Search results for: solar architecture

Authors: Lamaa Sellami, Bechir Alaya

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Nowadays, video-on-demand (VoD) applications are becoming one of the tendencies driving vehicular network users. In this paper, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different cars included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over VANET. The proposed algorithm takes advantage of the concept of small cells and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)- Advanced network. The proposed clustering algorithm considers multiple characteristics such as the vehicle’s position and acceleration to reduce latency and packet loss. Therefore, each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.

Keywords: video-on-demand, vehicular ad-hoc network, mobility, vehicular traffic load, small cell, wireless backhaul, LTE-advanced, latency, packet loss

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Authors: Leila Trabelsi

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The urbanization of Information Systems (IS) is an effective approach to master the complexity of the organization. It strengthens the coherence of IS and aligns it with the business strategy. Moreover, this approach has significant advantages such as reducing Information Technologies (IT) costs, enhancing the IS position in a competitive environment and ensuring the scalability of the IS through the integration of technological innovations. Therefore, the urbanization is considered as a business strategic decision. Thus, its embedding becomes a necessity in order to improve the IS practice. However, there is a lack of experimental cases studying meta-modelling of Urbanized Information System (UIS). The aim of this paper addresses new urbanization content meta-model which permits modelling, testing and taking into consideration organizational aspects. This methodological framework is structured according to two main abstraction levels, a conceptual level and an operational level. For each of these levels, different models are proposed and presented. The proposed model for has been empirically tested on company. The findings of this paper present an experimental study of urbanization meta-model. The paper points out the significant relationships between dimensions and their evolution.

Keywords: urbanization, information systems, enterprise architecture, meta-model

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Authors: Ahmad Al Aboudi

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The Department of Archaeology at King Saud University conduct a long Term excavations since 2004 at the archaeological site of (Qurh) in Al-Ula area. The history of the site goes back to the eighth century AD. The main aim of the excavations is the training of the students on the archaeological field work associated with the scientific skills of exploring, surveying, classifying, documentations and other necessary in the field archaeology. During the 12th Season of Excavations, an area of 20 × 40 m2 of the site was excavated. The depth of the excavating the site was reached to 2-3 m. Many of the architectural features of a residential area in the northern part of the site were excavated this season. Circular walls made of mud-brick and a brick column drums and tiles made of clay were revealed this season. Additionally, lots of findings such as Gemstones, jars, ceramic plates, metal, glass, and fabric, as well as some jewelers and coins were discovered. This paper will deal with the main results of this field project including the architectural features and phenomena and their interpretations, the classification of excavated material culture remains and stratigraphy.

Keywords: Islamic architecture, Islamic art, excavations, early Islamic city

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Authors: Somnath Mahato, Minarul Islam Sarkar, Luis Guillermo Gerling, Joaquim Puigdollers, Asit Kumar Kar

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Nanostructured Zinc Oxide (ZnO) thin films have been successfully deposited on indium tin oxide (ITO) coated glass substrates by a simple two electrode electrodeposition process at constant potential. The preparative parameters such as deposition time, deposition potential, concentration of solution, bath temperature and pH value of electrolyte have been optimized for deposition of uniform ZnO thin films. X-ray diffraction studies reveal that the prepared ZnO thin films have a high preferential oriented c-axis orientation with compact hexagonal (wurtzite) structure. Surface morphological studies show that the ZnO films are smooth, continuous, uniform without cracks or holes and compact with nanorod-like structure on the top of the surface. Optical properties reveal that films exhibit higher absorbance in the violet region of the optical spectrum; it gradually decreased in the visible range with increases in wavelength and became least at the beginning of NIR region. The photoluminescence spectra shows that the observed peaks are attributed to the various structural defects in the nanostructured ZnO crystal. The microstructural and optical properties suggest that the electrodeposited ZnO thin films are suitable for application in photosensitive devices such as photovoltaic solar cells photoelectrochemical cells and light emitting diodes etc.

