Search results for: maintenance sequence planning.

Authors: Yi-Zhong Weng, Chien-Kang Huang, Yu-Feng Huang, Chi-Yuan Yu, Darby Tien-Hao Chang

Abstract:

Search for a tertiary substructure that geometrically matches the 3D pattern of the binding site of a well-studied protein provides a solution to predict protein functions. In our previous work, a web server has been built to predict protein-ligand binding sites based on automatically extracted templates. However, a drawback of such templates is that the web server was prone to resulting in many false positive matches. In this study, we present a sequence-order constraint to reduce the false positive matches of using automatically extracted templates to predict protein-ligand binding sites. The binding site predictor comprises i) an automatically constructed template library and ii) a local structure alignment algorithm for querying the library. The sequence-order constraint is employed to identify the inconsistency between the local regions of the query protein and the templates. Experimental results reveal that the sequence-order constraint can largely reduce the false positive matches and is effective for template-based binding site prediction.

Keywords: Protein structure, binding site, functional prediction

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Authors: Juan P. Novoa, Mario A. Rios

Abstract:

This paper presents a transmission planning methodology that considers the conversion of HVAC transmission lines to HVDC as an alternative of expansion of power systems, as a consequence of restrictions for the construction of new lines. The transmission expansion planning problem formulates an optimization problem that minimizes the total cost that includes the investment cost to convert lines from HVAC to HVDC and possible required reinforcements of the power system prior to the conversion. The costs analysis assesses the impact of the conversion on the reliability because transmission lines are out of service during the conversion work. The presented methodology is applied to a test system considering a planning a horizon of 10 years.

Keywords: Cost optimization, energy non supplied, HVAC, HVDC, transmission expansion planning.

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Authors: D. Pérez, M. M. E. Alemany

Abstract:

In this work, a framework to model the Supply Chain (SC) Collaborative Planning (CP) process is proposed. The main contributions of this framework concern 1) the presentation of the decision view, the most important one due to the characteristics of the process, jointly within the physical, organisation and information views, and 2) the simultaneous consideration of the spatial and temporal integration among the different supply chain decision centres. This framework provides the basis for a realistic and integrated perspective of the supply chain collaborative planning process and also the analytical modeling of each of its decisional activities.

Keywords: Collaborative Planning, Decision View, Distributed Decision-Making, Framework.

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Authors: Masaru Furukawa, Shigeki Hirobayashi, Tadanobu Misawa

Abstract:

Nowadays, IT/Business strategy alignment is still a key topic of concern among managers worldwide. Change has always being considered the primary challenge affecting the strategy alignment. Planning for alignment in uncertain and dynamic changing environments is burdened with risk as organizations seek to understand how much flexibility to build in their management information system so as to maintain high levels of alignment. The literature review showed that there is a tight relationship between IT infrastructure flexibility and the strategy alignment with strategic information systems (SIS) planning serving as a moderator of this relationship, and that emphasized the needs for organizations to use SIS planning consistently and to monitor the relationship between IS flexibility and the alignment. This paper presents the procedure of SIS planning with IS flexibility renovation via future oriented analysis of POC (penalty of change) as a function of cost and time. Using this SIS planning and monitoring IS flexibility and the alignment during periods of increased change in dynamic and uncertain environments reduces the risk that could transform IT into an inhibitor rather than an enabler of change.

Keywords: IT/Business strategy alignment, strategic information systems (SIS) planning, IS flexibility, penalty of change (POC).

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Authors: Chong-Yang Qiao, Teeravarunyou Sakol

Abstract:

Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.

Keywords: Augmented reality, situation awareness, decision-making, problem-solving.

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Authors: Mohammad Mirabi

Abstract:

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To meet the requirements on time and to minimize the make-span performance of large permutation flow-shop scheduling problems in which there are sequence dependent setup times on each machine, this paper develops one hybrid genetic algorithms (HGA). Proposed HGA apply a modified approach to generate population of initial chromosomes and also use an improved heuristic called the iterated swap procedure to improve initial solutions. Also the author uses three genetic operators to make good new offspring. The results are compared to some recently developed heuristics and computational experimental results show that the proposed HGA performs very competitively with respect to accuracy and efficiency of solution.

Keywords: Hybrid genetic algorithm, Scheduling, Permutationflow-shop, Sequence dependent

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Authors: Varin Chouvatut, Suthep Madarasmi, Mihran Tuceryan

Abstract:

This paper aims to propose a novel, robust, and simple method for obtaining a human 3D face model and camera pose (position and orientation) from a video sequence. Given a video sequence of a face recorded from an off-the-shelf digital camera, feature points used to define facial parts are tracked using the Active- Appearance Model (AAM). Then, the face-s 3D structure and camera pose of each video frame can be simultaneously calculated from the obtained point correspondences. This proposed method is primarily based on the combined approaches of Gradient Descent and Powell-s Multidimensional Minimization. Using this proposed method, temporarily occluded point including the case of self-occlusion does not pose a problem. As long as the point correspondences displayed in the video sequence have enough parallax, these missing points can still be reconstructed.

