Search results for: automated teller machines

Authors: Kingsley Oturu, Winifred Ijomah, Wale Coker, Chibueze Achi

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With the impact of BREXIT and the need for cross-border collaboration, this international research investigated the use of a conceptual model for remanufacturing medical equipment (with a focus on anesthetic machines and baby incubators). Early findings of the research suggest that contextual factors need to be taken into consideration, as well as an emphasis on cleaning (e.g., sterilization) during the process of remanufacturing medical equipment. For example, copper tubings may be more important in the remanufacturing of anesthetic equipment in tropical climates than in cold climates.

Keywords: medical equipment remanufacture, sustainability, circular business models, remanufacture process model

Procedia PDF Downloads 151

Authors: Joel Niklaus, Matthias Sturmer

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The publication of judicial proceedings is a cornerstone of many democracies. It enables the court system to be made accountable by ensuring that justice is made in accordance with the laws. Equally important is privacy, as a fundamental human right (Article 12 in the Declaration of Human Rights). Therefore, it is important that the parties (especially minors, victims, or witnesses) involved in these court decisions be anonymized securely. Today, the anonymization of court decisions in Switzerland is performed either manually or semi-automatically using primitive software. While much research has been conducted on anonymization for tabular data, the literature on anonymization for unstructured text documents is thin and virtually non-existent for court decisions. In 2019, it has been shown that manual anonymization is not secure enough. In 21 of 25 attempted Swiss federal court decisions related to pharmaceutical companies, pharmaceuticals, and legal parties involved could be manually re-identified. This was achieved by linking the decisions with external databases using regular expressions. An automated re-identification system serves as an automated test for the safety of existing anonymizations and thus promotes the right to privacy. Manual anonymization is very expensive (recurring annual costs of over CHF 20M in Switzerland alone, according to an estimation). Consequently, many Swiss courts only publish a fraction of their decisions. An automated anonymization system reduces these costs substantially, further leading to more capacity for publishing court decisions much more comprehensively. For the re-identification system, topic modeling with latent dirichlet allocation is used to cluster an amount of over 500K Swiss court decisions into meaningful related categories. A comprehensive knowledge base with publicly available data (such as social media, newspapers, government documents, geographical information systems, business registers, online address books, obituary portal, web archive, etc.) is constructed to serve as an information hub for re-identifications. For the actual re-identification, a general-purpose language model is fine-tuned on the respective part of the knowledge base for each category of court decisions separately. The input to the model is the court decision to be re-identified, and the output is a probability distribution over named entities constituting possible re-identifications. For the anonymization system, named entity recognition (NER) is used to recognize the tokens that need to be anonymized. Since the focus lies on Swiss court decisions in German, a corpus for Swiss legal texts will be built for training the NER model. The recognized named entities are replaced by the category determined by the NER model and an identifier to preserve context. This work is part of an ongoing research project conducted by an interdisciplinary research consortium. Both a legal analysis and the implementation of the proposed system design ESRA will be performed within the next three years. This study introduces the system design of ESRA, an end-to-end system for re-identification and anonymization of Swiss court decisions. Firstly, the re-identification system tests the safety of existing anonymizations and thus promotes privacy. Secondly, the anonymization system substantially reduces the costs of manual anonymization of court decisions and thus introduces a more comprehensive publication practice.

Keywords: artificial intelligence, courts, legal tech, named entity recognition, natural language processing, ·privacy, topic modeling

Procedia PDF Downloads 127

Authors: Bernstein Ran, Shafir Tal, Tsachor Rachelle, Studd Karen, Schuster Assaf

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Laban Movement Analysis (LMA), developed in the dance community over the past seventy years, is an effective method for observing, describing, notating, and interpreting human movement to enhance communication and expression in everyday and professional life. Many applications that use motion capture data might be significantly leveraged if the Laban qualities will be recognized automatically. This paper presents an automated recognition method of Laban qualities from motion capture skeletal recordings and it is demonstrated on the output of Microsoft’s Kinect V2 sensor.

