Search results for: automatic classification of tremor types

Authors: Amy Lebar, Kim L. Trenbath, Bennett Doherty, William Livingood

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Plug and process loads (PPLs) account for 47% of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering and data storage. A laboratory proof of concept (PoC) demonstrated all but the data storage capabilities and these capabilities were validated using an office building scenario. The PoC can identify when a device is plugged into an outlet and the location of the device in the building. When a device is moved, the PoC’s dashboard and database are automatically updated with the new location. The PoC implements controls to devices from the system dashboard so that devices maintain correct schedules regardless of where they are plugged in within a building. ATLIS’s primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. A system like ATLIS could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

Keywords: commercial buildings, grid-interactive efficient buildings (GEB), miscellaneous electric loads (MELs), plug loads, plug load management (PLM)

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Authors: Benjamin Goldsmith, Felix Heisel

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The building industry must reduce its emissions in order to meet 2030 neutrality targets, and modular and/or offsite construction is seen as an alternative to conventional construction methods which could help achieve this goal. Modular construction has previously been shown to be less wasteful and has a lower global warming potential (GWP). While many studies have been conducted investigating the life cycle impacts of modular and conventional construction, few studies have compared different types of modular assembly and construction in order to determine which offer the greatest environmental benefits over their whole life cycle. This study seeks to investigate three different modular construction types -infill frame, core, and podium- in order to determine environmental impacts such as GWP as well as circularity indicators. The study will focus on the emissions of the production, construction, and end-of-life phases. The circularity of the various approaches will be taken into consideration in order to acknowledge the potential benefits of the ability to reuse and/or reclaim materials, products, and assemblies. The study will conduct hypothetical case studies for the three different modular construction types, and in doing so, control the parameters of location, climate, program, and client. By looking in-depth at the GWP of the beginning and end phases of various simulated modular buildings, it will be possible to make suggestions on which type of construction has the lowest global warming potential.

Keywords: modular construction, offsite construction, life cycle analysis, global warming potential, environmental impact, circular economy

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Authors: Dar-Bin Shieh, Gwo-Bin Lee, Chen-Ming Chang, Chen Sheng Yeh, Chih-Chia Huang, Tsung-Ju Li

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Mitochondrial defects have a significant impact in many human diseases and aging associated phenotypes. The pathogenic mitochondrial DNA (mtDNA) mutations are diverse and usually present as heteroplasmic. mtDNA 4977bps deletion is one of the common mtDNA defects, and the ratio of mutated versus normal copy is significantly associated with clinical symptoms thus their quantitative detection has become an important unmet needs for advanced disease diagnosis and therapeutic guidelines. This study revealed a Micro-electro-mechanical-system (MEMS) enabled automatic microfluidic chip that only required minimal sample. The system integrated multiple laboratory operation steps into a Lab-on-a-Chip for high-sensitive and prompt measurement. The entire process including magnetic nanoparticle based mtDNA extraction in chip, mutation selective photonic DNA cleavage, and nanoparticle accelerated photonic quantitative polymerase chain reaction (qPCR). All subsystems were packed inside a miniature three-dimensional micro structured system and operated in an automatic manner. Integration of magnetic beads with microfluidic transportation could promptly extract and enrich the specific mtDNA. The near infrared responsive magnetic nanoparticles enabled micro-PCR to be operated by pulse-width-modulation controlled laser pulsing to amplify the desired mtDNA while quantified by fluorescence intensity captured by a complementary metal oxide system array detector. The proportions of pathogenic mtDNA in total DNA were thus obtained. Micro capillary electrophoresis module was used to analyze the amplicone products. In conclusion, this study demonstrated a new magnetophotonic based qPCR MEMS system that successfully detects and quantify specific disease related DNA mutations thus provides a promising future for rapid diagnosis of mitochondria diseases.

