Search results for: encrypted traffic classification

Authors: Ramin Mirzada

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This research investigates the valuation of public transport importance in decreasing congestion and in introduction of bus rapid transit in Kabul city. The main concern and main problem of the Kabul city public transport is traffic congestion. When buses and trams are stuck in traffic jams, it is clear that they fall behind from the schedule and this cause lots of problem for Kabul residence. In this research, the main attention has been given to improve current public transport in Kabul city which Public transport has large share almost 50% share among all mode. The main purpose of this research is to improve public transport system, to examine the demand and the supply of public transport in Kabul city, and to improve public transport system by introducing Bus rapid transit (BRT) system in Kabul city. The data which is used in this research is gathered by Transport Ministry, Kabul Municipality and Japan Cooperation Agency in Afghanistan (JICA). Urban transportation modeling system (UTMS) which is also known as traditional four-step modeling is used as the methodology of this research. The outcome of this research shows that by improving public transport which is local bus system mostly congestion problem of Kabul city become solve, and for those lanes which has the high demand and has more congestion, it is needed to introduce bus rapid transit system.

Keywords: transportation, planning, public transport, bus rapid transit, Kabul, Afghanistan

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Authors: Veronique Troch, Wouter Van der Borght, Véronique De Bleeker, Bram Marynissen, Nathan Van der Eecken, Gijs Du Laing

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Among the challenges associated with increased urban food production are health risks from food contamination, due to the higher pollution loads in urban areas, compared to rural sites. Therefore, the risks posed by industrial or traffic pollution of locally grown food, was defined as one of five high-priority issues of urban agriculture requiring further investigation. The impact of air pollution on urban horticulture is the subject of this study. More particular, this study focuses on the atmospheric deposition of trace metals on leaf vegetables cultivated in the city of Ghent, Belgium. Ghent is a particularly interesting study site as it actively promotes urban agriculture. Plants accumulate heavy metals by absorption from contaminated soils and through deposition on parts exposed to polluted air. Accumulation of trace metals in vegetation grown near roads has been shown to be significantly higher than those grown in rural areas due to traffic-related contaminants in the air. Studies of vegetables demonstrated, that the uptake and accumulation of trace metals differed among crop type, species, and among plant parts. Studies on vegetables and fruit trees in Berlin, Germany, revealed significant differences in trace metal concentrations depending on local traffic, crop species, planting style and parameters related to barriers between sampling site and neighboring roads. This study aims to supplement this scarce research on heavy metal accumulation in urban horticulture. Samples from leaf vegetables were collected from different sites, including allotment gardens, in Ghent. Trace metal contents on these leaf vegetables were analyzed by ICP-MS (inductively coupled plasma mass spectrometry). In addition, precipitation on each sampling site was collected by NILU-type bulk collectors and similarly analyzed for trace metals. On one sampling site, different parameters which might influence trace metal content in leaf vegetables were analyzed in detail. These parameters are distance of planting site to the nearest road, barriers between planting site and nearest road, and type of leaf vegetable. For comparison, a rural site, located farther from city traffic and industrial pollution, was included in this study. Preliminary results show that there is a high correlation between trace metal content in the atmospheric deposition and trace metal content in leaf vegetables. Moreover, a significant higher Pb, Cu and Fe concentration was found on spinach collected from Ghent, compared to spinach collected from a rural site. The distance of planting site to the nearest road significantly affected the accumulation of Pb, Cu, Mo and Fe on spinach. Concentrations of those elements on spinach increased with decreasing distance between planting site and the nearest road. Preliminary results did not show a significant effect of barriers between planting site and the nearest road on accumulation of trace metals on leaf vegetables. The overall goal of this study is to complete and refine existing guidelines for urban gardening to exclude potential health risks from food contamination. Accordingly, this information can help city governments and civil society in the professionalization and sustainable development of urban agriculture.

Keywords: atmospheric deposition, leaf vegetables, trace metals, traffic pollution, urban agriculture

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Authors: Donghun Jeong, Somyoung Shin, Yeoil Yun

