Search results for: implicit coupling algorithm

Authors: Mohamed Mahmoud

Abstract:

This paper has developed an effect-cause analysis technique for fault diagnosis in digital circuits. The main algorithm of our technique is based on the Enhanced Deduction Algorithm, which processes the real response of the CUT to the applied test T to deduce the values of the internal lines. An experimental version of the algorithm has been implemented in C++. The code takes about 7592 lines. The internal values are determined based on the logic values under the permanent stuck-fault model. Using a backtracking strategy guarantees that the actual values are covered by at least one solution, or no solution is found.

Keywords: enhanced deduction algorithm, backtracking strategy, automatic test equipment, verfication

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Authors: Siamak Dawazdah Emami, Amin Khodaei, Harith Bin Ahmad, Hairul A. Adbul-Rashid

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The Fano resonance effect on plasmonic nanoparticle materials results in such materials possessing a number of unique optical properties, and the potential applicability for sensing, nonlinear devices and slow-light devices. A Fano resonance is a consequence of coherent interference between superradiant and subradiant hybridized plasmon modes. Incident light on subradiant modes will initiate excitation that results in superradiant modes, and these superradient modes possess zero or finite dipole moments alongside a comparable negligible coupling with light. This research work details the derivation of an electrodynamics coupling model for the interaction of dipolar transitions and radiation via plasmonic nanoclusters such as quadrimers, pentamers and heptamers. The directivity calculation is analyzed in order to qualify the redirection of emission. The geometry of a configured array of nanostructures strongly influenced the transmission and reflection properties, which subsequently resulted in the directivity of each antenna being related to the nanosphere size and gap distances between the nanospheres in each model’s structure. A well-separated configuration of nanospheres resulted in the structure behaving similarly to monomers, with spectra peaks of a broad superradiant mode being centered within the vicinity of 560 nm wavelength. Reducing the distance between ring nanospheres in pentamers and heptamers to 20~60 nm caused the coupling factor and charge distributions to increase and invoke a subradiant mode centered within the vicinity of 690 nm. Increasing the outside ring’s nanosphere distance from the centered nanospheres caused the coupling factor to decrease, with the coupling factor being inversely proportional to cubic of the distance between nanospheres. This phenomenon led to a dramatic decrease of the superradiant mode at a 200 nm distance between the central nanosphere and outer rings. Effects from a superradiant mode vanished beyond a 240 nm distance between central and outer ring nanospheres.

Keywords: fano resonance, optical antenna, plasmonic, nano-clusters

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Authors: Prasenjit Singha, Sunil Yadav, Soumya Ranjan Mohantry, Ajay Kumar Shukla

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Temperature distribution in the hematite ore mixed with 7.5% coal was predicted by solving a 1-D heat conduction equation using an implicit finite difference approach. In this work, it was considered a square slab of 20 cm x 20 cm, which assumed the coal to be uniformly mixed with hematite ore. It was solved the equations with the use of MATLAB 2018a software. Heat transfer effects in this 1D dimensional slab convective and the radiative boundary conditions are also considered. Temperature distribution obtained inside hematite slab by considering microwave heating time, thermal conductivity, heat capacity, carbon percentage, sample dimensions, and many other factors such as penetration depth, permittivity, and permeability of coal and hematite ore mixtures. The resulting temperature profile can be used as a guiding tool for optimizing the microwave-assisted carbothermal reduction process of hematite slab was extended to other dimensions as well, viz., 1 cm x 1 cm, 5 cm x 5 cm, 10 cm x 10 cm, 20 cm x 20 cm. The model predictions are in good agreement with experimental results.

Keywords: hematite ore, coal, microwave processing, heat transfer, implicit method, temperature distribution

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Authors: Yanhua Zhao, Chenli Rao, Dongdong Li, Chuanmin Tao

