscopic fungi Penicillium canescence E2 and Aspergillus versicolor Z 17 were obtained with activities 220 U/g /1200 U/g and 125 U/g /940 U/g, correspondingly. Main technical characteristics were as follows: the highest enzyme activities were obtained for mesophilic strain Penicillium canescence E2 at 45-500C, while almost the same enzyme activities were fixed for the thermophilic strain Aspergillus versicolor Z 17 at temperature 60-65°C, exceeding the temperature optimum of the mesophile by 150C. Optimum pH of action of the studied cellulase/xylanases from mesophileic and thermophilic strains were similar and equaled to 4.5-5.0 It has been shown that cellulase/xylanase technical preparations from selected strains of Penicillium canescence E2 and Aspergillus versicolor Z17 hydrolyzed cellulose of untreated wheat straw to reducible sugars by 46-52%, and to glucose by 22-27%. However the thermophilic enzyme preparations from the thermophilic A.versicolor strains conducted the process at 600C higher by 100C as compared to mesophlic analogue. Rate of hydrolyses of the pretreated substrate by the same enzyme preparations to reducible sugars and glucose conducted at optimum for their action 60 and 500C was 52-61% and 29-33%, correspondingly. Thus, maximum yield of glucose and reducible sugars form untreated and pretreated wheat straw was achieved at higher temperature (600C) by enzyme preparations from thermophilic strain, which gives advantage for their industrial application.

Keywords: cellulase/xylanase, cellulose hydrolysis, microscopic fungi, thermophilic strain

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Song Xinze, Cai Kejian

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To further explore the application of waste plastics in asphalt pavement, this paper begins with the classification and characteristics of waste plastics. It then provides a state-of-the-art review of the preparation methods and processes of waste plastic modifiers, waste plastic-modified asphalt, and waste plastic-modified asphalt mixtures. The paper also analyzes the factors influencing the compatibility between waste plastics and asphalt and summarizes the performance evaluation indicators for waste plastic-modified asphalt and its mixtures. It explores the research approaches and findings of domestic and international scholars and presents examples of waste plastics applications in pavement engineering. The author believes that there is a basic consensus that waste plastics can improve the high-temperature performance of asphalt. The use of cracking processes to solve the storage stability of waste plastic polymer-modified asphalt is the key to promoting its application. Additionally, the author anticipates that future research will concentrate on optimizing the recycling, processing, screening, and preparation of waste plastics, along with developing composite plastic modifiers to improve their compatibility and long-term performance in asphalt pavements.

Keywords: waste plastics, asphalt pavement, asphalt performance, asphalt modification

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Patricia P. M. C. Lourenco, Javier Bringué Sala, Anaisa D. A. de Sena

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Almost everyone in Dramaland knows the names of big Korean stars that grace their computer screens on a roll through social media and video streaming platforms that enable awareness of Korean dramas and lifestyle at a click. A surface culture instilled with notions of belonging has redefined the meaning of friendship and challenged deep inner values. Not everyone, however, knows Chinese Dramas or their stars, which is a consequence of Dramaland's focus on Korean dramas and promoting the Korean experience. Despite a parity in terms of production quality, star power, scripts and compelling visual settings, Chinese Dramas have been playing catch up to their famous counterparts. While they might have a strong competitive soft power for international drama fans, the soft power of Korean dramas is imbued with substantial societal values that they want to share with others. Those values are portrayed in an artistic way that connects with audiences who experience loneliness in the non-virtual world contrary to the way Chinese Dramas are perceived.

Keywords: Chinese dramas, fandom, Korean dramas, participatory culture, value perception, soft power, surface culture

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Authors: N. Philipova

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The influence of the geometric parameters of trapezoidal labyrinth channel on the emitter discharge is investigated in this work. The impact of the dentate angle, the dentate spacing, and the dentate height are studied among the geometric parameters of the labyrinth channel. Numerical simulations of the water flow movement are performed according to central cubic composite design using Commercial codes GAMBIT and FLUENT. Inlet pressure of the dripper is set up to be 1 bar. The objective of this paper is to derive a mathematical model of the emitter discharge depending on the dentate angle, the dentate spacing, the dentate height of the labyrinth channel. As a result, the obtained mathematical model is a second-order polynomial reporting 2-way interactions among the geometric parameters. The dentate spacing has the most important and positive influence on the emitter discharge, followed by the simultaneous impact of the dentate spacing and the dentate height. The dentate angle in the observed interval has no significant effect on the emitter discharge. The obtained model can be used as a basis for a future emitter design.

