Search results for: multi track diplomacy

Authors: George Oliveira, Luana D. Fronza, Luiza Medeiros, Patricia D. M. Plentz

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The research presented in this article is part of a wide project that proposes a scheduling system for multi-robots in intelligent warehouses employing multi-robot path-planning (MPP) and multi-robot task allocation (MRTA) to reconcile multiple restrictions (task delivery time, task priorities, charging capacity, and robots battery capacity). We present the software component capable of interconnecting an open streaming processing architecture and robot operating system (ROS), ensuring communication and message exchange between robots and the environment in which they are inserted. Simulation results show the good performance of our proposed technique for connecting ROS and streaming platforms.

Keywords: complex distributed systems, mobile robots, smart warehouses, streaming platforms

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Authors: Mohamed Barbary, Mohamed H. Abd El-azeem

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Maneuvering non-ellipsoidal extended object tracking (M-NEOT) using high-resolution inverse synthetic aperture radar (ISAR) observations is gaining momentum recently. This work presents a new robust implementation of the Jump Markov (JM) multi-Bernoulli (MB) filter for M-NEOT, where the M-NEOT’s ISAR observations are characterized using a skewed (SK) non-symmetrically normal distribution. To cope with the possible abrupt change of kinematic state, extension, and observation distribution over an extended object when a target maneuvers, a multiple model technique is represented based on an MB-track-before-detect (TBD) filter supported by SK-sub-random matrix model (RMM) or sub-ellipses framework. Simulation results demonstrate this remarkable impact.

Keywords: maneuvering extended objects, ISAR, skewed normal distribution, sub-RMM, JM-MB-TBD filter

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Authors: Ali Afaghi, Sehraneh Ghaemi

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The coordination of the multi-agent systems has been one of the interesting topic in recent years, because of its potential applications in many branches of science and engineering such as sensor networks, flocking, underwater vehicles and etc. In the most of the related studies, it is assumed that the dynamics of the multi-agent systems are integer-order and linear and the multi-agent systems with the fractional-order nonlinear dynamics are rarely considered. However many phenomena in nature cannot be described within integer-order and linear characteristics. This paper investigates the leader-following consensus problem for a class of nonlinear fractional-order multi-agent systems based on observer-based cooperative control. In the system, the dynamics of each follower and leader are nonlinear. For a multi-agent system with fixed directed topology firstly, an observer-based consensus protocol is proposed based on the relative observer states of neighboring agents. Secondly, based on the property of the stability theory of fractional-order system, some sufficient conditions are presented for the asymptotical stability of the observer-based fractional-order control systems. The proposed method is applied on a five-agent system with the fractional-order nonlinear dynamics and unavailable states. The simulation example shows that the proposed scenario results in the good performance and can be used in many practical applications.

Keywords: fractional-order multi-agent systems, leader-following consensus, nonlinear dynamics, directed graphs

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Authors: A. R. Manu, V. K. Agrawal, K. N. Balasubramanya Murthy

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Authentication is required in stored database systems so that only authorized users can access the data and related cloud infrastructures. This paper proposes an authentication technique using multi-factor and multi-dimensional authentication system with multi-level security. The proposed technique is likely to be more robust as the probability of breaking the password is extremely low. This framework uses a multi-modal biometric approach and SMS to enforce additional security measures with the conventional Login/password system. The robustness of the technique is demonstrated mathematically using a statistical analysis. This work presents the authentication system along with the user authentication architecture diagram, activity diagrams, data flow diagrams, sequence diagrams, and algorithms.

Keywords: design, implementation algorithms, performance, biometric approach

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Authors: Majid Khalili

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This paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new multi-objective variable neighborhood algorithm (MOVNS). A set of experimental instances are carried out to evaluate the algorithm by advanced multi-objective performance measures. The algorithm is carefully evaluated for its performance against available algorithm by means of multi-objective performance measures and statistical tools. The related results show that a variant of our proposed MOVNS provides sound performance comparing with other algorithms.

Keywords: no-wait hybrid flowshop scheduling; multi-objective variable neighborhood algorithm; makespan; total weighted tardiness

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Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller

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Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.

