Search results for: artificial islands.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2308

Search results for: artificial islands.

868 Impact of Similarity Ratings on Human Judgement

Authors: Ian A. McCulloh, Madelaine Zinser, Jesse Patsolic, Michael Ramos

Abstract:

Recommender systems are a common artificial intelligence (AI) application. For any given input, a search system will return a rank-ordered list of similar items. As users review returned items, they must decide when to halt the search and either revise search terms or conclude their requirement is novel with no similar items in the database. We present a statistically designed experiment that investigates the impact of similarity ratings on human judgement to conclude a search item is novel and halt the search. 450 participants were recruited from Amazon Mechanical Turk to render judgement across 12 decision tasks. We find the inclusion of ratings increases the human perception that items are novel. Percent similarity increases novelty discernment when compared with star-rated similarity or the absence of a rating. Ratings reduce the time to decide and improve decision confidence. This suggests the inclusion of similarity ratings can aid human decision-makers in knowledge search tasks.

Keywords: ratings, rankings, crowdsourcing, empirical studies, user studies, similarity measures, human-centered computing, novelty in information retrieval

Procedia PDF Downloads 131
867 Untangling the Greek Seafood Market: Authentication of Crustacean Products Using DNA-Barcoding Methodologies

Authors: Z. Giagkazoglou, D. Loukovitis, C. Gubili, A. Imsiridou

Abstract:

Along with the increase in human population, demand for seafood has increased. Despite the strict labeling regulations that exist for most marketed species in the European Union, seafood substitution remains a persistent global issue. Food fraud occurs when food products are traded in a false or misleading way. Mislabeling occurs when one species is substituted and traded under the name of another, and it can be intentional or unintentional. Crustaceans are one of the most regularly consumed seafood in Greece. Shrimps, prawns, lobsters, crayfish, and crabs are considered a delicacy and can be encountered in a variety of market presentations (fresh, frozen, pre-cooked, peeled, etc.). With most of the external traits removed, products as such are susceptible to species substitution. DNA barcoding has proven to be the most accurate method for the detection of fraudulent seafood products. To our best knowledge, the DNA barcoding methodology is used for the first time in Greece, in order to investigate the labeling practices for crustacean products available in the market. A total of 100 tissue samples were collected from various retailers and markets across four Greek cities. In an effort to cover the highest range of products possible, different market presentations were targeted (fresh, frozen and cooked). Genomic DNA was extracted using the DNeasy Blood & Tissue Kit, according to the manufacturer's instructions. The mitochondrial gene selected as the target region of the analysis was the cytochrome c oxidase subunit I (COI). PCR products were purified and sequenced using an ABI 3500 Genetic Analyzer. Sequences were manually checked and edited using BioEdit software and compared against the ones available in GenBank and BOLD databases. Statistical analyses were conducted in R and PAST software. For most samples, COI amplification was successful, and species-level identification was possible. The preliminary results estimate moderate mislabeling rates (25%) in the identified samples. Mislabeling was most commonly detected in fresh products, with 50% of the samples in this category labeled incorrectly. Overall, the mislabeling rates detected by our study probably relate to some degree of unintentional misidentification, and lack of knowledge surrounding the legal designations by both retailers and consumers. For some species of crustaceans (i.e. Squila mantis) the mislabeling appears to be also affected by the local labeling practices. Across Greece, S. mantis is sold in the market under two common names, but only one is recognized by the country's legislation, and therefore any mislabeling is probably not profit-motivated. However, the substitution of the speckled shrimp (Metapenaus monoceros) for the distinct, giant river prawn (Macrobranchium rosenbergii), is a clear example of deliberate fraudulent substitution, aiming for profit. To our best knowledge, no scientific study investigating substitution and mislabeling rates in crustaceans has been conducted in Greece. For a better understanding of Greece's seafood market, similar DNA barcoding studies in other regions with increased touristic importance (e.g., the Greek islands) should be conducted. Regardless, the expansion of the list of species-specific designations for crustaceans in the country is advised.