Keywords: Laban movement analysis, multitask learning, Kinect sensor, machine learning

Procedia PDF Downloads 322

Authors: Yusarina Mat-Isa, Zuraidah Mohd-Sanusi, Mohd-Nizal Haniff, Paul A. Barnes

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In view that money laundering has become eminent for banking institutions, it is an obligation for the banking institutions to adopt a risk-based approach as the integral component of the accepted policies on anti-money laundering. In doing so, those involved with the banking operations are the most critical group of personnel as these are the people who deal with the day-to-day operations of the banking institutions and are obligated to form a judgement on the level of impending risk. This requirement is extended to all relevant banking institutions staff, such as tellers and customer account representatives for them to identify suspicious customers and escalate it to the relevant authorities. Banking institutions staffs, however, face enormous challenges in identifying and distinguishing money launderers from other legitimate customers seeking genuine banking transactions. Banking institutions staffs are mostly educated and trained with the business objective in mind to serve the customers and are not trained to be “detectives with a detective’s power of observation”. Despite increasing awareness as well as trainings conducted for the banking institutions staff, their competency in assessing money laundering risk is still insufficient. Several gaps have prompted this study including the lack of behavioural perspectives in the assessment of money laundering risk in the banking institutions. Utilizing experimental approach, respondents are randomly assigned within a controlled setting with manipulated situations upon which judgement of the respondents is solicited based on various observations related to the situations. The study suggests that it is imperative that informed judgement is exercised in arriving at the decision to proceed with the banking services required by the customers. Judgement forms a basis of opinion for the banking institution staff to decide if the customers posed money laundering risk. Failure to exercise good judgement could results in losses and absorption of unnecessary risk into the banking institutions. Although the banking institutions are exposed with choices of automated solutions in assessing money laundering risk, the human factor in assessing the risk is indispensable. Individual staff in the banking institutions is the first line of defence who are responsible for screening the impending risk of any customer soliciting for banking services. At the end of the spectrum, the individual role involvement on the subject of money laundering risk assessment is not a substitute for automated solutions as human judgement is inimitable.

Keywords: banking institutions, experimental approach, money laundering, risk assessment

Procedia PDF Downloads 239

Authors: Faraz Tahir, M. Usman Akram, Albab Ahmad Khan, Mujahid Abbass, Ahmad Tariq, Nuzhat Qaiser

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The objective of this study was to evaluate the Degree of anemia by taking the picture of the palpebral conjunctiva using Smartphone Camera. We have first localized the region of interest from the image and then extracted certain features from that Region of interest and trained SVM classifier on those features and then, as a result, our system classifies the image in real-time on their level of hemoglobin. The proposed system has given an accuracy of 70%. We have trained our classifier on a locally gathered dataset of 30 patients.

Keywords: anemia, palpebral conjunctiva, SVM, smartphone

Procedia PDF Downloads 480

Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Maciej Zasuwa, Grzegorz Ptasinski, Antoni Kopyt

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Nowadays flight simulators offer tremendous possibilities for safe and cost-effective pilot training, by utilization of powerful, computational tools. Due to technology outpacing methodology, vast majority of training related work is done by human instructors. It makes assessment not efficient, and vulnerable to instructors’ subjectivity. The research presents an Objective Assessment Tool (gOAT) developed at the Warsaw University of Technology, and tested on SW-4 helicopter flight simulator. The tool uses database of the predefined manoeuvres, defined and integrated to the virtual environment. These were implemented, basing on Aeronautical Design Standard Performance Specification Handling Qualities Requirements for Military Rotorcraft (ADS-33), with predefined Mission-Task-Elements (MTEs). The core element of the gOAT enhanced algorithm that provides instructor a new set of information. In details, a set of objective flight parameters fused with report about psychophysical state of the pilot. While the pilot performs the task, the gOAT system automatically calculates performance using the embedded algorithms, data registered by the simulator software (position, orientation, velocity, etc.), as well as measurements of physiological changes of pilot’s psychophysiological state (temperature, sweating, heart rate). Complete set of measurements is presented on-line to instructor’s station and shown in dedicated graphical interface. The presented tool is based on open source solutions, and flexible for editing. Additional manoeuvres can be easily added using guide developed by authors, and MTEs can be changed by instructor even during an exercise. Algorithm and measurements used allow not only to implement basic stress level measurements, but also to reduce instructor’s workload significantly. Tool developed can be used for training purpose, as well as periodical checks of the aircrew. Flexibility and ease of modifications allow the further development to be wide ranged, and the tool to be customized. Depending on simulation purpose, gOAT can be adjusted to support simulator of aircraft, helicopter, or unmanned aerial vehicle (UAV).

