Search results for: time series data mining

Authors: Mabrouka Algherinai, Fatma Karkouri

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Today, Short Message Service (SMS) is an important means of communication. SMS is not only used in informal environment for communication and transaction, but it is also used in formal environments such as institutions, organizations, companies, and business world as a tool for communication and transactions. Therefore, there is a need to secure the information that is being transmitted through this medium to ensure security of information both in transit and at rest. But, encryption has been identified as a means to provide security to SMS messages in transit and at rest. Several past researches have proposed and developed several encryption algorithms for SMS and Information Security. This research aims at comparing the performance of common Asymmetric encryption algorithms on SMS security. The research employs the use of three algorithms, namely RSA, McEliece, and RABIN. Several experiments were performed on SMS of various sizes on android mobile device. The experimental results show that each of the three techniques has different key generation, encryption, and decryption times. The efficiency of an algorithm is determined by the time that it takes for encryption, decryption, and key generation. The best algorithm can be chosen based on the least time required for encryption. The obtained results show the least time when McEliece size 4096 is used. RABIN size 4096 gives most time for encryption and so it is the least effective algorithm when considering encryption. Also, the research shows that McEliece size 2048 has the least time for key generation, and hence, it is the best algorithm as relating to key generation. The result of the algorithms also shows that RSA size 1024 is the most preferable algorithm in terms of decryption as it gives the least time for decryption.

Keywords: SMS, RSA, McEliece, RABIN

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Authors: Anna Fredriksson Häägg, Charlotte Weil, Niklas Rönnberg

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Map-based dashboards are used for data exploration every day. The present study used an insight-based methodology for evaluating a map-based dashboard that presents research findings of water management and ecosystem services in the Amazon. In addition to analyzing the insights gained from using the dashboard, the evaluation method was compared to standardized questionnaires and task-based evaluations. The result suggests that the dashboard enabled the participants to gain domain-relevant, complex insights regarding the topic presented. Furthermore, the insight-based analysis highlighted unexpected insights and hypotheses regarding causes and potential adaptation strategies for remediation. Although time- and resource-consuming, the insight-based methodology was shown to have the potential of thoroughly analyzing how end users can utilize map-based dashboards for data exploration and decision making. Finally, the insight-based methodology is argued to evaluate tools in scenarios more similar to real-life usage compared to task-based evaluation methods.

Keywords: visual analytics, dashboard, insight-based evaluation, geographic visualization

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Authors: Smah Almotiri

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One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

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Authors: Unchalee Inkampa, Tuanjai Somboonwiwat

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Painting process of automobiles and automobile parts, which is a continuous process based on EDP (Electrode position paint, EDP). Through EDP, all work pieces will be continuously sent to the painting process. Work process can be divided into 2 groups based on the running time: Painting Room 1 and Painting Room 2. This leads to continuous operation. The problem that arises is waiting for workloads onto Painting Room. The grading process EDP to Painting Room is a major problem. Therefore, this paper aim to develop production sequencing method by applying EDP to painting process. It also applied fixed rate launching for painting room and earliest due date (EDD) for EDP process and swap pairwise interchange for waiting time to a minimum of machine. The result found that the developed method could improve painting reduced waiting time, on time delivery, meeting customers wants and improved productivity of painting unit.

Keywords: sequencing, mixed model lines, painting process, electrode position paint

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Authors: Gary Peach, Furqan Hameed

