Search results for: labeling automation

Authors: Nan Xu

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In airlines, the crew scheduling problem is usually decomposed into two stages: crew pairing and crew rostering. In the crew pairing stage, pairings are generated such that each flight is covered by exactly one pairing and the overall cost is minimized. In the crew rostering stage, the pairings generated in the crew pairing stage are combined with off days, training and other breaks to create individual work schedules. The paper focuses on cabin crew rostering problem, which is challenging due to the extremely large size and the complex working rules involved. In our approach, the objective of rostering consists of two major components. The first is to minimize the number of unassigned pairings and the second is to ensure the fairness to crew members. There are two measures of fairness to crew members, the number of overnight duties and the total fly-hour over a given period. Pairings should be assigned to each crew member so that their actual overnight duties and fly hours are as close to the expected average as possible. Deviations from the expected average are penalized in the objective function. Since several small deviations are preferred than a large deviation, the penalization is quadratic. Our model of the airline crew rostering problem is based on column generation. The problem is decomposed into a master problem and subproblems. The mater problem is modeled as a set partition problem and exactly one roster for each crew is picked up such that the pairings are covered. The restricted linear master problem (RLMP) is considered. The current subproblem tries to find columns with negative reduced costs and add them to the RLMP for the next iteration. When no column with negative reduced cost can be found or a stop criteria is met, the procedure ends. The subproblem is to generate feasible crew rosters for each crew member. A separate acyclic weighted graph is constructed for each crew member and the subproblem is modeled as resource constrained shortest path problems in the graph. Labeling algorithm is used to solve it. Since the penalization is quadratic, a method to deal with non-additive shortest path problem using labeling algorithm is proposed and corresponding domination condition is defined. The major contribution of our model is: 1) We propose a method to deal with non-additive shortest path problem; 2) Operation to allow relaxing some soft rules is allowed in our algorithm, which can improve the coverage rate; 3) Multi-thread techniques are used to improve the efficiency of the algorithm when generating Line-of-Work for crew members. Here a column generation based algorithm for the airline cabin crew rostering problem is proposed. The objective is to assign a personalized roster to crew member which minimize the number of unassigned pairings and ensure the fairness to crew members. The algorithm we propose in this paper has been put into production in a major airline in China and numerical experiments show that it has a good performance.

Keywords: aircrew rostering, aircrew scheduling, column generation, SPPRC

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Authors: Serzhan Ashirov, Dana Nour, Rafat Rob, Khaled Alotaibi

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There has been a fast growth in the introduction and use of communications, information, monitoring, and sensing technologies. The new technologies are making their way to the Industrial Control Systems as embedded in products, software applications, IT services, or commissioned to enable integration and automation of increasingly global supply chains. As a result, the lines that separated the physical, digital, and cyber world have diminished due to the vast implementation of the new, disruptive digital technologies. The variety and increased use of these technologies introduce many cybersecurity risks affecting cyber-resilience of the supply chain, both in terms of the product or service delivered to a customer and members of the supply chain operation. US department of energy considers supply chain in the IR4 space to be the weakest link in cybersecurity. The IR4 identified the digitization of the field devices, followed by digitalization that eventually moved through the digital transformation space with little care for the new introduced cybersecurity risks. This paper will examine the best methodologies for securing the electrical substations from cybersecurity attacks due to supply chain risks, and due to digitization effort. SCADA systems are the most vulnerable part of the power system infrastructure due to digitization and due to the weakness and vulnerabilities in the supply chain security. The paper will discuss in details how create a secure supply chain methodology, secure substations, and mitigate the risks due to digitization

Keywords: cybersecurity, supply chain methodology, secure substation, digitization

