Search results for: stream computing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1590

Search results for: stream computing

660 Deploying a Platform as a Service Cloud Solution to Support Student Learning

Authors: Jiangping Wang

Abstract:

This presentation describes the design and implementation of PaaS (platform as a service) cloud-based labs that are used in database-related courses to teach students practical skills. Traditionally, all labs are implemented in a desktop-based environment where students have to install heavy client software to access database servers. In order to release students from that burden, we have successfully deployed the cloud-based solution to support database-related courses, from which students and teachers can practice and learn database topics in various database courses via cloud access. With its development environment, execution runtime, web server, database server, and collaboration capability, it offers a shared pool of configurable computing resources and comprehensive environment that supports students’ needs without the complexity of maintaining the infrastructure.

Keywords: PaaS, database environment, e-learning, web server

Procedia PDF Downloads 255
659 An Early Detection Type 2 Diabetes Using K - Nearest Neighbor Algorithm

Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

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This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among the people living in Malaysia using Particle Swarm Optimized Artificial. With the skyrocketing prevalence of Type 2 diabetes in Malaysia, the system can be used to encourage affected people to seek further medical attention to prevent the onset of diabetes or start managing it early enough to avoid the associated complications. The study sought to find out the best predictive variables of Type 2 Diabetes Mellitus, developed a system to diagnose diabetes from the variables using Artificial Neural Networks and tested the system on accuracy to find out the patent generated from diabetes diagnosis result in machine learning algorithms even at primary or advanced stages.

Keywords: diabetes diagnosis, Artificial Neural Networks, artificial intelligence, soft computing, medical diagnosis

Procedia PDF Downloads 316
658 New Approaches to the Determination of the Time Costs of Movements

Authors: Dana Kristalova

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This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms, etc. have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is surface of the terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for commander´s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: surface of a terrain, movement of vehicles, geographical factor, optimization of routes

Procedia PDF Downloads 446
657 Predicting Data Center Resource Usage Using Quantile Regression to Conserve Energy While Fulfilling the Service Level Agreement

Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

Procedia PDF Downloads 93
656 Assessing the Suitability of South African Waste Foundry Sand as an Additive in Clay Masonry Products

Authors: Nthabiseng Portia Mahumapelo, Andre van Niekerk, Ndabenhle Sosibo, Nirdesh Singh

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The foundry industry generates large quantities of solid waste in the form of waste foundry sand. The ever-increasing quantities of this type of industrial waste put pressure on land-filling space and its proper management has become a global concern. The South African foundry industry is not different when it comes to this solid waste generation. Utilizing the foundry waste sand in other applications has become an attractive avenue to deal with this waste stream. In the present paper, an evaluation was done on the suitability of foundry waste sand as an additive in clay masonry products. Purchased clay was added to the foundry waste sand sample in a 50/50 ratio. The mixture was named FC sample. The FC sample was mixed with water in a pan mixer until the mixture was consistent and suitable for extrusion. The FC sample was extruded and cut into briquettes. Water absorption, shrinkage and modulus of rupture tests were conducted on the resultant briquettes. Foundry waste sand and FC samples were respectively characterized mineralogically using X-Ray Diffraction, and the major and trace elements were determined using Inductively Coupled Plasma Optical Emission Spectroscopy. Adding purchased clay to the foundry waste sand positively influenced the workability of the test sample. Another positive characteristic was the low linear shrinkage, which indicated that products manufactured from the FC sample would not be susceptible to cracking. The water absorption values were acceptable and the unfired and fired strength values of the briquette’s samples were acceptable. In conclusion, tests showed that foundry waste sand can be used as an additive in masonry clay bricks, provided it is blended with good quality clay.

Keywords: foundry waste sand, masonry clay bricks, modulus of rupture, shrinkage

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655 Computational Analysis on Thermal Performance of Chip Package in Electro-Optical Device

Authors: Long Kim Vu

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The central processing unit in Electro-Optical devices is a Field-programmable gate array (FPGA) chip package allowing flexible, reconfigurable computing but energy consumption. Because chip package is placed in isolated devices based on IP67 waterproof standard, there is no air circulation and the heat dissipation is a challenge. In this paper, the author successfully modeled a chip package which various interposer materials such as silicon, glass and organics. Computational fluid dynamics (CFD) was utilized to analyze the thermal performance of chip package in the case of considering comprehensive heat transfer modes: conduction, convection and radiation, which proposes equivalent heat dissipation. The logic chip temperature varying with time is compared between the simulation and experiment results showing the excellent correlation, proving the reasonable chip modeling and simulation method.