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Musaimeer outfall tunnel is one of the longest storm water tunnels in the world, with a total length of 10.15 km. The tunnel will accommodate surface and rain water received from the drainage networks from 270 km of urban areas in southern Doha with a pumping capacity of 19.7m³/sec. The tunnel is excavated by Tunnel Boring Machine (TBM) through Rus Formation, Midra Shales, and Simsima Limestone. Water inflows at high pressure, complex mixed ground, and weaker ground strata prone to karstification with the presence of vertical and lateral fractures connected to the sea bed were also encountered during mining. In addition to pre-tender geotechnical investigations, the Contractor carried out a supplementary offshore geophysical investigation in order to fine-tune the existing results of geophysical and geotechnical investigations. Electric resistivity tomography (ERT) and Seismic Reflection survey was carried out. Offshore geophysical survey was performed, and interpretations of rock mass conditions were made to provide an overall picture of underground conditions along the tunnel alignment. This allowed the critical tunnelling area and cutter head intervention to be planned accordingly. Karstification was monitored with a non-intrusive radar system facility installed on the TBM. The Boring Electric Ahead Monitoring(BEAM) was installed at the cutter head and was able to predict the rock mass up to 3 tunnel diameters ahead of the cutter head. BEAM system was provided with an online system for real time monitoring of rock mass condition and then correlated with the rock mass conditions predicted during the interpretation phase of offshore geophysical surveys. The further correlation was carried by Samples of the rock mass taken from tunnel face inspections and excavated material produced by the TBM. The BEAM data was continuously monitored to check the variations in resistivity and percentage frequency effect (PFE) of the ground. This system provided information about rock mass condition, potential karst risk, and potential of water inflow. BEAM system was found to be more than 50% accurate in picking up the difficult ground conditions and faults as predicted in the geotechnical interpretative report before the start of tunnelling operations. Upon completion of the project, it was concluded that the combined use of different geophysical investigation results can make the execution stage be carried out in a more confident way with the less geotechnical risk involved. The approach used for the prediction of rock mass condition in Geotechnical Interpretative Report (GIR) and Geophysical Reflection and electric resistivity tomography survey (ERT) Geophysical Reflection surveys were concluded to be reliable as the same rock mass conditions were encountered during tunnelling operations.

Keywords: tunnel boring machine (TBM), subsea, karstification, seismic reflection survey

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Authors: Sreejith Jayachandran, Mojtaba Ghods, Morteza Mohammadzaheri

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The modern busy world is running behind new embedded technologies based on computers and software; meanwhile, some people forget to do their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience, while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. Engineers and medical experts have come together to give birth to a new device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. Various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data is collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud, and stores it there, and the processed digital data is instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors and other health staff can collect this data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate this data for awareness of the patient's current health status. Moreover, the system is connected to a Global Positioning System (GPS) module. In emergencies, the concerned team can position the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud, and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the RHMS is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system (11×10×10) cm³ with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured with 100 GBP, which can be used not only for health systems, it can be used for numerous other uses including aerospace and transportation sections.

Keywords: embedded technology, telemonitoring system, microcontroller, Arduino UNO, cloud storage, global positioning system, remote health monitoring system, alert system

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Authors: Gabriel Efomeh Omolaiye, Olatunji Seminu, Jimoh Ajadi, Yusuf Ayoola Jimoh

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The Nigerian part of the Chad Basin till date has been one of the few critically studied basins, with few published scholarly works, compared to other basins such as Niger Delta, Dahomey, etc. This work was undertaken by the integration of 3D seismic interpretations and the well data analysis of eight wells fairly distributed in block A, Baga/Lake sub-basin in Borno basin with the aim of determining the thickness of Chad, Kerri-Kerri, Fika, and Gongila Formations in the sub-basin. Da-1 well (type-well) used in this study was subdivided into stratigraphic units based on the regional stratigraphic subdivision of the Chad basin and was later correlated with other wells using similarity of observed log responses. The combined density and sonic logs were used to generate synthetic seismograms for seismic to well ties. Five horizons were mapped, representing the tops of the formations on the 3D seismic data covering the block; average velocity function with maximum error/residual of 0.48% was adopted in the time to depth conversion of all the generated maps. There is a general thickening of sediments from the west to the east, and the estimated thicknesses of the various formations in the Baga/Lake sub-basin are Chad Formation (400-750 m), Kerri-Kerri Formation (300-1200 m), Fika Formation (300-2200 m) and Gongila Formation (100-1300 m). The thickness of the Bima Formation could not be established because the deepest well (Da-1) terminates within the formation. This is a modification to the previous and widely referenced studies of over forty decades that based the estimation of formation thickness within the study area on the observed outcrops at different locations and the use of few well data.

Keywords: Baga/Lake sub-basin, Chad basin, formation thickness, seismic, velocity

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Authors: Said Boularouk, Didier Josselin, Eitan Altman

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In this paper, we present a vocal ontology of OpenStreetMap data for the apprehension of space by visually impaired people. Indeed, the platform based on produsage gives a freedom to data producers to choose the descriptors of geocoded locations. Unfortunately, this freedom, called also folksonomy leads to complicate subsequent searches of data. We try to solve this issue in a simple but usable method to extract data from OSM databases in order to send them to visually impaired people using Text To Speech technology. We focus on how to help people suffering from visual disability to plan their itinerary, to comprehend a map by querying computer and getting information about surrounding environment in a mono-modal human-computer dialogue.

