Search results for: 99.95% IoT data transmission savings

Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

Abstract:

Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

Procedia PDF Downloads 280

Authors: Abeer S. Elsherbiny, Ali H. Gemeay

Abstract:

In this study, graphene oxide (GO) nanosheets have been synthesized and characterized using different spectroscopic tools such as X-ray diffraction spectroscopy, infrared Fourier transform (FT-IR) spectroscopy, BET specific surface area and Transmission Electronic Microscope (TEM). The prepared GO was investigated for the removal of malachite green, a cationic dye from aqueous solution. The removal methods of malachite green has been proceeded via adsorption process. GO nanosheets can be predicted as a good adsorbent material for the adsorption of cationic species. The adsorption of the malachite green onto the GO nanosheets has been carried out at different experimental conditions such as adsorption kinetics, concentration of adsorbate, pH, and temperature. The kinetics of the adsorption data were analyzed using four kinetic models such as the pseudo first-order model, pseudo second-order model, intraparticle diffusion, and the Boyd model to understand the adsorption behavior of malachite green onto the GO nanosheets and the mechanism of adsorption. The adsorption isotherm of adsorption of the malachite green onto the GO nanosheets has been investigated at 25, 35 and 45 °C. The equilibrium data were fitted well to the Langmuir model. Various thermodynamic parameters such as the Gibbs free energy (ΔG°), enthalpy (ΔH°), and entropy (ΔS°) change were also evaluated. The interaction of malachite green onto the GO nanosheets has been investigated by infrared Fourier transform (FT-IR) spectroscopy.

Keywords: adsorption, graphene oxide, kinetics, malachite green

Procedia PDF Downloads 411

Authors: A. Cherifi, B. Bouazza, A. O. Dahmane, B. Yagoubi

Abstract:

Transmission over Optical channels will introduce inter-symbol interference (ISI) as well as inter-channel (or inter-carrier) interference (ICI). To decrease the effects of ICI, this paper proposes equalizer for the Optical OFDM system based on the fractional Fourier transform (FrFFT). In this FrFT-OFDM system, traditional Fourier transform is replaced by fractional Fourier transform to modulate and demodulate the data symbols. The equalizer proposed consists of sampling the received signal in the different time per time symbol. Theoretical analysis and numerical simulation are discussed.

Keywords: OFDM, (FrFT) fractional fourier transform, optical OFDM, equalization algorithm

Procedia PDF Downloads 430

Authors: James Kinsella

Abstract:

There is currently very little understanding of how the interaction between in- vestors, consumers, the firms (agents) affect a) the transmission of information, and b) the creation and transfer of value and wealth between these two groups. Employing scholarly ideas from multiple research areas (behavioural finance, emotional finance, econo-biology, and game theory) we develop a conceptual the- oretic model (the ‘bow-tie’ model) as a framework for considering this interaction. Our bow-tie model views information transfer, value and wealth creation, and transfer through the lens of “investor-consumer connection facilitated through the communicative medium of the ‘firm’ (agents)”. We confront our bow-tie model with theoretical and practical examples. Next, we utilise consumer and business confidence data alongside index data, to conduct quantitative analy- sis, to support our bow-tie concept, and to introduce the concept of “investor- consumer connection”. We highlight the importance of information persuasiveness, knowledge, and emotional categorization of characteristics in facilitating a communicative relationship between investors, consumers, and the firm (agents), forming academic and practical applications of the conceptual bow-tie model, alongside applications to wider instances, such as those seen within the Covid-19 pandemic.

