Search results for: industrial wireless network (IWN)

Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

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As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

Procedia PDF Downloads 136

Authors: Bahriye Gülgün, Gökhan Balik, Şükrü Dursun, Kübra Yazici

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The main reasons such as economic growth of society increase of the world population and rapid changes of industrialization cause the amount and the types of pollutants to increase over time. Soil pollution is the typical side effect of industrial activities. As a result of industrial activities, there are large amounts of heavy metal emission every year. Heavy metals are one of the highest pollution sources according to the soil pollution aspect. The usage of hyperaccumulator plants to clean heavy metal polluted soils and the selection of plants for phytoremediation gain importance recently. There are limited numbers of researches on the ornamental plant types of phytoremediation thus; researches on this subject are important. This research is prepared based on the ornamental plant types with phytoremediation abilities.

Keywords: phytoremediation, ornamental plants, landscape reclamation, soil reclamation, environmental pollution

Procedia PDF Downloads 397

Authors: Daniel Olshansky, Ramiro Rodrıguez Colmeiro

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Relay Mining presents a scalable solution employing probabilistic mechanisms and crypto-economic incentives to estimate RPC volume usage, facilitating decentralized multitenant rate limiting. Network traffic from individual applications can be concurrently serviced by multiple RPC service providers, with costs, rewards, and rate limiting governed by a native cryptocurrency on a distributed ledger. Building upon established research in token bucket algorithms and distributed rate-limiting penalty models, our approach harnesses a feedback loop control mechanism to adjust the difficulty of mining relay rewards, dynamically scaling with network usage growth. By leveraging crypto-economic incentives, we reduce coordination overhead costs and introduce a mechanism for providing RPC services that are both geopolitically and geographically distributed.

Keywords: remote procedure call, crypto-economic, commit-reveal, decentralization, scalability, blockchain, rate limiting, token bucket

Procedia PDF Downloads 40

Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

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This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

Procedia PDF Downloads 353

Authors: Hiroaki Nasu, Ryota Miyamoto, Yuta Kodera, Yasuyuki Nogami

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To promote Industry 4.0 and Society 5.0 and so on, it is important to connect and share data so that every member can trust it. Blockchain (BC) technology is currently attracting attention as the most advanced tool and has been used in the financial field and so on. However, the data collaboration using BC has not progressed sufficiently among companies on the supply chain of manufacturing industry that handle sensitive data such as product quality, manufacturing conditions, etc. There are two main reasons why data utilization is not sufficiently advanced in the industrial supply chain. The first reason is that manufacturing information is top secret and a source for companies to generate profits. It is difficult to disclose data even between companies with transactions in the supply chain. In the blockchain mechanism such as Bitcoin using PKI (Public Key Infrastructure), in order to confirm the identity of the company that has sent the data, the plaintext must be shared between the companies. Another reason is that the merits (scenarios) of collaboration data between companies are not specifically specified in the industrial supply chain. For these problems this paper proposes a Business to Business (B2B) collaboration system using homomorphic encryption and BC technique. Using the proposed system, each company on the supply chain can exchange confidential information on encrypted data and utilize the data for their own business. In addition, this paper considers a scenario focusing on quality data, which was difficult to collaborate because it is a top secret. In this scenario, we show a implementation scheme and a benefit of concrete data collaboration by proposing a comparison protocol that can grasp the change in quality while hiding the numerical value of quality data.