Keywords: TTS, ontology, open street map, visually impaired

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Authors: Jacqueline Żammit

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Online learning has become more popular as a substitute for traditional classroom instruction because of the COVID-19 epidemic. The study aimed to investigate how adult Maltese language learners evaluated the benefits and drawbacks of online instruction. 35 adult participants provided data through semi-structured interviews with open-ended questions. NVivo software was used to analyze the interview data using the thematic analysis method in order to find themes and group the data based on common responses. The advantages of online learning that the participants mentioned included accessing subject content even without live learning sessions, balancing learning with household duties, and lessening vulnerability to problems like fatigue, time-wasting traffic, school preparation, and parking space constraints. Conversely, inadequate Internet access, inadequate IT expertise, a shortage of personal computers, and domestic distractions adversely affected virtual learning. Lack of an Internet connection, IT expertise, a personal computer, or a phone with Internet access caused inequality in access to online learning sessions. Participants thought online learning was a way to resume academic activity, albeit with drawbacks. In order to address the challenges posed by online learning, several solutions are proposed in the research's conclusion.

Keywords: adult learners, online education, e-learning, challenges of online learning, benefits ofonline learning

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Authors: Emilienne Lardy, Eric Ballot, Mariam Lafkihi

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Efficient urban logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modelling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed, to describe extensively the kinetic and dynamic aspects of the driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Factor Analysis and a Generalized Linear Model have been established to link kinetic parameters with independent categorical contextual variables. The results include an assessment of the adjustment quality and the robustness of the models, as well as an overview of the model’s outputs.

Keywords: factor analysis, generalised linear model, real world driving data, traffic congestion, urban logistics, vehicle kinematics

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Fevy Kae Mateo, Kimberly Javier, Alyzza Marie Palles

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Leadership is a process of relationship involving interaction with other people. Leaders emphasise authority, which executes and implements regulations, maintains the rules and leads to a better future. The First Time voters are very significant because there are the stakeholders of the type of leader to be deployed. They also have the capacity of engaging the government and can be the agents of change. The objective of the study is to identify the strengths and weaknesses of leader. Moreover, the study identifies the qualities of a leader. Finally, the study determines first-time voter’s representation of a leader. Focus Group Discussion was carried out into two groups of first time voter’s ages 18 to 21 years old. Verbatim transcripts of the discussion were analyzed using Thematic Analysis. Overall results showed super ordinate themes for weaknesses of leader: Lace of transparency in the government, poor communication strategy, and valuing experience over potential and other contributory factor; for strength of a leader: analytical skill, emotional intelligence in political work, analytical ability and economic status on political participation; finally, in the representation of a leader: positive representation of a leader and negative representation of a leader.

Keywords: first time voters, focus group discussion, leadership, qualitative research design

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Authors: Husni Mohd Radzi, Lilie Zahara Ramly, Sapora Sipon, Salhah Abdullah

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Malaysia have been experiencing series of huge floods all around the country for the past decades despide planned development done by local authorities. The floods incurred due to factors like natural climate change or man-made disaster. Floods have caused a lot of damages, destructions and losses in term of infrastructure, financial implications and physical health. However, other damaging aspect was not being given much attention are the psychological need of the flood victim. The traumatic impact from the natural disaster like floods may cause serious psychological and spiritual deterioration. Many flood relief shelters in the past did not provide counseling services for flood victims to consult, and as a result, it contributes to added stress among the flood victims, as the issue were not being addressed. Some studies indicates that flood victims did not look for counseling service being offered. A total of 257 flood victim was involved in this study. Main area of the study was Kg Bukit Changgang, Kg. Rancangan Tanah Belia, Kg. Labohan Dagang and Kg.Olak Lempit in Kuala Langat, Selangor. The flood victims have responded to the survey given and the data was analyze using SPSS for descriptive information and other measures. At least 13 victims were reported to have experienced moderate to severe level of stress and anxiety over the flood disaster incidents and a total of 88 respondents admitted to have at least thought and consider getting counseling service.

