Search results for: decision matrix

Authors: G. Beulah Gnana Ananthi, A. Jaffer Sathick, M. Abirami

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Fibre reinforced concrete (FRC) has been widely used in industrial pavements and non-structural elements such as pipes, culverts, tunnels, and precast elements. The strengthening effect of fibres in the concrete matrix is achieved primarily due to the bridging effect of fibres at the crack interfaces. The workability of the concrete was reduced on addition of high percentages of steel fibres. The optimum percentage of addition of steel fibres varies with its aspect ratio. For this study, 1% addition of steel has resulted to be the optimum percentage for both Hooked and Crimped Steel Fibres and was added to the beam specimens. The fibres restrain efficiently the cracks and take up residual stresses beyond the cracking. In this sense, diagonal cracks are effectively stitched up by fibres crossing it. The failure of beams within the shear failure range changed from shear to flexure in the presence of sufficient steel fibre quantity. The shear strength is increased with the addition of steel fibres and had exceeded the enhancement obtained with the transverse reinforcement. However, such increase is not directly in proportion with the quantity of fibres used. Considering all the clarification made in the present experimental investigation, it is concluded that 1% of crimped steel fibres with an aspect ratio of 50 is the best type of steel fibres for replacement of transverse stirrups in high strength concrete beams when compared to the steel fibres with hooked ends.

Keywords: fibre reinforced concrete, steel fibre, shear strength, crack pattern

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Authors: Susana F. Casla

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Talent Gaming is an innovative methodology based on a large research done for years about how table board games can be used to empower teams. This methodology was developed thinking about the efficiency of facilitating team coaching sessions and the importance of bringing out the best of individuals when working as a team. The fact that more senses are involved in playing a board game, linked with the psychological element of space and “permission to play”, help us travel to earlier stages of our life when our authenticity was at its heights. By being focused on playing the board game, the individual does not direct their consciousness in a particular way and is rather focused in winning the board game. By doing this, his or her inner talents and authenticity surfaces and the fact that all the senses are involved impacts enormously his behaviors and attitudes. All of this combined results in an arena where our talents show up and our decision making process is not impacted by other elements, such as appearances, status or hierarchy.

Keywords: talent, team, board game, business psychology, coaching teams at work

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Authors: Mayuri Roy Choudhury, Deepti Paul

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Many states in the United States are aiming for high renewable energy targets by the year 2045. In order to achieve this goal, they must do transition to Electrical Vehicles (EVS). We first applied the Multi-Level perspective framework to describe the inter-disciplinary complexities associated with the transition to EVs. Thereafter we addressed these complexities by creating an inter-disciplinary policy framework that uses data science algorithms to create evidence-based policies in favor of EVs. Our policy framework uses a systems level approach as it addresses transitions to EVs from a technology, economic, business and social perspective. By Systems-Level we mean approaching a problem from a multi-disciplinary perspective. Our systems-level approach could be a beneficial decision-making tool to a diverse number of stakeholders such as engineers, entrepreneurs, researchers, and policymakers. In addition, it will add value to the literature of electrical vehicles, sustainable energy, energy economics, and management as well as efficient policymaking.

Keywords: transition, electrical vehicles, systems-level, algorithms

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Authors: Panyawutthi Rimdusit, Krittapas Charoensuk, Sarawut Rimdusit

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A biobased toughening filler for polylactic acid (PLA) based on natural rubber is developed in this work. Deproteinized natural rubber (DPNR) was modified by grafting polymerization with methyl methacrylate monomer (MMA) and further crosslinked by e-beam irradiation and spray drying process to achieve ultrafine full vulcanized powdered natural rubber grafted with polymethylmethacrylate (UFPNRg-PMMA) to solves in the challenges of incompatibility between natural rubber and PLA. Intriguingly, UFPNR-g-PMMA revealed outstanding and unique properties with minimal particle aggregation. The average particle size of rubber powder obtained from UFPNR-g-PMMA at PMMA grafting content of 20 phr reduced to 3.3±1.2 µm, compared to that of neat UFPNR of 5.3±2.3 µm which also showed partial particle aggregation. It is also found that the impact strength of the filled PLA was enhanced to 33.4±5.6 kJ/m2 at PLA/UFPNR-gPMMA 20 wt% compared to neat PLA of 9.6±3 kJ/m2. The thermal degradation temperature of the PLA composites was enhanced with increasing UFPNR-g-PMMA content without affecting the glass transition temperature of the composites. The fracture surface of PLA/ UFPNR-g-PMMA suggested internal cavitation and crazes are the main effects of rubber toughening PLA with substantial interfacial interaction between the filler and the matrix.