Keywords: automated assessment, flight simulator, human factors, pilot training

Procedia PDF Downloads 128

Authors: Loke Mun Sei

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Software testing has become a mandatory process in assuring the software product quality. Hence, test management is needed in order to manage the test activities conducted in the software test life cycle. This paper discusses on the challenges faced in the software test life cycle, and how the test processes and test activities, mainly on test cases creation, test execution, and test reporting is being managed and automated using several test automation tools, i.e. Jira, Robot Framework, and Jenkins.

Keywords: test automation tools, test case, test execution, test reporting

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Authors: O. Ekrami, P. Claes, S. Van Dongen

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Fluctuating asymmetry (FA) has been studied for many years as an indicator of developmental stability or ‘genetic quality’ based on the assumption that perfect symmetry is ideally the expected outcome for a bilateral organism. Further studies have also investigated the possible link between FA and attractiveness or levels of masculinity or femininity. These hypotheses have been mostly examined using 2D images, and the structure of interest is usually presented using a limited number of landmarks. Such methods have the downside of simplifying and reducing the dimensionality of the structure, which will in return increase the error of the analysis. In an attempt to reach more conclusive and accurate results, in this study we have used high-resolution 3D scans of human faces and have developed an algorithm to measure and localize FA, taking a spatially-dense approach. A symmetric spatially dense anthropometric mask with paired vertices is non-rigidly mapped on target faces using an Iterative Closest Point (ICP) registration algorithm. A set of 19 manually indicated landmarks were used to examine the precision of our mapping step. The protocol’s accuracy in measurement and localizing FA is assessed using simulated faces with known amounts of asymmetry added to them. The results of validation of our approach show that the algorithm is perfectly capable of locating and measuring FA in 3D simulated faces. With the use of such algorithm, the additional captured information on asymmetry can be used to improve the studies of FA as an indicator of fitness or attractiveness. This algorithm can especially be of great benefit in studies of high number of subjects due to its automated and time-efficient nature. Additionally, taking a spatially dense approach provides us with information about the locality of FA, which is impossible to obtain using conventional methods. It also enables us to analyze the asymmetry of a morphological structures in a multivariate manner; This can be achieved by using methods such as Principal Components Analysis (PCA) or Factor Analysis, which can be a step towards understanding the underlying processes of asymmetry. This method can also be used in combination with genome wide association studies to help unravel the genetic bases of FA. To conclude, we introduced an algorithm to study and analyze asymmetry in human faces, with the possibility of extending the application to other morphological structures, in an automated, accurate and multi-variate framework.

Keywords: developmental stability, fluctuating asymmetry, morphometrics, 3D image processing

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Authors: Ahmed Elmarhomy, K. Terada

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An automated method for counting passerby has been proposed using virtual-vertical measurement lines. Space-time image is representing the human regions which are treated using the segmentation process. Different color space has been used to perform the template matching. A proper template matching has been achieved to determine direction and speed of passing people. Distinguish one or two passersby has been investigated using a correlation between passerby speed and the human-pixel area. Finally, the effectiveness of the presented method has been experimentally verified.

Keywords: counting people, measurement line, space-time image, segmentation, template matching

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Authors: Monu Verma, Hyunook Kim

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Heavy metals and organic dyes are the major sources of water pollution. Herein, a trifunctional β−cyclodextrin−ethylenediaminetetraacetic acid−chitosan (β−CD−EDTA−CS) polymer was synthesized using an easy and simple chemical route by the reaction of activated β−CD with CS through EDTA as a cross-linker (amidation reaction) for the removal of inorganic and organic pollutants from aqueous solution under different parameters such as pH, time effect, initial concentration, reusability, etc. The synthesized adsorbent was characterized using powder X-ray diffraction, Fourier transform infrared spectroscopy, field scanning electron microscopy, energy dispersive spectroscopy, Brunauer-Emmett-Teller (BET), thermogravimetric analyzer techniques to investigate their structural, functional, morphological, elemental compositions, surface area, and thermal properties, respectively. Two types of heavy metals, i.e., mercury (Hg²⁺) and cadmium (Cd²⁺), and three organic dyes, i.e., methylene blue (MB), crystal violet (CV), and safranin O (SO), were chosen as inorganic and organic pollutants, respectively, to study the adsorption capacity of β-CD-EDTA-CS in aqueous solution. The β-CD-EDTA-CS shows a monolayer adsorption capacity of 346.30 ± 14.0 and 202.90 ± 13.90 mg g−¹ for Hg²⁺ and Cd²⁺, respectively, and a heterogeneous adsorption capacity of 107.20 ± 5.70, 77.40 ± 5.30 and 55.30 ± 3.60 mg g−¹ for MB, CV and SO, respectively. Kinetics results followed pseudo-second order (PSO) kinetics behavior for both metal ions and dyes, and higher rate constants values (0.00161–0.00368 g mg−¹ min−¹) for dyes confirmed the cavitation of organic dyes (physisorption). In addition, we have also demonstrated the performance of β-CD-EDTA-CS for the four heavy metals, Hg²⁺, Cd²⁺, Ni²⁺, and Cu²⁺, and three dyes MB, CV, and SO in secondary treated wastewater. The findings of this study indicate that β-CD-EDTA-CS is simple and easy to synthesize and can be used in wastewater treatment.