Keywords: business to business data collaboration, industrial supply chain, blockchain, homomorphic encryption

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Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: Murray Matarab Konzang

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Lae Port Development Project, Four Lane Highway and other development in the extraction industry which have direct road link to Lae City are predicted to have significant impact on its road network system. This paper evaluates Lae roads improvement program with forecast on planning, economic and the installation of bypasses to ease congestion, effective and convenient transport service for bulk goods and reduce travel time. Land-use transportation study and plans for local area traffic management scheme will be considered. City roads are faced with increased number of traffic and some inadequate road pavement width, poor transport plans, and facilities to meet this transportation demand. Lae also has drainage system which might not hold a 100 year flood. Proper evaluation, plan, design and intersection analysis is needed to evaluate road network system thus recommend improvement and estimate future growth. Repetitive and cyclic loading by heavy commercial vehicles with different axle configurations apply on the flexible pavement which weakens and tear the pavement surface thus small cracks occur. Rain water seeps through and overtime it creates potholes. Effective planning starts from experimental research and appropriate design standards to enable firm embankment, proper drains and quality pavement material. This paper will address traffic problems as well as road pavement, capacities of intersections, and pedestrian flow during peak hours. The outcome of this research will be to identify heavily trafficked road sections and recommend treatments to reduce traffic congestions, road classification, and proposal for bypass routes and improvement. First part of this study will describe transport or traffic related problems within the city. Second part would be to identify challenges imposed by traffic and road related problems and thirdly to recommend solutions after the analyzing traffic data that will indicate current capacities of road intersections and finally recommended treatment for improvement and future growth.

Keywords: Lae, road network, highway, vehicle traffic, planning

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Authors: Kalpana Rajouriya, Ajay Taneja

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Particulates are ubiquitous in the air environment and cause serious threats to human beings, such as lung cancer, COPD, and Asthma. Particulates mainly arise from industrial effluent, vehicular emission, and other anthropogenic activities. In the glass industrial city Firozabad, real-time monitoring of size segregated Particulate Matter (PM) and black carbon was done by Aerosol Black Carbon Detector (ABCD) and GRIMM portable aerosol Spectrometer at two different sites in which one site is urban and another is rural. The average mass concentration of size segregated PM during the study period (March & April 2022) was recorded as PM10 (223.73 g/m⁻³), PM5.0 (44.955 g/m⁻³), PM2.5 (59.275 g/m⁻³), PM1.0 (33.02 g/m⁻³), PM0.5 (2.05 g/m⁻³), and PM0.25 (2.99 g/m⁻³). The highest concentration of BC was found in Urban due to the emissions from diesel engines and wood burning, while NO2 was highest at the rural sites. The average concentrations of PM10 (6.08 and 2.73 times) PM2.5 exceeded the NAAQS and WHO guidelines. Particulate Matter deposition and health risk assessment was done by MPPD and USEPA model to know about the particulate matter toxicity in industrial residents. Health risk assessment results showed that Children are most likely to be affected by exposure of PM10 and PM2.5 and may have various non-carcinogenic and carcinogenic diseases. Deposition results inferred that the sensitive exposed population, especially 9 years old children, have high PM deposition as well as visualization and may be at risk of developing health-related problems from exposure to size-segregated PM. They will be discussed during presentation.

Keywords: particulate matter, black carbon, NO2, deposition of PM, health risk

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Authors: Oyebade K. Oyedotun

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The cardiotocogram is a technical recording of the heartbeat rate and uterine contractions of a fetus during pregnancy. During pregnancy, several complications can occur to both the mother and the fetus; hence it is very crucial that medical experts are able to find technical means to check the healthiness of the mother and especially the fetus. It is very important that the fetus develops as expected in stages during the pregnancy period; however, the task of monitoring the health status of the fetus is not that which is easily achieved as the fetus is not wholly physically available to medical experts for inspection. Hence, doctors have to resort to some other tests that can give an indication of the status of the fetus. One of such diagnostic test is to obtain cardiotocograms of the fetus. From the analysis of the cardiotocograms, medical experts can determine the status of the fetus, and therefore necessary medical interventions. Generally, medical experts classify examined cardiotocograms into ‘normal’, ‘suspect’, or ‘pathological’. This work presents an artificial neural network based decision support system which can filter cardiotocograms data, producing the corresponding statuses of the fetuses. The capability of artificial neural network to explore the cardiotocogram data and learn features that distinguish one class from the others has been exploited in this research. In this research, feedforward and radial basis neural networks were trained on a publicly available database to classify the processed cardiotocogram data into one of the three classes: ‘normal’, ‘suspect’, or ‘pathological’. Classification accuracies of 87.8% and 89.2% were achieved during the test phase of the trained network for the feedforward and radial basis neural networks respectively. It is the hope that while the system described in this work may not be a complete replacement for a medical expert in fetus status evaluation, it can significantly reinforce the confidence in medical diagnosis reached by experts.

