Search results for: analog signal processing

Authors: Dilshad Ali Mohammed, Ziyad Nayef Shamsulddin Aldoski, Millet Salim Mohammed

Abstract:

The increase in levels of traffic congestion along urban signalized arterials needs efficient traffic management. The application of traffic signal coordination can improve the traffic operation and safety for a series of signalized intersection along the arterials. The objective of this study is to evaluate the benefits achievable through actuated traffic signal coordination and make a comparison in control delay against the same signalized intersection in case of being isolated. To accomplish this purpose, a series of eight signalized intersections located on two major arterials in Duhok City was chosen for conducting the study. Traffic data (traffic volumes, link and approach speeds, and passenger car equivalent) were collected at peak hours. Various methods had been used for collecting data such as video recording technique, moving vehicle method and manual methods. Geometric and signalization data were also collected for the purpose of the study. The coupling index had been calculated to check the coordination attainability, and then time space diagrams were constructed representing one-way coordination for the intersections on Barzani and Zakho Streets, and others represented two-way coordination for the intersections on Zakho Street with accepted progression bandwidth efficiency. The results of this study show great progression bandwidth of 54 seconds for east direction coordination and 17 seconds for west direction coordination on Barzani Street under suggested controlled speed of 60 kph agreeable with the present data. For Zakho Street, the progression bandwidth is 19 seconds for east direction coordination and 18 seconds for west direction coordination under suggested controlled speed of 40 kph. The results show that traffic signal coordination had led to high reduction in intersection control delays on both arterials.

Keywords: bandwidth, congestion, coordination, traffic, signals, streets

Procedia PDF Downloads 307

Authors: N. A. Masevhe, M. Nemukula, S. S. Gololo, K. G. Kgosana

Abstract:

Background and Study Significance: Legume seeds are important in agriculture as they are used for feed formulations due to their nutrient-dense, low-cost, and easy accessibility. Although they are important sources of energy, proteins, carbohydrates, vitamins, and minerals, they contain abundant quantities of anti-nutritive factors that reduce the bioavailability of nutrients, digestibility of proteins, and mineral absorption in livestock. However, the removal of these factors is too costly as it requires expensive state-of-the-art techniques such as high pressure and thermal processing. Basic Methodologies: The aim of the study was to investigate cost-effective methods that can be used to reduce the inherent phytates as putative antinutrients in the legume seeds. The seeds of Arachis hypogaea, Pisum sativum and Vigna radiata L. were subjected to the single processing methods viz raw seeds plus dehulling (R+D), soaking plus dehulling (S+D), ordinary cooking plus dehulling (C+D), infusion plus dehulling (I+D), autoclave plus dehulling (A+D), microwave plus dehulling (M+D) and five combined methods (S+I+D; S+A+D; I+M+D; S+C+D; S+M+D). All the processed seeds were dried, ground into powder, extracted, and analyzed on a microplate reader to determine the percentage of phytates per dry mass of the legume seeds. Phytic acid was used as a positive control, and one-way ANOVA was used to determine the significant differences between the means of the processing methods at a threshold of 0.05. Major Findings: The results of the processing methods showed the percentage yield ranges of 39.1-96%, 67.4-88.8%, and 70.2-93.8% for V. radiata, A. hypogaea and P. sativum, respectively. Though the raw seeds contained the highest contents of phytates that ranged between 0.508 and 0.527%, as expected, the R+D resulted in a slightly lower phytate percentage range of 0.469-0.485%, while other processing methods resulted in phytate contents that were below 0.35%. The M+D and S+M+D methods showed low phytate percentage ranges of 0.276-0.296% and 0.272-0.294%, respectively, where the lowest percentage yield was determined in S+M+D of P. sativum. Furthermore, these results were found to be significantly different (p<0.05). Though phytates cause micronutrient deficits as they chelate important minerals such as calcium, zinc, iron, and magnesium, their reduction may enhance nutrient bioavailability since they cannot be digested by the ruminants. Concluding Statement: Despite the nutritive aspects of the processed legume seeds, which are still in progress, the M+D and S+M+D methods, which significantly reduced the phytates in the investigated legume seeds, may be recommended to the local farmers and feed-producing industries so as to enhance animal health and production at an affordable cost.

