Search results for: real time digital simulator

Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

Abstract:

This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

Procedia PDF Downloads 99

Authors: Manlika Rajchakit

Abstract:

This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, lyapunov functional, linear matrix inequalities

Procedia PDF Downloads 426

Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

Abstract:

This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

Procedia PDF Downloads 390

Authors: Basit Shahzad, Abdullatif M. Abdullatif

Abstract:

Recent advancements in Information and Communication Technologies (ICT) and easy access to Internet have made social media the first choice for information sharing related to any important events or news. On Twitter, trend is a common feature that quantifies the level of popularity of a certain news or event. In this work, we examine the impact of Twitter trends on real world events by hypothesizing that Twitter trends have an influence on print media in Pakistan. For this, Twitter is used as a platform and Twitter trends as a base line. We first collect data from two sources (Twitter trends and print media) in the period May to August 2016. Obtained data from two sources is analyzed and it is observed that social media is significantly influencing the print media and majority of the news printed in newspaper are posted on Twitter earlier.

Keywords: twitter trends, text mining, effectiveness of trends, print media

Procedia PDF Downloads 255

Authors: A. Maruf Aytekin

Abstract:

We present our approach on using continuous delivery pattern for release management. One of the key practices of agile and lean teams is the continuous delivery of new features to stakeholders. The main benefits of this approach lie in the ability to release new applications rapidly which has real strategic impact on the competitive advantage of an organization. Organizations that successfully implement Continuous Delivery have the ability to evolve rapidly to support innovation, provide stable and reliable software in more efficient ways, decrease the amount of resources need for maintenance, and lower the software delivery time and costs. One of the objectives of this paper is to elaborate a case study where IT division of Central Securities Depository Institution (MKK) of Turkey apply Continuous Delivery pattern to improve release management process.

Keywords: automation, continuous delivery, deployment, release management

Procedia PDF Downloads 248

Authors: Divyans Mahansaria

Abstract:

User authentication is an important security measure for protecting confidential data and systems. However, the vulnerability while authenticating into a system has significantly increased. Thus, necessary mechanisms must be deployed during the process of authenticating a user to safeguard him/her from the vulnerable attacks. The proposed solution implements a novel authentication mechanism to counter various forms of security breach attacks including phishing, Trojan horse, replay, key logging, Asterisk logging, shoulder surfing, brute force search and others. QR code (Quick Response Code) is a type of matrix barcode or two-dimensional barcode that can be used for storing URLs, text, images and other information. In the proposed solution, during each new authentication request, a QR code is dynamically generated and presented to the user. A piece of generic information is mapped to plurality of elements and stored within the QR code. The mapping of generic information with plurality of elements, randomizes in each new login, and thus the QR code generated for each new authentication request is for one-time use only. In order to authenticate into the system, the user needs to decode the QR code using any QR code decoding software. The QR code decoding software needs to be installed on handheld mobile devices such as smartphones, personal digital assistant (PDA), etc. On decoding the QR code, the user will be presented a mapping between the generic piece of information and plurality of elements using which the user needs to derive cipher secret information corresponding to his/her actual password. Now, in place of the actual password, the user will use this cipher secret information to authenticate into the system. The authentication terminal will receive the cipher secret information and use a validation engine that will decipher the cipher secret information. If the entered secret information is correct, the user will be provided access to the system. Usability study has been carried out on the proposed solution, and the new authentication mechanism was found to be easy to learn and adapt. Mathematical analysis of the time taken to carry out brute force attack on the proposed solution has been carried out. The result of mathematical analysis showed that the solution is almost completely resistant to brute force attack. Today’s standard methods for authentication are subject to a wide variety of software, hardware, and human attacks. The proposed scheme can be very useful in controlling the various types of authentication related attacks especially in a networked computer environment where the use of username and password for authentication is common.

