Search results for: multi valued mappings

Authors: A. Elbyed

Abstract:

Nowadays, ontologies are used for achieving a common understanding within a user community and for sharing domain knowledge. However, the de-centralized nature of the web makes indeed inevitable that small communities will use their own ontologies to describe their data and to index their own resources. Certainly, accessing to resources from various ontologies created independently is an important challenge for answering end user queries. Ontology mapping is thus required for combining ontologies. However, mapping complete ontologies at run time is a computationally expensive task. This paper proposes a system in which mappings between concepts may be generated dynamically as the concepts are encountered during user queries. In this way, the interaction itself defines the context in which small and relevant portions of ontologies are mapped. We illustrate application of the proposed system in the context of Technology Enhanced Learning (TEL) where learners need to access to learning resources covering specific concepts.

Keywords: resources query, ontologies, ontology mapping, similarity measures, semantic web, e-learning

Procedia PDF Downloads 287

Authors: Zhe Li, Aihua Cai

Abstract:

Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

Procedia PDF Downloads 51

Authors: Ramayanam Suresh, A. Nagaraja Rao, B. Eswara Reddy

Abstract:

Texture features of mammogram images are useful for finding masses or cancer cases in mammography, which have been used by radiologists. Textures are greatly succeeded for segmented images rather than normal images. It is necessary to perform segmentation for exclusive specification of cancer and non-cancer regions separately. Region of interest (ROI) is most commonly used technique for mammogram segmentation. Limitation of this method is that it is unable to explore segmentation for large collection of mammogram images. Therefore, this paper is proposed multi-ROI segmentation for addressing the above limitation. It supports greatly in finding the best texture features of mammogram images. Experimental study demonstrates the effectiveness of proposed work using benchmarked images.

Keywords: texture features, region of interest, multi-ROI segmentation, benchmarked images

Procedia PDF Downloads 281

Authors: Ibtissem Daoudi, Raoudha Chebil, Wided Lejouad Chaari

Abstract:

Serious games constitute actually a recent and attractive way supposed to replace the classical boring courses. However, the choice of the adapted serious game to a specific learning environment remains a challenging task that makes teachers unwilling to adopt this concept. To fill this gap, we present, in this paper, a multi-agent-based simulator allowing to predict the impact of a serious game integration in a learning environment given several game and players characteristics. As results, the presented tool gives intensities of several emotional aspects characterizing learners reactions to the serious game adoption. The presented simulator is tested to predict the effect of basing a coding course on the serious game ”CodeCombat”. The obtained results are compared with feedbacks of using the same serious game in a real learning process.

Keywords: emotion, learning process, multi-agent simulation, serious games

Procedia PDF Downloads 381

Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

Abstract:

In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

Procedia PDF Downloads 113

Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

Abstract:

Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

Procedia PDF Downloads 207

Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj K. Biswas, Frank Ferrese

Abstract:

This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star topology, fault tolerance, conditional diagnosability, multi-agent system, automated power system

Procedia PDF Downloads 486

Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj Biswas, Frank Ferrese

Abstract:

This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star topology, fault tolerance, conditional diagnosability, multi-agent system, automated power system

Procedia PDF Downloads 439

Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir

Abstract:

In this paper, a new neural network based variable neighborhood search is proposed for the multi-objective dynamic, flexible job shop scheduling problems. The neural network controls the problems' constraints to prevent infeasible solutions, while the Variable Neighborhood Search (VNS) applies moves, based on the critical block concept to improve the solutions. Two approaches are used for managing the constraints, in the first approach, infeasible solutions are modified according to the constraints, after the moves application, while in the second one, infeasible moves are prevented. Several neighborhood structures from the literature with some modifications, also new structures are used in the VNS. The suggested neighborhoods are more systematically defined and easy to implement. Comparison is done based on a multi-objective flexible job shop scheduling problem that is dynamic because of the jobs different release time and machines breakdowns. The results show that the presented method has better performance than the compared VNSs selected from the literature.

