Search results for: lane marking filter

Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

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Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

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Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: Scott R. Butler

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Ontario, Canada’s largest province, is in the midst of an interesting experiment in mandated asset management planning for local governments. At the beginning of 2021, Ontario’s 444 municipalities were responsible for the management of 302,864 lane kilometers of roads that have a replacement cost of $97.545 billion CDN. Roadways are by far the most complex, expensive, and extensive assets that a municipality is responsible for overseeing. Since adopting Ontario Regulation 588/47: Asset Management Planning for Municipal Infrastructure in 2017, the provincial government has established prescriptions for local road authorities regarding asset category and levels of service being provided. This provincial regulation further stipulates that asset data such as extent, condition, and life cycle costing are to be captured in manner compliant with qualitative descriptions and technical metrics. The Ontario Good Roads Association undertook an exercise to aggregate the road-related data contained within the 444 asset management plans that municipalities have filed with the provincial government. This analysis concluded that collectively Ontario municipal roadways have a $34.7 billion CDN in deferred maintenance. The ill-state of repair of Ontario municipal roads has lasting implications for province’s economic competitiveness and has garnered considerable political attention. Municipal efforts to address the maintenance backlog are stymied by the extremely limited fiscal parameters municipalities must operate within in Ontario. Further exacerbating the program are provincially designed programs that are ineffective, administratively burdensome, and not necessarily aligned with local priorities or strategies. This paper addresses how municipal asset management plans – and more specifically, the data contained in these plans – can be used to design innovative policy frameworks, flexible funding programs, and new levels of service that respond to these funding challenges, as well as emerging issues such as local economic development and climate change. To fully unlock the potential that Ontario Regulation 588/17 has imposed will require a resolute commitment to data standardization and horizontal collaboration between municipalities within regions.

Keywords: transportation, municipal asset management, subnational policy design, subnational funding program design

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Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

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In the current paper, an indoor positioning system is proposed with consideration of measurement delay. Firstly, an estimation filter with a measurement delay is designed for the indoor positioning mechanism under a weighted least square criterion, which utilizes only finite measurements on the most recent window. The proposed estimation filtering based scheme gives the filtered estimates for position, velocity and acceleration of moving target in real-time, while removing undesired noisy effects and preserving desired moving positions. Secondly, the proposed scheme is shown to have good inherent properties such as unbiasedness, efficiency, time-invariance, deadbeat, and robustness due to the finite memory structure. Finally, computer simulations shows that the performance of the proposed estimation filtering based scheme can outperform to the existing infinite memory filtering based mechanism.

Keywords: indoor positioning system, wireless sensor networks, measurement delay

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: Obaid Algahtani

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An interval may be defined as a convex combination as follows: I=[a,b]={x_α=(1-α)a+αb: α∈[0,1]}. Consequently, we may adopt interval operations by applying the scalar operation point-wise to the corresponding interval points: I ∙J={x_α∙y_α ∶ αϵ[0,1],x_α ϵI ,y_α ϵJ}, With the usual restriction 0∉J if ∙ = ÷. These operations are associative: I+( J+K)=(I+J)+ K, I*( J*K)=( I*J )* K. These two properties, which are missing in the usual interval operations, will enable the extension of the usual linear system concepts to the interval setting in a seamless manner. The arithmetic introduced here avoids such vague terms as ”interval extension”, ”inclusion function”, determinants which we encounter in the engineering literature that deal with interval linear systems. On the other hand, these definitions were motivated by our attempt to arrive at a definition of interval random variables and investigate the corresponding statistical properties. We feel that they are the natural ones to handle interval systems. We will enable the extension of many results from usual state space models to interval state space models. The interval state space model we will consider here is one of the form X_((t+1) )=AX_t+ W_t, Y_t=HX_t+ V_t, t≥0, where A∈ 〖IR〗^(k×k), H ∈ 〖IR〗^(p×k) are interval matrices and 〖W 〗_t ∈ 〖IR〗^k,V_t ∈〖IR〗^p are zero – mean Gaussian white-noise interval processes. This feeling is reassured by the numerical results we obtained in a simulation examples.

