Search results for: user interface.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3337

Search results for: user interface.

1237 Implementation of Successive Interference Cancellation Algorithms in the 5g Downlink

Authors: Mokrani Mohamed Amine

Abstract:

In this paper, we have implemented successive interference cancellation algorithms in the 5G downlink. We have calculated the maximum throughput in Frequency Division Duplex (FDD) mode in the downlink, where we have obtained a value equal to 836932 b/ms. The transmitter is of type Multiple Input Multiple Output (MIMO) with eight transmitting and receiving antennas. Each antenna among eight transmits simultaneously a data rate of 104616 b/ms that contains the binary messages of the three users; in this case, the Cyclic Redundancy Check CRC is negligible, and the MIMO category is the spatial diversity. The technology used for this is called Non-Orthogonal Multiple Access (NOMA) with a Quadrature Phase Shift Keying (QPSK) modulation. The transmission is done in a Rayleigh fading channel with the presence of obstacles. The MIMO Successive Interference Cancellation (SIC) receiver with two transmitting and receiving antennas recovers its binary message without errors for certain values of transmission power such as 50 dBm, with 0.054485% errors when the transmitted power is 20dBm and with 0.00286763% errors for a transmitted power of 32 dBm(in the case of user 1) as well as with 0.0114705% errors when the transmitted power is 20 dBm also with 0.00286763% errors for a power of 24 dBm(in the case of user2) by applying the steps involved in SIC.

Keywords: 5G, NOMA, QPSK, TBS, LDPC, SIC, capacity

Procedia PDF Downloads 103
1236 Analysis of Brain Activities due to Differences in Running Shoe Properties

Authors: Kei Okubo, Yosuke Kurihara, Takashi Kaburagi, Kajiro Watanabe

Abstract:

Many of the ever-growing elderly population require exercise, such as running, for health management. One important element of a runner’s training is the choice of shoes for exercise; shoes are important because they provide the interface between the feet and road. When we purchase shoes, we may instinctively choose a pair after trying on many different pairs of shoes. Selecting the shoes instinctively may work, but it does not guarantee a suitable fit for running activities. Therefore, if we could select suitable shoes for each runner from the viewpoint of brain activities, it would be helpful for validating shoe selection. In this paper, we describe how brain activities show different characteristics during particular task, corresponding to different properties of shoes. Using five subjects, we performed a verification experiment, applying weight, softness, and flexibility as shoe properties. In order to affect the shoe property’s differences to the brain, subjects run for ten min. Before and after running, subjects conducted a paced auditory serial addition task (PASAT) as the particular task; and the subjects’ brain activities during the PASAT are evaluated based on oxyhemoglobin and deoxyhemoglobin relative concentration changes, measured by near-infrared spectroscopy (NIRS). When the brain works actively, oxihemoglobin and deoxyhemoglobin concentration drastically changes; therefore, we calculate the maximum values of concentration changes. In order to normalize relative concentration changes after running, the maximum value are divided by before running maximum value as evaluation parameters. The classification of the groups of shoes is expressed on a self-organizing map (SOM). As a result, deoxyhemoglobin can make clusters for two of the three types of shoes.

Keywords: brain activities, NIRS, PASAT, running shoes

Procedia PDF Downloads 373
1235 Time and Wavelength Division Multiplexing Passive Optical Network Comparative Analysis: Modulation Formats and Channel Spacings

Authors: A. Fayad, Q. Alqhazaly, T. Cinkler

Abstract:

In light of the substantial increase in end-user requirements and the incessant need of network operators to upgrade the capabilities of access networks, in this paper, the performance of the different modulation formats on eight-channels Time and Wavelength Division Multiplexing Passive Optical Network (TWDM-PON) transmission system has been examined and compared. Limitations and features of modulation formats have been determined to outline the most suitable design to enhance the data rate and transmission reach to obtain the best performance of the network. The considered modulation formats are On-Off Keying Non-Return-to-Zero (NRZ-OOK), Carrier Suppressed Return to Zero (CSRZ), Duo Binary (DB), Modified Duo Binary (MODB), Quadrature Phase Shift Keying (QPSK), and Differential Quadrature Phase Shift Keying (DQPSK). The performance has been analyzed by varying transmission distances and bit rates under different channel spacing. Furthermore, the system is evaluated in terms of minimum Bit Error Rate (BER) and Quality factor (Qf) without applying any dispersion compensation technique, or any optical amplifier. Optisystem software was used for simulation purposes.

