Abstract: In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.
Abstract: 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.
Abstract: Butterfly valves are widely used industrial piping components as on-off and flow controlling devices. The main challenge in the design process of this type of valves is the correct dimensioning to ensure proper mechanical performance as well as to minimise flow losses that affect the efficiency of the system. Butterfly valves are typically dimensioned in a closed position based on mechanical approaches considering uniform hydrostatic pressure, whereas the flow losses are analysed by means of CFD simulations. The main limitation of these approaches is that they do not consider either the influence of the dynamics of the manoeuvring stage or coupled phenomena. Recent works have included the influence of the flow on the mechanical behaviour for different opening angles by means of one-way FSI approach. However, these works consider steady-state flow for the selected angles, not capturing the effect of the transient flow evolution during the manoeuvring stage. Two-way FSI modelling approach could allow overcoming such limitations providing more accurate results. Nevertheless, the use of this technique is limited due to the increase in the computational cost. In the present work, the applicability of FSI one-way and two-way approaches is evaluated for the analysis of butterfly valves, showing that not considering fluid-structure coupling involves not capturing the most critical situation for the valve disc.
Abstract: Minimizing the weight in flexible structures means
reducing material and costs as well. However, these structures could
become prone to vibrations. Attenuating these vibrations has become
a pivotal engineering problem that shifted the focus of many research
endeavors. One technique to do that is to design and implement
an active control system. This system is mainly composed of a
vibrating structure, a sensor to perceive the vibrations, an actuator
to counteract the influence of disturbances, and finally a controller to
generate the appropriate control signals. In this work, two different
techniques are explored to create two different mathematical models
of an active control system. The first model is a finite element model
with a reduced number of nodes and it is called a super-element.
The second model is in the form of state-space representation, i.e.
a set of partial differential equations. The damping coefficients are
calculated and incorporated into both models. The effectiveness of
these models is demonstrated when the system is excited by its first
natural frequency and an active control strategy is developed and
implemented to attenuate the resulting vibrations. Results from both
modeling techniques are presented and compared.
Abstract: An increasing degree of automation in air traffic will also change the role of the air traffic controller (ATCO). ATCOs will fulfill significantly more monitoring tasks compared to today. However, this rather passive role may lead to Out-Of-The-Loop (OOTL) effects comprising vigilance decrement and less situation awareness. The project MINIMA (Mitigating Negative Impacts of Monitoring high levels of Automation) has conceived a system to control and mitigate such OOTL phenomena. In order to demonstrate the MINIMA concept, an experimental simulation set-up has been designed. This set-up consists of two parts: 1) a Task Environment (TE) comprising a Terminal Maneuvering Area (TMA) simulator as well as 2) a Vigilance and Attention Controller (VAC) based on neurophysiological data recording such as electroencephalography (EEG) and eye-tracking devices. The current vigilance level and the attention focus of the controller are measured during the ATCO’s active work in front of the human machine interface (HMI). The derived vigilance level and attention trigger adaptive automation functionalities in the TE to avoid OOTL effects. This paper describes the full-scale experimental set-up and the component development work towards it. Hence, it encompasses a pre-test whose results influenced the development of the VAC as well as the functionalities of the final TE and the two VAC’s sub-components.
Abstract: E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.
Abstract: With recent trends in Big Data and advancements
in Information and Communication Technologies, the healthcare
industry is at the stage of its transition from clinician oriented to
technology oriented. Many people around the world die of cancer
because the diagnosis of disease was not done at an early stage.
Nowadays, the computational methods in the form of Machine
Learning (ML) are used to develop automated decision support
systems that can diagnose cancer with high confidence in a timely
manner. This paper aims to carry out the comparative evaluation
of a selected set of ML classifiers on two existing datasets: breast
cancer and cervical cancer. The ML classifiers compared in this study
are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest
Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and
Artificial Neural Networks (ANN). The evaluation is carried out based
on standard evaluation metrics Precision (P), Recall (R), F1-score and
Accuracy. The experimental results based on the evaluation metrics
show that ANN showed the highest-level accuracy (99.4%) when
tested with breast cancer dataset. On the other hand, when these
ML classifiers are tested with the cervical cancer dataset, Ensemble
(Bagged Tree) technique gave better accuracy (93.1%) in comparison
to other classifiers.
