Search results for: network structure

Authors: Min Zhou, Kaixuan Lin, Yaping Huang

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In this paper, the industrial space of metropolitan area in Wuhan is taken as a sample. First of all, it puts forward that the structure of service economy, circle gradient relocation and high degree of regional collaboration are the rules of industrial spatial development in the modern world cities. Secondly, using the economic statistics and land use vector data (1993, 2004, 2010, and 2013) of Wuhan, it analyzes the present situation of industry development and the characteristics of industrial space layout from three aspects of the industrial economic structure, industrial layout, and industrial regional synergy. Then, based on the industrial development regularity of world cities, it puts forward to construct the industrial spatial level of ‘complex industrial concentration area + modular industry unit’ and the industrial spatial structure of ‘13525’. Finally, it comes up with the optimization tactics of the industrial space’s transformation in the future under the background of new economic era.

Keywords: big city of metropolitan area, industrial space, characteristics, layout, strategy

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Authors: Lucia Antonela Mitidieri

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This research analyzes the application of a model of settlements management based on networks of territorial integration that advocates planning as a cyclical and participatory process that engages early on with civic society, the private sector and the state. Through qualitative methods such as participant observation, interviews with snowball technique and an active research on territories, concrete results of community empowerment are obtained from the promotion of productive enterprises and community spaces of encounter and exchange. Studying the cultural and organizational dimensions of empowerment allows building indicators such as increase of capacities or community cohesion that can lead to support local governments in achieving sustainable urban development for a reduction of urban poverty.

Keywords: community spaces, empowerment, network urbanism, participatory process

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Authors: Somayyeh Kalami, Mojgan Nejad

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Based on the source (softwood, hardwood or annual crop) and isolation method (kraft, organosolv, sulfite or pre-enzymatic treatment), there are significant variations in lignin structure and properties. The first step in using lignin as biobased feedstock is to make sure that specific lignin is suitable for intended application. Complete characterization of lignin and measuring its chemical, physical and thermal properties can help to predict its suitability. To replace 100% phenol portion of phenolic adhesive, lignin should have high reactivity toward formaldehyde. Theoretically, lignins with closer backbone structure to phenol should be better candidate for this application. In this study, a number of different lignins were characterized and used to formulate phenolic adhesive. One of the main findings was that lignin sample with higher percentage of hydroxyl-phenyl units was better candidate than lignin with more syringyl units. This could be explained by the fact that hydroxyl-phenyl lignin units have two available ortho positions for reaction with formaldehyde while in syringyl units all ortho and para positions are occupied, and there is no available site in lignin structure to react with formaldehyde.

Keywords: lignin, phenolic adhesive, biobased, sustainable

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Authors: C. Iihoshi, G. A. MacRae, G. W. Rodgers, J. G. Chase

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Slab Sliding System (SSS) with Coulomb friction interface between slab and supporting frame is a passive structural vibration control technology. The system can significantly reduce the slab acceleration and accompanied lateral force of the frame. At the same time it is expected to cause the slab displacement magnification by sliding movement. To obtain the general comprehensive seismic response of a single story structure, inelastic response spectra were computed for a large ensemble of ground motions and a practical range of structural periods and friction coefficient values. It was shown that long period structures have no trade-off relation between force reduction and displacement magnification with respect to elastic response, unlike short period structures. For structures with the majority of mass in the slab, the displacement magnification value can be predicted according to simple inelastic displacement relation for in elastically responding SDOF structures because the system behaves elastically to a SDOF structure.

Keywords: earthquake, isolation, slab, sliding

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Authors: Dimitra Alexiou, Stefanos Katsavounis, Ria Kalfakakou

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In an urban area the determination of transportation routes should be planned so as to minimize the provoked pollution taking into account the cost of such routes. In the sequel these routes are cited as pollution routes. The transportation network is expressed by a weighted graph G= (V, E, D, P) where every vertex represents a location to be served and E contains unordered pairs (edges) of elements in V that indicate a simple road. The distances/cost and a weight that depict the provoked air pollution by a vehicle transition at every road are assigned to each road as well. These are the items of set D and P respectively. Furthermore the investigated pollution routes must not exceed predefined corresponding values concerning the route cost and the route pollution level during the vehicle transition. In this paper we present an algorithm that generates such routes in order that the decision maker selects the most appropriate one.