Keywords: behavioral finance, emotional finance, economy-biology, social mood

Procedia PDF Downloads 126

Authors: Krishnamoorthy Sathiyan, Shanti Gopal Patra, Ronen Bar-Ziv, Tomer Zidki

Abstract:

Developing efficient non-noble metal catalysts that are cheap and durable for oxygen evolution reaction (OER) is a great challenge. Moreover, altering the electronic structure of the catalyst and structural engineering of the materials provide a new direction for enhancing the OER. Herein, we have successfully synthesized Fe and Co incorporated MoS₂ catalysts, which show improved catalytic activity for OER when compared with MoS₂, Fe-MoS₂, and Co-MoS₂. It was found that at an optimal ratio of Fe and Co, the electronic and structural modification of MoS₂ occurs, which leads to change in orientation and thereby enhances the active catalytic sites on the edges, which are more exposed for OER. The nanocomposites have been well characterized by X-ray diffraction (XRD), scanning electron microscope (SEM), and energy dispersive X-ray analysis (EDX), Elemental Mapping, transmission electron microscope (TEM), and high-resolution transmission electron microscope (HR-TEM) analysis. Among all, a particular ratio of FeCo-MoS₂ exhibits a much smaller onset with better catalytic current density. The remarkable catalytic activity is mainly attributed to the synergistic effect from the Fe and Co. Most importantly, our work provides an essential insight in altering the electronic structure of MoS₂ based materials by incorporating promoters such as Co and Fe in an optimal amount, which enhances OER activity.

Keywords: electrocatalysts, molybdenum disulfide, oxygen evolution reaction, transition metals

Procedia PDF Downloads 130

Authors: A. Talaei, M. Ahiduzzaman, A. Kumar

Abstract:

In Canada, an increase in the production of iron and steel is anticipated for satisfying the increasing demand of iron and steel in the oil sands and automobile industries. It is predicted that GHG emissions from iron and steel sector will show a continuous increase till 2030 and, with emissions of 20 million tonnes of carbon dioxide equivalent, the sector will account for more than 2% of total national GHG emissions, or 12% of industrial emissions (i.e. 25% increase from 2010 levels). Therefore, there is an urgent need to improve the energy intensity and to implement energy efficiency measures in the industry to reduce the GHG footprint. This paper analyzes the current energy consumption in the Canadian iron and steel industries and identifies energy efficiency opportunities to improve the energy intensity and mitigate greenhouse gas emissions from this industry. In order to do this, a demand tree is developed representing different iron and steel production routs and the technologies within each rout. The main energy consumer within the industry is found to be flared heaters accounting for 81% of overall energy consumption followed by motor system and steam generation each accounting for 7% of total energy consumption. Eighteen different energy efficiency measures are identified which will help the efficiency improvement in various subsector of the industry. In the sintering process, heat recovery from coolers provides a high potential for energy saving and can be integrated in both new and existing plants. Coke dry quenching (CDQ) has the same advantages. Within the blast furnace iron-making process, injection of large amounts of coal in the furnace appears to be more effective than any other option in this category. In addition, because coal-powered electricity is being phased out in Ontario (where the majority of iron and steel plants are located) there will be surplus coal that could be used in iron and steel plants. In the steel-making processes, the recovery of Basic Oxygen Furnace (BOF) gas and scrap preheating provides considerable potential for energy savings in BOF and Electric Arc Furnace (EAF) steel-making processes, respectively. However, despite the energy savings potential, the BOF gas recovery is not applicable in existing plants using steam recovery processes. Given that the share of EAF in steel production is expected to increase the application potential of the technology will be limited. On the other hand, the long lifetime of the technology and the expected capacity increase of EAF makes scrap preheating a justified energy saving option. This paper would present the results of the assessment of the above mentioned options in terms of the costs and GHG mitigation potential.

Keywords: Iron and Steel Sectors, Energy Efficiency Improvement, Blast Furnace Iron-making Process, GHG Mitigation

Procedia PDF Downloads 396

Authors: H. Fekhar

Abstract:

Design and implementation acquisition system using radio frequency (RF) ASK module and micro controllers PIC is proposed in this work. The paper includes hardware and software design. The design tools are divided into two units , namely the sender MCU and receiver.The system was designed to measure temperatures of two furnaces and pressure pneumatic process. The wireless transmitter unit use the 433.95 MHz band directly interfaced to micro controller PIC18F4620. The sender unit consists of temperatures-pressure sensors , conditioning circuits , keypad GLCD display and RF module.Signal conditioner converts the output of the sensors into an electric quantity suitable for operation of the display and recording system.The measurements circuits are connected directly to 10 bits multiplexed A/D converter.The graphic liquid crystal display (GLCD) is used . The receiver (RF) module connected to a second microcontroller ,receive the signal via RF receiver , decode the Address/data and reproduces the original data . The strategy adopted for establishing communication between the sender MCU and receiver uses the specific protocol “Header, Address and data”.The communication protocol dealing with transmission and reception have been successfully implemented . Some experimental results are provided to demonstrate the effectiveness of the proposed wireless system. This embedded system track temperatures – pressure signal reasonably well with a small error.