Keywords: anti-nutritive factors, extraction, legume seeds, phytate

Procedia PDF Downloads 28

Authors: Izabella Szollosi, Klara Marton

Abstract:

Aphasia can be defined as a weakness in accessing linguistic information. Accessing linguistic information is strongly related to information processing, which in turn is associated with the cognitive control system. According to the literature, a deficit in the cognitive control system interferes with language processing and contributes to non-fluent speech performance. The aim of our study was to explore this hypothesis by investigating how cognitive control interacts with language performance in participants with non-fluent aphasia. Cognitive control is a complex construct that includes working memory (WM) and the ability to resist proactive interference (PI). Based on previous research, we hypothesized that impairments in domain-general (DG) cognitive control abilities have negative effects on language processing. In contrast, better DG cognitive control functioning supports goal-directed behavior in language-related processes as well. Since stroke itself might slow down information processing, it is important to examine its negative effects on both cognitive control and language processing. Participants (N=52) in our study were individuals with non-fluent Broca’s aphasia (N = 13), with transcortical motor aphasia (N=13), individuals with stroke damage without aphasia (N=13), and unimpaired speakers (N = 13). All participants performed various computer-based tasks targeting cognitive control functions such as WM and resistance to PI in both linguistic and non-linguistic domains. Non-linguistic tasks targeted primarily DG functions, while linguistic tasks targeted more domain specific (DS) processes. The results showed that participants with Broca’s aphasia differed from the other three groups in the non-linguistic tasks. They performed significantly worse even in the baseline conditions. In contrast, we found a different performance profile in the linguistic domain, where the control group differed from all three stroke-related groups. The three groups with impairment performed more poorly than the controls but similar to each other in the verbal baseline condition. In the more complex verbal PI condition, however, participants with Broca’s aphasia performed significantly worse than all the other groups. Participants with Broca’s aphasia demonstrated the most severe language impairment and the highest vulnerability in tasks measuring DG cognitive control functions. Results support the notion that the more severe the cognitive control impairment, the more severe the aphasia. Thus, our findings suggest a strong interaction between cognitive control and language. Individuals with the most severe and most general cognitive control deficit - participants with Broca’s aphasia - showed the most severe language impairment. Individuals with better DG cognitive control functions demonstrated better language performance. While all participants with stroke damage showed impaired cognitive control functions in the linguistic domain, participants with better language skills performed also better in tasks that measured non-linguistic cognitive control functions. The overall results indicate that the level of cognitive control deficit interacts with the language functions in individuals along with the language spectrum (from severe to no impairment). However, future research is needed to determine any directionality.

Keywords: cognitive control, information processing, language performance, non-fluent aphasia

Procedia PDF Downloads 122

Authors: Deepak M. Sajnekar, S. B. Deshpande, R. M. Mohril

Abstract:

At present many rotary excitation control system are using analog type of Automatic Voltage Regulator which now started to replace with the digital automatic voltage regulator which is provided with PID controller and tuning of PID controller is a challenging task. The cases where digital excitation control system is used tuning of PID controller are still carried out by pole placement method. Tuning of PID controller used for static excitation control system is not challenging because it does not involve exciter time constant. This paper discusses two methods of tuning PID controller i.e. Pole placement method and pole zero cancellation method. GUI prepared for both the methods on the platform of MATLAB. Using this GUI, performance results and time required for tuning for both the methods are compared. Sensitivity of the methods is also presented with parameter variation like loop gain ‘K’ and exciter time constant ‘te’.

Keywords: digital excitation system, automatic voltage regulator, pole placement method, pole zero cancellation method

Procedia PDF Downloads 678

Authors: A. T. Zhakiyenova, E. E. Zhatkanbaev, Zh. K. Zhatkanbaeva

Abstract:

Nickel plays an important role in mechanical engineering and creation of military equipment; practically all steel are alloyed by nickel and other metals for receiving more durable, heat-resistant, corrosion-resistant steel and cast iron. There are many ways of processing of nickel in the world. Generally, it is igneous metallurgy methods. In this article, the review of majority existing ways of technologies of processing silicate nickel - cobalt ores is considered. Leaching of ores of a field Bugetkol is investigated by solution of sulfuric acid. We defined a specific consumption of sulfuric acid in relation to the mass of ore and to the mass of metal.

Keywords: cobalt, degree of extraction, hydrometallurgy, igneous metallurgy, leaching, matte, nickel

Procedia PDF Downloads 385

Authors: Benjamin Kuester, Bjoern Eilert, Malte Stonis, Ludger Overmeyer

Abstract:

Increasing quality requirements make reliable and effective quality management indispensable. This includes the complaint handling in which the 8D method is widely used. The 8D report as a written documentation of the 8D method is one of the key quality documents as it internally secures the quality standards and acts as a communication medium to the customer. In practice, however, the 8D report is mostly faulty and of poor quality. There is no quality control of 8D reports today. This paper describes the use of natural language processing for the automated evaluation of 8D reports. Based on semantic analysis and text-mining algorithms the presented system is able to uncover content and formal quality deficiencies and thus increases the quality of the complaint processing in the long term.

