Search results for: neighborhood component analysis

Authors: Suresh Kumar Bandooni, Mirana Laishram

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The Mid Himalaya of Garhwal Himalaya in Uttarakhand (India) has a complex Physiographic features withdiversified climatic conditions and therefore it is suspect to environmental vulnerability. Thenatural disasters and also anthropogenic activities accelerate the rate of environmental vulnerability. To analyse the environmental vulnerability, we have used geoinformatics technologies and numerical models and it is adoptedby using Spatial Principal Component Analysis (SPCA). The model consist of many factors such as slope, landuse/landcover, soil, forest fire risk, landslide susceptibility zone, human population density and vegetation index. From this model, the environmental vulnerability integrated index (EVSI) is calculated for Pasol Gad Watershed of Garhwal Himalaya for the years 1987, 2000, and 2013 and the Vulnerability is classified into five levelsi.e. Very low, low, medium, high and very highby means of cluster principle. The resultsforeco-environmental vulnerability distribution in study area shows that medium, high and very high levels are dominating in the area and it is mainly caused by the anthropogenic activities and natural disasters. Therefore, proper management forconservation of resources is utmost necessity of present century. It is strongly believed that participation at community level along with social worker, institutions and Non-governmental organization (NGOs) have become a must to conserve and protect the environment.

Keywords: eco-environment vulnerability, spatial principal component analysis, remote sensing, geographic information system, institutions, Himalaya

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Authors: Yuliia Skrynnik

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This research focuses on the interaction of verbal, non-verbal, and super-verbal communicative components used by the speaker changing social roles in the marketing discourse. The changing/performing of social roles is implemented through communicative strategies and tactics, the structural, semantic, and linguo-pragmatic means of which are characterized by specific features and differ for the performance of either a role of a supplier or a customer. Communication within the marketing discourse is characterized by symmetrical roles’ relation between communicative opponents. The strategy of a supplier’s social role realization and the strategy of a customer’s role realization influence the discursive personality's linguistic repertoire in the marketing discourse. This study takes into account that one person can be both a supplier and a customer under different circumstances, thus, exploring the one individual who can be both a supplier and a customer. Cooperative and non-cooperative tactics are the instruments for the implementation of these strategies. In the marketing discourse, verbal and non-verbal behaviour of the speaker performing a customer’s social role is highly informative for speakers who perform the role of a supplier. The research methods include discourse, context-situational, pragmalinguistic, pragmasemantic analyses, the method of non-verbal components analysis. The methodology of the study includes 5 steps: 1) defining the configurations of speakers’ social roles on the selected material; 2) establishing the type of the discourse (marketing discourse); 3) describing the specific features of a discursive personality as a subject of the communication in the process of social roles realization; 4) selecting the strategies and tactics which direct the interaction in different roles configurations; 5) characterizing the structural, semantic and pragmatic features of the strategies and tactics realization, including the analysis of interaction between verbal and non-verbal components of communication. In the marketing discourse, non-verbal behaviour is usually spontaneous but not purposeful. Thus, the adequate decoding of a partner’s non-verbal behavior provides more opportunities both for the supplier and the customer. Super-verbal characteristics in the marketing discourse are crucial in defining the opponent's social status and social role at the initial stage of interaction. The research provides the scenario of stereotypical situations of the play of a supplier and a customer. The performed analysis has perspectives for further research connected with the study of discursive variativity of speakers' verbal and non-verbal behaviour considering the intercultural factor influencing the process of performing the social roles in the marketing discourse; and the formation of the methods for the scenario construction of non-stereotypical situations of social roles realization/change in the marketing discourse.

Keywords: discursive personality, marketing discourse, non-verbal component of communication, social role, strategy, super-verbal component of communication, tactic, verbal component of communication

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Authors: T. Vijayashree, A. Gopal

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The aim of the work is to classify and authenticate medicinal plant materials and herbs widely used for Indian herbal medicinal preparation. The quality and authenticity of these raw materials are to be ensured for the preparation of herbal medicines. These raw materials are to be carefully screened, analyzed and documented due to mistaken of look-alike materials which do not have medicinal characteristics.