Keywords: CFD, FPGA, heat transfer, thermal analysis

Procedia PDF Downloads 171
654 Occurrence and Fate of EDCs in Wastewater and Aquatic Environments in the West Bank of Palestine

Authors: Wa`d Odeh, Alon Tal, Alfred Abed Rabbo, Nader Al Khatib, Shai Arnon

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The presence of endocrine disrupting compounds (EDCs) in raw sewage and effluents from wastewater treatment plants (WWTPs) has been increasingly studied in the last few decades. Higher risks are said to characterize situations where raw sewage streams are found to be flowing, or where partial and inadequate wastewater treatment exists. Such conditions are prevalent in the West Bank area of Palestine. To our knowledge, no previous data concerning the occurrence and fate of EDCs in the aquatic environment has ever been systematically evaluated in the region. Hence, the main objective of this study was to identify the occurrence and concentrations of major EDCs in raw sewage, wastewater effluents produced by treatment plants and in the receiving environments, including streams and groundwater in the West Bank, Palestine. Water samples were collected and analyzed for four times during the years of 2013 and 2014. Two large-scale conventional activated sludge WWTPs, two wastewater watercourses, one naturally perennial stream, and five groundwater locations close to wastewater sources were sampled and analyzed by GC/MS following EPA methods (525.2). Five EDCs (estriol, estrone, testosterone, bisphenol A, and octylphenol) were detected in trace concentrations (ng/l) in wastewater streams and at inputs to WWTPs. WWTPs were not able to achieve complete removal of all EDCs, and EDCs were still found in the effluents. In this regard, the most significant environmental estrogenic impact was due to estrone concentrations. Nevertheless, no EDCs were detected in groundwater. Yet, in order for effluents to be reused, significant improvement in treatment infrastructure should be a top priority for environmental managers in the region.

Keywords: endocrine disrupting compounds, raw sewage streams, conventional activated sludge WWTPs, WWTPs effluents

Procedia PDF Downloads 387
653 When Your Change The Business Model ~ You Change The World

Authors: H. E. Amb. Terry Earthwind Nichols

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Over the years Ambassador Nichols observed that successful companies all have one thing in common - belief in people. His observations of people in many companies, industries, and countries have also concluded one thing - groups of achievers far exceed the expectations and timelines of their superiors. His experience with achieving this has brought forth a model for the 21st century that will not only exceed expectations of companies, but it will also set visions for the future of business globally. It is time for real discussion around the future of work and the business model that will set the example for the world. Methodologies: In-person observations over 40 years – Ambassador Nichols present during the observations. Audio-visual observations – TV, Cinema, social media (YouTube, etc.), various news outlet Reading the autobiography of some of successful leaders over the last 75 years that lead their companies from a distinct perspective your people are your commodity. Major findings: People who believe in the leader’s vision for the company so much so that they remain excited about the future of the company and want to do anything in their power to ethically achieve that vision. People who are achieving regularly in groups, division, companies, etcetera: Live more healthfully lowering both sick time off and on-the-job accidents. Cannot wait to physically get to work as much as they can to feed off the high energy present in these companies. They are fully respected and supported resulting in near zero attrition. Simply put – they do not “Burn Out”. Conclusion: To the author’s best knowledge, 20th century practices in business are no longer valid and people are not going to work in those environments any longer. The average worker in the post-covid world is better educated than 50 years ago and most importantly, they have real-time information about any subject and can stream injustices as they happen. The Consortium Model is just the model for the evolution of both humankind and business in the 21st century.

Keywords: business model, future of work, people, paradigm shift, business management

Procedia PDF Downloads 60
652 Learning Grammars for Detection of Disaster-Related Micro Events

Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

Procedia PDF Downloads 465
651 A Quality Index Optimization Method for Non-Invasive Fetal ECG Extraction

Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

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Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

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650 Impact of Biological Treatment Effluent on the Physico-Chemical Quality of a Receiving Stream in Ile-Ife, Southwest Nigeria