Keywords: natural rubber, ultrafine fully vulcanized powder rubber, polylactic acid, polymer composites

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Authors: Benhui Fan, Fahmi Bedoui, Jinbo Bai

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Incorporated carbon nanotube-BaTiO₃ hybrids (H-CNT-BT) with core-shell structure, a better dispersion of CNTs can be achieved in a semi-crystalline polymeric matrix, polyvinylidene fluoride (PVDF). Carried by BT particles, CNTs are easy to mutually connect which helps to obtain an extremely low percolation threshold (fc). After thermal treatments, the dielectric constants (ε’) of samples further increase which depends on the conditions of thermal treatments such as annealing temperatures, annealing durations and cooling ways. Thus, in order to study more comprehensively about the influence of thermal treatments on composite’s dielectric behaviors, in situ synchrotron X-ray is used to detect re-crystalline behavior of PVDF. Results of wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) show that after the thermal treatment, the content of β polymorph (the polymorph with the highest ε’ among all the polymorphs of PVDF’s crystalline structure) has increased nearly double times at the interfacial region of CNT-PVDF, and the thickness of amorphous layers (La) in PVDF’s long periods (Lp) has shrunk around 10 Å. The evolution of CNT’s network possibly occurs in the procedure of La shrinkage, where the strong interfacial polarization may be aroused and increases ε’ at low frequency. Moreover, an increase in the thickness of crystalline lamella may also arouse more orientational polarization and improve ε’ at high frequency.

Keywords: dielectric properties, thermal treatments, carbon nanotubes, crystalline structure

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Authors: Sheng Huang, Xin Zhao, Xiaofeng Gao, Tao Zhou, Shijin Dai, Youcai Zhao

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Adsorption of heavy metal pollutants (Zn, Cd, Pb, Cr, Cu) and organic pesticide (phorate, dithiophosphate diethyl, triethyl phosphorothioate), along with their multi-contamination on the surface of industrial construction & demolition waste (C&D waste) was investigated. Brick powder was selected as the appropriate waste while its maximum equilibrium adsorption amount of heavy metal under single controlled contamination matrix reached 5.41, 0.81, 0.45, 1.13 and 0.97 mg/g, respectively. Effects of pH and spiking dose of ICDW was also investigated. Equilibrium adsorption amount of organic pesticide varied from 0.02 to 0.97 mg/g, which was negatively correlated to the size distribution and hydrophilism. Existence of organic pesticide on surface of ICDW caused various effects on the heavy metal adsorption, mainly due to combination of metal ions and the floccule formation along with wrapping behaviors by pesticide pollutants. Adsorption of Zn was sharply decreased from 7.1 to 0.15 mg/g compared with clean ICDW and phorate contaminated ICDW, while that of Pb, Cr and Cd experienced an increase- then decrease procedure. On the other hand, runoff of pesticide contaminants was investigated under 25 mm/h simulated rainfall. Results showed that the cumulative runoff amount fitted well with curve obtained from a power function, of which r2=0.95 and 0.91 for 1DAA (1 day between contamination and runoff) and 7DAA, respectively. This study helps provide evaluation of industrial construction and demolition waste contamination into aquatic systems.

Keywords: adsorption mechanism, industrial construction waste, metals, pesticide, runoff

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Authors: Irfan Ali, Srikant Gupta, Aquil Ahmed

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Every country needs a sustainable development (SD) for its economic growth by forming suitable policies and initiative programs for the development of different sectors of the country. This paper is comprised of modeling and optimization of different sectors of India that form a multi-criterion model. In this paper, we developed a fractional goal programming (FGP) model that helps in providing the efficient allocation of resources simultaneously by achieving the sustainable goals in gross domestic product (GDP), electricity consumption (EC) and greenhouse gasses (GHG) emission by the year 2030. Also, a weighted model of FGP is presented to obtain varying solution according to the priorities set by the policy maker for achieving future goals of GDP growth, EC, and GHG emission. The presented models provide a useful insight to the decision makers for implementing strategies in a different sector.