Keywords: constrained optimization, neural network, variable neighborhood search, flexible job shop scheduling, dynamic multi-objective optimization

Procedia PDF Downloads 323

Authors: F. Lhafiane, A. Elbyed, M. Bouchoum

Abstract:

The design of Reverse logistics Network has attracted growing attention with the stringent pressures from both environmental awareness and business sustainability. Reverse logistical activities include return, remanufacture, disassemble and dispose of products can be quite complex to manage. In addition, demand can be difficult to predict, and decision making is one of the challenges tasks. This complexity has amplified the need to develop an integrated architecture for product return as an enterprise system. The main purpose of this paper is to design Multi agent system (MAS) architecture using the Prometheus methodology to efficiently manage reverse logistics processes. The proposed MAS architecture includes five types of agents: Gate keeping Agent, Collection Agent, Sorting Agent, Processing Agent and Disposal Agent which act respectively during the five steps of reverse logistics Network.

Keywords: reverse logistics, multi agent system, prometheus methodology

Procedia PDF Downloads 441

Authors: Ravi Patel, Krishna K. Krishnan

Abstract:

In global supply chains, appropriate and sustainable suppliers play a vital role in supply chain development and feasibility. In a larger organization with huge number of suppliers, it is necessary to divide suppliers based on their past history of quality and delivery of each product category. Since performance of any organization widely depends on their suppliers, well evaluated selection criteria and decision-making models lead to improved supplier assessment and development. In this paper, SCOR® performance evaluation approach and ISO standards are used to determine selection criteria for better utilization of supplier assessment by using hybrid model of Analytic Hierchchy Problem (AHP) and Fuzzy Techniques for Order Preference by Similarity to Ideal Solution (FTOPSIS). AHP is used to determine the global weightage of criteria which helps TOPSIS to get supplier score by using triangular fuzzy set theory. Both qualitative and quantitative criteria are taken into consideration for the proposed model. In addition, a multi-product and multi-time period model is selected for order allocation. The optimization model integrates multi-objective integer linear programming (MOILP) for order allocation and a hybrid approach for supplier selection. The proposed MOILP model optimizes order allocation based on manufacturing process and product tolerances as per manufacturer’s requirement for quality product. The integrated model and solution approach are tested to find optimized solutions for different scenario. The detailed analysis shows the superiority of proposed model over other solutions which considered individual decision making models.

Keywords: AHP, fuzzy set theory, multi-criteria decision making, multi-objective integer linear programming, TOPSIS

Procedia PDF Downloads 149

Authors: Dao Phuong Nam, Do Trong Tan, Pham Tam Thanh, Le Duy Tung, Tran Hoang Anh

Abstract:

This paper considers the problem of cascade control system for unmanned aerial vehicles (UAVs). Due to the complicated modelling technique of UAV, it is necessary to separate them into two subsystems. The proposed cascade control structure is a hierarchical scheme including a robust control for inner subsystem based on H infinity theory and trajectory generator using genetic algorithm (GA), outer loop control law based on multi-parametric programming (MPP) technique to overcome the disadvantage of a big amount of calculations. Simulation results are presented to show that the equivalent path has been found and obtained by proposed cascade control scheme.

Keywords: genetic algorithm, GA, H infinity, multi-parametric programming, MPP, unmanned aerial vehicles, UAVs

Procedia PDF Downloads 190

Authors: Mohanad Alhabo, Naveed Nawaz

Abstract:

The ongoing call or data session must be maintained to ensure a good quality of service. This can be accomplished by performing the handover procedure while the user is on the move. However, the dense deployment of small cells in 5G networks is a challenging issue due to the extensive number of handovers. In this paper, a neighbour cell list method is proposed to reduce the number of target small cells and hence minimizing the number of handovers. The neighbour cell list is built by omitting cells that could cause an unnecessary handover and handover failure because of short time of stay of the user in these cells. A multi-attribute decision making technique, simple additive weighting, is then applied to the optimized neighbour cell list. Multi-tier small cells network is considered in this work. The performance of the proposed method is analysed and compared with that of the existing methods. Results disclose that our method has decreased the candidate small cell list, unnecessary handovers, handover failure, and short time of stay cells compared to the competitive method.