Authors: Asibor Godwin, Adeniyi Funsho

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This study was carried out to investigate the impact of biological treated effluent on the physico-chemical properties of receiving waterbodies and also to establish its suitability for other purposes. It focused on the changes of some physic-chemical variables as one move away from the point of discharge downstream of the waterbodies. Water samples were collected from 14 sampling stations made up of the untreated effluent, treated effluent and receiving streams (before and after treated effluent discharge) over a period of 6 months spanning the dry and rainy seasons. Analyses were carried out on the following: temperature, turbidity, pH, conductivity, major anions and cation, dissolved oxygen, percentage oxygen Saturation, biological oxygen demand (BOD), solids (total solids, suspended solids and dissolved solids), nitrates, phosphates, organic matter and flow discharge using standard analytical methods. The relationships between investigated sites with regards to their physico-chemical properties were analyzed using student-t statistics. Also changes in the treated effluent receiving streams after treated effluent outfall was discussed fully. The physico-chemical water quality of the receiving water bodies meets most of the general water requirements for both domestic and industrial uses. The untreated effluent quality was shown to be of biological origin based on the biological oxygen demand, chloride, dissolved oxygen, total solids, pH and organic matter. The treated effluent showed significant improvement over the raw untreated effluent based on most parameters assessed. There was a significant difference (p<0.05) between the physico-chemical quality of untreated effluent and the treated effluent for the most of the investigated physico-chemical quality. The difference between the discharged treated effluent and the unimpacted section of the receiving waterbodies was also significant (p<0.05) for the most of the physico-chemical parameters.

Keywords: eflluent, Opa River, physico-chemical, waterbody

Procedia PDF Downloads 247
649 Modal FDTD Method for Wave Propagation Modeling Customized for Parallel Computing

Authors: H. Samadiyeh, R. Khajavi

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A new FD-based procedure, modal finite difference method (MFDM), is proposed for seismic wave propagation modeling, in which simulation is dealt with in the modal space. The method employs eigenvalues of a characteristic matrix formed by appropriate time-space FD stencils. Since MFD runs for different modes are totally independent of each other, MFDM can easily be parallelized while considerable simplicity in parallel-algorithm is also achieved. There is no requirement to any domain-decomposition procedure and inter-core data exchange. More important is the possibility to skip processing of less-significant modes, which enables one to adjust the procedure up to the level of accuracy needed. Thus, in addition to considerable ease of parallel programming, computation and storage costs are significantly reduced. The method is qualified for its efficiency by some numerical examples.

Keywords: Finite Difference Method, Graphics Processing Unit (GPU), Message Passing Interface (MPI), Modal, Wave propagation

Procedia PDF Downloads 277
648 Spatial Variability of Heavy Metals in Sediments of Two Streams of the Olifants River System, South Africa

Authors: Abraham Addo-Bediako, Sophy Nukeri, Tebatso Mmako

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Many freshwater ecosystems have been subjected to prolonged and cumulative pollution as a result of human activities such as mining, agricultural, industrial and human settlements in their catchments. The objective of this study was to investigate spatial variability of heavy metal pollution of sediments and possible sources of pollutants in two streams of the Olifants River System, South Africa. Stream sediments were collected and analysed for Arsenic (As), Cadmium (Cd), Chromium (Cr), Copper (Cu), Lead (Pb), Nickel (Ni) and Zinc (Zn) concentrations using inductively coupled plasma-mass mass spectrometry (ICP-MS). In both rivers, As, Cd, Cu, Pb and Zn fell within the concentration ranges recommended by CCME and ANZECC, while the concentrations of Cr and Ni exceeded the standards; the results indicated that Cr and Ni in the sediments originated from human activities and not from natural geological background. The index of geo-accumulation (Igeo) was used to assess the degree of pollution. The results of the geo-accumulation index evaluation showed that Cr and Ni were present in the sediments of the rivers at moderately to extremely polluted levels, while As, Cd, Cu, Pb and Zn existed at unpolluted to moderately polluted levels. Generally, heavy metal concentrations increased along the gradient in the rivers. The high concentrations of Cr and Ni in both rivers are of great concern, as previously these two rivers were classified to be supplying the Olifants River with water of good quality. There is a critical need, therefore to monitor heavy metal concentrations and distributions, as well as a comprehensive plan to prevent health risks, especially those communities still reliant on untreated water from the rivers, as sediment pollution may pose a risk of secondary water pollution under sediment disturbance and/or changes in the geo-chemistry of sediments.