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The Chinese Centers for Disease Control and Prevention (CCDC) issued a new laboratory-based algorithm for HIV diagnosis on April 2016, which initially screens with a combination HIV-1/HIV-2 antigen/antibody fourth-generation immunoassay (IA) followed, when reactive, an HIV-1/HIV-2 undifferentiated antibody IA in duplicate. Reactive specimens with concordant results undergo supplemental tests with western blots, or HIV-1 nucleic acid tests (NATs) and non-reactive specimens with discordant results receive HIV-1 NATs or p24 antigen tests or 2-4 weeks follow-up tests. However, little data evaluating the application of the new algorithm have been reported to date. The study was to evaluate the performance of new laboratory-based HIV diagnostic algorithm in an inpatient population of Southwest China over the initial 6 months by compared with the old algorithm. Plasma specimens collected from inpatients from May 1, 2016, to October 31, 2016, are submitted to the laboratory for screening HIV infection performed by both the new HIV testing algorithm and the old version. The sensitivity and specificity of the algorithms and the difference of the categorized numbers of plasmas were calculated. Under the new algorithm for HIV diagnosis, 170 of the total 52 749 plasma specimens were confirmed as positively HIV-infected (0.32%). The sensitivity and specificity of the new algorithm were 100% (170/170) and 100% (52 579/52 579), respectively; while 167 HIV-1 positive specimens were identified by the old algorithm with sensitivity 98.24% (167/170) and 100% (52 579/52 579), respectively. Three acute HIV-1 infections (AHIs) and two early HIV-1 infections (EHIs) were identified by the new algorithm; the former was missed by old procedure. Compared with the old version, the new algorithm produced fewer WB-indeterminate results (2 vs. 16, p = 0.001), which led to fewer follow-up tests. Therefore, the new HIV testing algorithm is more sensitive for detecting acute HIV-1 infections with maintaining the ability to verify the established HIV-1 infections and can dramatically decrease the greater number of WB-indeterminate specimens.

Keywords: algorithm, diagnosis, HIV, laboratory

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Authors: Suraka Bhattacharjee, Ranjan Chaudhury

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The interaction between the charge degrees of freedom for itinerant antiferromagnets is investigated in terms of generalized charge stiffness constant corresponding to nearest neighbour t-J model and t1-t2-t3-J model. The low dimensional hole doped antiferromagnets are the well known systems that can be described by the t-J-like models. Accordingly, we have used these models to investigate the fermionic pairing possibilities and the coupling between the itinerant charge degrees of freedom. A detailed comparison between spin and charge couplings highlights that the charge and spin couplings show very similar behaviour in the over-doped region, whereas, they show completely different trends in the lower doping regimes. Moreover, a qualitative equivalence between generalized charge stiffness and effective Coulomb interaction is also established based on the comparisons with other theoretical and experimental results. Thus it is obvious that the enhanced possibility of fermionic pairing is inherent in the reduction of Coulomb repulsion with increase in doping concentration. However, the increased possibility can not give rise to pairing without the presence of any other pair producing mechanism outside the t-J model. Therefore, one can conclude that the t-J-like models themselves solely are not capable of producing conventional momentum-based superconducting pairing on their own.

Keywords: generalized charge stiffness constant, charge coupling, effective Coulomb interaction, t-J-like models, momentum-space pairing

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Authors: Doru Anastasiu Popescu, Dan Rădulescu

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In this paper, we determine the similarity of two HTML web applications. We are going to use a genetic algorithm in order to determine the most significant web pages of each application (we are not going to use every web page of a site). Using these significant web pages, we will find the similarity value between the two applications. The algorithm is going to be efficient because we are going to use a reduced number of web pages for comparisons but it will return an approximate value of the similarity. The binary trees are used to keep the tags from the significant pages. The algorithm was implemented in Java language.

Keywords: Tag, HTML, web page, genetic algorithm, similarity value, binary tree

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Authors: Engy Adel Mohamed, Yasser Gamal-Eldin Hegazy

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This paper presents a firefly based algorithm for optimal sizing and allocation of distributed generators for profit maximization. Distributed generators in the proposed algorithm are of photovoltaic and combined heat and power technologies. Combined heat and power distributed generators are modeled as voltage controlled nodes while photovoltaic distributed generators are modeled as constant power nodes. The proposed algorithm is implemented in MATLAB environment and tested the unbalanced IEEE 37-node feeder. The results show the effectiveness of the proposed algorithm in optimal selection of distributed generators size and site in order to maximize the total system profit.

Keywords: distributed generators, firefly algorithm, IEEE 37-node feeder, profit maximization

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Authors: Selcuk Aslan, Dervis Karaboga, Celal Ozturk

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Artificial Bee Colony (ABC) algorithm is one of the most successful swarm intelligence based metaheuristics. It has been applied to a number of constrained or unconstrained numerical and combinatorial optimization problems. In this paper, we presented a parallelized version of ABC algorithm by adapting employed and onlooker bee phases to the Compute Unified Device Architecture (CUDA) platform which is a graphical processing unit (GPU) programming environment by NVIDIA. The execution speed and obtained results of the proposed approach and sequential version of ABC algorithm are compared on functions that are typically used as benchmarks for optimization algorithms. Tests on standard benchmark functions with different colony size and number of parameters showed that proposed parallelization approach for ABC algorithm decreases the execution time consumed by the employed and onlooker bee phases in total and achieved similar or better quality of the results compared to the standard sequential implementation of the ABC algorithm.