Abstract: The rapid progress of technology in today's competitive conditions has also accelerated companies' technology development activities. As a result, companies are paying more attention to R&D studies and are beginning to allocate a larger share to R&D projects. A more systematic, comprehensive, target-oriented implementation of R&D studies is crucial for the company to achieve successful results. As a consequence, Technology Roadmap (TRM) is gaining importance as a management tool. It has critical prospects for achieving medium and long term success as it contains decisions about past business, future plans, technological infrastructure. When studies on TRM are examined, projects to be placed on the roadmap are selected by many different methods. Generally preferred methods are based on multi-criteria decision making methods. Management of selected projects becomes an important point after the selection phase of the projects. At this stage, TRM are used. TRM can be created in many different ways so that each institution can prepare its own Technology Roadmap according to their strategic plan. Depending on the intended use, there can be TRM with different layers at different sizes. In the evaluation phase of the R&D projects and in the creation of the TRM, HAVELSAN, Turkey's largest defense company in the software field, carries out this process with great care and diligence. At the beginning, suggested R&D projects are evaluated by the Technology Management Board (TMB) of HAVELSAN in accordance with the company's resources, objectives, and targets. These projects are presented to the TMB periodically for evaluation within the framework of certain criteria by board members. After the necessary steps have been passed, the approved projects are added to the time-based TRM, which is composed of four layers as market, product, project and technology. The use of a four-layered roadmap provides a clearer understanding and visualization of company strategy and objectives. This study demonstrates the benefits of using TRM, four-layered Technology Roadmapping and the possibilities for the institutions in the defense industry.
Abstract: Traffic congestion is a worldwide issue, especially in developing countries. This is also the case of Afghanistan, especially in Kabul-the capital city, whose rapid population growth makes it the fifth fastest growing city in the world. Traffic congestion affects not only the mobility of people and goods but also the air quality that leads to numerous deaths (3000 people) every year. There are many factors that contribute to traffic congestion. The insufficiency and inefficiency of public transportation system along with the increase of private vehicles can be considered among the most important contributing factors. This paper addresses the traffic congestion and attempts to suggest possible solutions that can help improve the current public transportation system in Kabul. To this end, the methodology used in this paper includes field work conducted in Kabul city and literature review. The outcome suggests that improving the public transportation system is likely to contribute to the reduction of traffic congestion and the improvement of air quality, thereby reducing the number of death related to air quality.
Abstract: Bio-batteries represent an entirely new long-term, reasonable, reachable and ecofriendly approach to produce sustainable energy. In the present experimental work, we have studied the effect of generation of power by bio-battery using different electrode pairs. The tests show that it is possible to generate electricity using cow dung as an electrolyte. C-Mg electrode pair shows maximum voltage and SCC (Short Circuit Current) while C-Zn electrode pair shows less OCV (Open Circuit Voltage) and SCC. We have chosen C-Zn electrodes because Mg electrodes are not economical. By the studies of different electrodes and cow dung, it is found that C-Zn electrode battery is more suitable. This result shows that the bio-batteries have the potency to full fill the need of electricity demand for lower energy equipment.
Abstract: The objective of this research is to optimize the process of cutting cylindrical workpieces utilizing live tooling on a HAAS ST-20 lathe. Surface roughness (Ra) has been investigated as the indicator of quality characteristics for machining process. Aluminum alloy was used to conduct experiments due to its wide range usages in engineering structures and components where light weight or corrosion resistance is required. In this study, Taguchi methodology is utilized to determine the effects that each of the parameters has on surface roughness (Ra). A total of 18 experiments of each process were designed according to Taguchi’s L9 orthogonal array (OA) with four control factors at three levels of each and signal-to-noise ratios (S/N) were computed with Smaller the better equation for minimizing the system. The optimal parameters identified for the surface roughness of the turning operation utilizing live tooling were a feed rate of 3 inches/min(A3); a spindle speed of 1300 rpm(B3); a 2-flute titanium nitrite coated 3/8” endmill (C1); and a depth of cut of 0.025 inches (D2). The mean surface roughness of the confirmation runs in turning operation was 8.22 micro inches. The final results demonstrate that Taguchi methodology is a sufficient way of process improvement in turning process on surface roughness.