Keywords: decision support, cardiotocogram, classification, neural networks

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Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt

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To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.

Keywords: 100% renewable electricity, California, capacity expansion, mixed integer non-linear programming

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Authors: Natalya G. Filimonova, Mariya G. Ozerova, Irina N. Ermakova

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The long-term strategy of the economic development of Russia up to 2030 is based on the concept of sustainable growth. The determining factor of such development is complex changes in the economic system which may be achieved by making progressive changes in its structure. The structural changes determine the character and the direction of economic development, as well as they include all elements of this system without exception, and their regulated character ensures the most rapid aim achievement. This article has discussed the industrial structure of the agriculture in Russia. With the use of the system of indexes, the article has determined the directions, intensity, and speed of structural shifts. The influence of structural changes on agricultural production development has been found out. It is noticed that the changes in the industrial structure are synchronized with the changes in the organisation and economic structure. Efficiency assessment of structural changes allowed to trace the efficiency of structural changes and elaborate the main directions for agricultural policy improvement.

Keywords: Russian agricultural sectors, sectoral structure, organizational and economic structure, structural changes

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Authors: Noor Farizah Ibrahim, Christopher Durugbo

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This study aims to investigate how the Twittersphere reacted during the recent historical event of robotic landing on a comet. The news is about Philae, a robotic lander from European Space Agency (ESA), which successfully made the first-ever rendezvous and touchdown of its kind on a nucleus comet on November 12, 2014. In order to understand how Twitter is practically used in spreading messages on historical events, we conducted an analysis of one-week tweet feeds that contain the #CometLanding hashtag. We studied the trends of tweets, the diffusion of the information and the characteristics of the social network created. The results indicated that the use of Twitter as a platform enables online communities to engage and spread the historical event through social media network (e.g. tweets, retweets, mentions and replies). In addition, it was found that comprehensible and understandable hashtags could influence users to follow the same tweet stream compared to other laborious hashtags which were difficult to understand by users in online communities.

Keywords: diffusion of information, hashtag, social media, Twitter

Procedia PDF Downloads 306

Authors: Wenjuan Lu

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China and Hungary have risen from a friendly and comprehensive cooperative relationship to a comprehensive strategic partnership in recent years, and the economic and trade relations between the two countries have developed smoothly. As an important country along the ‘Belt and Road’, Hungary and China have strong economic complementarities and have unique advantages in carrying China's industrial transfer and economic transformation and development. The construction of the China-Hungary Economic and Trade Cooperation Zone, which was initiated by the ‘Sino-Hungarian Borsod Industrial Zone’ and the ‘Hungarian Central European Trade and Logistics Cooperation Park’ has promoted infrastructure construction, optimized production capacity, promoted industrial restructuring, and formed brand and agglomeration effects. Enhancing the influence of Chinese companies in the European market has also promoted economic development in Hungary and even in Central and Eastern Europe. However, as the China-Hungary Economic and Trade Cooperation Zone is still in its infancy, there are still shortcomings such as small scale, single function, and no prominent platform. In the future, based on the needs of China's cooperation with ‘17+1’ and China-Hungary cooperation, on the basis of appropriately expanding the scale of economic and trade cooperation zones and appropriately increasing the number of economic and trade cooperation zones, it is better to focus on optimizing and adjusting its functions and highlighting different economic and trade cooperation. The differentiated function of the trade zones strengthens the multi-faceted cooperation of economic and trade cooperation zones and highlights its role as a platform for cooperation in information, capital, and services.