Keywords: handover, HetNets, multi-attribute decision making, small cells

Procedia PDF Downloads 88

Authors: Julio C. Ferreira, Maria T. A. Steiner

Abstract:

The aim of this work is to present a solution procedure referred to here as the Multi-objective Optimization for Green Vehicle Routing Problem (MOOGVRP) to provide solutions for a case study. The proposed methodology consists of three stages to resolve Scenario A. Stage 1 consists of the “treatment” of data; Stage 2 consists of applying mathematical models of the p-Median Capacitated Problem (with the objectives of minimization of distances and homogenization of demands between groups) and the Asymmetric Traveling Salesman Problem (with the objectives of minimizing distances and minimizing time). The weighted method was used as the multi-objective procedure. In Stage 3, an analysis of the results is conducted, taking into consideration the environmental aspects related to the case study, more specifically with regard to fuel consumption and air pollutant emission. This methodology was applied to a (partial) database that addresses newspaper distribution in the municipality of Curitiba, Paraná State, Brazil. The preliminary findings for Scenario A showed that it was possible to improve the distribution of the load, reduce the mileage and the greenhouse gas by 17.32% and the journey time by 22.58% in comparison with the current scenario. The intention for future works is to use other multi-objective techniques and an expanded version of the database and explore the triple bottom line of sustainability.

Keywords: Asymmetric Traveling Salesman Problem, Green Vehicle Routing Problem, Multi-objective Optimization, p-Median Capacitated Problem

Procedia PDF Downloads 89

Authors: Serhat Tüzün, Tufan Demirel

Abstract:

The objective of the present study is to select the most suitable location for a wind power plant station through Choquet integral method. The problem of selecting the location for a wind power station was considered as a multi-criteria decision-making problem. The essential and sub-criteria were specified and location selection was expressed in a hierarchic structure. Among the main criteria taken into account in this paper are wind potential, technical factors, social factors, transportation, and costs. The problem was solved by using different approaches of Choquet integral and the best location for a wind power station was determined. Then, the priority weights obtained from different Choquet integral approaches are compared and commented on.

Keywords: multi-criteria decision making, choquet integral, fuzzy sets, location of a wind power plant

Procedia PDF Downloads 394

Authors: Nasser S. Shebka

Abstract:

Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

Procedia PDF Downloads 65

Authors: Mehdi Radmehr, Amir Hamed Mashhadzadeh, Mehdi Jafari

Abstract:

Traditional HVDC systems are tough to DC short circuits as they are current regulated with a large reactance connected in series with cables. Multi-terminal DC wind farm topologies are attracting increasing research attempt. With AC/DC converters on the generator side, this topology can be developed into a multi-terminal DC network for wind power collection, which is especially suitable for large-scale offshore wind farms. For wind farms, the topology uses high-voltage direct-current transmission based on voltage-source converters (VSC-HVDC). Therefore, they do not suffer from over currents due to DC cable faults and there is no over current to react to. In this study, the multi-terminal DC wind farm topology is introduced. Then, possible internal DC faults are analyzed according to type and characteristic. Fault over current expressions are given in detail. Under this characteristic analysis, fault detection and detailed protection methods are proposed. Theoretical analysis and PSCAD/EMTDC simulations are provided.

Keywords: DC short circuits, multi-terminal DC wind farm topologies, HVDC transmission based on VSC, fault analysis

Procedia PDF Downloads 400

Authors: Ngozi Nwogu, Mohammed Kajama, Emmanuel Anyanwu, Edward Gobina

Abstract:

With the objective to create technologically advanced materials to be scientifically applicable, multi-layer silica alumina membranes were molecularly fabricated by continuous surface coating silica layers containing hybrid material onto a ceramic porous substrate for flue gas separation applications. The multi-layer silica alumina membrane was prepared by dip coating technique before further drying in an oven at elevated temperature. The effects of substrate physical appearance, coating quantity, the cross-linking agent, a number of coatings and testing conditions on the gas separation performance of the membrane have been investigated. Scanning electron microscope was used to investigate the development of coating thickness. The membrane shows impressive perm selectivity especially for CO2 and N2 binary mixture representing a stimulated flue gas stream

Keywords: gas separation, silica membrane, separation factor, membrane layer thickness

Procedia PDF Downloads 384

Authors: Aydin Teymourifar, Gurkan Ozturk

Abstract:

In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization

Procedia PDF Downloads 338

Authors: Supanan Chansap, Werachon Cheukamud, Pornanan Kueakhai, Narin Changklungmoa

Abstract:

Fasciola species (Fasciola spp.) is caused fasciolosis in ruminants such as cattle, sheep, and buffalo. Fasciola gigantica (F.gigantica) commonly infects tropical regions. Fasciola hepatica (F.hepatica) in temperate regions. Liver fluke infection affects livestock economically, for example, reduced milk and meat production, weight loss, sterile animals. Currently, Triclabendazole is used to treat liver flukes. However, liver flukes have also been found to be resistant to drugs in countries. Therefore, vaccination is an attractive alternative to prevent liver fluke infection. Peptide vaccines are new vaccine technologies that mimic epitope antigens that trigger an immune response. An interesting antigen used in vaccine production is catepsin L, a family of proteins that play an important role in the life of the parasite in the host. This study aims to identify immunogenic regions of protein and construct a multi-epidetope vaccine using an immunoinformatic tool. Fasciola gigantica Cathepsin L1 (FgCatL1), Fasciola gigantica Cathepsin L1G (FgCatL1G), and Fasciola gigantica Cathepsin L1H (FgCatL1H) were predicted B-cell and Helper T lymphocytes (HTL) by Immune Epitope and Analysis Resource (IEDB) servers. Both B-cell and HTL epitopes aligned with cathepsin L of the host and Fasciola hepatica (F. hepatica). Epitope groups were selected from non-conserved regions and overlapping sequences with F. hepatica. All overlapping epitopes were linked with the GPGPG and KK linker. GPGPG linker was linked between B-cell epitope. KK linker was linked between HTL epitope and B-cell and HTL epitope. The antigenic scores of multi-epitope peptide vaccine was 0.7824. multi-epitope peptide vaccine was non-allergen, non-toxic, and good soluble. Multi-epitope peptide vaccine was predicted tertiary structure and refinement model by I-Tasser and GalaxyRefine server, respectively. The result of refine structure model was good quality that was generated by Ramachandran plot analysis. Discontinuous and linear B-cell epitopes were predicted by ElliPro server. Multi-epitope peptide vaccine model was two and seven of discontinuous and linear B-cell epitopes, respectively. Furthermore, multi-epitope peptide vaccine was docked with Toll-like receptor 2 (TLR-2). The lowest energy ranged from -901.3 kJ/mol. In summary, multi-epitope peptide vaccine was antigenicity and probably immune response. Therefore, multi-epitope peptide vaccine could be used to prevent F. gigantica infections in the future.

Keywords: fasciola gigantica, Immunoinformatic tools, multi-epitope, Vaccine

Procedia PDF Downloads 49

Authors: Homa Ghave, Parmis Shahmaleki

Abstract:

This paper presents a new multi-criteria stochastic mathematical model for a single machine scheduling with outsourcing allowed. There are multiple jobs processing in batch. For each batch, all of job or a quantity of it can be outsourced. The jobs have stochastic processing time and lead time and deterministic due dates arrive randomly. Because of the stochastic inherent of processing time and lead time, we use the chance constrained programming for modeling the problem. First, the problem is formulated in form of stochastic programming and then prepared in a form of deterministic mixed integer linear programming. The objectives are considered in the model to minimize the maximum tardiness and outsourcing cost simultaneously. Several procedures have been developed to deal with the multi-criteria problem. In this paper, we utilize the concept of satisfaction functions to increases the manager’s preference. The proposed approach is tested on instances where the random variables are normally distributed.

Keywords: single machine scheduling, multi-criteria mathematical model, outsourcing strategy, uncertain lead times and processing times, chance constrained programming, satisfaction function

Procedia PDF Downloads 241

Authors: Raja Rajeswari K

Abstract:

Orthogonal Frequency Division Multiplexing (OFDM), a multi Carrier transmission technique that has been used in implementing the majority of wireless applications like Wireless Network Protocol Standards (like IEEE 802.11a, IEEE 802.11n), in telecommunications (like LTE, LTE-Advanced) and also in Digital Audio & Video Broadcast standards. The latest research and development in the area of orthogonal frequency division multiplexing, Universal Filtered Multi Carrier (UFMC) & Filtered OFDM (F-OFDM) has attracted lots of attention for wideband wireless communications. In this paper UFMC & F-OFDM system are implemented and comparative analysis are carried out in terms of M-ary QAM modulation scheme over Dolph-chebyshev filter & rectangular window filter and to estimate Bit Error Rate (BER) over Rayleigh fading channel.

