Search results for: input processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5666

Search results for: input processing

5066 Testing the Impact of Formal Interpreting Training on Working Memory Capacity: Evidence from Turkish-English Student-Interpreters

Authors: Elena Antonova Unlu, Cigdem Sagin Simsek

Abstract:

The research presents two studies examining the impact of formal interpreting training (FIT) on Working Memory Capacity (WMC) of student-interpreters. In Study 1, the storage and processing capacities of the working memory (WM) of last-year student-interpreters were compared with those of last-year Foreign Language Education (FLE) students. In Study 2, the impact of FIT on the WMC of student-interpreters was examined via comparing their results on WM tasks at the beginning and the end of their FIT. In both studies, Digit Span Task (DST) and Reading Span Task (RST) were utilized for testing storage and processing capacities of WM. The results of Study 1 revealed that the last-year student-interpreters outperformed the control groups on the RST but not on the DST. The findings of Study 2 were consistent with Study 1 showing that after FIT, the student-interpreters performed better on the RST but not on the DST. Our findings can be considered as evidence supporting the view that FIT has a beneficial effect not only on the interpreting skills of student-interpreters but also on the central executive and processing capacity of their WM.

Keywords: working memory capacity, formal interpreting training, student-interpreters, cross-sectional and longitudinal data

Procedia PDF Downloads 206
5065 Trusting Smart Speakers: Analysing the Different Levels of Trust between Technologies

Authors: Alec Wells, Aminu Bello Usman, Justin McKeown

Abstract:

The growing usage of smart speakers raises many privacy and trust concerns compared to other technologies such as smart phones and computers. In this study, a proxy measure of trust is used to gauge users’ opinions on three different technologies based on an empirical study, and to understand which technology most people are most likely to trust. The collected data were analysed using the Kruskal-Wallis H test to determine the statistical differences between the users’ trust level of the three technologies: smart speaker, computer and smart phone. The findings of the study revealed that despite the wide acceptance, ease of use and reputation of smart speakers, people find it difficult to trust smart speakers with their sensitive information via the Direct Voice Input (DVI) and would prefer to use a keyboard or touchscreen offered by computers and smart phones. Findings from this study can inform future work on users’ trust in technology based on perceived ease of use, reputation, perceived credibility and risk of using technologies via DVI.

Keywords: direct voice input, risk, security, technology, trust

Procedia PDF Downloads 191
5064 Reliability and Cost Focused Optimization Approach for a Communication Satellite Payload Redundancy Allocation Problem

Authors: Mehmet Nefes, Selman Demirel, Hasan H. Ertok, Cenk Sen

Abstract:

A typical reliability engineering problem regarding communication satellites has been considered to determine redundancy allocation scheme of power amplifiers within payload transponder module, whose dominant function is to amplify power levels of the received signals from the Earth, through maximizing reliability against mass, power, and other technical limitations. Adding each redundant power amplifier component increases not only reliability but also hardware, testing, and launch cost of a satellite. This study investigates a multi-objective approach used in order to solve Redundancy Allocation Problem (RAP) for a communication satellite payload transponder, focusing on design cost due to redundancy and reliability factors. The main purpose is to find the optimum power amplifier redundancy configuration satisfying reliability and capacity thresholds simultaneously instead of analyzing respectively or independently. A mathematical model and calculation approach are instituted including objective function definitions, and then, the problem is solved analytically with different input parameters in MATLAB environment. Example results showed that payload capacity and failure rate of power amplifiers have remarkable effects on the solution and also processing time.

Keywords: communication satellite payload, multi-objective optimization, redundancy allocation problem, reliability, transponder

Procedia PDF Downloads 261
5063 Implementation of a Method of Crater Detection Using Principal Component Analysis in FPGA

Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

Abstract:

We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.

Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time

Procedia PDF Downloads 555
5062 A Controlled Natural Language Assisted Approach for the Design and Automated Processing of Service Level Agreements

Authors: Christopher Schwarz, Katrin Riegler, Erwin Zinser

Abstract:

The management of outsourcing relationships between IT service providers and their customers proofs to be a critical issue that has to be stipulated by means of Service Level Agreements (SLAs). Since service requirements differ from customer to customer, SLA content and language structures vary largely, standardized SLA templates may not be used and an automated processing of SLA content is not possible. Hence, SLA management is usually a time-consuming and inefficient manual process. For overcoming these challenges, this paper presents an innovative and ITIL V3-conform approach for automated SLA design and management using controlled natural language in enterprise collaboration portals. The proposed novel concept is based on a self-developed controlled natural language that follows a subject-predicate-object approach to specify well-defined SLA content structures that act as templates for customized contracts and support automated SLA processing. The derived results eventually enable IT service providers to automate several SLA request, approval and negotiation processes by means of workflows and business rules within an enterprise collaboration portal. The illustrated prototypical realization gives evidence of the practical relevance in service-oriented scenarios as well as the high flexibility and adaptability of the presented model. Thus, the prototype enables the automated creation of well defined, customized SLA documents, providing a knowledge representation that is both human understandable and machine processable.

Keywords: automated processing, controlled natural language, knowledge representation, information technology outsourcing, service level management

Procedia PDF Downloads 432
5061 PsyVBot: Chatbot for Accurate Depression Diagnosis using Long Short-Term Memory and NLP

Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

Abstract:

The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

Procedia PDF Downloads 69
5060 Comparison of Accumulated Stress Based Pore Pressure Model and Plasticity Model in 1D Site Response Analysis

Authors: Saeedullah J. Mandokhail, Shamsher Sadiq, Meer H. Khan

Abstract:

This paper presents the comparison of excess pore water pressure ratio (ru) predicted by using accumulated stress based pore pressure model and plasticity model. One dimensional effective stress site response analyses were performed on a 30 m deep sand column (consists of a liquefiable layer in between non-liquefiable layers) using accumulated stress based pore pressure model in Deepsoil and PDMY2 (PressureDependentMultiYield02) model in Opensees. Three Input motions with different peak ground acceleration (PGA) levels of 0.357 g, 0.124 g, and 0.11 g were used in this study. The developed excess pore pressure ratio predicted by the above two models were compared and analyzed along the depth. The time history of the ru at mid of the liquefiable layer and non-liquefiable layer were also compared. The comparisons show that the two models predict mostly similar ru values. The predicted ru is also consistent with the PGA level of the input motions.

Keywords: effective stress, excess pore pressure ratio, pore pressure model, site response analysis

Procedia PDF Downloads 227
5059 Enhancement of Mechanical Properties for Al-Mg-Si Alloy Using Equal Channel Angular Pressing

Authors: W. H. El Garaihy, A. Nassef, S. Samy

Abstract:

Equal channel angular pressing (ECAP) of commercial Al-Mg-Si alloy was conducted using two strain rates. The ECAP processing was conducted at room temperature and at 250 °C. Route A was adopted up to a total number of four passes in the present work. Structural evolution of the aluminum alloy discs was investigated before and after ECAP processing using optical microscopy (OM). Following ECAP, simple compression tests and Vicker’s hardness were performed. OM micrographs showed that, the average grain size of the as-received Al-Mg-Si disc tends to be larger than the size of the ECAP processed discs. Moreover, significant difference in the grain morphologies of the as-received and processed discs was observed. Intensity of deformation was observed via the alignment of the Al-Mg-Si consolidated particles (grains) in the direction of shear, which increased with increasing the number of passes via ECAP. Increasing the number of passes up to 4 resulted in increasing the grains aspect ratio up to ~5. It was found that the pressing temperature has a significant influence on the microstructure, Hv-values, and compressive strength of the processed discs. Hardness measurements demonstrated that 1-pass resulted in increase of Hv-value by 42% compared to that of the as-received alloy. 4-passes of ECAP processing resulted in additional increase in the Hv-value. A similar trend was observed for the yield and compressive strength. Experimental data of the Hv-values demonstrated that there is a lack of any significant dependence on the processing strain rate.