Keywords: bi-criteria, pollution, shortest paths, computation

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Authors: Sana Rezig, Yosr Ben Mlik, Mounir Jaouadi, Foued Khoffi, Slah Msahli, Bernard Durand

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Increasing interest in environmental concerns, natural fibers are once again being considered as reinforcements for polymer composites. The main objective of this study is to explore another natural resource, Typha fiber; which is renewable without production cost and available abundantly in nature. The aim of this study was to study the flexural properties of composite resin with and without reinforcing Typha leaf and stem fibers. The specimens were made by the hand-lay-up process using polyester matrix. In our work, we focused on the effect of various treatment conditions (sea water, alkali treatment and a combination of the two treatments), as a surface modifier, on the flexural properties of the Typha fibers reinforced polyester composites. Moreover, weight ratio of Typha leaf or stem fibers was investigated. Besides, both fibers from leaf and stem of Typha plant were used to evaluate the reinforcing effect. Another parameter, which is reinforcement structure, was investigated. In fact, a first composite was made with air-laid nonwoven structure of fibers. A second composite was with a mixture of fibers and resin for each kind of treatment. Results show that alkali treatment and combined process provided better mechanical properties of composites in comparison with fiber treated by sea water. The fiber weight ratio influenced the flexural properties of composites. Indeed, a maximum value of flexural strength of 69.8 and 62,32 MPa with flexural modulus of 6.16 and 6.34 GPawas observed respectively for composite reinforced with leaf and stem fibers for 12.6 % fiber weight ratio. For the different treatments carried out, the treatment using caustic soda, whether alone or after retting seawater, show the best results because it improves adhesion between the polyester matrix and the fibers of reinforcement. SEM photographs were made to ascertain the effects of the surface treatment of the fibers. By varying the structure of the fibers of Typha, the reinforcement used in bulk shows more effective results as that used in the non-woven structure. In addition, flexural strength rises with about (65.32 %) in the case of composite reinforced with a mixture of 12.6% leaf fibers and (27.45 %) in the case of a composite reinforced with a nonwoven structure of 12.6 % of leaf fibers. Thus, to better evaluate the effect of the fiber origin, the reinforcing structure, the processing performed and the reinforcement factor on the performance of composite materials, a statistical study was performed using Minitab. Thus, ANOVA was used, and the patterns of the main effects of these parameters and interaction between them were established. Statistical analysis, the fiber treatment and reinforcement structure seem to be the most significant parameters.

Keywords: flexural properties, fiber treatment, structure and weight ratio, SEM photographs, Typha leaf and stem fibers

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Authors: Kamel Taıbı, Abdelmadjid Rais

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Nickel–Aluminium ferrites with the general formula Ni Alx Fe2-x O4 (0 ≤ x ≤ 1) were studied using X-ray diffraction, Infra Red and Raman spectroscopy. XRD diffraction patterns and their Reitveld refinements show that all samples have a pure single-phase cubic spinel structure. From these patterns, the lattice parameters of these samples have been calculated and compared with those predicted theoretically. Most of the values were found to decrease with increasing Al content. Infra Red spectra showed two significant absorption bands. The high band corresponds to tetrahedral (A) sites and the lower band to octahedral [B] sites, thus confirming the single phase spinel structure. For all compositions, Raman spectra show the five active modes A1g + E1g + 3 T2g of the motion of O2- ions and both the A-site and B-site ions. The Raman frequencies trend with aluminium concentration show a blue shift for all modes consistent with the replacement of Fe3+ by lower mass Al3+. Composition dependence of the Raman frequency modes is discussed in relationship with the cations distribution among the A-sites and B-sites.

Keywords: Ni-Al ferrites, spinel structure, XRD, Raman spectroscopy

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Authors: Tianle Yang

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As a common mental disorder, depression is a leading cause of various diseases worldwide. Early detection and treatment of depression can dramatically promote remission and prevent relapse. However, conventional ways of depression diagnosis require considerable human effort and cause economic burden, while still being prone to misdiagnosis. On the other hand, recent studies report that physical characteristics are major contributors to the diagnosis of depression, which inspires us to mine the internal relationship by neural networks instead of relying on clinical experiences. In this paper, neural networks are constructed to predict depression from physical characteristics. Two initialization methods are examined - Xaiver and Kaiming initialization. Experimental results show that a 3-layers neural network with Kaiming initialization achieves 83% accuracy.