Keywords: mitochondrial DNA, micro-electro-mechanical-system, magnetophotonics, PCR

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Authors: Lemac Tin

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This paper deals with the lyrical subject of the confessional poetry which is the main part of her stylistic strucuture. We concluded two types of this subject in the classical confessional poetic discourse; reflexive and authentic subject. We offer the model of their genesis, textual features and appeareance realisations. Genesis is related to the theories of deriving poetry from emotion and magic and their similar position in the primitive lyrics and lyrics of the ancient civilizations. Textual features are related to the emotive and semiotic analysis of each type. Appearance realisations of these two types are I-subject, We-subject, transvocal and objectified subject. We check this approaches on some of the poems from World literature.

Keywords: confessional poetry, confessional lyrical subject, magic, emotion, emotive analysis, semiotic analysis

Procedia PDF Downloads 271

Authors: G. S. Ryu, K. T. Koh, H. Y. Kim, G. H. An, D. W. Seo

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Geopolymer mortar is produced by alkaline activation of pozzolanic materials such as fly ground granulated blast-furnace slag (GGBFS) and fly ash (FA). Its unique reaction pathway facilitates rapid strength development in comparison with hydration of ordinary Portland cement (OPC). Geopolymer can be fabricated using various types and dosages of alkali-activator, which effectively gives a wider control over the performance of the final product. The present study investigates the effect of types of precursors and curing conditions on the fresh state and strength development characteristics of geopolymers, thereby comparatively exploring the effect of precursors from various sources of origin. The obtained result showed that the setting time and strength development of the specimens with the identical mix proportion but different precursors displayed significant variations.

Keywords: alkali-activated material, blast furnace slag, fly ash, flowability, strength development

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Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: M. Abdo, Ahmed Elghandour, Khairy Eltahlawy, Mohamed Shalaby

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A key development in the field of inertial sensors, fiber-optic gyroscopes (FOGs) are currently thought to be a competitive alternative to mechanical gyroscopes for inertial navigation and control applications. For the past few years, research and development efforts have been conducted all around the world using the FOG as a crucial sensor for high-accuracy inertial navigation systems. The main fundamentals of optical gyros were covered in this essay, followed by discussions of the main types of optical gyros—fiber optic gyroscopes and ring laser gyroscopes—and comparisons between them. We also discussed different types of fiber optic gyros, including interferometric, resonator, and brillion fiber optic gyroscopes.

Keywords: mechanical gyros, ring laser gyros, interferometric fiber optic gyros, resonator fiber optic gyros

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Authors: Husam El-Asfour, Fateh Adhnouss, Kenneth McIsaac, Abdul Mutalib Wahaishi, Raafat Aburukba, Idris El-Feghia

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Although intelligence is commonly referred to as the observable behavior in various fields and domains, it must also be shown how it develops by exhibiting multiple forms and without observing the inherent behavior. There have been several official and informal definitions of intelligence in various areas; however, no scientific agreement on a definition has been agreed upon. There must be a single definition, structure, and precise modeling for articulating how intelligence is perceived by people and machines in order to comprehend intelligence. Another key challenge is defining the different environment types based on the integral elements (agents) and their possible interactions. On the basis of conceptualization, this paper proposes a formal model for defining and developing intelligence. Forms of intelligence are derived from an ontological view, and thus intelligence is defined, described, and modeled based on the various types of environments.

Keywords: intelligence, forms, transformation, conceptualization, ontological view

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

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Authors: Cherrie Mae S. Sia, Noel J. Belonguel, Jarungchai Anton S. Vatanagul