Procedia PDF Downloads 43

Authors: Nemanja Kajtez, Yue Zhan, Basel Halak

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The significant rise in the cost of manufacturing of nanoscale integrated circuits (IC) has led the majority of IC design companies to outsource the fabrication of their products to other companies, often located in different countries. This multinational nature of the hardware supply chain has led to a host of security threats, including IP piracy, IC overproduction, and Trojan insertion. To combat that, researchers have proposed logic locking techniques to protect the intellectual properties of the design and increase the difficulty of malicious modification of its functionality. However, the adoption of logic locking approaches is rather slow due to the lack of the integration with IC production process and the lack of efficacy of existing algorithms. This work automates the logic locking process by developing software using Python that performs the locking on a gate-level netlist and can be integrated with the existing digital synthesis tools. Analysis of the latest logic locking algorithms has demonstrated that the SFLL-HD algorithm is one of the most secure and versatile in trading-off levels of protection against different types of attacks and was thus selected for implementation. The presented tool can also be expanded to incorporate the latest locking mechanisms to keep up with the fast-paced development in this field. The paper also presents a case study to demonstrate the functionality of the tool and how it could be used to explore the design space and compare different locking solutions. The source code of this tool is available freely from (https://www.researchgate.net/publication/353195333_Source_Code_for_The_Lockit_Tool).

Keywords: design automation, hardware security, IP piracy, logic locking

Procedia PDF Downloads 155

Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Julia Huggins, Fabien Munyaneza

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Background: Partners In Health – Malawi introduced one of Operational Researches called Primary Health Care (PHC) Surveys in 2020, which seeks to assess progress of delivery of care in the district. The study consists of 5 long surveys, namely; Facility assessment, General Patient, Provider, Sick Child, Antenatal Care (ANC), primarily conducted in 4 health facilities in Neno district. These facilities include Neno district hospital, Dambe health centre, Chifunga and Matope. Usually, these annual surveys are conducted from January, and the target is to present final report by June. Once data is collected and analyzed, there are a series of reviews that take place before reaching final report. In the first place, the manual process took over 9 months to present final report. Initial findings reported about 76.9% of the data that added up when cross-checked with paper-based sources. Purpose: The aim of this approach is to run away from manually pulling the data, do fresh analysis, and reporting often associated not only with delays in reporting inconsistencies but also with poor quality of data if not done carefully. This automation approach was meant to utilize features of new technologies to create visualizations, reports, and dashboards in Power BI that are directly fished from the data source – CommCare hence only require a single click of a ‘refresh’ button to have the updated information populated in visualizations, reports, and dashboards at once. Methodology: We transformed paper-based questionnaires into electronic using CommCare mobile application. We further connected CommCare Mobile App directly to Power BI using Application Program Interface (API) connection as data pipeline. This provided chance to create visualizations, reports, and dashboards in Power BI. Contrary to the process of manually collecting data in paper-based questionnaires, entering them in ordinary spreadsheets, and conducting analysis every time when preparing for reporting, the team utilized CommCare and Microsoft Power BI technologies. We utilized validations and logics in CommCare to capture data with less errors. We utilized Power BI features to host the reports online by publishing them as cloud-computing process. We switched from sharing ordinary report files to sharing the link to potential recipients hence giving them freedom to dig deep into extra findings within Power BI dashboards and also freedom to export to any formats of their choice. Results: This data automation approach reduced research timelines from the initial 9 months’ duration to 5. It also improved the quality of the data findings from the original 76.9% to 98.9%. This brought confidence to draw conclusions from the findings that help in decision-making and gave opportunities for further researches. Conclusion: These results suggest that automating the research data process has the potential of reducing overall amount of time spent and improving the quality of the data. On this basis, the concept of data automation should be taken into serious consideration when conducting operational research for efficiency and decision-making.

Keywords: reporting, decision-making, power BI, commcare, data automation, visualizations, dashboards

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Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

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This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

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Authors: Yogesh C. Sharma, A. Seetharaman

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The decision-making process in humans is a complicated system influenced by a variety of intrinsic and extrinsic factors. Human decisions have a ripple effect on subsequent decisions. In this study, the scope of human decision making is limited to employees. In an organisation, a person makes a variety of decisions from the time they are hired to the time they retire. The goal of this research is to identify various elements that influence decision-making. In addition, the environment in which a decision is made is a significant aspect of the decision-making process. Employees in today's workplace use artificial intelligence (AI) systems for automation and decision augmentation. The impact of AI systems on the decision-making process is examined in this study. This research is designed based on a systematic literature review. Based on gaps in the literature, limitations and the scope of future research have been identified. Based on these findings, a research framework has been designed to identify various factors affecting employee decision making. Employee decision making is influenced by technological advancement, data-driven culture, human trust, decision automation-augmentation, and workplace motivation. Hybrid human-AI systems require the development of new skill sets and organisational design. Employee psychological safety and supportive leadership influences overall job satisfaction.