Keywords: COI gene, food fraud, labelling control, molecular identification

Procedia PDF Downloads 67
866 Experimental Testing of a Synthetic Mulch to Reduce Runoff and Evaporative Water Losses

Authors: Yasmeen Saleem, Pedro Berliner, Nurit Agam

Abstract:

The most severe limitation for plant production in arid areas is water. Rainfall events are rare but can have pulses of high intensity. As a result, crusts are formed, which decreases infiltration into the soil, and results additionally in erosive losses of soil. Direct evaporation of water from the wetted soil can account for large fractions of the water stored in the soil. Different kinds of mulches have been used to decrease the loss of water in arid and semi-arid region. This study aims to evaluate the effect of polystyrene styrofoam pellets mulch on soil infiltration, runoff, and evaporation as a more efficient and economically viable mulch alternative. Polystyrene styrofoam pellets of two sizes (0.5 and 1 cm diameter) will be placed on top of the soil in two mulch layer depths (1 and 2 cm), in addition to the non-mulched treatment. The rainfall simulator will be used as an artificial source of rain. The preliminary results in the prototype experiment indicate that polystyrene styrofoam pellets decreased runoff, increased soil-water infiltration. We are still testing the effect of these pellets on decreasing the soil-water evaporation.

Keywords: synthetic mulch, runoff, evaporation, infiltration

Procedia PDF Downloads 123
865 Parametric Study of Ball and Socket Joint for Bio-Mimicking Exoskeleton

Authors: Mukesh Roy, Basant Singh Sikarwar, Ravi Prakash, Priya Ranjan, Ayush Goyal

Abstract:

More than 11% of people suffer from weakness in the bone resulting in inability in walking or climbing stairs or from limited upper body and limb immobility. This motivates a fresh bio-mimicking solution to the design of an exo-skeleton to support human movement in the case of partial or total immobility either due to congenital or genetic factors or due to some accident or due to geratological factors. A deeper insight and detailed understanding is required into the workings of the ball and socket joints. Our research is to mimic ball and socket joints to design snugly fitting exoskeletons. Our objective is to design an exoskeleton which is comfortable and the presence of which is not felt if not in use. Towards this goal, a parametric study is conducted to provide detailed design parameters to fabricate an exoskeleton. This work builds up on real data of the design of the exoskeleton, so that the designed exo-skeleton will be able to provide required strength and support to the subject.

Keywords: bio-mimicking, exoskeleton, ball joint, socket joint, artificial limb, patient rehabilitation, joints, human-machine interface, wearable robotics

Procedia PDF Downloads 295
864 Liquid Crystal Elastomers as Light-Driven Star-Shaped Microgripper

Authors: Indraj Singh, Xuan Lee, Yu-Chieh Cheng

Abstract:

Scientists are very keen on biomimetic research that mimics biological species to micro-robotic devices with the novel functionalities and accessibility. The source of inspiration is the complexity, sophistication, and intelligence of the biological systems. In this work, we design a light-driven star-shaped microgripper, an autonomous soft device which can change the shape under the external stimulus such as light. The design is based on light-responsive Liquid Crystal Elastomers which fabricated onto the polymer coated aligned substrate. The change in shape, controlled by the anisotropicity and the molecular orientation of the Liquid Crystal Elastomer, based on the external stimulus. This artificial star-shaped microgripper is capable of autonomous closure and capable to grab the objects in response to an external stimulus. This external stimulus-responsive materials design, based on soft active smart materials, provides a new approach to autonomous, self-regulating optical systems.

Keywords: liquid crystal elastomers, microgripper, smart materials, robotics

Procedia PDF Downloads 140
863 A Neural Network Based Clustering Approach for Imputing Multivariate Values in Big Data

Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

Procedia PDF Downloads 274
862 A Review on Comparative Analysis of Path Planning and Collision Avoidance Algorithms

Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

Procedia PDF Downloads 232
861 The Effect of Artificial Intelligence on Decoration Designs

Authors: Ayed Mouris Gad Elsayed Khalil

Abstract:

This research focuses on historical techniques associated with the Lajevardin and Haft-Rangi production methods in tile production, with particular attention to identifying techniques for applying gold leaf to the surface of these historical glazed tiles. In this context, the history of the production of glazed, gilded and glazed Lajevardin ceramics from the Khwarizmanshahid and Mongol periods (11th to 13th centuries) was first evaluated in order to better understand the context and history of the methods of historical enameling. After a historical overview of glazed ceramic production techniques and the adoption of these techniques by civilizations, we focused on the niche production methods of glazes and Lajevardin glazes, two categories of decoration commonly found on tiles. A general method for classifying the different types of gold tiles was then introduced, applicable to tiles from to the Safavid period (16th-17th centuries). These categories include gold glazed Lajevardina tiles, haft rangi gold tiles, gold glazed monolithic tiles and gold mosaic tiles.