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Background: Parkinson’s disease (PD) is a chronic progressive, neurodegenerative disorder known for its motor symptoms such as bradykinesia, resting tremor, muscle rigidity, and postural instability. Patients with PD also experience non-motor symptoms (NMS) such as depression, fatigue, and sleep disturbances that are most of the time unrecognized by clinicians. This may be due to the lack of spontaneous reports from the patients or partly because of the lack of systematic questioning from the healthcare professional. There is limited data with regards to these NMS especially that of Filipino patients with PD. Objectives: This study aims to determine the non-motor symptoms of Filipino patients with Parkinson’s disease. Materials and Methods: This is a prospective, cohort study involving thirty-four patients of Filipino-descent diagnosed with PD in three out-patient clinics in Cebu City from April to September 2014. Each patient was interviewed using the Non-Motor Symptom Scale (NMSS). A Cebuano version of the NMSS was also provided for the non-English speaking patients. Interview time was approximately ten to fifteen minutes for each respondent. Results: Of the thirty-four patients with Parkinson’s disease, majority was noted to be males (N=19) and the disease was noted to be more prevalent in patients with a mean age of 62 (SD±9) years old. Hypertension (59%) and diabetes mellitus (29%) were the common co-morbidities in the study population. All patients presented more than one NMS, with insomnia (41.2%), poor memory (23.5%) and depression (14.7%) being the first non-motor symptoms to occur. Symptoms involving mood/cognition (mean=2.21), and attention/memory (mean=2.05) were noted to be the most frequent and of moderate severity. Based on the NMSS, the symptoms that were noted to be mild and often to occur were those that involved the mood/cognition (score=3.84), attention/memory (score=3.50), and sleep/fatigue (score=3.00) domains. Levodopa-Carbidopa, Ropinirole, and Pramipexole were the most frequently used medications in the study population. Conclusion: Non-motor symptoms (NMS) are common in patients with Parkinson’s disease (PD). They appear at the time of diagnosis of PD or even before the motor symptoms manifest. The earliest non-motor symptoms to occur are insomnia, poor memory, and depression. Those pertaining to mood/cognition and attention/memory are the most frequent NMS and they are of moderate severity. Identifying these NMS by doing a questionnaire-guided interview such as the Non-Motor Symptom Scale (NMSS) before they can become more severe and affect the patient’s quality of life is a must for every clinician caring for a PD patient. Early treatment and control of these NMS can then be given, hence, improving the patient’s outcome and prognosis.

Keywords: non motor symptoms, Parkinson's Disease, insomnia, depression

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Authors: Mari Chaikovskaia, Jean-Philippe Gayon, Alain Quilliot

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We consider a fleet of elementary robots that can be connected in different ways to transport loads of different types. For instance, a single robot can transport a small load, and the association of two robots can either transport a large load or two small loads. We seek to determine the optimal number of robots to transport a set of loads in a given time interval, with or without reconfiguration. We show that the problem with reconfiguration is strongly NP-hard by a reduction to the bin-packing problem. Then, we study a special case with unit capacities and derive simple formulas for the minimum number of robots, up to 3 types of loads. For this special case, we compare the minimum number of robots with or without reconfiguration and show that the gain is limited in absolute value but may be significant for small fleets.

Keywords: fleet sizing, reconfigurability, robots, transportation

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Authors: Piotr-Robert Lazik, Lena Teichmann, Harald Garrecht

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Many concrete technologists are looking for a solution to replace fly ashes as a component that occurs as a major component of many types of concrete. The importance of such a component is clear -it saves cement and reduces the amount of CO₂ in the atmosphere that occurs during cement production. For example, the amount of cement in ultrahigh strength concrete (UHPC) is approximately 700-800 kg/m³ in normal concrete up to 350 kg/m³. For this reason, it is easy to follow that the use of components like fly ashes or wood ashes protect the environment. The newest investigations carried out at the University of Stuttgart have clearly shown that the use of wood ashes with appropriate pre-treatment in concrete has a positive effect. German-wide, there are hundreds of tons of wood ashes, which can be used in a wide range of construction materials. The strengths of the concrete with different types of cement and with wood ashes have given the same or, in some cases, better results than those with the use of fly ashes. There are many areas in building construction, where the clays of wood ashes can be used as a by-product. This does not only require a strength test but also, for example, an examination of structural-physical parameters. Especially the heat and moisture characteristics have an important role in times of energy-efficient construction. These are therefore determined and then compared with the characteristics of the concretes with fly ashes. The University of Stuttgart has decided to investigate the buildings' physical properties of different types of concrete with wood ashes to find their application in construction. After the examination of the buildings' physical properties in combination with strength tests, it is possible to determine in which field of civil engineering, this type of concrete can be used.