Keywords: authenticity, standardization, principal component analysis, imaging processing, signal processing

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Authors: Ebrahim Safarian, Kadir Bilen, Akif Ceviz

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The turbocharger and turbocharging have been the inherent component of diesel engines, so that critical parameters of such engines, as BSFC(Brake Specific Fuel Consumption) or thermal efficiency, fuel consumption, BMEP(Brake Mean Effective Pressure), the power density output and emission level have been improved extensively. In general, the turbocharger can be considered as the most complex component of diesel engines, because it has closely interrelated turbomachinery concepts of the turbines and the compressors to thermodynamic fundamentals of internal combustion engines and stress analysis of all components. In this paper, a waste gate for a conventional single stage radial turbine is investigated by consideration of turbochargers operation constrains and engine operation conditions, without any detail designs in the turbine and the compressor. Amount of opening waste gate which extended between the ranges of full opened and closed valve, is demonstrated by limiting compressor boost pressure ratio. Obtaining of an optimum point by regard above mentioned items is surveyed by three linked meanline modeling programs together which consist of Turbomatch®, Compal®, Rital®madules in concepts NREC® respectively.

Keywords: turbocharger, wastegate, diesel engine, concept NREC programs

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Authors: Ranjit Singh

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Body fat % lean body mass and body type play vital role in sports performance. A sports person who is having optional body composition can show its performance flawlessly whereas other who is not physical fit may be more prone to injury. Competitive swimming is an association of plethora of aspects like morphological, physiological, biochemical, biomechanical and psychological. The primary key of the present research is to examine the correlation among selected morphological dimensions such as height, weight, body fat%, lean body mass, somatotype and swimming performance. The present study also focused to investigate by potential deficiencies if any and to find out remedial measures to curb the training stresses. Thirty (age group 10-14 years) swimmers undergoing training under skilled and professional coaches were selected in the present study. The morphological variables and performance criterion like 50 meter swimming time and speed were calculated by using standard training methodology. Correlation coefficient among body composition, somatotype and performance variables were assessed by using standard statistical package SPSS. Mean height, weight, fat% and lean body mass of the present group is 150.97±8.68 cm, 44.0±9.34 kg., 15.97±4.42 % and 37.10±8.77 kg respectively. Somatotype of the young swimmers of this research is revealed ectomorphic mesomorph. The analysis of the results Illustrated that swimming performance is significantly correlated (p<0.05) with height, body weight, mesomorphoic component and lean body mass. Body fat is significantly and negatively correlated (p<0.05) with mesomorphic component, lean body mass and swimming speed. From this present study, it can be concluded that along with techniques and tactics other the physical attributes also play significant role in swimming performance which can help the swimmers to excel in higher level of competition and swimmers having improved morphological qualities can ultimately perform well.

Keywords: body fat, mass, mesomorphic component, somatotype

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Authors: Elizabeta Sivevska, Sunchica Petrovska, Vaska Antevska, Lidija Todorovska, Sanja Manchevska, Beti Dejanova, Ivanka Karagjozova, Jasmina Pluncevic Gligoroska

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Introduction: Body composition plays an important role in the selection of young soccer players and it is associated with their successful performance. The most commonly used model of body composition divides the body into two compartments: fat components and fat-free mass (muscular and bone components). The aims of the study were to determine the body composition parameters of young male soccer players and to show the differences in age groups. Material and methods: A sample of 52 young male soccer players, with an age span from 9 to 14 years were divided into two groups according to the age (group 1 aged 9 to 12 years and group 2 aged 12 to 14 years). Anthropometric measurements were taken according to the method of Mateigka. The following measurements were made: body weight, body height, circumferences (arm, forearm, thigh and calf), diameters (elbow, knee, wrist, ankle) and skinfold thickness (biceps, triceps, thigh, leg, chest, abdomen). The measurements were used in Mateigka’s equations. Results: Body mass components were analyzed as absolute values (in kilograms) and as percentage values: the muscular component (MC kg and MC%), the bone component (BCkg and BC%) and the body fat (BFkg and BF%). The group up to 12 years showed the following mean values of the analyzed parameters: MM=21.5kg; MM%=46.3%; BC=8.1kg; BC%=19.1%; BF= 6.3kg; BF%= 15.7%. The second group aged 12-14 year had mean values of body composition parameters as follows: MM=25.6 kg; MM%=48.2%; BC = 11.4 kg; BC%=21.6%; BF= 8.5 kg; BF%= 14. 7%. Conclusions: The young soccer players aged 12 up to 14 years who are in the pre-pubertal phase of growth and development had higher bone component (p<0.05) compared to younger players. There is no significant difference in muscular and fat body component between the two groups of young soccer players.

