Search results for: fault detection and classification

Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

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In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.

Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction

Procedia PDF Downloads 503

Authors: J. Silva, P. Arezes, R. Schierl, N. Costa

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In order to study environmental contamination by cytostatic drugs in Portugal hospitals, sampling campaigns were conducted in three hospitals in 2015 (112 samples). Platinum containing drugs and fluorouracil were chosen because both were administered in high amounts. The detection limit was 0.01 pg/cm² for platinum and 0.1 pg/cm² for fluorouracil. The results show that spills occur mainly on the patient`s chair, while the most referenced occurrence is due to an inadequately closed wrapper. Day hospitals facilities were detected as having the largest number of contaminated samples and with higher levels of contamination.

Keywords: cytostatic, contamination, hospital, procedures, handling

Procedia PDF Downloads 287

Authors: Ang Chia Hong, Julian Khoo Xubin, Burra Venkata Durga Kumar

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Distributed systems offer many benefits to the healthcare industry. From big data analysis to business intelligence, the increased computational power and efficiency from distributed systems serve as an invaluable resource in the healthcare sector to utilize. However, as the usage of these distributed systems increases, many issues arise. The main focus of this paper will be on security issues. Many security issues stem from distributed systems in the healthcare industry, particularly information security. The data of people is especially sensitive in the healthcare industry. If important information gets leaked (Eg. IC, credit card number, address, etc.), a person’s identity, financial status, and safety might get compromised. This results in the responsible organization losing a lot of money in compensating these people and even more resources expended trying to fix the fault. Therefore, a framework for a blockchain-based healthcare data management system for healthcare was proposed. In this framework, the usage of a blockchain network is explored to store the encryption key of the patient’s data. As for the actual data, it is encrypted and its encrypted data, called ciphertext, is stored in a cloud storage platform. Furthermore, there are some issues that have to be emphasized and tackled for future improvements, such as a multi-user scheme that could be proposed, authentication issues that have to be tackled or migrating the backend processes into the blockchain network. Due to the nature of blockchain technology, the data will be tamper-proof, and its read-only function can only be accessed by authorized users such as doctors and nurses. This guarantees the confidentiality and immutability of the patient’s data.

Keywords: distributed, healthcare, efficiency, security, blockchain, confidentiality and immutability

Procedia PDF Downloads 168

Authors: Lev Bertovsky

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The purpose of this study was to determine the reasons for the formation of false testimony from witnesses and make recommendations on the recognition of such cases. During the studies, which were based on the achievements of professionals in the field of psychology, as well as personal investigative practice, the stages of perception of the information were studied, as well as the process of its reclaim from the memory and transmission to the communicator upon request. Based on the principles of the human brain, kinds of conscientious witness mistakes were systematized. Proposals were formulated for the optimization of investigative actions in cases where the witnesses make an honest mistake with respect to the effects previously observed by them.

Keywords: criminology, eyewitness testimony, honest mistake, information, investigator, investigation, questioning

Procedia PDF Downloads 179

Authors: T. G. Pathrikar, A. D. Urhekar, M. P. Bansal

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To find out S. aureus from patient samples on the basis of coagulase test. We have evaluated slide coagulase (n=46 positive), tube coagulase (n=48 positive) and DNase test (n=44, positive) , We have isolated and identified MRSA from various clinical samples and specimens by disc diffusion method determined the incidence of MRSA 50% in patients. Found out the in vitro antimicrobial susceptibility pattern of MRSA isolates and also the MIC of MRSA of oxacillin by E-Test.