Keywords: fly ashes, wood ashes, structural-physical parameters, UHPC

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Authors: Kwan Hee Han

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In today’s business environments, frequent change of customer requirements is a tough challenge to manufacturing company. To cope with these challenges, a production planning and scheduling (PP&S) function might be established to provide accountability for both customer service and operational efficiency. Nowadays, many manufacturing firms have utilized PP&S software solutions to generate a realistic production plan and schedule to adapt to external changes efficiently. However, companies which consider the introduction of PP&S software solution, still have difficulties for selecting adequate solution to meet their specific needs. Since the task of PP&S is the one of major building blocks of SCM (Supply Chain Management) architecture, which deals with short term decision making in the production process of SCM, it is needed that the functionalities of PP&S should be analysed within the whole SCM process. The aim of this paper is to analyse the PP&S functionalities and its system architecture from the SCM perspective by using the criteria of level of planning hierarchy, major 4 SCM processes and problem-solving approaches, and finally propose a classification framework of PP&S solutions to facilitate the comparison among various commercial software solutions. By using proposed framework, several major PP&S solutions are classified and positioned according to their functional characteristics in this paper. By using this framework, practitioners who consider the introduction of computerized PP&S solutions in manufacturing firms can prepare evaluation and benchmarking sheets for selecting the most suitable solution with ease and in less time.

Keywords: production planning, production scheduling, supply chain management, the advanced planning system

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Authors: Ilma Robo, Saimir Heta, Vera Ostreni, Elsaida Agrushi, Eduart Kapaj

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Introduction: Cyclic hormonal fluctuations are known from literature to have a clinically visible effects on gingival tissue reactions, to the diagnosed processes of gingival inflammation. Materials and methods: At a total of 47 female patients, ad-hock presented at the University Clinic, were recorded data on effect of hormonal oscillations at periodontal treatment protocol. Oral examination was performed on soft tissue of gingiva and the oral mucous membrane, always respecting the air-drying procedure and then checking with free eye differences in oral mucosal relief. After the patients were informed about the study protocol, the purpose of the study and the ongoing procedure, verbal consensus was required. Results: The study was conducted in a total of 47 patients, out of which 13 patients were under the gingivitis classification, and 24 patients under the periodontal classification. Patients included in the study are divided by age, cycle week respectively 1,2,3 and 4.The younger age of female patients is more prone to the appearance of gingivitis, which is further aggravated by the effects of sexual hormones and the effect of the controlled or non-regulated fluctuations of the latter. Conclusions: The healing process is more fuel-intensive in the absence of high hormone levels, as they are these pro-inflammatory hormones, both in or near the ho Younger women are more open to volunteering in studies that record individual and study data that may last in time.

Keywords: gingiva, hormonal oscillations, female patients, mucosa, periodontal non-surgical treatment

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Authors: Fernanda A. P. Peres, Thiago N. Peres, Flavio S. Fogliatto, Michel J. Anzanello