Keywords: body composition, young soccer players, body fat, fat-free mass

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Aron Miranda Burgos, Ergon Cugler de Moraes Silva

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In the present article, it is observed that the constant advancement of issues related to misinformation impacts the guarantee of the public policy cycle. Thus, it is found that the dissemination of false information has a direct influence on each of the component stages of this cycle. Therefore, in order to maintain scientific and theoretical credibility in the qualitative analysis process, it was necessary to logically interpose the concepts of firehosing of falsehood, fake news, public policy cycle, as well as using the epistemological and pragmatic mechanism at the intersection of such academic concepts, such as the scientific method. It was found, through the analysis of official documents and public notes, how the multiple theoretical perspectives evidence the commitment of the provision and elaboration of public policies, verifying the way in which the fake news impact each part of the process in this atmosphere.

Keywords: firehosing of falsehood, governance, misinformation, post-truth

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Authors: Shinji Kawakura, Ryosuke Shibasaki

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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis

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Authors: Amol M. Jadhav, Sharad S. Chudhari, S. S. Khedkar

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This review presents a through survey of research paper work on the experimental analysis, FEM Analysis & simulation of the metal spinning process. In this literature survey all the papers being taken from Elsevier publication and most of the from journal of material processing technology. In a last two decade or so, metal spinning process gradually used as chip less formation for the production of engineering component in a small to medium batch quantities. The review aims to provide include into the experimentation, FEM analysis of various components, simulation of metal spinning process and act as guide for research working on metal spinning processes. The review of existing work has several gaps in current knowledge of metal spinning processes. The evaluation of experiment is thickness strain, the spinning force, the twisting angle, the surface roughness of the conventional & shear metal spinning process; the evaluation of FEM of metal spinning to path definition with sufficient fine mesh to capture behavior of work piece; The evaluation of feed rate of roller, direction of roller,& type of roller stimulated. The metal spinning process has the more flexible to produce a wider range of product shape & to form more challenge material.

Keywords: metal spinning, FEM analysis, simulation of metal spinning, mechanical engineering

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: Sireen Irsheid

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Despite concerted efforts to improve education attainment with progress in recent years, student achievement and attainment remain among the most significant challenges for school districts across the United States. Many scholars have argued that students who do not complete high school do not drop out of school voluntarily but are ‘pushed out’ of schools through multiple mechanisms related to structural and socioeconomic barriers, behavioral health challenges, pedagogical practices, and administrative procedures. Extant literature has shown that living in historically disadvantaged neighborhoods or attending under-resourced schools exacerbates student-level risk factors for grade retention and school pushout. Most efforts to respond to the school pushout phenomenon have focused on individual characteristics of students, with relatively little attention to addressing these multiple system-level characteristics related to perpetuating inequities. This study is built on a growing body of social justice-oriented research concerned with the systemic influences that shape the experiences and mental health challenges of young people. Specifically, this study examined how young people who have been experiencing education inequities make meaning and navigate the structural factors related to neighborhood and school disinvestment and access to resources and supports, and their risk for school pushout. Furthermore, schools as political, cultural, and ideologically reproductive spaces often serve as sites of resistance and can support students who are impacted by educational inequity. Study findings provide education, neighborhood, school psychology, social work practice, and policy considerations.

Keywords: education policy, mental health, school prison nexus, school pushout, structural trauma

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Authors: Yutae Lee

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In this paper, we consider the performance and availability of a redundancy model. The redundancy model is a form of resilience that ensures service availability in the event of component failure. This paper considers a 2N redundancy model. In the model there are at most one active service unit and at most one standby service unit. The active one is providing the service while the standby is prepared to take over the active role when the active fails. We design our analysis model using Stochastic Reward Nets, and then evaluate the performance and availability of 2N redundancy model using Stochastic Petri Net Package (SPNP).