Keywords: drip irrigation, labyrinth channel hydrodynamics, numerical simulations, Reynolds stress model.

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Authors: Zahra Khan

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Hydrogels are a macromolecular network of hydrophilic copolymers with physical or chemical cross-linking structures with significant water uptake capabilities. They are a promising substrate for surface-enhanced Raman spectroscopy (SERS) as they are both flexible and biocompatible materials. Conventional SERS-active substrates suffer from limitations such as instability and inflexibility, which restricts their use in broader applications. Gelatin-based hydrogels have been synthesised in a facile and relatively quick method without the use of any toxic cross-linking agents. Composite gel material was formed by combining the gelatin with simple polymers to enhance the functional properties of the gel. Gold nanoparticles prepared by a reproducible seed-mediated growth method were combined into the bulk material during gel synthesis. After gel formation, the gel was submerged in the analyte solution overnight. SERS spectra were then collected from the gel using a standard Raman spectrometer. A wide range of analytes was successfully detected on these hydrogels showing potential for further optimization and use as SERS substrates for biomedical applications.

Keywords: gelatin, hydrogels, flexible materials, SERS

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Authors: A. S. Bouchikhi, A. Megueni, S. Habibi

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One major problem when using bonded Fiber Reinforced Polymer is the presence of high inter facial stresses near the end of the composite laminate which might govern the failure of the strengthening schedule. It is known that the decrease of FRP plate thickness and the fitness of adhesive reduce the stress concentration at plate ends. Another way is to use a plate with a non uniform section or tapered ends and softer adhesive at the edges. In this paper, a comprehensive finite element (FE) study has been conducted to investigate the effect of mixed adhesive joints (MAJ) and tapering plate on the inter facial stress distribution in the adhesive layer, this paper presents the results of a study of application of two adhesives with different stiffnesses (bi-adhesive) along the joint strength length between the CFRP-strengthened steel beam for tapered and untapered plate on the distribution of inter facial stresses. A stiff adhesive was applied in the middle portion of the joint strength, while a low modulus adhesive was applied towards the edges prone to stress concentrations.

Keywords: FRP, mixed adhesive joints, stresses, tapered plate, retrofitted beams bonded

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Authors: Ma Lei-Lei, Zhou You

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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

Procedia PDF Downloads 90

Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu

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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.

Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature

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Authors: Juliana V. Pereira, Adriana S. M. Batista, Jefferson P. Nascimento, Clascídia A. Furtado, Luiz O. Faria

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The combination of the properties of graphene oxide (OG) and PVDF homopolymer makes their combined composite materials as multifunctional systems with great potential. Knowledge of the molecular structure is essential for better use. In this work, the degradation of PVDF polymer exposed to gamma irradiation in oxygen atmosphere in high dose rate has been studied and compared to degradation of PVDF/OG composites. The samples were irradiated with a Co-60 source at constant dose rate, with doses ranging from 100 kGy to 1,000 kGy. In FTIR data shown that the formation of oxidation products was at the both samples with formation of carbonyl and hydroxyl groups amongst the most prevalent products in the pure PVDF samples. In the other hand, the composites samples exhibit less presence of degradation products with predominant formation of carbonyl groups, these results also seen in the UV-Vis analysis. The results show that the samples of composites may have greater resistance to the irradiation process, since they have less degradation products than pure PVDF samples seen by spectroscopic techniques.

Keywords: gamma irradiation, PVDF, PVDF/OG composites, spectroscopic techniques

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Authors: G. L. Devnani, Shishir Sinha

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Natural fiber reinforced polymer composite is a very attractive area among the scientific community because of their low cost, eco-friendly and sustainable in nature. Among all advantages there are few issues which need to be addressed, those issues are the poor adhesion and compatibility between two opposite nature materials that is fiber and matrix and their relatively high water absorption. Therefore, natural fiber modifications are necessary to improve their adhesion with different matrices. Excellent properties could be achieved with the surface treatment of these natural fibers ultimately leads to property up-gradation of their reinforced composites with different polymer matrices. Lot of work is going on to improve the adhesion between reinforced fiber phase and polymer matrix phase to improve the properties of composites. Researchers have suggested various methods for natural fiber treatment like silane treatment, treatment with alkali, acetylation, acrylation, maleate coupling, etc. In this study a review is done on the different methods used for the surface treatment of natural fibers and what are the advance treatment methodologies for natural fiber surface treatment for property improvement of natural fiber reinforced polymer composites.

