{"title":"An Optimal Integrated Maintenance to production with Carbon Emission for a Closed-loop System","authors":"S. Bouslikhane, Z. Hajej, N. Rezg","doi":"10.1109/CoDIT.2018.8394895","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394895","url":null,"abstract":"An optimal integrated maintenance to production under carbon emission constraint is developed for a closed-loop system. The closed-loop system is composed by a principal unit producing a single type of product and a second unit for remanufacturing the returned products. The two units are subject to random failures. An economical production policy and a maintenance strategy under carbon emission constraint are proposed to minimize the total cost of production, emission and maintenance. Taking into account the correlation of the manufacturing unit degradation with its production rates and the given maintenance plan of the remanufacturing unit, we determine the economical production plans of both units as well as the emission carbon quantities and the optimal plan of maintenance for the principal manufacturing unit.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131811902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Decision tree and Parametrized classifier for Estimating occupancy in energy management","authors":"Manar Amayri, S. Ploix","doi":"10.1109/CoDIT.2018.8394848","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394848","url":null,"abstract":"A new kind of supervised learning approach is proposed to determine the number of occupants in a room in order to use these estimate for improved energy management. It introduces the concept of Parametrized classifier. It relies on the predetermined structure of supervised learning classifiers, where any classifier could be used to evaluate this approach. The parameters will be adjusted according to the incoming data sensors (i.e CO2 concentration, acoustic pressure, …) using a tuning mechanism depends on an optimization process. This paper provides different supervised learning methods (i.e decision tree random forest) to determine the required structure in order to be used in parametrized classifier approach. The structure of decision tree has been chosen which represents the classification rules and limit the depth of the tree to facilitate the generalization process. In order to evaluate the generalization possibilities of a supervised learning approach (i.e. decision tree), it has been chosen to extrapolate results from office H358 to another similar office H355. The knowledge has been extracted from a decision tree built on H358 office then applied and tuned for H355 using parameterized classifier approach. Moreover, experiments implement occupancy estimations and hot water productions control show that energy efficiency can be increased by about 6% over known optimal control techniques and more than 26% over rule-based control besides maintaining the occupant comfort standards. The building efficiency gain is strongly connected with the occupancy estimation accuracy.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126169376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Minimum flows in directed s-t planar networks with arcs and nodes capacities","authors":"E. Ciurea, Oana Georgescu, Camelia Schiopu","doi":"10.1109/CoDIT.2018.8394790","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394790","url":null,"abstract":"We present an algorithm for finding maximum cut and an algorithm for finding minimum flow in directed s-t planar networks with arcs and nodes capacities. As a final part, we present an example for these two algorithms.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126209316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Genetic Algorithm for Open Shop Scheduling Problem","authors":"Yacine Benziani, I. Kacem, Pierre Laroche","doi":"10.1109/CoDIT.2018.8394932","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394932","url":null,"abstract":"In this paper, we present a genetic algorithm for the open shop scheduling problem. We use a simple and efficient chromosome representation based on the job's occurrence and the fitness function reflect the length of the schedule. The solutions obtained after performing the different operators of the genetic algorithm are always feasible. Heuristic approaches are also developed to generate the initial population and to improve the obtained solutions. The algorithm was implemented and computational results show interesting result.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129966298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The MANTIS Architecture for Proactive Maintenance","authors":"Csaba Hegedüs, P. Varga, I. Moldován","doi":"10.1109/CoDIT.2018.8394904","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394904","url":null,"abstract":"Data collection, processing and visualization techniques has been going through a rapid evolution in recent years. Various applications utilize these new results; especially combined. Parallel to this, there are new developments within the Cyber-Physical Systems (CPS) domain. Beside the main purpose of CPS - getting physical systems serve to work better, faster, more optimized -, the concept can improve the long-term usability of the physical equipment, as well. The principles of proactive maintenance are rooted from the need of short-term fault correction and long-term usability. The idea is to track system status not only for operations but for maintenance purpose as well. This allows for scheduling maintenance based on need - rather than based on operating time or “mileage”. This paper presents the MANTIS framework for proactive maintenance. It utilizes CPS concepts for system modeling, furthermore, it proposes a combined tool set for data collection, processing and presentation. In order to cover the full value chain, the framework applies for all the three Tiers: the Edge, the Platform, and the Enterprise, as well.