Keywords: availability, performance, stochastic reward net, 2N redundancy

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Authors: Yogesh Bacchaw, Ashish Dabade

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Nowadays oral health is raising concern in society. Acid producing microorganisms changes the oral pH and creates a favorable environment for microbial growth. This growth not only promotes dental decay but also bad breath. Generally Recognized As Safe (GRAS) listed component was incorporated in chewing gum as an antimicrobial agent. The chewing gum produced exhibited up to 9 hours of antimicrobial activity against oral microflora. The toxicity of GRAS component per RACC value of chewing gum was negligible as compared to actual toxicity level of GRAS component. The antibacterial efficiency of chewing gum was tested by using total plate count (TPC) and colony forming unit (CFU). Nine hours were required to microflora to reach TPC/CFU of before chewing gum consumption. This chewing gum not only provides mouth freshening activity but also helps in lowering dental decay, bad breath, and enamel whitening.

Keywords: colony forming unit (CFU), chewing gum, generally recognized as safe (GRAS), microbial growth, microorganisms, oral health, RACC, total plate count (TPC), antimicrobial agent, enamel whitening, oral pH

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Authors: G. Punithavathy

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The research proposes a statistical model for the distributed acoustic sensor interrogation units that broadcast a laser pulse into the fiber optics, where interactions within the fiber determine the localized acoustic energy that causes light reflections known as backscatter. The backscattered signal's amplitude and phase can be calculated using explicit equations. The created model makes amplitude signal spectrum and autocorrelation predictions that are confirmed by experimental findings. Phase signal characteristics that are useful for researching optical time domain reflectometry (OTDR) system sensing applications are provided and examined, showing good agreement with the experiment. The experiment was successfully done with the use of Python coding. In this research, we can analyze the entire distributed acoustic sensing (DAS) component parts separately. This model assumes that the fiber is in a static condition, meaning that there is no external force or vibration applied to the cable, that means no external acoustic disturbances present. The backscattered signal consists of a random noise component, which is caused by the intrinsic imperfections of the fiber, and a coherent component, which is due to the laser pulse interacting with the fiber.

Keywords: distributed acoustic sensing, optical fiber devices, optical time domain reflectometry, Rayleigh scattering

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Authors: Thanatip Lerttanaporn, Tuanjai Somboonwiwat, Charoenchai Khompatraporn

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The automotive parts industry is one of the vital sectors in Thai economy and now is facing a greater competition from ASEAN Economic Community (AEC). This article identifies important factors that impact the competitiveness of Thai automotive parts industry. There are eight groups of factors with a total of 58 factors. Due to a variety of factors, the Exploratory Factor Analysis and Principle Component Analysis have been applied to classify factors into groups or principle components. The results show that there are 15 groups and four of them are critical, covering 80% of important value. These four critical groups are then used to formulate strategies to improve the competitiveness of the Thai automotive parts industry.

Keywords: factor analysis, Thai automotive parts, principle components, exploratory factor, ASEAN economic community

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Authors: Varangkana Thaotumpitak, Jarukorn Sripradite, Saharuetai Jeamsripong

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Environmental contamination from wastewater discharges originated from anthropogenic activities introduces the accumulation of enteropathogenic bacteria in aquatic animals, especially in oysters, and in shellfish harvesting areas. The consumption of raw or partially cooked oysters can be a risk for seafood-borne diseases in human. This study aimed to evaluate the relationship between the presence of Salmonella in oyster meat samples, and environmental factors (ambient air temperature, relative humidity, gust wind speed, average wind speed, tidal condition, precipitation and season) by using the principal component analysis (PCA). One hundred and forty-four oyster meat samples were collected from four oyster harvesting areas in Phang Nga province, Thailand from March 2016 to February 2017. The prevalence of Salmonella of each site was ranged from 25.0-36.11% in oyster meat. The results of PCA showed that ambient air temperature, relative humidity, and precipitation were main factors correlated with Salmonella detection in these oysters. Positive relationship was observed between positive Salmonella in the oysters and relative humidity (PC1=0.413) and precipitation (PC1=0.607), while the negative association was found between ambient air temperature (PC1=0.338) and the presence of Salmonella in oyster samples. These results suggested that lower temperature and higher precipitation and higher relative humidity will possibly effect on Salmonella contamination of oyster meat. During the high risk period, harvesting of oysters should be prohibited to reduce pathogenic bacteria contamination and to minimize a hazard of humans from Salmonellosis.