Keywords: authentication, QR code, cipher / decipher text, one time password, secret information

Procedia PDF Downloads 265

Authors: Ranjeet Kumar, Pravin Suryakantrao Deshmukh, Sonal Sharma, Basudev Banerjee

Abstract:

With the tremendous increase in exposure to radiofrequency microwaves emitted by mobile phones, globally public awareness has grown with regard to the potential health hazards of microwaves on the nervous system in the brain. India alone has more than one billion mobile users out of 4.3 billion globally. Our studies have suggested that radio frequency able to affect neuronal alterations in the brain, and hence, affecting cognitive behaviour. However, adverse effect of low-intensity microwave exposure with endoplasmic reticulum stress and autophagy has not been evaluated yet. In this study, we explore whether low-intensity microwave induces endoplasmic reticulum stress and autophagy with varying frequency and time duration in Wistar rat. Ninety-six male Wistar rat were divided into 12 groups of 8 rats each. We studied at 900 MHz, 1800 MHz, and 2450 MHz frequency with reference to sham-exposed group. At the end of the exposure, the rats were sacrificed to collect brain tissue and expression of CHOP, ATF-4, XBP-1, Bcl-2, Bax, LC3 and Atg-4 gene was analysed by real-time PCR. Significant fold change (p < 0.05) of gene expression was found in all groups of 1800 MHz and 2450 MHz exposure group in comparison to sham exposure group. In conclusion, the microwave exposure able to induce ER stress and modulate autophagy. ER (endoplasmic reticulum) stress and autophagy vary with increasing frequency as well as the duration of exposure. Our results suggested that microwave exposure is harmful to neuronal health as it induces ER stress and hampers autophagy in neuron cells and thereby increasing the neuron degeneration which impairs cognitive behaviour of experimental animals.

Keywords: autophagy, ER stress, microwave, nervous system, rat

Procedia PDF Downloads 128

Authors: Michal Kopcek, Tomas Skulavik, Michal Kebisek, Gabriela Krizanova

Abstract:

The operation of nuclear power plants involves continuous monitoring of the environment in their area. This monitoring is performed using a complex data acquisition system, which collects status information about the system itself and values of many important physical variables e.g. temperature, humidity, dose rate etc. This paper describes a proposal and optimization of communication that takes place in teledosimetric system between the central control server responsible for the data processing and storing and the decentralized measuring stations, which are measuring the physical variables. Analyzes of ongoing communication were performed and consequently the optimization of the system architecture and communication was done.

Keywords: communication protocol, transmission optimization, data acquisition, system architecture

Procedia PDF Downloads 514

Authors: Aleksandra Zysk, Pawel Badura

Abstract:

Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: classification, singing, spectral analysis, vocal emission, vocal register

Procedia PDF Downloads 297

Authors: Akhilesh G. Naik, Dipankar Pal

Abstract:

In today’s scenario, the complexity of digital signal processing (DSP) applications and various microcontroller architectures have been increasing to such an extent that the traditional approaches to multiplier design in most processors are becoming outdated for being comparatively slow. Modern processing applications require suitable pipelined approaches, and therefore, algorithms that are friendlier with pipelined architectures. Traditional algorithms like Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda architectures have been proven to be comparatively slow for pipelined architectures. These architectures, therefore, need to be optimized or combined with other architectures amongst them to enhance its performances and to be made suitable for pipelined hardware/architectures. Recently, Vedic algorithm mathematically has proven to be efficient by appearing to be less complex and with fewer steps for its output establishment and have assumed renewed importance. This paper describes and shows how the Vedic algorithm can be better suited for pipelined architectures and also can be combined with traditional architectures and algorithms for enhancing its ability even further. In this paper, we also established that for complex applications on DSP and other microcontroller architectures, using Vedic approach for multiplication proves to be the best available and efficient option.

Keywords: Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda, Vedic, Single-Stage Karatsuba (SSK), Looped Karatsuba (LK)

Procedia PDF Downloads 166

Authors: Sarah Noaman

Abstract:

Utilizing renewable resources has become extensive solution for most problems in Egypt nowadays. It plays role in environmental issues such as energy crisis, lake of natural resources and climate change. This paper focuses on the importance of working with the key concepts of creating eco-friendly spaces in Egypt by using traditional perennial plants, such as Guadua bamboo as renewable resources in structures manufacture. Egypt is in critical need to search for alternative raw materials. Thus, this paper focuses on studying the usage of neglected yet affordable materials, such as Guadua bamboo in light weight structures and digital fabrication. Guadua bamboo has been cultivated throughout in tropical and subtropical areas. In Egypt, they exist in many rural areas where people try to control their growth by using pesticides as it serves no economic purpose. This paper aims to discuss the usage of Guadua bamboo either in its original state or after fabrication in the context of interior design and architecture. The results will show the applicability of using perennial plants as complementary materials in the manufacturing processes; also the conclusion will focus the lights on the importance of re-forming shallow water plants in interior design and architecture.