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A large-scale traffic accident refers to an accident in which more than three people die or more than thirty people are dead or injured. In order to prevent a large-scale traffic accident from causing a big loss of lives or establish effective improvement measures, it is important to analyze accident situations in-depth and understand the effects of major accident variables on an accident. This study aims to analyze the contribution of individual accident variables to accident results, based on the accurate reconstruction of traffic accidents using PC-Crash’s Multi-Body, which is an accident reconstruction program, and simulation of each scenario. Multi-Body system of PC-Crash accident reconstruction program is used for multi-body accident reconstruction that shows motions in diverse directions that were not approached previously. MB System is to design and reproduce a form of body, which shows realistic motions, using several bodies. Targeting the 'freight truck cargo drop accident around the Changwon Tunnel' that happened in November 2017, this study conducted a simulation of the freight truck cargo drop accident and analyzed the contribution of individual accident majors. Then on the basis of the driving speed, cargo load, and stacking method, six scenarios were devised. The simulation analysis result displayed that the freight car was driven at a speed of 118km/h(speed limit: 70km/h) right before the accident, carried 196 oil containers with a weight of 7,880kg (maximum load: 4,600kg) and was not fully equipped with anchoring equipment that could prevent a drop of cargo. The vehicle speed, cargo load, and cargo anchoring equipment were major accident variables, and the accident contribution analysis results of individual variables are as follows. When the freight car only obeyed the speed limit, the scattering distance of oil containers decreased by 15%, and the number of dropped oil containers decreased by 39%. When the freight car only obeyed the cargo load, the scattering distance of oil containers decreased by 5%, and the number of dropped oil containers decreased by 34%. When the freight car obeyed both the speed limit and cargo load, the scattering distance of oil containers fell by 38%, and the number of dropped oil containers fell by 64%. The analysis result of each scenario revealed that the overspeed and excessive cargo load of the freight car contributed to the dispersion of accident damage; in the case of a truck, which did not allow a fall of cargo, there was a different type of accident when driven too fast and carrying excessive cargo load, and when the freight car obeyed the speed limit and cargo load, there was the lowest possibility of causing an accident.

Keywords: accident reconstruction, large-scale traffic accident, PC-Crash, MB system

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Authors: Jie Zheng, Ruifeng Luo

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The United States is the world’s most developed economy with the strongest military power. China is the fastest growing country with growing comprehensive strength and its economic strength is second only to the US. However, the conflict between them is getting serious in recent years. President’s address is the representative of a nation’s ideology. The paper has built up a small sized corpus of President Xi Jinping and Trump’s speech in Davos to investigate their respective use and types of metaphors and calculate the respective percentage of each type of metaphor. The result shows President Xi Jinping employs more metaphors than Trump. The metaphors of Xi includes “building” metaphor, “plant” metaphor, “journey” metaphor, “ship” metaphor, “traffic” metaphor, “nation is a person” metaphor, “show” metaphor, etc while Trump’s comprises “war” metaphor, “building” metaphor, “journey” metaphor, “traffic” metaphor, “tax” metaphor, “book” metaphor, etc. After investigating metaphor use differences, the paper makes an analysis of the underlying ideology between the two nations. China is willing to strengthen ties with all the countries all over the world and has built a platform of development for them and itself to go to the destination of social well being while the US pays much concern to itself, emphasizing its first leading position and is also willing to help its alliances to development. The paper’s comparison of the ideology difference between the two countries will help them get a better understanding and reduce the conflict to some extent.

Keywords: metaphor; corpus; ideology; conflict

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Authors: Soha A. Bahanshal, Byung G. Kim

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Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: Kimuel Suyat, Francis Aldrine Uy, John Paul Carreon

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The Philippines, composed of many islands, is connected with approximately 8030 bridges. Continuous evaluation of the structural condition of these bridges is needed to safeguard the safety of the general public. With most bridges reaching its design life, retrofitting and replacement may be needed. Concerned government agencies allocate huge costs for periodic monitoring and maintenance of these structures. The rising volume of traffic and aging of these infrastructures is challenging structural engineers to give rise for structural health monitoring techniques. Numerous techniques are already proposed and some are now being employed in other countries. Vibration Analysis is one way. The natural frequency and vibration of a bridge are design criteria in ensuring the stability, safety and economy of the structure. Its natural frequency must not be so high so as not to cause discomfort and not so low that the structure is so stiff causing it to be both costly and heavy. It is well known that the stiffer the member is, the more load it attracts. The frequency must not also match the vibration caused by the traffic loads. If this happens, a resonance occurs. Vibration that matches a systems frequency will generate excitation and when this exceeds the member’s limit, a structural failure will happen. This study presents a method for calculating dynamic fragility through the use of vibration-based monitoring system. Dynamic fragility is the probability that a structural system exceeds a limit state when subjected to dynamic loads. The bridge is modeled in SAP2000 based from the available construction drawings provided by the Department of Public Works and Highways. It was verified and adjusted based from the actual condition of the bridge. The bridge design specifications are also checked using nondestructive tests. The approach used in this method properly accounts the uncertainty of observed values and code-based structural assumptions. The vibration response of the structure due to actual loads is monitored using installed sensors on the bridge. From the determinacy of these dynamic characteristic of a system, threshold criteria can be established and fragility curves can be estimated. This study conducted in relation with the research project between Department of Science and Technology, Mapúa Institute of Technology, and the Department of Public Works and Highways also known as Mapúa-DOST Smart Bridge Project deploys Structural Health Monitoring Sensors at Zamora Bridge. The bridge is selected in coordination with the Department of Public Works and Highways. The structural plans for the bridge are also readily available.