Keywords: perception, acceptance towards counseling, counseling service for flood victim, disaster

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Authors: Nayak Amar, Turner Naomi, Gobina Edward

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The Scottish Higher Education Institutes must report their scope 1 & 2 emissions, whereas reporting scope 3 is optional. Scope 3 is indirect emissions which embodies a significant component of total carbon footprint and therefore it is important to record, measure and report it accurately. Robert Gordon University (RGU) reported only business travel, grid transmission and distribution, water supply and transport, and recycling scope 3 emissions. This study estimates the RGUs total scope 3 emissions by comparing it with a similar HEI in scale. The scope 3 emission reporting of sixteen Scottish HEI was studied. Glasgow Caledonian University was identified as the nearest neighbour by comparing its students' full time equivalent, staff full time equivalent, research-teaching split, budget, and foundation year. Apart from the peer, data was also collected from the Higher Education Statistics Agency database. RGU reported emissions from business travel, grid transmission and distribution, water supply, and transport and recycling. This study estimated RGUs scope 3 emissions from procurement, student-staff commute, and international student trip. The result showed that RGU covered only 11% of the scope 3 emissions. The major contributor to scope 3 emissions were procurement (48%), student commute (21%), international student trip (16%), and staff commute (4%). The estimated scope 3 emission was more than 14 times the reported emissions. This study has shown the relative importance of each scope 3 emissions source, which gives a guideline for the HEIs, on where to focus their attention to capture maximum scope 3 emissions. Moreover, it has demonstrated that it is possible to estimate the scope 3 emissions with limited data.

Keywords: HEI, university, emission calculations, scope 3 emissions, emissions reporting

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Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, Lionel L. J. Ang, Algernon C. S. Hong, Danette S. E. Tan, Grace H. B. Foo, K. Q. Hong, L. M. Cheng, M. L. Leong

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This paper presents a novel rapid soil classification technique that combines computer vision with four-probe soil electrical resistivity method and cone penetration test (CPT), to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from local construction projects are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labour-intensive. Thus, a rapid classification method is needed at the SGs. Computer vision, four-probe soil electrical resistivity and CPT were combined into an innovative non-destructive and instantaneous classification method for this purpose. The computer vision technique comprises soil image acquisition using industrial grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). Complementing the computer vision technique, the apparent electrical resistivity of soil (ρ) is measured using a set of four probes arranged in Wenner’s array. It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the soil strength is measured using a modified mini cone penetrometer, and w is measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay” and an even mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay”. It is also found that these parameters can be integrated with the computer vision technique on-site to complete the rapid soil classification in less than three minutes.

Keywords: Computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: Arash Kosari, Ali Araghi

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A mathematical model for an optical-fiber communication channel is developed which results in an expression that calculates the throughput and loss of the corresponding link. The data are assumed to be transmitted by using of separate photons with different polarizations. The derived model also shows the dependency of data throughput with length of the channel and depolarization factor. It is observed that absorption of photons affects the throughput in a more intensive way in comparison with that of depolarization. Apart from that, the probability of depolarization and the absorption of radiated photons are obtained.

Keywords: absorption, data throughput, depolarization, optical fiber

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Authors: Bindhiya Thomas, Rehana Hafeez

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Background: The Surgical Ambulatory Unit (SAU) also known as the Same Day Emergency Care (SDEC) is an established part of many hospitals providing same day emergency care service to surgical patients who would have otherwise required admission through the A&E. Prior to Covid, the SAU was functioning as a 12-hour service, but during the Covid crisis this service was transformed to a 24 hour functioning Surgical Ambulatory Assessment unit (SAAU). We studied the effects that this change brought about in-patient care in our hospital. Objective: The objective of the study was to assess the impact of a 24-hour Surgical Ambulatory Assessment unit on patient care during the time of Covid, in particular its role in freeing A&E capacity and delivering effective patient care. Methods: We collected two sets of data retrospectively. The first set was collected over a 6-week period when the SAU was functioning at the Princess Royal University Hospital. On March 23rd, 2020, the SAU was transformed into a 24-hour SAAU. Following this transformation, a second set of patient data was collected over a period of 6 weeks. A comparison was made between data collected from when the hospital had a 12-hour Surgical Ambulatory unit and later when it was transformed into a 24-hour facility. Its effects on the change in the number of patients breaching the four hour waiting period and the number of emergency surgical admissions. Results: The 24-hour Surgical Ambulatory Assessment unit brought significant reductions in the number of patients breaching the waiting period of 4 hours in A&E from 44% during the period of the 12-hour Surgical Ambulatory care facility to 0% from when the 24-hour Surgical Ambulatory Assessment Unit was established. A 28% reduction was also seen in the number of surgical patients' admissions from A&E. Conclusions: The 24-hour SAAU was found to have a profound positive impact on emergency care of surgical patients. Especially during the Covid crisis, it played a crucial role in providing not only effective and accessible patient care but also in reducing the A&E workload and admissions. It thus proved to be a strategic tool that helped to deal with the immense workload in emergency care during the Covid crisis and helped free much needed headspace at a time of uncertainty for the A&E to better configure their services. If sustained, the 24-hour SAAU could be relied on to augment the NHS emergency services in the future, especially in the event of another crisis.