Keywords: Camera Pose, Face Reconstruction, Gradient Descent, Powell's Multidimensional Minimization.

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Authors: M. Kashiripoor

Abstract:

Existing indicators for sustainable urban development do not identify the features of cities’ planning structures and their architecture. Iranian city has special relevance problem of assessing the conformity of their planning and development of the concept of sustainable development. Based on theoretical sources, the author concludes that, despite the existence of common indicators for sustainable development of settlements, specialized evaluation criteria city structure planning has not been developed. He is trying to fill this gap and put forward a system of indicators characterizing the level of development of the architectural-planning structure of the city. The proposed system of indicators is designed based on technical and economic urban standard indicators from different countries. Alternative designing systems and requirements of modern rating systems like LEED-ND comprise a criterion for evaluation of urban structures in accordance with principles of "Green" building and New Urbanism. Urban development trends are close in spirit of sustainable development and developed under its influence. The study allowed concluding that a system of indicators to identify the relevant architectural-planning structure of the city, requirements of sustainable development, should be adapted to the conditions of each country, particularly in Iran. The article attempts typology proposed indicators, which are presented in tabular form and are divided into two types: planning and spatial. This article discusses the known indicators of sustainable development and proposed specific system of indicators characterizing the level of development of architectural-planning structure of the city. This article examines indicators for evaluating level of city' planning structure development. The proposed system of indicators is derived from the urban planning standards and rating systems such as LEED-ND, BREEAM Community and CASBEE-UD.

Keywords: Architectural-planning structure of cities, urban planning indicators, urban space indicators.

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Authors: Michele Sinico

Abstract:

In the Giovanelli illusion, some collinear dots appear misaligned, when each dot lies within a circle and the circles are not collinear. In this illusion, the role of the frame of reference, determined by the circles, is considered a crucial factor. Three experiments were carried out to study the influence of directionality of the circles on the misalignment. The adjustment method was used. Participants changed the orthogonal position of each dot, from the left to the right of the sequence, until a collinear sequence of dots was achieved. The first experiment verified the illusory effect of the misalignment. In the second experiment, the influence of two different directionalities of the circles (-0.58° and +0.58°) on the misalignment was tested. The results show an over-normalization on the sequences of the dots. The third experiment tested the misalignment of the dots without any inclination of the sequence of circles (0°). Only a local illusory effect was found. These results demonstrate that the directionality of the circles, as a global factor, can increase the misalignment. The findings also indicate that directionality and the frame of reference are independent factors in explaining the Giovanelli illusion.

Keywords: Giovanelli illusion, visual illusion, directionality, misalignment, frame of reference.

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Authors: Georgia Pozoukidou

Abstract:

TELUM software is a land use model designed specifically to help metropolitan planning organizations (MPOs) prepare their transportation improvement programs and fulfill their numerous planning responsibilities. In this context obtaining, preparing, and validating socioeconomic forecasts are becoming fundamental tasks for an MPO in order to ensure that consistent population and employment data are provided to travel demand models. Chittenden County Metropolitan Planning Organization of Vermont State was used as a case study to test the applicability of TELUM land use model. The technical insights and lessons learned from the land use model application have transferable value for all MPOs faced with land use forecasting development and transportation modeling.

Keywords: Calibration data requirements, land use models, land use planning, Metropolitan Planning Organizations.

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Authors: Matías Micheletto, Rodrigo Santos, Sergio F. Ochoa

Abstract:

In developing countries, most roads in rural areas are dirt road. They require frequent maintenance since they are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the maintenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: Dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision.

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Authors: Niranjali Jayasuirya, Majell Backhausen

Abstract:

Water Sensitive Urban Design (WSUD) features are increasingly used to treat and manage polluted stormwater runoff in urbanised areas. It is important to monitor and evaluate the effectiveness of the infrastructure in achieving their intended performance targets after constructing and operating these features overtime. The paper presents the various methods of analysis used to assess the effectiveness of the in-situ WSUD features, such as: onsite visual inspections during operational and non operational periods, maintenance audits and periodic water quality testing. The results will contribute to a better understanding of the operational and maintenance needs of in-situ WSUD features and assist in providing recommendations to better manage life cycle performance.

Keywords: Bio-retention swales, Maintenance plan, Operational plan, Water Sensitive Urban Design, Water quality improvement.