Keywords: geo-accumulation index, heavy metals, sediment pollution, water quality

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647 Autonomic Threat Avoidance and Self-Healing in Database Management System

Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

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Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

Procedia PDF Downloads 490
646 Automatic Queuing Model Applications

Authors: Fahad Suleiman

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Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

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645 Risks beyond Cyber in IoT Infrastructure and Services

Authors: Mattias Bergstrom

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Significance of the Study: This research will provide new insights into the risks with digital embedded infrastructure. Through this research, we will analyze each risk and its potential negation strategies, especially for AI and autonomous automation. Moreover, the analysis that is presented in this paper will convey valuable information for future research that can create more stable, secure, and efficient autonomous systems. To learn and understand the risks, a large IoT system was envisioned, and risks with hardware, tampering, and cyberattacks were collected, researched, and evaluated to create a comprehensive understanding of the potential risks. Potential solutions have then been evaluated on an open source IoT hardware setup. This list shows the identified passive and active risks evaluated in the research. Passive Risks: (1) Hardware failures- Critical Systems relying on high rate data and data quality are growing; SCADA systems for infrastructure are good examples of such systems. (2) Hardware delivers erroneous data- Sensors break, and when they do so, they don’t always go silent; they can keep going, just that the data they deliver is garbage, and if that data is not filtered out, it becomes disruptive noise in the system. (3) Bad Hardware injection- Erroneous generated sensor data can be pumped into a system by malicious actors with the intent to create disruptive noise in critical systems. (4) Data gravity- The weight of the data collected will affect Data-Mobility. (5) Cost inhibitors- Running services that need huge centralized computing is cost inhibiting. Large complex AI can be extremely expensive to run. Active Risks: Denial of Service- It is one of the most simple attacks, where an attacker just overloads the system with bogus requests so that valid requests disappear in the noise. Malware- Malware can be anything from simple viruses to complex botnets created with specific goals, where the creator is stealing computer power and bandwidth from you to attack someone else. Ransomware- It is a kind of malware, but it is so different in its implementation that it is worth its own mention. The goal with these pieces of software is to encrypt your system so that it can only be unlocked with a key that is held for ransom. DNS spoofing- By spoofing DNS calls, valid requests and data dumps can be sent to bad destinations, where the data can be extracted for extortion or to corrupt and re-inject into a running system creating a data echo noise loop. After testing multiple potential solutions. We found that the most prominent solution to these risks was to use a Peer 2 Peer consensus algorithm over a blockchain to validate the data and behavior of the devices (sensors, storage, and computing) in the system. By the devices autonomously policing themselves for deviant behavior, all risks listed above can be negated. In conclusion, an Internet middleware that provides these features would be an easy and secure solution to any future autonomous IoT deployments. As it provides separation from the open Internet, at the same time, it is accessible over the blockchain keys.

Keywords: IoT, security, infrastructure, SCADA, blockchain, AI

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644 Functional Feeding Groups and Trophic Levels of Benthic Macroinvertebrates Assemblages in Albertine Rift Rivers and Streams in South Western Uganda

Authors: Peace Liz Sasha Musonge

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Behavioral aspects of species nutrition such as feeding methods and food type are archetypal biological traits signifying how species have adapted to their environment. This concept of functional feeding groups (FFG) analysis is currently used to ascertain the trophic levels of the aquatic food web in a specific microhabitat. However, in Eastern Africa, information about the FFG classification of benthic macroinvertebrates in highland rivers and streams is almost absent, and existing studies have fragmented datasets. For this reason, we carried out a robust study to determine the feed type, trophic level and FFGs, of 56 macroinvertebrate taxa (identified to family level) from Albertine rift valley streams. Our findings showed that all five major functional feeding groups were represented; Gatherer Collectors (GC); Predators (PR); shredders (SH); Scrapers (SC); and Filterer collectors. The most dominant functional feeding group was the Gatherer Collectors (GC) that accounted for 53.5% of the total population. The most abundant (GC) families were Baetidae (7813 individuals), Chironomidae NTP (5628) and Caenidae (1848). Majority of the macroinvertebrate population feed on Fine particulate organic matter (FPOM) from the stream bottom. In terms of taxa richness the Predators (PR) had the highest value of 24 taxa and the Filterer Collectors group had the least number of taxa (3). The families that had the highest number of predators (PR) were Corixidae (1024 individuals), Coenagrionidae (445) and Libellulidae (283). However, Predators accounted for only 7.4% of the population. The findings highlighted the functional feeding groups and habitat type of macroinvertebrate communities along an altitudinal gradient.