Keywords: depression, neural network, Xavier initialization, Kaiming initialization

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Authors: Ju-Hong Lee, Chong-Jia Ciou, Yuan-Hau Yang

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This paper deals with the problem of two-dimensional (2-D) recursive doubly complementary (DC) digital filter design. We present a structure of 2-D recursive DC filters by using 2-D symmetric half-plane (SHP) recursive digital all-pass lattice filters (DALFs). The novelty of using 2-D SHP recursive DALFs to construct a 2-D recursive DC digital lattice filter is that the resulting 2-D SHP recursive DC digital lattice filter provides better performance than the existing 2-D SHP recursive DC digital filter. Moreover, the proposed structure possesses a favorable 2-D DC half-band (DC-HB) property that allows about half of the 2-D SHP recursive DALF’s coefficients to be zero. This leads to considerable savings in computational burden for implementation. To ensure the stability of a designed 2-D SHP recursive DC digital lattice filter, some necessary constraints on the phase of the 2-D SHP recursive DALF during the design process are presented. Design of a 2-D diamond-shape decimation/interpolation filter is presented for illustration and comparison.

Keywords: all-pass digital filter, doubly complementary, lattice structure, symmetric half-plane digital filter, sampling rate conversion

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Authors: Zhi Liu, Hui Jiang, Jin Li, Kunhao Chen, Langfang Zhang

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Fast acquisition of the seismic information and accurate assessment of the earthquake disaster is the key problem for emergency rescue after a destructive earthquake. In order to meet the requirements of the earthquake emergency response and rescue for the cities and counties, a quasi real-time comprehensive evaluation system for earthquake disaster is developed. Based on monitoring data of Micro-Electro-Mechanical Systems (MEMS) strong motion network, structure database of a county area and the real-time disaster information by the mobile terminal after an earthquake, fragility analysis method and dynamic correction algorithm are synthetically obtained in the developed system. Real-time evaluation of the seismic disaster in the county region is finally realized to provide scientific basis for seismic emergency command, rescue and assistant decision.

Keywords: quasi real-time, earthquake disaster data collection, MEMS accelerometer, dynamic correction, comprehensive evaluation

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Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira

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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

Keywords: artificial neural networks, digital image processing, pattern recognition, phytosanitary

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Authors: Yongfang Deng, Dunwen Zuo

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An attempt is made here to join 2024 aluminum alloy plate by friction stir joining (FSJ) using different types of tools. Joint surface morphology was observed, and both arc line spacing and flash were measured. Study is carried out on the effect of pin, shoulder and eccentricity of the tool on the surface topography of the joint and the formation of the joint surface topography is analyzed. It is found that, eccentric squeezing action of the tool is the mainly motive power to form arc lines contour and flash structure. Little flash appears in the advancing side but with severe deformation, while the flash in the retreating side is heavy but with soft deformation. The pin of tool has a deep impact on the flash on the advancing side of the joints. Shoulder can widen the arc lines, refine arcs structure, reduce flash in the retreat side, but will increase the flash in the advancing side. Increasing the amount of eccentricity, it has litter effect on the arc line spacing but will destroy the arc lines morphology in the joint surface and promote the formation of filamentous flash structure in the joint.

Keywords: FSJ, surface morphology, tool, joint

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Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method Web-App auto-generated twin data structure replication. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi" has been developed. A special login form has been developed with a special instance of data validation; this verification process secures the web application from its early stages. The system has been tested and validated, up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database

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Authors: Afif Saleh Abugharsa

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The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

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Authors: Humeyra Bolakar Tosun

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The transport sector has an undisputed place in human life. People need transport access to continuous increase day by day with growing population. The number of rail network, urban transport planning, infrastructure improvements, transportation management and other related areas is a key factor affecting our country made it quite necessary to improve the work of transportation. In this context, it plays an important role in domestic rail freight demand planning. Alternatives that the increase in the transportation field and has made it mandatory requirements such as the demand for improving transport quality. In this study generally is known and used in studies by the definition, rail freight transport, railway line length, population, energy consumption. In this study, Iron Road Load Net Demand was modeled by multiple regression and ANN methods. In this study, model dependent variable (Output) is Iron Road Load Net demand and 6 entries variable was determined. These outcome values extracted from the model using ANN and regression model results. In the regression model, some parameters are considered as determinative parameters, and the coefficients of the determinants give meaningful results. As a result, ANN model has been shown to be more successful than traditional regression model.