Keywords: interval analysis, interval matrices, state space model, Kalman Filter

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Authors: Osiris Terry, Kenneth Hopkinson, Laura Humphrey

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Systematic resampling is the most popularly used resampling method in particle filters. This paper seeks to further the understanding of systematic resampling by defining a formula made up of variables from the sampling equation and the particle weights. The formula is then verified via SPARK, a software verification language. The verified systematic resampling formula states that the minimum/maximum number of possible samples taken of a particle is equal to the floor/ceiling value of particle weight divided by the sampling interval, respectively. This allows for the creation of a randomness spectrum that each resampling method can fall within. Methods on the lower end, e.g., systematic resampling, have less randomness and, thus, are quicker to reach an estimate. Although lower randomness allows for error by having a larger bias towards the size of the weight, having this bias creates vulnerabilities to the noise in the environment, e.g., jamming. Conclusively, this is the first step in characterizing each resampling method. This will allow target-tracking engineers to pick the best resampling method for their environment instead of choosing the most popularly used one.

Keywords: SPARK, software verification, resampling, systematic resampling, particle filter, tracking

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Authors: Abhimanyu Kumar, Chirag Gupta

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This work presents a comprehensive study on the employment of Model Predictive Control (MPC) for a three-phase voltage-source inverter to regulate the output voltage efficiently. The inverter is modeled via the Clarke Transformation, considering a scenario where the load is unknown. An LC filter model is developed, demonstrating its efficacy in Total Harmonic Distortion (THD) reduction. The system, when implemented with fault-tolerant multilevel inverter topologies, ensures reliable operation even under fault conditions, a requirement that is paramount with the increasing dependence on renewable energy sources. The research also integrates a Fuzzy Logic based fault tolerance system which identifies and manages faults, ensuring consistent inverter performance. The efficacy of the proposed methodology is substantiated through rigorous simulations and comparative results, shedding light on the voltage prediction efficiency and the robustness of the model even under fault conditions.

Keywords: total harmonic distortion, fuzzy logic, renewable energy sources, MLI

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Authors: Olivier Mills, Bernard McDonell, Laura A. S. MacDonald

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The increasing availability and quality of internet access throughout the developing world provides an opportunity to utilize online spaces to disseminate water, sanitation and hygiene (WASH) knowledge to practitioners. Since 2001, CAWST has provided in-person education, training and consulting services to thousands of WASH practitioners all over the world, supporting them to start, troubleshoot, improve and expand their WASH projects. As CAWST continues to grow, the organization faces challenges in meeting demand from clients and in providing consistent, timely technical support. In 2012, CAWST began utilizing online spaces to expand its reach by developing a series of resources websites and webinars. CAWST has developed a WASH Education and Training resources website, a Biosand Filter (BSF) Knowledge Base, a Household Water Treatment and Safe Storage Knowledge Base, a mobile app for offline users, a live chat support tool, a WASH e-library, and a series of webinar-style online training sessions to complement its in-person capacity development services. In order to determine the preliminary outcomes of providing these online services, CAWST has monitored and analyzed registration to the online spaces, downloads of the educational materials, and webinar attendance; as well as conducted user surveys. The purpose of this analysis was to find out who was using the online spaces, where users came from, and how the resources were being used. CAWST’s WASH Resources website has served over 5,800 registered users from 3,000 organizations in 183 countries. Additionally, the BSF Knowledge Base has served over 1000 registered users from 68 countries, and over 540 people from 73 countries have attended CAWST’s online training sessions. This indicates that the online spaces are effectively reaching a large numbers of users, from a range of countries. A 2016 survey of the Biosand Filter Knowledge Base showed that approximately 61% of users are practitioners, and 39% are either researchers or students. Of the respondents, 46% reported using the BSF Knowledge Base to initiate a BSF project and 43% reported using the information to train BSF technicians. Finally, 61% indicated they would like even greater support from CAWST’s Technical Advisors going forward. The analysis has provided an encouraging indication that CAWST’s online spaces are contributing to its objective of engaging and supporting WASH practitioners to start, improve and expand their initiatives. CAWST has learned several lessons during the development of these online spaces, in particular related to the resources needed to create and maintain the spaces, and respond to the demand created. CAWST plans to continue expanding its online spaces, improving user experience of the sites, and involving new contributors and content types. Through the use of online spaces, CAWST has been able to increase its global reach and impact without significantly increasing its human resources by connecting WASH practitioners with the information they most need, in a practical and accessible manner. This paper presents on CAWST’s use of online spaces through the CAWST-developed platforms discussed above and the analysis of the use of these platforms.