Keywords: electrodeposition, microstructure, optical properties, ZnO thin films

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Authors: Ravi Raghav Sonani, Niraj Kumar Singh, Jitendra Kumar, Datta Madamwar

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Phycobiliproteins (PBPs) are light harvesting proteins showing very strong absorbance and fluorescence in the visible range of the solar spectrum. Phycoerythrin (PE) and phycocyanin (PC) are majorly found PBPs in the cyanobacteria and red algae. In the present study, we have investigated the reactive oxygen species (ROS)-averting capacity of purified PE and PC of cyanobacterial origin. Furthermore, the possibility - whether the ROS-averting potential of PBPs can be explored in the therapeutics of oxidative stress associated physiological anomalies including aging and neurodegenerative diseases. The nematode Caenorhabditis elegans has been used as model organism in this study. PE and PC treatment moderated normal aging and associated physiological functionalities like pharyngeal pumping and locomotion of C. elegans. Moreover, PE-treatment enhanced the stress (oxidative and heat) tolerance upon PE and PC treatment. Specifically, PE treatment was also noted to moderate the progression of Alzheimer’s disease in transgenic C. elegans CL4176. However, PC-treatment curtailed the polyQ aggregation mediated proteotoxicity in C. elegans AM141 (Huntington disease model) under stressed (paraquat stress) as well as normal conditions. The effectiveness of PE and PC in expanding the lifespan of mutant C. elegans knockout for some up- (daf 16) and down- (daf-2 and age-1) stream regulators of insulin/IGF-1 signalling (IIS) shows the independency of their effects from DAF-2–AGE-1–DAF-16 signalling pathway. In conclusion, the present report demonstrates the anti-aging and neuro-protective potential of cyanobacterial PE and PC.

Keywords: phycobiliproteins, aging, alzheimer, huntington, C. elegans

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: Manal E. A Elhalwagy, Nadia Amin Abdulmajeed, Hanan S. Alnahdi, Enas N. Danial

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Baron is herbicide includes (48% glyphosate) widely used in Egypt. The present study assesses the cytotoxic and genotoxic effect of baron on rats liver. Two groups of rats were treated orally with 1/10 LD 50, (275.49 mg kg -1) and 1/40 LD 50, (68.86 mg kg-1) glyphosate for 28 days compared with control group. Serum and liver tissues were taken at 14 and 28 days of treatment. An inhibition in Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities were recorded at both treatment periods and reduction in total serum protein (TP) and albumin (ALB). However, non-significant changes in serum acetylcholinesterase (AChE). Elevation in oxidative stress biomarker malondyaldehyde (MDA) and the decline in detoxification biomarker total reduced glutathione (GSH), Glutathione S-transferase (GST) and superoxide dismutase (SOD) in liver tissues led to increase in percentage of DNA damage. Destruction in liver tissue architecture was observed . Although, Baron was classified in the safe category pesticides repeated exposure to small doses has great danger effect.

Keywords: glyphosate, liver toxicity, oxidative stress, DNA damage, commet assay

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Alexander Hudson, Shaogang Gong

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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

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Authors: Manop Aorpimai, Ponthep Navakitkanok

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In this paper, the development of the ephemeris generation module used for the Thaichote satellite operations is presented. It is a vital part of the flight dynamics system, which comprises, the orbit determination, orbit propagation, event prediction and station-keeping maneuver modules. In the generation of the spacecraft ephemeris data, the estimated orbital state vector from the orbit determination module is used as an initial condition. The equations of motion are then integrated forward in time to predict the satellite states. The higher geopotential harmonics, as well as other disturbing forces, are taken into account to resemble the environment in low-earth orbit. Using a highly accurate numerical integrator based on the Burlish-Stoer algorithm the ephemeris data can be generated for long-term predictions, by using a relatively small computation burden and short calculation time. Some events occurring during the prediction course that are related to the mission operations, such as the satellite’s rise/set viewed from the ground station, Earth and Moon eclipses, the drift in ground track as well as the drift in the local solar time of the orbital plane are all detected and reported. When combined with other modules to form a flight dynamics system, this application is aimed to be applied for the Thaichote satellite and successive Thailand’s Earth-observation missions.