Keywords: sustainable and economic development, multi-objective fractional programming, fuzzy goal programming, weighted fuzzy goal programming

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Authors: Anna Fredriksson Häägg, Charlotte Weil, Niklas Rönnberg

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Map-based dashboards are used for data exploration every day. The present study used an insight-based methodology for evaluating a map-based dashboard that presents research findings of water management and ecosystem services in the Amazon. In addition to analyzing the insights gained from using the dashboard, the evaluation method was compared to standardized questionnaires and task-based evaluations. The result suggests that the dashboard enabled the participants to gain domain-relevant, complex insights regarding the topic presented. Furthermore, the insight-based analysis highlighted unexpected insights and hypotheses regarding causes and potential adaptation strategies for remediation. Although time- and resource-consuming, the insight-based methodology was shown to have the potential of thoroughly analyzing how end users can utilize map-based dashboards for data exploration and decision making. Finally, the insight-based methodology is argued to evaluate tools in scenarios more similar to real-life usage compared to task-based evaluation methods.

Keywords: visual analytics, dashboard, insight-based evaluation, geographic visualization

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Authors: Christian Böning, Henrik Prinzhorn, Eric C. Hund, Malte Stonis

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In this article, the flexible job-shop scheduling problem is extended by consideration of energy costs which arise owing to the power peak, and further decision variables such as work in process and throughput time are incorporated into the objective function. This enables a production plan to be simultaneously optimized in respect of the real arising energy and logistics costs. The energy-costs-aware flexible job-shop scheduling problem (EFJSP) which arises is described mathematically, and a memetic algorithm (MA) is presented as a solution. In the MA, the evolutionary process is supplemented with a local search. Furthermore, repair procedures are used in order to rectify any infeasible solutions that have arisen in the evolutionary process. The potential for lowering the real arising costs of a production plan through consideration of energy consumption levels is highlighted.

Keywords: energy costs, flexible job-shop scheduling, memetic algorithm, power peak

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Authors: Soha A. Bahanshal, Byung G. Kim

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Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps

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Authors: Cesar Hernández, Diego Giral, Fernando Santa

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The spectral handoff is important in cognitive wireless networks to ensure an adequate quality of service and performance for secondary user communications. This work proposes a benchmarking of performance of the three spectrum handoff models: VIKOR, SAW and MEW. Four evaluation metrics are used. These metrics are, accumulative average of failed handoffs, accumulative average of handoffs performed, accumulative average of transmission bandwidth and, accumulative average of the transmission delay. As a difference with related work, the performance of the three spectrum handoff models was validated with captured data of spectral occupancy in experiments realized at the GSM frequency band (824 MHz-849 MHz). These data represent the actual behavior of the licensed users for this wireless frequency band. The results of the comparative show that VIKOR Algorithm provides 15.8% performance improvement compared to a SAW Algorithm and, 12.1% better than the MEW Algorithm.

Keywords: cognitive radio, decision making, MEW, SAW, spectrum handoff, VIKOR

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Authors: Noureddine Ramdani

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In recent years, extensive attention has been given to the study of conductive nanocomposites due to their unique properties, which are dependent on their size and shape. The potential applications of these materials include electromagnetic interference shielding, energy storage, photovoltaics, and others. These outstanding properties have led to increased interest and research in this field. In this work, a conductive poly benzoxazine nanocomposite, PBZ/Gr-Cu, was synthesized through a compression molding technique to achieve a high-performance material suitable for electromagnetic interference (EMI) shielding applications. The microstructure of the nanocomposites was analyzed using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The thermal stability, electrical conductivity, and EMI shielding properties of the nanocomposites were evaluated using thermogravimetric analysis, a four-point probe, and a VNA analyzer, respectively. The TGA results revealed that the thermal stability and electrical conductivity of the nanocomposites were significantly enhanced by the incorporation of Gr/Cu nanoparticles. The nanocomposites exhibited a low percolation threshold of about 3.5 wt.% and an increase in carrier concentration and mobility of the carriers with increasing hybrid nanofiller content, causing the composites to behave as n-type semiconductors. These nanocomposites also displayed a high dielectric constant and a high dissipation factor in the frequency range of 8-12 GHz, resulting in higher EMI shielding effectiveness (SE) of 25-44 dB. These characteristics make them promising candidates for lightweight EMI shielding materials in aerospace and radar evasion applications.