Keywords: UFMC, F-OFDM, BER, M-ary QAM

Procedia PDF Downloads 139

Authors: Yin-Yann Chen, Jia-Ying Li

Abstract:

Assembly line balancing problems can be categorized into one-sided, two-sided, and multi-manned ones by using the number of operators deployed at workstations. This study explores the balancing problem of a resource-constrained assembly line with multi-manned workstations. Resources include machines or tools in assembly lines such as jigs, fixtures, and hand tools. A mathematical programming model was developed to carry out decision-making and planning in order to minimize the numbers of workstations, resources, and operators for achieving optimal production efficiency. To improve the solution-finding efficiency, a genetic algorithm (GA) and a simulated annealing algorithm (SA) were designed and developed in this study to be combined with a practical case in car making. Results of the GA/SA and mathematics programming were compared to verify their validity. Finally, analysis and comparison were conducted in terms of the target values, production efficiency, and deployment combinations provided by the algorithms in order for the results of this study to provide references for decision-making on production deployment.

Keywords: heuristic algorithms, line balancing, multi-manned workstation, resource-constrained

Procedia PDF Downloads 178

Authors: Madhura Bandyopadhyay

Abstract:

Teaching writing within multicultural and multiethnic communities poses many unique challenges not the least of which is that of intercultural communication. When the writing is in English, pedagogical imperatives often encounter the universalizing tendencies of standardization of both language use and structural parameters which are often at odds with maintaining local practices which preserve cultural pluralism. English often becomes the contact zone within which individual identities of students play out against the standardization imperatives of the larger world. Writing classes can serve as places which become instruments of assimilation of ethnic minorities to a larger globalizing or nationalistic agenda. Hence, for those outside of the standard practices of writing English, adaptability towards a mastery of those practices valued as standard become the focus of teaching taking away from diversity of local English use and other modes of critical thinking. In a very multicultural and multiethnic context such as the US or Singapore, these dynamics become very important. This paper will argue that multiethnic writing classrooms can greatly benefit from taking up a cultural studies approach whereby the students’ lived environments and experiences are analyzed as cultural texts to produce writing. Such an approach eliminates limitations of using both literary texts as foci of discussion as in traditional approaches to teaching writing and the current trend in teaching composition without using texts at all. By bringing in students’ lived experiences into the classroom and analyzing them as cultural compositions stressing the ability to communicate across cultures, cultural competency is valued rather than adaptability while privileging pluralistic experiences as valuable even as universal shared experience are found. Specifically, while teaching writing in English in a multicultural classroom, a cultural studies approach makes both teacher and student aware of the diversity of the English language as it exists in our global context in the students’ experience while making space for diversity in critical thinking, structure and organization of writing effective in an intercultural context.

Keywords: English, multicultural, teaching, writing

Procedia PDF Downloads 483

Authors: Yang Yang, Dan Liu

Abstract:

Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

Procedia PDF Downloads 94

Authors: Abdon Choque-Rivero

Abstract:

The Jacobi system with the Dirichlet boundary condition is considered on a half-line lattice when the coefficients are real valued. The inverse problem of recovery of the coefficients from various data sets containing the so-called transmission eigenvalues is analyzed. The Marchenko method is utilized to solve the corresponding inverse problem.

