Search results for: building energy system optimization

Authors: Huiqiang Yang, Domingo Santana

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Reducing parasitic power consumption of concentrating solar power plants is the main challenge to increase the overall efficiency, particularly for molten salt tower technology. One of the most effective approaches to reduce the parasitic power consumption is to implement a natural draft dry cooling system instead of the standard utilized mechanical draft dry cooling system. In this paper, a thermo-economic analysis of a natural draft direct cooling system was performed based on a 100MWe commercial scale molten salt power plant. In this configuration with a natural draft direct cooling system, the exhaust steam from steam turbine flows directly to the heat exchanger bundles inside the natural draft dry cooling tower, which eliminates the power consumption of circulation pumps or fans, although the cooling tower shadows a portion of the heliostat field. The simulation results also show that compared to a mechanical draft cooling system the annual solar field efficiency is decreased by about 0.2% due to the shadow, which is equal to a reduction of approximately 13% of the solar field area. As a contrast, reducing the solar field size by 13% in purpose in a molten salt power plant with a natural draft drying cooling system actually will lead to a reduction of levelized cost of electricity (LCOE) by about 4.06% without interfering the power generated.

Keywords: molten salt power tower, natural draft dry cooling, parasitic power consumption, commercial scale

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Deepak Singh, Rail Kuliev

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The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

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Authors: Celal Dudak, Aslı Utku, Burak Yağlioğlu

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Uninterrupted and continuous satellite communication through the whole orbit time is becoming more indispensable every day. Data relay systems are developed and built for various high/low data rate information exchanges like TDRSS of USA and EDRSS of Europe. In these missions, a couple of task-dedicated communication satellites exist. In this regard, for Turkey a data relay system is attempted to be defined exchanging low data rate information (i.e. TTC) for Earth-observing LEO satellites appointing commercial GEO communication satellites all over the world. First, justification of this attempt is given, demonstrating duration enhancements in the link. Discussion of preference of RF communication is, also, given instead of laser communication. Then, preferred communication GEOs – including TURKSAT4A already belonging to Turkey- are given, together with the coverage enhancements through STK simulations and the corresponding link budget. Also, a block diagram of the communication system is given on the LEO satellite.

Keywords: communication, GEO satellite, data relay system, coverage

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Authors: J. S. Savier

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Real power is the component power which is converted into useful energy whereas reactive power is the component of power which cannot be converted to useful energy but it is required for the magnetization of various electrical machineries. If the reactive power is compensated at the consumer end, the need for reactive power flow from generators to the load can be avoided and hence the overall power loss can be reduced. In this scenario, this paper presents a succinct method called JSS method for allocation of reactive power losses to consumers connected to radial distribution networks in a deregulated environment. The proposed method has the advantage that no assumptions are made while deriving the reactive power loss allocation method.

Keywords: deregulation, reactive power loss allocation, radial distribution systems, succinct method

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Authors: Anthony Oppong Kyekyeku, Sussana Antwi-Boasiako, Emmanuel De-Graft Johnson Owusu Ansah

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In this observational study, the performance of a known conventional storage system was tested and evaluated for fitness for its intended purpose. The system has a scope extended for the storage of dry cocoa beans. System sensitivity, reproducibility and uncertainties are not known in details. This study discusses the system performance in the context of existing literature on factors that influence the quality of cocoa beans during storage. Controlled conditions were defined precisely for the system to give reliable base line within specific established procedures. Minitab® 17 and R statistical software (R-3.3.1) were used for the statistical analyses. The approach to the storage system testing was to observe and compare through laboratory test methods the quality of the cocoa beans samples before and after storage. The samples were kept in Kilner jars and the temperature of the storage environment controlled and monitored over a period of 408 days. Standard test methods use in international trade of cocoa such as the cut test analysis, moisture determination with Aqua boy KAM III model and bean count determination were used for quality assessment. The data analysis assumed the entire population as a sample in order to establish a reliable baseline to the data collected. The study concluded a statistically significant mean value at 95% Confidence Interval (CI) for the performance data analysed before and after storage for all variables observed. Correlational graphs showed a strong positive correlation for all variables investigated with the exception of All Other Defect (AOD). The weak relationship between the before and after data for AOD had an explained variability of 51.8% with the unexplained variability attributable to the uncontrolled condition of hidden infestation before storage. The current study concluded with a high-performance criterion for the storage system.