Keywords: polybenzoxazine matrix, conductive nanocomposites, electrical conductivity, EMI shielding

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Authors: Robson da C. Santos, Carlos Henrique de A. S. P. Coutinho, Lucas Moreira Dias, Gerson Gomes Cunha

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The article refers to the development of an augmented reality 3D display, through the control of servo motors and projection of image with aid of video projector on the model. Augmented Reality is a branch that explores multiple approaches to increase real-world view by viewing additional information along with the real scene. The article presents the broad use of electrical, electronic, mechanical and industrial automation for geospatial visualizations, applications in mathematical models with the visualization of functions and 3D surface graphics and volumetric rendering that are currently seen in 2D layers. Application as a 3D display for representation and visualization of Digital Terrain Model (DTM) and Digital Surface Models (DSM), where it can be applied in the identification of canyons in the marine area of the Campos Basin, Rio de Janeiro, Brazil. The same can execute visualization of regions subject to landslides, as in Serra do Mar - Agra dos Reis and Serranas cities both in the State of Rio de Janeiro. From the foregoing, loss of human life and leakage of oil from pipelines buried in these regions may be anticipated in advance. The physical design consists of a table consisting of a 9 x 16 matrix of servo motors, totalizing 144 servos, a mesh is used on the servo motors for visualization of the models projected by a retro projector. Each model for by an image pre-processing, is sent to a server to be converted and viewed from a software developed in C # Programming Language.

Keywords: visualization, 3D models, servo motors, C# programming language

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Dilip Depan, Austin Simoneaux, William Chirdon, Ahmed Khattab

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In this study, we present a novel approach to synthesize polymer nanocomposites with nanohybrid shish-kebab architecture (NHSK). For this low-density and high density polyethylene (PE) was crystallized on various carbon nano-fillers using a novel and convenient method to prepare high-yield NHSK. Polymer crystals grew epitaxially on carbon nano-fillers using a solution crystallization method. The mixture of polymer and carbon fillers in xylene was flocculated and precipitated in ethanol to improve the product yield. Carbon nanofillers of varying diameter were also used as a nucleating template for polymer crystallization. The morphology of the prepared nanocomposites was characterized scanning electron microscopy (SEM), while differential scanning calorimetry (DSC) was used to quantify the amount of crystalline polymer. Interestingly, whatever the diameter of the carbon nanofiller is, the lamellae of PE is always perpendicular to the long axis of nanofiller. Surface area analysis was performed using BET. Our results indicated that carbon nanofillers of varying diameter can be used to effectively nucleate the crystallization of polymer. The effect of molecular weight and concentration of the polymer was discussed on the basis of chain mobility and crystallization capability of the polymer matrix. Our work shows a facile, rapid, yet high-yield production method to form polymer nanocomposites to reveal application potential of NHSK architecture.

Keywords: carbon nanotubes, polyethylene, nanohybrid shish-kebab, crystallization, morphology

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Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian

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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: ensembles, false positives, feature selection, one side class algorithm

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Authors: Ewelina Nowak, Anna Wisla-Swider, Gohar Khachatryan, Krzysztof Danel