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Authors: S. Werrlich, E. Eichstetter, K. Nitsche, G. Notni

Abstract:

Augmented Reality (AR) is a strong growing research topic in different training domains such as medicine, sports, military, education and industrial use cases like assembly and maintenance tasks. AR claims to improve the efficiency and skill-transfer of training tasks. This paper gives a comprehensive overview of evaluations using AR for assembly and maintenance training tasks published between 1992 and 2017. We search in a structured way in four different online databases and get 862 results. We select 17 relevant articles focusing on evaluating AR-based training applications for assembly and maintenance tasks. This paper also indicates design guidelines which are necessary for creating a successful application for an AR-based training. We also present five scientific limitations in the field of AR-based training for assembly tasks. Finally, we show our approach to solve current research problems using Design Science Research (DSR).

Keywords: Assembly, augmented reality, survey, training.

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Authors: Jiratta Phuboon-ob, Raweewan Auepanwiriyakul

Abstract:

A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance. Therefore, in this paper, we introduce a new approach aimed to solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that 2PO outperform the original algorithms in terms of query processing cost and view maintenance cost.

Keywords: Data warehouse, materialized views, view selectionproblem, two-phase optimization.

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Authors: H. Shayeghi, M. Mahdavi

Abstract:

Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.

Keywords: Adequacy Optimization, Transmission Expansion Planning, DCGA.

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Authors: M. Königová, J. Fejfar

Abstract:

Business continuity management (BCM) identifies potential external and internal threats to an organization and their impacts to business operations. The goal of the article is to identify, based on the analysis of employee turnover in organizations in the Czech Republic, the role of personnel planning in BCM. The article is organized as follows. The first part of the article concentrates on the theoretical background of the topic. The second part of the article is dedicated to the evaluation of the outcomes of the survey conducted (questionnaire survey), focusing on the analysis of employee turnover in organizations in the Czech Republic. The final part of the article underlines the role of personnel planning in BCM, since poor planning of staff needs in an organization can represent a future threat for business continuity ensuring.

Keywords: Business continuity management, key employees, personnel planning, turnover.

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Authors: Leila Jafari, Viliam Makis

Abstract:

In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: Condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand.

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Authors: Jinghua Zhang, Charles B. Owen, Jinsheng Xu

Abstract:

A new hybrid coding method for compressing animated polygonal meshes is presented. This paper assumes the simplistic representation of the geometric data: a temporal sequence of polygonal meshes for each discrete frame of the animated sequence. The method utilizes a delta coding and an octree-based method. In this hybrid method, both the octree approach and the delta coding approach are applied to each single frame in the animation sequence in parallel. The approach that generates the smaller encoded file size is chosen to encode the current frame. Given the same quality requirement, the hybrid coding method can achieve much higher compression ratio than the octree-only method or the delta-only method. The hybrid approach can represent 3D animated sequences with higher compression factors while maintaining reasonable quality. It is easy to implement and have a low cost encoding process and a fast decoding process, which make it a better choice for real time application.

Keywords: animated polygonal meshes, compression, deltacoding, octree.

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

Abstract:

This paper and its companion (Part 2) deal with modeling and optimization of two NP-hard problems in production planning of flexible manufacturing system (FMS), part type selection problem and loading problem. The part type selection problem and the loading problem are strongly related and heavily influence the system-s efficiency and productivity. The complexity of the problems is harder when flexibilities of operations such as the possibility of operation processed on alternative machines with alternative tools are considered. These problems have been modeled and solved simultaneously by using real coded genetic algorithms (RCGA) which uses an array of real numbers as chromosome representation. These real numbers can be converted into part type sequence and machines that are used to process the part types. This first part of the papers focuses on the modeling of the problems and discussing how the novel chromosome representation can be applied to solve the problems. The second part will discuss the effectiveness of the RCGA to solve various test bed problems.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm

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Authors: Fredrik Pettersson

Abstract:

The paper applies a discourse analytical approach to investigate important concepts influencing the infrastructure planning process in the region of Scania in southern Sweden. Two discourses, one concerning regional development and one concerning sustainability are identified, discussed and contrasted. It is argued that the perceptions of problems and their suggested solutions related to transportation are based on specific ideas, in turn dependent on the importance given to certain concepts, such as regional enlargement, Scania as a transit region, the national environmental quality goals and regional attractiveness. These concepts, their underlying meaning structures and their relevance for the infrastructure planning process are analyzed. The handling of conflicting interests in the planning process, and the possible implications this may have is also discussed. The results indicate that the regional development discourse is dominant and although the solutions to the problems caused by transport are framed in similar ways in the two discourses a harmonization between conflicting goals is proving difficult to achieve.

Keywords: Discourse analysis, Infrastructure planning, Regional development, Sustainability.