Keywords: structural health monitoring, dynamic characteristic, threshold criteria, traffic loads

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Amar Partap Singh Pharwaha, Balkrishan Jindal

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In this paper, a new method is developed for hiding image in a digital image with multilayer security. In the proposed method, the secret image is encrypted in the first instance using a flexible matrix based symmetric key to add first layer of security. Then another layer of security is added to the secret data by encrypting the ciphered data using Pythagorean Theorem method. The ciphered data bits (4 bits) produced after double encryption are then embedded within digital image in the spatial domain using Least Significant Bits (LSBs) substitution. To improve the image quality of the stego-image, an improved form of pixel adjustment process is proposed. To evaluate the effectiveness of the proposed method, image quality metrics including Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), entropy, correlation, mean value and Universal Image Quality Index (UIQI) are measured. It has been found experimentally that the proposed method provides higher security as well as robustness. In fact, the results of this study are quite promising.

Keywords: Pythagorean theorem, pixel adjustment, ciphered data, image hiding, least significant bit, flexible matrix

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Authors: Bangun F., Crevits B., Bellet T., Banet A., Boy G. A., Katili I.

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This paper seeks the incoherencies in cognitive process during an accident of Powered Two Wheelers (PTW) by understanding the factual sequences of events and causal relations for each case of accident. The principle of this approach is undertaking in-depth investigations on case per case of PTW accidents based on elaborate data acquisitions on accident sites that officially stamped in Police Crash Report (PCRs) 2012 of Medan with criteria, involved at least one PTW and resulted in serious injury and fatalities. The analysis takes into account four modules: accident chronologies, perpetrator, and victims, injury surveillance, vehicles and road infrastructures, comprising of traffic facilities, road geometry, road alignments and weather. The proposal for improvement could have provided a favorable influence on the chain of functional processes and events leading to collision. Decision Aiding Processes (DAP) assists in structuring different entities at different decisional levels, as each of these entities has its own objectives and constraints. The entities (A) are classified into 6 groups of accidents: solo PTW accidents; PTW vs. PTW; PTW vs. pedestrian; PTW vs. motor-trishaw; and PTW vs. other vehicles and consecutive crashes. The entities are also distinguished into 4 decisional levels: level of road users and street systems; operational level (crash-attended police officers or CAPO and road engineers), tactical level (Regional Traffic Police, Department of Transportation, and Department of Public Work), and strategic level (Traffic Police Headquarters (TCPHI)), parliament, Ministry of Transportation and Ministry of Public Work). These classifications will lead to conceptualization of Problem Situations (P) and Problem Formulations (I) in DAP context. The DAP concerns the sequences process of the incidents until the time the accident occurs, which can be modelled in terms of five activities of procedural rationality: identification on initial human features (IHF), investigation on proponents attributes (PrAT), on Injury Surveillance (IS), on the interaction between IHF and PrAt and IS (intercorrelation), then unravel the sequences of incidents; filtering and disclosure, which include: what needs to activate, modify or change or remove, what is new and what is priority. These can relate to the activation or modification or new establishment of law. The PrAt encompasses the problems of environmental, road infrastructure, road and traffic facilities, and road geometry. The evaluation model (MP) is generated to bridge P and I since MP is produced by the intercorrelations among IHF, PrAT and IS extracted from the PCRs 2012 of Medan. There are 7 findings of incoherences: lack of knowledge and awareness on the traffic regulations and the risks of accidents, especially when riding between 0 < x < 10 km from house, riding between 22 p.m.–05.30 a.m.; lack of engagements on procurement of IHF Data by CAPO; lack of competency of CAPO on data procurement in accident-sites; no intercorrelation among IHF and PrAt and IS in the database systems of PCRs; lack of maintenance and supervision on the availabilities and the capacities of traffic facilities and road infrastructure; instrumental bias with wash-back impacts towards the TCPHI; technical robustness with wash-back impacts towards the CAPO and TCPHI.