Keywords: employee decision making, artificial intelligence (AI) environment, human trust, technology innovation, psychological safety

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Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: Emmanuel D. Buedi, K. O. Boateng, Griffith S. Klogo

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Electrical distribution networks are prone to power quality disturbances originating from the complexity of the distribution network, mode of distribution (overhead or underground) and types of loads used by customers. Data on the types of disturbances present and frequency of occurrence is needed for economic evaluation and hence finding solution to the problem. Utility companies have resorted to using secondary power quality devices such as smart meters to help gather the required data. Even though this approach is easier to adopt, data gathered from these devices may not serve the required purpose, since the installation of these devices in the electrical network usually does not conform to available PQM placement methods. This paper presents a design of a PQM that is capable of integrating into an existing DAS infrastructure to take advantage of available placement methodologies. The monitoring component of the design is implemented and installed to monitor an existing LV network. Data from the monitor is analyzed and presented. A portion of the LV network of the Electricity Company of Ghana is modeled in MATLAB-Simulink and analyzed under various earth fault conditions. The results presented show the ability of the PQM to detect and analyze PQ disturbance such as voltage sag and overvoltage. By adopting a placement methodology and installing these nodes, utilities are assured of accurate and reliable information with respect to the quality of power delivered to consumers.

Keywords: power quality, remote monitoring, distributed automation system, economic evaluation, LV network

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Authors: Mahiout Tassadit

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As part of the study of a compliance and quality aspect concerning one of the plant-based products: drugs for herbal teas sold in pharmacies, a survey targeting: the general population (100 people of different age groups) as well as dispensary pharmacists (40 pharmacists from rural or urban areas) of the wilaya of Tizi-Ouzou (central Algeria) was carried out followed by a macroscopic and microscopic analysis of 4 samples of the said drugs, the survey carried out using two questionnaires, the data of which were collected and then analyzed, made it possible to estimate the population's use of herbal products and medicinal plants, and the place occupied by herbal medicine in our pharmacies. The second part made it possible to control and evaluate the information present on the packaging of drugs for herbal teas; anomalies concerning the packaging, labeling and composition of these products were noted. As a result, it is more than necessary to establish regulations for this type of product; the community pharmacist again places himself as an essential element for the proper dispensation of these remedies.

Keywords: drugs, herbal teas, macroscopic analysis, microscopic analysis

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Authors: Pavel Chmelar, Martin Dobrovolny

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Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

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Authors: Roli Pradhan

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All over the globe, the resources of the government are declining, and the funding requirements in education are on a constant rise. The governments are desperately increasing the budgetary allocation for higher education, the economic plans have been labeling investment in higher education to be immensely vital for development of the nation. Still the fact is that the government of the developing nations like India lacks the potential to fund the rising demands of this sector. In the face of declining government funding for higher education, there are the growing needs and justifiable pressure for direct beneficiaries to bear a reasonable part of the cost of higher education. The supply-demand gap in higher education in India is on the increase. This paper evaluates the Indian National Education Policy over the past three decades, furnishes the need of financing of education by private players. The paper also covers the aspects of incorporating the different forms of financing in education and also focuses on the regulations pertaining to quality maintenance in the education system. The paper also targets to suggest policy imperatives for the future education policy for India.

Keywords: national education policy, privatisation, private financing, government funding

Procedia PDF Downloads 303

Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

Procedia PDF Downloads 90

Authors: Kelvin Lo

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Nowadays, numerical modelling in geotechnical engineering is very common but sophisticated. Many advanced input settings and considerable computational efforts are required to optimize the design to reduce the construction cost. To optimize a design, it usually requires huge numerical models. If the optimization is conducted manually, there is a potentially dangerous consequence from human errors, and the time spent on the input and data extraction from output is significant. This paper presents an automation process introduced to numerical modelling (Plaxis 2D) of a trench excavation supported by a secant-pile retaining structure for a top-down tunnel project. Python code is adopted to control the process, and numerical modelling is conducted automatically in every 20m chainage along the 200m tunnel, with maximum retained height occurring in the middle chainage. Python code continuously changes the geological stratum and excavation depth under groundwater flow conditions in each 20m section. It automatically conducts trial and error to determine the required pile length and the use of props to achieve the required factor of safety and target displacement. Once the bending moment of the pile exceeds its capacity, it will increase in size. When the pile embedment reaches the default maximum length, it will turn on the prop system. Results showed that it saves time, increases efficiency, lowers design costs, and replaces human labor to minimize error.