Keywords: BER, DuoBinary, NRZ-OOK, TWDM-PON

Procedia PDF Downloads 149
1234 Intelligent Tooling Embedded Sensors for Monitoring the Wear of Cutting Tools in Turning Applications

Authors: Hatim Laalej, Jon Stammers

Abstract:

In machining, monitoring of tool wear is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Currently, the task of monitoring the wear on the cutting tool is carried out by the operator who performs manual inspections of the cutting tool, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from loss of productivity. The cutting tool consumable costs may also be higher than necessary when tools are changed before the end of their useful life. Furthermore, damage can be caused to the workpiece when tools are not changed soon enough leading to a significant increase in the costs of manufacturing. The present study is concerned with the development of break sensor printed on the flank surface of poly-crystalline diamond (PCD) cutting to perform on-line condition monitoring of the cutting tool used to machine Titanium Ti-6al-4v bar. The results clearly show that there is a strong correlation between the break sensor measurements and the amount of wear in the cutting tool. These findings are significant in that they help the user/operator of the machine tool to determine the condition of the cutting tool without the need of performing manual inspection, thereby reducing the manufacturing costs such as the machine down time.

Keywords: machining, manufacturing, tool wear, signal processing

Procedia PDF Downloads 245
1233 The Influence of Social Media on Gym Memberships in the UAE

Authors: Mohammad Obeidat

Abstract:

In recent years, social media has revolutionized the way businesses market their products and services. Platforms such as Instagram, Facebook, YouTube, and TikTok have become powerful tools for reaching large audiences and engaging with consumers in real-time. These platforms allow businesses to create visually appealing content, interact with customers, and leverage user-generated content to enhance brand visibility and credibility. Recent statistics indicate that businesses that actively participate in social media marketing see improvements in brand visibility, customer engagement, and revenue generation. For example, several studies reveal that 70% of business-to-consumer marketers have gained customers through Facebook. This study aims to contribute to the academic literature on social media marketing and consumer behavior, specifically within the context of the fitness industry in the UAE. The findings will provide valuable insights for gym and fitness center managers, marketers, and social media strategists looking to enhance their engagement with potential customers. By understanding the impact of social media on purchasing decisions, businesses can tailor their marketing efforts to meet consumer expectations better and drive membership growth.

Keywords: social media, consumer behavior, digital native, influencer

Procedia PDF Downloads 47
1232 The Implementation of the Multi-Agent Classification System (MACS) in Compliance with FIPA Specifications

Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). Microsoft's .NET windows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, implementation, multi-agent, SOA, autonomous, WCF

Procedia PDF Downloads 274
1231 Efficient Delivery of Biomaterials into Living Organism by Using Noble Metal Nanowire Injector

Authors: Kkochorong Park, Keun Cheon Kim, Hyoban Lee, Eun Ju Lee, Bongsoo Kim

Abstract:

Introduction of biomaterials such as DNA, RNA, proteins is important for many research areas. There are many methods to introduce biomaterials into living organisms like tissue and cells. To introduce biomaterials, several indirect methods including virus‐mediated delivery, chemical reagent (i.e., lipofectamine), electrophoresis have been used. Such methods are passive delivery using an endocytosis process of cell, reducing an efficiency of delivery. Unlike the indirect delivery method, it has been reported that a direct delivery of exogenous biomolecules into nucleus have been more efficient to expression or integration of biomolecules. Nano-sized material is beneficial for detect signal from cell or deliver stimuli/materials into the cell at cellular and molecular levels, due to its similar physical scale. Especially, because 1 dimensional (1D) nanomaterials such as nanotube, nanorod and nanowire with high‐aspect ratio have nanoscale geometry and excellent mechanical, electrical, and chemical properties, they could play an important role in molecular and cellular biology. In this study, by using single crystalline 1D noble metal nanowire, we fabricated nano-sized 1D injector which can successfully interface with living cells and directly deliver biomolecules into several types of cell line (i.e., stem cell, mammalian embryo) without inducing detrimental damages on living cell. This nano-bio technology could be a promising and robust tool for introducing exogenous biomaterials into living organism.