Keywords: microcontrollers, sensors, graphic liquid cristal display, protocol, temperature, pressure

Procedia PDF Downloads 459

Authors: Ankit Shai

Abstract:

CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

Procedia PDF Downloads 292

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

Procedia PDF Downloads 78

Authors: Manea Viorel, Puscoci Sorin, Stoichescu Dan Alexandru

Abstract:

Free Space Optics (FSO) is an optical telecommunication system that uses laser beam to transmit data at high bit rates via terrestrial atmosphere. This article describes a method to obtain higher bit rates, under unfavorable weather conditions using multiple optical beams, which carry information with low optical power. Optical link quality assessment is given by the attenuation on different weather conditions. The goal of this paper is to compare two transmission techniques: mono and multi beam, both affected by atmospheric attenuation, using OOK and L-PPM modulation. Link availability is evaluated using eye-diagram that provides information about the overall bit error rate of the system.

Keywords: free space optics, wireless optic, laser communication, spatial diversity

Procedia PDF Downloads 505

Authors: Nalinee Sophatsathit

Abstract:

This paper presents a variation of navigation systems which tallies every node along the shortest path from start to destination nodes. The underlying technique rests on the well-established Dijkstra Algorithm. The ultimate goal is to serve as a user navigation guide that furnishes stop over cost of every node along this shortest path, whereby users can decide whether or not to visit any specific nodes. The output is an implementable module that can be further refined to run on the Internet and smartphone technology. This will benefit large organizations having physical installations spreaded over wide area such as hospitals, universities, etc. The savings on service personnel, let alone lost time and unproductive work, are attributive to innovative navigation system management.

Keywords: navigation systems, shortest path, smartphone technology, user navigation guide

Procedia PDF Downloads 338

Authors: Nazli W. Hardy

Abstract:

A critical component in the Internet of Things (IoT) ecosystem is the need for secure and appropriate transmission, processing, and storage of the data. Our current forms of authentication, and identity and access management do not suffice because they are not designed to service cohesive, integrated, interconnected devices, and service applications. The seemingly endless opportunities of IoT are in fact circumscribed on multiple levels by concerns such as trust, privacy, security, loss of control, and related issues. This paper considers multi-factor authentication (MFA) mechanisms and cohesive identity relationship management (IRM) standards. It also surveys messaging protocols that are appropriate for the IoT ecosystem.

Keywords: identity relation management, multifactor authentication, protocols, survey of internet of things ecosystem

Procedia PDF Downloads 354

Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

Procedia PDF Downloads 246

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

Procedia PDF Downloads 378

Authors: Lim Sanny, Felix Christian

Abstract:

The use of heavy equipment in Indonesia is always increasing. Cost reduction in procurement of spare parts is the aim of the company. The spare parts in this research are focused in the kind of filters. On the early step, the choosing of priority filter will be studied further by using the ABC analysis. To find out future demand of the filter, this research is using demand forecast by utilizing the QM software for windows. And to find out the best method of inventory control for each kind of filter is by comparing the total cost of Economic Order Quantity and Quick response inventory method. For the three kind of filters which are Cartridge, Engine oil – pn : 600-211-123, Element, Transmission – pn : 424-16-11140, and Element, Hydraulic – pn : 07063-01054, the best forecasting method is Linear regression. The best method for inventory control of Cartridge, Engine oil – pn : 600-211-123 and Element, Transmission – pn : 424-16-11140, is Quick Response Inventory, while the best method for Element, Hydraulic – pn : 07063-01054 is Economic Order Quantity.