Keywords: ‘One Belt, One Road’ Initiative, China-Hungary economic and trade cooperation zone, function optimization, Central and Eastern Europe

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Authors: Abdelheq Boukarkar, Omar Guermoua

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In this paper, we propose a miniaturized and wideband patch antenna for C-band applications. The antenna miniaturization is obtained by loading shorting vias along one patch edge. At the same time, the wideband performance is achieved by combining two resonances using one feed line. The measured results reveal that the antenna covers the frequency band 4.32 GHz to 6.52 GHz (41%) with a peak gain and a peak efficiency of 5.5 dBi and 87%, respectively. The antenna occupies a relatively small size of only 26 x 22 x 5.6 mm³, making it suitable for compact wireless devices requiring a stable unidirectional gain over a wide frequency range.

Keywords: miniaturized antennas, patch antennas, stable gain, wideband antennas

Procedia PDF Downloads 196

Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

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The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: femtocell networks, game theory, interference mitigation, spectrum allocation

Procedia PDF Downloads 140

Authors: Cheng Fang Hsu

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Call center is the core of building customer relationship management system. Under the strong competitive stress, it becomes a new profiting challenge for a successful enterprise. Call center is a department not only to provide customer service but also to bring business profit. This is the qualitative case study in Taiwan bank service industry which goes on deeper exploration, and analysis by business interviews and industrial analysis. This study starts from the establishment, development, and management after the reforming of the case call center. Through SWOT analysis, and industrial analysis, this study adopted 7S model to explain how the call center reforms from service oriented to profit oriented and from cost management to profit management. The results indicated how service innovation management promotes call center to be operated as a market profit competition center. The recommendations are indicated to support the call center on marketing profit by service innovation management.

Keywords: call center, 7S model, service innovation management, bioinformatics

Procedia PDF Downloads 466

Authors: Qidi Lin, Jinbin Huang, Weile Liang

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This paper introduces a video sharing platform based on WiFi, which consists of camera, mobile phone and PC server. This platform can receive wireless signal from the camera and show the live video on the mobile phone captured by camera. In addition that, it is able to send commands to camera and control the camera’s holder to rotate. The platform can be applied to interactive teaching and dangerous area’s monitoring and so on. Testing results show that the platform can share the live video of mobile phone. Furthermore, if the system’s PC sever and the camera and many mobile phones are connected together, it can transfer photos concurrently.

Keywords: Wifi Camera, socket mobile, platform video monitoring, remote control

Procedia PDF Downloads 321

Authors: Jungyeol Hong, Dongjoo Park

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The primary purpose of this study is to develop a methodological framework to predict daily subway ridership at a station-level and to examine the association between subway ridership and bus demand incorporating commercial business facility in the vicinity of each subway station. The socio-economic characteristics, land-use, and built environment as factors may have an impact on subway ridership. However, it should be considered not only the endogenous relationship between bus and subway demand but also the characteristics of commercial business within a subway station’s sphere of influence, and integrated transit network topology. Regarding a statistical approach to estimate subway ridership at a station level, therefore it should be considered endogeneity and heteroscedastic issues which might have in the subway ridership prediction model. This study focused on both discovering the impacts of bus demand, commercial business characteristics, and network topology on subway ridership and developing more precise subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers entire Seoul city in South Korea and includes 243 stations with the temporal scope set at twenty-four hours with one-hour interval time panels each. The data for subway and bus ridership was collected Seoul Smart Card data from 2015 and 2016. Three-Stage Least Square(3SLS) approach was applied to develop daily subway ridership model as capturing the endogeneity and heteroscedasticity between bus and subway demand. Independent variables incorporating in the modeling process were commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. As a result, it was found that bus ridership and subway ridership were endogenous each other and they had a significantly positive sign of coefficients which means one transit mode could increase another transportation mode’s ridership. In other words, two transit modes of subway and bus have a mutual relationship instead of the competitive relationship. The commercial business characteristics are the most critical dimension among the independent variables. The variables of commercial business facility rate in the paper containing six types; medical, educational, recreational, financial, food service, and shopping. From the model result, a higher rate in medical, financial buildings, shopping, and food service facility lead to increment of subway ridership at a station, while recreational and educational facility shows lower subway ridership. The complex network theory was applied for estimating integrated network topology measures that cover the entire Seoul transit network system, and a framework for seeking an impact on subway ridership. The centrality measures were found to be significant and showed a positive sign indicating higher centrality led to more subway ridership at a station level. The results of model accuracy tests by out of samples provided that 3SLS model has less mean square error rather than OLS and showed the methodological approach for the 3SLS model was plausible to estimate more accurate subway ridership. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT (2017R1C1B2010175).