Keywords: oyster, Phang Nga Bay, principal component analysis, Salmonella

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Authors: Giselle Tran, Ralitza Parina, Phuong T. Nguyen

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Background/Aims: Pancreatic cysts (PC) have recently become an increasingly common entity, often diagnosed as incidental findings on cross-sectional imaging. Clinically, management of the lesions is difficult because of uncertainties in their potential for malignant degeneration. Prior series have reported that carcinoembryonic antigen (CEA), a biomarker collected from cyst fluid aspiration, has a high diagnostic accuracy for discriminating between mucinous and non-mucinous lesions, at the patient’s initial presentation. To the author’s best knowledge, no prior studies have reported PC CEA levels obtained from endoscopic ultrasound fine-needle aspiration (EUS-FNA) over years of serial EUS surveillance imaging. Methods: We report a consecutive retrospective series of 624 patients who underwent EUS evaluation for a PC between 11/20/2009 and 11/13/2018. Of these patients, 401 patients had CEA values obtained at the point of entry. Of these, 157 patients had two or more CEA values obtained over the course of their EUS surveillance. Of the 157 patients (96 F, 61 M; mean age 68 [range, 62-76]), the mean interval of EUS follow-up was 29.7 months [3.5-128]. The mean number of EUS procedures was 3 [2-7]. To assess CEA value fluctuations, we defined an appreciable increase in CEA as "spikes" – two-times increase in CEA on a subsequent EUS-FNA of the same cyst, with the second CEA value being greater than 1000 ng/mL. Using this definition, cysts with a spike in CEA were compared to those without a spike in a bivariate analysis to determine if a CEA spike is associated with poorer outcomes and the presence of high-risk features. Results: Of the 157 patients analyzed, 29 had a spike in CEA. Of these 29 patients, 5 had a cyst with size increase >0.5cm (p=0.93); 2 had a large cyst, >3cm (p=0.77); 1 had a cyst that developed a new solid component (p=0.03); 7 had a cyst with a solid component at any time during surveillance (p=0.08); 21 had a complex cyst (p=0.34); 4 had a cyst categorized as "Statistically Higher Risk" based on molecular analysis (p=0.11); and 0 underwent surgical resection (p=0.28). Conclusion: With serial EUS imaging in the surveillance of PC, an increase in CEA level defined as a spike did not predict poorer outcomes. Most notably, a spike in CEA did not correlate with the number of patients sent to surgery or patients with an appreciable increase in cyst size. A spike in CEA did not correlate with the development of a solid nodule within the PC nor progression on molecular analysis. Future studies should focus on the selected use of CEA analysis when patients undergo EUS surveillance evaluation for PCs.

Keywords: carcinoembryonic antigen (CEA), endoscopic ultrasound (EUS), fine-needle aspiration (FNA), pancreatic cyst, spike

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Authors: Mouna Mesbahi, M. Loutfi Benkhedir

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In CZTS films solar cell, the preferable reaction between Cu and sulfur vapor was likely to be induced by out diffusion of the bottom Cu component to the surface; this would lead to inhomogeneous distribution of the Cu component to form the Cu2SnS3 secondary phase and formation of many voids and crevices in the resulting CZTS film; which is also the cause of the decline in performance. In this work we study the electronic and optical properties of Cu2SnS3. For this purpose we used the Wien2k code based on the theory of density functional theory (DFT) with the modified Becke-Johnson exchange potential mBJ and the Hubbard potential individually or combined. We have found an energy gap 0.92 eV. The results are in good agreement with experimental results.