Keywords: strategy, inventory, ABC analysis, forecasting, economic order quantity, quick response inventory

Procedia PDF Downloads 364

Authors: A. Zarenezhad, A. Esfandiari, E. Zarenezhad, M. Mardkhoshnood

Abstract:

The aim of this study was to investigate the ultra-structure of the photoreceptor layer of male rats under the effect of methanol intoxication and protective effect of silymarin against the methanol toxicity. Fifteen adult male rats were divided into three groups: Control group, Experimental group I (received 4g/kg methanol by intraperitoneal injection for five days), Experimental group II (received 4 g/kg methanol by intraperitoneal injection for five days and received 250 mg/kg silymarin orally for three months). At the end of the experiment, the eyes were removed; retina was separated near the optic disc and studied by transmission electron microscope. Results showed that the retina in the experimental group I exhibited loss of outer segments and disorganization in inner segment. Increased extra cellular space, disappearance of outer limiting membrane and pyknotic nuclei were seen in this group. But normal outer segment, organized inner segment and normal outer limiting membrane were obvious after treatment with silymarin in experimental group II. These findings show that methanol causes damage in the photoreceptor layer of the rat retina and silymarin can protect the damage to retina against the methanol intoxication.

Keywords: ultra-structure, photoreceptor layer, methanol intoxication, silymarin, rat

Procedia PDF Downloads 292

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

Procedia PDF Downloads 162

Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 226

Authors: Basheer Idrees Balarabe, Aminu Hamisu Kura, Nabila Shehu

Abstract:

As the power demand rapidly increases, the generation and transmission systems are affected because of inadequate resources, environmental restrictions and other losses. The role of transient stability control in maintaining the steady-state operation in the occurrence of large disturbance and fault is to describe the ability of the power system to survive serious contingency in time. The application of a Unified power flow controller (UPFC) plays a vital role in controlling the active and reactive power flows in a transmission line. In this research, a genetic algorithm (GA) method is applied to determine the optimal location of the UPFC device in a power system network for the enhancement of the power-system Transient Stability. Optimal location of UPFC has Significantly Improved the transient stability, the damping oscillation and reduced the peak over shoot. The GA optimization Technique proposed was iteratively searches the optimal location of UPFC and maintains the unusual bus voltages within the satisfy limits. The result indicated that transient stability is improved and achieved the faster steady state. Simulations were performed on the IEEE 14 Bus test systems using the MATLAB/Simulink platform.

Keywords: UPFC, transient stability, GA, IEEE, MATLAB and SIMULINK

Procedia PDF Downloads 13

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

Procedia PDF Downloads 82

Authors: Bin Zhou, Tongli Lu, Jianwu Zhang, Hongtao Hao

Abstract:

Dual clutch transmissions (DCT) offer a high comfort performance in terms of the gearshift. Hydraulic multi-disk clutches are the key components of DCT, its engagement determines the shifting comfort. The prefill of the clutches requests an initial engagement which the clutches just contact against each other but not transmit substantial torque from the engine, this initial clutch engagement point is called the touch point. Open-loop control is typically implemented for the clutch prefill, a lot of uncertainties, such as oil temperature and clutch wear, significantly affects the prefill, probably resulting in an inappropriate touch point. Underfill causes the engine flaring in gearshift while overfill arises clutch tying up, both deteriorating the shifting comfort of DCT. Therefore, it is important to enable an adaptive capacity for the clutch prefills regarding the uncertainties. In this paper, a dynamic model of the hydraulic actuator system is presented, including the variable force solenoid and clutch piston, and validated by a test. Subsequently, the open-loop clutch prefill is simulated based on the proposed model. Two control parameters of the prefill, fast fill time and stable fill pressure is analyzed with regard to the impact on the prefill. The former has great effects on the pressure transients, the latter directly influences the touch point. Finally, an adaptive method is proposed for the clutch prefill during gear shifting, in which clutch fill control parameters are adjusted adaptively and continually. The adaptive strategy is changing the stable fill pressure according to the current clutch slip during a gearshift, improving the next prefill process. The stable fill pressure is increased by means of the clutch slip while underfill and decreased with a constant value for overfill. The entire strategy is designed in the Simulink/Stateflow, and implemented in the transmission control unit with optimization. Road vehicle test results have shown the strategy realized its adaptive capability and proven it improves the shifting comfort.

