Search results for: auditory processing delays

Authors: Joanna Wielochowska, Aneta Wielochowska

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Whilst the relationship between scientific areas such as cognitive psychology, neurobiology and philosophy of mind has been emphasized in recent decades of scientific research, concepts and discoveries made in both fields overlap and complement each other in their quest for answers to similar questions. The object of the following case study is to describe, analyze and illustrate the nature and characteristics of a certain cognitive experience which appears to display features of synaesthesia, or rather high-level synaesthesia (ideasthesia). The following research has been conducted on the subject of two authors, monozygotic twins (both polysynaesthetes) experiencing involuntary associations of identical nature. Authors made attempts to identify which cognitive and conceptual dependencies may guide this experience. Operating on self-introduced nomenclature, the described phenomenon- multi-dimensional processing of textual and visual information- aims to define a relationship that involuntarily and immediately couples the content introduced by means of text or image a sensation of appearing in a certain place in the mind’s eye. More precisely: (I) defining a concept introduced by means of textual content during activity of reading or writing, or (II) defining a concept introduced by means of visual content during activity of looking at image(s) with simultaneous sensation of being allocated to a given place in the mind’s eye. A place can be then defined as a cognitive representation of a certain concept. During the activity of processing information, a person has an immediate and involuntary feel of appearing in a certain place themselves, just like a character of a story, ‘observing’ a venue or a scenery from one or more perspectives and angles. That forms a unique and unified experience, constituting a background mental landscape of text or image being looked at. We came to a conclusion that semantic allocations to a given place could be divided and classified into the categories and subcategories and are naturally linked with an individual’s semantic knowledge-base. A place can be defined as a representation one’s unique idea of a given concept that has been established in their semantic knowledge base. A multi-level structure of selectivity of places in the mind’s eye, as a reaction to a given information (one stimuli), draws comparisons to structures and patterns found in botany. Double-flowered varieties of flowers and a whorl system (arrangement) which is characteristic to components of some flower species were given as an illustrative example. A composition of petals that fan out from one single point and wrap around a stem inspired an idea that, just like in nature, in philosophy of mind there are patterns driven by the logic specific to a given phenomenon. The study intertwines terms perceived through the philosophical lens, such as definition of meaning, subjectivity of meaning, mental atmosphere of places, and others. Analysis of this rare experience aims to contribute to constantly developing theoretical framework of the philosophy of mind and influence the way human semantic knowledge base and processing given content in terms of distinguishing between information and meaning is researched.

Keywords: information and meaning, information processing, mental atmosphere of places, patterns in nature, philosophy of mind, selectivity, semantic knowledge base, senses, synaesthesia

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Authors: Tobias Schmithuesen, Johannes Henrich Schleifenbaum

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The additive manufacturing process laser powder bed fusion offers many advantages over conventional manufacturing processes. For example, almost any complex part can be produced, such as topologically optimized lightweight parts, which would be inconceivable with conventional manufacturing processes. A major challenge posed by the LPBF process, however, is, in most cases, the need to use and remove support structures on critically inclined part surfaces (α < 45 ° regarding substrate plate). These are mainly used for dimensionally accurate mapping of part contours and to reduce distortion by absorbing process-related internal stresses. Furthermore, they serve to transfer the process heat to the substrate plate and are, therefore, indispensable for the LPBF process. A major challenge for the economical use of the LPBF process in industrial process chains is currently still the high manual effort involved in removing support structures. According to the state of the art (SoA), the parts are usually treated by simple hand tools (e.g., pliers, chisels) or by machining (e.g., milling, turning). New automatable approaches are the removal of support structures by means of wet chemical ablation and thermal deburring. According to the state of the art, the support structures are essentially adapted to the LPBF process and not to potential post-processing steps. The aim of this study is the determination of support structure designs that are adapted to the mentioned post-processing approaches. In the first step, the essential boundary conditions for complete removal by means of the respective approaches are identified. Afterward, a representative demonstrator part with various macroscopic support structure designs will be LPBF-manufactured and tested with regard to a complete powder and support removability. Finally, based on the results, potentially suitable support structure designs for the respective approaches will be derived. The investigations are carried out on the example of the aluminum alloy AlSi10Mg.