Keywords: ethnicity, multi-cultural, jewelry, craft techniquemycenaean, ceramic, provenance, pigmentAmorium, glass bracelets, image, Byzantine empire

Procedia PDF Downloads 56
860 Optimal Solutions for Real-Time Scheduling of Reconfigurable Embedded Systems Based on Neural Networks with Minimization of Power Consumption

Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

Abstract:

In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

Procedia PDF Downloads 371
859 Outdoor Thermal Environment Measurement and Simulations in Traditional Settlements in Taiwan

Authors: Tzu-Ping Lin, Shing-Ru Yang

Abstract:

Climate change has a significant impact on human living environment, while the traditional settlement may suffer extreme thermal stress due to its specific building type and living behavior. This study selected Lutaoyang, which is the largest settlement in mountainous areas of Tainan County, for the investigation area. The microclimate parameters, such as air temperature, relative humidity, wind speed, and mean radiant temperature. The micro climate parameters were also simulated by the ENVI-met model. The results showed the banyan tree area providing good thermal comfort condition due to the shading. On the contrary, the courtyard (traditionally for the crops drying) surrounded by low rise building and consisted of artificial pavement contributing heat stress especially in summer noon. In the climate change simulations, the courtyard will become very hot and are not suitable for residents activities. These analytical results will shed light on the sustainability related to thermal environment in traditional settlements and develop adaptive measure towards sustainable development under the climate change challenges.

Keywords: thermal environment, traditional settlement, ENVI-met, Taiwan

Procedia PDF Downloads 479
858 Vertical Urban Design Guideline and Its Application to Measure Human Cognition and Emotions

Authors: Hee Sun (Sunny) Choi, Gerhard Bruyns, Wang Zhang, Sky Cheng, Saijal Sharma

Abstract:

This research addresses the need for a comprehensive framework that can guide the design and assessment of multi-level public spaces and public realms and their impact on the built environment. The study aims to understand and measure the neural mechanisms involved in this process. By doing so, it can lay the foundation for vertical and volumetric urbanism and ensure consistency and excellence in the field while also supporting scientific research methods for urban design with cognitive neuroscientists. To investigate these aspects, the paper focuses on the neighborhood scale in Hong Kong, specifically examining multi-level public spaces and quasi-public spaces within both commercial and residential complexes. The researchers use predictive Artificial Intelligence (AI) as a methodology to assess and comprehend the applicability of the urban design framework for vertical and volumetric urbanism. The findings aim to identify the factors that contribute to successful public spaces within a vertical living environment, thus introducing a new typology of public spaces.

Keywords: vertical urbanism, scientific research methods, spatial cognition, urban design guideline

Procedia PDF Downloads 81
857 Effect of Exercise on Sexual Behavior and Semen Quality of Sahiwal Bulls

Authors: Abdelrasoul, Khalid Ahmed Elrabie

Abstract:

The study was conducted on Sahiwal cattle bulls maintained at the Artificial Breeding Complex, NDRI, Karnal, Hayana, India, to determine the effect of exercise on the sexual behavior and semen quality. Fourteen Sahiwal bulls were classified into two groups of seven each. Group-1, bulls were exercised by walking in a bull exerciser once a week one hour before semen collection, whereas bulls in group-2 were exercised daily. Sexual behavior and semen quality traits studied were: Reaction time (RT), Dismounting time (DMT), Total time taken in mounts (TTTM), Flehmen response (FR), Erection Score (ES), Protrusion Score (PS), Intensity of thrust (ITS), Temperament Score (TS), Libido Score (LS), Semen volume, Physical appearance, Mass activity, Initial progressive motility, Non-eosinophilic spermatozoa count (NESC) and post thaw motility percent. Data were analyzed by least squares technique. Group-2 showed significantly (p < 0.01) higher value in RT (sec), DMT (sec), TTTM (sec), ES, PS, ITS, LS, semen volume, semen color density and mass activity.