Keywords: DNA, gene delivery, nanoinjector, nanowire

Procedia PDF Downloads 275
1230 Single Chip Controller Design for Piezoelectric Actuators with Mixed Signal FPGA

Authors: Han-Bin Park, Taesam Kang, SunKi Hong, Jeong Hoi Gu

Abstract:

The piezoelectric material is being used widely for actuators due to its large power density with simple structure. It can generate a larger force than the conventional actuators with the same size. Furthermore, the response time of piezoelectric actuators is very short, and thus, it can be used for very fast system applications with compact size. To control the piezoelectric actuator, we need analog signal conditioning circuits as well as digital microcontrollers. Conventional microcontrollers are not equipped with analog parts and thus the control system becomes bulky compared with the small size of the piezoelectric devices. To overcome these weaknesses, we are developing one-chip micro controller that can handle analog and digital signals simultaneously using mixed signal FPGA technology. We used the SmartFusion™ FPGA device that integrates ARM®Cortex-M3, analog interface and FPGA fabric in a single chip and offering full customization. It gives more flexibility than traditional fixed-function microcontrollers with the excessive cost of soft processor cores on traditional FPGAs. In this paper we introduce the design of single chip controller using mixed signal FPGA, SmartFusion™[1] device. To demonstrate its performance, we implemented a PI controller for power driving circuit and a 5th order H-infinity controller for the system with piezoelectric actuator in the FPGA fabric. We also demonstrated the regulation of a power output and the operation speed of a 5th order H-infinity controller.

Keywords: mixed signal FPGA, PI control, piezoelectric actuator, SmartFusion™

Procedia PDF Downloads 520
1229 Emotion Oriented Students' Opinioned Topic Detection for Course Reviews in Massive Open Online Course

Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

Abstract:

Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

Procedia PDF Downloads 262
1228 Tribological Response of Self-Mated Zircaloy-4 under Varying Conditions

Authors: Bharat Kumar, Deepak Kumar, Vijay Chaudhry

Abstract:

Zirconium alloys are widely used for the core components of a pressurized heavy water reactor (PHWR) or Canada deuterium (CANDU) reactor due to their low neutron absorption cross-section and excellent mechanical properties. The components made of Zirconium alloys are subjected to flow-induced vibrations, resulting in fretting wear at the interface of; pressure tubes and bearing pads, pressure tubes and calandria tubes, and calandria tubes and Liquid injection shutdown system (LISS) nozzles. There is a need to explore the tribological response under such conditions. Present work simulates the contact between calandria tube and LISS nozzle of PHWR/CANDU reactor as cylinder-on-cylinder contact configuration. Reciprocating tribo-tests were conducted on Zircaloy-4 (Zr-4) under the self-mated condition at varying amplitude, frequency, and sliding time. To understand the active wear mechanism, worn surfaces were analyzed using Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS). The change in amplitude severely affects the wear than other factors. The wear mechanism transits from adhesion to abrasion with increasing test amplitude. The dominant wear mechanisms are micro-cutting and micro-plowing followed by delamination in some areas. However, the coefficient of friction has indifferent behaviors.

Keywords: zircaloy-4, tribology, calandria tube, LISS nozzle, PHWR

Procedia PDF Downloads 209
1227 Periodontal Disease or Cement Disease: New Frontier in the Treatment of Periodontal Disease in Dogs

Authors: C. Gallottini, W. Di Mari, A. Amaddeo, K. Barbaro, A. Dolci, G. Dolci, L. Gallottini, G. Barraco, S. Eramo

Abstract:

A group of 10 dogs (group A) with Periodontal Disease in the third stage, were subjected to regenerative therapy of periodontal tissues, by use of nano hydroxy apatite (NHA). These animals induced by general anesthesia, where treated by ultrasonic scaling, root planning, and at the end by a mucogingival flap in which it was applied NHA. The flap was closed and sutured with simple steps. Another group of 10 dogs (group B), control group, was treated only by scaling and root planning. No patient was subjected to antibiotic therapy. After three months, a check was made by inspection of the oral cavity, radiography and bone biopsy at the alveolar level. Group A showed a total restitutio ad integrum of the periodontal structures, and in group B still mild gingivitis in 70% of cases and 30% of the state remains unchanged. Numerous experimental studies both in animals and humans have documented that the grafts of porous hydroxyapatite are rapidly invaded by fibrovascular tissue which is subsequently converted into mature lamellar bone tissue by activating osteoblast. Since we acted on the removal of necrotic cementum and rehabilitating the root tissue by polishing without intervention in the ligament but only on anatomical functional interface of cement-blasts, we can connect the positive evolution of the clinical-only component of the cement that could represent this perspective, the only reason that Periodontal Disease become a Cement Disease, while all other clinical elements as nothing more than a clinical pathological accompanying.