Keywords: education and training, knowledge sharing, online resources, water and sanitation

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Authors: Imtiaz Sarwar

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Air conditioning in homes may account for one-third of the electricity during period in summer when most of the energy is required in large cities. It is not consuming only electricity but also has a serious impact on environment including greenhouse effect. Circular polarizer filter can be used to selectively absorb or pass clockwise or counter-clock wise circularly polarized light. My research is about putting two circular polarized glasses parallel to each other and make a circular window with it. When we will place two circular polarized glasses exactly same way (0 degree to each other) then nothing will be noticed rather it will work as a regular window through which all light and heat can pass on. While we will keep rotating one of the circular polarized glasses, the angle between the glasses will keep increasing and the window will keep blocking more and more lights. It will completely block all the lights and a portion of related heat when one of the windows will reach 90 degree to another. On the other hand, we can just open the window when fresh air is necessary. It will reduce the necessity of using Air condition too much or consumer will use electric fan rather than air conditioning system. Thus, we can save a significant amount of electricity and we can go green.

Keywords: circular polarizer, window, air condition, light, energy

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Authors: Janine Just, Kerstin Meints

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The research aims to compare vocabulary size and grammatical development between US American English- and British English-speaking children at age 2;0. As there is evidence that precocious children with large vocabularies develop grammar skills earlier than their typically developing peers, it was investigated if this also holds true across varieties of English. Thus, if US American children start to produce words earlier than their British counterparts, this could mean that US children are also at an advantage in the early developmental stages of acquiring grammar. This research employs a British English adaptation of the MacArthur-Bates CDI Words and Sentences (Lincoln Toddler CDI) to compare vocabulary and also grammar scores with the updated US Toddler CDI norms. At first, the Lincoln TCDI was assessed for its concurrent validity with the Preschool Language Scale (PLS-5 UK). This showed high correlations for the vocabulary and grammar subscales between the tests. In addition, the frequency of the Toddler CDI’s words was also compared using American and British English corpora of adult spoken and written language. A paired-samples t-test found a significant difference in word frequency between the British and the American CDI demonstrating that the TCDI’s words were indeed of higher frequency in British English. We then compared language and grammar scores between US (N = 135) and British children (N = 96). A two-way between groups ANOVA examined if the two samples differed in terms of SES (i.e. maternal education) by investigating the impact of SES and country on vocabulary and sentence complexity. The two samples did not differ in terms of maternal education as the interaction effects between SES and country were not significant. In most cases, scores were not significantly different between US and British children, for example, for overall word production and most grammatical subscales (i.e. use of words, over- regularizations, complex sentences, word combinations). However, in-depth analysis showed that US children were significantly better than British children at using some noun categories (i.e. people, objects, places) and several categories marking early grammatical development (i.e. pronouns, prepositions, quantifiers, helping words). However, the effect sizes were small. Significant differences for grammar were found for irregular word forms and progressive tense suffixes. US children were more advanced in their use of these grammatical categories, but the effect sizes were small. In sum, while differences exist in terms of vocabulary and grammar ability, favouring US children, effect sizes were small. It can be concluded that most British children are ‘catching up’ with their US American peers at age 2;0. Implications of this research will be discussed.

Keywords: first language acquisition, grammar, parent report instrument, vocabulary

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Authors: Abhijeet Kumar, Palaniswamy N. K.

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Heavy metal contamination in water sources endangers both the environment and human health. Various water filtration techniques have been employed till now for purification and removal of hazardous metals from water. Among all the existing methods, nanofibres have emerged as a viable alternative for effective heavy metal removal in recent years because of their unique qualities, such as large surface area, interconnected porous structure, and customizable surface chemistry. Among the numerous manufacturing techniques, solution blow spinning has gained popularity as a versatile process for producing nanofibers with customized properties. This paper seeks to offer a complete overview of the use of nanofibers for heavy metal filtration, particularly those produced using solution blow spinning. The review discusses current advances in nanofiber materials, production processes, and heavy metal removal performance. Furthermore, the field's difficulties and future opportunities are examined in order to direct future research and development activities.