Keywords: composites, acetylation, natural fiber, surface treatment

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Authors: Ren Guangchun

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The village in the city is surrounded by formal cities but retains distinct social and morphological characteristics of the countryside, and has the ability of self-growth. County is the basic unit of urban-rural integration development, and urban village is the key focus of integration. At present, the flow of urban and rural factors in Chongqing does not match the development needs of urban villages. Based on the multi-case study of Chongqing 's districts and counties, this paper studies the characteristics of its geospatial advantages, composite functions, open spatial structure, pluralistic social structure, and reciprocity. From the aspects of community governance, social relations and space construction, this paper analyzes the dilemma of lack of subjectivity and social atomization faced by the interaction between urban villages and cities, and explores the strategies of community opening and social integration in urban villages, so as to present diversified landscapes and value spaces.

Keywords: gated community, open community, city update, Urban village

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Authors: Ghusen al-Kafri, Mohammed Ali Abdallah Elsageer, Ahmed Mohamed Hadya Alsdaai, Abdeimanam Salhien Salih Khalifa

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In this paper, external reinforcement to enhance a reinforced concrete structure performance has been done using externally bonded steel plate. This technique has been reported effective in enhancing the strength of reinforced concrete beam, a study to determine the effectiveness of steel plate as an external reinforcement was carried out. A total of two groups of beams and one group content five beams, each 750 mm long, 150 mm wide, and 150 mm deep were cast, strengthened and tested till failure under two point loads. One beam was act as a control beam without strengthening and other four beams were strengthened with steel plate at a different arrangement. Other group beams were strengthened with steel plate in shear zone and also strengthened at bottom as first group. The behaviours of the strengthened beams were studied through their load-deflection characteristic upon bending, cracking and mode of failure. The results confirmed that all steel plate arrangements enhanced the strength of the reinforced concrete beam, the positioning of the steel plate affect the moment carrying capacity of the beam.

Keywords: beams, bending, beflection, steel plates

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Authors: J. O. Idoko, I. Nwajiaku

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Unripe and ripe plantain were dried and milled into flour and used with wheat flour in biscuit production to determine the best plantain-wheat composite flour for biscuit production. The blends as follows: 100% wheat flour, 100% ripe plantain flour, 100% unripe plantain flour, 50% wheat flour and 50% ripe plantain flour and 50% wheat flour and 50% unripe plantain flour. The Biscuit samples were stored at ambient temperature for 8 weeks after which the equilibrium moisture content and water activity were determined. The sensory evaluation of the biscuit samples was also determined. The results of these analyses showed 100% unripe plantain flour as the most stable of the biscuit samples judging from its equilibrium moisture content level of 0.32% and water activity of 0.62. The sensory evaluation results showed Biscuit made from 150:50 ripe plantain and wheat flour as most generally accepted at 5% level of significance.

Keywords: biscuit, equilibrium moisture content, performance, plantain, water activity

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Authors: M. Khajezadeh, M. Saied Fallah Niasar, S. Ali Asli, D. Davani Davari, M. Godarzi, Y. Asgari

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This study aims to explore the joint application of both Boston and Ansoff matrices in the operational development of the product. We conduct deep analysis, by utilizing the Artificial Neural Network, to predict the position of the product in the market while the company is interested in increasing its share. The data are gathered from two industries, called hygiene and detergent. In doing so, the effort is being made by investigating the behavior of top player companies and, recommend strategic orientations. In conclusion, this combination analysis is appropriate for operational development; as well, it plays an important role in providing the position of the product in the market for both hygiene and detergent industries. More importantly, it will elaborate on the company’s strategies to increase its market share related to a combination of the Boston Consulting Group (BCG) Matrix and Ansoff Matrix.