Keywords: cefoxitin disc diffusion MRSA detection, e – test, S. aureus devastating pathogen, tube coagulase confirmation

Procedia PDF Downloads 480

Authors: Petr Slobodian, Pavel Riha, Jiri Matyas, Robert Olejnik, Nuri Karakurt

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Thermoelectric devices generate an electrical current when there is a temperature gradient between the hot and cold junctions of two dissimilar conductive materials typically n-type and p-type semiconductors. Consequently, also the polymeric semiconductors composed of polymeric matrix filled by different forms of carbon nanotubes with proper structural hierarchy can have thermoelectric properties which temperature difference transfer into electricity. In spite of lower thermoelectric efficiency of polymeric thermoelectrics in terms of the figure of merit, the properties as stretchability, flexibility, lightweight, low thermal conductivity, easy processing, and low manufacturing cost are advantages in many technological and ecological applications. Polyethylene-octene copolymer based highly elastic composites filled with multi-walled carbon nanotubes (MWCTs) were prepared by sonication of nanotube dispersion in a copolymer solution followed by their precipitation pouring into non-solvent. The electronic properties of MWCNTs were moderated by different treatment techniques such as chemical oxidation, decoration by Ag clusters or addition of low molecular dopants. In this concept, for example, the amounts of oxygenated functional groups attached on MWCNT surface by HNO₃ oxidation increase p-type charge carriers. p-type of charge carriers can be further increased by doping with molecules of triphenylphosphine. For partial altering p-type MWCNTs into less p-type ones, Ag nanoparticles were deposited on MWCNT surface and then doped with 7,7,8,8-tetracyanoquino-dimethane. Both types of MWCNTs with the highest difference in generated thermoelectric power were combined to manufacture polymeric based thermoelectric module generating thermoelectric voltage when the temperature difference is applied between hot and cold ends of the module. Moreover, it was found that the generated voltage by the thermoelectric module at constant temperature gradient was significantly affected when exposed to vapors of different volatile organic compounds representing then a self-powered thermoelectric sensor for chemical vapor detection.

Keywords: carbon nanotubes, polymer composites, thermoelectric materials, self-powered gas sensor

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Authors: Victor Bloch, Eerikki Kaila, Reetta Palva

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Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.

Keywords: agricultural robot, field robot, plant detection, robot performance

Procedia PDF Downloads 62

Authors: Shveta Bathla, Preeti Rawat, Sudarshan Kumar, Rubina Baithalu, Jogender Singh Rana, Tushar Kumar Mohanty, Ashok Kumar Mohanty

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Pregnancy is a complex process which includes series of events such as fertilization, formation of blastocyst, implantation of embryo, placental formation and development of fetus. The success of these events depends on various interactions which are synchronized by endocrine interaction between a receptive dam and competent embryo. These interactions lead to change in expression of hormones and proteins. But till date no protein biomarker is available which can be used to detect successful completion of these events. We employed quantitative proteomics approach to develop putative serological biomarker which has diagnostic applicability for early detection of pregnancy in cows. For this study, sera were collected from control (non-pregnant, n=6) and pregnant animals on successive days of pregnancy (7, 19, 45, n=6). The sera were subjected to depletion for removal of albumin using Norgen depletion kit. The tryptic peptides were labeled with iTRAQ. The peptides were pooled and fractionated using bRPLC over 80 min gradient. Then 12 fractions were injected to nLC for identification and quantitation in DDA mode using ESI. Identification using Mascot search revealed 2056 proteins out of which 352 proteins were differentially expressed. Twenty proteins were upregulated and twelve proteins were down-regulated with fold change > 1.5 and < 0.6 respectively (p < 0.05). The gene ontology studies of DEPs using Panther software revealed that majority of proteins are actively involved in catalytic activities, binding and enzyme regulatory activities. The DEP'S such as NF2, MAPK, GRIPI, UGT1A1, PARP, CD68 were further subjected to pathway analysis using KEGG and Cytoscape plugin Cluego that showed involvement of proteins in successful implantation, maintenance of pluripotency, regulation of luteal function, differentiation of endometrial macrophages, protection from oxidative stress and developmental pathways such as Hippo. Further efforts are continuing for targeted proteomics, western blot to validate potential biomarkers and development of diagnostic kit for early pregnancy diagnosis in cows.