Keywords: Princess Royal University Hospital, surgical ambulatory assessment unit, surgical ambulatory unit, same day emergency care

Procedia PDF Downloads 148

Authors: Michelle J. Miller

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In recent year, there has been a rise of two emerging issues that impact the global employment and business market that the legal community must review closer: offshore outsourcing and data privacy. These two issues intersect because employment opportunities are shifting due to offshore outsourcing and some States, like the United States, anti-outsourcing legislation has been passed or presented to retain jobs within the country. In addition, the legal requirements to retain the privacy of data as a global employer extends to employees and third party service provides, including services outsourced to offshore locations. For this reason, this paper will review the intersection of these two issues with a specific focus on data privacy.

Keywords: outsourcing, data privacy, international compliance, multinational corporations

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Authors: Haniyeh Okhovat, Mahmood Hosseini, Omid Kaveh Ahangari, Mona Zaryoun

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Shavadoon is a type of underground living space, formerly used in urban residences of Dezful and Shooshtar cities in southwestern Iran. In spite of their high efficiency in creating cool spaces for hot summers of that area, Shavadoons were abandoned, like many other components of vernacular architecture, as a result of the modernism movement. However, Shavadoons were used by the local people as shelters during the 8-year Iran-Iraq war, and although several cases of bombardment happened during those years, no case of damage was reported in those two cities. On this basis, and regarding the high seismicity of Iran, the use of Shavadoons as post-disasters shelters can be considered as a good issue for research. This paper presents the results of a thorough study conducted on these spaces and their seismic behavior. First, the architectural aspects of Shavadoon and their construction technique are presented. Then, the results of seismic evaluation of a sample Shavadoon, conducted by a series of time history analyses, using Plaxis software and a set of selected earthquakes, are briefly explained. These results show that Shavadoons have good stability against seismic excitations. This stability is mainly because of the high strength of conglomerate materials inside which the Shavadoons have been excavated. On this basis, and considering other merits of this components of vernacular architecture in southwest of Iran, it is recommended that the revival of these components is seriously reconsidered by both architects and civil engineers.

Keywords: Shavadoon, Iran high seismicity, Conglomerate, Modeling in Plaxis, Vernacular sustainable architecture

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Authors: El Miloudi Djelloul

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Based on analysis on applications by perception control technology in computer network security status and security protection measures, from the angles of network physical environment and network software system environmental security, this paper provides network security system perception control solution using Internet of Things (IOT), telecom and other perception technologies. Security Perception Control System is in the computer network environment, utilizing Radio Frequency Identification (RFID) of IOT and telecom integration technology to carry out integration design for systems. In the network physical security environment, RFID temperature, humidity, gas and perception technologies are used to do surveillance on environmental data, dynamic perception technology is used for network system security environment, user-defined security parameters, security log are used for quick data analysis, extends control on I/O interface, by development of API and AT command, Computer Network Security Perception Control based on Internet and GSM/GPRS is achieved, which enables users to carry out interactive perception and control for network security environment by WEB, E-MAIL as well as PDA, mobile phone short message and Internet. In the system testing, through middle ware server, security information data perception in real time with deviation of 3-5% was achieved; it proves the feasibility of Computer Network Security Perception Control System.

Keywords: computer network, perception control system security strategy, Radio Frequency Identification (RFID)

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Authors: Xinqi Guo, Karen R. Dobkins