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Complexes of ionic liquids with different heterocyclic-rings were synthesized by ion exchange reactions with pure salmon DNA. Ionic liquids (ILs) like 1-hexyl-3-methylimidazolium chloride, 1-butyl-4-methylpyridinium chloride and 1-ethyl-1-methylpyrrolidinium bromide were used. The ILs were built into helical state and confirmed by IR spectrometric techniques. Patterns of UV-Vis, photoluminescence, IR, and CD spectra indicated inclusion of small molecules into DNA structure. Molecular weight and radii of gyrations values of ILs-DNA complexes chains were established by HPSEC–MALLS–RI method. Modification DNA with 1-ethyl-1-methylpyrrolidinium bromide gives more uniform material and leads to elimination of high molecular weight chains. Thus, the incorporation DNA double helical structure with both 1-hexyl-3-methylimidazolium chloride and 1-butyl-4-methylpyridinium chloride exhibited higher molecular weight values. Scanning electron microscopy images indicate formation of nanofibre structures in all DNA complexes. Fluorescence depends strongly on the environment in which the chromophores are inserted and simultaneously on the molecular interactions with the biopolymer matrix. The most intensive emission was observed for DNA-imidazole ring complex. Decrease in intensity UV-Vis peak absorption is a consequence of a reduction in the spatial order of polynucleotide strands and provides different π–π stacking structure. Changes in optical properties confirmed by spectroscopy methods make DNA-ILs complexes potential biosensor applications.

Keywords: biopolymers, biosensors, cationic surfactant, DNA, DNA-gels

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Authors: Rajaian Hoonejani Mohammad, Eshraghi Pegah, Zomorodian Zahra Sadat, Tahsildoost Mohammad

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Ku Aina Afiqah Ku Adzman, Manmeet Mahinderjit Singh, Zarul Fitri Zaaba

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NFC operates on low-range 13.56 MHz frequency within a distance from 4cm to 10cm, and the applications can be categorized as touch and go, touch and confirm, touch and connect, and touch and explore. NFC applications are vulnerable to various security and privacy attacks such due to its physical nature; unprotected data stored in NFC tag and insecure communication between its applications. This paper aims to determine the likelihood of security risks happening in an NFC technology and application. We present an NFC technology taxonomy covering NFC standards, types of application and various security and privacy attack. Based on observations and the survey presented to evaluate the risk assessment within the touch and go application demonstrates two security attacks that are high risks namely data corruption and DOS attacks. After the risks are determined, risk countermeasures by using AHP is adopted. The guideline and solutions to these two high risks, attacks are later applied to a secure NFC-enabled Smartphone Attendance System.

Keywords: Near Field Communication (NFC), risk assessment, multi-criteria decision making, Analytical Hierarchy Process (AHP)

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Authors: Elke Meex, Elke Knapen, Griet Verbeeck

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The focus of sustainable building is gradually shifting from energy efficiency towards the more global environmental impact of building design during all life-cycle stages. In this context, many tools have been developed that use a LCA-approach to assess the environmental impact on a whole building level. Since the building design strongly influences the final environmental performance and the architect plays a key role in the design process, it is important that these tools are adapted to his work method and support the decision making from the early design phase on. Therefore, a comparative evaluation of the degree of architect-friendliness of some LCA tools on building level is made, based on an evaluation framework specifically developed for the architect’s viewpoint. In order to allow comparison of the results, a reference building has been designed, documented for different design phases and entered in all software tools. The evaluation according to the framework shows that the existing tools are not very architect-friendly. Suggestions for improvement are formulated.

Keywords: architect-friendliness, design supportive value, evaluation framework, tool comparison

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Authors: Mohamed H. El-Newehy, Badr M. Thamer, Nasser A. M. Barakat, Mohammad A.Abdelkareem, Salem S. Al-Deyab, Hak Y. Kim

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In this study, the influence of nitrogen doping on the electrocatalytic activity of carbon nanofibers with nickel nanoparticles toward methanol oxidation is introduced. The modified carbon nanofibers have been synthesized from calcination of electrospun nanofiber mats composed of nickel acetate tetrahydrate, poly(vinyl alcohol) and urea in argon atmosphere at 750oC. The utilized physicochemical characterizations indicated that the proposed strategy leads to form carbon nanofibers having nickel nanoparticles and doped by nitrogen. Moreover, due to the high-applied voltage during the electrospinning process, the utilized urea chemically bonds with the polymer matrix, which leads to form nitrogen-doped CNFs after the calcination process. Investigation of the electrocatalytic activity indicated that nitrogen doping NiCNFs strongly enhances the oxidation process of methanol as the current density increases from 52.5 to 198.5 mA/cm2 when the urea content in the original electrospun solution was 4 wt% urea. Moreover, the nanofibrous morphology exhibits distinct impact on the electrocatalytic activity. Also, nitrogen-doping enhanced the stability of the introduced Ni-based electrocatalyst. Overall, the present study introduces effective and simple strategy to modify the electrocatalytic activity of the nickel-based materials.