Keywords: multi-agent system, safety analysis, safety model, integration map

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Authors: Farzad Jafarpour Taher, Maghsud Solimanpur

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Production planning is one of the complex tasks in multi-product firms that produce a wide range of products. Since resources in mass production companies are limited and different products use common resources, there must be a careful plan so that firms can respond to customer needs efficiently. Azar-battery Company is a firm that provides twenty types of products for its customers. Therefore, careful planning must be performed in this company. In this research, the current conditions of Azar-battery Company were investigated to provide a mathematical programming model to determine the optimum production rate of the products in this company. The production system of this company is multi-stage, multi-product and multi-period. This system is studied in terms of a one-year planning horizon regarding the capacity of machines and warehouse space limitation. The problem has been modeled as a linear programming model with deterministic demand in which shortage is not allowed. The objective function of this model is to minimize costs (including raw materials, assembly stage, energy costs, packaging, and holding). Finally, this model has been solved by Lingo software using the branch and bound approach. Since the computation time was very long, the solver interrupted, and the obtained feasible solution was used for comparison. The proposed model's solution costs have been compared to the company’s real data. This non-optimal solution reduces the total production costs of the company by about %35.

Keywords: multi-period, multi-product production, multi-stage, production planning

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Authors: Norie A. Akeel, Z. Sajuri, A. K. Ariffin

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This paper discusses the effect of different loading analysis on crack initiation life of wheel/rail in the contact region. A simulated three dimensional (3D) elasto plastic model of a wheel/rail contact is modeled using the fine mesh technique in the contact region by using Finite Element Method FEM code ANSYS 11.0 software. Different loads of approximately from 70 to 140 KN was applied on the wheel tread through the running surface on the railhead surface to simulate stress distribution (Von Mises) and a life prediction of the crack initiation under rolling contact motion. Stress analysis is achieved and the fatigue life to the rail head surface is calculated numerically by using a multi-axial fatigue life of crack initiation model. All results obtained from the previous researches are compared with this research.

Keywords: FEM, rolling contact, rail track, stress distribution, fatigue life

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Authors: Iram Zahra

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Friction and wear properties of multilayer graphene coatings (MLG) on nickel substrate were investigated at the macroscale, and different failure mechanisms working at the interface of nickel-graphene coatings were evaluated. Multilayer graphene coatings were produced on a nickel substrate using the atmospheric chemical vapour deposition (CVD) technique. Wear tests were performed on the pin-on-disk tribometer apparatus under dry air conditions, and using the saltwater solution, distilled water, and mineral oil lubricants and counterparts used in these wear tests were fabricated of stainless steel, chromium, and silicon nitride. The wear test parameters such as rotational speed, wear track diameter, temperature, relative humidity, and load were 60 rpm, 6 mm, 22˚C, 45%, and 2N, respectively. To analyse the friction and wear behaviour, coefficient of friction (COF) vs time curves were plotted, and the sliding surfaces of the samples and counterparts were examined using the optical microscope. Results indicated that graphene-coated nickel in mineral oil lubrication and dry conditions gave the minimum average value of COP (0.05) and wear track width ( ̴151 µm) against the three different types of counterparts. In contrast, uncoated nickel samples indicated a maximum wear track width ( ̴411 µm) and COF (0.5). Thorough investigation and analysis concluded that graphene-coated samples have two times lower COF and three times lower wear than the bare nickel samples. Furthermore, mechanical failures were significantly lower in the case of graphene-coated nickel. The overall findings suggested that multilayer graphene coatings have drastically decreased wear and friction on nickel substrate at the macroscale under various lubricating conditions and against different counterparts.

Keywords: friction, lubricity, multilayer graphene, sliding, wear

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Authors: Marwa Hussien Mohamed, Mohamed Helmy Khafagy

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Map-Reduce is a programming model which is widely used to extract valuable information from enormous volumes of data. Map-reduce designed to support heterogeneous datasets. Apache Hadoop map-reduce used extensively to uncover hidden pattern like data mining, SQL, etc. The most important operation for data analysis is joining operation. But, map-reduce framework does not directly support join algorithm. This paper explains and compares two-way and multi-way map-reduce join algorithms for map reduce also we implement MR join Algorithms and show the performance of each phase in MR join algorithms. Our experimental results show that map side join and map merge join in two-way join algorithms has the longest time according to preprocessing step sorting data and reduce side cascade join has the longest time at Multi-Way join algorithms.