Keywords: benchmarking performance data, cocoa beans, hidden infestation, storage system validation

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Authors: Kumar Vikas

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Education is to be anticipated for Human resource development and then national development. However, in most of the developing countries, due to the inadequacy of resources it is almost unattainable to educate all of their citizens through on-campus teaching. Huge amount of money is necessary to establish the infrastructure for on-campus teaching which is out of the reach of the developing countries. In these circumstances, to educate their huge inhabitants the developing countries are to depend on open learning and distance education system. However, a question still stands: can the educators dissimulate knowledge to the learners smoothly through this new system of education? Some recent research shows that the graduates of the open and distance learning institutions in the developing countries are treated as second-grade graduates. This paper aims to identify the challenges or barriers in the development of distance and Open learning system in India and suggest possible alternatives may be followed to overcome the barriers.

Keywords: barriers, distance education, developing countries, motivation, alternative solutions

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Authors: Mohammed A. Hajeeh

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This paper examines the behavior of a system, which upon failure is either replaced with certain probability p or imperfectly repaired with probability q. The system is analyzed using Kolmogorov's forward equations method; the analytical expression for the steady state availability is derived as an indicator of the system’s performance. It is found that the analysis becomes more complex as the number of imperfect repairs increases. It is also observed that the availability increases as the number of states and replacement probability increases. Using such an approach in more complex configurations and in dynamic systems is cumbersome; therefore, it is advisable to resort to simulation or heuristics. In this paper, an example is provided for demonstration.

Keywords: repairable models, imperfect, availability, exponential distribution

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Authors: Wang Liguang, Zhang Xueqing

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The build-operate-transfer (BOT) project delivery system has provided effective routes to mobilize private sector funds, innovative technologies, management skills and operational efficiencies for public infrastructure development and have been widely used in China during the last 20 years. Many BOT projects in China will be smoothly transferred to the government soon and the transfer stage, which is considered as the last stage, must be studied carefully and handled well to achieve the overall success of BOT projects. There will be many issues faced by both the public sector and private sector in the transfer stage of BOT projects, including project post-assessment, technology and documents transfer, personal training and staff transition, etc. and sometimes additional legislation is needed for future operation and management of facilities. However, most previous studies focused on the bidding, financing, and building and operation stages instead of transfer stage. This research identifies nine key issues in the transfer stage of BOT projects through a comprehensive study on three cases in China, and the expert interview and expert discussion meetings are held to validate the key issues and give detail analysis. A proposed framework of transfer management is prepared based on the experiences derived and lessons drawn from the case studies and expert interview and discussions, which is expected to improve the transfer management of BOT projects in practice.

Keywords: BOT project, key issues, transfer management, transfer stage

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Authors: Suyeb Ahmed Khan, Mahmood Mian

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Simulation plays an important role during all phases of the design and engineering of communications systems, from early stages of conceptual design through the various stages of implementation, testing, and fielding of the system. In the present paper, a simulation model has been constructed for the WCDMA system in order to evaluate the performance. This model describes multiusers effects and calculation of BER (Bit Error Rate) in 3G mobile systems using Simulink MATLAB 7.1. Gaussian Approximation defines the multi-user effect on system performance. BER has been analyzed with comparison between transmitting data and receiving data.

Keywords: WCDMA, simulations, BER, MATLAB

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Authors: Nikhil Verma, Akshay Kant Mishra, Rishabh Rastogi, Bikarama Prasad Yadav

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Emerging fire incidents are the protuberant contributor out turning into life loss, property damage and importantly firefighters. It insinuates that a firefighting and rescue operation of the existing equipment or apparatus and their proficiency is limited, particularly in annihilating firefighting environments. The proposed methodology will help in developing a technology which can be useful in minimizing the risks and losses due to fire. In this paper, design and development of combat mini vehicle comprising of multi-purpose nozzle system is proposed which can target diverse fires simultaneously at distinct time and location. Basically, the system is semi-automated type protection system which can be manoeuvred by controller. Designing of robust vehicle based on semi-automated protection type system is consummated using SolidWorks platform. Concept of developing a robust vehicle will help to fight fires in multiple directions reducing the time required to douse multiple fires.