Keywords: electrospinning, methanol electrooxidation, fuel cells, nitrogen-doping, nickel

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Authors: Aleksandra Twarda, Dobrosława Krzemień, Grzegorz Dubin, Tad A. Holak

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Stabilin-2 belongs to the group of scavenger receptors and plays a crucial role in clearance of more than 10 ligands from the bloodstream, including hyaluronic acid, products of degradation of extracellular matrix and metabolic products. The Link domain, a defining feature of stabilin-2, has a sequence similar to Link domains in other hyaluronic acid receptors, such as CD44 or TSG-6, and is responsible for most of ligands binding. Present knowledge of signal transduction by stabilin-2, as well as ligands’ recognition and binding mechanism, is limited. Until now, no experimental structures have been solved for any segments of stabilin-2. It has recently been demonstrated that the stabilin-2 knock-out or blocking of the receptor by an antibody effectively opposes cancer metastasis by elevating the level of circulating hyaluronic acid. Moreover, loss of expression of stabilin-2 in a peri-tumourous liver correlates with increased survival. Solving of the crystal structure of stabilin-2 and elucidation of the binding mechanism of hyaluronic acid could enable the precise characterization of the interactions in the binding site. These results may allow for designing specific small-molecule inhibitors of stabilin-2 that could be used in cancer therapy. To carry out screening for crystallization of stabilin-2, we cloned constructs of the Link domain of various lengths with or without surrounding domains. The folding properties of the constructs were checked by nuclear magnetic resonance (NMR). It is planned to show the binding of hyaluronic acid to the Link domain using several biochemical methods, i.a. NMR, isothermal titration calorimetry and fluorescence polarization assay.

Keywords: stabilin-2, Link domain, X-ray crystallography, NMR, hyaluronic acid, cancer

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Authors: Yousef S. Kh. S. Hashem

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Accurate estimation of initial gas in place (IGIP) plays an important factor in the decision to develop a gas field. One of the methods that are available in the industry to estimate the IGIP is material balance. This method required that the well has to be shut-in while pressure is measured as it builds to average reservoir pressure. Since gas demand is high and shut-in well surveys are very expensive, flowing gas material balance (FGMB) is sometimes used instead of material balance. This work investigated the effect of reservoir properties (pressure, permeability, and reservoir size) on the estimation of IGIP when using FGMB. A gas reservoir simulator that accounts for friction loss, wellbore storage, and the non-Darcy effect was used to simulate 165 different possible causes (3 pressures, 5 reservoir sizes, and 11 permeabilities). Both tubing pressure and bottom-hole pressure were analyzed using FGMB. The results showed that the FGMB method is very sensitive for tied reservoirs (k < 10). Also, it showed which method is best to be used for different reservoir properties. This study can be used as a guideline for the application of the FGMB method.

Keywords: flowing material balance, gas reservoir, reserves, gas simulator

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Authors: Ashish Kumar, Kaptan Singh, Amit Saxena

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Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.

Keywords: K-nearest neighbor, random forest, decision tree, pre-processing

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Authors: Farzaneh Bayat

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Successful and effective presence in regional and global markets along with optimal use of available utilities and proper utilization of new sources for offering desirable services based on customer satisfaction is inevitable. Commitment has a significant role in offering optimal services. Offering high quality job and desirable services to the customers are personnel’s commitment. Thus, Shiraz Chamran Hospital which is affiliated with Shiraz Medical School and is one of the orthopedic poles in southern Iran was studied. This hospital has 750 personnel and physicians which a sample of 200 of them were chosen as the statistic society for a 5 month period from June to November 2009. Main variables in this decision are: responsibility and responsiveness, job security, team work, task autonomy, gradation opportunity, information sharing, payments and commitment. The study approach is descriptive-correlative. With applied and segmental nature of the tests and statistic analysis, the 7 hypotheses were approved with 95% of certainty.