Keywords: automation, numerical modelling, Python, retaining structures

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Authors: M. Javahar, H. B. Dong

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Single crystal components manufactured using Ni-base Superalloys are routinely used in the hot sections of aero engines and industrial gas turbines due to their outstanding high temperature strength, toughness and resistance to degradation in corrosive and oxidative environments. To control the quality of the single crystal turbine blades, particular attention has been paid to grain selection, which is used to obtain the single crystal morphology from a plethora of columnar grains. For this purpose, different designs of grain selectors are employed and the most common type is the spiral grain selector. A typical spiral grain selector includes a starter block and a spiral (helix) located above. It has been found that the grains with orientation well aligned to the thermal gradient survive in the starter block by competitive grain growth while the selection of the single crystal grain occurs in the spiral part. In the present study, 2D spiral selectors with different geometries were designed and produced using a state-of-the-art Bridgeman Directional Solidification casting furnace to investigate the competitive growth during grain selection in 2d grain selectors. The principal advantage of using a 2-D selector is to facilitate the wax injection process in investment casting by enabling significant degree of automation. The automation within the process can be derived by producing 2D grain selector wax patterns parts using a split die (metal mold model) coupled with wax injection stage. This will not only produce the part with high accuracy but also at an acceptable production rate.

Keywords: grain selector, single crystal, directional solidification, CMSX-4 superalloys, investment casting

Procedia PDF Downloads 563

Authors: Dmitrii Starikov, Evgeny Rybakov, Denis Zhuravlev

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Plastic for 3D printing is very necessary material part for printers. But plastic production is technological process, which implies application of different control algorithms. Possible algorithms of providing set diameter of plastic fiber are proposed and described in the article. Results of research were proved by existing unit of filament production.

Keywords: ABS-plastic, automation, control system, extruder, filament, PID-algorithm

Procedia PDF Downloads 386

Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

Procedia PDF Downloads 126

Authors: Chia-Jung Chen, Yu-Chi Hsu, June-Dong Lin, Kun-Chen Chan, Chieh-Tien Wang, Li-Ching Wu, Chung-Feng Liu

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With fast advances in healthcare technology, various total laboratory automation (TLA) processes have been proposed. However, adopting TLA needs quite high funding. This study explores an early adoption experience by Taiwan’s large-scale hospital group, the Chimei Hospital Group (CMG), which owns three branch hospitals (Yongkang, Liouying and Chiali, in order by service scale), based on the five stages of Everett Rogers’ Diffusion Decision Process. 1.Knowledge stage: Over the years, two weaknesses exists in laboratory department of CMG: 1) only a few examination categories (e.g., sugar testing and HbA1c) can now be completed and reported within a day during an outpatient clinical visit; 2) the Yongkang Hospital laboratory space is dispersed across three buildings, resulting in duplicated investment in analysis instruments and inconvenient artificial specimen transportation. Thus, the senior management of the department raised a crucial question, was it time to process the redesign of the laboratory department? 2.Persuasion stage: At the end of 2013, Yongkang Hospital’s new building and restructuring project created a great opportunity for the redesign of the laboratory department. However, not all laboratory colleagues had the consensus for change. Thus, the top managers arranged a series of benchmark visits to stimulate colleagues into being aware of and accepting TLA. Later, the director of the department proposed a formal report to the top management of CMG with the results of the benchmark visits, preliminary feasibility analysis, potential benefits and so on. 3.Decision stage: This TLA suggestion was well-supported by the top management of CMG and, finally, they made a decision to carry out the project with an instrument-leasing strategy. After the announcement of a request for proposal and several vendor briefings, CMG confirmed their laboratory automation architecture and finally completed the contracts. At the same time, a cross-department project team was formed and the laboratory department assigned a section leader to the National Taiwan University Hospital for one month of relevant training. 4.Implementation stage: During the implementation, the project team called for regular meetings to review the results of the operations and to offer an immediate response to the adjustment. The main project tasks included: 1) completion of the preparatory work for beginning the automation procedures; 2) ensuring information security and privacy protection; 3) formulating automated examination process protocols; 4) evaluating the performance of new instruments and the instrument connectivity; 5)ensuring good integration with hospital information systems (HIS)/laboratory information systems (LIS); and 6) ensuring continued compliance with ISO 15189 certification. 5.Confirmation stage: In short, the core process changes include: 1) cancellation of signature seals on the specimen tubes; 2) transfer of daily examination reports to a data warehouse; 3) routine pre-admission blood drawing and formal inpatient morning blood drawing can be incorporated into an automatically-prepared tube mechanism. The study summarizes below the continuous improvement orientations: (1) Flexible reference range set-up for new instruments in LIS. (2) Restructure of the specimen category. (3) Continuous review and improvements to the examination process. (4) Whether installing the tube (specimen) delivery tracks need further evaluation.

