Search results for: automated programming
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1711

Search results for: automated programming

1411 The Comparative Study of Binary Artifact Repository Managers

Authors: Evgeny Chugunnyy, Alena Gerasimova, Kirill Chernyavskiy, Alexander Krasnov

Abstract:

One of the primary component of Continuous deployment (CD) is a binary artifact repository — the place where artifacts are stored with metadata in a structured way. The binary artifact repository manager (BARM) is a software, which implements this repository logic and exposes a public application programming interface (API) for managing these artifacts. Almost every programming language ecosystem has its own artifact repository kind. During creating Artipie — BARM constructor and server, we analyzed and implemented a lot of different artifact repositories. In this paper we present criterias for comparing artifact repositories, and analyze the most popular repositories using these metrics. We also describe some of the notable features of different repositories. This paper aimed to help people who are creating, maintaining or optimizing software repository and CI tools.

Keywords: artifact, repository, continuous deployment, build automation, artifacts management

Procedia PDF Downloads 112
1410 A New Prediction Model for Soil Compression Index

Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

Abstract:

This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

Procedia PDF Downloads 340
1409 A New Reliability Allocation Method Based on Fuzzy Numbers

Authors: Peng Li, Chuanri Li, Tao Li

Abstract:

Reliability allocation is quite important during early design and development stages for a system to apportion its specified reliability goal to subsystems. This paper improves the reliability fuzzy allocation method and gives concrete processes on determining the factor set, the factor weight set, judgment set, and multi-grade fuzzy comprehensive evaluation. To determine the weight of factor set, the modified trapezoidal numbers are proposed to reduce errors caused by subjective factors. To decrease the fuzziness in the fuzzy division, an approximation method based on linear programming is employed. To compute the explicit values of fuzzy numbers, centroid method of defuzzification is considered. An example is provided to illustrate the application of the proposed reliability allocation method based on fuzzy arithmetic.

Keywords: reliability allocation, fuzzy arithmetic, allocation weight, linear programming

Procedia PDF Downloads 306
1408 Leveraging Community Partnerships for Social Impact

Authors: T. Moody, E. Mitchell, T. Dang, A. Barry, T. Proshan, S. Andrisse, V. Odero-Marah

Abstract:

Women’s prison and reentry programs are focused primarily on reducing recidivism but neglect how an individual’s intersecting identities influence their risk of violence and ways that histories of gender-based violence (GBV) must be addressed for these women to recover from traumas. Light To Life (LTL) and From Prison Cells to Ph.D. (P2P) Womxn’s Cohort program recognizes this need; providing national gender-responsive programming (GRP), and trauma-informed programming to justice-impacted survivors through digital resources, leadership opportunities, educational workshops, and healing justice approaches for positive health outcomes. Through the support of a community-university partnership (CUP), a comparative evaluation study is being conducted among intimate-partner violence (IPV) survivors with histories of incarceration who have or have not participated in the cohort. The objectives of the partnership are to provide mutually beneficial training and consultation for evaluating GRP through a rigorously tested research methodology. This collaborative applies a rigorous methodology of semi-structured interviews with an intervention and control group to evaluate the impact of LTL’s programming in the P2P Womxn’s Cohort. The CUP is essential to achieve the expected results of the project. It will measure primary outcomes, including participants' level of engagement and satisfaction with programming, reduction in attitudes that accept violence in relationships, and increase in interpersonal and intrapersonal skills that lead to healthy relationships. This community-based approach will provide opportunities to evaluate the effectiveness of the program. The results addressed in the hypothesis will provide learning lessons to improve this program, to scale it up, and apply it to other similarly affected populations. The partnership experience and anticipated outcomes contribute to the knowledge in women’s health and criminal justice by fostering public awareness on the importance of developing new partnerships and fostering CUP to establish a framework to the leveraging of partnerships for social impact available to academic institutions.