Keywords: Al-Mg-Si alloy, equal channel angular pressing, grain refinement, severe plastic deformation

Procedia PDF Downloads 435
5058 Fuzzy Inference System for Risk Assessment Evaluation of Wheat Flour Product Manufacturing Systems

Authors: Yas Barzegaar, Atrin Barzegar

Abstract:

The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

Procedia PDF Downloads 102
5057 Dairy Value Chain: Assessing the Inter Linkage of Dairy Farm and Small-Scale Dairy Processing in Tigray: Case Study of Mekelle City

Authors: Weldeabrha Kiros Kidanemaryam, DepaTesfay Kelali Gidey, Yikaalo Welu Kidanemariam

Abstract:

Dairy services are considered as sources of income, employment, nutrition and health for smallholder rural and urban farmers. The main objective of this study is to assess the interlinkage of dairy farms and small-scale dairy processing in Mekelle, Tigray. To achieve the stated objective, a descriptive research approach was employed where data was collected from 45 dairy farmers and 40 small-scale processors and analyzed by calculating the mean values and percentages. Findings show that the dairy business in the study area is characterized by a shortage of feed and water for the farm. The dairy farm is dominated by breeds of hybrid type, followed by the so called ‘begait’. Though the farms have access to medication and vaccination for the cattle, they fell short of hygiene practices, reliable shade for the cattle and separate space for the claves. The value chain at the milk production stage is characterized by a low production rate, selling raw milk without adding value and a very meager traditional processing practice. Furthermore, small-scale milk processors are characterized by collecting milk from farmers and producing cheese, butter, ghee and sour milk. They do not engage in modern milk processing like pasteurized milk, yogurt and table butter. Most small-scale milk processors are engaged in traditional production systems. Additionally, the milk consumption and marketing part of the chain is dominated by the informal market (channel), where market problems, lack of skill and technology, shortage of loans and weak policy support are being faced as the main challenges. Based on the findings, recommendations and future research areas are forwarded.

Keywords: value-chain, dairy, milk production, milk processing

Procedia PDF Downloads 34
5056 JaCoText: A Pretrained Model for Java Code-Text Generation

Authors: Jessica Lopez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri

Abstract:

Pretrained transformer-based models have shown high performance in natural language generation tasks. However, a new wave of interest has surged: automatic programming language code generation. This task consists of translating natural language instructions to a source code. Despite the fact that well-known pre-trained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformer neural network. It aims to generate java source code from natural language text. JaCoText leverages the advantages of both natural language and code generation models. More specifically, we study some findings from state of the art and use them to (1) initialize our model from powerful pre-trained models, (2) explore additional pretraining on our java dataset, (3) lead experiments combining the unimodal and bimodal data in training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.

Keywords: java code generation, natural language processing, sequence-to-sequence models, transformer neural networks

Procedia PDF Downloads 286
5055 Correlation Analysis between Sensory Processing Sensitivity (SPS), Meares-Irlen Syndrome (MIS) and Dyslexia

Authors: Kaaryn M. Cater

Abstract:

Students with sensory processing sensitivity (SPS), Meares-Irlen Syndrome (MIS) and dyslexia can become overwhelmed and struggle to thrive in traditional tertiary learning environments. An estimated 50% of tertiary students who disclose learning related issues are dyslexic. This study explores the relationship between SPS, MIS and dyslexia. Baseline measures will be analysed to establish any correlation between these three minority methods of information processing. SPS is an innate sensitivity trait found in 15-20% of the population and has been identified in over 100 species of animals. Humans with SPS are referred to as Highly Sensitive People (HSP) and the measure of HSP is a 27 point self-test known as the Highly Sensitive Person Scale (HSPS). A 2016 study conducted by the author established base-line data for HSP students in a tertiary institution in New Zealand. The results of the study showed that all participating HSP students believed the knowledge of SPS to be life-changing and useful in managing life and study, in addition, they believed that all tutors and in-coming students should be given information on SPS. MIS is a visual processing and perception disorder that is found in approximately 10% of the population and has a variety of symptoms including visual fatigue, headaches and nausea. One way to ease some of these symptoms is through the use of colored lenses or overlays. Dyslexia is a complex phonological based information processing variation present in approximately 10% of the population. An estimated 50% of dyslexics are thought to have MIS. The study exploring possible correlations between these minority forms of information processing is due to begin in February 2017. An invitation will be extended to all first year students enrolled in degree programmes across all faculties and schools within the institution. An estimated 900 students will be eligible to participate in the study. Participants will be asked to complete a battery of on-line questionnaires including the Highly Sensitive Person Scale, the International Dyslexia Association adult self-assessment and the adapted Irlen indicator. All three scales have been used extensively in literature and have been validated among many populations. All participants whose score on any (or some) of the three questionnaires suggest a minority method of information processing will receive an invitation to meet with a learning advisor, and given access to counselling services if they choose. Meeting with a learning advisor is not mandatory, and some participants may choose not to receive help. Data will be collected using the Question Pro platform and base-line data will be analysed using correlation and regression analysis to identify relationships and predictors between SPS, MIS and dyslexia. This study forms part of a larger three year longitudinal study and participants will be required to complete questionnaires at annual intervals in subsequent years of the study until completion of (or withdrawal from) their degree. At these data collection points, participants will be questioned on any additional support received relating to their minority method(s) of information processing. Data from this study will be available by April 2017.