Keywords: subway ridership, bus ridership, commercial business characteristic, endogeneity, network topology

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 123

Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

Procedia PDF Downloads 107

Authors: Nadjib Drouiche

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Water resources in Algeria are scarce, often low quality, fragile, and unevenly distributed in space and time. The pressure on water resources can be associated with industrial development, a steady population growth, and demanding land irrigation measures. These conditions createa tense competitionfor managing waterresourcesand sharing thembetween agricultural development, drinking water supply, industrial activities, etc. Moreover, the impact of climate change has placed in the forefront national policies focused on the water-energy-food nexus (WEF). In this context, desalination membrane technologies could play an increasing rolefor supporting segments of the Algerian economy that are heavily water-dependent. By implementing water reuse and desalination strategies together in the agricultural sector, there is an opportunity to expand the access to healthy food and clean water, thereby keeping the WEF nexus effects under control.

Keywords: desalination, mitigation, climate change, sustainable development goals

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Authors: Jae-Hyun Ro, Yong-Jun Kim, Eui-Hak Lee, Hyoung-Kyu Song

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Mobile communication has been developing very rapidly since it appeared. However, although mobile communication market has been rapidly developing, many mobile users are not offered good quality of service (QoS) due to increment of the amount of data traffic. Recently, femtocell is very hot issue in mobile communication because femtocell can solve the problems of data traffic and offer better QoS to mobile users. However, the deployment of femtocell in existing macrocell coverage area is not so simple due to the influence of inter-cell-interference (ICI) with existing macrocell. Thus, this paper proposes femtocell scheme which is able to reduce the influence of ICI to deploy femtocell easily.

Keywords: CDD, femtocell, interference, macrocell, OFDM

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Authors: Alberto Mínguez-Martínez, Jesús de Vicente y Oliva

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Modern manufacturing processes have led to the miniaturization of systems and, as a result, parts at the micro-and nanoscale are produced. This trend seems to become increasingly important in the near future. Besides, as a requirement of Industry 4.0, the digitalization of the models of production and processes makes it very important to ensure that the dimensions of newly manufactured parts meet the specifications of the models. Therefore, it is possible to reduce the scrap and the cost of non-conformities, ensuring the stability of the production at the same time. To ensure the quality of manufactured parts, it becomes necessary to carry out traceable measurements at scales lower than one millimeter. Providing adequate traceability to the SI unit of length (the meter) to 2D and 3D measurements at this scale is a problem that does not have a unique solution in industrial environments. Researchers in the field of dimensional metrology all around the world are working on this issue. A solution for industrial environments, even if it is not complete, will enable working with some traceability. At this point, we believe that the study of the surfaces could provide us with a first approximation to a solution. Among the different options proposed in the literature, the areal topography methods may be the most relevant because they could be compared to those measurements performed using Coordinate Measuring Machines (CMM’s). These measuring methods give (x, y, z) coordinates for each point, expressing it in two different ways, either expressing the z coordinate as a function of x, denoting it as z(x), for each Y-axis coordinate, or as a function of the x and y coordinates, denoting it as z (x, y). Between others, optical measuring instruments, mainly microscopes, are extensively used to carry out measurements at scales lower than one millimeter because it is a non-destructive measuring method. In this paper, the authors propose a calibration procedure for the scales of optical measuring instruments, particularizing for a confocal microscope, using material standards easy to find and calibrate in metrology and quality laboratories in industrial environments. Confocal microscopes are measuring instruments capable of filtering the out-of-focus reflected light so that when it reaches the detector, it is possible to take pictures of the part of the surface that is focused. Varying and taking pictures at different Z levels of the focus, a specialized software interpolates between the different planes, and it could reconstruct the surface geometry into a 3D model. As it is easy to deduce, it is necessary to give traceability to each axis. As a complementary result, the roughness Ra parameter will be traced to the reference. Although the solution is designed for a confocal microscope, it may be used for the calibration of other optical measuring instruments by applying minor changes.