Keywords: digital fabrication, Guadua bamboo, zero-waste material, sustainable material, interior architecture

Procedia PDF Downloads 148

Authors: A. V. Patil

Abstract:

The microwave dielectric relaxation study of diethanolamine with triethanolamine binary mixture have been determined over the frequency range of 10 MHz to 20 GHz, at various temperatures using time domain reflectometry (TDR) method for 11 concentrations of the system. The present work reveals molecular interaction between same multi-functional groups [−OH and –NH2] of the alkanolamines (diethanolamine and triethanolamine) using different models such as Debye model, Excess model, and Kirkwood model. The dielectric parameters viz. static dielectric constant (ε0) and relaxation time (τ) have been obtained with Debye equation characterized by a single relaxation time without relaxation time distribution by the least squares fit method.

Keywords: diethanolamine, excess properties, kirkwood properties, time domain reflectometry, triethanolamine

Procedia PDF Downloads 296

Authors: Stephen Bahooshy

Abstract:

Our understanding of gender inequality has advanced in recent years. Differences in pay and societal gendered behaviour expectations have been emphasized. It is acknowledged globally that gender shapes everyone’s experiences of health and social care, including access to care, use of services and products, and the interaction with care providers. NHS Digital in England collects data from local authorities on the number of carers and people with support needs and the services they access. This data does not provide a gender breakdown. Caring can have many positive and negative impacts on carers’ health and wellbeing. For example, caring can improve physical health, provide a sense of pride and purpose, and reduced stress levels for those who undertake a caring role by choice. Negatives of caring include financial concerns, social isolation, a reduction in earnings, and not being recognized as a carer or involved and consulted by health and social care professionals. Treating male and female carers differently is by definition unequitable and precludes one gender from receiving the benefits of caring whilst potentially overburdening the other with the negatives of caring. In order to explore the issue on a preliminary basis, five local authorities who provide statutory adult social care services in England were sent Freedom of Information requests in 2019. The authorities were selected to include county councils and London boroughs. The authorities were asked to provide data on the amount of money spent on care at home packages to people over 65 years, broken down by gender and carer gender for each financial year between 2013 and 2019. Results indicated that in each financial year, female carers supporting someone over 65 years received less financial support for care at home support packages than male carers. Over the six-year period, this difference equated to a £9.5k deficit in financial support received on average per female carer when compared to male carers. An example of a London borough with the highest disparity presented an average weekly spend on care at home for people over 65 with a carer of £261.35 for male carers and £165.46 for female carers. Consequently, female carers in this borough received on average £95.89 less per week in care at home support than male carers. This highlights a real and potentially detrimental disparity in the care support received to female carers in order to support them to continue to care in parts of England. More research should be undertaken in this area to better explore this issue and to understand if these findings are unique to these social care providers or part of a wider phenomenon. NHS Digital should request local authorities collect data on gender in the same way that large employers in the United Kingdom are required by law to provide data on staff salaries by gender. People who allocate social care packages of support should consider the impact of gender when allocating support packages to people with support needs and who have carers to reduce any potential impact of gender bias on their decision-making.

Keywords: caregivers, carers, gender equality, social care

Procedia PDF Downloads 161

Authors: Nomfundo Ngombane, Topside E. Mathonsi

Abstract:

Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

Procedia PDF Downloads 75

Authors: Mahnaz Hosseinzadeh, Shaghayegh Rezaee Amiri

Abstract:

This paper presents a methodology for serial production planning problem in wire and cable manufacturing process that addresses the problem of input-output imbalance in different consecutive stations, hoping to minimize the halt of machines in each stage. To this end, a linear Goal Programming (GP) model is developed, in which four main categories of constraints as per the number of runs per machine, machines’ sequences, acceptable inventories of machines at the end of each period, and the necessity of fulfillment of the customers’ orders are considered. The model is formulated based upon on the real data obtained from IKO TAK Company, an important supplier of wire and cable for oil and gas and automotive industries in Iran. By solving the model in GAMS software the optimal number of runs, end-of-period inventories, and the possible minimum idle time for each machine are calculated. The application of the numerical results in the target company has shown the efficiency of the proposed model and the solution in decreasing the lead time of the end product delivery to the customers by 20%. Accordingly, the developed model could be easily applied in wire and cable companies for the aim of optimal production planning to reduce the halt of machines in manufacturing stages.