Keywords: flight dynamics system, orbit propagation, satellite ephemeris, Thailand’s Earth Observation Satellite

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Authors: Maria Christofi, George Plastiras, Rafaella Elia, Vaggelis Tsiourtis, Theocharis Theocharides, Miltiadis Katsaros

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The rapidly expanding urban areas of the world constitute a challenge of how we need to make the transition to "the next urbanization", which will be defined by new analytical tools and new sources of data. This paper is about the production of a spatial application, the ‘FUMapp’, where space and its initiative will be available literally, in meters, but also abstractly, at a sensed level. While existing spatial applications typically focus on illustrations of the urban infrastructure, the suggested application goes beyond the existing: It investigates how our environment's perception adapts to the alterations of the built environment through a dataset construction of biophysical measurements (eye-tracking, heart beating), and physical metrics (spatial characteristics, size of stimuli, rhythm of mobility). It explores the intersections between architecture, cognition, and computing where future design can be improved and identifies the flexibility and livability of the ‘available space’ of specific examined urban paths.

Keywords: biophysical data, flexibility of urban, livability, next urbanization, spatial application

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Authors: Lei Guo, Xu Zhang, Weigang Hou

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Since the traditional network is closed and it has no architecture to create applications, it has been unable to evolve with changing demands under the rapid innovation in services. Additionally, due to the lack of the whole network profile, the quality of service cannot be well guaranteed in the traditional network. The Software Defined Network (SDN) utilizes global resources to support on-demand applications/services via open, standardized and programmable interfaces. In this paper, we implement the traffic grooming application under a real SDN environment, and the corresponding analysis is made. In our SDN: 1) we use OpenFlow protocol to control the entire network by using software applications running on the network operating system; 2) several virtual switches are combined into the data forwarding plane through Open vSwitch; 3) An OpenFlow controller, NOX, is involved as a logically centralized control plane that dynamically configures the data forwarding plane; 4) The traffic grooming based on SDN is demonstrated through dynamically modifying the idle time of flow entries. The experimental results demonstrate that the SDN-based traffic grooming effectively reduces the end-to-end delay, and the improvement ratio arrives to 99%.

Keywords: NOX, OpenFlow, Software Defined Network (SDN), traffic grooming

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Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Taehyun Kim, Hyunjoo Park, Taehyun Kim

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Public deliberation committee on Shin-Gori Nuclear Reactors No. 5 & 6 in South Korea recently suggested policy recommendation in July 2017 including complementary measures for resumption of construction: 1) nuclear power generation reduction, 2) expansion of investment to increase proportion of renewable energy, 3) repositories of spent nuclear fuel. Even when constructing eco-friendly renewable energy facilities such as solar and wind power plants, local residents are opposed to construction of these facilities due to environmental pollution and health impacts. In order to transform eco-friendly energy, it is necessary to convert nuclear energy into renewable energy and to take measures to increase the acceptance of residents through the participation of citizens. Therefore, this study aims to compare the factors of local acceptance of renewable energy facilities and spent nuclear fuel repositories through literature review and in-depth interview. The results show that environmental and economic concerns, risk perceptions, sociality, demographic characteristics and subjective recognition types affect the local acceptance for spent nuclear fuel repository. The factors of local acceptance for renewable energy facilities are partially coincide with those for spent nuclear fuel repository. The results of this study will contribute to improving residents' acceptance and reducing conflicts when determining the location of facilities in the future.

Keywords: local acceptance, renewable energy facility, spent nuclear fuel repository, interview

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Authors: Chaya B. M., C. Dhanush, Inti Sai Srikar, Akula Pavan Parvatalu, Chirag Gowda R

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Recently, there has been a lot of interest in µ-LED technology because of its exceptional qualities, including auto emission, high visibility, low consumption of power, rapid response and longevity. Light-emitting diodes (LED) using III-nitride, such as lighting sources, visible light communication (VLC) devices, and high-power devices, are finding increasing use as miniaturization technology advances. The use of micro-LED displays in place of traditional display technologies like liquid crystal displays (LCDs) and organic light-emitting diodes (OLEDs) is one of the most prominent recent advances, which may even represent the next generation of displays. The development of fully integrated, multifunctional devices and the incorporation of extra capabilities into micro-LED displays, such as sensing, light detection, and solar cells, are the pillars of advanced technology. Due to the wide range of applications for micro-LED technology, the effectiveness and dependability of these devices in numerous harsh conditions are becoming increasingly important. Enough research has been conducted to overcome the under-effectiveness of micro-LED devices. In this paper, different Micro LED design structures are proposed in order to achieve optimized optical properties. In order to attain improved external quantum efficiency (EQE), devices' light extraction efficiency (LEE) has also been boosted.