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122783865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-Dynamics Analysis of QRS Complex for Atrial Fibrillation Diagnosis","authors":"Youssef Trardi, B. Ananou, Z. Haddi, M. Ouladsine","doi":"10.1109/CoDIT.2018.8394935","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394935","url":null,"abstract":"This paper presents an effective atrial fibrillation (AF) diagnosis algorithm based on multi-dynamics analysis of QRS complex. The idea behind this approach is to produce a variety of heartbeat time series features employing several linear and nonlinear functions via different dynamics of the QRS complex signal. These extracted features from these dynamics will be connected through machine learning based algorithms such as Support Vector Machine (SVM) and Multiple Kernel Learning (MKL), to detect AF episode occurrences. The reported performances of these methods were evaluated on the Long-Term AF Database which includes 84 of 24-hour ECG recording. Thereafter, each record was divided into consecutive intervals of one-minute segments to feed the classifier models. The obtained sensitivity, specificity and positive classification using SVM were 96.54%, 99.69%, and 99.62%, respectively, and for MKL they reached 95.47%, 99.89%, and 99.87%, respectively. Therefore, these medical-oriented detectors can be clinically valuable to healthcare professional for screening AF pathology.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123965680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A method for automated generation of inference rules","authors":"S. Gorshkov","doi":"10.1109/CoDIT.2018.8394808","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394808","url":null,"abstract":"The safety-related decision making support systems requires provability of each proposed decision, which makes OWL-based inference rules a good choice as an inference technology. However, the manual composition of a large amount of inference rules is a complex and resource intensive task. This article offers a method for automation of inference rules construction, based on analysis of the decisions made by the experts in particular situations. The method allows reproducing the logic that lays behind the expert's decisions. The tic-tac-toe game strategy analysis is used to evaluate the method.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124425309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"PNeS: Tools for the Design and Analysis Petri Nets","authors":"Z. Suraj","doi":"10.1109/CoDIT.2018.8394909","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394909","url":null,"abstract":"Petri net is a strong mathematical modeling language that can be used to represent parallel or concurrent activities in a system. The practical use of Petri nets is strongly dependent upon the existence of adequate computer tools. For Petri nets one needs editors as well as analysis programs. Modern computers provide an opportunity to work directly with the graphical representations of Petri nets. This paper describes integrated graphical Petri net tools called PNeS for construction of nets, as well as modification and analysis. PNeS allows us to work with different classes of Petri nets. Several analysis tools are available for each of these classes. PNeS works on any computer under any operating system.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132200335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vinicius C. Oliveira, Souad Rabah, H. Coppier, M. Chadli, Didier Escalon
{"title":"Preliminary Study of Numerical Corrector for a Bubbling Fluidized Bed Incinerator","authors":"Vinicius C. Oliveira, Souad Rabah, H. Coppier, M. Chadli, Didier Escalon","doi":"10.1109/CoDIT.2018.8394787","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394787","url":null,"abstract":"The establishment of recent laws regarding wastewater treatment has made the treatment of sewage sludge in incineration processes even more complex. In an attempt to follow this new environmental legislation, SIAAP optimizes its wastewater treatment by using a bubbling fluidized-bed incinerator technique. Its PID control system does not ensure an appropriate operation of incineration due to the complexity of the incinerator structure, what can lead the system into a dangerous behavior. Thus, a predictive control system is required in order to foresee any deviation from incineration behavior. The predictive control allows the incineration system to prevent itself from risky situations by acting in advance. This paper describes a preliminary methodology to obtain a predictive-control numerical corrector. This corrector forecasts the future outputs of a PID-controlled incineration model via Matlab/Simulink simulations and operates the system closed-loop feedback so as to avoid system instabilities.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128058708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dong Ji, Jun Yu, T. Kurihara, Liangfeng Xu, Shu Zhan
{"title":"Automatic Prostate Segmentation on MR Images with Deeply Supervised Network","authors":"Dong Ji, Jun Yu, T. Kurihara, Liangfeng Xu, Shu Zhan","doi":"10.1109/CoDIT.2018.8394836","DOIUrl":"https://doi.org/10.1109/CoDIT.2018.8394836","url":null,"abstract":"Accurate and efficient segmentation of prostate image plays an important role in the diagnosis of prostate cancer. Since convolutional neural network demonstrates superior performance in computer vision applications, we present a multi-layer deeply supervised deconvolution network (DSDN) which completes end-to-end training to automatically segment magnetic resonance (MR) images. We put additional deeply supervised layers to supervise the performance of hidden layers. During training, the backpropagation process of gradient information in the additional deeply supervised layers accelerates the parameters update for hidden layers, which makes the trained model has strong capacity of features learning as well as passes the extracted features from shallow layers to higher layers effectively. A set of experiments using prostate magnetic resonance (MR) images is carried out to demonstrate that significant segmentation accuracy improvement has been achieved by our proposed method compared to other reported approaches.","PeriodicalId":128011,"journal":{"name":"2018 5th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116373367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}