Keywords: goal programming approach, GP, production planning, serial manufacturing process, wire and cable industry

Procedia PDF Downloads 155

Authors: Rui Liu, Pengyu Cui, Nan Jiang

Abstract:

At present, there is much research on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing between land, sea, and air navigation targets is not deeply applied into the research of navigation information service, especially in the information expression. Targeting at this problem, the paper carries out works about the expression pattern of navigation electronic map for ground vehicles under air and land united navigation mechanism. At first, with the support from multi-source information fusion of GIS vector data, RS data, GPS data, etc., an air and land united information expression pattern is designed aiming at specific navigation task of emergency rescue in the earthquake. And then, the characteristics and specifications of the united expression of air and land navigation information under the constraints of map load are summarized and transferred into expression rules in the rule bank. At last, the related navigation experiment is implemented to evaluate the effect of the expression pattern. The experiment selects evaluation factors of the navigation task accomplishment time and the navigation error rate as the main index, and make comparisons with the traditional single information expression pattern. To sum up, the research improved the theory of navigation electronic map and laid a certain foundation for the design and realization of united navigation system in the aspect of real-time navigation information delivery.

Keywords: navigation electronic map, united navigation, multi-element expression pattern, multi-source information fusion

Procedia PDF Downloads 193

Authors: K. S. Parlak, E. Turan

Abstract:

The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.

Keywords: decision tree, feature extraction, k-means clustering, marble classification

Procedia PDF Downloads 378

Authors: Rabih Nehme, Abdullah Al Mutawa

Abstract:

The general goal behind this research is to gain a better understanding of factors leading to dysfunctional behavior of auditors. Recent accounting scandals -Enron, Waste Management Inc., WorldCom, Xerox Corporation, etc. -provided an ample proof of how the role of auditors has become the basis of controversial debates in many circles and instances in our modern time. The majority of lawsuits and accounting scandals seem to have a central topic in focus, namely the question ''Where were the auditors? The survey we offer up for research is made up of 34 questions that are designed to analyse the perception of auditors and the cause of dysfunctional behavior. The object of this research is comprised of auditors positioned and employed at the Big Four audit firms in Kuwait. Dysfunctional behavior (DB) is measured against two signal proxies of dysfunctional behavior; premature sign-off and under reporting of chargeable time. DB is analysed against time budget pressure and time deadline pressure. The research results' suggest that the general belief among auditors is that the profession of accountancy predetermines their tendency to commit certain patterns of dysfunctional behavior. Having our investigation conducted at the Big Four audit firms, we have come to the conclusion that there is a general difference in behavior patterns among perceptions of dysfunctional behavior and normal skeptic professional behavior.

Keywords: big four, dysfunctional behavior, time budget, time deadline

Procedia PDF Downloads 463

Authors: Jaypalsinh B. Parmar, Pintu Nakrani, Ashish Chaurasia

Abstract:

Digital Elevation Model (DEM) is considered as an important data in GIS-based terrain analysis for many applications and assessment of processes such as environmental and climate change studies, hydrologic modelling, etc. Vertical accuracy of DEM having geographically dynamic nature depends on different parameters which affect the model simulation outcomes. Vertical accuracy assessment in Indian landscape especially in low-lying coastal urban terrain such as lower Tapi Basin is very limited. In the present study, attempt has been made to evaluate the vertical accuracy of 30m resolution open source Indian National Cartosat-1 DEM v3 for Lower Tapi Basin (LTB) from western India. The extensive field investigation is carried out using stratified random fast static DGPS survey in the entire study region, and 117 high accuracy ground control points (GCPs) have been obtained. The above open source DEM was compared with obtained GCPs, and different statistical attributes were envisaged, and vertical error histograms were also evaluated.