Keywords: industrial environment, confocal microscope, optical measuring instrument, traceability

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Authors: Abimbola M. Enitan, Josiah Adeyemo, Sheena Kumari, Feroz M. Swalaha, Faizal Bux

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With the competing demand on water resources and water reuse, discharge of industrial effluents into the aquatic environment has become an important issue. Much attention has been placed on the impact of industrial wastewater on water bodies worldwide due to the accumulation of organic and inorganic matter in the receiving water bodies. The scope of the present work is to assess the physic-chemical composition of the wastewater produced from one of the brewery industry in South Africa. This is to estimate the environmental impact of its discharge into the receiving water bodies or the municipal treatment plant. The parameters monitored for the quantitative analysis of brewery wastewater include biological oxygen demand (BOD5), chemical oxygen demand (COD), total suspended solids, volatile suspended solids, ammonia, total oxidized nitrogen, nitrate, nitrite, phosphorus, and alkalinity content. In average, the COD concentration of the brewery effluent was 5340.97 mg/l with average pH values of 4.0 to 6.7. The BOD and the solids content of the wastewater from the brewery industry were high. This means that the effluent is very rich in organic content and its discharge into the water bodies or the municipal treatment plant could cause environmental pollution or damage the treatment plant. In addition, there were variations in the wastewater composition throughout the monitoring period. This might be as a result of different activities that take place during the production process, as well as the effects of the peak period of beer production on the water usage.

Keywords: Brewery wastewater, environmental pollution, industrial effluents, physic-chemical composition

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale, Rubens Maribondo do Nascimento, José Ubiragi de Lima Mendes

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Recycling has been greatly stimulated by the market. There are already several products that are produced with recycled materials and various wastes have been studied in various forms of applications. The vast majority of insulation applications in domestic, commercial and industrial systems in the range of low and medium temperatures (up to 180 ° C), using the aggressive nature materials such as glass wool, rock wool, polyurethane, polystyrene. Such materials, while retaining the effectiveness of the heat flux, are disposed as expensive and take years too absorbed by nature. Thus, trying to adapt to a global policy on the preservation of the environment, a study in order to develop an insulating compound of natural / industrial waste and biodegradable materials conducted. Thus, this research presents the development of a composite material based zest tire and latex for thermal and electrical insulation.