Keywords: commitment, information sharing, responsibility and responsiveness, job security, task autonomy

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Authors: Mohammed Mashrei

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Ferrocement is a type of thin reinforced concrete made of cement-sand matrix with closely spaced relatively small diameter wire meshes, with or without steel bars of small diameter called skeletal steel. This work concerns on the behavior of square ferrocement slabs of dimensions (500) mm x (500) mm and 30 mm subjected to a central load. This study includes testing thirteen ferrocement slabs. The main variables considered in the experimental work are the number of wire mesh layers, percentage of silica fume and the presence of steel fiber. The effects of these variables on the behavior and load carrying capacity of tested slabs under central load were investigated. From the experimental results, it is found that by increasing the percentage of silica fume from (0 to 1.5, 3, 4.5 and 6) of weight of cement the ultimate loads are affected. Also From this study, it is observed that the load carrying capacity increases with the presence of steel fiber reinforcement, the ductility is high in the case of steel fibers. The increasing wire mesh layer from six to ten layers increased the load capacity by 76%. Also, a reduction in width of crack with increasing in number of cracks in the samples that content on steel fibers comparing with samples without steel fibers was observed from the results.

Keywords: ferrocement, fibre, silica fume, slab, strength

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Authors: Liqiang Gong, Hanguang Fu

Abstract:

In order to further improve the wear resistance of Hypereutectic High Chromium Cast iron (HHCCI), the effects of different Cu contents on the microstructure and properties of HHCCI were systematically studied. It was found that with the increase of Cu content, the carbide size was refined, and the increase of Cu content led to the increase of austenite and the decrease of hardness in as-cast HHCCI. After heat treatment at 1050 °C, the hardness of HHCCI increased significantly compared with as-cast. And with the increase of Cu content, the hardness of HHCCI increased first and then decreased, and the hardness was the highest when 0.5 wt.% Cu was added. The increase of copper content promotes the precipitation of secondary carbides and makes the interface between α-Fe and M23C6-type secondary carbides a semi-coherent boundary. With the increase of Cu content, the wear loss of HHCCI decreased after heat treatment at 1050 °C, and the wear resistance improved. When the Cu content increased to 1.0 wt.%, the wear resistance of HHCCI was the best, which was 2.6 times that of copper-free HHCCI. The continued increase of copper content has no obvious effect on the wear resistance of HHCCI. In addition, a small amount of Cu tends to adsorb on the (0001) preferential growth surface of M₇C₃-type carbides, thereby refining the carbides. From the First-principles calculations, the solid solution strengthening effect of Cu on the matrix and the adsorption and refinement of carbides were revealed, and the influence mechanism on the wear resistance of HHCCI was characterized.

Keywords: hypereutectic high chromium cast iron, cu alloying, carbides, wear resistance, first-principles calculations

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Authors: Summer Hassan, David Crossman

Abstract:

Myocardial fibrosis (MF) has been loosely defined as the process occurring in the pathological remodeling of the myocardium due to excessive production and deposition of extracellular matrix (ECM) proteins, including collagen. This reduces tissue compliance and accelerates progression to heart failure, as well as affecting the electrical properties of the myocytes resulting in arrhythmias. Microscopic interrogation of MF is key to understanding the molecular orchestrators of disease. It is well-established that recruitment and stimulation of myofibroblasts result in Collagen deposition and the resulting expansion in the ECM. Many types of Collagens have been identified and implicated in scarring of tissue. In a series of experiments conducted at our lab, we aim to elucidate the role collagen VI plays in the development of myocardial fibrosis and its direct impact on myocardial function. This was investigated through an animal experiment in Rats with Collagen VI knockout diseased and healthy animals as well as Collagen VI wild diseased and healthy rats. Echocardiogram assessments of these rats ensued at four-time points, followed by microscopic interrogation of the myocardium aiming to correlate the role collagen VI plays in myocardial function. Our results demonstrate a deterioration in cardiac function as represented by the ejection fraction in the knockout healthy and diseased rats. This elucidates a potential protective role that collagen-VI plays following a myocardial insult. Current work is dedicated to the microscopic characterisation of the fibrotic process in all rat groups, with the results to follow.

Keywords: heart failure, myocardial fibrosis, collagen, echocardiogram, confocal microscopy

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