Keywords: heavy metals, nanofiber composite, filter membranes, adsorption, impaction

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Fadwa Alaskar, Fang-Chieh Chou, Carlos Flores, Xiao-Yun Lu, Alexandre M. Bayen

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This article proposes a perception model for enhancing the accuracy and stability of car-following control of a longitudinally automated truck. We applied a fusion-based tracking algorithm on measurements of a single preceding vehicle needed for car-following control. This algorithm fuses two types of data, radar and LiDAR data, to obtain more accurate and robust longitudinal perception of the subject vehicle in various weather conditions. The filter’s resulting signals are fed to the gap control algorithm at every tracking loop composed by a high-level gap control and lower acceleration tracking system. Several highway tests have been performed with two trucks. The tests show accurate and fast tracking of the target, which impacts on the gap control loop positively. The experiments also show the fulfilment of control design requirements, such as fast speed variations tracking and robust time gap following.

Keywords: object tracking, perception, sensor fusion, adaptive cruise control, cooperative adaptive cruise control

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Authors: Takhchi Jamal, Ouisse Morvan, Sadoulet-Reboul Emeline, Bouhaddi Noureddine, Gagliardini Laurent, Bornet Frederic, Lakrad Faouzi

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Structural intensity is a technique that can be used to indicate both the magnitude and direction of power flow through a structure from the excitation source to the dissipation sink. However, current analysis is limited to the low frequency range. At medium and high frequencies, a rotational component appear in the field, masking the energy flow and make its understanding difficult or impossible. The objective of this work is to implement a methodology to filter out the rotational components of the structural intensity field in order to fully understand the energy flow in complex structures. The approach is based on the Helmholtz decomposition. It allows to decompose the structural intensity field into rotational, irrotational, and harmonic components. Only the irrotational component is needed to describe the net power flow from a source to a dissipative zone in the structure. The methodology has been applied on academic structures, and it allows a good analysis of the energy transfer paths.

Keywords: structural intensity, power flow, helmholt decomposition, irrotational intensity

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: Murray Matarab Konzang

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

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

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Authors: M. Hilani, B. Nassih

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Phishing is one of the oldest and best known scams on the Internet. It can be defined as any type of telecommunications fraud that uses social engineering tricks to obtain confidential data from its victims. It’s a cybercrime aimed at stealing your sensitive information. Phishing is generally done via private email, so scammers impersonate large companies or other trusted entities to encourage victims to voluntarily provide information such as login credentials or, worse yet, credit card numbers. The COVID-19 theme is used by cybercriminals in multiple malicious campaigns like phishing. In this environment, messaging filtering solutions have become essential to protect devices that will now be used outside of the secure perimeter. Despite constantly updating methods to avoid these cyberattacks, the end result is currently insufficient. Many researchers are looking for optimal solutions to filter phishing emails, but we still need good results. In this work, we concentrated on solving the problem of detecting phishing emails using the different steps of NLP preprocessing, and we proposed and trained a model using one-dimensional CNN. Our study results show that our model obtained an accuracy of 99.99%, which demonstrates how well our model is working.

Keywords: phishing, e-mail, NLP preprocessing, CNN, e-mail filtering

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Authors: S. M. Ahuja

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A Rice Sheller is used for obtaining polished white rice from paddy. There are about 3000 Rice Shellers in Punjab and 50000 in India. During the process of shelling lot of dust is emitted from different unit operations like paddy silo, paddy shaker, bucket elevators, huskers, paddy separator etc. These dust emissions have adverse effect on the health of the workers and the wear and tear of the shelling machinery is also fast. All the dust emissions spewing out of these unit operations of a rice Sheller were contained by providing suitable hoods and enclosures while ensuring their workability. These were sucked by providing an induced draft fan followed by a high efficiency cyclone separator that has got an overall dust collection efficiency of more than 90 %. This cyclone separator replaced two cyclone separators and a filter bag house, which the Rice Sheller was already having. The dust concentration in the stack after the installation of cyclone separator is well within the stipulated standards. Besides controlling pollution there is improvement in the quality of products like bran and the life of shelling machinery has also enhanced. The payback period of this technology is less than four shelling months.