Keywords: CartoDEM, Digital Elevation Model, GPS, lower Tapi basin

Procedia PDF Downloads 354

Authors: Alia El Akhrass, Raheed Al Jifri, Sara Babalghoum, Jana Bushnag

Abstract:

This project delves into exploring the functionalities of Mailchimp, an artificial intelligence application. The objective is to comprehend its operations through the AI tools it offers. To achieve this, a survey was conducted among peers, seeking insights into Mailchimp's functionality, accessibility, efficiency, and overall benefits. The survey aimed to gather valuable feedback for analysis. Subsequently, a thorough analysis of the collected data was performed to identify trends, patterns, and areas of improvement. Visual representations were then crafted to effectively summarize the findings, aiding in conveying the research outcomes clearly. Founded in 2001, Mailchimp initially provided email marketing services but has since expanded into a comprehensive marketing platform. Its focus on simplicity and accessibility has contributed to its success among businesses of all sizes. Alternative platforms such as Constant Contact, AWeber, and GetResponse offer similar services with their own unique strengths. Mailchimp's journey exemplifies the importance of vision and adaptability in the ever-evolving digital marketing landscape. By prioritizing innovation, user-centricity, and customer service, Mailchimp has established itself as a trusted partner in the field of digital marketing, enabling businesses to effectively connect with their customers and achieve their marketing goals.

Keywords: email marketing, ai tool, connect, communicate, generate

Procedia PDF Downloads 38

Authors: Linqing Ma, Huiling Feng, Jihong Liang, Yi Qian

Abstract:

In China, some villages have survived in the long history of changes and remain until today with their unique styles and featured culture developed in the past. Those ancient villages, usually aged for hundreds or thousands of years, are the mirror for traditional Chinese culture, especially the farming-studying culture represented by the Confucianism. Gaoqian, an ancient village with a population of 3,000 in Zhejiang province, is such a case. With a history dating back to Yuan Dynasty, Gaoqian Village has 13 well-preserved traditional Chinese houses with a courtyard, which were built in the Ming and Qing Dynasty. It is a fine specimen to study traditional rural China. In China, some villages have survived in the long history of changes and remain until today with their unique styles and featured culture developed in the past. Those ancient villages, usually aged for hundreds or thousands of years, are the mirror for traditional Chinese culture, especially the farming-studying culture represented by the Confucianism. Gaoqian, an ancient village with a population of 3,000 in Zhejiang province, is such a case. With a history dating back to Yuan Dynasty, Gaoqian Village has 13 well-preserved traditional Chinese houses with a courtyard, which were built in the Ming and Qing Dynasty. It is a fine specimen to study traditional rural China. Then a repository for the memory of the Village will be completed by doing arrangement and description for those multimedia resources such as texts, photos, videos and so on. Production of Creative products with digital technologies is also possible based a thorough understanding of the culture feature of Gaoqian Village using research tools for literature and history studies and a method of comparative study. Finally, the project will construct an exhibition platform for the Village and its culture by telling its stories with completed structures and treads.

Keywords: ancient villages, digital exhibition, multimedia, traditional culture

Procedia PDF Downloads 581

Authors: Saima Q. Memon, Mazhar I. Khaskheli

Abstract:

The aim of present study was to investigate the efficiency of mulberry leaves for the removal of both arsenic (III) and arsenic (V) from aqueous medium. Batch equilibrium studies were carried out to optimize various parameters such as pH of metal ion solution, volume of sorbate, sorbent doze, and agitation speed and agitation time. Maximum sorption efficiency of mulberry leaves for As (III) and As (V) at optimum conditions were 2818 μg.g-1 and 4930 μg.g-1, respectively. The experimental data was a good fit to Freundlich and D-R adsorption isotherm. Energy of adsorption was found to be in the range of 3-6 KJ/mole suggesting the physical nature of process. Kinetic data followed the first order rate, Morris-Weber equations. Developed method was applied to remove arsenic from real water samples.

Keywords: arsenic removal, mulberry, adsorption isotherms, kinetics of adsorption

Procedia PDF Downloads 267

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

Abstract:

Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 74

Authors: Adrian Bostan, Nicolae Tapus, Adriana Tapus

Abstract:

The purpose of this research paper is to study and develop a system that is able to help identify problems and improve human rehabilitation after traumatic injuries. Traumatic injuries in human’s lower limbs can occur over a life time and can have serious side effects if they are not treated correctly. In this paper, we developed an intelligent cane (IntelliCane) so as to help individuals in their rehabilitation process and provide feedback to the users. The first stage of the paper involves an analysis of the existing systems on the market and what can be improved. The second stage presents the design of the system. The third part, which is still under development is the validation of the system in real world setups with people in need. This paper presents mainly stages one and two.