Keywords: exercise, Sahiwal bulls, semen quality, sexual behavior

Procedia PDF Downloads 327
856 Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

Procedia PDF Downloads 512
855 Optimization of Agricultural Water Demand Using a Hybrid Model of Dynamic Programming and Neural Networks: A Case Study of Algeria

Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: water management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network

Procedia PDF Downloads 115
854 The Use of Modern Technologies and Computers in the Archaeological Surveys of Sistan in Eastern Iran

Authors: Mahyar MehrAfarin

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The Sistan region in eastern Iran is a significant archaeological area in Iran and the Middle East, encompassing 10,000 square kilometers. Previous archeological field surveys have identified 1662 ancient sites dating from prehistoric periods to the Islamic period. Research Aim: This article aims to explore the utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, and the benefits derived from their implementation. Methodology: The research employs a descriptive-analytical approach combined with field methods. New technologies and software, such as GPS, drones, magnetometers, equipped cameras, satellite images, and software programs like GIS, Map source, and Excel, were utilized to collect information and analyze data. Findings: The use of modern technologies and computers in archaeological field surveys proved to be essential. Traditional archaeological activities, such as excavation and field surveys, are time-consuming and costly. Employing modern technologies helps in preserving ancient sites, accurately recording archaeological data, reducing errors and mistakes, and facilitating correct and accurate analysis. Creating a comprehensive and accessible database, generating statistics, and producing graphic designs and diagrams are additional advantages derived from the use of efficient technologies in archaeology. Theoretical Importance: The integration of computers and modern technologies in archaeology contributes to interdisciplinary collaborations and facilitates the involvement of specialists from various fields, such as geography, history, art history, anthropology, laboratory sciences, and computer engineering. The utilization of computers in archaeology spanned across diverse areas, including database creation, statistical analysis, graphics implementation, laboratory and engineering applications, and even artificial intelligence, which remains an unexplored area in Iranian archaeology. Data Collection and Analysis Procedures: Information was collected using modern technologies and software, capturing geographic coordinates, aerial images, archeogeophysical data, and satellite images. This data was then inputted into various software programs for analysis, including GIS, Map source, and Excel. The research employed both descriptive and analytical methods to present findings effectively. Question Addressed: The primary question addressed in this research is how the use of modern technologies and computers in archeological field surveys in Sistan, Iran, can enhance archaeological data collection, preservation, analysis, and accessibility. Conclusion: The utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, has proven to be necessary and beneficial. These technologies aid in preserving ancient sites, accurately recording archaeological data, reducing errors, and facilitating comprehensive analysis. The creation of accessible databases, statistics generation, graphic designs, and interdisciplinary collaborations are further advantages observed. It is recommended to explore the potential of artificial intelligence in Iranian archaeology as an unexplored area. The research has implications for cultural heritage organizations, archaeology students, and universities involved in archaeological field surveys in Sistan and Baluchistan province. Additionally, it contributes to enhancing the understanding and preservation of Iran's archaeological heritage.

Keywords: Iran, sistan, archaeological surveys, computer use, modern technologies

Procedia PDF Downloads 79
853 Simulation of Flow through Dam Foundation by FEM and ANN Methods Case Study: Shahid Abbaspour Dam

Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

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In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

Procedia PDF Downloads 474
852 Imports of Intermediate Inputs: A Study of the Main Research Streams

Authors: Marta Fernández Olmos, Jorge Fleta, Talia Gómez

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This article shares the results of a temporal analysis of the literature on imports of intermediate inputs based on review techniques. The aim of this paper is to identify the main lines of research, their trends, topics, and the research agenda. The internationalization field has attracted considerable scholars and practitioners’ attention in recent years and has grown, rapidly, resulting in a large body of knowledge scattered in different areas of specialization. However, there are no studies that are entirely restricted to imports, intermediate inputs and innovation performance. The performance analysis provided an updated overview of the evolution of the importing literature from 1970 to 2022 and quantitatively identified the most productive and influential journals, articles, authors, and countries. The results show that the current topics are mainly based on modes of importing, innovation performance of importing intermediate imports and collaborations. Future lines of research are identified from topics with lower co-occurrence, such as artificial intelligence, entrepreneurship, and alternative business models such as multinational enterprises (MNEs) versus non-MNEs.