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Background and Objectives: Humans are probably the only animals whose minds are constantly filled with thoughts, feelings and emotions. Previous studies have investigated human minds from different dimensions, including its proportion of time for not being present, its representative format, its personal relevance, its temporal locus, and affect valence. The current study aims at characterizing human mind by employing Experience Sampling Methods (ESM), a self-report research procedure for studying daily experience. This study emphasis on answering the following questions: 1) How does the contents of the inner experience vary across demographics, 2) Are certain types of inner experiences correlated with level of mindfulness and mental well-being (e.g., are people who spend more time being present happier, and are more mindful people more at-present?), 3) Will being prompted to report one’s inner experience increase mindfulness and mental well-being? Methods: Participants were recruited from the subject pool of UC San Diego or from the social media. They began by filling out two questionnaires: 1) Five Facet Mindfulness Questionnaire-Short Form, and 2) Warwick-Edinburgh Mental Well-being Scale, and demographic information. Then they participated in the ESM part by responding to the prompts which contained questions about their real-time inner experience: if they were 'at-present', 'mind-wandering', or 'zoned-out'. The temporal locus, the clarity, and the affect valence, and the personal importance of the thought they had the moment before the prompt were also assessed. A mobile app 'RealLife Exp' randomly delivered these prompts 3 times/day for 6 days during wake-time. After the 6 days, participants completed questionnaire (1) and (2) again. Their changes of score were compared to a control group who did not participate in the ESM procedure (yet completed (1) and (2) one week apart). Results: Results are currently preliminary as we continue to collect data. So far, there is a trend that participants are present, mind-wandering and zoned-out, about 53%, 23% and 24% during wake-time, respectively. The thoughts of participants are ranked to be clearer and more neutral if they are present vs. mind-wandering. Mind-wandering thoughts are 66% about the past, consisting 80% of inner speech. Discussion and Conclusion: This study investigated the subjective account of human mind by a tool with high ecological validity. And it broadens the understanding of the relationship between contents of mind and well-being.

Keywords: experience sampling method, meta-memory, mindfulness, mind-wandering

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Authors: Md. Shafiullah, Ali T. Al-Awami

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This project proposes optimal scheduling of imported power of a load aggregator with the utilization of EVs to maximize its profit. As with the increase of renewable energy resources, electricity price in competitive market becomes more uncertain and, on the other hand, with the penetration of renewable distributed generators in the distribution network the predicted load of a load aggregator also becomes uncertain in real time. Though there is uncertainties in both load and price, the use of EVs storage capacity can make the operation of load aggregator flexible. LA submits its offer to day-ahead market based on predicted loads and optimized use of its EVs to maximize its profit, as well as in real time operation it uses its energy storage capacity in such a way that it can maximize its profit. In this project, load aggregators profit maximization algorithm is formulated and the optimization problem is solved with the help of CVX. As in real time operation the forecasted loads differ from actual load, the mismatches are settled in real time balancing market. Simulation results compare the profit of a load aggregator with a hypothetical group of 1000 EVs and without EVs.

Keywords: CVX, electricity market, load aggregator, load and price uncertainties, profit maximization, real time balancing operation

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Authors: D. Kuvshinov, A. Siswanto, J. Lozano-Parada, W. Zimmerman

Abstract:

Ozone is well known as a powerful fast reaction rate oxidant. The ozone based processes produce no by-product left as a non-reacted ozone returns back to the original oxygen molecule. Therefore an application of ozone is widely accepted as one of the main directions for a sustainable and clean technologies development. There are number of technologies require ozone to be delivered to specific points of a production network or reactors construction. Due to space constrains, high reactivity and short life time of ozone the use of ozone generators even of a bench top scale is practically limited. This requires development of mini/micro scale ozone generator which can be directly incorporated into production units. Our report presents a feasibility study of a new micro scale rector for ozone generation (MROG). Data on MROG calibration and indigo decomposition at different operation conditions are presented. At selected operation conditions with residence time of 0.25 s the process of ozone generation is not limited by reaction rate and the amount of ozone produced is a function of power applied. It was shown that the MROG is capable to produce ozone at voltage level starting from 3.5kV with ozone concentration of 5.28E-6 (mol/L) at 5kV. This is in line with data presented on numerical investigation for a MROG. It was shown that in compare to a conventional ozone generator, MROG has lower power consumption at low voltages and atmospheric pressure. The MROG construction makes it applicable for emerged and dry systems. With a robust compact design MROG can be used as incorporated unit for production lines of high complexity.

Keywords: dielectric barrier discharge (DBD), micro reactor, ozone, plasma

Procedia PDF Downloads 320

Authors: Nishtha Madaan, Prateek Chaudhury, Nishant Kumar, Srikanta Bedathur

Abstract:

In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods.