Keywords: IntelliCane, 3D printing, microprocessor, weight measurement, rehabilitation tool

Procedia PDF Downloads 237

Authors: Zheng Zhang, Xin Chen, Guoqing Ding

Abstract:

Electronic apex locators (EAL) has been widely used clinically for measuring root canal working length with high accuracy, which is crucial for successful endodontic treatment. In order to maintain high accuracy in different measurement environments, this study presented a system for root canal length measurement based on multifrequency impedance method. This measuring system can generate a sweep current with frequencies from 100 Hz to 1 MHz through a direct digital synthesizer. Multiple impedance ratios with different combinations of frequencies were obtained and transmitted by an analog-to-digital converter and several of them with representatives will be selected after data process. The system analyzed the functional relationship between these impedance ratios and the distance between the file and the apex with statistics by measuring plenty of teeth. The position of the apical foramen can be determined by the statistical model using these impedance ratios. The experimental results revealed that the accuracy of the system based on multifrequency impedance ratios method to determine the position of the apical foramen was higher than the dual-frequency impedance ratio method. Besides that, for more complex measurement environments, the performance of the system was more stable.

Keywords: root canal length, apex locator, multifrequency impedance, sweep frequency

Procedia PDF Downloads 154

Authors: Noor Azwa Azreen Binti Abd. Aziz, Muhamad Zaim Bin Mohd Rozi

Abstract:

Moving towards the 4th Industrial Revolution, artificial intelligence (AI) is now more popular than ever. This subject is gaining significance every day and is continually expanding, often merging with other fields. Instead of merely being passive observers, there are benefits to understanding modern technology by delving into its inner workings. However, in a world teeming with digital information, the impact of AI on the spread of disinformation has garnered significant attention. The dissemination of inaccurate or misleading information is referred to as misinformation, posing a serious threat to democratic society, public debate, and individual decision-making. This article delves deep into the connection between AI and the dissemination of false information, exploring its potential, risks, and ethical issues as AI technology advances. The rise of AI has ushered in a new era in the dissemination of misinformation as AI-driven technologies are increasingly responsible for curating, recommending, and amplifying information on online platforms. While AI holds the potential to enhance the detection and mitigation of misinformation through natural language processing and machine learning, it also raises concerns about the amplification and propagation of false information. AI-powered deepfake technology, for instance, can generate hyper-realistic videos and audio recordings, making it increasingly challenging to discern fact from fiction.

Keywords: artificial intelligence, digital information, disinformation, ethical issues, misinformation

Procedia PDF Downloads 81

Authors: Maria C. Mariani, Md Al Masum Bhuiyan, Osei K. Tweneboah, Hector G. Huizar

Abstract:

This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties.

Keywords: Augmented Dickey Fuller Test, geophysical time series, maximum likelihood estimation, stochastic volatility model

Procedia PDF Downloads 307

Authors: Niklas Panten, Eberhard Abele

Abstract:

This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

Procedia PDF Downloads 185

Authors: Kadrefi Athanasia, Fronimaki Evgenia, Mavri Maria

Abstract:

3D Printing (3DP) is a distinct, disruptive technology that belongs to a wider group of manufacturing technologies, Additive Manufacturing (AM). In 3DP, a custom digital file turns into a solid object using a single computer and a 3D printer. Among multiple advantages, 3DP offers production with fewer steps compared to conventional manufacturing, lower production costs, and customizable designs. 3DP can be performed by several techniques, while the most common is Fused Deposition Modeling (FDM). FDM belongs to a wider group of AM techniques, material extrusion, where a digital file converts into a solid object using raw material (called filament) melted in high temperatures. As in most manufacturing procedures, environmental issues have been raised here, too. This study aims to review the literature on issues that determine technical and mechanical factors that affect the sustainability and resilience of a final 3D-printed object. The research focuses on the collection of papers that deal with 3D printing techniques and use keywords or phrases like ‘3D printed objects’, ‘factors of 3DP sustainability’, ‘waste materials,’ ‘infill patterns,’ and ‘support structures.’ After determining factors, a pilot survey will be conducted at the 3D Printing Lab in order to define the significance of each factor in the final 3D printed object.

Keywords: additive manufacturing, 3D printing, sustainable manufacturing, sustainable production

Procedia PDF Downloads 53

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

Procedia PDF Downloads 413