Search results for: Real time collision avoidance.

Authors: Henok Hailemariam, Frank Wuttke

Abstract:

Collapsible soils are weak soils that appear to be stable in their natural state, normally dry condition, but rapidly deform under saturation (wetting), thus generating large and unexpected settlements which often yield disastrous consequences for structures unwittingly built on such deposits. In this study, a prediction model for the relative subsidence of stressed collapsible soils based on dielectric permittivity measurement is presented. Unlike most existing methods for soil subsidence prediction, this model does not require moisture content as an input parameter, thus providing the opportunity to obtain accurate estimation of the relative subsidence of collapsible soils using dielectric measurement only. The prediction model is developed based on an existing relative subsidence prediction model (which is dependent on soil moisture condition) and an advanced theoretical frequency and temperature-dependent electromagnetic mixing equation (which effectively removes the moisture content dependence of the original relative subsidence prediction model). For large scale sub-surface soil exploration purposes, the spatial sub-surface soil dielectric data over wide areas and high depths of weak (collapsible) soil deposits can be obtained using non-destructive high frequency electromagnetic (HF-EM) measurement techniques such as ground penetrating radar (GPR). For laboratory or small scale in-situ measurements, techniques such as an open-ended coaxial line with widely applicable time domain reflectometry (TDR) or vector network analysers (VNAs) are usually employed to obtain the soil dielectric data. By using soil dielectric data obtained from small or large scale non-destructive HF-EM investigations, the new model can effectively predict the relative subsidence of weak soils without the need to extract samples for moisture content measurement. Some of the resulting benefits are the preservation of the undisturbed nature of the soil as well as a reduction in the investigation costs and analysis time in the identification of weak (problematic) soils. The accuracy of prediction of the presented model is assessed by conducting relative subsidence tests on a collapsible soil at various initial soil conditions and a good match between the model prediction and experimental results is obtained.

Keywords: Collapsible soil, relative subsidence, dielectric permittivity, moisture content.

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Authors: S. Pesina, T. Solonchak

Abstract:

In the process of information transmission (concept verbalization) we deal mostly with the substance (contents), and then pay attention to the form. Recalling events from the remote past, often we cannot exactly reproduce specific heard or pronounced words, as well as the syntactic structures. We remember events, feelings, images; we recall the general contents of the discourse. The thought gets a specific language form only during the concept verbalization phase. With minimum time for pondering, depending on the language competence level, the grammar and syntactic shaping often occurs automatically with the use of famous models and stereotypes. This means that the language form adapts itself to the consciousness, and not vice versa.

Keywords: Lexical eidos, phenomenology, noema, polysemantic word, semantic core.

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Authors: Shankar Kambhampaty, Venkata Srinivas Modali

Abstract:

When architecting an application, key nonfunctional requirements such as performance, scalability, availability and security, which influence the architecture of the system, are some times not adequately addressed. Performance of the application may not be looked at until there is a concern. There are several problems with this reactive approach. If the system does not meet its performance objectives, the application is unlikely to be accepted by the stakeholders. This paper suggests an approach for performance modeling for web based J2EE and .Net applications to address performance issues early in the development life cycle. It also includes a Performance Modeling Case Study, with Proof-of-Concept (PoC) and implementation details for .NET and J2EE platforms.

Keywords: Performance Measures, Performance Modeling, Performance Testing, Resource Utilization, Response Time, Throughput.

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Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri

Abstract:

In this study, ¹⁷⁷Lu-DOTATOC was prepared under optimized conditions (radiochemical purity: > 99%, radionuclidic purity: > 99%). The percentage of injected dose per gram (%ID/g) was calculated for organs up to 168 h post injection. Compartmental model was applied to mathematical description of the drug behaviour in tissue at different times. The biodistribution data showed the significant excretion of the radioactivity from the kidneys. The adrenal and pancreas, as major expression sites for somatostatin receptor (SSTR), had significant uptake. A pharmacokinetic model of ¹⁷⁷Lu-DOTATOC was presented by compartmental analysis which demonstrates the behavior of the complex.

Keywords: Biodistribution, compartmental modeling, 177Lu, octreotide.