Keywords: decision aiding processes, evaluation model, PTW accidents, police crash reports

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Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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Authors: Kabuga Daniel

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Road accidents resulting to deaths and injuries have become a new public health challenge especially in developing countries including Tanzania. Reports from Tanzania Traffic Police Force shows that last year 2016 accidents increased compare to previous year 2015, accident happened from 3710 up to 5219, accidents and safety data indicate that children are the most vulnerable to road crashes where 78 pupils died and 182 others were seriously injured in separate roads accident last year. A survey done by Amend indicates that Pupil mode of transport in Dar es salaam schools are by walk 87%, bus 9.21%, car 1.32%, motorcycle 0.88%, 3-wheeler 0.24%, train 0.14%, bicycle 0.10%, ferry 0.07%, and combined mode 0.44%. According to this study, majority of school children’s uses walking mode, most of school children’s agreed to continue using walking mode and request to have signs for traffic control during crossing road like STOP sign and CHILD CROSSING sign for safe crossing. Because children not only sit inside this buses (Daladala) but also they walk in a group to/from school, and few (33.2%) parents or adults are willing to supervise their children’s during working to school while 50% of parents agree to let their children walking alone to school if the public transport started from nearby street. The study used both qualitative and quantitative methods of research by conducting physical surveying on sample districts. The main objectives of this research are to carries out all factors affecting school children’s when they use public road, to promote and encourage the safe use of public road by all classes especially pupil or student through the circulation of advice, information and knowledge gain from research and to recommends future direction for the developments for road design or plan to vulnerable users. The research also critically analyze the problems causing death and injuries to school children’s in Dar es Salaam Region. This study determines the relationship between road traffic accidents and factors, such as socio-economic, status, and distance from school, number of sibling, behavioral problems, knowledge and attitudes of public and their parents towards road safety and parent educational study traffic. The study comes up with some of recommendations including Infrastructure Improvements like, safe footpaths, Safe crossings, Speed humps, Speed limits, Road signs. However, Planners and policymakers wishing to increase walking and cycling among children need to consider options that address distance constraints, the land use planners and transport professionals use better understanding of the various factors that affect children’s choices of school travel mode, results suggest that all school travel attributes should be considered during school location.

Keywords: accidents, childrens, school, Tanzania

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Authors: Pratham Baheti, Rohan Sanghi, Aditya Gupta

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In the largely populated city of New Delhi, India, there are a lot of people that travel by two-wheelers. Majority of the people wear helmets while traveling and know how important it is to wear helmets for their safety. Still, the number of deaths because of road accidents involving two-wheelers is significant. We had conducted a survey by traveling within and in the outskirts of Delhi so as to see the variation in data and in the opinion of people towards helmet being a safety device rather than to escape the traffic police. We conducted a survey at traffic junctions and crossings of all the stakeholders and collected feedback on the Helmet scenario in India. According to the survey, the possible reason for these deaths is that the people, being unaware of helmet safety standards (ISI standards for helmets), buy helmets with fake ISI mark from unauthorized helmet sellers for a cheap price. Also, for the people who do not wear a helmet at all or wear a helmet just because it is a law, the reasons that they do not want to wear a helmet is heavyweight, lack of ventilation, inconvenience due to a strap, and hair problems. To address all these problems, we are designing a helmet with reduced weight and also working on the Helmet’s retention system and ventilation. We plan to provide this product at a cheap cost whilst maintaining the ISI standards so that a larger section of the population would be able to afford the helmet.

Keywords: safety, survey, ISI marks, stakeholders, helmet

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Authors: Sungho Kim, Jaechoul Shin, Yujin Baek, Nakseok Kim, Kyungnam Kim, Shinhaeng Jo

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The climate change and increase in heavy traffic have been accelerating damages that cause the problems such as pothole on asphalt pavement. Pothole causes traffic accidents, vehicle damages, road casualties and traffic congestion. A quick and efficient maintenance method is needed because pothole is caused by stripping and accelerates pavement distress. In this study, we propose a rapid and systematic pothole management by developing a pothole automated repairing equipment including a volume measurement system of pothole. Three kinds of cold mix asphalt mixture were investigated to select repair materials. The materials were evaluated for satisfaction with quality standard and applicability to automated equipment. The volume measurement system of potholes was composed of multi-sensor that are combined with laser sensor and ultrasonic sensor and installed in front and side of the automated repair equipment. An algorithm was proposed to calculate the amount of repair material according to the measured pothole volume, and the system for releasing the correct amount of material was developed. Field test results showed that the loss of repair material amount could be reduced from approximately 20% to 6% per one point of pothole. Pothole rapid automated repair equipment will contribute to improvement on quality and efficient and economical maintenance by not only reducing materials and resources but also calculating appropriate materials. Through field application, it is possible to improve the accuracy of pothole volume measurement, to correct the calculation of material amount, and to manage the pothole data of roads, thereby enabling more efficient pavement maintenance management. Acknowledgment: The author would like to thank the MOLIT(Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: automated equipment, management, multi-beam sensor, pothole

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Authors: Amit Kumar Jain, Surbhi Jain