Keywords: railway load carrying, neural network, modelling transport, transportation

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Authors: John M. Lyne, K. Andrea Scott

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In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

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Authors: WonHo Lee, Hyo-Gyoung Kwak

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A numerical model considering slip behavior of steel-concrete composite structure is introduced. This model is based on a linear bond stress-slip relation along the interface. Single node was considered at the interface of steel and concrete member in finite element analysis, and it improves analytical problems of model that takes double nodes at the interface by adopting spring elements to simulate the partial interaction. The slip behavior is simulated by modifying material properties of steel element contacting concrete according to the derived formulation. Decreased elastic modulus simulates the slip occurrence at the interface and decreased yield strength simulates drop in load capacity of the structure. The model is verified by comparing numerical analysis applying this model with experimental studies. Acknowledgment—This research was supported by a grant(13SCIPA01) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport(MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement(KAIA) and financially supported by Korea Ministry of Land, Infrastructure and Transport(MOLIT) as U-City Master and Doctor Course Grant Program.

Keywords: bond-slip, composite structure, partial interaction, steel-concrete structure

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Gwanghee Heo, Geonhyeok Bang, Chunggil Kim, Chinok Lee

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This paper attempts to develop a wireless feedback control system as a primary step eventually toward a bio-inspired structure system where inanimate structure behaves like a life form autonomously. It is a standalone wireless control system which is supposed to measure externally caused structural responses, analyze structural state from acquired data, and take its own action on the basis of the analysis with an embedded logic. For an experimental examination of its effectiveness, we applied it on a model of two-span bridge and performed a wireless control test. Experimental tests have been conducted for comparison on both the wireless and the wired system under the conditions of Un-control, Passive-off, Passive-on, and Lyapunov control algorithm. By proving the congruence of the test result of the wireless feedback control system with the wired control system, its control performance was proven to be effective. Besides, it was found to be economical in energy consumption and also autonomous by means of a command algorithm embedded into it, which proves its basic capacity as a bio-inspired system.

Keywords: structural vibration control, wireless system, MR damper, feedback control, embedded system

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Authors: Ramin Mirzada, Takuya Maruyama

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Kabul is the heart of political, commercial, cultural, educational and social life in Afghanistan and the fifth fastest growing city in the world. Minimum income inclined most of Kabul residents to use public transport, especially buses, although there is no proper bus system, beside that there is no proper fare exist in Kabul city Due to wars. From 1992 to 2001 during civil wars, Kabul suffered damage and destruction of its transportation facilities including pavements, sidewalks, traffic circles, drainage systems, traffic signs and signals, trolleybuses and almost all of the public transport system (e.g. Millie bus). This research is mainly focused on Kabul city’s transportation system. In this research, the data used have been gathered by Japan International Cooperation Agency (JICA) in 2008 and this data will be used to find demand and fare structure, additionally a survey was done in 2016 to find satisfaction level of Kabul residents for fare structure. Aim of this research is to observe the demand for Large Buses, compare to the actual supply from the government, analyze the current fare structure and compare it with the proposed fare (distance based fare) structure which has already been analyzed. Outcome of this research shows that the demand of Kabul city residents for the public transport (Large Buses) exceeds from the current supply, so that current public transportation (Large Buses) is not sufficient to serve public transport in Kabul city, worth to be mentioned, that in order to overcome this problem, there is no need to build new roads or exclusive way for buses. This research proposes government to change the fare from fixed fare to distance based fare, invest on public transportation and increase the number of large buses so that the current demand for public transport is met.

Keywords: transportation, planning, public transport, large buses, Kabul, Afghanistan

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Authors: F.Bendahma, S.Bentata

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In this paper, we study numerically the eigenstates existing in a GaAs/AlxGa1-xAs superlattice with structural disorder in trimer height barrier (THB). Aluminium concentration x takes at random two different values, one of them appears only in triply and remains inferior to the second in the studied structure. In spite of the presence of disorder, the system exhibits two kinds of sets of propagating states lying below the barrier due to the characteristic structure of the superlattice. This result allows us to note the existence of a single laser emission in trimer and wavelengths are obtained in the mid-infrared.

Keywords: infrared (IR), laser emission, superlattice, trimer

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Authors: Moh Hanif Mubarok, Muhammad Rivai

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The public's response to quality rice is very high. So it is necessary to set minimum standards in checking the quality of rice. Most rice quality measurements still use manual methods, which are prone to errors due to limited human vision and the subjectivity of testers. So, a gas detection system can be a solution that has high effectiveness and subjectivity for solving current problems. The use of gas sensors in testing rice quality must pay attention to several parameters. The parameters measured in this research are the percentage of rice water content, gas concentration, output voltage, and measurement time. Therefore, this research was carried out to identify carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄) gases in rice quality using a series of gas sensors using the Neural Network method.