Keywords: fire douse vehicle, multiple fires, multi-purpose nozzle, semi-automated system

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Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Yuri Zinchenko

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Recently, distributed storage systems have been used more and more in various aspects of everyday life. They provide such necessary properties as Scalability, Fault Tolerance, Durability, and others. At the same time, not only reliable but also fast data storage remains one of the most pressing issues in this area. That brings us to the consensus algorithm as one of the most important components that has a great impact on the functionality of a distributed system. This paper is the result of an analysis of several well-known consensus algorithms, such as Paxos and Raft. The algorithm it offers, called Sync, promotes, but does not insist on simultaneous writing to the nodes (which positively affects the overall writing speed) and tries to minimize the system's inactive time. This allows nodes to reach agreement on the system state in a shorter period, which is a critical factor for distributed systems. Also when developing Sync, a lot of attention was paid to such criteria as simplicity and intuitiveness, the importance of which is difficult to overestimate.

Keywords: sync, consensus algorithm, distributed system, leader-based, synchronization.

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Authors: A. Iaaly, O. Jadayel, R. Jadayel

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This paper explores the effectiveness of approaches used for the implementation of technology within central governments specifically Geographic Information Systems (GIS). It examines the extent to which various strategies to GIS implementation and its roll out to users within an organization is crucial for its long term assimilation. Depending on the contextual requirements, various implementation strategies exist spanning from the most revolutionary to the most evolutionary, which have an influence on the success of GIS projects and the realization of resulting business benefits within the central governments. This research compares between two strategies of GIS implementation within the Lebanese Municipalities. The first strategy is the “Technological Approach” which is focused on technology acquisition, overlaid on existing governmental frameworks. This approach gives minimal attention to capability building and the long term sustainability of the implemented program. The second strategy, referred to as the “Ecological Approach”, is naturally oriented to the function of the organization. This approach stresses on fostering the evolution of the program and on building the human capabilities. The Union of the Joumeh Municipalities will be presented as a case study under the “Ecological Approach” and the role of the GIS Center at the University of Balamand will be highlighted. Thus, this research contributes to the development of knowledge on technology implementation and the vital role of academia in the specific context of the Lebanese public sector so that this experience may pave the way for further applications.

Keywords: ecological approach GIS, low income countries, technological approach

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Authors: Sylvia Nkiru Ogbuoji

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This paper discussed the consequences of inadequate funding in Nigerian education system. It briefly explained the meaning of education in relation to the context and identified various ways education in Nigeria can be funded. It highlighted some of the consequences of inadequate funding education system to include: Inadequate facilitates for teaching and learning, western brain drain, unemployment, crises of poverty, low staff morale it. Finally, some recommendations were put forward, the government should improve the annual budget allocation to education, in order to achieve educational objective, also government should monitor the utilization of allocated funds to minimize embezzlement.

Keywords: consequences, corruption, education, funding

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Authors: Ala Abdessemed, Mohamed Seddik Oussama Belahmadi, Nabil Charchar, Abdefettah Gherib, Bradai Fares, Boussadia Chouaib Nour El-Islem

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Algerian cities are confronted with large quantities of waste generated by the disposal of household and similar residues in technical landfills (CET), such as the one in the location of Batna. The interaction between waste components and incoming water generates leachates rich in organic matter and trace elements, which require treatment before discharge. The aim of this study was to propose an effective process for treating the leachates, which were subjected to an initial chemical treatment using the (H₂O₂/UV) system. Optimal treatment conditions were determined at [H₂O₂] of 0.3 M and pH of 8.6. Next, two hybrid biological treatment systems were applied: hybrid system I (H₂O₂/UV/bacteria) and hybrid system II (H₂O₂/UV/bacteria/microalgae). The three processes resulted in the following degradation rates, expressed in terms of total organic carbon (TOC) 27.4% for the (H₂O₂/UV) system; 58.1% for the hybrid system I (H₂O₂/UV/Bacteria); 67.86% for the hybrid system II (H₂O₂/UV/Bacteria/Microalgae). This study demonstrates that a hybrid approach combining advanced oxidation processes and biological treatments is a highly effective alternative to achieve satisfactory treatment.