Keywords: innovation decision process, total laboratory automation, health care

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Authors: Oluibukun G. Ajayi, Joseph O. Odumosu, Oladimeji T. Babafemi, Azeez Z. Opeyemi, Asaleye O. Samuel

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The need for the complete automation of every procedure of surveying and most especially, its engineering applications cannot be overemphasized due to the many demerits of the conventional manual or analogue approach. This paper presents the summarized details of the development of a Route Information Management (RIM) software. The software, codenamed ‘AutoROUTE’, was encoded using Microsoft visual studio-visual basic package, and it offers complete automation of the computational procedures and plan production involved in route surveying. It was experimented using a route survey data (longitudinal profile and cross sections) of a 2.7 km road which stretches from Dama to Lunko village in Minna, Niger State, acquired with the aid of a Hi-Target DGPS receiver. The developed software (AutoROUTE) is capable of computing the various simple curve parameters, horizontal curve, and vertical curve, and it can also plot road alignment, longitudinal profile, and cross-section with a capability to store this on the SQL incorporated into the Microsoft visual basic software. The plotted plans with AutoROUTE were compared with the plans produced with the conventional AutoCAD Civil 3D software, and AutoROUTE proved to be more user-friendly and accurate because it plots in three decimal places whereas AutoCAD plots in two decimal places. Also, it was discovered that AutoROUTE software is faster in plotting and the stages involved is less cumbersome compared to AutoCAD Civil 3D software.

Keywords: automated systems, cross sections, curves, engineering construction, longitudinal profile, route surveying

Procedia PDF Downloads 111

Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

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Authors: Weili Jiang, Simon Cadavid Lopera, Klaus Drechsler

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Fuel cell vehicle has become the most competitive solution for the transportation sector in the hydrogen economy. Type IV pressure vessel is currently the most popular and widely developed technology for the on-board storage, based on their high reliability and relatively low cost. Due to the stringent requirement on mechanical performance, the pressure vessel is subject to great amount of composite material, a major cost driver for the hydrogen tanks. Evidently, the optimization of composite layup design shows great potential in reducing the overall material usage, yet requires comprehensive understanding on underlying mechanisms as well as the influence of different design parameters on mechanical performance. Given the type of materials and manufacturing processes by which the type IV pressure vessels are manufactured, the design and optimization are a nuanced subject. The manifold of stacking sequence and fiber orientation variation possibilities have an out-standing effect on vessel strength due to the anisotropic property of carbon fiber composites, which make the design space high dimensional. Each variation of design parameters requires computational resources. Using finite element analysis to evaluate different designs is the most common method, however, the model-ing, setup and simulation process can be very time consuming and result in high computational cost. For this reason, it is necessary to build a reliable automation scheme to set up and analyze the di-verse composite layups. In this research, the simulation process of different tank designs regarding various parameters is conducted and automatized in a commercial finite element analysis framework Abaqus. Worth mentioning, the modeling of the composite overwrap is automatically generated using an Abaqus-Python scripting interface. The prediction of the winding angle of each layer and corresponding thickness variation on dome region is the most crucial step of the modeling, which is calculated and implemented using analytical methods. Subsequently, these different composites layups are simulated as axisymmetric models to facilitate the computational complexity and reduce the calculation time. Finally, the results are evaluated and compared regarding the ultimate tank strength. By automatically modeling, evaluating and comparing various composites layups, this system is applicable for the optimization of the tanks structures. As mentioned above, the mechanical property of the pressure vessel is highly dependent on composites layup, which requires big amount of simulations. Consequently, to automatize the simulation process gains a rapid way to compare the various designs and provide an indication of the optimum one. Moreover, this automation process can also be operated for creating a data bank of layups and corresponding mechanical properties with few preliminary configuration steps for the further case analysis. Subsequently, using e.g. machine learning to gather the optimum by the data pool directly without the simulation process.