Keywords: carbon dioxide, dinitrogen oxide, methane, semiconductor gas sensor, neural network

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Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Site response has a profound effect on earthquake damages. Seismic interaction of urban tunnels with surface structures could also affect seismic site response. Here, we use FLAC 2D to investigate the interaction of a single tunnel and twin tunnels-surface structures on the site response. Soil stratification and properties are selected based on Line. No 7 of the Tehran subway. The effect of surface structure is considered in two ways: Equivalent surcharge and geometrical modeling of the structure. Comparison of the results shows that consideration of the structure geometry is vital in dynamic analysis and leads to the changes in the magnitude of displacements, accelerations and response spectrum. Therefore it is necessary for the surface structures to be wholly modeled and not just considered as a surcharge in dynamic analysis. The use of twin tunnel also leads to the reduction of dynamic residual settlement.

Keywords: superstructure, tunnel, site response, surcharge, interaction

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Suzan Abd El Majid, Menachem Bamberger, Alexander Katsman

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Two Al-4 wt. % Cu based alloys, A201 and A201+Si were investigated in the as-cast, solution treated and aged conditions. The addition of Si was used to improve the castability of the basic alloy. The all investigated alloys in the as-cast condition contained a eutectic structure along grain boundaries (GBs) with the composition Al-50at. %Cu that was found by HRSEM EDS. Addition of Si refined the grain structure and changed the amount of the eutectic regions, their size and shape. Additionally, the A201+Si microstructure contained Si rods and small amount of Al6Mn4Cu3Fe2Si-phase. Solution treatment (ST) at 550°C for ~ 20 hours resulted in a slight dissolution of the eutectic structure in the A201 alloy while substantial dissolution and change of the eutectic composition was detected in the A201+Si alloy. After ST, the A201alloy contained θ-Al2Cu, Al5Cu2Mn3 and Al9Cu7Mn3(Fe) phases associated to the GBs, while the ST A201+Si alloy contained θ-Al2Cu, Al6Mn4Cu3(Fe,Si) and Si94Mn3Al2Cu phases. Precipitation hardening during aging at 170°C was investigated for both alloys. The microhardness of the ST A201alloy increased during aging and reached the maximum value ~ 140 HV after 2 h of aging. Initial microhardness of the ST A201+Si alloy was distinctly higher than one of the ST A201 alloy, but it decreased during the first hour of aging, then increased and reached the same maximum value ~ 140 HV after ~ 4 h of aging. It was concluded that the Si addition influenced the precipitation sequence and slowed down the age hardening process. The Si induced grain refining and evolution of the eutectic structure during the heat treatments applied are discussed.

Keywords: A201 alloys, castability, microstructure, micro-hardness

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Authors: Hugo Espinosa-Andrews

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Introduction: Yogurt is widely accepted worldwide due to its high nutritional value, consistency, and texture. Their rheological properties play a significant role in consumer acceptance and are related to the manufacturing process and formulation. Typically, the viscoelastic characteristics of yogurts are studied using the small amplitude oscillatory shear test; however, the initial stages of flow and oral processing are described in the nonlinear zone, in which a large amplitude oscillatory stress test is applied. The objective of this work was to analyze the nonlinear viscoelastic behavior of commercial yogurts using Lissajous curves. Methods: Two commercial yogurts were purchased in a local store in Guadalajara Jalisco Mexico: a natural Greek-style yogurt and a low-fat traditional yogurt. Viscoelastic properties were evaluated using a large amplitude oscillatory stress procedure (LAOS). A crosshatch geometry of 40 mm and a truncation of 1000 µm were used. Stress sweeps were performed at 6.28 rad/s from 1 to 250 Pa at 5°C. The nonlinear viscoelastic properties were analyzed using the Lissajous curves. Results: The yogurts showed strain-viscoelastic behavior related to deformation-dependent materials. In the low-strain region, the elastic modulus predominated over the viscous modulus, showing gel-elastic properties. The sol-gel transitions were observed at approximately 66.5 Pa for the Greek yogurt, double that detected for traditional yogurt. The viscoelastic behavior of the yogurts was characteristic of weak excess deformation: behavior indicating a stable molecular structure at rest, and moderate structure at medium shear-forces. The normalized Lissajous curves characterized viscoelastic transitions of the yogurt as the stress increased. Greater viscoelasticity deformation was observed in Greek yogurt than in traditional yogurt, which is related to the presence of a protein network with a greater degree of crosslinking. Conclusions: The yogurt composition influences the viscoelastic properties of the material. Yogurt with the higher percentage of protein has greater viscoelastic and viscous properties, which describe a product of greater consistency and creaminess.