Keywords: 8D report, complaint management, evaluation system, text-mining

Procedia PDF Downloads 315

Authors: Sipu Guo, Silin Huang

Abstract:

Background: Most studies investigate the link between executive function and allostatic load (AL) among adults aged 18 years and older. Studies differed regarding the specific biological indicators studied and executive functions accounted for. Specific executive functions may be differentially related to allostatic load. We investigated the comorbidities of executive functions and allostatic load via network analysis. Methods: We included 603 adolescents (49.84% girls; Mean age = 12.38, SD age = 1.79) from junior high school in rural China. Eight biological markers at T1 and four executive function tasks at T2 were used to evaluate networks. Network analysis was used to determine the network structure, core symptoms, and bridge symptoms in the AL-executive function network among rural adolescents. Results: The executive functions were related to 6 AL biological markers, not to cortisol and epinephrine. The most influential symptoms were inhibition control, cognitive flexibility, processing speed, and systolic blood pressure (SBP). SBP, dehydroepiandrosterone, and processing speed were the bridges through which AL was related to executive functions. dehydroepiandrosterone strongly predicted processing speed. The SBP was the biggest influencer in the entire network. Conclusions: We found evidence for differential relations between markers and executive functions. SBP was a driver in the network; dehydroepiandrosterone showed strong relations with executive function.

Keywords: allostatic load, executive function, network analysis, rural adolescent

Procedia PDF Downloads 52

Authors: Weijie Gu, Sergio Martinez, Hoai Nguyen, Hongtao Xu, Piet Herdewijn, Steven De Jonghe, Kalyan Das

Abstract:

Nucleotide analogs are used for treating viral infections such as HIV, hepatitis B, hepatitis C, influenza, and SARS-CoV-2. To become polymerase substrates, a nucleotide analog must be phosphorylated by cellular kinases, which are rate-limiting. The goal of this study is to develop dNTP/NTP analogs directly from nucleotides. Tenofovir (TFV) analogs were synthesized by conjugating with natural or unnatural amino acids. It demonstrates that some conjugates act as dNTP analogs, and HIV-1 reverse transcriptase (RT) catalytically incorporates the TFV part as the chain terminator. X-ray structures in complex with HIV-1 RT/dsDNA showed binding of the conjugates at the polymerase active site, however, in different modes in the presence of Mg²⁺ vs. Mn²⁺ ions. The adaptability of the compounds is seemingly essential for catalytic incorporation of TFV by RT. 4d with a carboxyl sidechain demonstrated the highest incorporation. 4e showed weak incorporation and rather behaved as a dNTP-competitive inhibitor. This result advocates the feasibility of designing NTP/dNTP analogs by chemical substitutions to nucleotide analogs.

Keywords: dNTP analogs, nucleotide analogs, polymerase, tenofovir, X-ray structure

Procedia PDF Downloads 153

Authors: Xiaoyan Dai, Hsieh Yisan

Abstract:

Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

Procedia PDF Downloads 168

Authors: Magali Mari, Misha Muller

Abstract:

The present study’s objectives were to determine how diverse implicit stereotypes affect the processing of written information and linguistic inferential processes, such as presupposition accommodation. When reading a text, one constructs a representation of the described situation, which is then updated, according to new outputs and based on stereotypes inscribed within society. If the new output contradicts stereotypical expectations, the representation must be corrected, resulting in longer reading times. A similar process occurs in cases of linguistic inferential processes like presupposition accommodation. Presupposition accommodation is traditionally regarded as fast, automatic processing of background information (e.g., ‘Mary stopped eating meat’ is quickly processed as Mary used to eat meat). However, very few accounts have investigated if this process is likely to be influenced by domains of social cognition, such as implicit stereotypes. To study the effects of implicit stereotypes on presupposition accommodation, adults were recorded while they read sentences in French, combining two methods, an eye-tracking task and a classic self-paced reading task (where participants read sentence segments at their own pace by pressing a computer key). In one condition, presuppositions were activated with the French definite articles ‘le/la/les,’ whereas in the other condition, the French indefinite articles ‘un/une/des’ was used, triggering no presupposition. Using a definite article presupposes that the object has already been uttered and is thus part of background information, whereas using an indefinite article is understood as the introduction of new information. Two types of stereotypes were under examination in order to enlarge the scope of stereotypes traditionally analyzed. Study 1 investigated gender stereotypes linked to professional occupations to replicate previous findings. Study 2 focused on nationality-related stereotypes (e.g. ‘the French are seducers’ versus ‘the Japanese are seducers’) to determine if the effects of implicit stereotypes on reading are generalizable to other types of implicit stereotypes. The results show that reading is influenced by the two types of implicit stereotypes; in the two studies, the reading pace slowed down when a counter-stereotype was presented. However, presupposition accommodation did not affect participants’ processing of information. Altogether these results show that (a) implicit stereotypes affect the processing of written information, regardless of the type of stereotypes presented, and (b) that implicit stereotypes prevail over the superficial linguistic treatment of presuppositions, which suggests faster processing for treating social information compared to linguistic information.