Abstract: Low-temperature waste heat is abundant in the process industries, and large amounts of Liquefied Natural Gas (LNG) cold energy are discarded without being recovered properly in LNG terminals. Power generation is an effective way to utilize low-temperature waste heat and LNG cold energy simultaneously. Organic Rankine Cycles (ORCs) and CO2 power cycles are promising technologies to convert low-temperature waste heat and LNG cold energy into electricity. If waste heat and LNG cold energy are utilized simultaneously in one system, the performance may outperform separate systems utilizing low-temperature waste heat and LNG cold energy, respectively. Low-temperature waste heat acts as the heat source and LNG regasification acts as the heat sink in the combined system. Due to the large temperature difference between the heat source and the heat sink, cascaded power cycle configurations are proposed in this paper. Cascaded power cycles can improve the energy efficiency of the system considerably. The cycle operating at a higher temperature to recover waste heat is called top cycle and the cycle operating at a lower temperature to utilize LNG cold energy is called bottom cycle in this study. The top cycle condensation heat is used as the heat source in the bottom cycle. The top cycle can be an ORC, transcritical CO2 (tCO2) cycle or supercritical CO2 (sCO2) cycle, while the bottom cycle only can be an ORC due to the low-temperature range of the bottom cycle. However, the thermodynamic path of the tCO2 cycle and sCO2 cycle are different from that of an ORC. The tCO2 cycle and the sCO2 cycle perform better than an ORC for sensible waste heat recovery due to a better temperature match with the waste heat source. Different combinations of the tCO2 cycle, sCO2 cycle and ORC are compared to screen the best configurations of the cascaded power cycles. The influence of the working fluid and the operating conditions are also investigated in this study. Each configuration is modeled and optimized in Aspen HYSYS. The results show that cascaded tCO2/ORC performs better compared with cascaded ORC/ORC and cascaded sCO2/ORC for the case study.
Abstract: Selective catalytic reduction systems for nitrogen oxides reduction by ammonia has been the chosen technology by most of diesel vehicle (i.e. bus and truck) manufacturers in Brazil, as also in Europe. Furthermore, at some conditions, over-stoichiometric ammonia availability is also needed that increases the NH3 slips even more. Ammonia (NH3) by this vehicle exhaust aftertreatment system provides a maximum efficiency of NOx removal if a significant amount of NH3 is stored on its catalyst surface. In the other words, the practice shows that slightly less than 100% of the NOx conversion is usually targeted, so that the aqueous urea solution hydrolyzes to NH3 via other species formation, under relatively low temperatures. This paper presents a model based on neural networks integrated with a road vehicle simulator that allows to estimate NH3-slip emission factors for different driving conditions and patterns. The proposed model generates high NH3slips which are not also limited in Brazil, but more efforts needed to be made to elucidate the contribution of vehicle-emitted NH3 to the urban atmosphere.
Abstract: This paper presents an intelligent tuning method of
microwave filter based on complex neural network and improved
space mapping. The tuning process consists of two stages: the initial
tuning and the fine tuning. At the beginning of the tuning, the return
loss of the filter is transferred to the passband via the error of phase.
During the fine tuning, the phase shift caused by the transmission line
and the higher order mode is removed by the curve fitting. Then, an
Cauchy method based on the admittance parameter (Y-parameter) is
used to extract the coupling matrix. The influence of the resonant
cavity loss is eliminated during the parameter extraction process. By
using processed data pairs (the amount of screw variation and the
variation of the coupling matrix), a tuning model is established by
the complex neural network. In view of the improved space mapping
algorithm, the mapping relationship between the actual model and
the ideal model is established, and the amplitude and direction of the
tuning is constantly updated. Finally, the tuning experiment of the
eight order coaxial cavity filter shows that the proposed method has
a good effect in tuning time and tuning precision.
Abstract: Architecture in Iran has a continuous history from at least 5000 BC to the present, and numerous Iranian pre-Islamic elements have contributed significantly to the formation of Islamic art. At first, decoration was limited to small objects and containers and then progressed in the art of plaster and brickwork. They later applied in architecture as well. The art of gypsum and brickwork, which was prevalent in the form of motifs (animals and plants) in pre-Islam, was used in the aftermath of Islam with the art of calligraphy in decorations. The splendor and beauty of Iranian architecture, especially during the Islamic era, are related to decoration and design. After the invasion of Iran by the Arabs and the introduction of Islam to Iran, the arrival of the Iranian classical architecture significantly changed, and we saw the Arabic calligraphy decoration of the mosques in Iran. The principles of aesthetics in the art of calligraphy in Iran are based precisely on the principles of the beauty of ancient Iranian and Islamic art. On the other hand, after Islam, calligraphy was one of the most important sources of Islamic art in Islam and one of the important features of Islamic culture. First, the calligraphy had no cultural meaning and was only for decoration and beautification, it had the same meaning only in the inscriptions; however, over time, it became meaningful. This article provides a summary of the history of calligraphy in the mosques (from the entrance to Islam until the Safavid period), which cannot ignore the role of the calligraphy in their decorative ideas; and also, the important role that decorative elements play in creating a public space in terms of social and aesthetic performance. This study was conducted using library studies and field studies. The purpose of this study is to show the characteristics of architecture and art of decorations in Iran, especially in the mosque's architecture, which reaches the pinnacle of progress. We will see that religious beliefs and artistic practices are merging and trying to bring a single concept.