Keywords: bRPLC, Cluego, ESI, iTRAQ, KEGG, Panther

Procedia PDF Downloads 447

Authors: Somaya A. Abd El Mottaleb, Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

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In this paper, we present the performance of spectral amplitude coding optical code division multiple access using different detectors at different transmission distances using single photodiode detection technique. Modified double weight codes are used as signature codes. Simulation results show that the system using avalanche photo detector can move distance longer than that using positive intrinsic negative photo detector.

Keywords: avalanche photodiode, modified double weight, multiple access technique, single photodiode.

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Authors: Amarjit Singh

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In this paper, a method for extraction of text subtitles in large video is proposed. The video data needs to be annotated for many multimedia applications. Text is incorporated in digital video for the motive of providing useful information about that video. So need arises to detect text present in video to understanding and video indexing. This is achieved in two steps. First step is text localization and the second step is text verification. The method of text detection can be extended to text recognition which finds applications in automatic video indexing; video annotation and content based video retrieval. The method has been tested on various types of videos.

Keywords: video, subtitles, extraction, annotation, frames

Procedia PDF Downloads 592

Authors: Yunxiang Fang

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With the aging trend continuing to accelerate, open space is important for the daily life of the elderly, and its old-age friendliness is worthy of attention. Based on behavioral observation and literature research, this paper studies the behavior of the elderly in urban open space. Through the investigation, classification and quantitative analysis of the activity types, time characteristics and spatial behavior order of the elderly in Xicheng Square in Hangzhou, it summarizes the square space suitable for the psychological needs, physiology and activity needs of the elderly, combined with the basis of literature research. Finally, the suggestions for the improvement of the old-age friendship of Xicheng Square are put forward, from the aspects of microclimate, safety and accessibility, space richness and service facility quality.

Keywords: behavior characteristics, old-age friendliness, open space, square

Procedia PDF Downloads 162

Authors: Andrey Vinajera-Zamora, Norge Coello-Machado, Elke Glistau

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The objective of this research is calculate the added value in operations of electric power meters (EPM) supply chains, specifically the EPM of 220v. The tool used is composed by six steps allowing at same time the identification of calibration of EPM as the bottleneck operation according the net added value being at same time the process of higher added value. On the other hand, this methodology allows calculate the amount of money to buy the raw material. The main conclusions are related to the analyze ‘s way and calculating of added value in supply chain integrated by the echelons procurement, production and distribution or any of these.

Keywords: economic value added, supply chain management, value chain, bottleneck detection

Procedia PDF Downloads 289

Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Ambika Selvaraj

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Magnetic iron oxide nanoparticles (IO) of < 20nm (superparamagnetic) become promising tool in cancer therapy, and integrated nanodevices for cancer detection and screening. The obstacles include particle heterogeneity and cost. It can be overcome by developing monodispersed nanoparticles in economical approach. We have successfully synthesized < 7 nm IO by low temperature controlled technique, in which Fe0 is sandwiched between stabilizer and Fe2+. Size analysis showed the excellent size control from 31 nm at 33°C to 6.8 nm at 10°C. Resultant monodispersed IO were found to be stable for > 50 reuses, proved its applicability in biomedical applications.

Keywords: low temperature synthesis, hybrid iron nanoparticles, cancer therapy, biomedical applications

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

Procedia PDF Downloads 314

Authors: Shweta Pinjarkar, Shrutika Yawale, Mayuri Patil, Reshma Adagale

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Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this, demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application. Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this , demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application.

Keywords: face detection, face recognition, eigen faces, algorithm

Procedia PDF Downloads 346

Authors: R. Horchani

Abstract:

Optical pumping technique with laser fields combined with photo-association of ultra-cold atoms leads to control on demand the vibrational and/or the rotational population of molecules. Here, we review the basic concepts and main steps should be followed, including the excitation schemes and detection techniques we use to achieve the ro-vibrational cooling of Cs2 molecules. We also discuss the extension of this technique to other molecules. In addition, we present a theoretical model used to support the experiment. These simulations can be widely used for the preparation of various experiments since they allow the optimization of several important experimental parameters.