Keywords: eye-tracking, implicit stereotypes, reading, social cognition

Procedia PDF Downloads 198

Authors: Edgar Gasafi, Robert Pardemann, Linus Perander

Abstract:

For the production of lithium carbonate or hydroxide out of lithium bearing ores, a thermal activation (calcination/decrepitation) is required for the phase transition in the mineral to enable an acid respectively soda leaching in the downstream hydrometallurgical section. In this paper, traditional processing in Lithium industry is reviewed, and opportunities to reduce energy consumption and improve product quality and recovery rate will be discussed. The conventional process approach is still based on rotary kiln calcination, a technology in use since the early days of lithium ore processing, albeit not significantly further developed since. A new technology, at least for the Lithium industry, is fluidized bed calcination. Decrepitation of lithium ore was investigated at Outotec’s Frankfurt Research Centre. Focusing on fluidized bed technology, a study of major process parameters (temperature and residence time) was performed at laboratory and larger bench scale aiming for optimal product quality for subsequent processing. The technical feasibility was confirmed for optimal process conditions on pilot scale (400 kg/h feed input) providing the basis for industrial process design. Based on experimental results, a comprehensive Aspen Plus flow sheet simulation was developed to quantify mass and energy flow for the rotary kiln and fluidized bed system. Results show a significant reduction in energy consumption and improved process performance in terms of temperature profile, product quality and plant footprint. The major conclusion is that a substantial reduction of energy consumption can be achieved in processing Lithium bearing ores by using fluidized bed based systems. At the same time and different from rotary kiln process, an accurate temperature and residence time control is ensured in fluidized-bed systems leading to a homogenous temperature profile in the reactor which prevents overheating and sintering of the solids and results in uniform product quality.

Keywords: calcination, decrepitation, fluidized bed, lithium, spodumene

Procedia PDF Downloads 230

Authors: Maher Ali Rusho, Sudipta Halder

Abstract:

The purpose of the study is to develop optimal solutions for models of parallel computing systems using the Java language. During the study, programmes were written for the examined models of parallel computing systems. The result of the parallel sorting code is the output of a sorted array of random numbers. When processing data in parallel, the time spent on processing and the first elements of the list of squared numbers are displayed. When processing requests asynchronously, processing completion messages are displayed for each task with a slight delay. The main results include the development of optimisation methods for algorithms and processes, such as the division of tasks into subtasks, the use of non-blocking algorithms, effective memory management, and load balancing, as well as the construction of diagrams and comparison of these methods by characteristics, including descriptions, implementation examples, and advantages. In addition, various specialised libraries were analysed to improve the performance and scalability of the models. The results of the work performed showed a substantial improvement in response time, bandwidth, and resource efficiency in parallel computing systems. Scalability and load analysis assessments were conducted, demonstrating how the system responds to an increase in data volume or the number of threads. Profiling tools were used to analyse performance in detail and identify bottlenecks in models, which improved the architecture and implementation of parallel computing systems. The obtained results emphasise the importance of choosing the right methods and tools for optimising parallel computing systems, which can substantially improve their performance and efficiency.

Keywords: algorithm optimisation, memory management, load balancing, performance profiling, asynchronous programming.

Procedia PDF Downloads 12

Authors: E. A. Alshaafi, A. Prakash

Abstract:

Oil-water emulsions are commonly encountered in various industrial operations and at different stages of crude oil production and processing. Emulsions are often difficult to track and treat and can cause a number of costly problems which need to be avoided. The characteristics of the emulsion phase can vary with crude composition and types of impurities present in oil. The objectives of this study are the development of ultrasonic techniques to track and characterize emulsion phase generated during production and cleaning of crude oil. The position of emulsion layer is monitored with the help of ultrasonic probes suitably placed in the vessel. The sensitivity of the technique and its potential has been demonstrated based on extensive testing with different oil samples. The technique is also being developed to monitor emulsion phase characteristics such as stability, composition, and droplet size distribution. The ultrasonic parameters recorded are changes in acoustic velocity, signal attenuation and its frequency spectrum. Emulsion has been prepared with light mineral oil sample and the effects of various factors including mixing speed, temperature, surfactant, and solid particles concentrations have been investigated. The applied frequency for ultrasonic waves has been varied from 1 to 5 MHz to carry out a sensitivity analysis. Emulsion droplet structure is observed with optical microscopy and stability is examined by tracking the changes in ultrasonic parameters with time. A model based on ultrasonic attenuation spectroscopy is being developed and tested to track changes in droplet size distribution with time.