Keywords: leachate, landfill, advanced oxidation processes, biological treatment, bacteria, microalgae, total organic carbon

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Authors: Christofas Stergianos, Jason Atkin, Herve Morvan

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As air traffic increases, more airports are interested in utilizing optimization methods. Many processes happen in parallel at an airport, and complex models are needed in order to have a reliable solution that can be implemented for ground movement operations. The ground movement for aircraft in an airport, allocating a path to each aircraft to follow in order to reach their destination (e.g. runway or gate), is one process that could be optimized. The Quickest Path Problem with Time Windows (QPPTW) algorithm has been developed to provide a conflict-free routing of vehicles and has been applied to routing aircraft around an airport. It was subsequently modified to increase the accuracy for airport applications. These modifications take into consideration specific characteristics of the problem, such as: the pushback process, which considers the extra time that is needed for pushing back an aircraft and turning its engines on; stand holding where any waiting should be allocated to the stand; and runway sequencing, where the sequence of the aircraft that take off is optimized and has to be respected. QPPTW involves searching for the quickest path by expanding the search in all directions, similarly to Dijkstra’s algorithm. Finding a way to direct the expansion can potentially assist the search and achieve a better performance. We have further modified the QPPTW algorithm to use a heuristic approach in order to guide the search. This new algorithm is based on the A-star search method but estimates the remaining time (instead of distance) in order to assess how far the target is. It is important to consider the remaining time that it is needed to reach the target, so that delays that are caused by other aircraft can be part of the optimization method. All of the other characteristics are still considered and time windows are still used in order to route multiple aircraft rather than a single aircraft. In this way the quickest path is found for each aircraft while taking into account the movements of the previously routed aircraft. After running experiments using a week of real aircraft data from Zurich Airport, the new algorithm (A-star QPPTW) was found to route aircraft much more quickly, being especially fast in routing the departing aircraft where pushback delays are significant. On average A-star QPPTW could route a full day (755 to 837 aircraft movements) 56% faster than the original algorithm. In total the routing of a full week of aircraft took only 12 seconds with the new algorithm, 15 seconds faster than the original algorithm. For real time application, the algorithm needs to be very fast, and this speed increase will allow us to add additional features and complexity, allowing further integration with other processes in airports and leading to more optimized and environmentally friendly airports.

Keywords: a-star search, airport operations, ground movement optimization, routing and scheduling

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Authors: Abdallah F. Abd El-Mohsen, Ahmed A. Abdelsamee, Nouby M. Ghazaly

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Engine exhaust noise is considered one of the largest sources of vehicle exterior noise. Further reduction of noise from the vehicle exhaust system will be required, as the vehicle exterior noise regulations become stricter. Therefore, the present study has been carried out to illustrate the role of engine operating parameters and exhaust system construction factors on exhaust noise emitted. The measurements carried out using different exhaust systems, which are mainly used in today’s vehicle. The effect of engine speed on the spectra level of exhaust noise is recorded at engine speeds of 900 rpm, 1800 rpm, 2700, rpm 3600 rpm and 4500 rpm. The results indicate that the increase of engine speed causes a significant increase in the spectrum level of exhaust noise. The increase in the number of the outlet of the expansion chamber also reduces the overall level of exhaust noise.

Keywords: exhaust system, expansion chamber, engine speed, spectra

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Authors: Alex Sidarta Guglielmoni

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Since the 1970s, sustainable development has become increasingly present on the international agenda. The present work has as general objective to analyze, discuss and bring answers to the following question, what is the importance of the generation of electric energy through the wind power plants in the Brazilian electricity matrix between 2013 and 2019? To answer this question, we analyzed the generation of renewable energy from wind farms and the consumption of electricity in Brazil during the period of January 2013 until December 2020. The specific objectives of this research are: to analyze the public data, to identify the total wind generation, to identify the total wind capacity generation, to identify the percentage participation of the generation and generation capacity of wind energy in the Brazilian electricity matrix. In order to develop this research, it was necessary a bibliographic search, collection of secondary data, tabulation of generation data, and electricity capacity by a comparative analysis between wind power and the Brazilian electricity matrix. As a result, it was possible to observe how important Brazil is for global sustainable development and how much this country can grow with this, in view of its capacity and potential for generating wind power since this percentage has grown in past few years.

Keywords: wind power, Brazilian market, electricity matrix, generation capacity

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Authors: Antony Thomas Vanchipurrakkal

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Common property resource like fisheries is conserved and managed by fishermen with the help of Local Ecological Knowledge system. Various forms of Social and Ecological elements adapted to formularize management of Chakara fishery. This study tries for a better understanding of elements involved in fishery management in India, such traditional knowledge system practicing within the fishing communities for management and conservation of the marine resources. Participatory Rural Appraisal technique is applied to seize the traditional knowledge system in central Kerala coastal region, India. Socio-Ecological Analysis framework is used for the study. This paper discusses that traditional knowledge systems of chakara fishery and discloses need for inclusive governance system. The paper also discusses adaptation of different elements of the ecological, biological and institutional knowledge system in local ecological knowledge for sustain the fishery. A framework is formulized based on elements operating in chakara fishery management.