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Batch processes are widely used in food industry and have an important role in the production of high added value products, such as chocolate. Process performance is usually described by variables that are monitored as the batch progresses. Data arising from these processes are likely to display a strong correlation-autocorrelation structure, and are usually monitored using control charts based on multiway principal components analysis (MPCA). Process control of a new batch is carried out comparing the trajectories of its relevant process variables with those in a reference set of batches that yielded products within specifications; it is clear that proper determination of the reference set is key for the success of a correct signalization of non-conforming batches in such quality control schemes. In chocolate manufacturing, misclassifications of non-conforming batches in the conching phase may lead to significant financial losses. In such context, the accuracy of process control grows in relevance. In addition to that, the main assumption in MPCA-based monitoring strategies is that all batches are synchronized in duration, both the new batch being monitored and those in the reference set. Such assumption is often not satisfied in chocolate manufacturing process. As a consequence, traditional techniques as MPCA-based charts are not suitable for process control and monitoring. To address that issue, the objective of this work is to compare the performance of three dynamic time warping (DTW) methods in the alignment and synchronization of chocolate conching process variables’ trajectories, aimed at properly determining the reference distribution for multivariate statistical process control. The power of classification of batches in two categories (conforming and non-conforming) was evaluated using the k-nearest neighbor (KNN) algorithm. Real data from a milk chocolate conching process was collected and the following variables were monitored over time: frequency of soybean lecithin dosage, rotation speed of the shovels, current of the main motor of the conche, and chocolate temperature. A set of 62 batches with durations between 495 and 1,170 minutes was considered; 53% of the batches were known to be conforming based on lab test results and experts’ evaluations. Results showed that all three DTW methods tested were able to align and synchronize the conching dataset. However, synchronized datasets obtained from these methods performed differently when inputted in the KNN classification algorithm. Kassidas, MacGregor and Taylor’s (named KMT) method was deemed the best DTW method for aligning and synchronizing a milk chocolate conching dataset, presenting 93.7% accuracy, 97.2% sensitivity and 90.3% specificity in batch classification, being considered the best option to determine the reference set for the milk chocolate dataset. Such method was recommended due to the lowest number of iterations required to achieve convergence and highest average accuracy in the testing portion using the KNN classification technique.

Keywords: batch process monitoring, chocolate conching, dynamic time warping, reference set distribution, variable duration

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: Paul Licina, Emma M. Johnston, David Lisle, Mark Young, Chris Brady

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Background: Lumbar pars pathology is a common cause of pain in the growing spine. It can be seen in young athletes participating in at-risk sports and can affect sporting performance and long-term health due to its resistance to traditional management. There is a current lack of consensus of classification and treatment for pars injuries. Previous systems used CT to stage pars defects but could not assess early stress reactions. A modified classification is proposed that considers findings on MRI, significantly improving early treatment guidance. The treatment protocol is designed for patients aged 5 to 19 years. Method: Clinical screening identifies patients with a low, medium, or high index of suspicion for lumbar pars injury using patient age, sport participation and pain characteristics. MRI of the at-risk cohort enables augmentation of existing CT-based classification while avoiding ionising radiation. Patients are classified into five categories based on MRI findings. A type 0 lesion (stress reaction) is present when CT is normal and MRI shows high signal change (HSC) in the pars/pedicle on T2 images. A type 1 lesion represents the ‘early defect’ CT classification. The group previously referred to as a 'progressive stage' defect on CT can be split into 2A and 2B categories. 2As have HSC on MRI, whereas 2Bs do not. This distinction is important with regard to healing potential. Type 3 lesions are terminal stage defects on CT, characterised by pseudarthrosis. MRI shows no HSC. Results: Stress reactions (type 0) and acute fractures (1 and 2a) can heal and are treated in a custom-made hard brace for 12 weeks. It is initially worn 23 hours per day. At three weeks, patients commence basic core rehabilitation. At six weeks, in the absence of pain, the brace is removed for sleeping. Exercises are progressed to positions of daily living. Patients with continued pain remain braced 23 hours per day without exercise progression until becoming symptom-free. At nine weeks, patients commence supervised exercises out of the brace for 30 minutes each day. This allows them to re-learn muscular control without rigid support of the brace. At 12 weeks, bracing ceases and MRI is repeated. For patients with near or complete resolution of bony oedema and healing of any cortical defect, rehabilitation is focused on strength and conditioning and sport-specific exercise for the full return to activity. The length of this final stage is approximately nine weeks but depends on factors such as development and level of sports participation. If significant HSC remains on MRI, CT scan is considered to definitively assess cortical defect healing. For these patients, return to high-risk sports is delayed for up to three months. Chronic defects (2b and 3) cannot heal and are not braced, and rehabilitation follows traditional protocols. Conclusion: Appropriate clinical screening and imaging with MRI can identify pars pathology early. In those with potential for healing, we propose hard bracing and appropriate rehabilitation as part of a multidisciplinary management protocol. The validity of this protocol will be tested in future studies.