Keywords: trophic levels, functional feeding groups, macroinvertebrates, Albertine rift

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643 Catalytic Soot Gasification in Single and Mixed Atmospheres of CO2 and H2O in the Presence of CO and H2

Authors: Yeidy Sorani Montenegro Camacho, Samir Bensaid, Nunzio Russo, Debora Fino

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LiFeO2 nano-powders were prepared via solution combustion synthesis (SCS) method and were used as carbon gasification catalyst in a reduced atmosphere. The gasification of soot with CO2 and H2O in the presence of CO and H2 (syngas atmosphere) were also investigated under atmospheric conditions using a fixed-bed micro-reactor placed in an electric, PID-regulated oven. The catalytic bed was composed of 150 mg of inert silica, 45 mg of carbon (Printex-U) and 5 mg of catalyst. The bed was prepared by ball milling the mixture at 240 rpm for 15 min to get an intimate contact between the catalyst and soot. A Gas Hourly Space Velocity (GHSV) of 38.000 h-1 was used for the tests campaign. The furnace was heated up to the desired temperature, a flow of 120 mL/min was sent into the system and at the same time the concentrations of CO, CO2 and H2 were recorded at the reactor outlet using an EMERSON X-STREAM XEGP analyzer. Catalytic and non-catalytic soot gasification reactions were studied in a temperature range of 120°C – 850°C with a heating rate of 5 °C/min (non-isothermal case) and at 650°C for 40 minutes (isothermal case). Experimental results show that the gasification of soot with H2O and CO2 are inhibited by the H2 and CO, respectively. The soot conversion at 650°C decreases from 70.2% to 31.6% when the CO is present in the feed. Besides, the soot conversion was 73.1% and 48.6% for H2O-soot and H2O-H2-soot gasification reactions, respectively. Also, it was observed that the carbon gasification in mixed atmosphere, i.e., when simultaneous carbon gasification with CO2 and steam take place, with H2 and CO as co-reagents; the gasification reaction is strongly inhibited by CO and H2, as well has been observed in single atmospheres for the isothermal and non-isothermal reactions. Further, it has been observed that when CO2 and H2O react with carbon at the same time, there is a passive cooperation of steam and carbon dioxide in the gasification reaction, this means that the two gases operate on separate active sites without influencing each other. Finally, despite the extreme reduced operating conditions, it has been demonstrated that the 32.9% of the initial carbon was gasified using LiFeO2-catalyst, while in the non-catalytic case only 8% of the soot was gasified at 650°C.

Keywords: soot gasification, nanostructured catalyst, reducing environment, syngas

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642 CFD Modeling of Air Stream Pressure Drop inside Combustion Air Duct of Coal-Fired Power Plant with and without Airfoil

Authors: Pakawhat Khumkhreung, Yottana Khunatorn

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The flow pattern inside rectangular intake air duct of 300 MW lignite coal-fired power plant is investigated in order to analyze and reduce overall inlet system pressure drop. The system consists of the 45-degree inlet elbow, the flow instrument, the 90-degree mitered elbow and fans, respectively. The energy loss in each section can be determined by Bernoulli’s equation and ASHRAE standard table. Hence, computational fluid dynamics (CFD) is used in this study based on Navier-Stroke equation and the standard k-epsilon turbulence modeling. Input boundary condition is 175 kg/s mass flow rate inside the 11-m2 cross sectional duct. According to the inlet air flow rate, the Reynolds number of airstream is 2.7x106 (based on the hydraulic duct diameter), thus the flow behavior is turbulence. The numerical results are validated with the real operation data. It is found that the numerical result agrees well with the operating data, and dominant loss occurs at the flow rate measurement device. Normally, the air flow rate is measured by the airfoil and it gets high pressure drop inside the duct. To overcome this problem, the airfoil is planned to be replaced with the other type measuring instrument, such as the average pitot tube which generates low pressure drop of airstream. The numerical result in case of average pitot tube shows that the pressure drop inside the inlet airstream duct is decreased significantly. It should be noted that the energy consumption of inlet air system is reduced too.