Keywords: air pollution, cyclone separator, pneumatic conveying, rice shellers

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Authors: Paulina Zavistanaviciute, Vita Krungleviciute, Elena Bartkiene

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Lactic acid bacteria (LAB) are microbial supplements that increase the nutritional, therapeutic, and safety value of food and feed. Often LAB strains are incubated in an expensive commercially available de Man-Rogosa-Sharpe (MRS) medium; the cultures are centrifuged, and the cells are washing with sterile water. Potato juice and apple juice industry bio-products are industrial wastes which may constitute a source of digestible nutrients for microorganisms. Due to their low cost and good chemical composition, potato juice and apple juice production bio- products could have a potential application in LAB encapsulation. In this study, pure LAB (P. acidilactici and P. pentosaceus) were multiplied in a crushed potato juice and apple juice industry bio-products medium. Before using, bio-products were sterilized and filtered. No additives were added to mass, except apple juice industry bioproducts were diluted with sterile water (1/5; v/v). The tap of sterilised mass, and LAB cell suspension (5 mL), containing of 8.9 log10 colony-forming units (cfu) per mL of the P. acidilactici and P. pentosaceus was used to multiply the LAB for 72 h. The final colony number in the potato juice and apple juice bio- products substrate was on average 9.60 log10 cfu/g. In order to stabilize the LAB, several methods of dehydration have been tested: lyophilisation (MilrockKieffer Lane, Kingston, USA) and dehydration in spray drying system (SD-06, Keison, Great Britain). Into the spray drying system multiplied LAB in a crushed potato juice and apple juice bio-products medium was injected in peristaltic way (inlet temperature +60 °C, inlet air temperature +150° C, outgoing air temperature +80 °C, air flow 200 m3/h). After lyophilisation (-48 °C) and spray drying (+150 °C) the viable cell concentration in the fermented potato juice powder was 9.18 ± 0.09 log10 cfu/g and 9.04 ± 0.07 log10 cfu/g, respectively, and in apple mass powder 8.03 ± 0.04 log10 cfu/g and 7.03 ± 0.03 log10 cfu/g, respectively. Results indicated that during the storage (after 12 months) at room temperature (22 +/- 2 ºC) LAB count in dehydrated products was 5.18 log10 cfu/g and 7.00 log10 cfu/g (in spray dried and lyophilized potato juice powder, respectively), and 3.05 log10 cfu/g and 4.10 log10 cfu/g (in spray dried and lyophilized apple juice industry bio-products powder, respectively). According to obtained results, potato juice could be used as alternative substrate for P. acidilactici and P. pentosaceus cultivation, and by drying received powders can be used in food/feed industry as the LAB starters. Therefore, apple juice industry by- products before spray drying and lyophilisation should be modified (i. e. by using different starches) in order to improve its encapsulation.

Keywords: bio-products, encapsulation, lactic acid bacteria, sustainability

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Authors: Tibor Ajtai, Máté Pintér, Noémi Utry, Gergely Kiss-Albert, Andrea Palágyi, László Manczinger, Csaba Vágvölgyi, Gábor Szabó, Zoltán Bozóki