Keywords: Cu2SnS3, DFT, electronic and optical properties, mBJ+U, WIEN2K

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, S. Caglar Aksezer

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Since the age of industrialization, maintenance has always been a very crucial element for all kinds of factories and plants. With today’s increasingly developing technology, the system structure of such facilities has become more complicated, and even a small operational disruption may return huge losses in profits for the companies. In order to reduce these costs, effective maintenance planning is crucial, but at the same time, it is a difficult task because of the complexity of systems. The most important aspect of correct maintenance planning is to understand the structure of the system, not to ignore the dependencies among the components and as a result, to model the system correctly. In this way, it will be better to understand which component improves the system more when it is maintained. Undoubtedly, proactive maintenance at a scheduled time reduces costs because the scheduled maintenance prohibits high losses in profits. But the necessity of corrective maintenance, which directly affects the situation of the system and provides direct intervention when the system fails, should not be ignored. When a fault occurs in the system, if the problem is not solved immediately and proactive maintenance time is awaited, this may result in increased costs. This study proposes various maintenance methods with different efficiency measures under corrective maintenance strategy on a subsystem of a thermal power plant. To model the dependencies between the components, dynamic Bayesian Network approach is employed. The proposed maintenance methods aim to minimize the total maintenance cost in a planning horizon, as well as to find the most appropriate component to be attacked on, which improves the system reliability utmost. Performances of the methods are compared under corrective maintenance strategy. Furthermore, sensitivity analysis is also applied under different cost values. Results show that all fault effect methods perform better than the replacement effect methods and this conclusion is also valid under different downtime cost values.

Keywords: dynamic Bayesian networks, maintenance, multi-component systems, reliability

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Authors: Mohamed Hrouda

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The Principal Component Analysis (PCA) was performed on a dataset comprising 41 biomarker concentrations from twenty-three core source rocks samples and seven oil samples from different location, with the objective of establishing the major sources of variance within the steranes, tricyclic terpanes, hopanes, and triaromatic steroid. This type of analysis can be used as an aid when deciding which molecular biomarker maturity, source facies or depositional environment parameters should be plotted, because the principal component loadings plots tend to extract the biomarker variables related to maturity, source facies or depositional environment controls. Facies characterization of the source rock samples separate the Silurian and Devonian source rock samples into three groups. Maturity evaluation of source rock samples based on biomarker and aromatic hydrocarbon distributions indicates that not all the samples are strongly affected by maturity, the Upper Devonian samples from wells located in the northern part of the basin are immature, whereas the other samples which have been selected from the Lower Silurian are mature and have reached the main stage of the oil window, the Lower Silurian source rock strata revealed a trend of increasing maturity towards the south and southwestern part of Ghadames Basin. Most of the facies-based parameters employed in this project using biomarker distributions clearly separate the oil samples into three groups. Group I contain oil samples from wells within Al-Wafa oil field Located in the south western part of the basin, Group II contains oil samples collected from Al-Hamada oil field complex in the south and the third group contains oil samples collected from oil fields located in the north

Keywords: Ghadamis basin, geochemistry, silurian, devonian

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Authors: Zoran Šverko, Saša Vlahinić, Nino Stojković, Ivan Markovinović

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In this article, the classification of target letters is performed using data from the EEG P300 Speller paradigm. Neural networks trained with the results of dynamic connectivity analysis between different brain regions are used for classification. Dynamic connectivity analysis is based on the adaptive window size and the imaginary part of the complex Pearson correlation coefficient. Brain dynamics are analysed using the relative intersection of confidence intervals for the imaginary component of the complex Pearson correlation coefficient method (RICI-imCPCC). The RICI-imCPCC method overcomes the shortcomings of currently used dynamical connectivity analysis methods, such as the low reliability and low temporal precision for short connectivity intervals encountered in constant sliding window analysis with wide window size and the high susceptibility to noise encountered in constant sliding window analysis with narrow window size. This method overcomes these shortcomings by dynamically adjusting the window size using the RICI rule. This method extracts information about brain connections for each time sample. Seventy percent of the extracted brain connectivity information is used for training and thirty percent for validation. Classification of the target word is also done and based on the same analysis method. As far as we know, through this research, we have shown for the first time that dynamic connectivity can be used as a parameter for classifying EEG signals.