Keywords: clutch prefill, clutch slip, dual clutch transmission, touch point, variable force solenoid

Procedia PDF Downloads 308

Authors: H. Mayton, X. Yan, A. G. Taylor

Abstract:

Infested tomato seeds were used to investigate the influence of Xanthomonas euvesicatoria on germination and seed to seedling transmission in a controlled environment and greenhouse assays in an effort to develop effective seed treatments and characterize seed borne transmission of bacterial leaf spot of tomato. Bacterial leaf spot of tomato, caused by four distinct Xanthomonas species, X. euvesicatoria, X. gardneri, X. perforans, and X. vesicatoria, is a serious disease worldwide. In the United States, disease prevention is expensive for commercial growers in warm, humid regions of the country, and crop losses can be devastating. In this study, four different infested tomato seed lots were extracted from tomato fruits infected with bacterial leaf spot from a field in New York State in 2017 that had been inoculated with X. euvesicatoria. In addition, vacuum infiltration at 61 kilopascals for 1, 5, 10, and 15 minutes and seed soaking for 5, 10, 15, and 30 minutes with different bacterial concentrations were used to artificially infest seed in the laboratory. For controlled environment assays, infested tomato seeds from the field and laboratory were placed othe n moistened blue blotter in square plastic boxes (10 cm x 10 cm) and incubated at 20/30 ˚C with an 8/16 hour light cycle, respectively. Infested tomato seeds from the field and laboratory were also planted in small plastic trays in soil (peat-lite medium) and placed in the greenhouse with 24/18 ˚C day and night temperatures, respectively, with a 14-hour photoperiod. Seed germination was assessed after eight days in the laboratory and 14 days in the greenhouse. Polymerase chain reaction (PCR) using the hrpB7 primers (RST65 [5’- GTCGTCGTTACGGCAAGGTGGTG-3’] and RST69 [5’-TCGCCCAGCGTCATCAGGCCATC-3’]) was performed to confirm presence or absence of the bacterial pathogen in seed lots collected from the field and in germinating seedlings in all experiments. For infested seed lots from the field, germination was lowest (84%) in the seed lot with the highest level of bacterial infestation (55%) and ranged from 84-98%. No adverse effect on germination was observed from artificially infested seeds for any bacterial concentration and method of infiltration when compared to a non-infested control. Germination in laboratory assays for artificially infested seeds ranged from 82-100%. In controlled environment assays, 2.5 % were PCR positive for the pathogen, and in the greenhouse assays, no infected seedlings were detected. From these experiments, X. euvesicatoria does not appear to adversely influence germination. The lowest rate of germination from field collected seed may be due to contamination with multiple pathogens and saprophytic organisms as no effect of artificial bacterial seed infestation in the laboratory on germination was observed. No evidence of systemic movement from seed to seedling was observed in the greenhouse assays; however, in the controlled environment assays, some seedlings were PCR positive. Additional experiments are underway with green fluorescent protein-expressing isolates to further characterize seed to seedling transmission of the bacterial leaf spot pathogen in tomato.

Keywords: bacterial leaf spot, seed germination, tomato, Xanthomonas euvesicatoria

Procedia PDF Downloads 134

Authors: Chenyu Huang, Minrong Cui, Hua Fang, Luqing Zhang, Yunlong Yu

Abstract:

The emergence and spread of antibiotic resistance genes (ARGs) have become a pressing issue in global agricultural production. However, understanding how these ARGs spread across different spatial scales, especially when exposed to both pesticides and antibiotics, has remained a challenge. Here, metagenomic assembly and binning methodologies were used to determine the mechanism of ARG propagation within soil-lettuce systems exposed to both fungicides and antibiotics. The results of our study showed that the presence of fungicide and antibiotic stresses had a significant impact on certain bacterial communities. Notably, we observed that ARGs were primarily transferred from the soil to the plant through plasmids. The selective pressure exerted by fungicides and antibiotics contributed to an increase in unique ARGs present on lettuce leaves. Moreover, ARGs located on chromosomes and plasmids followed different transmission patterns. The presence of diverse selective pressures, a result of compound treatments involving antibiotics and fungicides, amplifies this phenomenon. Consequently, there is a higher probability of bacteria developing multi-antibiotic resistance under the combined pressure of fungicides and antibiotics. In summary, our findings highlight that combined fungicide and antibiotic treatments are more likely to drive the acquisition of ARGs within the soil-plant system and may increase the risk of human ingestion.