Keywords: ultrasonic techniques, emulsion, characterization, droplet size

Procedia PDF Downloads 175

Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf

Abstract:

Enacted tasks are typically remembered better than when the same task materials are only verbally encoded, a robust finding referred to as the enactment effect. It has been assumed that enactment effect is independent of object presence but the size of enactment effect can be increased by providing objects at study phase in adults. To clarify the issues in children, free recall and cued recall performance of action phrases with or without using real objects were compared in 410 school-aged children from four age groups (8, 10, 12 and 14 years old). In this study, subjects were instructed to learn a series of action phrases under three encoding conditions, participants listened to verbal action phrases (VTs), performed the phrases (SPTs: subject-performed tasks), and observed the experimenter perform the phrases (EPTs: experimenter-performed tasks). Then, free recall and cued recall memory tests were administrated. The results revealed that the real object compared with imaginary objects improved recall performance in SPTs and EPTs, but more so in VTs. It was also found that the object presence was not necessary for the occurrence of the enactment effect but it was changed the size of enactment effect in all age groups. The size of enactment effect was more pronounced for imaginary objects than the real object in both free recall and cued recall memory tests in children. It was discussed that SPTs and EPTs deferentially facilitate item-specific and relation information processing and providing the objects can moderate the processing underlying the encoding conditions.

Keywords: action memory, enactment effect, item-specific processing, object, relational processing, school-aged children

Procedia PDF Downloads 238

Authors: Muhammad Bilal, Adil Ahmed

Abstract:

This study proposes an approach for electrical induction motor predictive maintenance utilizing machine learning algorithms. On the basis of a study of temperature data obtained from sensors put on the motor, the goal is to predict motor failures. The proposed models are trained to identify whether a motor is defective or not by utilizing machine learning algorithms like Support Vector Machines (SVM) and K-Nearest Neighbors (KNN). According to a thorough study of the literature, earlier research has used motor current signature analysis (MCSA) and vibration data to forecast motor failures. The temperature signal methodology, which has clear advantages over the conventional MCSA and vibration analysis methods in terms of cost-effectiveness, is the main subject of this research. The acquired results emphasize the applicability and effectiveness of the temperature-based predictive maintenance strategy by demonstrating the successful categorization of defective motors using the suggested machine learning models.

Keywords: predictive maintenance, electrical induction motors, machine learning, temperature signal methodology, motor failures

Procedia PDF Downloads 117

Authors: Jordan Gallant

Abstract:

In the compound word processing literature, much attention has been paid to the relationship between a compound’s denotational meaning and that of its morphological whole-word constituents, which is referred to as ‘semantic transparency’. However, the parallel relationship between a compound’s connotation and that of its constituents has not been addressed at all. For instance, while a compound like ‘painkiller’ might be semantically transparent, it is not ‘affectively transparent’. That is, both constituents have primarily negative connotations, while the whole compound has a positive one. This paper investigates the role of affective transparency on compound processing using two methodologies commonly employed in this field: a lexical decision task and a typing task. The critical stimuli used were 112 English bi-constituent compounds that differed in terms of the effective transparency of their constituents. Of these, 36 stimuli contained constituents with similar connotations to the compound (e.g., ‘dreamland’), 36 contained constituents with more positive connotations (e.g. ‘bedpan’), and 36 contained constituents with more negative connotations (e.g. ‘painkiller’). Connotation of whole-word constituents and compounds were operationalized via valence ratings taken from an off-line ratings database. In Experiment 1, compound stimuli and matched non-word controls were presented visually to participants, who were then asked to indicate whether it was a real word in English. Response times and accuracy were recorded. In Experiment 2, participants typed compound stimuli presented to them visually. Individual keystroke response times and typing accuracy were recorded. The results of both experiments provided positive evidence that compound processing is influenced by effective transparency. In Experiment 1, compounds in which both constituents had more negative connotations than the compound itself were responded to significantly more slowly than compounds in which the constituents had similar or more positive connotations. Typed responses from Experiment 2 showed that inter-keystroke intervals at the morphological constituent boundary were significantly longer when the connotation of the head constituent was either more positive or more negative than that of the compound. The interpretation of this finding is discussed in the context of previous compound typing research. Taken together, these findings suggest that affective transparency plays a role in the recognition, storage, and production of English compound words. This study provides a promising first step in a new direction for research on compound words.