Keywords: Hadoop, MapReduce, multi-way join, two-way join, Ubuntu

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Authors: Sudhina H. K, Ravi M. Yadahalli, N. M. Shetti

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Reconfigurable antennas represent a recent innovation in antenna design that changes from classical fixed-form, Fixed function antennas to modifiable structures that can be adapted to fit the requirements of a time varying system. The ability to control the operating band of an antenna system can have many useful applications. Systems that operate in an acquire-and-track configuration would see a benefit from active bandwidth control. In such systems a wide band search mode is first employed to find a desired signal, Then a narrow band track mode is used to follow only that signal. Utilizing active antenna bandwidth control, A single antenna would function for both the wide band and narrow band configurations providing the rejection of unwanted signals with the antenna hardware. This ability to move a portion of the RF filtering out of the receiver and onto the antenna itself will also aid in reducing the complexity of the often expensive RF processing subsystems.

Keywords: designing methods, mems, stack, reconfigurable elements

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a new hybrid particle swarm optimization algorithm is proposed for the multi-objective flexible job shop scheduling problem that is very important and hard combinatorial problem. The Pareto approach is used for solving the multi-objective problem. Several new local search heuristics are integrated into an algorithm based on the critical block concept to enhance the performance of the algorithm. The algorithm is compared with the recently published multi-objective algorithms based on benchmarks selected from the literature. Several metrics are used for quantifying performance and comparison of the achieved solutions. The algorithms are also compared based on the Weighting summation of objectives approach. The proposed algorithm can find the Pareto solutions more efficiently than the compared algorithms in less computational time.

Keywords: swarm-based optimization, local search, Pareto optimality, flexible job shop scheduling, multi-objective optimization

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Authors: Zhibo Xiao, Tharini Nayanika de Silva, Kezhi Mao

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In this paper, we present an evolving knowledge extraction system named AKEOS (Automatic Knowledge Extraction from Online Sources). AKEOS consists of two modules, including a one-time learning module and an evolving learning module. The one-time learning module takes in user input query, and automatically harvests knowledge from online unstructured resources in an unsupervised way. The output of the one-time learning is a structured vector representing the harvested knowledge. The evolving learning module automatically schedules and performs repeated one-time learning to extract the newest information and track the development of an event. In addition, the evolving learning module summarizes the knowledge learned at different time points to produce a final knowledge vector about the event. With the evolving learning, we are able to visualize the key information of the event, discover the trends, and track the development of an event.

Keywords: evolving learning, knowledge extraction, knowledge graph, text mining

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Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

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Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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Authors: Jolly Puri, Shiv Prasad Yadav

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Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.

Keywords: multi-component DEA, fuzzy multi-component DEA, fuzzy resources, decision making units (DMUs)

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo, Linhang Zhu

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This study proposed a 3D human body reconstruction method, which integrates multi-view joint information into a set of joints and processes it with a parametric human body template. Firstly, we obtained human body image information captured from multiple perspectives. The multi-view information can avoid self-occlusion and occlusion problems during the reconstruction process. Then, we used the MvP algorithm to integrate multi-view joint information into a set of joints. Next, we used the parametric human body template SMPL-X to obtain more accurate three-dimensional human body reconstruction results. Compared with the traditional single-view parametric human body template reconstruction, this method significantly improved the accuracy and stability of the reconstruction.

Keywords: parametric human body templates, reconstruction of the human body, multi-view, joint

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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Authors: Aedah Abd Rahman

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Software organisations may implement single or multiple frameworks in order to remain competitive. There are wide selection of generic Software Process Improvement (SPI) frameworks, best practices and standards implemented with different focuses and goals. Issues and difficulties emerge in the SPI practices from the context of software development and IT Service Management (ITSM). This research looks into the integration of multiple frameworks from the perspective of software development and ITSM. The research question of this study is how to define steps of methodology to solve the multi model software process improvement problem. The objective of this study is to define the research approach and methodologies to produce a more integrated and efficient Multi Model Process Improvement (MMPI) solution. A multi-step methodology is used which contains the case study, framework mapping and Delphi study. The research outcome has proven the usefulness and appropriateness of the proposed framework in SPI and quality practice in Malaysian software industries. This mixed method research approach is used to tackle problems from every angle in the context of software development and services. This methodology is used to facilitate the implementation and management of multi model environment of SPI frameworks in multiple domains.

Keywords: Delphi study, methodology, multi model software process improvement, service management

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Authors: Laabidi Mounira, Zayani Rafk, Bouallegue Ridha

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Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC/OQAM) is presently known as a sustainable alternative to conventional Orthogonal Frequency Division Multiplexing (OFDM) for signal transmission over multi-path fading channels. Like all multicarrier systems, FBMC/OQAM suffers from high Peak to Average Power Ratio (PAPR). Due to the symbol overlap inherent in the FBMC/OQAM system, the direct application of conventional OFDM PAPR reduction scheme is far from being effective. This paper suggests a novel scheme termed Multi-Blocks Selective Mapping (MB-SLM) whose simulation results show that its performance in terms of PAPR reduction is almost identical to that of OFDM system.