Keywords: common property, fisheries, India, local ecological knowledge, management

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Authors: Masoume Ehsani, Ning Zhu, Huu Doan, Ali Lohi, Amira Abdelrasoul

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Membrane fouling poses severe challenges in membrane-based wastewater treatment applications. Ultrasound (US) has been considered an effective fouling remediation technique in filtration processes. Bubble cavitation in the liquid medium results from the alternating rarefaction and compression cycles during the US irradiation at sufficiently high acoustic pressure. Cavitation microbubbles generated under US irradiation can cause eddy current and turbulent flow within the medium by either oscillating or discharging energy to the system through microbubble explosion. Turbulent flow regime and shear forces created close to the membrane surface cause disturbing the cake layer and dislodging the foulants, which in turn improve the cleaning efficiency and filtration performance. Therefore, the number, size, velocity, and oscillation pattern of the microbubbles created in the liquid medium play a crucial role in foulant detachment and permeate flux recovery. The goal of the current study is to gain in depth understanding of the influence of the US power intensity and frequency on the microbubble dynamics and its characteristics generated under US irradiation. In comparison with other imaging techniques, the synchrotron in-line Phase Contrast Imaging technique at the Canadian Light Source (CLS) allows in-situ observation and real-time visualization of microbubble dynamics. At CLS biomedical imaging and therapy (BMIT) polychromatic beamline, the effective parameters were optimized to enhance the contrast gas/liquid interface for the accuracy of the qualitative and quantitative analysis of bubble cavitation within the system. With the high flux of photons and the high-speed camera, a typical high projection speed was achieved; and each projection of microbubbles in water was captured in 0.5 ms. ImageJ software was used for post-processing the raw images for the detailed quantitative analyses of microbubbles. The imaging has been performed under the US power intensity levels of 50 W, 60 W, and 100 W, in addition to the US frequency levels of 20 kHz, 28 kHz, and 40 kHz. For the duration of 2 seconds of imaging, the effect of the US power and frequency on the average number, size, and fraction of the area occupied by bubbles were analyzed. Microbubbles’ dynamics in terms of their velocity in water was also investigated. For the US power increase of 50 W to 100 W, the average bubble number and the average bubble diameter were increased from 746 to 880 and from 36.7 µm to 48.4 µm, respectively. In terms of the influence of US frequency, a fewer number of bubbles were created at 20 kHz (average of 176 bubbles rather than 808 bubbles at 40 kHz), while the average bubble size was significantly larger than that of 40 kHz (almost seven times). The majority of bubbles were captured close to the membrane surface in the filtration unit. According to the study observations, membrane cleaning efficiency is expected to be improved at higher US power and lower US frequency due to the higher energy release to the system by increasing the number of bubbles or growing their size during oscillation (optimum condition is expected to be at 20 kHz and 100 W).

Keywords: bubble dynamics, cavitational bubbles, membrane fouling, ultrasonic cleaning

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Authors: Rajeshwar S. Matche, Subhash V. Pawde, Suraj P, Sachin R. Chaudhari

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Time Temperature Indicator’s (TTI) are trending approach in a food packaging that will be insightful to have safe and hygienic food products. Currently, available TTI in the market are mostly a product specific and sometime even difficult to handle especially in supply chain as these are pre-activated and require specific storage conditions. In the present study, research focus is on the development of a cost-effective lactic acid based TTI that can work over a wide range of temperature and can be activated at time of packaging or on demand. The correlation between activation energies of colour change of the developed indicator and packed pasteurized milk spoilage with respect to time and temperature was established. Developed lactic acid based TTI strips have range of activation energy from 10.13 to 24.20 KJ/mol. We found that the developed TTI strip’s with activation energy 12.42, and 14.41KJ/mol can be correlated with spoilage activation energy of packed pasteurized milk which was 25.71 KJ/mol with factor of 2 at storage temperature 4°C. The implementation of these TTI on packed pasteurized milk allow us see visual colour change during the storage and can be fruitful to monitoring quality of the milk and understand its freshness especially in a cold supply chain, viz distributor and road vendor etc.