Keywords: inverse scattering, discrete system, transmission eigenvalues, Marchenko method

Procedia PDF Downloads 120

Authors: Rosa Amalia Safitri, Ine van der Fels-Klerx, Henk Hogeveen

Abstract:

Halal is a dietary law observed by people following Islamic faith. It is considered as a type of credence food quality which cannot be easily assured by consumers even upon and after consumption. Therefore, Halal certification takes place as a practical tool for the consumers to make an informed choice particularly in a non-Muslim majority country, including the Netherlands. Discrete choice experiment (DCE) was employed in this study for its ability to assess the importance of attributes attached to Halal beef in the Dutch market and to investigate consumer utilities. Furthermore, willingness to pay (WTP) for the desired Halal certification was estimated. Four most relevant attributes were selected, i.e., the slaughter method, traceability information, place of purchase, and Halal certification. Price was incorporated as an attribute to allow estimation of willingness to pay for Halal certification. There were 242 Muslim respondents who regularly consumed Halal beef completed the survey, from Dutch (53%) and non-Dutch consumers living in the Netherlands (47%). The vast majority of the respondents (95%) were within the age of 18-45 years old, with the largest group being student (43%) followed by employee (30%) and housewife (12%). Majority of the respondents (76%) had disposable monthly income less than € 2,500, while the rest earned more than € 2,500. The respondents assessed themselves of having good knowledge of the studied attributes, except for traceability information with 62% of the respondents considered themselves not knowledgeable. The findings indicated that slaughter method was valued as the most important attribute, followed by Halal certificate, place of purchase, price, and traceability information. This order of importance varied across sociodemographic variables, except for the slaughter method. Both Dutch and non-Dutch subgroups valued Halal certification as the third most important attributes. However, non-Dutch respondents valued it with higher importance (0,20) than their Dutch counterparts (0,16). For non-Dutch, the price was more important than Halal certification. The ideal product preferred by the consumers indicated the product serving the highest utilities for consumers, and characterized by beef obtained without pre-slaughtering stunning, with traceability info, available at Halal store, certified by an official certifier, and sold at 2.75 € per 500 gr. In general, an official Halal certifier was mostly preferred. However, consumers were not willing to pay for premium for any type of Halal certifiers, indicated by negative WTP of -0.73 €, -0.93 €, and -1,03€ for small, official, and international certifiers, respectively. This finding indicated that consumers tend to lose their utility when confronted with price. WTP estimates differ across socio-demographic variables with male and non-Dutch respondents had the lowest WTP. The unfamiliarity to traceability information might cause respondents to perceive it as the least important attribute. In the context of Halal certified meat, adding traceability information into meat packaging can serve two functions, first consumers can justify for themselves whether the processes comply with Halal requirements, for example, the use of pre-slaughtering stunning, and secondly to assure its safety. Therefore, integrating traceability info into meat packaging can help to make informed decision for both Halal status and food safety.

Keywords: consumer utilities, discrete choice experiments, Halal certification, willingness to pay

Procedia PDF Downloads 104

Authors: Ekin Nurbaş

Abstract:

One of the essential challenges in array signal processing, which has drawn enormous research interest over the past several decades, is estimating the direction of arrival (DOA) of plane waves impinging on an array of sensors. In recent years, the Compressive Sensing based DoA estimation methods have been proposed by researchers, and it has been discovered that the Compressive Sensing (CS)-based algorithms achieved significant performances for DoA estimation even in scenarios where there are multiple coherent sources. On the other hand, the Genetic Algorithm, which is a method that provides a solution strategy inspired by natural selection, has been used in sparse representation problems in recent years and provides significant improvements in performance. With all of those in consideration, in this paper, a method that combines the Genetic Algorithm (GA) and the Multi-Criteria Decision Making (MCDM) approaches for Direction of Arrival (DoA) estimation in the Compressive Sensing (CS) framework is proposed. In this method, we generate a multi-objective optimization problem by splitting the norm minimization and reconstruction loss minimization parts of the Compressive Sensing algorithm. With the help of the Genetic Algorithm, multiple non-dominated solutions are achieved for the defined multi-objective optimization problem. Among the pareto-frontier solutions, the final solution is obtained with the multiple MCDM methods. Moreover, the performance of the proposed method is compared with the CS-based methods in the literature.

Keywords: genetic algorithm, direction of arrival esitmation, multi criteria decision making, compressive sensing

Procedia PDF Downloads 117

Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

Abstract:

Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

Procedia PDF Downloads 849

Authors: Serhat Tuzun, Tufan Demirel

Abstract:

Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

Procedia PDF Downloads 196