Keywords: Community-university partnership, gender-responsive programming, incarceration, intimate-partner violence, POC, women

Procedia PDF Downloads 36
1407 Positive Bias and Length Bias in Deep Neural Networks for Premises Selection

Authors: Jiaqi Huang, Yuheng Wang

Abstract:

Premises selection, the task of selecting a set of axioms for proving a given conjecture, is a major bottleneck in automated theorem proving. An array of deep-learning-based methods has been established for premises selection, but a perfect performance remains challenging. Our study examines the inaccuracy of deep neural networks in premises selection. Through training network models using encoded conjecture and axiom pairs from the Mizar Mathematical Library, two potential biases are found: the network models classify more premises as necessary than unnecessary, referred to as the ‘positive bias’, and the network models perform better in proving conjectures that paired with more axioms, referred to as ‘length bias’. The ‘positive bias’ and ‘length bias’ discovered could inform the limitation of existing deep neural networks.

Keywords: automated theorem proving, premises selection, deep learning, interpreting deep learning

Procedia PDF Downloads 139
1406 Towards a Complete Automation Feature Recognition System for Sheet Metal Manufacturing

Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

Abstract:

Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

Procedia PDF Downloads 325
1405 "Revolutionizing Geographic Data: CADmapper's Automated Precision in CAD Drawing Transformation"

Authors: Toleen Alaqqad, Kadi Alshabramiy, Suad Zaafarany, Basma Musallam

Abstract:

CADmapper is a significant tool of software for transforming geographic data into realistic CAD drawings. It speeds up and simplifies the conversion process by automating it. This allows architects, urban planners, engineers, and geographic information system (GIS) experts to solely concentrate on the imaginative and scientific parts of their projects. While the future incorporation of AI has the potential for further improvements, CADmapper's current capabilities make it an indispensable asset in the business. It covers a combination of 2D and 3D city and urban area models. The user can select a specific square section of the map to view, and the fee is based on the dimensions of the area being viewed. The procedure is straightforward: you choose the area you want, then pick whether or not to include topography. 3D architectural data (if available), followed by selecting whatever design program or CAD style you want to publish the document which contains more than 200 free broad town plans in DXF format. If you desire to specify a bespoke area, it's free up to 1 km2.

Keywords: cadmaper, gdata, 2d and 3d data conversion, automated cad drawing, urban planning software

Procedia PDF Downloads 33
1404 Metal Ship and Robotic Car: A Hands-On Activity to Develop Scientific and Engineering Skills for High School Students

Authors: Jutharat Sunprasert, Ekapong Hirunsirisawat, Narongrit Waraporn, Somporn Peansukmanee

Abstract:

Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.

Keywords: hands-on activity, STEM education, computer programming, metal work

Procedia PDF Downloads 435
1403 Binary Programming for Manufacturing Material and Manufacturing Process Selection Using Genetic Algorithms

Authors: Saleem Z. Ramadan

Abstract:

The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: optimization, material selection, process selection, genetic algorithm

Procedia PDF Downloads 384
1402 A New Mathematical Model for Scheduling Preventive Maintenance and Renewal Projects of Multi-Unit Systems; Application to Railway Track

Authors: Farzad Pargar

Abstract:

We introduce the preventive maintenance and renewal scheduling problem for a multi-unit system over a finite and discretized time horizon. Given the latest possible time for carrying out the next maintenance and renewal projects after the previous ones and considering several common set-up costs, the introduced scheduling model tries to minimize the cost of projects by grouping them and simultaneously finding the optimal balance between doing maintenance and renewal. We present a 0-1 pure integer linear programming that determines which projects should be performed together on which location and in which period (e.g., week or month). We consider railway track as a case for our study and test the performance of the proposed model on a set of test problems. The experimental results show that the proposed approach performs well.

Keywords: maintenance, renewal, scheduling, mathematical programming model

Procedia PDF Downloads 663
1401 The Impact of Transaction Costs on Rebalancing an Investment Portfolio in Portfolio Optimization

Authors: B. Marasović, S. Pivac, S. V. Vukasović

Abstract:

Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.