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Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

Abstract:

Industrial end users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both Machine Learning and First Principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed from breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems and humans – including asset maintenance operations – in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: Degradation models, ageing, anomaly detection, soft sensor, incremental learning.

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Authors: Javad Abdalkhani

Abstract:

Convergence of power series solutions for a class of non-linear Abel type equations, including an equation that arises in nonlinear cooling of semi-infinite rods, is very slow inside their small radius of convergence. Beyond that the corresponding power series are wildly divergent. Implementation of nonlinear sequence transformation allow effortless evaluation of these power series on very large intervals..

Keywords: Nonlinear transformation, Abel Volterra Equations, Mathematica

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Authors: Jiratta Phuboon-ob, Raweewan Auepanwiriyakul

Abstract:

A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance cost. Therefore, in this paper, we introduce a new approach aimed at solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that our method provides a further improvement in term of query processing cost and view maintenance cost.

Keywords: Data warehouse, materialized views, view selectionproblem, two-phase optimization.

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Authors: Neha Asthana, Vishal Krishna Prasad

Abstract:

Collaborative Planning and Forecasting is an innovative and systematic approach towards productive integration and assimilation of data synergized into information. The changing and variable market dynamics have persuaded global business chains to incorporate Collaborative Planning and Forecasting as an imperative tool. Thus, it is essential for the supply chains to constantly improvise, update its nature, and mould as per changing global environment.

Keywords: Information transfer, Forecasting, Optimization.

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Authors: M. Bakhouya, S. A. Bahra, T. El-Ghazawi

Abstract:

The Partitioned Global Address Space (PGAS) programming paradigm offers ease-of-use in expressing parallelism through a global shared address space while emphasizing performance by providing locality awareness through the partitioning of this address space. Therefore, the interest in PGAS programming languages is growing and many new languages have emerged and are becoming ubiquitously available on nearly all modern parallel architectures. Recently, new parallel machines with multiple cores are designed for targeting high performance applications. Most of the efforts have gone into benchmarking but there are a few examples of real high performance applications running on multicore machines. In this paper, we present and evaluate a parallelization technique for implementing a local DNA sequence alignment algorithm using a PGAS based language, UPC (Unified Parallel C) on a chip multithreading architecture, the UltraSPARC T1.

Keywords: Partitioned Global Address Space, Unified Parallel C, Multicore machines, Multi-threading Architecture, Sequence alignment.

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Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: Automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation.

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Authors: JiEun Jeong, Se-Won Kang, Hee-Ju Hwang, Sung-Hwa Chae, Sang-Haeng Choi, Hong-SeogPark, YeonSoo Han, Bok-Reul Lee, Dae-Hyun Seog, Yong Seok Lee

Abstract:

Tofurther advance research on immune-related genes from T. molitor, we constructed acDNA library and analyzed expressed sequence taq (EST) sequences from 1,056 clones. After removing vector sequence and quality checkingthrough thePhred program (trim_alt 0.05 (P-score>20), 1039 sequences were generated. The average length of insert was 792 bp. In addition, we identified 162 clusters, 167 contigs and 391 contigs after clustering and assembling process using a TGICL package. EST sequences were searchedagainst NCBI nr database by local BLAST (blastx, EKeywords: EST, Innate immunity, Tenebriomolitor

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Authors: G.K.Panda, S.S.Rout

Abstract:

The balancing numbers are natural numbers n satisfying the Diophantine equation 1 + 2 + 3 + · · · + (n - 1) = (n + 1) + (n + 2) + · · · + (n + r); r is the balancer corresponding to the balancing number n.The nth balancing number is denoted by Bn and the sequence {Bn}1 n=1 satisfies the recurrence relation Bn+1 = 6Bn-Bn-1. The balancing numbers posses some curious properties, some like Fibonacci numbers and some others are more interesting. This paper is a study of recurrent sequence {xn}1 n=1 satisfying the recurrence relation xn+1 = Axn - Bxn-1 and possessing some curious properties like the balancing numbers.

Keywords: Recurrent sequences, Balancing numbers, Lucas balancing numbers, Binet form.

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Authors: M. Kusá, M. Matúšová, A. Javorová, K. Velí

Abstract:

This paper deals about four items assembly process of linear drive. This assembly will be realized in flexible assembly cell on Institute of Manufacturing Systems and Applied Mechanics. There is defined manufacturing cell, individual actuators created our flexible cell. Next chapter is about control type, detailed describe a sequence control type, which will be used in mentioned flexible assembly cell. All cell control is divided in individual steps instructions. There instructions illustrate table number III.

Keywords: assembly, flexible cell, sequence control

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Authors: R. B. Mishra

Abstract:

Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.

Keywords: BDI, HMM, neural activation, optimal states, working conditions.

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