Keywords: dynamic connectivity analysis, EEG, neural networks, Pearson correlation coefficients

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Authors: Zain Ul Hassan, Muhammad Zain Ul Abadin, Muhammad Zubair Khan

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Unmanned aerial vehicles (UAVs) have now become of predominant importance for various operations, and an immense amount of work is going on in this specific category. The structural stability and life of these UAVs is key factor that should be considered while deploying them to different intelligent operations as their failure leads to loss of sensitive real-time data and cost. This paper presents an applied research on the development of a structural health monitoring system for a UAV designed and fabricated by deploying modular approach. Firstly, a modular UAV has been designed which allows to dismantle and to reassemble the components of the UAV without effecting the whole assembly of UAV. This novel approach makes the vehicle very sustainable and decreases its maintenance cost to a significant value by making possible to replace only the part leading to failure. Then the SHM for the designed architecture of the UAV had been specified as a combination of wings integrated with strain gauges, on-board data logger, bridge circuitry and the ground station. For the research purpose sensors have only been attached to the wings being the most load bearing part and as per analysis was done on ANSYS. On the basis of analysis of the load time spectrum obtained by the data logger during flight, fatigue life of the respective component has been predicted using fracture mechanics techniques of Rain Flow Method and Miner’s Rule. Thus allowing us to monitor the health of a specified component time to time aiding to avoid any failure.

Keywords: fracture mechanics, rain flow method, structural health monitoring system, unmanned aerial vehicle

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Authors: Mohammad Taghi Karimi, Maryam Hasan Zahraee

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Background: Low back pain (LBP) is a common health and socioeconomic problem, especially the chronic one. The joint contact force is an important parameter during walking which increases the incidence of injury and degenerative joint disease. To our best knowledge, there are not enough evidences in literature on the muscular forces and joint contact forces in subjects with low back pain. Purpose: The main hypothesis associated with this research was that joint contact force of L4/L5 of non-specific chronic low back pain subjects was the same as that of normal. Therefore, the aim of this study was to determine the joint contact force difference between non-specific chronic low back pain and normal subjects. Method: This was an experimental-comparative study. 20 normal subjects and 20 non-specific chronic low back pain patients were recruited in this study. Qualysis motion analysis system and a Kistler force plate were used to collect the motions and the force applied on the leg, respectively. OpenSimm software used to determine joint contact force and muscle forces in this study. Some parameters such as force applied on the legs (pelvis), kinematic of hip and pelvic, peaks of muscles, force of trunk musculature and joint contact force of L5/S1 were used for further analysis. Differences between mean values of all data were measured using two-sample t-test among the subjects. Results: The force produced by Semitendinosus, Biceps Femoris, and Adductor muscles were significantly different between low back pain and normal subjects. Moreover, the mean value of breaking component of the force of the knee joint increased significantly in low back pain subjects, besides a significant decrease in mean value of the vertical component of joint reaction force compared to the normal ones. Conclusions: The forces produced by the trunk and pelvic muscles, and joint contact forces differ significantly between low back pain and normal subjects. It seems that those with non-specific chronic low back pain use trunk muscles more than normal subjects to stabilize the pelvic during walking.

Keywords: low back pain, joint contact force, kinetic, muscle force

Procedia PDF Downloads 217

Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

Procedia PDF Downloads 333

Authors: Seung Yeon Son

Abstract:

In today’s rapidly changing and increasingly complex environment, organizations have relied on their members’ positive attitude toward their employers. In particular, employees’ organizational commitment (primarily, the effective component) has been recognized as an essential component of organizational functioning and success. Hence, identifying the determinants of effective commitment is one of the most important research issues. This study tested the influence of leader-member exchange (LMX) and exchange ideology on employee’s effective commitment. In addition, the interactive effect of LMX and exchange ideology was examined. Data from 198 members of the Korean military supports each of the hypotheses. Lastly, implications for research and directions for future research are discussed.