Keywords: finite difference time domain, light out coupling efficiency, far field intensity, power density, quantum efficiency, flat panel displays

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Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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Authors: Samina Yasmin, Anzar Khaliq, Zareen Tabassum

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Acute power shortage in Pakistan requires an urgent attention to take preliminary steps to spread energy awareness at all levels. One such initiative is taken at Habib University (HU), Pakistan, through renewable energy course, one of the core offerings, where students are trained to investigate various aspects of renewable energy concepts. The course is offered to all freshmen enrolled at HU regardless of their academic backgrounds and degree programs. A four-credit modular course includes both theory and laboratory elements. Hands-on laboratories play an important role in science classes, particularly to enhance the motivation and deep understanding of energy science. A set of selected hands-on activities included in course introduced students to explore the latest developments in the field of renewable energy such as dye-sensitized solar cells, gas chromatography, global warming, climate change, fuel cell energy and power of biomass etc. These projects not only helped HU freshmen to build on energy fundamentals but also provided them greater confidence in investigating, questioning and experimenting with renewable energy related conceptions. A feedback survey arranged during and end of term revealed the effectiveness of the hands-on laboratory to enhance the common understanding of real world problems related to energy such as awareness of energy saving, the level of concern about global climate change, environmental pollution and science of energy behind the energy usage.

Keywords: biochemical approaches, energy curriculum, hands-on laboratory, renewable energy

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Authors: Hyunho Shin, Jaekwang Jung, Jeongho Park, Sungwon Hwang

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For the application of graphene quantum dots (GQDs) to optoelectronic nanodevices, it is of critical importance to understand the mechanisms which result in novel phenomena of their light absorption/emission. The optical transitions are known to be available up to ~6 eV in GQDs, especially useful for ultraviolet (UV) photodetectors (PDs). Here, we present size-dependent shape/edge-state variations of GQDs and visible photoluminescence (PL) showing anomalous size dependencies. With varying the average size (da) of GQDs from 5 to 35 nm, the peak energy of the absorption spectra monotonically decreases, while that of the visible PL spectra unusually shows nonmonotonic behaviors having a minimum at diameter ∼17 nm. The PL behaviors can be attributed to the novel feature of GQDs, that is, the circular-to-polygonal-shape and corresponding edge-state variations of GQDs at diameter ∼17 nm as the GQD size increases, as demonstrated by high resolution transmission electron microscopy. We believe that such a comprehensive scheme in designing device architecture and the structural formulation of GQDs provides a device for practical realization of environmentally benign, high performance flexible devices in the future.

Keywords: graphene, quantum dot, size, photoluminescence

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Authors: Rajashekhar K. Patil, Martin J. Babu

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Weaver ants-Oecophylla smaragdina live in colonies that have polymorphic castes. The females which include the queen, major and minor workers are haploid. The individuals of castes are dependent on olfactory cues for carrying out caste-specific behaviour. In an effort to understand whether organizational differences exist to support these behavioural differences, we studied the olfactory system at the level of the sensilla on the antennae, olfactory glomeruli and the Kenyon cells in the mushroom bodies (MB). The MB differ in major and minor workers in terms of their size, with the major workers having relatively larger calyces and peduncle. The morphology of different types of Kenyon cells as revealed by Golgi-rapid staining was studied and the major workers had more dendritic arbors than minor workers. This suggests a greater degree of olfactory processing in major workers. Differences in caste-specific arrangement of sensilla, olfactory glomeruli and celluar architecture of MB indicate a developmental programme that forms basis of differential behaviour.

Keywords: ant, oecophylla, caste, mushroom body

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Authors: Amin Ebrahimi Ghadi, Morteza Moalagh

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This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.

Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability

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Authors: Moustafa M. S. Sanad

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The worsening of energy supply crisis and the exacerbation of climate change by environmental pollution problems have become the greatest threat to human life. One of the ways to confront these problems is to rely on renewable energy and its storage systems. Nowadays, huge attention has been directed to the development of lithium-ion batteries (LIBs) as efficient tools for storing the clean energy produced by green sources like solar and wind energies. Accordingly, the demand for powerful electrode materials with excellent electrochemical characteristics has been progressively increased to meet fast and continuous growth in the market of energy storage systems. Therefore, the electronic and electrical properties of conversion anode materials for rechargeable lithium-ion batteries (LIBs) can be enhanced by introducing lattice defects and oxygen vacancies in the crystal structure. In this regard, the intended presentation will demonstrate new insights and effective ways for enhancing the electrical conductivity and improving the electrochemical performance of different anode materials such as MgFe₂O₄, CdFe₂O₄, Fe₃O₄, LiNbO₃ and Nb₂O₅. The changes in the physicochemical and morphological properties have been deeply investigated via structural and spectroscopic analyses (e.g., XRD, FESEM, HRTEM, and XPS). Moreover, the enhancement in the electrochemical properties of these anode materials will be discussed through Galvanostatic Cycling (GC), Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS) techniques.

Keywords: structure modification, cationic substitution, non-stoichiometric synthesis, plasma treatment, lithium-ion batteries

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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Authors: Shiksha Jain, Ramesh Mishra

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One of the most widely used complex signals processing operation is filtering. The most important FIR digital filter are widely used in DSP for filtering to alter the spectrum according to some given specifications. Power consumption and Area complexity in the algorithm of Finite Impulse Response (FIR) filter is mainly caused by multipliers. So we present a multiplier less technique (DA technique). In this technique, precomputed value of inner product is stored in LUT. Which are further added and shifted with number of iterations equal to the precision of input sample. But the exponential growth of LUT with the order of FIR filter, in this basic structure, makes it prohibitive for many applications. The significant area and power reduction over traditional Distributed Arithmetic (DA) structure is presented in this paper, by the use of slicing of LUT to the desired length. An architecture of 16 tap FIR filter is presented, with different length of slice of LUT. The result of FIR Filter implementation on Xilinx ISE synthesis tool (XST) vertex-4 FPGA Tool by using proposed method shows the increase of the maximum frequency, the decrease of the resources as usage saving in area with more number of slices and the reduction dynamic power.

Keywords: multiplier less technique, linear phase symmetric FIR filter, FPGA tool, look up table

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Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

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Authors: Deliou Adel, Saadalah Younes, Belkaid Khmissi, Dehbi Meriem

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Composite materials, in the most common sense of the term, are a set of synthetic materials designed and used mainly for structural applications; the mechanical function is dominant. The mechanical behaviors of the composite, as well as the degradation mechanisms leading to its rupture, depend on the nature of the constituents and on the architecture of the fiber preform. The profile is required because it guides the engineer in designing structures with precise properties in relation to the needs. This work is about studying the mechanical behavior of unidirectional composite laminates according to different failure criteria. Varying strength parameter values make it possible to compare the ultimate mechanical characteristics obtained by the criteria of Tsai-Hill, Fisher and maximum stress. The laminate is subjected to uniaxial tensile membrane forces. Estimates of their ultimate strengths and the plotting of the failure envelope constitute the principal axis of this study. Using the theory of maximum stress, we can determine the various modes of damage of the composite. The different components of the deformation are presented for different orientations of fibers.

Keywords: unidirectional kevlar/epoxy composite, failure criterion, membrane stress, deformations, failure envelope

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Authors: Ziwei Chen, Yujiang Gao

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The rapid urbanization has caused the massive physical space in Chinese cities to be in a state of duplication and dislocation through the rapid development, forming many daily spaces that cannot be standardized, typed, and identified, such as illegal construction. This phenomenon is known as urban spatial redundancy and is often excluded from mainstream architectural discussions because of its 'remaining' and 'excessive' derogatory label. In recent years, some practice architects have begun to pay attention to this phenomenon and tried to tap the value behind it. In this context, the author takes the redundancy phenomenon of resident space as the research object and explores the inspiration to the urban architectural renewal and the innovative residential area model, based on the urban survey of redundant living space in Hongkou District of Shanghai. On this basis, it shows that the changes accumulated in the long-term use of the building can be re-applied to the goals before the design, which is an important link and significance of the existence of an architecture.