Keywords: imports, intermediate inputs, innovation performance, review

Procedia PDF Downloads 74
851 Rising of Single and Double Bubbles during Boiling and Effect of Electric Field in This Process

Authors: Masoud Gholam Ale Mohammad, Mojtaba Hafezi Birgani

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An experimental study of saturated pool boiling on a single artificial nucleation site without and with the application of an electric field on the boiling surface has been conducted. N-pentane is boiling on a copper surface and is recorded with a high speed camera providing high quality pictures and movies. The accuracy of the visualization allowed establishing an experimental bubble growth law from a large number of experiments. This law shows that the evaporation rate is decreasing during the bubble growth, and underlines the importance of liquid motion induced by the preceding bubble. Bubble rise is therefore studied: once detached, bubbles accelerate vertically until reaching a maximum velocity in good agreement with a correlation from literature. The bubbles then turn to another direction. The effect of applying an electric field on the boiling surface in finally studied. In addition to changes in the bubble shape, changes are also shown in the liquid plume and the convective structures above the surface. Lower maximum rising velocities were measured in the presence of electric fields, especially with a negative polarity.

Keywords: single and double bubbles, electric field, boiling, rising

Procedia PDF Downloads 226
850 Chatbots vs. Websites: A Comparative Analysis Measuring User Experience and Emotions in Mobile Commerce

Authors: Stephan Boehm, Julia Engel, Judith Eisser

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During the last decade communication in the Internet transformed from a broadcast to a conversational model by supporting more interactive features, enabling user generated content and introducing social media networks. Another important trend with a significant impact on electronic commerce is a massive usage shift from desktop to mobile devices. However, a presentation of product- or service-related information accumulated on websites, micro pages or portals often remains the pivot and focal point of a customer journey. A more recent change of user behavior –especially in younger user groups and in Asia– is going along with the increasing adoption of messaging applications supporting almost real-time but asynchronous communication on mobile devices. Mobile apps of this type cannot only provide an alternative for traditional one-to-one communication on mobile devices like voice calls or short messaging service. Moreover, they can be used in mobile commerce as a new marketing and sales channel, e.g., for product promotions and direct marketing activities. This requires a new way of customer interaction compared to traditional mobile commerce activities and functionalities provided based on mobile web-sites. One option better aligned to the customer interaction in mes-saging apps are so-called chatbots. Chatbots are conversational programs or dialog systems simulating a text or voice based human interaction. They can be introduced in mobile messaging and social media apps by using rule- or artificial intelligence-based imple-mentations. In this context, a comparative analysis is conducted to examine the impact of using traditional websites or chatbots for promoting a product in an impulse purchase situation. The aim of this study is to measure the impact on the customers’ user experi-ence and emotions. The study is based on a random sample of about 60 smartphone users in the group of 20 to 30-year-olds. Participants are randomly assigned into two groups and participate in a traditional website or innovative chatbot based mobile com-merce scenario. The chatbot-based scenario is implemented by using a Wizard-of-Oz experimental approach for reasons of sim-plicity and to allow for more flexibility when simulating simple rule-based and more advanced artificial intelligence-based chatbot setups. A specific set of metrics is defined to measure and com-pare the user experience in both scenarios. It can be assumed, that users get more emotionally involved when interacting with a system simulating human communication behavior instead of browsing a mobile commerce website. For this reason, innovative face-tracking and analysis technology is used to derive feedback on the emotional status of the study participants while interacting with the website or the chatbot. This study is a work in progress. The results will provide first insights on the effects of chatbot usage on user experiences and emotions in mobile commerce environments. Based on the study findings basic requirements for a user-centered design and implementation of chatbot solutions for mobile com-merce can be derived. Moreover, first indications on situations where chatbots might be favorable in comparison to the usage of traditional website based mobile commerce can be identified.

Keywords: chatbots, emotions, mobile commerce, user experience, Wizard-of-Oz prototyping

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849 Rheological Characteristics of Ice Slurries Based on Propylene- and Ethylene-Glycol at High Ice Fractions

Authors: Senda Trabelsi, Sébastien Poncet, Michel Poirier

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Ice slurries are considered as a promising phase-changing secondary fluids for air-conditioning, packaging or cooling industrial processes. An experimental study has been here carried out to measure the rheological characteristics of ice slurries. Ice slurries consist in a solid phase (flake ice crystals) and a liquid phase. The later is composed of a mixture of liquid water and an additive being here either (1) Propylene-Glycol (PG) or (2) Ethylene-Glycol (EG) used to lower the freezing point of water. Concentrations of 5%, 14% and 24% of both additives are investigated with ice mass fractions ranging from 5% to 85%. The rheological measurements are carried out using a Discovery HR-2 vane-concentric cylinder with four full-length blades. The experimental results show that the behavior of ice slurries is generally non-Newtonian with shear-thinning or shear-thickening behaviors depending on the experimental conditions. In order to determine the consistency and the flow index, the Herschel-Bulkley model is used to describe the behavior of ice slurries. The present results are finally validated against an experimental database found in the literature and the predictions of an Artificial Neural Network model.