Keywords: adolescents, MRI classification, pars interticularis, treatment protocol

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Piotr Prewysz-Kwinto, Grazyna Voss

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In June 2013, the European Parliament and the Council adopted a directive on financial reporting (Directive 2013/34/EU). The main objective was to simplify the principles of the preparation of financial statements, including the principles of the presentation and disclosures of financial information by adapting reporting burdens to the type and size of an undertaking. Therefore, the Directive introduced a classification of all undertakings into five groups, i.e. micro, small, medium-sized, large and public-interest entities, and defined in detail the classification criteria. The principles of the preparation of financial statements and the presentation of financial information as well as applicable simplifications were defined for each group. The EU Member States had to implement the provisions of Directive 34 relating to accounting and financial reporting into domestic norms until January 1, 2016. In Poland, the provisions of Directive 34 were implemented into domestic accounting norms specified in the Polish Accounting Act on a gradual basis. On July 11, 2014, the Polish Parliament adopted an amendment to the Act, introducing the Directive's solutions for micro-undertakings and on July 23, 2015, for the remaining undertakings. The aim of this paper is to present Polish solutions relating to financial reporting after the implementation of Directive 34 and the results of the survey conducted among accountants regarding the evaluation of the implemented simplifications for micro and small undertakings.

Keywords: accounting standards, financial reporting, financial statement, simplification

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Authors: Ahmad Shahin, Walid Moudani, Ali Bekraki

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This research aims at presenting a predictive data mining model to handle an accurate diagnosis of acute appendicitis with patients for the purpose of maximizing the health service quality, minimizing morbidity/mortality, and reducing cost. However, acute appendicitis is the most common disease which requires timely accurate diagnosis and needs surgical intervention. Although the treatment of acute appendicitis is simple and straightforward, its diagnosis is still difficult because no single sign, symptom, laboratory or image examination accurately confirms the diagnosis of acute appendicitis in all cases. This contributes in increasing morbidity and negative appendectomy. In this study, the authors propose to generate an accurate model in prediction of patients with acute appendicitis which is based, firstly, on the segmentation technique associated to ABC algorithm to segment the patients; secondly, on applying fuzzy logic to process the massive volume of heterogeneous and noisy data (age, sex, fever, white blood cell, neutrophilia, CRP, urine, ultrasound, CT, appendectomy, etc.) in order to express knowledge and analyze the relationships among data in a comprehensive manner; and thirdly, on applying dynamic programming technique to reduce the number of data attributes. The proposed model is evaluated based on a set of benchmark techniques and even on a set of benchmark classification problems of osteoporosis, diabetes and heart obtained from the UCI data and other data sources.

Keywords: healthcare management, acute appendicitis, data mining, classification, decision tree

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Authors: Ying Ge

Abstract:

Wetlands are one of the essential types of ecosystems in the world. They are of great value to human society thanks to their special ecosystem functions and services, such as protecting biodiversity, adjusting hydrology and climate, providing essential habitats and, products and tourism resources. However, wetlands worldwide are degrading severely due to climate change, accelerated urbanization, and rapid economic development. Both nature and human factors drive wetland change, and the influences are variable from wetland types. Thus, the objectives of this study were to (1) to compare the changes in China’s wetland area during the three decades rapid growth period (1978-2008); (2) to analyze the effects of social economy and environmental factors on wetlands change (area loss and change of wetland types) in China during the high-speed economic development. The socio-economic influencing factors include population, income, education, development of agriculture, industry, infrastructure, wastewater amount, etc. Several statistical methods (canonical correlation analysis, principal component analysis, and regression analysis) were employed to analyze the relationship between socio-economic indicators and wetland area change. This study will determine the relevant driving socio-economic factors on wetland changes, which is of great significance for wetland protection and management.