Keywords: dyslexia, highly sensitive person (HSP), Meares-Irlen Syndrome (MIS), minority forms of information processing, sensory processing sensitivity (SPS)

Procedia PDF Downloads 245
5054 Systematic Literature Review of Therapeutic Use of Autonomous Sensory Meridian Response (ASMR) and Short-Term ASMR Auditory Training Trial

Authors: Christine H. Cubelo

Abstract:

This study consists of 2-parts: a systematic review of current publications on the therapeutic use of autonomous sensory meridian response (ASMR) and a within-subjects auditory training trial using ASMR videos. The main intent is to explore ASMR as potentially therapeutically beneficial for those with atypical sensory processing. Many hearing-related disorders and mood or anxiety symptoms overlap with symptoms of sensory processing issues. For this reason, inclusion and exclusion criteria of the systematic review were generated in an effort to produce optimal search outcomes and avoid overly confined criteria that would limit yielded results. Criteria for inclusion in the review for Part 1 are (1) adult participants diagnosed with hearing loss or atypical sensory processing, (2) inclusion of measures related to ASMR as a treatment method, and (3) published between 2000 and 2022. A total of 1,088 publications were found in the preliminary search, and a total of 13 articles met the inclusion criteria. A total of 14 participants completed the trial and post-trial questionnaire. Of all responses, 64.29% agreed that the duration of auditory training sessions was reasonable. In addition, 71.43% agreed that the training improved their perception of music. Lastly, 64.29% agreed that the training improved their perception of a primary talker when there are other talkers or background noises present.

Keywords: autonomous sensory meridian response, auditory training, atypical sensory processing, hearing loss, hearing aids

Procedia PDF Downloads 55
5053 A Novel Design in the Use of Planar Transformers for LDMOS Based Amplifiers in Bands II, III, DRM+, DVB-T and DAB+

Authors: Antonis Constantinides, Christos Yiallouras, Christakis Damianou

Abstract:

The coaxial transformer-coupled push-pull circuitry has been used widely in HF and VHF amplifiers for many decades without significant changes in the topology of the transformers. Basic changes over the years concerned the construction and turns ratio of the transformers as has been imposed upon the newer technologies active devices demands. The balun transmission line transformers applied in push-pull amplifiers enable input/output impedance transformation, but are mainly used to convert the balanced output into unbalanced and the input unbalanced into balanced. A simple and affordable alternative solution over the traditional coaxial transformer is the coreless planar balun. A key advantage over the traditional approach lies in the high specifications repeatability; simplifying the amplifier construction requirements as the planar balun constitutes an integrated part of the PCB copper layout. This paper presents the performance analysis of a planar LDMOS MRFE6VP5600 Push-Pull amplifier that enables robust operation in Band III, DVB-T, DVB-T2 standards but functions equally well in Band II, for DRM+ new generation transmitters.

Keywords: amplifier, balun, complex impedance, LDMOS, planar-transformers

Procedia PDF Downloads 440
5052 Qualitative and Quantitative Traits of Processed Farmed Fish in N. W. Greece

Authors: Cosmas Nathanailides, Fotini Kakali, Kostas Karipoglou

Abstract:

The filleting yield and the chemical composition of farmed sea bass (Dicentrarchus labrax); rainbow trout (Oncorynchus mykiss) and meagre (Argyrosomus regius) was investigated in farmed fish in NW Greece. The results provide an estimate of the quantity of fish required to produce one kilogram of fillet weight, an estimation which is required for the operational management of fish processing companies. Furthermore in this work, the ratio of feed input required to produce one kilogram of fish fillet (FFCR) is presented for the first time as a useful indicator of the ecological footprint of consuming farmed fish. The lowest lipid content appeared in meagre (1,7%) and the highest in trout (4,91%). The lowest fillet yield and fillet yield feed conversion ratio (FYFCR) was in meagre (FY=42,17%, FFCR=2,48), the best fillet yield (FY=53,8%) and FYFCR (2,10) was exhibited in farmed rainbow trout. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III. Investing in knowledge society through the European Social Fund.