Keywords: nanoidroxiaphatite, parodontal disease, cement disease, regenerative therapy

Procedia PDF Downloads 450
1226 A Review on Application of Phase Change Materials in Textiles Finishing

Authors: Mazyar Ahrari, Ramin Khajavi, Mehdi Kamali Dolatabadi, Tayebeh Toliyat, Abosaeed Rashidi

Abstract:

Fabric as the first and most common layer that is in permanent contact with human skin is a very good interface to provide coverage, as well as heat and cold insulation. Phase change materials (PCMs) are organic and inorganic compounds which have the capability of absorbing and releasing noticeable amounts of latent heat during phase transitions between solid and liquid phases at a low temperature range. PCMs come across phase changes (liquid-solid and solid-liquid transitions) during absorbing and releasing thermal heat; so, in order to use them for a long time, they should have been encapsulated in polymeric shells, so-called microcapsules. Microencapsulation and nanoencapsulation methods have been developed in order to reduce the reactivity of a PCM with outside environment, promoting the ease of handling, decreasing the diffusion and evaporation rates. Methods of incorporation of PCMs in textiles such as electrospinning and determining thermal properties had been summarized. Paraffin waxes catch a lot of attention due to their high thermal storage density, repeatability of phase change, thermal stability, small volume change during phase transition, chemical stability, non-toxicity, non-flammability, non-corrosive and low cost and they seem to play a key role in confronting with climate change and global warming. In this article, we aimed to review the researches concentrating on the characteristics of PCMs and new materials and methods of microencapsulation.

Keywords: thermoregulation, microencapsulation, phase change materials, thermal energy storage, nanoencapsulation

Procedia PDF Downloads 388
1225 An Eulerian Method for Fluid-Structure Interaction Simulation Applied to Wave Damping by Elastic Structures

Authors: Julien Deborde, Thomas Milcent, Stéphane Glockner, Pierre Lubin

Abstract:

A fully Eulerian method is developed to solve the problem of fluid-elastic structure interactions based on a 1-fluid method. The interface between the fluid and the elastic structure is captured by a level set function, advected by the fluid velocity and solved with a WENO 5 scheme. The elastic deformations are computed in an Eulerian framework thanks to the backward characteristics. We use the Neo Hookean or Mooney Rivlin hyperelastic models and the elastic forces are incorporated as a source term in the incompressible Navier-Stokes equations. The velocity/pressure coupling is solved with a pressure-correction method and the equations are discretized by finite volume schemes on a Cartesian grid. The main difficulty resides in that large deformations in the fluid cause numerical instabilities. In order to avoid these problems, we use a re-initialization process for the level set and linear extrapolation of the backward characteristics. First, we verify and validate our approach on several test cases, including the benchmark of FSI proposed by Turek. Next, we apply this method to study the wave damping phenomenon which is a mean to reduce the waves impact on the coastline. So far, to our knowledge, only simulations with rigid or one dimensional elastic structure has been studied in the literature. We propose to place elastic structures on the seabed and we present results where 50 % of waves energy is absorbed.

Keywords: damping wave, Eulerian formulation, finite volume, fluid structure interaction, hyperelastic material

Procedia PDF Downloads 323
1224 Thiazolo[5,4-D]Thiazole-Core Organic Chromophore with Furan Spacer for Organic Solar Cells

Authors: M. Nazim, S. Ameen, H. K. Seo, H. S. Shin

Abstract:

Energy is the basis of life and strong attention has been growing for the cost-effective energy production. Recently, solution-processed small molecule organic solar cells (SMOSCs) have grown much attention due to the wages such as well-defined molecular structures, definite molecular weight, easy synthesis and easy purification techniques. In particular, the size of donor (D) and acceptor (A) unit is a crucial factor for the exciton-diffusion towards D-A interface and then charge-separation for the effective charge-transport to the electrodes. Furan-bridged materials are more electron-rich, high fluorescence, with better molecular-packing, and greater rigidity and greater solubility than their thiophene-counterparts In this work, a furan-bridged thiazolo[5,4-d]thiazole based organic small molecule (RFTzR) was formulated and applied for BHJ organic solar cells (OSCs). The introduction of furan spacer with two terminal alkyl units improved its absorption and solubility in the common organic solvents, significantly. RFTzR exhibited a HOMO and LUMO energy levels of -5.36 eV and -3.14 eV, respectively. The fabricated solar cell devices of RFTzR (donor) with PC60BM (acceptor) as photoactive materials showed high performance of 2.72% (RFTzR:PC60BM, 2:1, w/w) ratio with open-circuit voltage of 0.756 V and high photocurrent density of 10.13 mA/cm².

Keywords: chromophore, organic solar cells, photoactive materials, small molecule

Procedia PDF Downloads 163
1223 Engagement Analysis Using DAiSEE Dataset

Authors: Naman Solanki, Souraj Mondal

Abstract:

With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

Procedia PDF Downloads 114
1222 Proposed Solutions Based on Affective Computing

Authors: Diego Adrian Cardenas Jorge, Gerardo Mirando Guisado, Alfredo Barrientos Padilla

Abstract:

A system based on Affective Computing can detect and interpret human information like voice, facial expressions and body movement to detect emotions and execute a corresponding response. This data is important due to the fact that a person can communicate more effectively with emotions than can be possible with words. This information can be processed through technological components like Facial Recognition, Gait Recognition or Gesture Recognition. As of now, solutions proposed using this technology only consider one component at a given moment. This research investigation proposes two solutions based on Affective Computing taking into account more than one component for emotion detection. The proposals reflect the levels of dependency between hardware devices and software, as well as the interaction process between the system and the user which implies the development of scenarios where both proposals will be put to the test in a live environment. Both solutions are to be developed in code by software engineers to prove the feasibility. To validate the impact on society and business interest, interviews with stakeholders are conducted with an investment mind set where each solution is labeled on a scale of 1 through 5, being one a minimum possible investment and 5 the maximum.

Keywords: affective computing, emotions, emotion detection, face recognition, gait recognition

Procedia PDF Downloads 369
1221 ChatGPT 4.0 Demonstrates Strong Performance in Standardised Medical Licensing Examinations: Insights and Implications for Medical Educators

Authors: K. O'Malley

Abstract:

Background: The emergence and rapid evolution of large language models (LLMs) (i.e., models of generative artificial intelligence, or AI) has been unprecedented. ChatGPT is one of the most widely used LLM platforms. Using natural language processing technology, it generates customized responses to user prompts, enabling it to mimic human conversation. Responses are generated using predictive modeling of vast internet text and data swathes and are further refined and reinforced through user feedback. The popularity of LLMs is increasing, with a growing number of students utilizing these platforms for study and revision purposes. Notwithstanding its many novel applications, LLM technology is inherently susceptible to bias and error. This poses a significant challenge in the educational setting, where academic integrity may be undermined. This study aims to evaluate the performance of the latest iteration of ChatGPT (ChatGPT4.0) in standardized state medical licensing examinations. Methods: A considered search strategy was used to interrogate the PubMed electronic database. The keywords ‘ChatGPT’ AND ‘medical education’ OR ‘medical school’ OR ‘medical licensing exam’ were used to identify relevant literature. The search included all peer-reviewed literature published in the past five years. The search was limited to publications in the English language only. Eligibility was ascertained based on the study title and abstract and confirmed by consulting the full-text document. Data was extracted into a Microsoft Excel document for analysis. Results: The search yielded 345 publications that were screened. 225 original articles were identified, of which 11 met the pre-determined criteria for inclusion in a narrative synthesis. These studies included performance assessments in national medical licensing examinations from the United States, United Kingdom, Saudi Arabia, Poland, Taiwan, Japan and Germany. ChatGPT 4.0 achieved scores ranging from 67.1 to 88.6 percent. The mean score across all studies was 82.49 percent (SD= 5.95). In all studies, ChatGPT exceeded the threshold for a passing grade in the corresponding exam. Conclusion: The capabilities of ChatGPT in standardized academic assessment in medicine are robust. While this technology can potentially revolutionize higher education, it also presents several challenges with which educators have not had to contend before. The overall strong performance of ChatGPT, as outlined above, may lend itself to unfair use (such as the plagiarism of deliverable coursework) and pose unforeseen ethical challenges (arising from algorithmic bias). Conversely, it highlights potential pitfalls if users assume LLM-generated content to be entirely accurate. In the aforementioned studies, ChatGPT exhibits a margin of error between 11.4 and 32.9 percent, which resonates strongly with concerns regarding the quality and veracity of LLM-generated content. It is imperative to highlight these limitations, particularly to students in the early stages of their education who are less likely to possess the requisite insight or knowledge to recognize errors, inaccuracies or false information. Educators must inform themselves of these emerging challenges to effectively address them and mitigate potential disruption in academic fora.