Keywords: cold molecule, photo-association, optical pumping, vibrational and rotational cooling

Procedia PDF Downloads 289

Authors: Amanpreet Kaur

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Wavelet transform (WT) is a powerful statistical tool used in applied mathematics for signal and image processing. The different mother, wavelet basis function, has been compared to select the optimal wavelet function that represents the electromyogram signal characteristics of upper limb amputees. Four different EMG electrode has placed on different location of shoulder muscles. Twenty one wavelet functions from different wavelet families were investigated. These functions included Daubechies (db1-db10), Symlets (sym1-sym5), Coiflets (coif1-coif5) and Discrete Meyer. Using mean square error value, the significance of the mother wavelet functions has been determined for teres, pectorals, and infraspinatus around shoulder muscles. The results show that the best mother wavelet is the db3 from the Daubechies family for efficient classification of the signal.

Keywords: Daubechies, upper limb amputation, shoulder muscles, Symlets, Coiflets

Procedia PDF Downloads 227

Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

Procedia PDF Downloads 149

Authors: Mahmoud M. S. Albattah

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Urbanization results in the expansion of administrative boundaries, mainly at the periphery, ultimately leading to changes in landcover. Agricultural land, naturally vegetated land, and other land types are converted into residential areas with a high density of constructs, such as transportation systems and housing. In urban regions of rapid growth and change, urban planners need regular information on up to date ground change. Amman (the capital of Jordan) is growing at unprecedented rates, creating extensive urban landscapes. Planners interact with these changes without having a global view of their impact. The use of aerial photographs and satellite images data combined with topographic information and field survey could provide effective information to develop urban change and growth inventory which could be explored towards producing a very important signature for the built-up area changes.

Keywords: highway design, satellite technologies, remote sensing, GIS, image segmentation, classification

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Authors: Jaber Nikpouri, Arsalan Amralizadeh

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In robotics manipulators, the trajectory should be optimum, thus the torque of the robot can be minimized in order to save power. This paper includes an optimal path planning scheme for a robotic manipulator. Recently, techniques based on metaheuristics of natural computing, mainly evolutionary algorithms (EA), have been successfully applied to a large number of robotic applications. In this paper, the improved BBO algorithm is used to minimize the objective function in the presence of different obstacles. The simulation represents that the proposed optimal path planning method has satisfactory performance.

Keywords: biogeography-based optimization, path planning, obstacle detection, robotic manipulator

Procedia PDF Downloads 283

Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

Procedia PDF Downloads 712

Authors: K. Tunde Olagunju, C. Scott Allen, Freek Van Der Meer

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Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization are only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two (2) operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the hydrocarbon spectral slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven (7) different hydrocarbon oils (crude and refined oil) taken on ten (10) different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).

Keywords: hydrocarbon, oil spill, remote sensing, hyperspectral, multispectral, hydrocarbon-substrate combination, Sentinel-2, WorldView-3

Procedia PDF Downloads 208

Authors: Zhao Haoyue

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Due to the combined effects of climate change, urban expansion, and population growth, various environmental issues, such as urban heat islands and pollution, arise. Therefore, reliable information on urban environmental climate is needed to address and mitigate the negative effects. The emergence of urban climate maps provides a practical basis for urban climate regulation and improvement. This article takes Shapingba District, Chongqing City, as an example to study the construction method of urban thermal environment climate maps based on GIS spatial analysis technology. The thermal load, ventilation potential analysis map, and thermal environment comprehensive analysis map were obtained. Based on the classification criteria obtained from the climate map, corresponding protection and planning mitigation measures have been proposed.