Keywords: socioeconomic effects, China, wetland change, wetland type

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: classifier ensemble, breast cancer survivability, data mining, SEER

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Authors: A. Nour Eddine, D. Chalet, L. Aixala, P. Chessé, X. Faure, N. Hatat

Abstract:

Thermal power technology such as the TEG (Thermo-Electric Generator) arouses significant attention worldwide for waste heat recovery. Despite the potential benefits of marine application due to the permanent heat sink from sea water, no significant studies on this application were to be found. In this study, a test rig has been designed and built to test the performance of the TEG on engine operating points. The TEG device is built from commercially available materials for the sake of possible economical application. Two types of commercial TEM (thermo electric module) have been studied separately on the test rig. The engine data were extracted from a commercial Diesel engine since it shares the same principle in terms of engine efficiency and exhaust with the marine Diesel engine. An open circuit water cooling system is used to replicate the sea water cold source. The characterization tests showed that the silicium-germanium alloys TEM proved a remarkable reliability on all engine operating points, with no significant deterioration of performance even under sever variation in the hot source conditions. The performance of the bismuth-telluride alloys was 100% better than the first type of TEM but it showed a deterioration in power generation when the air temperature exceeds 300 °C. The temperature distribution on the heat exchange surfaces revealed no useful combination of these two types of TEM with this tube length, since the surface temperature difference between both ends is no more than 10 °C. This study exposed the perspective of use of TEG technology for marine engine exhaust heat recovery. Although the results suggested non-sufficient power generation from the low cost commercial TEM used, it provides valuable information about TEG device optimization, including the design of heat exchanger and the types of thermo-electric materials.

Keywords: internal combustion engine application, Seebeck, thermo-electricity, waste heat recovery

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Authors: Bartosz Kedra, Robert Malkowski

Abstract:

This paper provides description and presentation of laboratory test unit built basing on 150 kVA power frequency converter and Simulink RealTime platform. Assumptions, based on criteria which load and generator types may be simulated using discussed device, are presented, as well as control algorithm structure. As laboratory setup contains transformer with thyristor controlled tap changer, a wider scope of setup capabilities is presented. Information about used communication interface, data maintenance, and storage solution as well as used Simulink real-time features is presented. List and description of all measurements are provided. Potential of laboratory setup modifications is evaluated. For purposes of Rapid Control Prototyping, a dedicated environment was used Simulink RealTime. Therefore, load model Functional Unit Controller is based on a PC computer with I/O cards and Simulink RealTime software. Simulink RealTime was used to create real-time applications directly from Simulink models. In the next step, applications were loaded on a target computer connected to physical devices that provided opportunity to perform Hardware in the Loop (HIL) tests, as well as the mentioned Rapid Control Prototyping process. With Simulink RealTime, Simulink models were extended with I/O cards driver blocks that made automatic generation of real-time applications and performing interactive or automated runs on a dedicated target computer equipped with a real-time kernel, multicore CPU, and I/O cards possible. Results of performed laboratory tests are presented. Different load configurations are described and experimental results are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area and arbitrary active and reactive power regulation basing on defined schedule.

Keywords: MATLAB, power converter, Simulink Real-Time, thyristor-controlled tap changer

Procedia PDF Downloads 323

Authors: Esra Polat

Abstract:

Partial Least Squares Discriminant Analysis (PLSDA) is a statistical method for classification and consists a classical Partial Least Squares Regression (PLSR) in which the dependent variable is a categorical one expressing the class membership of each observation. PLSDA can be applied in many cases when classical discriminant analysis cannot be applied. For example, when the number of observations is low and when the number of independent variables is high. When there are missing values, PLSDA can be applied on the data that is available. Finally, it is adapted when multicollinearity between independent variables is high. The aim of this study is to determine the economic and/or demographic indicators, which are effective in grouping the 28 European Union (EU) member countries and 7 candidate countries (including potential candidates Bosnia and Herzegovina (BiH) and Kosova) by using the data set obtained from database of the World Bank for 2014. Leaving the political issues aside, the analysis is only concerned with the economic and demographic variables that have the potential influence on country’s eligibility for EU entrance. Hence, in this study, both the performance of PLSDA method in classifying the countries correctly to their pre-defined groups (candidate or member) and the differences between the EU countries and candidate countries in terms of these indicators are analyzed. As a result of the PLSDA, the value of percentage correctness of 100 % indicates that overall of the 35 countries is classified correctly. Moreover, the most important variables that determine the statuses of member and candidate countries in terms of economic indicators are identified as 'external balance on goods and services (% GDP)', 'gross domestic savings (% GDP)' and 'gross national expenditure (% GDP)' that means for the 2014 economical structure of countries is the most important determinant of EU membership. Subsequently, the model validated to prove the predictive ability by using the data set for 2015. For prediction sample, %97,14 of the countries are correctly classified. An interesting result is obtained for only BiH, which is still a potential candidate for EU, predicted as a member of EU by using the indicators data set for 2015 as a prediction sample. Although BiH has made a significant transformation from a war-torn country to a semi-functional state, ethnic tensions, nationalistic rhetoric and political disagreements are still evident, which inhibit Bosnian progress towards the EU.