Keywords: soil-lettuce system, fungicide, antibiotic, ARG, transmission

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Authors: Ayed S. Al-Shihri, Abul Kalam, Abdullah G. Al-Sehemi, Gaohui Du, Tokeer Ahmad, Ahmad Irfan

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We report here the synthesis of nickel oxide (NiO) nanoparticles by microwave-assisted method, using a common precipitating agent followed by calcination in air at 400°C. The effect of the microwave and pH on the crystallite size, morphology, structure, energy band gap and surface area of NiO have been investigated by means of powder X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR), ultraviolet visible spectroscopy (UV-vis) and BET surface area studies. X-ray diffraction studies showed the formation of monophasic and highly crystalline cubic NiO. TEM analysis led to decrease the average grain size of NiO nanoparticles from 16.5 nm to 14 nm on increasing the amount of NaOH. FTIR studies also confirm the formation of NiO nanoparticles. It was observed that on increasing the volume of NaOH, the optical band gap energy (2.85 eV to 2.95 eV) and specific surface area (33.1 to 39.8 m2/g) increases, however the average particles size decreases (16.5 nm to 14 nm). This method may be extended to large scale synthesis of other metal oxides nanoparticles and the present study could be used for the potential applications in water treatment and many other fields.

Keywords: BET surface area analysis, electron microscopy, optical properties, X-ray techniques

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Authors: Pritika Ramharack, Mahmoud E. S. Soliman

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The re-emerging Zika virus is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus already been linked to irreversible chronic central nervous system (CNS) conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA-approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of Zika virus Methyltransferase and RNA-dependent RNA polymerase. This in silico “per-residue energy decomposition pharmacophore” virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.

Keywords: NS5 protein inhibitors, per-residue decomposition, pharmacophore model, virtual screening, Zika virus

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Authors: N. Khanyile, P. Dlamini, M. Masenya

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Background: Most of the population in Africa is still dependent on indigenous medicinal knowledge for treating and managing ailments. Indigenous traditional knowledge owners/practitioners who own this knowledge are consulted by communities, but their knowledge is not known how they get it. The question of how knowledge is acquired and preserved remains one of the biggest challenges in traditional healing and treatment with herbal medicines. It is regrettable that despite the importance and recognition of indigenous medicinal knowledge globally, the details of acquirement, storing and transmission, and preservation techniques are not known. Hence this study intends to unveil the process of acquirement and transmission, and preservation techniques of indigenous medical knowledge by its owners. Objectives: This study aims to assess the process of acquiring and preservation of traditional medicinal knowledge by traditional medicinal knowledge owners/practitioners in uMhlathuze Municipality, in the province of KwaZulu-Natal, South Africa. The study was guided by four research objectives which were to: identify the types of traditional medicinal knowledge owners who possess this knowledge, establish the approach used by indigenous medicinal knowledge owners/healers for acquiring medicinal knowledge, identify the process of preservation of medicinal knowledge by indigenous medicinal knowledge owners/healers, and determine the challenges encountered in transferring the knowledge. Method: The study adopted a qualitative research approach, and a snowball sampling technique was used to identify the study population. Data was collected through semi-structured interviews with indigenous medicinal knowledge owners. Results: The findings suggested that uMhlathuze municipality had different types of indigenous medicinal knowledge owners who possess valuable knowledge. These are diviners (Izangoma), faith healers (Abathandazi), and herbalists (Izinyanga). The study demonstrated that indigenous medicinal knowledge is acquired in many different ways, including visions, dreams, and vigorous training. The study also revealed the acquired knowledge is preserved or shared with specially chosen children and trainees. Conclusion: The study concluded that this knowledge is gotten through vigorous training, which requires the learner to be attentive and eager to learn. It was recommended that a study of this nature be conducted but at a broader level to enhance an informed conclusion and recommendations.