Keywords: composite, latex, scrapes tire, insulation, electrical

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Authors: Donghyun Lee, Cam Nguyen

Abstract:

Multi-band systems offer a great deal of benefit in modern communication and radar systems. In particular, multi-band antenna-array radar systems with their extended frequency diversity provide numerous advantages in detection, identification, locating and tracking a wide range of targets, including enhanced detection coverage, accurate target location, reduced survey time and cost, increased resolution, improved reliability and target information. An accurate calibration is a critical issue in antenna array systems. The amplitude and phase errors in multi-band and multi-polarization antenna array transceivers result in inaccurate target detection, deteriorated resolution and reduced reliability. Furthermore, the digital beam former without the RF domain phase-shifting is less immune to unfiltered interference signals, which can lead to receiver saturation in array systems. Therefore, implementing integrated front-end architecture, which can support calibration function with low insertion and filtering function from the farthest end of an array transceiver is of great interest. We report a dual K/Ka-band T/R/Calibration switch module with quasi-elliptic dual-bandpass filtering function implementing a Q-enhanced metamaterial transmission line. A unique dual-band frequency response is incorporated in the reception and calibration path of the proposed switch module utilizing the composite right/left-handed meta material transmission line coupled with a Colpitts-style negative generation circuit. The fabricated fully integrated T/R/Calibration switch module in 0.18-μm BiCMOS technology exhibits insertion loss of 4.9-12.3 dB and isolation of more than 45 dB in the reception, transmission and calibration mode of operation. In the reception and calibration mode, the dual-band frequency response centered at 24.5 and 35 GHz exhibits out-of-band rejection of more than 30 dB compared to the pass bands below 10.5 GHz and above 59.5 GHz. The rejection between the pass bands reaches more than 50 dB. In all modes of operation, the IP1-dB is between 4 and 11 dBm. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: microwaves, millimeter waves, T/R switch, wireless communications, wireless communications

Procedia PDF Downloads 146

Authors: Ho Yeon Park, Kyoung-Jae Kim

Abstract:

The purpose of this study is to investigate whether friendship in social media can be an important factor in recommender system through social scientific analysis of friendship in popular social media such as Facebook and Twitter. For this purpose, this study analyzes data on friendship in real social media using component analysis and clique analysis among sub-group analysis in social network analysis. In this study, we propose an algorithm to reflect the results of sub-group analysis on the recommender system. The key to this algorithm is to ensure that recommendations from users in friendships are more likely to be reflected in recommendations from users. As a result of this study, outcomes of various subgroup analyzes were derived, and it was confirmed that the results were different from the results of the existing recommender system. Therefore, it is considered that the results of the subgroup analysis affect the recommendation performance of the system. Future research will attempt to generalize the results of the research through further analysis of various social data.

Keywords: sub-group analysis, social media, social network analysis, recommender systems

Procedia PDF Downloads 343

Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: E. Behmanesh, J. Pannek

Abstract:

The distribution-allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution-allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near-optimal solutions particularly for large scales test problems. This paper, presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a novelty in population presentation. To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as a comparison basis for small size problems. In large size cases that we are dealing with in the real world, the Genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm.

Keywords: integrated logistics network, flexible path, memetic algorithm, genetic algorithm

Procedia PDF Downloads 360

Authors: Nataša Kalajdžija, Strahinja Kovačević, Davor Lončar, Sanja Podunavac Kuzmanović, Lidija Jevrić

Abstract:

In order to investigate the relationship between retention and structure, a quantitative Structure Retention Relationships (QSRRs) study was applied for the prediction of retention times of a set of 23 secoestrane derivatives in a reversed-phase thin-layer chromatography. After the calculation of molecular descriptors, a suitable set of molecular descriptors was selected by using step-wise multiple linear regressions. Artificial Neural Network (ANN) method was employed to model the nonlinear structure-activity relationships. The ANN technique resulted in 5-6-1 ANN model with the correlation coefficient of 0.98. We found that the following descriptors: Critical pressure, total energy, protease inhibition, distribution coefficient (LogD) and parameter of lipophilicity (miLogP) have a significant effect on the retention times. The prediction results are in very good agreement with the experimental ones. This approach provided a new and effective method for predicting the chromatographic retention index for the secoestrane derivatives investigated.

Keywords: lipophilicity, QSRR, RP TLC retention, secoestranes

Procedia PDF Downloads 436