Keywords: ice slurry, propylene-glycol, ethylene-glycol, rheology

Procedia PDF Downloads 262
848 Image Captioning with Vision-Language Models

Authors: Promise Ekpo Osaine, Daniel Melesse

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Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.

Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score

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847 Parameter Tuning of Complex Systems Modeled in Agent Based Modeling and Simulation

Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems

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846 Bio-Mimetic Foot Design for Legged Locomotion over Unstructured Terrain

Authors: Hannah Kolano, Paul Nadan, Jeremy Ryan, Sophia Nielsen

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The hooves of goats and other ruminants, or the family Ruminantia, are uniquely structured to adapt to rough terrain. Their hooves possess a hard outer shell and a soft interior that allow them to both conform to uneven surfaces and hook onto prominent features. In an effort to apply this unique mechanism to a robotics context, artificial feet for a hexapedal robot have been designed based on the hooves of ruminants to improve the robot’s ability to traverse unstructured environments such as those found on a rocky planet or asteroid, as well as in earth-based environments such as rubble, caves, and mountainous regions. The feet were manufactured using a combination of 3D printing and polyurethane casting techniques and attached to a commercially available hexapedal robot. The robot was programmed with a terrain-adaptive gait and proved capable of traversing a variety of uneven surfaces and inclines. This development of more adaptable robotic feet allows legged robots to operate in a wider range of environments and expands their possible applications.

Keywords: biomimicry, legged locomotion, robotic foot design, ruminant feet, unstructured terrain navigation

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845 Monitoring the Phenomenon of Black Sand in Hurghada’s Artificial Lakes from Sources of Groundwater and Removal Techniques

Authors: Ahmed M. Noureldin, Khaled M. Naguib

Abstract:

This experimental investigation tries to identify the root cause of the black sand issue in one of the man-made lakes in a well-known Hurghada resort. The lake is nourished by the underground wells' source, which continuously empties into the Red Sea. Chemical testing was done by looking at spots of stinky black sand beneath the sandy lake surface. The findings on samples taken from several locations (wells, lake bottom sand samples, and clean sand with exact specifications as bottom sand) indicated the existence of organic sulfur bacteria that are responsible for the phenomena of black sand. Approximately 39.139 mg/kg of sulfide in the form of hydrogen sulfide was present in the lake bottom sand, while 1.145 mg/kg, before usage, was in the bare sand. The study also involved modeling with the GPS-X program for cleaning bottom sand that uses hydro cyclones as a physical-mechanical treatment method. The modeling findings indicated a Total Organic Carbon (TOC) removal effectiveness of 0.65%. The research recommended using hydro cyclones to routinely mechanically clear the sand from lake bottoms.

Keywords: man-made lakes, organic sulfur bacteria, total organic carbon, hydro cyclone

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844 Reinforcement Learning for Self Driving Racing Car Games

Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh

Abstract:

This research aims to create a reinforcement learning agent capable of racing in challenging simulated environments with a low collision count. We present a reinforcement learning agent that can navigate challenging tracks using both a Deep Q-Network (DQN) and a Soft Actor-Critic (SAC) method. A challenging track includes curves, jumps, and varying road widths throughout. Using open-source code on Github, the environment used in this research is based on the 1995 racing game WipeOut. The proposed reinforcement learning agent can navigate challenging tracks rapidly while maintaining low racing completion time and collision count. The results show that the SAC model outperforms the DQN model by a large margin. We also propose an alternative multiple-car model that can navigate the track without colliding with other vehicles on the track. The SAC model is the basis for the multiple-car model, where it can complete the laps quicker than the single-car model but has a higher collision rate with the track wall.