Keywords: NLP applications, transformers, Word2vec, drift, word embeddings

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Authors: Kannapha Amaruchkul

Abstract:

We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

Procedia PDF Downloads 116

Authors: Jonathan Turner, Julie Doyle, Laura O’Philbin, Dympna O’Sullivan

Abstract:

People living with dementia should be at the centre of decision-making regarding goals for daily living. These goals include basic activities (dressing, hygiene, and mobility), advanced activities (finances, transportation, and shopping), and meaningful activities that promote well-being (pastimes and intellectual pursuits). However, there is limited involvement of people living with dementia in the design of technology to support their goals. A project is described that is co-designing intelligent computer-based support for, and with, people affected by dementia and their carers. The technology will support self-management, empower participation in shared decision-making with carers and help people living with dementia remain healthy and independent in their homes for longer. It includes information from the patient’s care plan, which documents medications, contacts, and the patient's wishes on end-of-life care. Importantly for this work, the plan can outline activities that should be maintained or worked towards, such as exercise or social contact. The authors discuss how to integrate care goal information from such a care plan with data collected from passive sensors in the patient’s home in order to deliver individualized planning and interventions for persons with dementia. A number of scientific challenges are addressed: First, to co-design with dementia patients and their carers computerized support for shared decision-making about their care while allowing the patient to share the care plan. Second, to develop a new and open monitoring framework with which to configure sensor technologies to collect data about whether goals and actions specified for a person in their care plan are being achieved. This is developed top-down by associating care quality types and metrics elicited from the co-design activities with types of data that can be collected within the home, from passive and active sensors, and from the patient’s feedback collected through a simple co-designed interface. These activities and data will be mapped to appropriate sensors and technological infrastructure with which to collect the data. Third, the application of machine learning models to analyze data collected via the sensing devices in order to investigate whether and to what extent activities outlined via the care plan are being achieved. The models will capture longitudinal data to track disease progression over time; as the disease progresses and captured data show that activities outlined in the care plan are not being achieved, the care plan may recommend alternative activities. Disease progression may also require care changes, and a data-driven approach can capture changes in a condition more quickly and allow care plans to evolve and be updated.

Keywords: care goals, decision-making, dementia, self-care, sensors

Procedia PDF Downloads 150

Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran

Abstract:

Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.

Keywords: higher education, perceptions, recommendations, online courses

Procedia PDF Downloads 249

Authors: Zhong-Dan Tu, Wang-Xi Fan, Yi-Chen Huang, Jen-Taut Yeh

Abstract:

Novel ultrahigh molecular weight polyethylene (UHMWPE)/cellulose nanofiber (CNF) (F100CNFy) and UHMWPE/modified cellulose nanofiber (MCNF) (F100MCNFxy) as-prepared nanocomposite fibers were prepared by spinning F100CNFy and F100MCNFxy gel solutions, respectively. Cellulose nanofibers were successfully prepared by proper acid treatment of cotton fibers using sulfuric acid solutions. The best prepared CNF is with specific surface areas around 120 m2/g and a nanofiber diameter of 20 nm. Modified cellulose nanofiber was prepared by grafting maleic anhydride grafted polyethylene (PE-g-MAH) onto cellulose nanofibers. The achievable draw ratio (Dra) values of each F100MCNFxy as-prepared fiber series specimens approached a maximal value as their MCNF contents reached the optimal value at 0.05 phr. In which, the maximum Dra value obtained for F100MCNFx0.05 as-prepared fiber specimen prepared at the optimal MCNF content reached another maximum value as the weight ratio of PE-g-MAH to CNF approach an optimal value at 6. Similar to those found for the achievable drawing properties of the as-prepared fibers, the orientation factor, tensile strength (σ f) and initial modulus (E) values of drawn F100MCNF6y fiber series specimens with a fixed draw ratio reach a maximal value as their MCNF contents approach the optimal value, wherein the σ f and E values of the drawn F100MCNFxy fiber specimens are significantly higher than those of the drawn F100 fiber specimens and corresponding drawn F100CNFy fiber specimens prepared at the same draw ratios and CNF contents but without modification. To understand the interesting ultradrawing, thermal, orientation and tensile properties of F100CNFy and F100MCNFxy fiber specimens, Fourier transform infra-red, specific surface areas, and transmission electron microcopic analyses of the original and modified CNF nanofillers were performed in this study.

Keywords: ultradrawing, cellulose nanofibers, ultrahigh molecular weight polyethylene, nanocomposite fibers

Procedia PDF Downloads 188

Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

Abstract:

The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

Procedia PDF Downloads 428