Keywords: airfoil, average pitot tube, combustion air, CFD, pressure drop, rectangular duct

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641 Decoding the Structure of Multi-Agent System Communication: A Comparative Analysis of Protocols and Paradigms

Authors: Gulshad Azatova, Aleksandr Kapitonov, Natig Aminov

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Multiagent systems have gained significant attention in various fields, such as robotics, autonomous vehicles, and distributed computing, where multiple agents cooperate and communicate to achieve complex tasks. Efficient communication among agents is a crucial aspect of these systems, as it directly impacts their overall performance and scalability. This scholarly work provides an exploration of essential communication elements and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of these protocols across various scenarios. The research also sheds light on emerging trends within communication protocols for multiagent systems, including the incorporation of machine learning methods and the adoption of blockchain-based solutions to ensure secure communication. These trends provide valuable insights into the evolving landscape of multiagent systems and their communication protocols.

Keywords: communication, multi-agent systems, protocols, consensus

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640 Using the Cluster Computing to Improve the Computational Speed of the Modular Exponentiation in RSA Cryptography System

Authors: Te-Jen Chang, Ping-Sheng Huang, Shan-Ten Cheng, Chih-Lin Lin, I-Hui Pan, Tsung- Hsien Lin

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RSA system is a great contribution for the encryption and the decryption. It is based on the modular exponentiation. We call this system as “a large of numbers for calculation”. The operation of a large of numbers is a very heavy burden for CPU. For increasing the computational speed, in addition to improve these algorithms, such as the binary method, the sliding window method, the addition chain method, and so on, the cluster computer can be used to advance computational speed. The cluster system is composed of the computers which are installed the MPICH2 in laboratory. The parallel procedures of the modular exponentiation can be processed by combining the sliding window method with the addition chain method. It will significantly reduce the computational time of the modular exponentiation whose digits are more than 512 bits and even more than 1024 bits.

Keywords: cluster system, modular exponentiation, sliding window, addition chain

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639 Efficient Heuristic Algorithm to Speed Up Graphcut in Gpu for Image Stitching

Authors: Tai Nguyen, Minh Bui, Huong Ninh, Tu Nguyen, Hai Tran

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GraphCut algorithm has been widely utilized to solve various types of computer vision problems. Its expensive computational cost encouraged many researchers to improve the speed of the algorithm. Recent works proposed schemes that work on parallel computing platforms such as CUDA. However, the problem of low convergence speed prevents the usage of GraphCut for real time applications. In this paper, we propose global suppression heuristic to boost the conver-gence process of the algorithm. A parallel implementation of GraphCut algorithm on CUDA designed for the image stitching problem is introduced. Our method achieves up to 3× time boost on the graph of size 80 × 480 compared to the best sequential GraphCut algorithm while achieving satisfactory stitched images, suitable for panorama applications. Our source code will be soon available for further research.

Keywords: CUDA, graph cut, image stitching, texture synthesis, maxflow/mincut algorithm

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638 Multimodal Characterization of Emotion within Multimedia Space

Authors: Dayo Samuel Banjo, Connice Trimmingham, Niloofar Yousefi, Nitin Agarwal

Abstract:

Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.

Keywords: affective computing, deep learning, emotion recognition, multimodal

Procedia PDF Downloads 134
637 Worm Gearing Design Improvement by Considering Varying Mesh Stiffness

Authors: A. H. Elkholy, A. H. Falah

Abstract:

A new approach has been developed to estimate the load share and stress distribution of worm gear sets. The approach is based upon considering the instantaneous tooth meshing stiffness where the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using the well established formulae of spur gears. By combining the results obtained for all slices, the entire envolute worm gear set loading and stressing was obtained. The geometric modelling method presented, allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. On the basis of the method introduced in this study, the instantaneous meshing stiffness and load share were obtained. In comparison with existing methods, this approach has both good analysis accuracy and less computing time.

Keywords: gear, load/stress distribution, worm, wheel, tooth stiffness, contact line

Procedia PDF Downloads 333
636 Accurate Algorithm for Selecting Ground Motions Satisfying Code Criteria

Authors: S. J. Ha, S. J. Baik, T. O. Kim, S. W. Han

Abstract:

For computing the seismic responses of structures, current seismic design provisions permit response history analyses (RHA) that can be used without limitations in height, seismic design category, and building irregularity. In order to obtain accurate seismic responses using RHA, it is important to use adequate input ground motions. Current seismic design provisions provide criteria for selecting ground motions. In this study, the accurate and computationally efficient algorithm is proposed for accurately selecting ground motions that satisfy the requirements specified in current seismic design provisions. The accuracy of the proposed algorithm is verified using single-degree-of-freedom systems with various natural periods and yield strengths. This study shows that the mean seismic responses obtained from RHA with seven and ten ground motions selected using the proposed algorithm produce errors within 20% and 13%, respectively.