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According to the best knowledge of the authors, here we experimentally demonstrate first, a quantified correlation between the real-time measured optical feature of the ambient and the off-line measured toxicity data. Finally, using these correlations we are presenting a novel methodology for real time characterisation of ambient toxicity based on the multi wavelength aerosol phase photoacoustic measurement. Ambient carbonaceous particulate matter is one of the most intensively studied atmospheric constituent in climate science nowadays. Beyond their climatic impact, atmospheric soot also plays an important role as an air pollutant that harms human health. Moreover, according to the latest scientific assessments ambient soot is the second most important anthropogenic emission source, while in health aspect its being one of the most harmful atmospheric constituents as well. Despite of its importance, generally accepted standard methodology for the quantitative determination of ambient toxicology is not available yet. Dominantly, ambient toxicology measurement is based on the posterior analysis of filter accumulated aerosol with limited time resolution. Most of the toxicological studies are based on operational definitions using different measurement protocols therefore the comprehensive analysis of the existing data set is really limited in many cases. The situation is further complicated by the fact that even during its relatively short residence time the physicochemical features of the aerosol can be masked significantly by the actual ambient factors. Therefore, decreasing the time resolution of the existing methodology and developing real-time methodology for air quality monitoring are really actual issues in the air pollution research. During the last decades many experimental studies have verified that there is a relation between the chemical composition and the absorption feature quantified by Absorption Angström Exponent (AAE) of the carbonaceous particulate matter. Although the scientific community are in the common platform that the PhotoAcoustic Spectroscopy (PAS) is the only methodology that can measure the light absorption by aerosol with accurate and reliable way so far, the multi-wavelength PAS which are able to selectively characterise the wavelength dependency of absorption has become only available in the last decade. In this study, the first results of the intensive measurement campaign focusing the physicochemical and toxicological characterisation of ambient particulate matter are presented. Here we demonstrate the complete microphysical characterisation of winter time urban ambient including optical absorption and scattering as well as size distribution using our recently developed state of the art multi-wavelength photoacoustic instrument (4λ-PAS), integrating nephelometer (Aurora 3000) as well as single mobility particle sizer and optical particle counter (SMPS+C). Beyond this on-line characterisation of the ambient, we also demonstrate the results of the eco-, cyto- and genotoxicity measurements of ambient aerosol based on the posterior analysis of filter accumulated aerosol with 6h time resolution. We demonstrate a diurnal variation of toxicities and AAE data deduced directly from the multi-wavelength absorption measurement results.

Keywords: photoacoustic spectroscopy, absorption Angström exponent, toxicity, Ames-test

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Authors: Chun-Yu Chen, Kua-Rong Wu, Yu-Cheng Chen, Perng-Jy Tsai

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Cooking fumes are known containing polycyclic aromatic hydrocarbons (PAHs) and aldehydes, and some of them have been proven carcinogenic or possibly carcinogenic to humans. Considering their chronic health effects, long-term exposure data is required for assessing cooking workers’ lifetime health risks. Previous exposure assessment studies, due to both time and cost constraints, mostly were based on the cross-sectional data. Therefore, establishing a long-term exposure data has become an important issue for conducting health risk assessment for cooking workers. An approach was proposed in this study. Here, the generation rates of both PAHs and aldehydes from a cooking process were determined by placing a sampling train exactly under the under the exhaust fan under the both the total enclosure condition and normal operating condition, respectively. Subtracting the concentration collected by the former (representing the total emitted concentration) from that of the latter (representing the hood collected concentration), the fugitive emitted concentration was determined. The above data was further converted to determine the generation rates based on the flow rates specified for the exhaust fan. The determinations of the above generation rates were conducted in a testing chamber with a selected cooking process (deep-frying chicken nuggets under 3 L peanut oil at 200°C). The sampling train installed under the exhaust fan consisted respectively an IOM inhalable sampler with a glass fiber filter for collecting particle-phase PAHs, followed by a XAD-2 tube for gas-phase PAHs. The above was also used to sample aldehydes, however, installed with a filter pre-coated with DNPH, and followed by a 2,4-DNPH-cartridge for collecting particle-phase and gas-phase aldehydes, respectively. PAHs and aldehydes samples were analyzed by GC/MS-MS (Agilent 7890B), and HPLC-UV (HITACHI L-7100), respectively. The obtained generation rates of both PAHs and aldehydes were applied to the near-field/ far-field exposure model to estimate the exposures of cooks (the estimated near-field concentration), and helpers (the estimated far-field concentration). For validating purposes, both PAHs and aldehydes samplings were conducted simultaneously using the same sampling train at both near-field and far-field sites of the testing chamber. The sampling results, together with the use of the mixed-effect model, were used to calibrate the estimated near-field/ far-field exposures. In the present study, the obtained emission rates were further converted to emission factor of both PAHs and aldehydes according to the amount of food oil consumed. Applying the long-term food oil consumption records, the emission rates for both PAHs and aldehydes were determined, and the long-term exposure databanks for cooks (the estimated near-field concentration), and helpers (the estimated far-field concentration) were then determined. Results show that the proposed approach was adequate to determine the generation rates of both PAHs and aldehydes under various fan exhaust flow rate conditions. The estimated near-field/ far-field exposures, though were significantly different from that obtained from the field, can be calibrated using the mixed effect model. Finally, the established long-term data bank could provide a useful basis for conducting long-term exposure assessments for cooking workers exposed to PAHs and aldehydes.