Keywords: pasteurised packed milk, time temperature indicator, spoilage, freshness

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Authors: R. Hellmuth, F. Wehner

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Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Short-term rescheduling can no longer be handled by on-site inspections and manual measurements. The tight time schedules require up-to-date planning models. Due to the high adaptation rate of factories described above, a methodology for rescheduling factories on the basis of a modern digital factory twin is conceived and designed for practical application in factory restructuring projects. The focus is on rebuild processes. The aim is to keep the planning basis (digital factory model) for conversions within a factory up to date. This requires the application of a methodology that reduces the deficits of existing approaches. The aim is to show how a digital factory model can be kept up to date during ongoing factory operation. A method based on photogrammetry technology is presented. The focus is on developing a simple and cost-effective solution to track the many changes that occur in a factory building during operation. The method is preceded by a hardware and software comparison to identify the most economical and fastest variant. 

Keywords: digital factory model, photogrammetry, factory planning, restructuring

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Authors: Hasan Farahneh

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Smart asset management along roadsides and in deserted areas is a topic of deprived attention. We find most of the work in emergency reporting services in intelligent transportation systems (ITS) and rural areas but not much in asset reporting. Currently, available asset management mechanisms are based on scheduled maintenance and do not effectively report any emergency situation in a timely manner. This paper is the continuation of our previous work, in which we proposed the usage of Foglets and VLC link between smart vehicles and road side assets. In this paper, we propose a hybrid communication system for asset management and emergency reporting architecture for smart transportation. We incorporate Foglets along with visible light communication (VLC) and radio frequency (RF) communication. We present the channel model and parameters of a hybrid model to support an intelligent transportation system (ITS) system. Simulations show high improvement in the system performance in terms of communication range and received data. We present a comparative analysis of a hybrid ITS system.

Keywords: Internet of Things, Foglets, VLC, RF, smart vehicle, roadside asset management

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Authors: Yonas Shuke Kitawa

Abstract:

Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

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Authors: Rajamani Doraiswami, Lahouari Cheded

Abstract:

Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: Khalil Ahmad Kakar

Abstract:

In developing countries increasing the automobile and low capacity public transport (para-transit) which are creating congestion, pollution, noise, and traffic accident are the most critical quandary. These issues are under the analysis of assessors to break down the puzzle and propose sustainable urban public transport system. Kabul city is one of those urban areas that the inhabitants are suffering from lack of tolerable and friendly public transport system. The city is the most-populous and overcrowded with around 4.5 million population. The para-transit is the only dominant public transit system with a very poor level of services and low capacity vehicles (6-20 passengers). Therefore, this study after detailed investigations suggests bus rapid transit (BRT) system in Kabul City. It is aimed to mitigate the role of informal transport and decreases congestion. The research covers three parts. In the first part, aggregated travel demand modelling (four-step) is applied to determine the number of users for para-transit and assesses BRT network based on higher passenger demand for public transport mode. In the second part, state preference (SP) survey and binary logit model are exerted to figure out the utility of existing para-transit mode and planned BRT system. Finally, the impact of predicted BRT system on para-transit is evaluated. The extracted outcome based on high travel demand suggests 10 km network for the proposed BRT system, which is originated from the district tenth and it is ended at Kabul International Airport. As well as, the result from the disaggregate travel mode-choice model, based on SP and logit model indicates that the predicted mass rapid transit system has higher utility with the significant impact regarding the reduction of para-transit.

Keywords: BRT, para-transit, travel demand modelling, Kabul City, logit model

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Authors: Takuya Sumi, Syoko Nukaya, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

Abstract:

We propose an unconstrained measurement system for scratching motion based on mathematical model of unconstrained bed sensing method which could measure the bed vibrations due to the motion of the person on the bed. In this paper, we construct mathematical model of the unconstrained bed monitoring system, and we apply the unconstrained bed sensing method to the system for detecting scratching motion. The proposed sensors are placed under the three bed feet. When the person is lying on the bed, the output signals from the sensors are proportional to the magnitude of the vibration due to the scratching motion. Hence, we could detect the subject’s scratching motion from the output signals from ceramic sensors. We evaluated two scratching motions using the proposed system in the validity experiment as follows: First experiment is the subject’s scratching the right side cheek with his right hand, and; second experiment is the subject’s scratching the shin with another foot. As the results of the experiment, we recognized the scratching signals that enable the determination when the scratching occurred. Furthermore, the difference among the amplitudes of the output signals enabled us to estimate where the subject scratched.

Keywords: unconstrained bed sensing method, scratching, body movement, itchy, piezoceramics

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

Abstract:

Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 64