Keywords: farmed fish, flesh quality, filleting yield, lipid

Procedia PDF Downloads 309
5051 Robustness of MIMO-OFDM Schemes for Future Digital TV to Carrier Frequency Offset

Authors: D. Sankara Reddy, T. Kranthi Kumar, K. Sreevani

Abstract:

This paper investigates the impact of carrier frequency offset (CFO) on the performance of different MIMO-OFDM schemes with high spectral efficiency for next generation of terrestrial digital TV. We show that all studied MIMO-OFDM schemes are sensitive to CFO when it is greater than 1% of intercarrier spacing. We show also that the Alamouti scheme is the most sensitive MIMO scheme to CFO.

Keywords: modulation and multiplexing (MIMO-OFDM), signal processing for transmission carrier frequency offset, future digital TV, imaging and signal processing

Procedia PDF Downloads 487
5050 Iris Cancer Detection System Using Image Processing and Neural Classifier

Authors: Abdulkader Helwan

Abstract:

Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

Procedia PDF Downloads 503
5049 Short Term Distribution Load Forecasting Using Wavelet Transform and Artificial Neural Networks

Authors: S. Neelima, P. S. Subramanyam

Abstract:

The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

Procedia PDF Downloads 437
5048 Exploring the Potential of Replika: An AI Chatbot for Mental Health Support

Authors: Nashwah Alnajjar

Abstract:

This research paper provides an overview of Replika, an AI chatbot application that uses natural language processing technology to engage in conversations with users. The app was developed to provide users with a virtual AI friend who can converse with them on various topics, including mental health. This study explores the experiences of Replika users using quantitative research methodology. A survey was conducted with 12 participants to collect data on their demographics, usage patterns, and experiences with the Replika app. The results showed that Replika has the potential to play a role in mental health support and well-being.

Keywords: Replika, chatbot, mental health, artificial intelligence, natural language processing

Procedia PDF Downloads 86
5047 Waste Derived from Refinery and Petrochemical Plants Activities: Processing of Oil Sludge through Thermal Desorption

Authors: Anna Bohers, Emília Hroncová, Juraj Ladomerský

Abstract:

Oil sludge with its main characteristic of high acidity is a waste product generated from the operation of refinery and petrochemical plants. Former refinery and petrochemical plant - Petrochema Dubová is present in Slovakia as well. Its activities was to process the crude oil through sulfonation and adsorption technology for production of lubricating and special oils, synthetic detergents and special white oils for cosmetic and medical purposes. Seventy years ago – period, when this historical acid sludge burden has been created – comparing to the environmental awareness the production was in preference. That is the reason why, as in many countries, also in Slovakia a historical environmental burden is present until now – 229 211 m3 of oil sludge in the middle of the National Park of Nízke Tatry mountain chain. Neither one of tried treatment methods – bio or non-biologic one - was proved as suitable for processing or for recovery in the reason of different factors admission: i.e. strong aggressivity, difficulty with handling because of its sludgy and liquid state et sim. As a potential solution, also incineration was tested, but it was not proven as a suitable method, as the concentration of SO2 in combustion gases was too high, and it was not possible to decrease it under the acceptable value of 2000 mg.mn-3. That is the reason why the operation of incineration plant has been terminated, and the acid sludge landfills are present until nowadays. The objective of this paper is to present a new possibility of processing and valorization of acid sludgy-waste. The processing of oil sludge was performed through the effective separation - thermal desorption technology, through which it is possible to split the sludgy material into the matrix (soil, sediments) and organic contaminants. In order to boost the efficiency in the processing of acid sludge through thermal desorption, the work will present the possibility of application of an original technology – Method of Blowing Decomposition for recovering of organic matter into technological lubricating oil.