Keywords: artificial intelligence, ChatGPT, generative ai, large language models, licensing exam, medical education, medicine, university

Procedia PDF Downloads 32
1220 Mountain Photo Sphere: An Android Application of Mountain Hiking Street View

Authors: Yanto Budisusanto, Aulia Rachmawati

Abstract:

Land navigation technology that is being developed is Google Street View to provide 360° street views, enabling the user to know the road conditions physically with the photo display. For climbers, especially beginners, detail information of climbing terrain is needed so climbers can prepare supplies and strategies before climbing. Therefore, we built a mountaineer guide application named Mountain Photo Sphere. This application displays a 360̊ panoramic view of mountain hiking trail and important points along the hiking path and its surrounding conditions. By combining panoramic photos 360̊ and tracking paths from coordinate data, a virtual tour will be formed. It is built using Java language and Android Studio. The hiking trail map composed by Google Maps API (Gaining access to google maps), Google GEO API (Gaining access to google maps), and OpenStreetMap API (Getting map files to be accessed offline on the Application). This application can be accessed offline so that climbers can use the application during climbing activities.

Keywords: google street view, panoramic photo 360°, mountain hiking, mountain photo sphere

Procedia PDF Downloads 166
1219 Hygrothermal Performance of Sheep Wool in Cold and Humid Climates

Authors: Yuchen Chen, Dehong Li, Bin Li, Denis Rodrigue, Xiaodong (Alice) Wang

Abstract:

When selecting insulation materials, not only should their thermal efficiency be considered, but also their impact on the environment. Compared to conventional insulation materials, bio-based materials not only have comparable thermal performance, but they also have a lower embodied energy. Sheep wool has the advantages of low negative health impact, high fire resistance, eco-friendliness, and high moisture resistance. However, studies on applying sheep wool insulation in cold and humid climates are still insufficient. The purpose of this study is to simulate the hygrothermal performance of sheep wool insulation for the Quebec City climate, as well as analyze the mold growth risks. The results show that a sheep wool wall has better thermal performance than a reference wall and that both meet the minimum requirements of the Quebec Code for the thermal performance of above-ground walls. The total water content indicates that the sheep wool wall can reach dynamic equilibrium in the Quebec climate and can dry out. At the same time, a delay of almost four months in the maximum total water content indicates that the sheep wool wall has high moisture absorption compared to the reference wall. The hygrothermal profiles show that the sheathing-insulation interface of both walls is at the highest risk for condensation. When the interior surface gypsum was replaced by stucco, the mold index significantly dropped.

Keywords: sheep wool, water content, hygrothermal performance, mould growth risk

Procedia PDF Downloads 91
1218 Architecture for Multi-Unmanned Aerial Vehicles Based Autonomous Precision Agriculture Systems

Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

Abstract:

The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

Procedia PDF Downloads 114
1217 Myers-Briggs Type Index Personality Type Classification Based on an Individual’s Spotify Playlists

Authors: Sefik Can Karakaya, Ibrahim Demir

Abstract:

In this study, the relationship between musical preferences and personality traits has been investigated in terms of Spotify audio analysis features. The aim of this paper is to build such a classifier capable of segmenting people into their Myers-Briggs Type Index (MBTI) personality type based on their Spotify playlists. Music takes an important place in the lives of people all over the world and online music streaming platforms make it easier to reach musical contents. In this context, the motivation to build such a classifier is allowing people to gain access to their MBTI personality type and perhaps for more reliably and more quickly. For this purpose, logistic regression and deep neural networks have been selected for classifier and their performances are compared. In conclusion, it has been found that musical preferences differ statistically between personality traits, and evaluated models are able to distinguish personality types based on given musical data structure with over %60 accuracy rate.