Keywords: Artificial Bee Colony algorithm, GPU computing, swarm intelligence, parallelization

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Authors: Qiang Zhang, Chun Yuan

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Since the PU (Prediction Unit) decision process is the most time consuming part of the emerging HEVC (High Efficient Video Coding) standardin intra and inter frame coding, this paper proposes the fast PU decision algorithm and speed up the algorithm using CUDA (Compute Unified Device Architecture). In intra frame coding, the fast PU decision algorithm uses the texture features to skip intra-frame prediction or terminal the intra-frame prediction for smaller PU size. In inter frame coding of HEVC, the fast PU decision algorithm takes use of the similarity of its own two Nx2N size PU's motion vectors and the hierarchical structure of CU (Coding Unit) partition to skip some modes of PU partition, so as to reduce the motion estimation times. The accelerate algorithm using CUDA is based on the fast PU decision algorithm which uses the GPU to make the motion search and the gradient computation could be parallel computed. The proposed algorithm achieves up to 57% time saving compared to the HM 10.0 with little rate-distortion losses (0.043dB drop and 1.82% bitrate increase on average).

Keywords: HEVC, PU decision, inter prediction, intra prediction, CUDA, parallel

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Authors: Mengjun Yang, Zhulin Zong, Jie Gao

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In this paper, a new and robust algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework. Traditional CS based methods have to assume that unknown scatters exactly lie on the pre-divided grids; otherwise, their reconstruction performance dropped significantly. In this processing algorithm, several basis shifts are utilized to achieve the same effect as grid refinement does. The detailed implementation of the basis shift algorithm is presented in this paper. From the simulation we can see that using the basis shift algorithm, imaging precision can be improved. The effectiveness and feasibility of the proposed method are investigated by the simulation results.

Keywords: ISAR imaging, sparse reconstruction, off-grid, basis shift

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: distributed control, game theory, multi-agent learning, reinforcement learning

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Authors: Mahmoud M. Othman, Y. G. Hegazy, A. Y. Abdelaziz

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This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.

Keywords: distributed generation, heuristic approach, optimization, planning

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Authors: Bei Zhang, Zhaoxin Zhang, Lidong Zhao

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Green infrastructures (GIs) for rainwater management can directly meet the multiple purposes of urban greening and non-point source pollution control. To reveal the overall layout law of GIs dominated by typical woody plants and their impact on urban environmental effects, we constructed a HYDRUS-1D and Stormwater management (SWMM) coupling model to simulate the response of typical root woody plant planting methods on urban hydrological. The results showed that the coupling model had high adaptability to the simulation of urban surface runoff control effect under different woody plant planting methods (NSE ≥0.64 and R² ≥ 0.71). The regulation effect on surface runoff showed that the average runoff reduction rate of GIs increased from 60 % to 71 % with the increase of planting area (5% to 25%) under the design rainfall event of the 2-year recurrence interval. Sophora japonica with tap roots was slightly higher than that of without plants (control) and Malus baccata (M. baccata) with fibrous roots. The comprehensive benefit evaluation system of rainwater utilization technology was constructed by using an analytic hierarchy process. The coupling model was used to evaluate the comprehensive benefits of woody plants with different planting areas in the study area in terms of environment, economy, and society. The comprehensive benefit value of planting 15% M. baccata was the highest, which was the first choice for the planting of woody plants in the study area. This study can provide a scientific basis for the decision-making of green facility layouts of woody plants.

Keywords: green infrastructure, comprehensive benefits, runoff regulation, woody plant layout, coupling model

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Authors: Luciano Garelli, Marco Schauer, Jorge D’Elia, Mario A. Storti, Sabine C. Langer

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This paper discuss a coupling strategy of two different software packages to provide fluid structure interaction (FSI) analysis. The basic idea is to combine the advantages of the two codes to create a powerful FSI solver for two and three dimensional analysis. The fluid part is computed by a program called PETSc-FEM, a software developed at Centro de Investigación de Métodos Computacionales (CIMEC). The structural part of the coupled process is computed by the research code elementary Parallel Solver (elPaSo) of the Technische Universität Braunschweig, Institut für Konstruktionstechnik (IK).