Keywords: urban climate, GIS, heat island analysis, urban thermal environment

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Authors: C. T. Eze, I. N. E. Onwurah

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An important hydrogeologic problem in areas of high faults formations is high environmental health hazard occasioned by microbial and heavy metals contamination of ground waters. Consequently, we examined the microbial load and heavy metals concentration of hospital wastewater discharged into the environment at Park Lane General Hospital Enugu Urban, Nigeria. The microbial counts, characteristics and frequency of occurrences of the isolated microorganisms were determined by cultural, morphological and biochemical characteristics using established procedure while the varying concentrations of the identified heavy metals were determined using the spectrophotometric method. The microbiological analyses showed a mean total aerobic bacteria counts from 13.7 ± 0.65 × 107 to 22.8 ± 1.14 ×1010 CFU/ml, mean total anaerobic bacteria counts from 6.0 ± 1.6 × 103 to 1.7 ± 0.41 ×104 CFU/ml and mean total fungal counts from 0 ± 0 to 2.3 ± 0.16 × 105 CFU/ml. The isolated micro-organisms which included both pathogenic and non-pathogenic organisms were Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Salmonella typhi, Bacillus subtilis, Proteus vulgaris, Klesbsiella pneumonia and bacteriodes sp. The only fungal isolate was Candida albican. The heavy metals identified in the leachate were Arsenic, Cadmium, Lead, Mercury and Chromium and their concentrations ranged from 0.003 ± 0.00082 to 0.14 ± 0.0082 mg/l. These values were above WHO permissible limits while others fall within the limits. Therefore, hospital waste water can pose the environmental health risk when not properly treated before discharge, especially in geologic formations with high fault formations.

Keywords: bacterial isolates, fungal isolates, heavy metals, hospital wastewater, microbial counts

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Authors: Loai Abdallah, Malik Yousef

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A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

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Authors: Thomas Ousterhout

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In an effort to test the ability of a commercial grade EEG headset to effectively measure the N400 ERP, a replication study was conducted to see if similar results could be produced as that which used a medical grade EEG. Pictures of meaningful and meaningless hand postures were borrowed from the original author and subjects were required to perform a semantic discrimination task. The N400 was detected indicating semantic processing of the meaningfulness of the hand postures. The results corroborate those of the original author and support the use of some commercial grade EEG headsets for non-critical research applications.

Keywords: EEG, ERP, N400, semantics, congruency, gestures, emotiv

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Authors: Metuku Shyamsunder, Kakarla Subbarao, P. Prasanna

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In radars, an electromagnetic waveform is sent, and an echo of the same signal is received by the receiver. From this received signal, by extracting various parameters such as round trip delay, Doppler frequency it is possible to find distance, speed, altitude, etc. However, nowadays as the technology increases, intruders are intercepting transmitted signal as it reaches them, and they will be extracting the characteristics and trying to modify them. So there is a need to develop a system whose signal cannot be identified by no cooperative intercept receivers. That is why LPI radars came into existence. In this paper, a brief discussion on LPI radar and its modulation (polytime code (PT1)), detection (cyclostationary (DFSM & FAM) techniques such as DFSM, FAM are presented and compared with respect to computational complexity.

Keywords: LPI radar, polytime codes, cyclostationary DFSM, FAM

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Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

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This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

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Authors: Ilirian Laçi, Alketa Spahiu

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Modality of treatment in hepatocellular carcinoma (HCC) patients depends on the stage of the disease. The Barcelona Clinic Liver Cancer Classification (BCLC) is the preferred staging system. There are many patients initially present with intermediate-stage disease. For these patients, transarterial chemoembolization (TACE) is the treatment of choice. The differences in individual factors that are not captured by the BCLC framework, such as the tumor growth pattern, degree of hypervascularity, and vascular supply, complicate further evaluation of these patients. Because of these differences, not all patients benefit equally from TACE. Several tools have been devised to aid the decision-making process, which have shown promising initial results but have failed external evaluation and have not been translated to the clinic aspects. Criteria for treatment decisions in daily clinical practice are needed in all stages of the disease.

Keywords: hepatocellular carcinoma, transarterial chemoembolization, TACE, liver

Procedia PDF Downloads 84