Keywords: Croatian capital market, Markowitz model, fractional quadratic programming, portfolio optimization, transaction costs

Procedia PDF Downloads 354
1400 A Stepwise Approach to Automate the Search for Optimal Parameters in Seasonal ARIMA Models

Authors: Manisha Mukherjee, Diptarka Saha

Abstract:

Reliable forecasts of univariate time series data are often necessary for several contexts. ARIMA models are quite popular among practitioners in this regard. Hence, choosing correct parameter values for ARIMA is a challenging yet imperative task. Thus, a stepwise algorithm is introduced to provide automatic and robust estimates for parameters (p; d; q)(P; D; Q) used in seasonal ARIMA models. This process is focused on improvising the overall quality of the estimates, and it alleviates the problems induced due to the unidimensional nature of the methods that are currently used such as auto.arima. The fast and automated search of parameter space also ensures reliable estimates of the parameters that possess several desirable qualities, consequently, resulting in higher test accuracy especially in the cases of noisy data. After vigorous testing on real as well as simulated data, the algorithm doesn’t only perform better than current state-of-the-art methods, it also completely obviates the need for human intervention due to its automated nature.

Keywords: time series, ARIMA, auto.arima, ARIMA parameters, forecast, R function

Procedia PDF Downloads 130
1399 Altasreef: Automated System of Quran Verbs for Urdu Language

Authors: Haq Nawaz, Muhammad Amjad Iqbal, Kamran Malik

Abstract:

"Altasreef" is an automated system available for Web and Android users which provide facility to the users to learn the Quran verbs. It provides the facility to the users to practice the learned material and also provide facility of exams of Arabic verbs variation focusing on Quran text. Arabic is a highly inflectional language. Almost all of its words connect to roots of three, four or five letters which approach the meaning of all their inflectional forms. In Arabic, a verb is formed by inserting the consonants into one of a set of verb patterns. Suffixes and prefixes are then added to generate the meaning of number, person, and gender. The active/passive voice and perfective aspect and other patterns are than generated. This application is designed for learners of Quranic Arabic who already have learn basics of Arabic conjugation. Application also provides the facility of translation of generated patterns. These translations are generated with the help of rule-based approach to give 100% results to the learners.

Keywords: NLP, Quran, Computational Linguistics, E Learning

Procedia PDF Downloads 131
1398 Barriers and Facilitators to Inclusive Programming for Children with Mental and/or Developmental Challenges: A Participatory Action Research of Perspectives from Families and Professionals

Authors: Minnie Y. Teng, Kathy Xie, Jarus Tal

Abstract:

Rationale: The traditional approach to community programs for children with mental and/or developmental challenges often involves segregation from typically-developing peers. However, studies show that inclusive education improves children’s quality of life, self-concept, and long term health outcomes. Investigating factors that influence inclusion can thus have important implications in the design and facilitation of community programs such that all children - across a spectrum of needs and abilities - may benefit. Objectives: This study explores barriers and facilitators to inclusive community programming for children aged 0 to 12 with developmental/mental challenges. Methods: Using a participatory-action research methodology, semi-structured focus groups and interviews will be used to explore perspectives of sighted students, instructors, and staff. Data will be transcribed and coded thematically. Practice Implications or Results: By having a deeper understanding of the barriers and facilitators to inclusive programming in the community, researchers can work with the broader community to facilitate inclusion in children’s community programs. Conclusions: Expanding inclusive practices may improve the health and wellbeing of the pediatric populations with disabilities, which consistently reports lower levels of participation. These findings may help to identify gaps in existing practices and ways to approach them.

Keywords: aquatic programs, children, disabilities, inclusion, community programs

Procedia PDF Downloads 88
1397 Automated Prepaid Billing Subscription System

Authors: Adekunle K. O, Adeniyi A. E, Kolawole E

Abstract:

One of the most dramatic trends in the communications market in recent years has been the growth of prepaid services. Today, prepaid no longer constitutes the low-revenue, basic-service segment. It is driven by a high margin, value-add service customers who view it as a convenient way of retaining control over their usage and communication spending while expecting high service levels. To service providers, prepaid services offer the advantage of reducing bad accounts while allowing them to predict usage and plan network resources. Yet, the real-time demands of prepaid services require a scalable, real-time platform to manage customers through their entire life cycle. It delivers integrated real-time rating, voucher management, recharge management, customer care and service provisioning for the generation of new prepaid services. It carries high scalability that can handle millions of prepaid customers in real-time through their entire life cycle.