Keywords: hazardous waste, oil sludge, remediation, thermal desorption

Procedia PDF Downloads 200
5046 Graph-Oriented Summary for Optimized Resource Description Framework Graphs Streams Processing

Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

Abstract:

Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

Procedia PDF Downloads 203
5045 Improved Simultaneous Performance in the Time Domain and in the Frequency Domain

Authors: Azeddine Ghodbane, David Bensoussan, Maher Hammami

Abstract:

An innovative approach for controlling unstable and invertible systems has demonstrated superior performance compared to conventional controllers. It has been successfully applied to a levitation system and drone control. Simulations have yielded satisfactory performances when applied to a satellite antenna controller. This design method, based on sensitivity analysis, has also been extended to handle multivariable unstable and invertible systems that exhibit dominant diagonal characteristics at high frequencies, enabling decentralized control. Furthermore, this control method has been expanded to the realm of adaptive control. In this study, we introduce an alternative adaptive architecture that enhances both time and frequency performance, helpfully mitigating the effects of disturbances from the input plant and external disturbances affecting the output. To facilitate superior performance in both the time and frequency domains, we have developed user-friendly interactive design methods using the GeoGebra platform.

Keywords: control theory, decentralized control, sensitivity theory, input-output stability theory, robust multivariable feedback control design

Procedia PDF Downloads 113
5044 A Multi-Regional Structural Path Analysis of Virtual Water Flows Caused by Coal Consumption in China

Authors: Cuiyang Feng, Xu Tang, Yi Jin

Abstract:

Coal is the most important primary energy source in China, which exerts a significant influence on the rapid economic growth. However, it makes the water resources to be a constraint on coal industry development, on account of the reverse geographical distribution between coal and water. To ease the pressure on water shortage, the ‘3 Red Lines’ water policies were announced by the Chinese government, and then ‘water for coal’ plan was added to that policies in 2013. This study utilized a structural path analysis (SPA) based on the multi-regional input-output table to quantify the virtual water flows caused by coal consumption in different stages. Results showed that the direct water input (the first stage) was the highest amount in all stages of coal consumption, accounting for approximately 30% of total virtual water content. Regional analysis demonstrated that virtual water trade alleviated the pressure on water use for coal consumption in water shortage areas, but the import of virtual water was not from the areas which are rich in water. Sectoral analysis indicated that the direct inputs from the sectors of ‘production and distribution of electric power and heat power’ and ‘Smelting and pressing of metals’ took up the major virtual water flows, while the sectors of ‘chemical industry’ and ‘manufacture of non-metallic mineral products’ importantly but indirectly consumed the water. With the population and economic growth in China, the water demand-and-supply gap in coal consumption would be more remarkable. In additional to water efficiency improvement measures, the central government should adjust the strategies of the virtual water trade to address local water scarcity issues. Water resource as the main constraints should be highly considered in coal policy to promote the sustainable development of the coal industry.

Keywords: coal consumption, multi-regional input-output model, structural path analysis, virtual water

Procedia PDF Downloads 302
5043 Investigation of a Natural Convection Heat Sink for LEDs Based on Micro Heat Pipe Array-Rectangular Channel

Authors: Wei Wang, Yaohua Zhao, Yanhua Diao

Abstract:

The exponential growth of the lighting industry has rendered traditional thermal technologies inadequate for addressing the thermal management challenges inherent to high-power light-emitting diode (LED) technology. To enhance the thermal management of LEDs, this study proposes a heat sink configuration that integrates a miniature heat pipe array based on phase change technology with rectangular channels. The thermal performance of the heat sink was evaluated through experimental testing, and the results demonstrated that when the input power was 100W, 150W, and 200W, the temperatures of the LED substrate were 47.64℃, 56.78℃, and 69.06℃, respectively. Additionally, the maximum temperature difference of the MHPA in the vertical direction was observed to be 0.32℃, 0.30℃, and 0.30℃, respectively. The results demonstrate that the heat sink not only effectively dissipates the heat generated by the LEDs, but also exhibits excellent temperature uniformity. In consideration of the experimental measurement outcomes, a corresponding numerical model was developed as part of this study. Following the model validation, the effect of the structural parameters of the heat sink on its heat dissipation efficacy was examined through the use of response surface methodology (RSM) analysis. The rectangular channel width, channel height, channel length, number of channel cross-sections, and channel cross-section spacing were selected as the input parameters, while the LED substrate temperature and the total mass of the heat sink were regarded as the response variables. Subsequently, the response was subjected to an analysis of variance (ANOVA), which yielded a regression model that predicted the response based on the input variables. This offers some direction for the design of the radiator.