Abstract: Andarokh basin is one of the main karstic regions in Khorasan Razavi province NE Iran. This basin is part of Kopeh-Dagh mega zone extending from Caspian Sea in the east to northern Afghanistan in the west. This basin is covered by Mozdooran Formation, Ngr evaporative formation and quaternary alluvium deposits in descending order of age. Mozdooran carbonate formation is notably karstified. The main surface karstic features in Mozdooran formation are Groove karren, Cleft karren, Rain pit, Rill karren, Tritt karren, Kamintza, Domes, and Table karren. In addition to surface features, deep karstic feature Andarokh Cave also exists in the region. Studying Ca, Mg, Mn, Sr, Fe concentration and Sr/Mn ratio in Mozdooran formation samples with distance to main faults and joints system using PCA analyses demonstrates intense meteoric digenesis role in controlling carbonate rock geochemistry. The karst evaluation in Andarokh basin varies from early stages 'deep seated karst' in Mesozoic to mature karstic system 'Exhumed karst' in quaternary period. Andarokh cave (the main cave in Andarokh basin) is rudimentary branch work consists of three passages of A, B and C and two entrances Andarokh and Sky.
Abstract: In this paper, the intelligent algorithm (IA) that is capable of adapting to dynamical tropical weather conditions is proposed based on fuzzy logic techniques. The IA effectively interacts with the quality of service (QoS) criteria irrespective of the dynamic tropical weather to achieve improvement in the satellite links. To achieve this, an adaptive network-based fuzzy inference system (ANFIS) has been adopted. The algorithm is capable of interacting with the weather fluctuation to generate appropriate improvement to the satellite QoS for efficient services to the customers. 5-year (2012-2016) rainfall rate of one-minute integration time series data has been used to derive fading based on ITU-R P. 618-12 propagation models. The data are obtained from the measurement undertaken by the Communication Research Group (CRG), Physics Department, Federal University of Technology, Akure, Nigeria. The rain attenuation and signal-to-noise ratio (SNR) were derived for frequency between Ku and V-band and propagation angle with respect to different transmitting power. The simulated results show a substantial reduction in SNR especially for application in the area of digital video broadcast-second generation coding modulation satellite networks.
Abstract: In this paper, we examine the connection between the human mind and body within the framework of Merleau-Ponty's phenomenology. We study the role of this connection in designing more efficient learning environments, alongside the findings in physical recognition and educational neuroscience. Our research shows the interplay between the mind and the body in the external world and discusses its implications. Based on these observations, we make suggestions as to how the educational system can benefit from taking into account the interaction between the mind and the body in educational affairs.
Abstract: Analysis of the elastic scattering of protons on 10B nuclei has been done in the framework of the optical model and single folding model at the beam energies up to 17 MeV. We could enhance the optical potential parameters using Esis88 Code, as well as SPI GENOA Code. Linear relationship between volume real potential (V0) and proton energy (Ep) has been obtained. Also, surface imaginary potential WD is proportional to the proton energy (Ep) in the range 0.400 and 17 MeV. The radiative reaction 10B(p,γ)11C has been analyzed using potential model. A comparison between 10B(p,γ)11C and 6Li(p,γ)7Be has been made. Good agreement has been found between theoretical and experimental results in the whole range of energy. The radiative resonance reaction 7Li(p,γ)8Be has been studied.
Abstract: Coatings based on polyaniline (PANI) can improve the resistance of steel against corrosion. In this work, the preparation of stable suspensions of colloidal PANI-SiO2 particles, suitable for obtaining of composite anticorrosive coating on steel, is described. Electrokinetic data as a function of pH are presented, showing that the zeta potentials of the PANI-SiO2 particles are governed primarily by the charged groups at the silica oxide surface. Electrosteric stabilization of the PANI-SiO2 particles’ suspension against aggregation is realized at pH>5.5 (EB form of PANI) by adsorption of positively charged polyelectrolyte molecules onto negatively charged PANI-SiO2 particles. The PANI-SiO2 particles are incorporated by electrodeposition into the metal matrix of zinc in order to obtain composite (hybrid) coatings. The latter are aimed to ensure sacrificial protection of steel mainly in aggressive media leading to local corrosion damages. The surface morphology of the composite zinc coatings is investigated with SEM. The influence of PANI-SiO2 particles on the cathodic and anodic processes occurring in the starting electrolyte for obtaining of the coatings is followed with cyclic voltammetry. The electrochemical and corrosion behavior is evaluated with potentiodynamic polarization curves and polarization resistance measurements. The beneficial effect of the stabilized PANI-SiO2 particles for the increased protective ability of the composites is commented and discussed.