Keywords: prepaid billing, voucher management, customers, automated, security

Procedia PDF Downloads 83
1396 Finite Dynamic Programming to Decision Making in the Use of Industrial Residual Water Treatment Plants

Authors: Oscar Vega Camacho, Andrea Vargas, Ellery Ariza

Abstract:

This paper presents the application of finite dynamic programming, specifically the "Markov Chain" model, as part of the decision making process of a company in the cosmetics sector located in the vicinity of Bogota DC. The objective of this process was to decide whether the company should completely reconstruct its waste water treatment plant or instead optimize the plant through the addition of equipment. The goal of both of these options was to make the required improvements in order to comply with parameters established by national legislation regarding the treatment of waste before it is released into the environment. This technique will allow the company to select the best option and implement a solution for the processing of waste to minimize environmental damage and the acquisition and implementation costs.

Keywords: decision making, markov chain, optimization, waste water

Procedia PDF Downloads 381
1395 Development and Implementation of Curvature Dependent Force Correction Algorithm for the Planning of Forced Controlled Robotic Grinding

Authors: Aiman Alshare, Sahar Qaadan

Abstract:

A curvature dependent force correction algorithm for planning force controlled grinding process with off-line programming flexibility is designed for ABB industrial robot, in order to avoid the manual interface during the process. The machining path utilizes a spline curve fit that is constructed from the CAD data of the workpiece. The fitted spline has a continuity of the second order to assure path smoothness. The implemented algorithm computes uniform forces normal to the grinding surface of the workpiece, by constructing a curvature path in the spatial coordinates using the spline method.

Keywords: ABB industrial robot, grinding process, offline programming, CAD data extraction, force correction algorithm

Procedia PDF Downloads 335
1394 A Reactive Flexible Job Shop Scheduling Model in a Stochastic Environment

Authors: Majid Khalili, Hamed Tayebi

Abstract:

This paper considers a stochastic flexible job-shop scheduling (SFJSS) problem in the presence of production disruptions, and reactive scheduling is implemented in order to find the optimal solution under uncertainty. In this problem, there are two main disruptions including machine failure which influences operation time, and modification or cancellation of the order delivery date during production. In order to decrease the negative effects of these difficulties, two derived strategies from reactive scheduling are used; the first one is relevant to being able to allocate multiple machine to each job, and the other one is related to being able to select the best alternative process from other job while some disruptions would be created in the processes of a job. For this purpose, a Mixed Integer Linear Programming model is proposed.

Keywords: flexible job-shop scheduling, reactive scheduling, stochastic environment, mixed integer linear programming

Procedia PDF Downloads 333
1393 Automated Parking System

Authors: N. Arunraj, C. P. V. Paul, D. M. D. Jayawardena, W. N. D. Fernando

Abstract:

Traffic congestion with increased numbers of vehicles is already a serious issue for many countries. The absence of sufficient parking spaces adds to the issue. Motorists are forced to wait in long queues to park their vehicles. This adds to the inconvenience faced by a motorist, kept waiting for a slot allocation, manually done along with the parking payment calculation. In Sri Lanka, nowadays, parking systems use barcode technology to identify the vehicles at both the entrance and the exit points. Customer management is handled by the use of man power. A parking space is, generally permanently sub divided according to the vehicle type. Here, again, is an issue. Parking spaces are not utilized to the maximum. The current arrangement leaves room for unutilized parking spaces. Accordingly, there is a need to manage the parking space dynamically. As a vehicle enters the parking area, available space has to be assigned for the vehicle according to the vehicle type. The system, Automated Parking System (APS), provides an automated solution using RFID Technology to identify the vehicles. Simultaneously, an algorithm manages the space allocation dynamically. With this system, there is no permanent parking slot allocation for a vehicle type. A desktop application manages the customer. A Web application is used to manage the external users with their reservations. The system also has an android application to view the nearest parking area from the current location. APS is built using java and php. It uses LED panels to guide the user inside the parking area to find the allocated parking slot accurately. The system ensures efficient performance, saving precious time for a customer. Compared with the current parking systems, APS interacts with users and increases customer satisfaction as well.