Keywords: compound processing, semantic transparency, typed production, valence

Procedia PDF Downloads 127

Authors: Steffen Schieweck, Johannes Dregger, Sascha Kaczmarek, Michael ten Hompel

Abstract:

Logistics distributors face the issue of having to provide increasing service levels while being forced to reduce costs at the same time. Same-day delivery, quick order processing and rapidly growing ranges of articles are only some of the prevailing challenges. One key aspect of the performance of an intra-logistics system is how often and in which amplitude congestions and dysfunctions affect the processing operations. By gaining knowledge of the so called ‘performance availability’ of such a system during the planning stage, oversizing and wasting can be reduced whereas planning transparency is increased. State of the art for the determination of this KPI are simulation studies. However, their structure and therefore their results may vary unforeseeably. This article proposes a concept for the establishment of ‘certified’ and hence reliable and comparable simulation models.

Keywords: intra-logistics, performance availability, simulation, warehousing

Procedia PDF Downloads 454

Authors: Eid Alharbi, Yaser Miaji

Abstract:

The quality level for fresh fruits is very important for the fruit industries. In presents study, an automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics, NIR, fruit quality, spectroscopic technology, mechatronic design

Procedia PDF Downloads 390

Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

Abstract:

Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

Procedia PDF Downloads 316

Authors: Tim Dunne, Jiaxiang Ren, Lei Zhao, Peng Cheng, Yi Song, Yu Liu, Wenhan Yue, Xiongwen Yang

Abstract:

Two decades of the Shale Revolution has transforming transformed the global energy market, in part by the adaption of multi-stage dissolvable frac plugs. Magnesium has been favored for the bulk of plugs, requiring development of materials to suit specific field requirements. Herein, the mechanical and dissolution results from equal channel angular pressing (ECAP) of two cast dissolvable magnesium alloy are described. ECAP was selected as a route to increase the mechanical properties of two formulations of dissolvable magnesium, as solutionizing failed. In this study, 1” square cross section samples cast Mg alloys formulations containing rare earth were processed at temperatures ranging from 200 to 350 °C, at a rate of 0.005”/s, with a backpressure from 0 to 70 MPa, in a brass, or brass + graphite sheet. Generally, the yield and ultimate tensile strength (UTS) doubled for all. For formulation DM-2, the yield increased from 100 MPa to 250 MPa; UTS from 175 MPa to 325 MPa, but the strain fell from 2 to 1%. Formulation DM-3 yield increased from 75 MPa to 200 MPa, UTS from 150 MPa to 275 MPa, with strain increasing from 1 to 3%. Meanwhile, ECAP has also been found to reduce the dissolution rate significantly. A microstructural analysis showed grain refinement of the alloy and the movement of secondary phases away from the grain boundary. It is believed that reconfiguration of the grain boundary phases increased the mechanical properties and decreased the dissolution rate. ECAP processing of dissolvable high rare earth content magnesium is possible despite the brittleness of the material. ECAP is a possible processing route to increase mechanical properties for dissolvable aluminum alloys that do not extrude.

Keywords: equal channel angular processing, dissolvable magnesium, frac plug, mechanical properties

Procedia PDF Downloads 116

Authors: S. J. Arif

Abstract:

In the presented technique, a simple method is given for accurate measurement and control of power frequency deviation. The sinusoidal signal for which the frequency deviation measurement is required is transformed to a low voltage level and passed through a zero crossing detector to convert it into a pulse train. Another stable square wave signal of 10 KHz is obtained using a crystal oscillator and decade dividing assemblies (DDA). These signals are combined digitally and then passed through decade counters to give a unique combination of pulses or levels, which are further encoded to make them equally suitable for both control applications and display units. The developed circuit using discrete components has a resolution of 0.5 Hz and completes measurement within 20 ms. The realized circuit is simulated and synthesized using Verilog HDL and subsequently implemented on FPGA. The results of measurement on FPGA are observed on a very high resolution logic analyzer. These results accurately match the simulation results as well as the results of same circuit implemented with discrete components. The proposed system is suitable for accurate measurement and control of power frequency deviation.

Keywords: digital encoder for frequency measurement, frequency deviation measurement, measurement and control systems, power systems

Procedia PDF Downloads 376

Authors: Harsh Vikram Singh, Ankur Rai, Anand Mohan

Abstract:

In this paper, we propose secure and robust data hiding algorithm based on DCT by Arnold transform and chaotic sequence. The watermark image is scrambled by Arnold cat map to increases its security and then the chaotic map is used for watermark signal spread in middle band of DCT coefficients of the cover image The chaotic map can be used as pseudo-random generator for digital data hiding, to increase security and robustness .Performance evaluation for robustness and imperceptibility of proposed algorithm has been made using bit error rate (BER), normalized correlation (NC), and peak signal to noise ratio (PSNR) value for different watermark and cover images such as Lena, Girl, Tank images and gain factor .We use a binary logo image and text image as watermark. The experimental results demonstrate that the proposed algorithm achieves higher security and robustness against JPEG compression as well as other attacks such as addition of noise, low pass filtering and cropping attacks compared to other existing algorithm using DCT coefficients. Moreover, to recover watermarks in proposed algorithm, there is no need to original cover image.