Keywords: type IV pressure vessels, carbon composites, finite element analy-sis, automation of simulation process

Procedia PDF Downloads 101

Authors: Hamilton V. Niculescu

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Following a three year study conducted on eighteen Irish people that are involved in growing vegetables in various community gardens around Dublin, Republic of Ireland, it was revealed that addition of some automated features aimed at improving agricultural practices represented a process which was regarded as potentially beneficial, and as a great tool to closely monitor climate conditions inside the greenhouses. The participants were provided with a free custom-built mobile app through which they could remotely monitor and control features such as irrigation, air ventilation, and windows to ensure optimal growing conditions for vegetables growing inside purpose-built greenhouses. While the initial interest was generally high, within weeks, the participants' level of interaction with the enclosures slowly declined. By employing a constructivist grounded theory methodology, following focus group discussions, in-depth semi-structured interviews, and observations, it was revealed that participants' trust in newer technologies, and renewables, in particular, was low. There are various reasons for this, but because the participants in this study consist of mainly working-class people, it can be argued that lack of education and knowledge are the main barriers acting against the adoption of innovations. Consequently, it was revealed that most participants eventually decided to "set and forget" the systems in automatic working mode, indicating that the immediate effect of introducing people to assisting technologies also introduced some unintended consequences into their lifestyle. It is argued that this occurrence also indicates the fact that people initially "read" newer technologies and only adopt those features that they find useful and less intrusive in regards to their current lifestyle.

Keywords: automation, communication, greenhouse, sustainable

Procedia PDF Downloads 103

Authors: Ahmad Odeh

Abstract:

Researchers are currently more concerned about the calculations of energy at the operational stage, mainly due to its larger environmental impact, but the fact remains, embodied energies represent a substantial contributor unaccounted for in the overall energy computation method. The calculation of materials’ embodied energy during the construction stage is complicated. This is due to the various factors involved. The equipment used, fuel needed, and electricity required for each type of materials varies with location and thus the embodied energy will differ for each project. Moreover, the method used in manufacturing, transporting and putting in place will have significant influence on the materials’ embodied energy. This anomaly has made it difficult to calculate or even bench mark the usage of such energies. This paper presents a model aimed at calculating embodied energies based on such variabilities. It presents a systematic approach that uses an efficient method of calculation to provide a new insight for the selection of construction materials. The model is developed in a BIM environment. The quantification of materials’ energy is determined over the three main stages of their lifecycle: manufacturing, transporting and placing. The model uses three major databases each of which contains set of the construction materials that are most commonly used in building projects. The first dataset holds information about the energy required to manufacture any type of materials, the second includes information about the energy required for transporting the materials while the third stores information about the energy required by machinery to place the materials in their intended locations. Through geospatial data analysis, the model automatically calculates the distances between the suppliers and construction sites and then uses dataset information for energy computations. The computational sum of all the energies is automatically calculated and then the model provides designers with a list of usable equipment along with the associated embodied energies.