Keywords: RFID, android, web based system, barcode, algorithm, LED panels

Procedia PDF Downloads 576
1392 Functional and Efficient Query Interpreters: Principle, Application and Performances’ Comparison

Authors: Laurent Thiry, Michel Hassenforder

Abstract:

This paper presents a general approach to implement efficient queries’ interpreters in a functional programming language. Indeed, most of the standard tools actually available use an imperative and/or object-oriented language for the implementation (e.g. Java for Jena-Fuseki) but other paradigms are possible with, maybe, better performances. To proceed, the paper first explains how to model data structures and queries in a functional point of view. Then, it proposes a general methodology to get performances (i.e. number of computation steps to answer a query) then it explains how to integrate some optimization techniques (short-cut fusion and, more important, data transformations). It then compares the functional server proposed to a standard tool (Fuseki) demonstrating that the first one can be twice to ten times faster to answer queries.

Keywords: data transformation, functional programming, information server, optimization

Procedia PDF Downloads 126
1391 Production Planning for Animal Food Industry under Demand Uncertainty

Authors: Pirom Thangchitpianpol, Suttipong Jumroonrut

Abstract:

This research investigates the distribution of food demand for animal food and the optimum amount of that food production at minimum cost. The data consist of customer purchase orders for the food of laying hens, price of food for laying hens, cost per unit for the food inventory, cost related to food of laying hens in which the food is out of stock, such as fine, overtime, urgent purchase for material. They were collected from January, 1990 to December, 2013 from a factory in Nakhonratchasima province. The collected data are analyzed in order to explore the distribution of the monthly food demand for the laying hens and to see the rate of inventory per unit. The results are used in a stochastic linear programming model for aggregate planning in which the optimum production or minimum cost could be obtained. Programming algorithms in MATLAB and tools in Linprog software are used to get the solution. The distribution of the food demand for laying hens and the random numbers are used in the model. The study shows that the distribution of monthly food demand for laying has a normal distribution, the monthly average amount (unit: 30 kg) of production from January to December. The minimum total cost average for 12 months is Baht 62,329,181.77. Therefore, the production planning can reduce the cost by 14.64% from real cost.

Keywords: animal food, stochastic linear programming, aggregate planning, production planning, demand uncertainty

Procedia PDF Downloads 353
1390 Automated Detection of Women Dehumanization in English Text

Authors: Maha Wiss, Wael Khreich

Abstract:

Animals, objects, foods, plants, and other non-human terms are commonly used as a source of metaphors to describe females in formal and slang language. Comparing women to non-human items not only reflects cultural views that might conceptualize women as subordinates or in a lower position than humans, yet it conveys this degradation to the listeners. Moreover, the dehumanizing representation of females in the language normalizes the derogation and even encourages sexism and aggressiveness against women. Although dehumanization has been a popular research topic for decades, according to our knowledge, no studies have linked women's dehumanizing language to the machine learning field. Therefore, we introduce our research work as one of the first attempts to create a tool for the automated detection of the dehumanizing depiction of females in English texts. We also present the first labeled dataset on the charted topic, which is used for training supervised machine learning algorithms to build an accurate classification model. The importance of this work is that it accomplishes the first step toward mitigating dehumanizing language against females.

Keywords: gender bias, machine learning, NLP, women dehumanization

Procedia PDF Downloads 55
1389 Design Off-Campus Interactive Cloud-Based Learning Model

Authors: Osamah Al Qadoori

Abstract:

Using cloud computing in educational sectors grow rapidly in UAE. Initially, within Cloud-Learning Environment Students whenever and wherever can remotely join the online-classroom, on the other hand, Cloud-Based Learning is greatly decreasing the infrastructure and the maintenance cost. Nowadays in many schools (K-12), institutes, colleges as well as universities in UAE Cloud-Based Teaching and Learning environments gain a higher demand and concern. Many students don’t use the available online-educational resources effectively. The challenging question is to which extend these educational resources which are installed in the cloud environment are valuable and constructive? In this paper the researcher is seeking to design an expert agent prototype where the huge information being accommodated inside the cloud environment will go through expert filtration before going to be utilized by other clients (students). To achieve this goal, the focus of the present research would be on two different directions the educational human expertise and the automated-educational expert systems.