Keywords: data hiding, watermarking, DCT, chaotic sequence, arnold transforms

Procedia PDF Downloads 515

Authors: Samira Baghbanbari, A. B. P. Lever, Payam S. Shabestari, Donald Weaver

Abstract:

Existing signal transmission models, although undoubtedly useful, have proven insufficient to explain the full complexity of information transfer within the central nervous system. The development of transformative models will necessitate a more comprehensive understanding of neuronal lipid membrane electrophysiology. Pursuant to this goal, the role of highly organized interfacial phospholipid-water layers emerges as a promising case study. A series of phospholipids in neural-glial gap junction interfaces as well as cholesterol molecules have been computationally modelled using high-performance density functional theory (DFT) calculations. Subsequent 'charge decomposition analysis' calculations have revealed a net transfer of charge from phospholipid orbitals through the organized interfacial water layer before ultimately finding its way to cholesterol acceptor molecules. The specific pathway of charge transfer from phospholipid via water layers towards cholesterol has been mapped in detail. Cholesterol is an essential membrane component that is overrepresented in neuronal membranes as compared to other mammalian cells; given this relative abundance, its apparent role as an electronic acceptor may prove to be a relevant factor in further signal transmission studies of the central nervous system. The timescales over which this electronic charge transfer occurs have also been evaluated by utilizing a system design that systematically increases the number of water molecules separating lipids and cholesterol. Memory loss through hydrogen-bonded networks in water can occur at femtosecond timescales, whereas existing action potential-based models are limited to micro or nanosecond scales. As such, the development of future models that attempt to explain faster timescale signal transmission in the central nervous system may benefit from our work, which provides additional information regarding fast timescale energy transfer mechanisms occurring through interfacial water. The study possesses a dataset that includes six distinct phospholipids and a collection of cholesterol. Ten optimized geometric characteristics (features) were employed to conduct binary classification through an artificial neural network (ANN), differentiating cholesterol from the various phospholipids. This stems from our understanding that all lipids within the first group function as electronic charge donors, while cholesterol serves as an electronic charge acceptor.

Keywords: charge transfer, signal transmission, phospholipids, water layers, ANN

Procedia PDF Downloads 72

Authors: M. Shaker, S. Minaei, M. H. Khoshtaghaza, A. Banakar, A. Jafari

Abstract:

In this study a system of machine vision and singulation was developed to separate paddy from rice and determine paddy husking and rice breakage percentages. The machine vision system consists of three main components including an imaging chamber, a digital camera, a computer equipped with image processing software. The singulation device consists of a kernel holding surface, a motor with vacuum fan, and a dimmer. For separation of paddy from rice (in the image), it was necessary to set a threshold. Therefore, some images of paddy and rice were sampled and the RGB values of the images were extracted using MATLAB software. Then mean and standard deviation of the data were determined. An Image processing algorithm was developed using MATLAB to determine paddy/rice separation and rice breakage and paddy husking percentages, using blue to red ratio. Tests showed that, a threshold of 0.75 is suitable for separating paddy from rice kernels. Results from the evaluation of the image processing algorithm showed that the accuracies obtained with the algorithm were 98.36% and 91.81% for paddy husking and rice breakage percentage, respectively. Analysis also showed that a suction of 45 mmHg to 50 mmHg yielding 81.3% separation efficiency is appropriate for operation of the kernel singulation system.

Keywords: breakage, computer vision, husking, rice kernel

Procedia PDF Downloads 381

Authors: Hazem Munawer Al-Otum

Abstract:

In this work, an efficient watermarking technique is proposed and can be used for detecting intentional attacks in RGB color images. The proposed technique can be implemented for image authentication and exhibits high robustness against unintentional common image processing attacks. It deploys two measures to discern between intentional and unintentional attacks based on using a quantization-based technique in a modified 2D multi-pyramidal DWT transform. Simulations have shown high accuracy in detecting intentionally attacked regions while exhibiting high robustness under moderate to severe common image processing attacks.