Keywords: preserving, indigenous medicinal knowledge, indigenous knowledge, indigenous medicinal knowledge owners/practitioners, acquiring

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Authors: Dong-Hyun Kim, Wan-Ho Chung, Hak-Sung Kim

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In this work, non-destructive evaluation was conducted to measure the sheet resistance of silver nanowire coated film and find a damage of that film using terahertz (THz) wave. Pulse type THz instrument was used, and the measurement was performed under transmission and pitch-catch reflection modes with 30 degree of incidence angle. In the transmission mode, the intensity of the THz wave was gradually increased as the conductivity decreased. Meanwhile, the intensity of THz wave was decreased as the conductivity decreased in the pitch-catch reflection mode. To confirm the conductivity of the film, sheet resistance was measured by 4-point probe station. Interaction formula was drawn from a relation between the intensity and the sheet resistance. Through substituting sheet resistance to the formula and comparing the resultant value with measured maximum THz wave intensity, measurement of sheet resistance using THz wave was more suitable than that using 4-point probe station. In addition, the damage on the silver nanowire coated film was detected by applying the THz image system. Therefore, the reliability of the entire film can be also be ensured. In conclusion, real-time monitoring using the THz wave can be applied in the transparent electrodes with detecting the damaged area as well as measuring the sheet resistance.

Keywords: terahertz wave, sheet resistance, non-destructive evaluation, silver nanowire

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Authors: Cha-ah C. N., Awah N. J., Mouiche M. M. M.

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Brucellosis is a neglected zoonotic disease of animals and man caused by bacteria of genus Brucella. Though eradicated in some parts of the world, it remains endemic in sub-Saharan Africa including Cameroon. The aim of this study was to contribute to the epidemiology of brucellosis in the North-West region of Cameroon by detecting the presence of anti-Brucella antibodies in bovine bulk milk as this serves as a route of transmission from animals to man. A cross sectional study was conducted to determine the prevalence of Brucella abortus antibodies in bovine bulk milk in the peri-urban zones of Bamenda. One hundred bulk milk samples were collected from 100 herds and tested by milk I-ELISA test. The conducted study revealed the presence of anti-Brucella abortus antibodies in bovine bulk milk. The study revealed that bovine brucellosis is widespread in animal production systems in this area. The animal infection pressure in these systems has remained strong due to movement of livestock in search of pasture, co-existence of animal husbandry, communal sharing of grazing land, concentration of animals around water points, abortions in production systems, locality of production systems and failure to quarantine upon introduction of new animals. The circulation of Brucella abortus antibodies in cattle farms recorded in the study revealed potential public health implication and suggest economic importance of brucellosis to the cattle industry in the Northwest region of Cameroon. The risk for re-emergence and transmission of brucellosis is evident as a result of the co-existence of animal husbandry activities and social-cultural activities that promote brucellosis transmission. Well-designed countrywide, evidence-based studies of brucellosis are needed. These could help to generate reliable frequency and potential impact estimates, to identify Brucella reservoirs, and to propose control strategies of proven efficacy.

Keywords: brucellosis, bulk milk, northwest region Cameroon, prevalence

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Authors: Kalaivani Pachiappan, Sabari Annaji, Nithya Jayakumar

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In recent years, Information security has emerged as foremost challenges in many fields. Especially in medical information systems security is a major issue, in handling reports such as patients’ diagnosis and medical images. These sensitive data require confidentiality for transmission purposes. Image sharing is a secure and fault-tolerant method for protecting digital images, which can use the cryptography techniques to reduce the information loss. In this paper, visual sharing method is proposed which embeds the patient’s details into a medical image. Then the medical image can be divided into numerous shared images and protected by various users. The original patient details and medical image can be retrieved by gathering the shared images.

Keywords: information security, medical images, cryptography, visual sharing

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

Procedia PDF Downloads 228