Keywords: adsorption isotherms, adsorption mechanism, amino-β-cyclodextrin, heavy metal ions, organic dyes

Procedia PDF Downloads 86

Authors: Sushma Yadav, Anil K. Saroha

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Complex industrial effluent generated from chemical industry is contaminated with toxic and hazardous organic compounds and not amenable to direct biological treatment. To effectively remove many toxic organic pollutants has made it evident that new, compact and more efficient systems are needed. Catalytic Wet Air Oxidation (CWAO) is a promising treatment technology for the abatement of organic pollutants in wastewater. A lot of information is available on using CWAO for the treatment of synthetic solution containing single organic pollutant. But the real industrial effluents containing multi-component mixture of organic compounds were less studied. The main objective of this study is to use the CWAO process for converting the organics into compounds more amenable to biological treatment; complete oxidation may be too expensive. Therefore efforts were made in the present study to explore the potential of alumina based Platinum (Pt) catalyst for the treatment of industrial organic raffinate containing toxic constituents like ammoniacal nitrogen, pyridine etc. The catalysts were prepared by incipient wetness impregnation method and characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX) and BET (Brunauer, Emmett, and Teller) surface area. CWAO experiments were performed at atmospheric pressure and (30 °C - 70 °C) temperature conditions and the results were evaluated in terms of COD removal efficiency. The biodegradability test was performed by BOD/COD ratio for checking the toxicity of the industrial wastewater as well as for the treated water. The BOD/COD ratio of treated water was significantly increased and signified that the toxicity of the organics was decreased while the biodegradability was increased, indicating the more amenability towards biological treatment.

Keywords: alumina based pt catalyst, BOD/COD ratio, catalytic wet air oxidation, COD removal efficiency, industrial organic raffinate

Procedia PDF Downloads 283

Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We present a taint analysis that can automatically detect when string operations result in a string that is free of taints, where all the tainted patterns have been removed. This is an improvement on the conservative behavior of previous taint analyzers, where a string operation on a tainted string always leads to a tainted string unless the operation is manually marked as a sanitizer. The taint analysis is built on top of a string analysis that uses finite state automata to approximate the sets of values that string variables can take during the execution of a program. The proposed approach has been implemented as an extension of FlowDroid and experimental results show that the resulting taint analyzer is much more precise than the original FlowDroid.

Keywords: android, static analysis, string analysis, taint analysis

Procedia PDF Downloads 156

Authors: Zouhair Issa Ahmed, Ahmed Abdulrasool Ahmed, Falah Hassan Abdulsada

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This paper presents a layout of a factory using Pro-Model simulation by choosing the best layout that gives the highest productivity and least work in process. The general problem is to find the best sequence in which jobs pass between the machines which are compatible with the technological constraints and optimal with respect to some performance criteria. The best simulation with Pro-Model program increased productivity and reduced work in process by balancing lines of production compared with the current layout of factory when productivity increased from 45 products to 180 products through 720 hours.

Keywords: scheduling, Pro-Model, simulation, balancing lines of production, layout planning, WIP

Procedia PDF Downloads 608

Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

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This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

Procedia PDF Downloads 465

Authors: Tatipamula Samiksha Goud, .A.Naveena, M.sresta

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Traffic congestion is a major issue in many cities throughout the world, particularly in urban areas, and it is past time to switch from a fixed timer mode to an automated system. The current traffic signalling system is a fixed-time system that is inefficient if one lane is more functional than the others. A structure for an intelligent traffic control system is being designed to address this issue. When traffic density is higher on one side of a junction, the signal's green time is extended in comparison to the regular time. This study suggests a technique in which the signal's time duration is assigned based on the amount of traffic present at the time. Infrared sensors can be used to do this.