Keywords: FBMC/OQAM, multi-blocks, OFDM, PAPR, SLM

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Authors: A. Sathiya Susuman

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Background: The importance of maternal and child healthcare services cannot be stressed enough. These services are very important for the health and health outcomes of the mother and that of the child and in ensuring that both maternal and child deaths are prevented. The objective of the study is to inspire good quality maternal and child health care services in Swaziland. Specifically, is Swaziland on track with the 2015 Millennium Development Goals? Methods: The study used secondary data from the Swaziland Demographic and Health Survey 2006-07. This is an explorative and descriptive study which used pre-selected variables to study factors influencing the use of maternal and child healthcare services in Swaziland. Different types of examinations, such as univariate, bivariate, and multivariate statistical analysis were adopted. Results: The study findings showed a high use rate of antenatal care (97.3%) and delivery care (74.0%), and a low rate of postnatal care use (20.5%). The uptake childhood immunization is also high in the country, averaging more than 80.0%. Moreover, certain factors which were found to be influencing the use of maternal healthcare and childhood immunization include: woman’s age, parity, media exposure, maternal education, wealth status, and residence. The findings also revealed that these factors affect the use of maternal and child health differently. Conclusion: It is important to study factors related to maternal and child health uptake to inform relevant stakeholders about possible areas of improvement. Programs to educate families about the importance of maternal and child healthcare services should be implemented. Swaziland needs to work hard on child survival and maternal health care services, no doubt it is on track with the MDG 4 & 5.

Keywords: maternal healthcare, antenatal care, delivery care, postnatal care, child health, immunization, socio-economic and demographic factors

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Authors: Kyung-Jin You, Kiwon Rhee, Marc H. Schieber, Nitish V. Thakor, Hyun-Chool Shin

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It remains unknown whether M1 neurons encode multi-finger movements independently or as a certain neural network of single finger movements although multi-finger movements are physically a combination of single finger movements. We present an evidence of correlation between single and multi-finger movements and also attempt a challenging task of semi-blind decoding of neural data with minimum training of the neural decoder. Data were collected from 115 task-related neurons in M1 of a trained rhesus monkey performing flexion and extension of each finger and the wrist (12 single and 6 two-finger-movements). By exploiting correlation of temporal firing pattern between movements, we found that correlation coefficient for physically related movements pairs is greater than others; neurons tuned to single finger movements increased their firing rate when multi-finger commands were instructed. According to this knowledge, neural semi-blind decoding is done by choosing the greatest and the second greatest likelihood for canonical candidates. We achieved a decoding accuracy about 60% for multiple finger movement without corresponding training data set. this results suggest that only with the neural activities on single finger movements can be exploited to control dexterous multi-fingered neuroprosthetics.

Keywords: finger movement, neural activity, blind decoding, M1

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Authors: Abdelazziz Aouiche, El Moundher Aouiche, Mouhamed Salah Soudani

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Renewable energy sources now significantly contribute to the replacement of traditional fossil fuel energy sources. One of the most potent types of renewable energy that has developed quickly in recent years is photovoltaic energy. We all know that solar energy, which is sustainable and non-depleting, is the best knowledge form of energy that we have at our disposal. Due to changing weather conditions, the primary drawback of conventional solar PV cells is their inability to track their maximum power point. In this study, we apply artificial neural networks (ANN) to automatically track and measure the maximum power point (MPP) of solar panels. In MATLAB, the complete system is simulated, and the results are adjusted for the external environment. The results are better performance than traditional MPPT methods and the results demonstrate the advantages of using neural networks in solar PV systems.

Keywords: modeling, photovoltaic panel, artificial neural networks, maximum power point tracking

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Authors: Justie Su-Tzu Juan, Ming-Jheng Li, Ching-Fen Lee, Ruei-Yu Wu

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A secret image sharing scheme is a way to protect images. The main idea is dispersing the secret image into numerous shadow images. A secret image sharing scheme can withstand the impersonal attack and achieve the highly practical property of multiuse  is more practical. Therefore, this paper proposes a verifiable and detectable secret image-sharing scheme called VDGMSISS to solve the impersonal attack and to achieve some properties such as encrypting multi-secret images at one time and multi-use. Moreover, our scheme can also be used for any genera access structure.