Keywords: computational fluid dynamics (CFD), fluid structure interaction (FSI), finite element method (FEM), software

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Authors: Masato Sasaki, Masayoshi Yamamoto

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The majority of wireless power transfer (WPT) systems transfer power in a directional manner. This paper describes a discrete exciting voltage control technique for WPT via magnetic resonant coupling with two orthogonal transmitter coils (2D omni-directional WPT system) which can maximize the power transfer efficiency in response to the change of coupling status. The theory allows the equations of the efficiency of the system to be determined at all the rate of the mutual inductance. The calculated results are included to confirm the advantage to one directional WPT system and the validity of the theory and the equations.

Keywords: wireless power transfer, omni-directional, orthogonal, efficiency

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Authors: Ashkan Ebadi, Adam Krzyzak

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Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: tourism, hotel recommender system, hybrid, implicit features

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Authors: Meng-Hui Chen, Chiao-Wei Yu, Pei-Chann Chang

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Imperial competitive algorithm (ICA) simulates a multi-agent algorithm. Each agent is like a kingdom has its country, and the strongest country in each agent is called imperialist, others are colony. Countries are competitive with imperialist which in the same kingdom by evolving. So this country will move in the search space to find better solutions with higher fitness to be a new imperialist. The main idea in this paper is using the peculiarity of ICA to explore the search space to solve the kinds of combinational problems. Otherwise, we also study to use the greed search to increase the local search ability. To verify the proposed algorithm in this paper, the experimental results of traveling salesman problem (TSP) is according to the traveling salesman problem library (TSPLIB). The results show that the proposed algorithm has higher performance than the other known methods.

Keywords: traveling salesman problem, artificial chromosomes, greedy search, imperial competitive algorithm

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Authors: Mohammad Sahadet Hossain, Shamsil Arifeen, Mehrab Hossian Likhon

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In this paper, we analyze a linear time invariant (LTI) descriptor system of large dimension. Since these systems are difficult to simulate, compute and store, we attempt to reduce this large system using Low Rank Cholesky Factorized Alternating Directions Implicit (LRCF-ADI) iteration followed by Square Root Balanced Truncation. LRCF-ADI solves the dual Lyapunov equations of the large system and gives low-rank Cholesky factors of the gramians as the solution. Using these cholesky factors, we compute the Hankel singular values via singular value decomposition. Later, implementing square root balanced truncation, the reduced system is obtained. The bode plots of original and lower order systems are used to show that the magnitude and phase responses are same for both the systems.

Keywords: low-rank cholesky factor alternating directions implicit iteration, LTI Descriptor system, Lyapunov equations, Square-root balanced truncation

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Authors: Abbas Mirakhorli

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A hub covering problem is a type of hub location problem that tries to maximize the coverage area with the least amount of installed hubs. There have not been many studies in the literature about multi-objective hubs covering location problems. Thus, in this paper, a bi-objective model for the hub covering problem is presented. The two objectives that are considered in this paper are the minimization of total transportation costs and the maximization of coverage of origin-destination nodes. A genetic algorithm is presented to solve the model when the number of nodes is increased. The genetic algorithm is capable of solving the model when the number of nodes increases by more than 20. Moreover, the genetic algorithm solves the model in less amount of time.

Keywords: facility location, hub covering, multi-objective optimization, genetic algorithm

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Authors: Masoumeh Ali Pouri, Hamid Haj Seyyed Javadi

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Nowadays, cloud processing is one of the important issues in information technology. Since scheduling of tasks graph is an NP-hard problem, considering approaches based on undeterminisitic methods such as evolutionary processing, mostly genetic and cuckoo algorithms, will be effective. Therefore, an efficient algorithm has been proposed for scheduling of tasks graph to obtain an appropriate scheduling with minimum time. In this algorithm, the new approach is based on making the length of the critical path shorter and reducing the cost of communication. Finally, the results obtained from the implementation of the presented method show that this algorithm acts the same as other algorithms when it faces graphs without communication cost. It performs quicker and better than some algorithms like DSC and MCP algorithms when it faces the graphs involving communication cost.

Keywords: cloud computing, scheduling, tasks graph, chakoos algorithm

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Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

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In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

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Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng

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Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.

Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm

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Authors: Runlin Liu, Shilong Li

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China is a mountainous country, with two-thirds of its territory covered by plateaus, hills, and mountains, and nearly half of the cities and towns are distributed in mountainous areas. Compared with the environmental constraints in the development path of cities and towns in the plains, there are heterogeneities in aspects such as spatial characteristics, growth mode, and ecological protection and so on for mountain village and townlets, and the development path of mountain village and townlets has a bidirectional relationship between mountain space and economic growth. Based on classical growth theory, this article explores the two-dimensional coupling relation between space and economy in mountain village and townlets under background of rural rejuvenation. GIS technology is adopted in the study to analyze spatial trends and patterns, economical spatial differentiation characteristics of village and townlets. This powerful tool can also help differentiate and analyze limiting factors and assessment systems in the economic growth of village and townlets under spatial dimension of mountainous space. To make the research more specific, this article selects mountain village and townlets in Southwest China as the object of study; this provides good cases for analyzing parallel coupling mechanism of the duality structure system between economic growth and spatial expansion and discussing the path selection of spatial economic growth of mountain village and towns with multiple constraints. The research results can provide quantitative references for the spatial and economic development paths of mountain villages and towns, which is helpful in realizing efficient and high-quality development mode with equal emphasis on spatial and economic benefits for these type of towns.

Keywords: coupling mechanism, geographic information technology, mountainous town, synergetic development, spatial economy

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Authors: Taha Ahmed Özbey, Sedat Nazlıbilek, Alparslan Çağrı Yapıcı

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Combline cavity filters have gained significant attention in recent years due to their exceptional narrowband characteristics, high unloaded Q, remarkable out-of-band rejection, and versatile post-manufacturing tuning capabilities. These filters play a vital role in various wireless communication systems, radar applications, and other advanced technologies where stringent frequency selectivity and superior performance are required. This paper represents combined cavity filter design and implementation by coupling matrix synthesis. Limited filter length, 50 dB out-of-band rejection, and agile design were aimed. To do so, CAD tools and intuitive methods were used.

Keywords: cavity, band pass filter, cavity combline filter, coupling matrix synthesis

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Authors: Girish Sambhaji Gund

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The controlled nanostructure growth and its strong coupling with the current collector are key factors to achieve good electrochemical performance of faradaic-dominant electroactive materials. We employed binder-less and additive-free hydrothermal and physical vapor doping methods for the synthesis of nickel (Ni) and cobalt (Co) based compounds nanostructures (NiO, NiCo2O4, NiCo2S4) deposited on different conductive substrates such as carbon nanotube (CNT) on stainless steel, and reduced graphene oxide (rGO) and N-doped rGO on nickel foam (NF). The size and density of Ni- and Co-based compound nanostructures are controlled through the strong coupling with carbon allotropes on stainless steel and NF substrates. This controlled nanostructure of Ni- and Co-based compounds with carbon allotropes leads to stable faradaic electrochemical reactions at the material/current collector interface and within the electrode, which is consequence of strong coupling of nanostructure with functionalized carbon surface as a buffer layer. Thus, it is believed that the results provide the synergistic approaches to stabilize electrode materials physically and chemically, and hence overall electrochemical activity of faradaic dominating battery-type electrode materials through buffer layer engineering.

Keywords: metal compounds, carbon allotropes, doping, electrochemicstry, hybrid supercapacitor

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Authors: Arbnor Pajaziti, Hasan Cana

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In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.

Keywords: robotic arm, neural network, genetic algorithm, optimization

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Authors: Yadwinder Kumar, Priyanka Rani Amandeep Singh

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In this paper the design of a multiband pre-fractal micro strip antenna with proximity coupling feed is presented. The proposed antenna resonates on seven different frequencies that are 2.6 GHz, 5.1 GHz, 9.4 GHz, 11.5 GHz, 13.8 GHz, 16.3 GHz, and 18.6 GHz. Simulated results presented here shows that the minimum return loss is achieved at the 16.3 GHz frequency which is up to 37 dB. Also the maximum band width of 700 MHz is achieved by the frequency bands 13.4 GHz to 14.1 GHz, 15.9 GHz to 16.6 GHz and 18.2 GHz to 18.9 GHz. The proposed feed line is sandwiched between two substrate layers and increases in the bandwidth of antenna has been observed up to 13% in comparison of micro strip feed line. Effect of key design parameters such as variation in substrate material, substrate height and feeding technique on antenna S-parameter have been investigated and discussed.

Keywords: fractal antenna, pre-fractals, micro strip antenna, ISM band, electromagnetic coupling, VSWR

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Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

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In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA) is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: balanced truncation, clustering, dominant pole, Hankel norm, model reduction

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Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

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Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs

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Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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