Keywords: infrared sensors, micro-controllers, LEDs, oscillators

Procedia PDF Downloads 119

Authors: Anusha Jain, Santosh Vishwanathan, Praveen K. Gupta, Shwetha S., Kavitha S. N.

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Agriculture has a major impact on the Indian economy, with the highest employment ratio than any sector of the country. Currently, most of the traditional agricultural practices and farming methods are manual, which results in farmers not realizing their maximum productivity often due to increasing in labour cost, inefficient use of water sources leading to wastage of water, inadequate soil moisture content, subsequently leading to food insecurity of the country. This research paper aims to solve this problem by developing a full-fledged web application-based platform that has the capacity to associate itself with a Microcontroller-based Automated Irrigation System which schedules the irrigation of crops based on real-time soil moisture content employing soil moisture sensors centric to the crop’s requirements using WSN (Wireless Sensor Networks) and M2M (Machine To Machine Communication) concepts, thus optimizing the use of the available limited water resource, thereby maximizing the crop yield. This robust automated irrigation system provides end-to-end automation of Irrigation of crops at any circumstances such as droughts, irregular rainfall patterns, extreme weather conditions, etc. This platform will also be capable of achieving a nationwide united farming community and ensuring the welfare of farmers. This platform is designed to equip farmers with prerequisite knowledge on tech and the latest farming practices in general. In order to achieve this, the MailChimp mailing service is used through which interested farmers/individuals' email id will be recorded and curated articles on innovations in the world of agriculture will be provided to the farmers via e-mail. In this proposed system, service is enabled on the platform where nearby crop vendors will be able to enter their pickup locations, accepted prices and other relevant information. This will enable farmers to choose their vendors wisely. Along with this, we have created a blogging service that will enable farmers and agricultural enthusiasts to share experiences, helpful knowledge, hardships, etc., with the entire farming community. These are some of the many features that the platform has to offer.

Keywords: WSN (wireless sensor networks), M2M (M/C to M/C communication), automation, irrigation system, sustainability, SAAS (software as a service), soil moisture sensor

Procedia PDF Downloads 106

Authors: Hammad Khalid

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In this paper, a strategy for computerized arranging of Fiber to the Home (FTTH) get to systems is proposed. We presented an efficient methodology for arranging access organize framework. The GIS information and a lot of calculations were utilized to make the arranging procedure increasingly programmed. The technique clarifies various strides of the arranging process. Considering various situations, various designs can be produced by utilizing the technique. It was likewise conceivable to produce the designs in an extremely brief temporal contrast with the conventional arranging. A contextual investigation is considered to delineate the utilization and abilities of the arranging technique. The technique, be that as it may, doesn't completely robotize the arranging however, make the arranging procedure fundamentally quick. The outcomes and dialog are displayed and end is given at last.

Keywords: FTTH, GIS, robotize, plan

Procedia PDF Downloads 128

Authors: Ivanka Valova

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This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation

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Authors: Igor Belykh

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Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when a digital image is resized on a diagnostic monitor. In this paper, we propose an automated grid artifacts detection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: grid, computed radiography, pattern recognition, image processing, filtering

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Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

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Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: features extraction, image segmentation, medical images, tumor detection

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Authors: B. Ladghem Chikouche

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The influence of slot wedges permeability on the electromagnetic performance of three-phase permanent magnet synchronous machine is investigated in this paper. It is shown that the back-EMF waveform, electromagnetic torque and electromagnetic torque ripple are all significantly affected by slot wedges permeability. The paper presents an accurate analytical subdomain model and confirmed by finite-element analyses.

Keywords: exact analytical calculation, finite-element method, magnetic field distribution, permanent magnet machines performance, stator slot wedges permeability

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Authors: Amy M. Kwon

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Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting.

Keywords: support vector machine, Margin, Hausdorff distance, representation selection, multiple-instance learning, machine learning

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Authors: Robin Singh, Jing-Chiou Liou

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The Internet of Things (IoT) devices are being used heavily as part of our everyday routines. Through improved communication and automated procedures, its popularity has assisted users in raising the quality of work. These devices are used in healthcare in order to better collect the patient’s data for their treatment. They are generally considered safe and secure. However, there is some possibility that some loopholes do exist which manufacturers do need to identify before some hacker takes advantage of them. For this study, we focused on two medical IoT devices which are pacemakers and hearing aids. The aim of this paper is to identify if there is any likelihood of these medical devices being hijacked and used as a botnet in Distributed Denial-Of Service attacks. Moreover, some mitigation strategies are being proposed to better secure

Keywords: cybersecurity, DDoS, IoT, medical devices

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Authors: J. Kaabi, Y. Harrath

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This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.