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The urban freight in a city constitutes 10 to 18 per cent of all city road traffic, and 40 per cent of air pollution and noise emissions, are directly related to commercial transport. The policy measures implemented by urban planners have sought to restrict rather than assist goods-vehicle operations. This approach has temporarily controlled the urban transport demand during peak hours of traffic but has not effectively solved transport congestion. The solution discussed in the paper envisages the development of a comprehensive network of Urban Freight Stations (UFS) connected through underground conveyor belts in the city in line with baggage segregation and distribution in any of the major airports. The transportation of freight shall be done in standard size containers/cars through rail borne carts. The freight can be despatched or received from any of the UFS. Once freight is booked for a destination from any of the UFS, it would be stuffed in the container and digitally tagged for the destination. The container would reach the destination UFS through a network of rail borne carts. The container would be de-stuffed at the destination UFS and sent for further delivery, or the consignee may be asked to collect the consignment from urban freight station. The obvious benefits would be decongestion of roads, reduction in air and noise pollution, saving in manpower used for freight transportation.

Keywords: congestion, urban freight, intelligent transport system, pollution

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Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: Tatiana Tunon, Gottfried Pestal

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Government agencies responsible for the management of fisheries resources publish many types of grey literature, and these materials are increasingly accessible to the public on agency websites. However, scope and quality vary considerably, and end-users need meta-data about the report series when deciding whether to use the information (e.g. apply the methods, include the results in a systematic review), or when prioritizing materials for archiving (e.g. library holdings, reference databases). A proposed taxonomy for these report series was developed based on a review of 41 report series from 6 government agencies in 4 countries (Canada, New Zealand, Scotland, and United States). Each report series was categorized according to multiple criteria describing peer-review process, content, and purpose. A robust classification tree was then fitted to these descriptions, and the resulting taxonomic groups were used to compare agency output from 4 countries using reports available in their online repositories.

Keywords: classification tree, fisheries, government, grey literature

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Authors: Ping Tan, Xiaomeng Su, Yi Shen

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The motion intention in the motor imagery braincomputer interface is identified by classifying the event-related desynchronization (ERD) and event-related synchronization ERS characteristics of sensorimotor rhythm (SMR) in EEG signals. When the subject imagines different limbs or different parts moving, the rhythm components and bandwidth will change, which varies from person to person. How to find the effective sensorimotor frequency band of subjects is directly related to the classification accuracy of brain-computer interface. To solve this problem, this paper proposes a Minimum Distance to Riemannian Mean Classification method based on Non-Uniform Filter Banks. During the training phase, the EEG signals are decomposed into multiple different bandwidt signals by using multiple band-pass filters firstly; Then the spatial covariance characteristics of each frequency band signal are computered to be as the feature vectors. these feature vectors will be classified by the MDRM (Minimum Distance to Riemannian Mean) method, and cross validation is employed to obtain the effective sensorimotor frequency bands. During the test phase, the test signals are filtered by the bandpass filter of the effective sensorimotor frequency bands, and the extracted spatial covariance feature vectors will be classified by using the MDRM. Experiments on the BCI competition IV 2a dataset show that the proposed method is superior to other classification methods.

Keywords: non-uniform filter banks, motor imagery, brain-computer interface, minimum distance to Riemannian mean

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Authors: Dercan Gencbas, Hatice Bebis, Sue Moorhead

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In the nursing process, many of the nursing classification systems were created to be used in international. From these, NANDA-I, Nursing Outcomes Classification (NOC) and Nursing Interventions Classification (NIC). In this direction, the main objective of this study is to establish a model for caregivers in hospitals and communities in Turkey and to ensure that nursing outputs are assessed by NOC-based measures. There are many scales to measure Urinary Incontinence (UI), which is very common in children, in old age, vaginal birth, NOC scales are ideal for use in the nursing process for comprehensive and holistic assessment, with surveys available. For this reason, the purpose of this study is to evaluate the validity of the NOC outputs and indicators used for UI NANDA-I. This research is a methodological study. In addition to the validity of scale indicators in the study, how much they will contribute to recovery after the nursing intervention was assessed by experts. Scope validations have been applied and calculated according to Fehring 1987 work model. According to this, nursing inclusion criteria and scores were determined. For example, if experts have at least four years of clinical experience, their score was 4 points or have at least one year of the nursing classification system, their score was 1 point. The experts were a publication experience about nursing classification, their score was 1 point, or have a doctoral degree in nursing, their score was 2 points. If the expert has a master degree, their score was 1 point. Total of 55 experts rated Fehring as a “senior degree” with a score of 90 according to the expert scoring. The nursing interventions to be applied were asked to what extent these indicators would contribute to recovery. For coverage validity tailored to Fehring's model, each NOC and NOC indicator from specialists was asked to score between 1-5. Score for the significance of indicators was from 1=no precaution to 5=very important. After the expert opinion, these weighted scores obtained for each NOC and NOC indicator were classified as 0.8 critical, 0.8 > 0.5 complements, > 0.5 are excluded. In the NANDA-I / NOC / NIC system (guideline), 5 NOCs proposed for nursing diagnoses for UI were proposed. These outputs are; Urinary Continence, Urinary Elimination, Tissue Integrity, Self CareToileting, Medication Response. After the scales are translated into Turkish, the weighted average of the scores obtained from specialists for the coverage of all 5 NOCs and the contribution of nursing initiatives exceeded 0.8. After the opinions of the experts, 79 of the 82 indicators were calculated as critical, 3 of the indicators were calculated as supplemental. Because of 0.5 > was not obtained, no substance was removed. All NOC outputs were identified as valid and usable scales in Turkey. In this study, five NOC outcomes were verified for the evaluation of the output of individuals who have received nursing knowledge of UI and variant types. Nurses in Turkey can benefit from the outputs of the NOC scale to perform the care of the elderly incontinence.