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Authors: Mohammad Ali Baradaran Ghahfarokhi, Parvin Baradaran Ghahfarokhi

Abstract:

In this paper, first we introduce the stable distribution, stable process and theirs characteristics. The a -stable distribution family has received great interest in the last decade due to its success in modeling data, which are too impulsive to be accommodated by the Gaussian distribution. In the second part, we propose major applications of alpha stable distribution in telecommunication, computer science such as network delays and signal processing and financial markets. At the end, we focus on using stable distribution to estimate measure of risk in stock markets and show simulated data with statistical softwares.

Keywords: stable distribution, SaS, infinite variance, heavy tail networks, VaR.

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Authors: S. B. Kotsiantis, D. Kanellopoulos, P. E. Pintelas

Abstract:

Many factors affect the success of Machine Learning (ML) on a given task. The representation and quality of the instance data is first and foremost. If there is much irrelevant and redundant information present or noisy and unreliable data, then knowledge discovery during the training phase is more difficult. It is well known that data preparation and filtering steps take considerable amount of processing time in ML problems. Data pre-processing includes data cleaning, normalization, transformation, feature extraction and selection, etc. The product of data pre-processing is the final training set. It would be nice if a single sequence of data pre-processing algorithms had the best performance for each data set but this is not happened. Thus, we present the most well know algorithms for each step of data pre-processing so that one achieves the best performance for their data set.

Keywords: Data mining, feature selection, data cleaning.

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Authors: Mara Magda Maftei

Abstract:

The article emphasizes the ideological commitment of the philosopher Emil Cioran. It presents firstly Cioran's works on the theme announced by the title, then the European context that determined the political option of Cioran and a brief analysis of his relationship with History during his French period. The anti- Semitism of Cioran was favored by his attachment to a few philosophers, but also by the European extremist and anti-Semitic context. The article seeks to demonstrate that the philosopher Cioran, known more for his pessimism and nihilism, maintained in time an obsessive relationship with History. His political philosophy is as important as his subjective philosophy, better known than the former.

Keywords: Cioran, French writings, History, Iron Guard

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

Abstract:

This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of the CSC modeling research accommodates conceptual or process models which present general management frameworks and do not relate to acknowledged soft Operations Research methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, objectives, modeling approach, solution methods and software used. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop optimization models for integrated CSCM. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without translating the generic concepts to the context of construction industry.

Keywords: Construction supply chain management, modeling, operations research, optimization and simulation.

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Authors: M.J. Park, K.H. Kim, O.M. Kwon

Abstract:

This paper proposes a delay-dependent leader-following consensus condition of multi-agent systems with both communication delay and probabilistic self-delay. The proposed methods employ a suitable piecewise Lyapunov-Krasovskii functional and the average dwell time approach. New consensus criterion for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical example showed that the proposed method is effective.

Keywords: Multi-agent systems, probabilistic self-delay, consensus, Lyapunov method, LMI.

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Authors: Martin Bader

Abstract:

During the last years, the genomes of more and more species have been sequenced, providing data for phylogenetic recon- struction based on genome rearrangement measures. A main task in all phylogenetic reconstruction algorithms is to solve the median of three problem. Although this problem is NP-hard even for the sim- plest distance measures, there are exact algorithms for the breakpoint median and the reversal median that are fast enough for practical use. In this paper, this approach is extended to the transposition median as well as to the weighted reversal and transposition median. Although there is no exact polynomial algorithm known even for the pairwise distances, we will show that it is in most cases possible to solve these problems exactly within reasonable time by using a branch and bound algorithm.

Keywords: Comparative genomics, genome rearrangements, me-dian, reversals, transpositions.

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Authors: Vultchan T. Gueorgiev, Racho M. Ivanov, Ivan S. Yatchev, Krastyo L. Hinov

Abstract:

An approach for experimental measurement of the dynamic characteristics of linear electromagnet actuators is presented. It uses accelerometer sensor to register the armature acceleration. The velocity and displacement of the moving parts can be obtained by integration of the acceleration results. The armature movement of permanent magnet linear actuator is acquired using this technique. The results are analyzed and the performance of the supposed approach is compared with the most commonly used experimental setup where the displacement of the armature vs. time is measured instead of its acceleration.

Keywords: Dynamic characteristics, dynamic simulation, linearactuators.