Keywords: reinforcement learning, soft actor-critic, deep q-network, self-driving cars, artificial intelligence, gaming

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843 The Relations of Volatile Compounds, Some Parameters and Consumer Preference of Commercial Fermented Milks in Thailand

Authors: Suttipong Phosuksirikul, Rawichar Chaipojjana, Arunsri Leejeerajumnean

Abstract:

The aim of research was to define the relations between volatile compounds, some parameters (pH, titratable acidity (TA), total soluble solid (TSS), lactic acid bacteria count) and consumer preference of commercial fermented milks. These relations tend to be used for controlling and developing new fermented milk product. Three leading commercial brands of fermented milks in Thailand were evaluated by consumers (n=71) using hedonic scale for four attributes (sweetness, sourness, flavour, and overall liking), volatile compounds using headspace-solid phase microextraction (HS-SPME) GC-MS, pH, TA, TSS and LAB count. Then the relations were analyzed by principal component analysis (PCA). The PCA data showed that all of four attributes liking scores were related to each other. They were also related to TA, TSS and volatile compounds. The related volatile compounds were mainly on fermented produced compounds including acetic acid, furanmethanol, furfural, octanoic acid and the volatiles known as artificial fruit flavour (beta pinene, limonene, vanillin, and ethyl vanillin). These compounds were provided the information about flavour addition in commercial fermented milk in Thailand.

Keywords: fermented milk, volatile compounds, preference, PCA

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842 Applied Bayesian Regularized Artificial Neural Network for Up-Scaling Wind Speed Profile and Distribution

Authors: Aghbalou Nihad, Charki Abderafi, Saida Rahali, Reklaoui Kamal

Abstract:

Maximize the benefit from the wind energy potential is the most interest of the wind power stakeholders. As a result, the wind tower size is radically increasing. Nevertheless, choosing an appropriate wind turbine for a selected site require an accurate estimate of vertical wind profile. It is also imperative from cost and maintenance strategy point of view. Then, installing tall towers or even more expensive devices such as LIDAR or SODAR raises the costs of a wind power project. Various models were developed coming within this framework. However, they suffer from complexity, generalization and lacks accuracy. In this work, we aim to investigate the ability of neural network trained using the Bayesian Regularization technique to estimate wind speed profile up to height of 100 m based on knowledge of wind speed lower heights. Results show that the proposed approach can achieve satisfactory predictions and proof the suitability of the proposed method for generating wind speed profile and probability distributions based on knowledge of wind speed at lower heights.

Keywords: bayesian regularization, neural network, wind shear, accuracy

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841 Adapting the Chemical Reaction Optimization Algorithm to the Printed Circuit Board Drilling Problem

Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

Abstract:

Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

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840 The Importance of Artificial Intelligence on Arts and Design

Authors: Mariam Adel Hakim Fouad

Abstract:

This quantitative examine investigates innovative arts teachers' perceptions regarding the implementation of an Inclusive innovative Arts curriculum. The study employs a descriptive method utilizing a 5-point Likert scale questionnaire comprising 15 objects to acquire data from innovative arts educators. The Census, with a disproportionate stratified sampling approach, became utilized to pick out 226 teachers from five academic circuits (Circuit A, B, C, D & E) within Offinso Municipality, Ghana. The findings suggest that most innovative arts instructors maintain a wonderful belief in enforcing an inclusive, innovative arts curriculum. Wonderful perceptions and attitudes amongst teachers are correlated with improved scholar engagement and participation in class sports. This has a look at recommends organizing workshops and in-carrier schooling periods centered on inclusive innovative arts schooling for creative Arts instructors. Moreover, it shows that colleges of education and universities accountable for trainer schooling integrate foundational guides in creative arts and special schooling into their number one schooling teacher training packages.

Keywords: arts-in-health, evidence based medicine, arts for health, expressive arts therapiesarts, cultural heritage, digitalization, ICTarts, design, font, identity

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839 Assessing Nutrient Concentration and Trophic Status of Brahma Sarover at Kurukshetra, India

Authors: Shailendra Kumar Patidar

Abstract:

Eutrophication of surface water is one of the most widespread environmental problems at present. Large number of pilgrims and tourists visit sacred artificial tank known as “Brahma Sarover” located at Kurukshetra, India to take holy dip and perform religious ceremonies. The sources of pollutants include impurities in feed water, mass bathing, religious offerings and windblown particulate matter. Studies so far have focused mainly on assessing water quality for bathing purpose by using physico-chemical and bacteriological parameters. No effort has been made to assess nutrient concentration and trophic status of the tank to take more appropriate measures for improving water quality on long term basis. In the present study, total nitrogen, total phosphorous and chlorophyll a measurements have been done to assess the nutrient level and trophic status of the tank. The results show presence of high concentration of nutrients and Chlorophyll a indicating mesotrophic and eutrophic state of the tank. Phosphorous has been observed as limiting nutrient in the tank water.

Keywords: Brahma Sarover, eutrophication, nutrients, trophic status

Procedia PDF Downloads 372