Keywords: aldehydes, cooking oil fumes, long-term exposure assessment, modeling, polycyclic aromatic hydrocarbons (PAHs)

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Authors: Wildan Maulana Wildan, Siti Annisa Rahmayani Icha

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Nowadays advances in information technology are needed by all the inhabitants of the earth for the sake of ease all their work, but it is worth to introduced the technological advances in the world of children. Before the technology is growing rapidly, children busy with various of traditional games and have high socialization. Moreover, after it presence, almost all of children spend more their time for playing gadget, It can affect the education of children and will change the character and personality children. However, children also can not be separated with the technology. Because the technology insight knowledge of children will be more extensive. Because the world can not be separated with advances in technology as well as with children, there should be developed a smartphone operating system that is child-friendly. The operating system is able to filter contents that do not deserve children, even in this system there is a reminder of a time study, prayer time and play time for children and there are interactive contents that will help the development of education and children's character. Children need technology, and there are some ways to introduce it to children. We must look at the characteristics of children in different environments. Thus advances in technology can be beneficial to the world children and their parents, and educators do not have to worry about advances in technology. We should be able to take advantage of advances in technology best possible.

Keywords: information technology, smartphone operating system, education, character

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Authors: Krishnamoorthy Shanmugaraj, Malaichamy Ilanchelian

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Ascorbic acid is an essential component in the diet of humans, and also is a typical long used pharmaceutical agent. In the present contribution, we have carried out a detailed study on the binding interaction of ascorbic acid (AA) with bovine hemoglobin (BHb) using steady state emission, time resolved fluorescence, UV-Vis absorption, circular dichroism (CD), Fourier transform infra-red (FT-IR) and three dimensional emission (3D) spectral studies. The results from the emission spectral studies unveiled that the quenching of BHb emission by AA is attributed to the formation of a complex in the ground state (static in nature) after correcting for inner filter effect. The binding parameters calculated from corrected emission quenching data revealed that BHb exhibited a significant binding affinity towards AA. Moreover, AA induced tertiary and secondary conformational changes of BHb were monitored by UV-Vis absorption, CD, FT-IR and 3D emission spectral studies. The results presented here will help to further understand the credible mechanism of BHb-AA system which is expected to provide insights into conformational and microenvironmental changes of BHb.

Keywords: ascorbic acid, bovine hemoglobin, circular dichroism, three dimensional emission spectral studies

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Authors: Akshat Kumar, Vidushi

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This paper identifies 27 KOIs, 26 of which are currently classified as candidates and one as false positives that have a high probability of being confirmed. For this purpose, 11 machine learning algorithms were implemented on the cumulative kepler dataset sourced from the NASA exoplanet archive; it was observed that the best-performing model was HistGradientBoosting and XGBoost with a test accuracy of 93.5%, and the lowest-performing model was Gaussian NB with a test accuracy of 54%, to test model performance F1, cross-validation score and RUC curve was calculated. Based on the learned models, the significant characteristics for confirm exoplanets were identified, putting emphasis on the object’s transit and stellar properties; these characteristics were namely koi_count, koi_prad, koi_period, koi_dor, koi_ror, and koi_smass, which were later considered to filter out the potential KOIs. The paper also calculates the Earth similarity index based on the planetary radius and equilibrium temperature for each KOI identified to aid in their classification.