Keywords: algorithm, ground motion, response history analysis, selection

Procedia PDF Downloads 273
635 Solar-Assisted City Bus Electrical Installation: Opportunities and Impact on the Environment in Sydney

Authors: M. J. Geca, T. Tulwin, A. Majczak

Abstract:

On-board electricity consumption in the diesel city bus during operation is an important energy source. Electricity is generated by a combustion engine-driven alternator. Increased fuel consumption to generate on-board electricity in the bus has a negative impact on the emission of toxic components and carbon dioxide. At the same time, the bus roof surface allows placing a set of lightweight photovoltaic panels with power from 1 to 1.5 kW. The article presents an experimental study of electricity consumption of a city bus with diesel engine equipped with photovoltaic installation. The stream of electricity consumed by the bus and generated by a standard alternator and PV system was recorded. Base on the experimental research carried out in central Europe; the article analyses the impact of an additional source of electricity in the form of a photovoltaic installation on fuel consumption and emissions of toxic components of vehicles located in the latitude of Sydney. In Poland, the maximum global value of horizontal irradiation GHI is 1150 kWh/m², while for Sydney 1652 kWh/m². In addition, the profile of temperature and sunshine per year is different for these two different latitudes as presented in the article. Electricity generated directly from the sun powers the bus's electrical receivers. The photovoltaic system is able to replace 23% of annual electricity consumption, which at the same time will reduce 4% of fuel consumption and CO₂ reduction. Approximately 25% of the light is lost during vehicle traffic in Sydney latitude. The temperature losses of photovoltaic panels are comparable due to the cooling during vehicle motion. Acknowledgement: The project/research was financed in the framework of the project Lublin University of Technology - Regional Excellence Initiative, funded by the Polish Ministry of Science and Higher Education (contract no. 030/RID/2018/19).

Keywords: electric energy, photovoltaic system, fuel consumption, CO₂

Procedia PDF Downloads 98
634 Unsupervised Assistive and Adaptative Intelligent Agent in Smart Enviroment

Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lorenço

Abstract:

The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in a smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore relying on fixed operational models would be inappropriate. This paper presents a study on developing an Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose an Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 538
633 Unsupervised Assistive and Adaptive Intelligent Agent in Smart Environment

Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

Abstract:

The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 624
632 The Effect of Land Cover on Movement of Vehicles in the Terrain

Authors: Krisstalova Dana, Mazal Jan

Abstract:

This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms etc., have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is the surface of a terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for the commander`s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: movement in a terrain, geographical factors, surface of a field, mathematical evaluation, optimization and searching paths

Procedia PDF Downloads 407
631 Fluvial Stage-Discharge Rating of a Selected Reach of Jamuna River

Authors: Makduma Zahan Badhan, M. Abdul Matin

Abstract:

A study has been undertaken to develop a fluvial stage-discharge rating curve for Jamuna River. Past Cross-sectional survey of Jamuna River reach within Sirajgonj and Tangail has been analyzed. The analysis includes the estimation of discharge carrying capacity, possible maximum scour depth and sediment transport capacity of the selected reaches. To predict the discharge and sediment carrying capacity, stream flow data which include cross-sectional area, top width, water surface slope and median diameter of the bed material of selected stations have been collected and some are calculated from reduced level data. A well-known resistance equation has been adopted and modified to a simple form in order to be used in the present analysis. The modified resistance equation has been used to calculate the mean velocity through the channel sections. In addition, a sediment transport equation has been applied for the prediction of transport capacity of the various sections. Results show that the existing drainage sections of Jamuna channel reach under study have adequate carrying capacity under existing bank-full conditions, but these reaches are subject to bed erosion even in low flow situations. Regarding sediment transport rate, it can be estimated that the channel flow has a relatively high range of bed material concentration. Finally, stage­ discharge curves for various sections have been developed. Based on stage-discharge rating data of various sections, water surface profile and sediment-rating curve of Jamuna River have been developed and also the flooding conditions have been analyzed from predicted water surface profile.

Keywords: discharge rating, flow profile, fluvial, sediment rating

Procedia PDF Downloads 170