Keywords: multi-secret image sharing scheme, verifiable, de-tectable, general access structure

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Authors: Iman Iraei, Mina Sharifi

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A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.

Keywords: mean shift, object tracking, blur extent, wavelet transform, motion blur

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Authors: Ahmed Machmoum, Malika El Kyal

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We consider iterative parallel multi-splitting method for differential algebraic equations. The main feature of the proposed idea is to use the asynchronous form. We prove that the multi-splitting technique can effectively accelerate the convergent performance of the iterative process. The main characteristic of an asynchronous mode is that the local algorithm not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays tobe substantial and unpredictable. Note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: computer, multi-splitting methods, asynchronous mode, differential algebraic systems

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Authors: Nidal Dwaikat

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This work presents the development of alpha spectroscopy method with Solid-state nuclear track detectors using aluminum thin films. The resolution of this method is high, and it is able to discriminate between alpha particles at different incident energy. It can measure the exact number of alpha particles at specific energy without needing a calibration of alpha track diameter versus alpha energy. This method was tested by using Cf-252 alpha standard source at energies 5.11 Mev, 3.86 MeV and 2.7 MeV, which produced by the variation of detector -standard source distance. On front side, two detectors were covered with two Aluminum thin films and the third detector was kept uncovered. The thickness of Aluminum thin films was selected carefully (using SRIM 2013) such that one of the films will block the lower two alpha particles (3.86 MeV and 2.7 MeV) and the alpha particles at higher energy (5.11 Mev) can penetrate the film and reach the detector’s surface. The second thin film will block alpha particles at lower energy of 2.7 MeV and allow alpha particles at higher two energies (5.11 Mev and 3.86 MeV) to penetrate and produce tracks. For uncovered detector, alpha particles at three different energies can produce tracks on it. For quality assurance and accuracy, the detectors were mounted on thick enough copper substrates to block exposure from the backside. The tracks on the first detector are due to alpha particles at energy of 5.11 MeV. The difference between the tracks number on the first detector and the tracks number on the second detector is due to alpha particles at energy of 3.8 MeV. Finally, by subtracting the tracks number on the second detector from the tracks number on the third detector (uncovered), we can find the tracks number due to alpha particles at energy 2.7 MeV. After knowing the efficiency calibration factor, we can exactly calculate the activity of standard source.

Keywords: aluminium thin film, alpha particles, copper substrate, CR-39 detector

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Authors: Tomas Barnak, Libor Matejka

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The aim of this study is to create a standard application using multi-criteria evaluation in the field of forensic engineering. This situation can occur in the professional assessment in several cases such as when it is necessary to consider more criteria variant of the structural subsystems, more variants according to several criteria based on a court claim, which requires expert advice. A problematic situation arises when it is necessary to clearly determine the ranking of the options according to established criteria, and reduce subjective evaluation. For the procurement in the field of construction which is based on the prepared text of the law not only economic criteria but also technical, technological and environmental criteria will be determined. This fact substantially changes the style of evaluation of individual bids. For the above-mentioned needs of procurement, the unification of expert’s decisions and the use of multi-criteria assessment seem to be a reasonable option. In the case of experimental verification when using multi-criteria evaluation of alternatives construction subsystem the economic, technical, technological and environmental criteria will be compared. The core of the solution is to compare a selected number of set criteria, application methods and evaluation weighting based on the weighted values assigned to each of the criteria to use multi-criteria evaluation methods. The sequence of individual variations is determined by the evaluation of the importance of the values of corresponding criteria concerning expertise in the problematic of outside wall constructional subsystems.

Keywords: criteria, expertise, multi-criteria evaluation, outside wall subsystems

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Authors: Mert Turanli, Hakan Temeltas

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In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: adaptive control, centroidal voronoi tessellations, composite adaptation, coordination, multi robots

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Authors: S. H. Lee, M. J. Park, O. M. Kwon

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In this paper, reliable consensus of multi-agent systems with sampled-data is investigated. By using a suitable Lyapunov-Krasovskii functional and some techniques such as Wirtinger Inequality, Schur Complement and Kronecker Product, the results of this systems are obtained by solving a set of Linear Matrix Inequalities(LMIs). One numerical example is included to show the effectiveness of the proposed criteria.

Keywords: multi-agent, linear matrix inequalities (LMIs), kronecker product, sampled-data, Lyapunov method

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