Keywords: BIM, lifecycle energy assessment, building automation, energy conservation

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Authors: Jefunnie Matahum, Yu-Chi Kuo, Chao-Ming Su, Tzong-Rong Ger

Abstract:

Magnetic cell labeling is of great importance in various applications in biomedical fields such as cell separation and cell sorting. Since analytical methods for quantification of cell uptake of magnetic nanoparticles (MNPs) are already well established, image analysis on single cell level still needs more characterization. This study reports an alternative non-destructive quantification methods of single-cell uptake of positively charged MNPs. Magnetophoresis experiments were performed to calculate the number of MNPs in a single cell. Mobility of magnetic cells and the area of intracellular MNP stained by Prussian blue were quantified by image processing software. ICP-MS experiments were also performed to confirm the internalization of MNPs to cells. Initial results showed that the magnetic cells incubated at 100 µg and 50 µg MNPs/mL concentration move at 18.3 and 16.7 µm/sec, respectively. There is also an increasing trend in the number and area of intracellular MNP with increasing concentration. These results could be useful in assessing the nanoparticle uptake in a single cell level.

Keywords: magnetic nanoparticles, single cell, magnetophoresis, image analysis

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

Abstract:

In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Amelia Tero-Vescan, Camil-Eugen Vari, Laura Ciulea, Cristina Filip, Silvia Imre

Abstract:

A HPLC –UV method for the identification of ephedrine (EPH), sibutramine (SB), yohimbine (Y) and caffeine (CF) was developed. Separation was performed on a Kromasil 100-RP8, 150 mm x 4.6 mm, 5 mm column equipped with a precolumn Kromasil RP 8. Mobile phase was a gradient of 80-35 % sodium dihydrogen phosphate pH=5 with NH4OH and acetonitrile over 15 minutes time of analysis. Based on the responses of 113 athletes about dietary supplements (DS) consumed for "fat burning" and weight loss which have a legal status in Romania, 28 supplements have been selected and investigated for their content in CF, Y, legal substances, and SB, EPH (prohibited substances in DS). The method allows quantitative determination of the four substances in a short analysis time and with minimum cost. The presence of SB and EPH in the analyzed DS was not detected while the content in CF and Y considering the dosage recommended by the manufacturer does not affect the health of the consumers. DS labeling (plant extracts with CF and Y content) allows manufacturers to avoid declaring correct and exact amounts per pharmaceutical form (pure CF or equivalent and Y, respectively).

Keywords: dietary supplements, sibutramine, ephedrine, yohimbine, caffeine, HPLC

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Authors: Alessandro Falconieri, Sara De Vincentiis, Vittoria Raffa

Abstract:

Mechanical force regulates axonal growth, elongation and maturation processes. This force is opening new frontiers in the field, contributing to a general understanding of the mechanisms of axon growth that, in the past, was thought to be governed exclusively by the growth cone and its ability to influence axonal growth in response to chemical signals. A method recently developed in our laboratory allows, through the labeling of neurons with magnetic nanoparticles (MNPs) and the use of permanent magnets, to apply extremely low mechanical forces, similar to those generated endogenously by the growth cone or by the increase of body mass during the organism growth. We found that these extremely low forces strongly enhance the spontaneous axonal elongation rate as well as neuronal sprouting. Data obtained don’t exclude that local phenomena, such as local transport and local translation, may be involved. These new advances could shed new light on what happens when the cell is subjected to external mechanical forces, opening new interesting scenarios in the field of mechanobiology.

Keywords: axon, external mechanical forces, magnetic nanoparticles, mechanotransduction

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Authors: Afsaneh Ghorbanzadeh, Afshin Farahbakhsh, Zakieh Bayat

Abstract:

The drug capsulation was used for release and targeted delivery in determined time, place and temperature or pH. The DOX nanocapsules were used to reduce and to minimize the unwanted side effects of drug. In this paper, the encapsulation methods of doxorubicin (DOX) and the labeling it by the magnetic core of iron (Fe3O4) has been studied. The Fe3O4 was conjugated with DOX via hydrazine bond. The solution was capsuled by the sensitive polymer of heat or pH such as chitosan-g-poly (N-isopropylacrylamide-co-N,N-dimethylacrylamide), dextran-g-poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide) and mPEG-G2.5 PAMAM by hydrazine bond. The drug release was very slow at temperatures lower than 380°C. There was a rapid and controlled drug release at temperatures higher than 380°C. According to experiments, the use mPEG-G2.5PAMAM is the best method of DOX nanocapsules synthesis, because in this method, the drug delivery time to certain place is lower than other methods and the percentage of released drug is higher. The synthesized magnetic carrier system has potential applications in magnetic drug-targeting delivery and magnetic resonance imaging.