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Authors: Lee Yih Rou, Hishammuddin Asmuni

Abstract:

Flexible Job Shop Problem (FJSP) is an extension of classical Job Shop Problem (JSP). The FJSP extends the routing flexibility of the JSP, i.e assigning machine to an operation. Thus it makes it more difficult than the JSP. In this study, Cooperative Coevolutionary Genetic Algorithm (CCGA) is presented to solve the FJSP. Makespan (time needed to complete all jobs) is used as the performance evaluation for CCGA. In order to test performance and efficiency of our CCGA the benchmark problems are solved. Computational result shows that the proposed CCGA is comparable with other approaches.

Keywords: Co-evolution, Genetic Algorithm (GA), Flexible JobShop Problem(FJSP)

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Authors: T. Kishore Kumar

Abstract:

Speech enhancement is the process of eliminating noise and increasing the quality of a speech signal, which is contaminated with other kinds of distortions. This paper is on developing an optimum cascaded system for speech enhancement. This aim is attained without diminishing any relevant speech information and without much computational and time complexity. LMS algorithm, Spectral Subtraction and Kalman filter have been deployed as the main de-noising algorithms in this work. Since these algorithms suffer from respective shortcomings, this work has been undertaken to design cascaded systems in different combinations and the evaluation of such cascades by qualitative (listening) and quantitative (SNR) tests.

Keywords: LMS, Kalman filter, Speech Enhancement and Spectral Subtraction.

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Authors: Gizem Intepe, Tufan Koc

Abstract:

S-Curves are commonly used in technology forecasting. They show the paths of product performance in relation to time or investment in R&D. It is a useful tool to describe the inflection points and the limit of improvement of a technology. Companies use this information to base their innovation strategies. However inadequate use and some limitations of this technique lead to problems in decision making. In this paper first technology forecasting and its importance for company level strategies will be discussed. Secondly the S-Curve and its place among other forecasting techniques will be introduced. Thirdly its use in technology forecasting will be discussed based on its advantages, disadvantages and limitations. Finally an application of S-curve on 3D TV technology using patent data will also be presented and the results will be discussed.

Keywords: Patent analysis, Technological forecasting. S curves, 3D TV

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Authors: Tomislav Stambolic, Anton Causevski

Abstract:

The deficit of power supply in Macedonia is almost 30% or reached up to 3000 GWh in a year. The existing thermal and hydro power plants are not enough to cover the power and energy, so the import increases every year. Therefore, in order to have more domestic energy supply, the new trends in renewable and energy efficiency should be implemented in power sector. The paper gives some perspectives for development of the power system in Macedonia, taking into account the growth of electricity demand and in the same time with implementation of renewable and energy efficiency. The development of power system is made for the period up to 2030 with the period of every 5 years.

Keywords: Energy, Power System, Renewable, Efficiency

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Authors: Farhad Kolahan, M. Hossein Abolbashari, Samaeddin Mohitzadeh

Abstract:

Several methods are available for weight and shape optimization of structures, among which Evolutionary Structural Optimization (ESO) is one of the most widely used methods. In ESO, however, the optimization criterion is completely case-dependent. Moreover, only the improving solutions are accepted during the search. In this paper a Simulated Annealing (SA) algorithm is used for structural optimization problem. This algorithm differs from other random search methods by accepting non-improving solutions. The implementation of SA algorithm is done through reducing the number of finite element analyses (function evaluations). Computational results show that SA can efficiently and effectively solve such optimization problems within short search time.

Keywords: Simulated annealing, Structural optimization, Compliance, C.V. product.

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Authors: Da-Xue Chen, Guang-Hui Liu

Abstract:

In this paper, we study the oscillation of a class of second-order nonlinear neutral damped variable delay dynamic equations on time scales. By using a generalized Riccati transformation technique, we obtain some sufficient conditions for the oscillation of the equations. The results of this paper improve and extend some known results. We also illustrate our main results with some examples.

Keywords: Oscillation theorem, second-order nonlinear neutral dynamic equation, variable delay, damping, Riccati transformation.