Keywords: nursing outcomes, content validity, nursing diagnosis, urinary incontinence

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Authors: Ho Yin Wickson Cheung, Liora Malki-Epshtein

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Outdoor air pollution presents a significant challenge for public health globally, especially in urban areas, with road traffic acting as the primary contributor to air pollution. Several studies have documented the antagonistic relation between traffic-related air pollution (TRAP) and the impact on health, especially to the vulnerable group of population, particularly young pupils. Generally, TRAP could cause damage to their brain, restricting the ability of children to learn and, more importantly, causing detrimental respiratory issues in later life. Butlittle is known about the specific exposure of children at school during the school day and the impact this may have on their overall exposure to pollution at a crucial time in their development. This project has set out to examine the air quality across primary schools in South-East London and assesses the variability of data found based on their geographic location and surroundings. Nitrogen dioxide, PM contaminants, and carbon dioxide were collected with diffusion tubes and portable monitoring equipment for eight schools across three local areas, that are Greenwich, Lewisham, and Tower Hamlets. This study first examines the geographical features of the schools surrounding (E.g., coverage of urban road structure and green infrastructure), then utilize three different methods to capture pollutants data. Moreover, comparing the obtained results with existing data from monitoring stations to understand the differences in air quality before and during the pandemic. Furthermore, most studies in this field have unfortunately neglected human exposure to pollutants and calculated based on values from fixed monitoring stations. Therefore, this paper introduces an alternative approach by calculating human exposure to air pollution from real-time data obtained when commuting within related areas (Driving routes and field walking). It is found that schools located highly close to motorways are generally not suffering from the most air pollution contaminants. Instead, one with the worst traffic congested routes nearby might also result in poor air quality. Monitored results also indicate that the annual air pollution values have slightly decreased during the pandemic. However, the majority of the data is currently still exceeding the WHO guidelines. Finally, the total human exposures for NO2 during commuting in the two selected routes were calculated. Results illustrated the total exposure for route 1 were 21,730 μm/m3 and 28,378.32 μm/m3, and for route 2 were 30,672 μm/m3 and 16,473 μm/m3. The variance that occurred might be due to the difference in traffic volume that requires further research. Exposure for NO2 during commuting was plotted with detailed timesteps that have shown their peak usually occurred while commuting. These have consolidated the initial assumption to the extremeness of TRAP. To conclude, this paper has yielded significant benefits to understanding air quality across schools in London with the new approach of capturing human exposure (Driving routes). Confirming the severity of air pollution and promoting the necessity of considering environmental sustainability for policymakers during decision making to protect society's future pillars.

Keywords: air pollution, schools, pupils, congestion

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Authors: K. Kalaiarasan, B. Pandeeswari, A. Arockia John Francis

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Wireless, Multi-hop networks consist of one or more intermediate nodes along the path that receive and forward packets via wireless links. The backpressure algorithm provides throughput optimal routing and scheduling decisions for multi-hop networks with dynamic traffic. Xpress, a cross-layer backpressure architecture was designed to reach the capacity of wireless multi-hop networks and it provides well coordination between layers of network by turning a mesh network into a wireless switch. Transmission over the network is scheduled using a throughput-optimal backpressure algorithm. But this architecture operates much below their capacity due to out-of-order packet delivery and variable packet size. In this paper, we present Xpress-T, a throughput optimal backpressure architecture with TCP support designed to reach maximum throughput of wireless multi-hop networks. Xpress-T operates at the IP layer, and therefore any transport protocol, including TCP, can run on top of Xpress-T. The proposed design not only avoids bottlenecks but also handles out-of-order packet delivery and variable packet size, optimally load-balances traffic across them when needed, improving fairness among competing flows. Our simulation results shows that Xpress-T gives 65% more throughput than Xpress.