Keywords: flow shop scheduling, genetic algorithm, maintenance, priority rules

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Authors: Joel Vilca Tarazona, Igor Aguilar-Alonso

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The problem of this research related to business intelligence is the lack of a tool that supports automated and efficient financial analysis for decision-making and allows an evaluation of the financial statements, which is why the availability of the information is difficult. Relevant information to managers and users as an instrument in decision making financial, and administrative. For them, a business intelligence solution is proposed that will reduce information access time, personnel costs, and process automation, proposing a 4-layer architecture based on what was reviewed by the research methodology.

Keywords: decision making, business intelligence, Google Cloud, Microsoft Power BI

Procedia PDF Downloads 77

Authors: Erekle Magradze, Davit Soselia, Levan Shughliashvili, Irakli Koberidze, Shota Tsiskaridze, Victor Kakhniashvili, Tamar Chaghiashvili

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Since the beginning of active publishing activity in Georgia, voluminous printed material has been accumulated, the digitization of which is an important task. Digitized materials will be available to the audience, and it will be possible to find text in them and conduct various factual research. Digitizing scanned documents means scanning documents, extracting text from the scanned documents, and processing the text into a corresponding language model to detect inaccuracies and grammatical errors. Implementing these stages requires a unified, scalable, and automated platform, where the digital service developed for each stage will perform the task assigned to it; at the same time, it will be possible to develop these services dynamically so that there is no interruption in the work of the platform.

Keywords: NLP, OCR, BERT, Kubernetes, transformers

Procedia PDF Downloads 124

Authors: Quin Emparan, Razif Harun, Dayang R. A. Biak, Rozita Omar, Michael K. Danquah

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Cultivation of immobilized microalgae cells is on the rise for biotechnological applications. In this study, cultivation of Chlorella vulgaris was carried out in the form of suspended free-cell and immobilized cells system. NaCS-PDMDAAC capsules were used to immobilize C. vulgaris. Initially, the synthesized NaCS with C. vulgaris culture were prepared at various concentration of 5- 20% (w/v) using a 6% hardening solution (PDMDAAC) to investigate the capsules' gel stability and suitability for microalgae cells growth. Then, the capsules produced from 15% NaCS with C. vulgaris culture were furthered investigated using 5%, 10%, and 15% (w/v) of PDMDAAC solution. The capsules' gel stability was evaluated through dissolution time and loss of uniform spherical shape of capsules, while suitability for microalgae cells growth was evaluated through the optical density of microalgae. In this study, the 15% NaCS-10% PDMDAAC capsules were found to be the most suitable to sustain the capsules' gel stability and microalgae cells growth in MLA. For that reason, the C. vulgaris immobilized in the 15% NaCS-10% PDMDAAC capsules were further characterized using physicochemical analysis in terms of morphological, carbon (C), hydrogen (H) and nitrogen (N), Fourier transform-infrared (FT-IR), scanning electron microscopy-energy dispersive X-ray (SEM-EDX), zeta potential and Brunauer-Emmet-Teller (BET) analyses. The results revealed that the presence of sulfonates in the synthesized NaCS and NaCS-PDMDAAC capsules without and with C. vulgaris proves that cellulose alcohol group was successfully bonded by sulfo group. Besides that, immobilized microalgae cells have a smaller cell size of 6.29 ± 1.09 µm and zeta potential of -11.93 ± 0.91 mV than suspended free-cells microalgae culture. It can be summarized that immobilization of C. vulgaris in the 15% NaCS-10% PDMDAAC capsules are relevant as a bioremediator for wastewater treatment purposes due to its suitable size of pore and capsules as well as structural and compositional properties.