Keywords: cloud computing, cloud-learning environment, online-classroom, the educational human expertise, the automated-educational expert systems

Procedia PDF Downloads 515
1388 The Human Process of Trust in Automated Decisions and Algorithmic Explainability as a Fundamental Right in the Exercise of Brazilian Citizenship

Authors: Paloma Mendes Saldanha

Abstract:

Access to information is a prerequisite for democracy while also guiding the material construction of fundamental rights. The exercise of citizenship requires knowing, understanding, questioning, advocating for, and securing rights and responsibilities. In other words, it goes beyond mere active electoral participation and materializes through awareness and the struggle for rights and responsibilities in the various spaces occupied by the population in their daily lives. In times of hyper-cultural connectivity, active citizenship is shaped through ethical trust processes, most often established between humans and algorithms. Automated decisions, so prevalent in various everyday situations, such as purchase preference predictions, virtual voice assistants, reduction of accidents in autonomous vehicles, content removal, resume selection, etc., have already found their place as a normalized discourse that sometimes does not reveal or make clear what violations of fundamental rights may occur when algorithmic explainability is lacking. In other words, technological and market development promotes a normalization for the use of automated decisions while silencing possible restrictions and/or breaches of rights through a culturally modeled, unethical, and unexplained trust process, which hinders the possibility of the right to a healthy, transparent, and complete exercise of citizenship. In this context, the article aims to identify the violations caused by the absence of algorithmic explainability in the exercise of citizenship through the construction of an unethical and silent trust process between humans and algorithms in automated decisions. As a result, it is expected to find violations of constitutionally protected rights such as privacy, data protection, and transparency, as well as the stipulation of algorithmic explainability as a fundamental right in the exercise of Brazilian citizenship in the era of virtualization, facing a threefold foundation called trust: culture, rules, and systems. To do so, the author will use a bibliographic review in the legal and information technology fields, as well as the analysis of legal and official documents, including national documents such as the Brazilian Federal Constitution, as well as international guidelines and resolutions that address the topic in a specific and necessary manner for appropriate regulation based on a sustainable trust process for a hyperconnected world.

Keywords: artificial intelligence, ethics, citizenship, trust

Procedia PDF Downloads 31
1387 Automated Buffer Box Assembly Cell Concept for the Canadian Used Fuel Packing Plant

Authors: Dimitrie Marinceu, Alan Murchison

Abstract:

The Canadian Used Fuel Container (UFC) is a mid-size hemispherical headed copper coated steel container measuring 2.5 meters in length and 0.5 meters in diameter containing 48 used fuel bundles. The contained used fuel produces significant gamma radiation requiring automated assembly processes to complete the assembly. The design throughput of 2,500 UFCs per year places constraints on equipment and hot cell design for repeatability, speed of processing, robustness and recovery from upset conditions. After UFC assembly, the UFC is inserted into a Buffer Box (BB). The BB is made from adequately pre-shaped blocks (lower and upper block) and Highly Compacted Bentonite (HCB) material. The blocks are practically ‘sandwiching’ the UFC between them after assembly. This paper identifies one possible approach for the BB automatic assembly cell and processes. Automation of the BB assembly will have a significant positive impact on nuclear safety, quality, productivity, and reliability.