Keywords: backpressure scheduling and routing, TCP, congestion control, wireless multihop network

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Igor Perechuda, Wojciech Cieśliński

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The paper identifies the features of Polish sports clubs in the particular organizational forms: profit and nonprofit. Identification and description of these features is carried out in terms of financial efficiency of the given organizational form. Under the terms of the efficiency the research allows you to specify the advantages of particular organizational sports club form and the following limitations. Paper considers features of sports clubs in range of Polish conditions as legal regulations. The sources of the functioning efficiency of sports clubs may lie in the organizational forms in which they operate. Each of the available forms can be considered either a for-profit or nonprofit enterprise. Depending on this classification there are different capabilities of increasing organizational and financial efficiency of a given sports club. Authors start with general classification and difference between for-profit and non-profit sport clubs. Next identifies specific financial and organizational conditions of both organizational form and then show examples of mixed activity forms and their efficiency effect.

Keywords: financial efficiency, for-profit, non-profit, sports club

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Authors: Sibel Kurt

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In this study, with the use of Goffee and Jones’s corporate culture classification and the scale of this classification, there aimed to analyze a company’s corporate culture which does not have a public relations or communication department. First of all, the type of corporate culture in the company had been determined. Then it questioned if there are subcultures which formed according to demographics or the department of work. In the survey questionnaire, there are 53 questions total. 6 of these questions are about demographics, and 47 of them are about corporate culture. 152 personnel of the company had answered the survey, and the data have been evaluated according to frequency, descriptive, and compare means tests. The type of corporate culture of the company was determined as the 'communal' from the typology of Goffee and Jones in the positive form. There are no subcultures in the company which bases on the demographics, but only one subculture has determined according to the department of work. As a result, the absence of public relations department, personnel’s low level of awareness about corporate culture, and the lack of information between management and employees has been revealed.

Keywords: corporate culture, subculture, public relations, organizational communication

Procedia PDF Downloads 162

Authors: T. Garlan, I. Gabelotaud, S. Lucas, E. Marchès

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Production of a global sedimentological seabed map has been initiated in 1995 to provide the necessary tool for searches of aircraft and boats lost at sea, to give sedimentary information for nautical charts, and to provide input data for acoustic propagation modelling. This original approach had already been initiated one century ago when the French hydrographic service and the University of Nancy had produced maps of the distribution of marine sediments of the French coasts and then sediment maps of the continental shelves of Europe and North America. The current map of the sediment of oceans presented was initiated with a UNESCO's general map of the deep ocean floor. This map was adapted using a unique sediment classification to present all types of sediments: from beaches to the deep seabed and from glacial deposits to tropical sediments. In order to allow good visualization and to be adapted to the different applications, only the granularity of sediments is represented. The published seabed maps are studied, if they present an interest, the nature of the seabed is extracted from them, the sediment classification is transcribed and the resulted map is integrated in the world map. Data come also from interpretations of Multibeam Echo Sounder (MES) imagery of large hydrographic surveys of deep-ocean. These allow a very high-quality mapping of areas that until then were represented as homogeneous. The third and principal source of data comes from the integration of regional maps produced specifically for this project. These regional maps are carried out using all the bathymetric and sedimentary data of a region. This step makes it possible to produce a regional synthesis map, with the realization of generalizations in the case of over-precise data. 86 regional maps of the Atlantic Ocean, the Mediterranean Sea, and the Indian Ocean have been produced and integrated into the world sedimentary map. This work is permanent and permits a digital version every two years, with the integration of some new maps. This article describes the choices made in terms of sediment classification, the scale of source data and the zonation of the variability of the quality. This map is the final step in a system comprising the Shom Sedimentary Database, enriched by more than one million punctual and surface items of data, and four series of coastal seabed maps at 1:10,000, 1:50,000, 1:200,000 and 1:1,000,000. This step by step approach makes it possible to take into account the progresses in knowledge made in the field of seabed characterization during the last decades. Thus, the arrival of new classification systems for seafloor has improved the recent seabed maps, and the compilation of these new maps with those previously published allows a gradual enrichment of the world sedimentary map. But there is still a lot of work to enhance some regions, which are still based on data acquired more than half a century ago.