Keywords: drug carrier, drug release, doxorubicin, iron oxide NPs

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Authors: D. Pranav

Abstract:

Pesticides are a class of Biocide, whose use in agriculture has led to a momentous increase in the yield of crops, fruits and vegetables all over the word and its effective use has also been the pillars of success for the Green Revolution. However, the incessant use of pesticides has now reached alarming levels. In 2007 alone, the world used an estimated 2.4 million tons of pesticides. Despite its tremendous benefits for agriculture, pesticide has been one of the major reasons for degradation of the natural environment and undesirable effects on human beings. It has not only caused damage to human health, but has also threatened the survival of few birds and animal species. In India, the sale and usage of banned pesticide, increased usage of pesticides and its inadequate labeling has caused Bio magnification, which is causing deleterious effects on child development, resulting in stunted mental and physical growth. This paper aims to bring to shed light on major loopholes in the current pesticide regulations such as the Insecticide Act of 1968. It further discusses loopholes in the yet to be tabled Pesticides Management Bill of 2008. It discusses and arrives at potential amendments to the laws and regulations concerning pesticides; that cannot only be applied to the Indian subcontinent but other developing countries as well.

Keywords: pesticides, India, human health, environment, regulations, reform

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Authors: Raghad Alhusari, Farag Omar, Moustafa Fadel

Abstract:

A traditional greenhouse is a metal frame agricultural building used for cultivation plants in a controlled environment isolated from external climatic changes. Using greenhouses in agriculture is an efficient way to reduce the water consumption, where agriculture field is considered the biggest water consumer world widely. Controlling greenhouse environment yields better productivity of plants but demands an increase of electric power. Although various control approaches have been used towards greenhouse automation, most of them are applied to traditional greenhouses with ventilation fans and/or evaporation cooling system. Such approaches are still demanding high energy and water consumption. The aim of this research is to develop a fuzzy control system that minimizes water and energy consumption by utilizing outside weather conditions and underground heat exchanger to maintain the optimum climate of the greenhouse. The proposed control system is implemented on an experimental model of thermally isolated greenhouse structure with dimensions of 6x5x2.8 meters. It uses fans for extracting heat from the ground heat exchanger system, motors for automatic open/close of the greenhouse windows and LED as lighting system. The controller is integrated also with environmental condition sensors. It was found that using the air-to-air horizontal ground heat exchanger with 90 mm diameter and 2 mm thickness placed 2.5 m below the ground surface results in decreasing the greenhouse temperature of 3.28 ˚C which saves around 3 kW of consumed energy. It also eliminated the water consumption needed in evaporation cooling systems which are traditionally used for cooling the greenhouse environment.

Keywords: automation, earth-to-air heat exchangers, fuzzy control, greenhouse, sustainable buildings

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Authors: Elizabeth Godwin Mahenge

Abstract:

This study seeks to investigate the portrayal of albinism in Swahili literature. People with albinism have faced many life-threatening challenges, from being hunted for their body parts of being assigned derogatory names that depict them as ghosts as or less than humans. Many studies have been conducted on the perception of people towards Persons with Albinism [PWA] worldwide. Findings showed there is negative perception or negative portrayal of PWA in different societies worldwide. These negative connotations raised hot debates around the world among different societies and associations of/for PWA. People with disability in different parts of the world started arguing the labeling and name calling same applied to persons with disability in Tanzania (albinism included). They went the same debate about name calling hence in 2010, the Tanzanian Parliament passed the bill on Persons with Disability Act which banned derogative names attached to disability in general and to albinism in particular. In Tanzanian societies, there have been a mixed feelings with regards to albinism. Some do have negative perceptions because of the killings with connection to superstitious believes, while in other societies are perceived positively as blessed children a family. From these two contradictory perceptions that exist in this society, the study seeks to find out how Swahili literature portrays albinism.

Keywords: albinism, portrayal, disability, Kiswahili literature

Procedia PDF Downloads 49