Keywords: image authentication, copyright protection, semi-fragile watermarking, tamper detection

Procedia PDF Downloads 255

Authors: S. Srinivasan, E. Cretu

Abstract:

The information flow (e.g. block-diagram or signal flow graph) paradigm for the design and simulation of Microelectromechanical (MEMS)-based systems allows to model MEMS devices using causal transfer functions easily, and interface them with electronic subsystems for fast system-level explorations of design alternatives and optimization. Nevertheless, the physical bi-directional coupling between different energy domains is not easily captured in causal signal flow modeling. Moreover, models of fundamental components acting as building blocks (e.g. gap-varying MEMS capacitor structures) depend not only on the component, but also on the specific excitation mode (e.g. voltage or charge-actuation). In contrast, the energy flow modeling paradigm in terms of generalized across-through variables offers an acausal perspective, separating clearly the physical model from the boundary conditions. This promotes reusability and the use of primitive physical models for assembling MEMS devices from primitive structures, based on the interconnection topology in generalized circuits. The physical modeling capabilities of Simscape have been used in the present work in order to develop a MEMS library containing parameterized fundamental building blocks (area and gap-varying MEMS capacitors, nonlinear springs, displacement stoppers, etc.) for the design, simulation and optimization of MEMS inertial sensors. The models capture both the nonlinear electromechanical interactions and geometrical nonlinearities and can be used for both small and large signal analyses, including the numerical computation of pull-in voltages (stability loss). Simscape behavioral modeling language was used for the implementation of reduced-order macro models, that present the advantage of a seamless interface with Simulink blocks, for creating hybrid information/energy flow system models. Test bench simulations of the library models compare favorably with both analytical results and with more in-depth finite element simulations performed in ANSYS. Separate MEMS-electronic integration tests were done on closed-loop MEMS accelerometers, where Simscape was used for modeling the MEMS device and Simulink for the electronic subsystem.

Keywords: across-through variables, electromechanical coupling, energy flow, information flow, Matlab/Simulink, MEMS, nonlinear, pull-in instability, reduced order macro models, Simscape

Procedia PDF Downloads 136

Authors: Shizra Waris, Saleem Akhtar

Abstract:

Big data is a research area receiving attention from academia and IT communities. In the digital world, the amounts of data produced and stored have within a short period of time. Consequently this fast increasing rate of data has created many challenges. In this paper, we use functionalism and structuralism paradigms to analyze the genesis of big data applications and its current trends. This paper presents a complete discussion on state-of-the-art big data technologies based on group and stream data processing. Moreover, strengths and weaknesses of these technologies are analyzed. This study also covers big data analytics techniques, processing methods, some reported case studies from different vendor, several open research challenges and the chances brought about by big data. The similarities and differences of these techniques and technologies based on important limitations are also investigated. Emerging technologies are suggested as a solution for big data problems.

Keywords: computer, it community, industry, big data

Procedia PDF Downloads 194

Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

Abstract:

This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

Procedia PDF Downloads 322

Authors: Sami Houry

Abstract:

Complex systems exhibit universal characteristics as they near a tipping point. Among them are common generic early warning signals which precede critical transitions. These signals include: critical slowing down in which the rate of recovery from perturbations decreases over time; an increase in the variance of the state variable; an increase in the skewness of the state variable; an increase in the autocorrelations of the state variable; flickering between different states; and an increase in spatial correlations over time. The presence of the signals has management implications, as the identification of the signals near the tipping point could allow management to identify intervention points. Despite the applications of the generic early warning signals in various scientific fields, such as fisheries, ecology and finance, a review of literature did not identify any applications that address the program student withdrawal problem at the undergraduate distance universities. This area could benefit from the application of generic early warning signals as the program withdrawal rate amongst distance students is higher than the program withdrawal rate at face-to-face conventional universities. This research specifically assessed the generic early warning signals through an intensive case study of undergraduate program student withdrawal at a Canadian distance university. The university is non-cohort based due to its system of continuous course enrollment where students can enroll in a course at the beginning of every month. The assessment of the signals was achieved through the comparison of the incidences of generic early warning signals among students who withdrew or simply became inactive in their undergraduate program of study, the true positives, to the incidences of the generic early warning signals among graduates, the false positives. This was achieved through significance testing. Research findings showed support for the signal pertaining to the rise in flickering which is represented in the increase in the student’s non-pass rates prior to withdrawing from a program; moderate support for the signals of critical slowing down as reflected in the increase in the time a student spends in a course; and moderate support for the signals on increase in autocorrelation and increase in variance in the grade variable. The findings did not support the signal on the increase in skewness of the grade variable. The research also proposes a new signal based on the fractal-like characteristic of student behavior. The research also sought to extend knowledge by investigating whether the emergence of a program withdrawal status is self-similar or fractal-like at multiple levels of observation, specifically the program level and the course level. In other words, whether the act of withdrawal at the program level is also present at the course level. The findings moderately supported self-similarity as a potential signal. Overall, the assessment of the signals suggests that the signals, with the exception with the increase of skewness, could be utilized as a predictive management tool and potentially add one more tool, the fractal-like characteristic of withdrawal, as an additional signal in addressing the student program withdrawal problem.

Keywords: critical transitions, fractals, generic early warning signals, program student withdrawal

Procedia PDF Downloads 185

Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

Abstract:

Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

Procedia PDF Downloads 107