Keywords: marine sedimentology, seabed map, sediment classification, world ocean

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Authors: M. G. Dirodi, G. Gugliotta, C. Leonardi

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The member states shall establish zones and agglomerations throughout their territory to assess and manage air quality in order to comply with European directives. In Italy decree 155/2010, transposing Directive 2008/50/EC on ambient air quality and cleaner air for Europe, merged into a single act the previous provisions on ambient air quality assessment and management, including those resulting from the implementation of Directive 2004/107/EC relating to arsenic, cadmium, nickel, mercury, and polycyclic aromatic hydrocarbons in ambient air. Decree 155/2010 introduced stricter rules for identifying zones on the basis of the characteristics of the territory in spite of considering pollution levels, as it was in the past. The implementation of such new criteria has reduced the great variability of the previous zoning, leading to a significant reduction of the total number of zones and to a complete and uniform ambient air quality assessment and management throughout the Country. The present document is related to the new zones definition in Italy according to Decree 155/2010. In particular, the paper contains the description and the analysis of the outcome of zoning and classification.

Keywords: zones, agglomerations, air quality assessment, classification

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Authors: Almahd Alshereef, Ahmed Alkilany, Hammad Said, Azuraliza Abu Bakar

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From time to time, electrical power grid is directed by the National Electricity Operator to conduct load shedding, which involves hours' power outages on the area of this study, Southern Electrical Grid of Libya (SEGL). Load shedding is conducted in order to alleviate pressure on the National Electricity Grid at times of peak demand. This approach has chosen a set of categories to study load-shedding problem considering the effect of the demand priorities on the operation of the power system during emergencies. Classification of category region for load shedding problem is solved by a new algorithm (the harmony algorithm) based on the "random generation list of category region", which is a possible solution with a proximity degree to the optimum. The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on SEGL.

Keywords: optimization, harmony algorithm, load shedding, classification

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder

Procedia PDF Downloads 287

Authors: Hamzeh Awad

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Disability is considered to be a worldwide complex phenomenon which rising at a phenomenal rate and caused by many different factors. Chronic diseases such as cardiovascular disease and diabetes can lead to mobility disability in particular and disability in general. The ICF is an integrative bio-psycho-social model of functioning and disability and considered by the World Health Organization (WHO) to be a reference for disability classification using its categories and core set to classify disorder’s functional limitations. Specialist programs at Sultan Bin Abdul Aziz Humanitarian City (SBAHC) are providing both inpatient and outpatient services have started to implement the ICF and use it as a problem solving tool in Rehab. Diabetes is leading contributing factor for disability and considered epidemic in several Gulf countries including the Kingdom of Saudi Arabia (KSA), where its prevalence continues to increase dramatically. Metabolic disorders, mainly diabetes are not well covered in Rehab field. The purpose of this study is present to research and clinical rehabilitation field of DREAM and ICF as a framework in clinical and research setting in Rehab service. Also, shed the light on using the ICF as problem solving tool at SBAHC. There are synergies between disability causes and wider public health priorities in relation to both chronic disease and disability prevention. Therefore, there is a need for strong advocacy and understanding of the role of ICF as a reference in Rehab settings in Middle East if we wish to seize the opportunity to reverse current trends of acquired disability in the region.

Keywords: international classification of functioning, disability and health (ICF), prototype, rehabilitation and diabetes

Procedia PDF Downloads 346

Authors: Jeongwoo Lee

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Children are the most vulnerable travelers and they are at risk for pedestrian injury. Creating a safe route to school is important because walking to school is one of the main opportunities for promotion of needed physical exercise among children. This study examined how the built environmental attributes near an elementary school influence traffic accidents among school-aged children. The study used two complementary data sources including the locations of police-reported pedestrian crashes and the built environmental characteristics of school areas. The environmental attributes of road segments were collected through GIS measurements of local data and actual site audits using the inventory developed for measuring pedestrian-crash risk scores. The inventory data collected at 840 road segments near 32 elementary schools in the city of Ulsan. We observed all segments in a 300-meter-radius area from the entrance of an elementary school. Segments are street block faces. The inventory included 50 items, organized into four domains: accessibility (17items), pleasurability (11items), perceived safety from traffic (9items), and traffic and land-use measures (13items). Elementary schools were categorized into two groups based on the distribution of the pedestrian-crash hazard index scores. A high pedestrian-crash zone was defined as an school area within the eighth, ninth, and tenth deciles, while no pedestrian-crash zone was defined as a school zone with no pedestrian-crash accident among school-aged children between 2013 and 2016. No- and high pedestrian-crash zones were compared to determine whether different settings of the built environment near the school lead to a different rate of pedestrian-crash incidents. The results showed that a crash risk can be influenced by several environmental factors such as a shape of school-route, number of intersections, visibility and land-use in a street, and a type of sidewalk. The findings inform policy for creating safe routes to school to reduce the pedestrian-crash risk among children by focusing on school zones.

Keywords: active school travel, school zone, pedestrian crash, safety route to school

Procedia PDF Downloads 243