Keywords: affective commitment, exchange ideology, leader-member exchange, commitment

Procedia PDF Downloads 405

Authors: A. Moawad, K. C. Yao, A. Mansour, R. Gautier

Abstract:

The detecting of an occupied frequency band is a major issue in cognitive radio systems. The detection process becomes difficult if the signal occupying the band of interest has faded amplitude due to multipath effects. These effects make it hard for an occupying user to be detected. This work mitigates the missed-detection problem in the context of cognitive radio in frequency-selective fading channel by proposing blind channel estimation method that is based on scattering transform. By initially applying conventional energy detection, the missed-detection probability is evaluated, and if it is greater than or equal to 50%, channel estimation is applied on the received signal followed by channel equalization to reduce the channel effects. In the proposed channel estimator, we modify the Morlet wavelet by using its first derivative for better frequency resolution. A mathematical description of the modified function and its frequency resolution is formulated in this work. The improved frequency resolution is required to follow the spectral variation of the channel. The channel estimation error is evaluated in the mean-square sense for different channel settings, and energy detection is applied to the equalized received signal. The simulation results show improvement in reducing the missed-detection probability as compared to the detection based on principal component analysis. This improvement is achieved at the expense of increased estimator complexity, which depends on the number of wavelet filters as related to the channel taps. Also, the detection performance shows an improvement in detection probability for low signal-to-noise scenarios over principal component analysis- based energy detection.

Keywords: channel estimation, cognitive radio, scattering transform, spectrum sensing

Procedia PDF Downloads 177

Authors: Bliss Singhal

Abstract:

Epilepsy is a prevalent neurological disorder affecting approximately 50 million individuals worldwide and 1.2 million Americans. There exist millions of pediatric patients with intractable epilepsy, a condition in which seizures fail to come under control. The occurrence of seizures can result in physical injury, disorientation, unconsciousness, and additional symptoms that could impede children's ability to participate in everyday tasks. Predicting seizures can help parents and healthcare providers take precautions, prevent risky situations, and mentally prepare children to minimize anxiety and nervousness associated with the uncertainty of a seizure. This research proposes a comprehensive framework to predict seizures in pediatric patients by evaluating machine learning algorithms on unimodal neuroimaging data consisting of electroencephalogram signals. The bandpass filtering and independent component analysis proved to be effective in reducing the noise and artifacts from the dataset. Various machine learning algorithms’ performance is evaluated on important metrics such as accuracy, precision, specificity, sensitivity, F1 score and MCC. The results show that the deep learning algorithms are more successful in predicting seizures than logistic Regression, and k nearest neighbors. The recurrent neural network (RNN) gave the highest precision and F1 Score, long short-term memory (LSTM) outperformed RNN in accuracy and convolutional neural network (CNN) resulted in the highest Specificity. This research has significant implications for healthcare providers in proactively managing seizure occurrence in pediatric patients, potentially transforming clinical practices, and improving pediatric care.

Keywords: intractable epilepsy, seizure, deep learning, prediction, electroencephalogram channels

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Authors: T. D. Tran, H. Schlegel, R. Neugebauer

Abstract:

Ball screws are an important component in machine tools. In mechatronic systems and machine tools, a ball screw has to work usually at a high speed. Otherwise the axial compliance of the ball screw, in combination with the inertia of the slide, the motor, the coupling and the screw, will cause an oscillation resonance, which limits the systems bandwidth and consequently influences performance of the motion controller. In this paper, the modal analysis method by measuring and analysing the vibrating parameters of the ball screw system to determine the dynamic characteristic of existing structures is used. On the one hand, the results of this study were obtained by the theoretical analysis and the modal testing of a ball screw system test station with the help of an impact hammer, respectively using excitation by motor. The experimental study showed oscillating forms of the ball screw for each frequency and obtained eigenfrequencies of the ball screw system. On the other hand, in this research a simulation with the help of the numerical modal analysis in order to analyse the oscillation and to find the eigenfrequencies of the ball screw system is used. Furthermore, the model order reduction by modal reduction and also according to Guyan is carried out. On the basis of these results a secure and also rapid commissioning of the control loops with regard to operating in their optimal function is targeted.

Keywords: modal analysis, ball screw, controller system, machine tools

Procedia PDF Downloads 436