Keywords: yogurt, viscoelastic properties, LAOS, elastic modulus

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Authors: Adriana Souza M. Batista, Cláubia Pereira, Luiz O. Faria

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The irradiation of polymeric materials has received much attention because it can produce diverse changes in chemical structure and physical properties. Thus, studying the chemical and structural changes of polymers is important in practice to achieve optimal conditions for the modification of polymers. The effect of gamma irradiation on the crystalline structure of poly(vinylidene fluoride) (PVDF) has been investigated using differential scanning calorimetry (DSC) and X-ray diffraction techniques (XRD). Gamma irradiation was carried out in atmosphere air with doses between 100 kGy at 3,000 kGy with a Co-60 source. In the melting thermogram of the samples irradiated can be seen a bimodal melting endotherm is detected with two melting temperature. The lower melting temperature is attributed to melting of crystals originally present and the higher melting peak due to melting of crystals reorganized upon heat treatment. These results are consistent with those obtained by XRD technique showing increasing crystallinity with increasing irradiation dose, although the melting latent heat is decreasing.

Keywords: differential scanning calorimetry, gamma irradiation, PVDF, X-ray diffraction technique

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

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Authors: Noxolo Mafu

Abstract:

This study presents an overview of strategic planning in South African higher education institutions by tracing its trends and mystique in order to identify its impact. Over the democratic decades, strategic planning has become integral to institutional survival. It has been used as a potent tool by several institutions to catch up and surpass counterparts. While planning has always been part of higher education, strategic planning should be considered different. Strategic planning is primarily about development and maintenance of a strategic fitting between an institution and its dynamic opportunities. This presupposes existence of sets of stages that institutions pursue of which, can be regarded for assessment of the impact of strategic planning in an institution. The network theory serves guides the study in demystifying apparent organisational networks in strategic planning processes.

Keywords: network theory, strategy, planning, strategic planning, assessment, impact

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Authors: Mazarine Roquet, Pierre Dewallef

Abstract:

The building sector, both residential and tertiary, accounts for a significant share of greenhouse gas emissions. In Belgium, partly due to poor insulation of the building stock, but certainly because of the massive use of fossil fuels for heating buildings, this share reaches almost 30%. To reduce carbon emissions from urban building heating, district heating networks emerge as a promising solution as they offer various assets such as improving the load factor, integrating combined heat and power systems, and enabling energy source diversification, including renewable sources and waste heat recovery. However, mainly for sake of simple operation, most existing district heating networks still operate at high or medium temperatures ranging between 120°C and 60°C (the socalled second and third-generations district heating networks). Although these district heating networks offer energy savings in comparison with individual boilers, such temperature levels generally require the use of fossil fuels (mainly natural gas) with combined heat and power. The fourth-generation district heating networks improve the transport and energy conversion efficiency by decreasing the operating temperature between 50°C and 30°C. Yet, to decarbonise the building heating one must increase the waste heat recovery and use mainly wind, solar or geothermal sources for the remaining heat supply. Fifth-generation networks operating between 35°C and 15°C offer the possibility to decrease even more the transport losses, to increase the share of waste heat recovery and to use electricity from renewable resources through the use of heat pumps to generate low temperature heat. The main objective of this contribution is to exhibit on a real-life test case the benefits of replacing an existing third-generation network by a fifth-generation one and to decarbonise the heat supply of the building stock. The second objective of the study is to highlight the difficulties resulting from the use of a fifth-generation, low-temperature, district heating network. To do so, a simulation model of the district heating network including its regulation is implemented in the modelling language Modelica. This model is applied to the test case of the heating network on the University of Liège's Sart Tilman campus, consisting of around sixty buildings. This model is validated with monitoring data and then adapted for low-temperature networks. A comparison of primary energy consumptions as well as CO2 emissions is done between the two cases to underline the benefits in term of energy independency and GHG emissions. To highlight the complexity of operating a lowtemperature network, the difficulty of adapting the mass flow rate to the heat demand is considered. This shows the difficult balance between the thermal comfort and the electrical consumption of the circulation pumps. Several control strategies are considered and compared to the global energy savings. The developed model can be used to assess the potential for energy and CO2 emissions savings retrofitting an existing network or when designing a new one.

Keywords: building simulation, fifth-generation district heating network, low-temperature district heating network, urban building heating

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