Keywords: artificial neural network, portfolio analysis, BCG matrix, Ansoff matrix

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Authors: Farid Amidi Fazli

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Replacement of plastics used in the food industry seems to be a serious issue to overcome mainly the environmental problems in recent years. This study investigates the hydrophilicity and permeability properties of starch biopolymer which ethylene vinyl alcohol (EVOH) (0-10%) and nanocrystalline cellulose (NCC) (1 -15%) were used to enhance its properties. Starch -EVOH nanocomposites were prepared by casting method in different formulations. NCC production by acid hydrolysis was confirmed by scanning electron microscopy. Solubility, water vapor permeability, water vapor transmission rate and moisture absorbance were measured on each of the nanocomposites. The results were analyzed by SAS software. The lowest moisture absorbance was measured in pure starch nanocomposite containing 8% NCC. The lowest permeability to water vapor belongs to starch nanocomposite containing 8% NCC and the sample containing 7.8% EVOH and 13% NCC. Also, the lowest solubility was observed in the composite contains the highest amount of EVOH. Applied Process resulted in production of bio films which have good resistance to water vapor permeability and solubility in water. The use of NCC and EVOH leads to reduced moisture absorbance property of the biofilms.

Keywords: starch, EVOH, nanocrystalline cellulose, hydrophilicity

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Authors: S. P. Jordan, G. Christian, S. P. Jeffs

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Modern composite materials are increasingly being chosen in replacement of heavier metallic material systems within many engineering fields including aerospace and automotive industries. The increasing push towards satisfying environmental targets are fuelling new material technologies and manufacturing processes. This paper will introduce materials and manufacturing processes using metal matrix composites along with manufacturing processes optimized at Alvant Ltd., based in Basingstoke in the UK which offers modern, cost effective, selectively reinforced composites for light-weighting applications within engineering. An overview and introduction into modern optimized manufacturing methods capable of producing viable replacements for heavier metallic and lower temperature capable polymer composites are offered. A review of the capabilities and future applications of this viable material is discussed to highlight the potential involved in further optimization of old manufacturing techniques, to fully realize the potential to lightweight material using cost-effective methods.

Keywords: aluminium matrix composites, light-weighting, hybrid squeeze casting, strategically placed reinforcements

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Authors: Tegan H. Emerson, Colin C. Olson, George Stantchev, Jason A. Edelberg, Michael Wilson

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Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.

Keywords: motion tracks, persistence images, time-delay embedding, topological data analysis

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Authors: Alexander Hudson, Shaogang Gong

Abstract:

Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

Procedia PDF Downloads 128

Authors: Clarissa Delariarte

Abstract:

With the aim of helping the poorest of the poor achieve quality education, Psychology students supported and served as teacher assistants to its Early Childhood Education Center in two barangays since the program began in 1999. Making use of qualitative approach, the impact of the program to 29 alumni who served as teacher assistants between 2000-2014 was assessed. Results show that the impact to the alumni is in cognitive as well as social-emotional in terms of feelings of deep satisfaction and sense of volunteerism which is being carried out in their respective workspaces. They also expressed positive feelings of inspiration, gratefulness and happiness. A wider perspective in life, being confident, creative and resourceful was also articulated as concrete impacts. It is concluded that the program had an impact on helping the helper and is a concrete manifestation of the academe being successful in its commitment of forming individuals into becoming integrated and compassionate in the service of the Church and Society. It implies that more opportunities of helping others be provided to students since, in the final analysis, is actually an opportunity of helping the helper be of better service to others.

Keywords: applied psychology, life skill, qualitative research, quality education

Procedia PDF Downloads 183

Authors: Stamataki Erofili Nellie, Benardos Andreas

Abstract:

Winemaking and aging in Greece has been performed so far in special facilities, designed either as above ground or shallow underground buildings. The latter are well-known in Santorini as “canaves,” dating back to the 1700s. Canaves were mainly used for wine storage and aging, although occasionally, they included a winepress to complete there the whole wine production. On the other hand, wine caves are subterranean caves of the same use as canaves in the wine manufacturing industry, but they are excavated at a much greater depth of more than 53 meters or 175 feet. Whereas canaves or a typical wine cellar is around 10 feet deep, with is equivalent to almost 3 meters. This paper discusses the advantages and the disadvantages of creating a wine cave for the vinification of a winery in Greece and the financial investment or risk that has to be taken. The data presented and analysed are given from wineries in Greece and especially from those located in Santorini island. The estimation of the cost for the excavation of the model selected as a wine cave will be compared with the financial budget of the existing premises and facilities above ground in Greek wineries. In order to show whether it is viable for a greek winery to invest in a wine cave.

Keywords: underground space use, subterranean winery, wine cave, underground winery, greece

Procedia PDF Downloads 174