Keywords: myers-briggs type indicator, music psychology, Spotify, behavioural user profiling, deep neural networks, logistic regression

Procedia PDF Downloads 144
1216 Role of Community Forestry to Address Climate Change in Nepal

Authors: Laxmi Prasad Bhattarai

Abstract:

Climate change is regarded as one of the most fundamental threats to sustainable livelihood and global development. There is a growing global concern in linking community-managed forests as potential climate change mitigation projects. This study was conducted to explore local people’s perception on climate change and the role of community forestry (CF) to combat climate change impacts. Two active community forest user groups (CFUGs) from Kaski and Syangja Districts in Nepal were selected as study sites, and various participatory tools were applied to collect primary data. Although most of the respondents were unaware about the words “Climate Change” in study sites, they were quite familiar with the irregularities in rainfall season and other weather extremities. 60% of the respondents had the idea that, due to increase in precipitation, there is a frequent occurrence of erosion, floods, and landslide. Around 85% of the people agreed that community forests help in stabilizing soil, reducing the natural hazards like erosion, landslide. Biogas as an alternative source of cooking energy, and changes in crops and their varieties are the common adaptation measures that local people start practicing in both CFUGs in Nepal.

Keywords: community forestry, climate change, global warming, adaptation, Nepal

Procedia PDF Downloads 305
1215 Development of Basic Patternmaking Using Parametric Modelling and AutoLISP

Authors: Haziyah Hussin, Syazwan Abdul Samad, Rosnani Jusoh

Abstract:

This study is aimed towards the automisation of basic patternmaking for traditional clothes for the purpose of mass production using AutoCAD to apply AutoLISP feature under software Hazi Attire. A standard dress form (industrial form) with the size of small (S), medium (M) and large (L) size is measured using full body scanning machine. Later, the pattern for the clothes is designed parametrically based on the measured dress form. Hazi Attire program is used within the framework of AutoCAD to generate the basic pattern of front bodice, back bodice, front skirt, back skirt and sleeve block (sloper). The generation of pattern is based on the parameters inputted by user, whereby in this study, the parameters were determined based on the measured size of dress form. The finalized pattern parameter shows that the pattern fit perfectly on the dress form. Since the pattern is generated almost instantly, these proved that using the AutoLISP programming, the manufacturing lead time for the mass production of the traditional clothes can be decreased.

Keywords: apparel, AutoLISP, Malay traditional clothes, pattern ganeration

Procedia PDF Downloads 256
1214 Hydrogen Production Using an Anion-Exchange Membrane Water Electrolyzer: Mathematical and Bond Graph Modeling

Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

Abstract:

Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

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1213 Automatic Teller Machine System Security by Using Mobile SMS Code

Authors: Husnain Mushtaq, Mary Anjum, Muhammad Aleem

Abstract:

The main objective of this paper is used to develop a high security in Automatic Teller Machine (ATM). In these system bankers will collect the mobile numbers from the customers and then provide a code on their mobile number. In most country existing ATM machine use the magnetic card reader. The customer is identifying by inserting an ATM card with magnetic card that hold unique information such as card number and some security limitations. By entering a personal identification number, first the customer is authenticated then will access bank account in order to make cash withdraw or other services provided by the bank. Cases of card fraud are another problem once the user’s bank card is missing and the password is stolen, or simply steal a customer’s card & PIN the criminal will draw all cash in very short time, which will being great financial losses in customer, this type of fraud has increase worldwide. So to resolve this problem we are going to provide the solution using “Mobile SMS code” and ATM “PIN code” in order to improve the verify the security of customers using ATM system and confidence in the banking area.