Keywords: rapid urbanization, living space redundancy, architectural renewal, residential area model

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Authors: Ashutosh Kumar, Irene M. C. Lo

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Ever since the discovery of TiO2 for decomposition of cyanide in water, it has been investigated extensively for the photocatalytic degradation of environmental pollutants, and became the most practical and prevalent photocatalyst. The superiority of TiO2 is due to its chemical and biological inertness, nontoxicity, strong oxidizing power and cost-effectiveness. However, during degradation of pollutants in wastewater, it suffers from problems, such as (a) separation after use, and (b) its poor photocatalytic performance under visible light irradiation (~45% of the solar spectrum). In order to bridge the research gaps, N-TiO2@SiO2@Fe3O4 nanophotocatalysts of average size 19 nm and effective surface area 47 m2 gm-1 were synthesized using sol-gel method. The characterization was performed using BET, TEM-EDX, VSM and XRD. The performance was improved by considering different factors involved during the synthesis, such as calcination temperature, amount of Fe3O4 nanoparticles used and amount of urea used for N-doping. The final nanophotocatalyst was calcined at 500 °C which was able to degrade 94% of the ibuprofen within 5 h of irradiation time. Under the influence of ~200 mT electromagnetic field, 95% nanophotocatalysts separation efficiency was achieved within 20-25 min. Moreover, the effect of different visible light source of similar irradiance, such as compact fluorescent lamp (CFL) and light emitting diode (LED), is also investigated in this research. The performance of nanophotocatalysts was found to be comparatively higher under ~310 µW cm-2 irradiance with peak emissive wavelengths of 543 nm emitted by CFL. Therefore, a promising visible-light-driven magnetically separable TiO2-based nanophotocatalysts was synthesized for the efficient degradation of ibuprofen.

Keywords: ibuprofen, magnetic N-TiO2, photocatalysis, visible light sources

Procedia PDF Downloads 249

Authors: Rimzhim Gupta, Bhanupriya Boruah, Jayant M. Modak, Giridhar Madras

Abstract:

Microbial contamination is one of the major concerns in the field of water treatment. AOP (advanced oxidation processes) is well-established method to resolve the issue of removal of contaminants in water. A Z-scheme composite g-C₃N₄/CuWO₄ was synthesized by sol-gel method for the photocatalytic inactivation of a mixed population of Gram-positive bacteria (S. aureus) and Gram-negative bacteria (E. coli). The photoinactivation was observed for different types of bacteria in the same medium together and individually in the absence of the nutrients. The lattice structures and phase purities were determined by X-ray diffraction. For morphological and topographical features, scanning electron microscopy and transmission electron microscopy analyses were carried out. The band edges of the semiconductor (valence band and conduction band) were determined by ultraviolet photoelectron microscopy. The lifetime of the charge carriers and band gap of the semiconductors were determined by time resolved florescence spectroscopy and diffused reflectance spectroscopy, respectively. The effect of weight ratio of C₃N₄ and CuWO₄ was observed by performing photocatalytic experiments. To investigate the exact mechanism and major responsible radicals for photocatalysis, scavenger studies were performed. The rate constants and order of the inactivation reactions were obtained by power law kinetics. For E. coli and S. aureus, the order of reaction and rate constants are 1.15, 0.9 and 1.39 ± 0.03 (CFU/mL)⁻⁰.¹⁵ h⁻¹, 47.95 ± 1.2 (CFU/mL)⁰.¹ h⁻¹, respectively.

Keywords: z-scheme, E. coli, S. aureus, sol-gel

Procedia PDF Downloads 149

Authors: Moon-Soo Kim

Abstract:

In order to cope with the increasing demand for multidisciplinary learning between academy and industry, a collaborative teaching and learning model and related operational tools enabling applications to engineering education are essential. This study proposes a web-based collaborative framework for interactive teaching and learning between academy and industry as an initial step for the development of a web- and mobile-based integrated system for both engineering students and industrial practitioners. The proposed web-based collaborative teaching and learning framework defines several entities such as learner, solver and supporter or sponsor for industrial problems, and also has a systematic architecture to build information system including diverse functions enabling effective interaction among the defined entities regardless of time and places. Furthermore, the framework, which includes knowledge and information self-reinforcing mechanism, focuses on the previous problem-solving records as well as subsequent learners’ creative reusing in solving process of new problems.

Keywords: collaborative teaching and learning model, academy and industry, web-based collaborative framework, self-reinforcing mechanism

Procedia PDF Downloads 326