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Authors: Frode van der Laak

Abstract:

The paper contributes to the feasibility of using a 5G mobile connection as a node for a Proof of Authority (PoA) blockchain, which is used for microtransactions at the same time. It uses the phone number identity of the users that are linked to the crypto wallet address. It also proposed a consensus protocol based on PoA blockchain; PoA is a permission blockchain where consensus is achieved through a set of designated authority rather than through mining, as is the case with a Proof of Work (PoW) blockchain. This report will first explain the concept of a PoA blockchain and how it works. It will then discuss the potential benefits and challenges of using a 5G mobile connection as a node in such a blockchain, and finally, the main open problem statement and proposed solutions with the requirements.

Keywords: 5G, mobile, connection, node, PoA, blockchain, microtransaction.

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Authors: G.R.A. Alberio, D. Scalone, G. Spagna

Abstract:

Anchovy (Engraulis Encrasicholus) and sardine (Sardina Pilchardus) are blue fishes linked to our alimentary tradition of Mediterranean. In our work, particularly, we tested for the first time physical and enzymatic methods to verify the freshness of species of blue fish, anchovy and sardine of Mediterranean. In connection with to the lowering of the pH after post-mortem stage we assisted to a increase in proteolytic activity of calpaine and catpsine. Already after 2 h in post-mortem there was a significant increase.

Keywords: Engraulis encrasicholus, Sardina pilchardus, freshness, index rigor.

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Authors: Thomas Meier

Abstract:

One of the major challenges for sustainable smart building systems is to support device interoperability, i.e. connecting sensor or actuator devices from different vendors, and present their functionality to the external applications. Furthermore, smart building systems are supposed to connect with devices that are not available yet, i.e. devices that become available on the market sometime later. It is of vital importance that a sustainable smart building platform provides an appropriate external interface that can be leveraged by external applications and smart services. An external platform interface must be stable and independent of specific devices and should support flexible and scalable usage scenarios. A typical approach applied in smart home systems is based on a generic device interface used within the smart building platform. Device functions, even of rather complex devices, are mapped to that generic base type interface by means of specific device drivers. Our new approach, presented in this work, extends that approach by using the smart building system’s rule engine to create complex virtual devices that can represent the most diverse properties of real devices. We examined and evaluated both approaches by means of a practical case study using a smart building system that we have developed. We show that the solution we present allows the highest degree of flexibility without affecting external application interface stability and scalability. In contrast to other systems our approach supports complex virtual device configuration on application layer (e.g. by administration users) instead of device configuration at platform layer (e.g. platform operators). Based on our work, we can show that our approach supports almost arbitrarily flexible use case scenarios without affecting the external application interface stability. However, the cost of this approach is additional appropriate configuration overhead and additional resource consumption at the IoT platform level that must be considered by platform operators. We conclude that the concept of complex virtual devices presented in this work can be applied to improve the usability and device interoperability of sustainable intelligent building systems significantly.

Keywords: Complex virtual devices, device integration, device interoperability, Internet of Things, smart building platform.

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

Abstract:

The problems arising from unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many researchers have found that the performance of existing classifiers tends to be biased towards the majority class. The k-nearest neighbors’ nonparametric discriminant analysis is a method that was proposed for classifying unbalanced classes with good performance. In this study, the methods of discriminant analysis are of interest in investigating misclassification error rates for classimbalanced data of three diabetes risk groups. The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification of class-imbalanced data of diabetes risk groups. Data from a project maintaining healthy conditions for 599 employees of a government hospital in Bangkok were obtained for the classification problem. The employees were divided into three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data including the variables of diabetes risk group, age, gender, blood glucose, and BMI were analyzed and bootstrapped for 50 and 100 samples, 599 observations per sample, for additional estimation of the misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples showed nonnormality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. Searching the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10) and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k=3 or k=4 and the defined prior probabilities of non-risk: risk: diabetic as 0.90: 0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of misclassification. The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: Bootstrap, diabetes risk groups, error rate, k-nearest neighbors.

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Authors: F. Raja, M.Rahgozar, N. Razavi, M. Siadaty

Abstract:

Main Memory Database systems (MMDB) store their data in main physical memory and provide very high-speed access. Conventional database systems are optimized for the particular characteristics of disk storage mechanisms. Memory resident systems, on the other hand, use different optimizations to structure and organize data, as well as to make it reliable. This paper provides a brief overview on MMDBs and one of the memory resident systems named FastDB and compares the processing time of this system with a typical disc resident database based on the results of the implementation of TPC benchmarks environment on both.