Keywords: PIN, inquiry, biometric, magnetic strip, iris recognition, face recognition

Procedia PDF Downloads 365
1212 Towards an Adversary-Aware ML-Based Detector of Spam on Twitter Hashtags

Authors: Niddal Imam, Vassilios G. Vassilakis

Abstract:

After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

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1211 A Study on the Reinforced Earth Walls Using Sandwich Backfills under Seismic Loads

Authors: Kavitha A.S., L.Govindaraju

Abstract:

Reinforced earth walls offer excellent solution to many problems associated with earth retaining structures especially under seismic conditions. Use of cohesive soils as backfill material reduces the cost of reinforced soil walls if proper drainage measures are taken. This paper presents a numerical study on the application of a new technique called sandwich technique in reinforced earth walls. In this technique, a thin layer of granular soil is placed above and below the reinforcement layer to initiate interface friction and the remaining portion of the backfill is filled up using the existing insitu cohesive soil. A 6 m high reinforced earth wall has been analysed as a two-dimensional plane strain finite element model. Three types of reinforcing elements such as geotextile, geogrid and metallic strips were used. The horizontal wall displacements and the tensile loads in the reinforcement were used as the criteria to evaluate the results at the end of construction and dynamic excitation phases. Also to verify the effectiveness of sandwich layer on the performance of the wall, the thickness of sand fill surrounding the reinforcement was varied. At the end of construction stage it is found that the wall with sandwich type backfill yielded lower displacements when compared to the wall with cohesive soil as backfill. Also with sandwich backfill, the reinforcement loads reduced substantially when compared to the wall with cohesive soil as backfill. Further, it is found that sandwich technique as backfill and geogrid as reinforcement is a good combination to reduce the deformations of geosynthetic reinforced walls during seismic loading.

Keywords: geogrid, geotextile, reinforced earth, sandwich technique

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1210 Generating Spherical Surface of Wear Drain in Cutting Metal by Finite Element Method Analysis

Authors: D. Kabeya Nahum, L. Y. Kabeya Mukeba

Abstract:

In this work, the design of surface defects some support of the anchor rod ball joint. The future adhesion contact was rocking in manufacture machining, for giving by the numerical analysis of a short simple solution of thermo-mechanical coupled problem in process engineering. The analysis of geometrical evaluation and the quasi-static and dynamic states are discussed in kinematic dimensional tolerances onto surfaces of part. Geometric modeling using the finite element method (FEM) in rough part of such phase provides an opportunity to solve the nonlinearity behavior observed by empirical data to improve the discrete functional surfaces. The open question here is to obtain spherical geometry of drain wear with the operation of rolling. The formulation with (1 ± 0.01) mm thickness near the drain wear semi-finishing tool for studying different angles, do not help the professional factor in design cutting metal related vibration, friction and interface solid-solid of part and tool during this physical complex process, with multi-parameters no-defined in Sobolev Spaces. The stochastic approach of cracking, wear and fretting due to the cutting forces face boundary layers small dimensions thickness of the workpiece and the tool in the machining position is predicted neighbor to ‘Yakam Matrix’.

Keywords: FEM, geometry, part, simulation, spherical surface engineering, tool, workpiece

Procedia PDF Downloads 274
1209 Information Seekers vs. Information Providers: New Vistas and New Challenges for the Libraries Today; A Case Study of the Panjab University Library, Chandigarh, India

Authors: Neeru Bhatia

Abstract:

This article presents the results of a case study designed to analyze and deduce Information seekers and the Information Providers in today’s context, wherein we come across a sea of change in the provision of Information services due to the changing electronic environment. The Panjab University Library is one of the biggest libraries of India and was inaugurated in 1963 by Pt. Jawaharlal Nehru, the then Prime Minister of India. The library always thrives to assimilate new technology for the provision of Information services. As we know that the Information seekers today are a whole lot different, they are tech savvy, like to be on their electronic gadgets most of the time, and their Information seeking patterns are also different, the challenge that lies before the libraries is to be always ready for these day to day challenges. The study explores the current status of the Information Services being provided by the Panjab University Library (the Information Providers) vs. the evaluation of these Information services by the users of Library (the Information Seekers). The present study aimed at finding out whether Panjab University Library is able to achieve its mission to be an innovative and user-oriented library by exploring all the new vistas and reach up to the expectations of the information seekers by taking up all the challenges being posed by the ever changing technological scenario.

Keywords: electronic environment, information seekers, information providers, new technology

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1208 Implementing a Neural Network on a Low-Power and Mobile Cluster to Aide Drivers with Predictive AI for Traffic Behavior

Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj

Abstract:

New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.

Keywords: CS pedagogy, student research, cluster computing, machine learning

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