Keywords: used fuel packing plant, automatic assembly cell, used fuel container, buffer box, deep geological repository

Procedia PDF Downloads 249
1386 Finding Data Envelopment Analysis Target Using the Multiple Objective Linear Programming Structure in Full Fuzzy Case

Authors: Raziyeh Shamsi

Abstract:

In this paper, we present a multiple objective linear programming (MOLP) problem in full fuzzy case and find Data Envelopment Analysis(DEA) targets. In the presented model, we are seeking the least inputs and the most outputs in the production possibility set (PPS) with the variable return to scale (VRS) assumption, so that the efficiency projection is obtained for all decision making units (DMUs). Then, we provide an algorithm for finding DEA targets interactively in the full fuzzy case, which solves the full fuzzy problem without defuzzification. Owing to the use of interactive methods, the targets obtained by our algorithm are more applicable, more realistic, and they are according to the wish of the decision maker. Finally, an application of the algorithm in 21 educational institutions is provided.

Keywords: DEA, MOLP, full fuzzy, target

Procedia PDF Downloads 278
1385 Application of Finite Dynamic Programming to Decision Making in the Use of Industrial Residual Water Treatment Plants

Authors: Oscar Vega Camacho, Andrea Vargas Guevara, Ellery Rowina Ariza

Abstract:

This paper presents the application of finite dynamic programming, specifically the "Markov Chain" model, as part of the decision making process of a company in the cosmetics sector located in the vicinity of Bogota DC. The objective of this process was to decide whether the company should completely reconstruct its wastewater treatment plant or instead optimize the plant through the addition of equipment. The goal of both of these options was to make the required improvements in order to comply with parameters established by national legislation regarding the treatment of waste before it is released into the environment. This technique will allow the company to select the best option and implement a solution for the processing of waste to minimize environmental damage and the acquisition and implementation costs.

Keywords: decision making, Markov chain, optimization, wastewater

Procedia PDF Downloads 460
1384 A Robust Optimization for Multi-Period Lost-Sales Inventory Control Problem

Authors: Shunichi Ohmori, Sirawadee Arunyanart, Kazuho Yoshimoto

Abstract:

We consider a periodic review inventory control problem of minimizing production cost, inventory cost, and lost-sales under demand uncertainty, in which product demands are not specified exactly and it is only known to belong to a given uncertainty set, yet the constraints must hold for possible values of the data from the uncertainty set. We propose a robust optimization formulation for obtaining lowest cost possible and guaranteeing the feasibility with respect to range of order quantity and inventory level under demand uncertainty. Our formulation is based on the adaptive robust counterpart, which suppose order quantity is affine function of past demands. We derive certainty equivalent problem via second-order cone programming, which gives 'not too pessimistic' worst-case.

Keywords: robust optimization, inventory control, supply chain managment, second-order programming

Procedia PDF Downloads 379
1383 A Robotic “Puppet Master” Application to ASD Therapeutic Support

Authors: Sophie Sakka, Rénald Gaboriau

Abstract:

This paper describes a preliminary work aimed at setting a therapeutic support for autistic teenagers using three humanoid robots NAO shared by ASD (Autism Spectrum Disorder) subjects. The studied population had attended successfully a first year program, and were observed with a second year program using the robots. This paper focuses on the content and the effects of the second year program. The approach is based on a master puppet concept: the subjects program the robots, and use them as an extension for communication. Twenty sessions were organized, alternating ten preparatory sessions and ten robotics programming sessions. During the preparatory sessions, the subjects write a story to be played by the robots. During the robot programming sessions, the subjects program the motions to be realized to make the robot tell the story. The program was concluded by a public performance. The experiment involves five ASD teenagers aged 12-15, who had all attended the first year robotics training. As a result, a progress in voluntary and organized communication skills of the five subjects was observed, leading to improvements in social organization, focus, voluntary communication, programming, reading and writing abilities. The changes observed in the subjects general behavior took place in a short time, and could be observed from one robotics session to the next one. The approach allowed the subjects to draw the limits of their body with respect to the environment, and therefore helped them confronting the world with less anxiety.

Keywords: autism spectrum disorder, robot, therapeutic support, rob'autism

Procedia PDF Downloads 224
1382 Optimal Maintenance and Improvement Policies in Water Distribution System: Markov Decision Process Approach

Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee

Abstract:

The Markov Decision Process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.

Keywords: Markov decision processes, dynamic programming, Monte Carlo simulation, periodic replacement, Weibull distribution

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