Keywords: biological capsules, immobilized cultivation, microalgae, physico-chemical analysis

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Authors: Sony, Ashok N. Bhaskarwar

Abstract:

Production of hydrogen from a renewable raw material without any co-synthesis of harmful greenhouse gases is the current need for sustainable energy solutions. The sulfur-iodine (SI) thermochemical cycle, using intermediate chemicals, is an efficient process for producing hydrogen at a much lower temperature than that required for the direct splitting of water. No net byproduct forms in the cycle. Hydrogen iodide (HI) decomposition is a crucial reaction in this cycle, as the product, hydrogen, forms only in this step. It is an endothermic, reversible, and equilibrium-limited reaction. The theoretical equilibrium conversion at 550°C is just a meagre of 24%. There is a growing interest, therefore, in enhancing the HI conversion to near-equilibrium values at lower reaction temperatures and by possibly improving the rate. The reaction is relatively slow without a catalyst, and hence catalytic decomposition of HI has gained much significance. Bi-metallic Ni-Co, Ni-Mn, Co-Mn, and tri-metallic Ni-Co-Mn catalysts over zirconia support were tested for HI decomposition reaction. The catalysts were synthesized via a sol-gel process wherein Ni was 3wt% in all the samples, and Co and Mn had equal weight ratios in the Co-Mn catalyst. Powdered X-ray diffraction and Brunauer-Emmett-Teller surface area characterizations indicated the polycrystalline nature and well-developed mesoporous structure of all the samples. The experiments were performed in a vertical laboratory-scale packed bed reactor made of quartz, and HI (55 wt%) was fed along with nitrogen at a WHSV of 12.9 hr⁻¹. Blank experiments at 500°C for HI decomposition suggested conversion of less than 5%. The activities of all the different catalysts were checked at 550°C, and the highest conversion of 23.9% was obtained with the tri-metallic 3Ni-Co-Mn-ZrO₂ catalyst. The decreasing order of the performance of catalysts could be expressed as: 3Ni-Co-Mn-ZrO₂ > 3Ni-2Co-ZrO₂ > 3Ni-2Mn-ZrO₂ > 2.5Co-2.5Mn-ZrO₂. The tri-metallic catalyst remained active till 360 mins at 550°C without any observable drop in its activity/stability. Among the explored catalyst compositions, the tri-metallic catalyst certainly has a better performance for HI conversion when compared to the bi-metallic ones. Owing to their low costs and ease of preparation, these trimetallic catalysts could be used for large-scale hydrogen production.

Keywords: sulfur-iodine cycle, hydrogen production, hydrogen iodide decomposition, bi-, and tri-metallic catalysts

Procedia PDF Downloads 166

Authors: Alexander Street, Nina Wollersberger, Paul Fernie, Leonardo Muller, Ming Hung HSU, Helen Odell-Miller, Jorg Fachner, Patrizia Di Campli San Vito, Stephen Brewster, Hari Shaji, Satvik Venkatesh, Paolo Itaborai, Nicolas Farina, Alexis Kirke, Sube Banerjee, Eduardo Reck Miranda

Abstract:

Escalating neuropsychiatric symptoms (NPS) in people with dementia may lead to earlier care home admission. Music listening has been reported to stimulate cognitive function, potentially reducing agitation in this population. We present a scoping review, reporting on current developments and discussing the potential for music listening with related technology in managing agitation in dementia care. Of two searches for music listening studies, one focused on older people or people living with dementia where music listening interventions, including technology, were delivered in participants’ homes or in institutions to address neuropsychiatric symptoms, quality of life and independence. The second included any population focusing on the use of music technology for health and wellbeing. In search one 70/251 full texts were included. The majority reported either statistical significance (6, 8.5%), significance (17, 24.2%) or improvements (26, 37.1%). Agitation was specifically reported in 36 (51.4%). The second search included 51/99 full texts, reporting improvement (28, 54.9%), significance (11, 21.5%), statistical significance (1, 1.9%) and no difference compared to the control (6, 11.7%). The majority in the first focused on mood and agitation, and the second on mood and psychophysiological responses. Five studies used AI or machine learning systems to select music, all involving healthy controls and reporting benefits. Most studies in both reviews were not conducted in a home environment (review 1 = 12; 17.1%; review 2 = 11; 21.5%). Preferred music listening may help manage NPS in the care home settings. Based on these and other data extracted in the review, a reasonable progression would be to co-design and test music listening systems and protocols for NPS in all settings, including people’s homes. Machine learning and automated technology for music selection and arousal adjustment, driven by live biodata, have not been explored in dementia care. Such approaches may help deliver the right music at the appropriate time in the required dosage, reducing the use of medication and improving quality of life.

Keywords: music listening, dementia, agitation, scoping review, technology

Procedia PDF Downloads 84