Keywords: light-emitting diodes, heat transfer, heat pipe, natural convection, response surface methodology

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5042 The Analysis of Thermal Conductivity in Porcine Meat Due to Electricity by Finite Element Method

Authors: Orose Rugchati, Sarawut Wattanawongpitak

Abstract:

This research studied the analysis of the thermal conductivity and heat transfer in porcine meat due to the electric current flowing between the electrode plates in parallel. Hot-boned pork sample was prepared in 2*1*1 cubic centimeter. The finite element method with ANSYS workbench program was applied to simulate this heat transfer problem. In the thermal simulation, the input thermoelectric energy was calculated from measured current that flowing through the pork and the input voltage from the dc voltage source. The comparison of heat transfer in pork according to two voltage sources: DC voltage 30 volts and dc pulsed voltage 60 volts (pulse width 50 milliseconds and 50 % duty cycle) were demonstrated. From the result, it shown that the thermal conductivity trends to be steady at temperature 40C and 60C around 1.39 W/mC and 2.65 W/mC for dc voltage source 30 volts and dc pulsed voltage 60 volts, respectively. For temperature increased to 50C at 5 minutes, the appearance color of porcine meat at the exposer point has become to fade. This technique could be used for predicting of thermal conductivity caused by some meat’s characteristics.

Keywords: thermal conductivity, porcine meat, electricity, finite element method

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5041 Embedded Digital Image System

Authors: Dawei Li, Cheng Liu, Yiteng Liu

Abstract:

This paper introduces an embedded digital image system for Chinese space environment vertical exploration sounding rocket. In order to record the flight status of the sounding rocket as well as the payloads, an onboard embedded image processing system based on ADV212, a JPEG2000 compression chip, is designed in this paper. Since the sounding rocket is not designed to be recovered, all image data should be transmitted to the ground station before the re-entry while the downlink band used for the image transmission is only about 600 kbps. Under the same condition of compression ratio compared with other algorithm, JPEG2000 standard algorithm can achieve better image quality. So JPEG2000 image compression is applied under this condition with a limited downlink data band. This embedded image system supports lossless to 200:1 real time compression, with two cameras to monitor nose ejection and motor separation, and two cameras to monitor boom deployment. The encoder, ADV7182, receives PAL signal from the camera, then output the ITU-R BT.656 signal to ADV212. ADV7182 switches between four input video channels as the program sequence. Two SRAMs are used for Ping-pong operation and one 512 Mb SDRAM for buffering high frame-rate images. The whole image system has the characteristics of low power dissipation, low cost, small size and high reliability, which is rather suitable for this sounding rocket application.

Keywords: ADV212, image system, JPEG2000, sounding rocket

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5040 Unlocking the Potential of Short Texts with Semantic Enrichment, Disambiguation Techniques, and Context Fusion

Authors: Mouheb Mehdoui, Amel Fraisse, Mounir Zrigui

Abstract:

This paper explores the potential of short texts through semantic enrichment and disambiguation techniques. By employing context fusion, we aim to enhance the comprehension and utility of concise textual information. The methodologies utilized are grounded in recent advancements in natural language processing, which allow for a deeper understanding of semantics within limited text formats. Specifically, topic classification is employed to understand the context of the sentence and assess the relevance of added expressions. Additionally, word sense disambiguation is used to clarify unclear words, replacing them with more precise terms. The implications of this research extend to various applications, including information retrieval and knowledge representation. Ultimately, this work highlights the importance of refining short text processing techniques to unlock their full potential in real-world applications.

Keywords: information traffic, text summarization, word-sense disambiguation, semantic enrichment, ambiguity resolution, short text enhancement, information retrieval, contextual understanding, natural language processing, ambiguity

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5039 Plasma Technology for Hazardous Biomedical Waste Treatment

Authors: V. E. Messerle, A. L. Mosse, O. A. Lavrichshev, A. N. Nikonchuk, A. B. Ustimenko

Abstract:

One of the most serious environmental problems today is pollution by biomedical waste (BMW), which in most cases has undesirable properties such as toxicity, carcinogenicity, mutagenicity, fire. Sanitary and hygienic survey of typical solid BMW, made in Belarus, Kazakhstan, Russia and other countries shows that their risk to the environment is significantly higher than that of most chemical wastes. Utilization of toxic BMW requires use of the most universal methods to ensure disinfection and disposal of any of their components. Such technology is a plasma technology of BMW processing. To implement this technology a thermodynamic analysis of the plasma processing of BMW was fulfilled and plasma-box furnace was developed. The studies have been conducted on the example of the processing of bone. To perform thermodynamic calculations software package Terra was used. Calculations were carried out in the temperature range 300 - 3000 K and a pressure of 0.1 MPa. It is shown that the final products do not contain toxic substances. From the organic mass of BMW synthesis gas containing combustible components 77.4-84.6% was basically produced, and mineral part consists mainly of calcium oxide and contains no carbon. Degree of gasification of carbon reaches 100% by the temperature 1250 K. Specific power consumption for BMW processing increases with the temperature throughout its range and reaches 1 kWh/kg. To realize plasma processing of BMW experimental installation with DC plasma torch of 30 kW power was developed. The experiments allowed verifying the thermodynamic calculations. Wastes are packed in boxes weighing 5-7 kg. They are placed in the box furnace. Under the influence of air plasma flame average temperature in the box reaches 1800 OC, the organic part of the waste is gasified and inorganic part of the waste is melted. The resulting synthesis gas is continuously withdrawn from the unit through the cooling and cleaning system. Molten mineral part of the waste is removed from the furnace after it has been stopped. Experimental studies allowed determining operating modes of the plasma box furnace, the exhaust gases was analyzed, samples of condensed products were assembled and their chemical composition was determined. Gas at the outlet of the plasma box furnace has the following composition (vol.%): CO - 63.4, H2 - 6.2, N2 - 29.6, S - 0.8. The total concentration of synthesis gas (CO + H2) is 69.6%, which agrees well with the thermodynamic calculation. Experiments confirmed absence of the toxic substances in the final products.

Keywords: biomedical waste, box furnace, plasma torch, processing, synthesis gas

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5038 Analysis and Design of Dual-Polarization Antennas for Wireless Communication Systems

Authors: Vladimir Veremey

Abstract:

The paper describes the design and simulation of dual-polarization antennas that use the resonance and radiating properties of the H00 mode of metal open waveguides. The proposed antennas are formed by two orthogonal slots in a finite conducting ground plane. The slots are backed by metal screens connected to the ground plane forming open waveguides. It has been shown that the antenna designs can be efficiently used in mm-wave bands. The antenna single mode operational bandwidth is higher than 10%. The antenna designs are very simple and low-cost. They allow flush installation and can be efficiently used in various communication and remote sensing devices on fast moving carriers. Mutual coupling between antennas of the proposed design is very low. Thus, multiple antenna structures with proposed antennas can be efficiently employed in multi-band and in multiple-input-multiple-output (MIMO) systems.

Keywords: antenna, antenna arrays, Multiple-Input-Multiple-Output (MIMO), millimeter wave bands, slot antenna, flush installation, directivity, open waveguide, conformal antennas

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5037 Studies on Microstructure and Mechanical Properties of Simulated Heat Affected Zone in a Micro Alloyed Steel

Authors: Sanjeev Kumar, S. K. Nath

Abstract:

Proper selection of welding parameters for getting excellent weld is a challenge. HAZ simulation helps in identifying suitable welding parameters like heating rate, cooling rate, peak temperature, and energy input. In this study, the influence of weld thermal cycle of heat affected zone (HAZ) is simulated for Submerged Arc Welding (SAW) using Gleeble ® 3800 thermomechanical simulator. A (Micro-alloyed) MA steel plate of thickness 18 mm having yield strength 450MPa is used for making test specimens. Determination of the mechanical properties of weld simulated specimens including Charpy V-notch toughness and hardness is performed. Peak temperatures of 1300°C, 1150°C, 1000°C, 900°C, 800°C, heat energy input of 22KJ/cm and preheat temperatures of 30°C have been used with Rykalin-3D simulation model. It is found that the impact toughness (75J) is the best for the simulated HAZ specimen at the peak temperature 900ºC. For parent steel, impact toughness value is 26.8J at -50°C in transverse direction.

Keywords: HAZ simulation, mechanical properties, peak temperature, ship hull steel, weldability

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