Keywords: classification, demographic indicators, economic indicators, European Union, partial least squares discriminant analysis

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Authors: Bouchemha Amel, Chachoui Takieddine, H. Maalem

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Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution.

Keywords: CFAR, threshold, clutter, distribution, Weibull, detection

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Authors: Muhammad Zafarullah Khan

Abstract:

Agricultural Extension Officers’ (AEOs) competency level in soil and environmental management awareness is important for interacting with farming communities of different types of soil. Questionnaire was developed for all AEOs for data collection to know the present position and needed position of competency on Likert scale from 01-05 by assigning very low (01) and very high (05). Wide gap was found in competency of suitability of various soil types for horticultural and agronomic crops and reclamation of saline soil. We observed that suitability ranking of various soil types for horticultural crops (Diff. = 1.21), agronomic crops (Diff. = 1.20) and soil borne diseases (Diff. = 1.19) were the top three important competencies where training or improvement is needed. To better fill this gap we recommend that professional qualification of AEOs should be enhanced and training opportunities should be provided to them particularly to deal with soil and environmental management awareness. Thus training opportunities may increase their competency and will add highly skilled manpower to the system for sustainable development to protect environment. It is therefore, recommended that AEOs may be provided pre and in service trainings of soil environmental management in order to equip them with a capacity to work with farming community effectively to boost the living standard of farming community and alleviate poverty for environmental protection.

Keywords: professional competency, agricultural extension officers, soil and environmental management awareness, plans implementation

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Authors: Siu Hua Chang, Ayub Md Som, Jagannathan Krishnan

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The kinetics of Cu(II) transport through a bulk liquid membrane with different membrane materials was investigated in this work. Three types of membrane materials were used: Fresh cooking oil, waste cooking oil, and kerosene each of which was mixed with di-2-ethylhexylphosphoric acid (carrier) and tributylphosphate (modifier). Kinetic models derived from the kinetic laws of two consecutive irreversible first-order reactions were used to study the facilitated transport of Cu(II) across the source, membrane, and receiving phases of bulk liquid membrane. It was found that the transport kinetics of Cu(II) across the source phase was not affected by different types of membrane materials but decreased considerably when the membrane materials changed from kerosene, waste cooking oil to fresh cooking oil. The rate constants of Cu(II) removal and recovery processes through the bulk liquid membrane were also determined.

Keywords: transport kinetics, Cu(II), bulk liquid membrane, waste cooking oil

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Authors: Mohammad A. U. Khan, Tariq M. Khan, Yinan Kong

Abstract:

Fingerprint image enhancement is one of the most important step in an automatic fingerprint identification recognition (AFIS) system which directly affects the overall efficiency of AFIS. The conventional fingerprint enhancement like Gabor and Anisotropic filters do fill the gaps in ridge lines but they fail to tackle scar lines. To deal with this problem we are proposing a method for enhancing the ridges and valleys with scar so that true minutia points can be extracted with accuracy. Our results have shown an improved performance in terms of enhancement.

Keywords: fingerprint image enhancement, removing noise, coherence, enhanced diffusion

Procedia PDF Downloads 516