Keywords: Kepler objects of interest, exoplanets, space exploration, machine learning, earth similarity index, transit photometry

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Authors: Hayat Omar

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Languages provide speakers with a wide range of linguistic units to organize and deliver information. There are several ways to verbally express the mental representations of events. According to the linguistic tools they have acquired, speakers select the one that brings out the most communicative effect to convey their message. Our study focuses on two markers, -mm and dämmo, in Amharic (Ethiopian Semitic language). Our aim is to examine, from a developmental perspective, how they are used by speakers. We seek to distinguish the communicative and pragmatic functions indicated by means of these markers. To do so, we created a corpus of sixty narrative productions of children from 5-6, 7-8 to 10-12 years old and adult Amharic speakers. The experimental material we used to collect our data is a series of pictures without text 'Frog, Where are you?'. Although -mm and dämmo are each used in specific contexts, they are sometimes analyzed as being interchangeable. The suffix -mm is complex and multifunctional. It marks the end of the negative verbal structure, it is found in the relative structure of the imperfect, it creates new words such as adverbials or pronouns, it also serves to coordinate words, sentences and to mark the link between macro-propositions within a larger textual unit. -mm was analyzed as marker of insistence, topic shift marker, element of concatenation, contrastive focus marker, 'bisyndetic' coordinator. On the other hand, dämmo has limited function and did not attract the attention of many authors. The only approach we could find analyzes it in terms of 'monosyndetic' coordinator. The paralleling of these two elements made it possible to understand their distinctive functions and refine their description. When it comes to marking a referent, the choice of -mm or dämmo is not neutral, depending on whether the tagged argument is newly introduced, maintained, promoted or reintroduced. The presence of these morphemes explains the inter-phrastic link. The information is seized by anaphora or presupposition: -mm goes upstream while dämmo arrows downstream, the latter requires new information. The speaker uses -mm or dämmo according to what he assumes to be known to his interlocutors. The results show that -mm and dämmo, although all the speakers use them both, do not always have the same scope according to the speaker and vary according to the age. dämmo is mainly used to mark a contrastive topic to signal the concomitance of events. It is more commonly used in young children’s narratives (F(3,56) = 3,82, p < .01). Some values of -mm (additive) are acquired very early while others are rather late and increase with age (F(3,56) = 3,2, p < .03). The difficulty is due not only because of its synthetic structure but primarily because it is multi-purpose and requires a memory work. It highlights the constituent on which it operates to clarify how the message should be interpreted.

Keywords: acquisition, cohesion, connection, contrastive topic, contrastive focus, discourse marker, pragmatics

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Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

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High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

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Authors: Mobarok Hossain Bhuyain

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Video surveillance processing has attracted various security fields transforming it into one of the leading research fields. Today's demand for detection and tracking of human mobility for security is very useful for human security, such as in crowded areas. Accordingly, video surveillance technology has seen a rapid advancement in recent years, with algorithms analyzing the behavior of people under surveillance automatically. The main motivation of this research focuses on the detection and tracking of the elderly and socially vulnerable people in crowded areas. Degenerate people are a major health concern, especially for elderly people and socially vulnerable people. One major disadvantage of video surveillance is the need for continuous monitoring, especially in crowded areas. To assist the security monitoring live surveillance video, image processing, and artificial intelligence methods can be used to automatically send warning signals to the monitoring officers about elderly people and socially vulnerable people.

Keywords: human detection, target tracking, neural network, particle filter

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Authors: Sourabh Jain, S. S. Jain

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Intelligent transportation system (ITS) is the application of technologies for developing a user–friendly transportation system to extend the safety and efficiency of urban transportation systems in developing countries. These systems involve vehicles, drivers, passengers, road operators, managers of transport services; all interacting with each other and the surroundings to boost the security and capacity of road systems. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. Intelligent transportation system is a product of the revolution in information and communications technologies that is the hallmark of the digital age. The basic ITS technology is oriented on three main directions: communications, information, integration. Information acquisition (collection), processing, integration, and sorting are the basic activities of ITS. In the paper, attempts have been made to present the endeavor that was made to interpret and evaluate the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of six lanes as well as eight lanes divided road network. Two categories of data have been collected such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, stop watch, radar gun, and mobile GPS (GPS tracker lite). From the analysis, the performance interpretations incorporated were the identification of peak and off-peak hours, congestion and level of service (LOS) at midblock sections and delay followed by plotting the speed contours. The paper proposed the urban corridor management strategies based on sensors integrated into both vehicles and on the roads that those have to be efficiently executable, cost-effective, and familiar to road users. It will be useful to reduce congestion, fuel consumption, and pollution so as to provide comfort, safety, and efficiency to the users.

Keywords: ITS strategies, congestion, planning, mobility, safety

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Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

Abstract:

Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

Procedia PDF Downloads 316