Keywords: Disk-Resident Database, FastDB, Main MemoryDatabase.

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Authors: K. Aloui, M. S. Naceur

Abstract:

The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a level-sets approach to delineating three-dimensional brain tumors. Then we introduce a compression plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.

Keywords: Medical imaging, level-sets, compression, meshess implification, telemedicine.

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Authors: Tero Halme, Juho Kanniainen, Markus Nordberg

Abstract:

According to the existing literature, companies manage analysts’ expectations of their future earnings by issuing pessimistic earnings guidance to meet the expectations. Consequently, one could expect that markets price this pessimistic bias in advance and penalize companies more for lowering the guidance than reward for beating the guidance. In this paper we confirm this empirically. In addition we show that although guidance revisions have a statistically significant relation to stock returns, that is not the case with the actual earnings surprise. Reason for this could be that, after the annual earnings report also information on future earnings power is given at the same time.

Keywords: Management guidance, earnings guidance, pessimistic bias

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Authors: Muna Tabuni

Abstract:

The paper contains an investigation on basic problems about the zeros of analytic theta functions. A brief introduction to analytic representation of finite quantum systems is given. The zeros of this function and there evolution time are discussed. Two open problems are introduced. The first problem discusses the cases when the zeros follow the same path. As the basis change the quantum state |f transforms into different quantum state. The second problem is to define a map between two toruses where the domain and the range of this map are the analytic functions on toruses.

Keywords: open problems, constraint, change of basis.

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Authors: Oday I. Abdullah, J. Schlattmann

Abstract:

In this study, the two dimensional heat conduction problem for the dry friction clutch disc is modeled mathematically analysis and is solved numerically using finite element method, to determine the temperature field when band contacts occurs between the rubbing surfaces during the operation of an automotive clutch. Temperature calculation have been made for contact area of different band width and the results obtained compared with these attained when complete contact occurs. Furthermore, the effects of slipping time and sliding velocity function are investigated as well. Both single and repeated engagements made at regular interval are considered.

Keywords: Band contact, dry friction clutch, frictional heating, temperature field, 2D FEM.

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Authors: Pavel Psota, Vít Lédl, Jan Václavík, Roman Doleček, Pavel Mokrý, Petr Vojtíšek

Abstract:

This paper presents advanced time average digital holography by means of frequency shift and phase modulation. This technique can measure amplitudes of vibrations at ultimate dynamic range while the amplitude distribution evaluation is done independently in every pixel. The main focus of the paper is to gain insight into behavior of the method at low amplitudes of vibrations. In order to reach that, a set of experiments was performed. Results of the experiments together with novel noise suppression show the limit of the method to be below 0.1 nm.

Keywords: Acousto-optical modulator, digital holography, low amplitudes, vibrometry.

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Authors: Tadatsugu Kitamoto

Abstract:

Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.

Keywords: Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation

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Authors: Tim Byrnes

Abstract:

Quantum computation using qubits made of two component Bose-Einstein condensates (BECs) is analyzed. We construct a general framework for quantum algorithms to be executed using the collective states of the BECs. The use of BECs allows for an increase of energy scales via bosonic enhancement, resulting in two qubit gate operations that can be performed at a time reduced by a factor of N, where N is the number of bosons per qubit. We illustrate the scheme by an application to Deutsch-s and Grover-s algorithms, and discuss possible experimental implementations. Decoherence effects are analyzed under both general conditions and for the experimental implementation proposed.

Keywords: Quantum, computing, information, Bose-Einstein condensates, macroscopic.

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Authors: Fouzia Brihmat

Abstract:

Economic planning models, which are used to build microgrids and Distributed Energy Resources (DER), are the current norm for expressing such confidence. These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1 GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation, the trade-off is that the model is more accurate, but the computation takes longer. We initially utilized the optimizer to run the model without multi-year in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower Cost Of Energy (COE) of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated.

Keywords: Battery, Corrosion, Diesel, Economic planning optimization, Hybrid energy system, HES, Lead-acid battery, Li-ion battery, multi-year planning, microgrid, price forecast, total net present cost, wind.

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