Keywords: additive manufacturing, laser powder bed fusion, laser beam melting, selective laser melting, post processing, tool-free, wet chemical ablation, thermal deburring, aluminum alloy, AlSi10Mg

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Authors: Shubhangi Salokhe

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Agriculture encompasses crop and livestock production, forestry, and fisheries for food and non-food products. Farmers combine land, water, commercial inputs, labor, and their management skills into practices and systems that produce food and fibre. Harvesting of agricultural produce is either followed by the processing of fresh produce or storage for later consumption. All these activities result in a vast generation of waste in terms of crop residue or food waste. So, a large amount of agricultural waste is produced every year. Waste arising from food and agricultural sectors has the potential for vast applications. So, agricultural waste management is an essential component of sustainable agriculture. The major portion of the waste comes from the residues of crops on farms, food processing, livestock, aquaculture, and agro-industry waste. Therefore, management of these agricultural wastes is an important task, and it requires robust strategic planning. It can contribute to three pillars of sustainable agriculture development. It protects the environment (environmental pillar), enhances the livelihoods of farmers (economic pillar), and can contribute to increasing the sustainability of the agricultural sector (social pillar). This paper addresses the essential technological aspects, possible solutions, and sound policy concerns to accomplish long-term way out of agriculture waste management and to minimize the negative impact of waste on the environment. The author has developed a sustainable agriculture waste management model for improving the sustainability of agriculture.

Keywords: agriculture, development, management, waste

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Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng

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Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).

Keywords: motion detection, motion tracking, trajectory analysis, video surveillance

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Authors: Mia I. Allen, Bernard N. Johnson, Gagan Deep, Yixin Su, Sangeeta Singth, Ashish Kumar, , Michael A. Nader

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With no FDA-approved treatments for cocaine use disorders (CUD), research has focused on the behavioral and neuropharmacological effects of cocaine in animal models, with the goal of identifying novel interventions. While the majority of people with CUD also use tobacco/nicotine, the majority of preclinical cocaine research does not include the co-use of nicotine. The present study examined nicotine and cocaine co-use under several conditions of intravenous drug self-administration in monkeys. In Experiment 1, male rhesus monkeys (N=3) self-administered cocaine (0.001-0.1 mg/kg/injection) alone and cocaine+nicotine (0.01-0.03 mg/kg/injection) under a progressive-ratio schedule of reinforcement. When nicotine was added to cocaine, there was a significant leftward shift and significant increase in peak break point. In Experiment 2, socially housed female and male cynomolgus monkeys (N=14) self-administered cocaine under a concurrent drug-vs-food choice schedule. Combining nicotine significantly decreased cocaine choice ED50 values (i.e., shifted the cocaine dose-response curve to the left) in females but not in males. There was no evidence of social rank differences. In delay discounting studies, the co-use of nicotine and cocaine required significantly larger delays to the preferred drug reinforcer to reallocate choice compared with cocaine alone. Overall, these results suggest drug interactions of nicotine and cocaine co-use is not simply a function of potency but rather a fundamentally distinctive condition that should be utilized to better understand the neuropharmacology of CUD and the evaluation of potential treatments.

Keywords: polydrug use, animal models, nonhuman primates, behavioral pharmacology, drug self-administration

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Authors: Atheer Al-Maqbali, Mohammed Al-Rizeiqi, Pankaj Pathare

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There is an ever-increased demand for the consumption of banana products in Oman and elsewhere in the region due to the nutritional value and the decent taste of the product. There are approximately 3,751 acres of land designated for banana cultivation in the Sultanate of Oman, which produces approximately 18,447 tons of banana product. The fresh banana product is extremely perishable, resulting in a significant post-harvest economic loss. Since the product has high sensory acceptability, the drying method is a common method for processing fresh banana products. This study aims to use the drying technology in the production of dried bananas to preserve the largest amount of natural color and delicious taste for the consumer. The study also aimed to assess the shelf stability of both water activity (aw) and color (L*, a*, b*) for fresh and finished dried bananas by using a Conventional Air Drying System. Water activity aw, color characteristic L a b, and product’s hardness were analyzed for 3mm, 5mm, and7 mm thickness at different temperaturesoC. All data were analyzed statistically using STATA 13.0, and α ≤ 0.05 was considered for the significance level. The study is useful to banana farmers to improve cultivation, food processors to optimize producer’s output and policy makers in the optimization of banana processing and post-harvest management of the products.

Keywords: banana, drying, oman, quality, thickness, hardness, color

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

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Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim

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A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.

Keywords: butterfly valve, flow coefficient, automatic CFD analysis, FSI analysis

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Authors: Sara T. K. Li, Belinda H. J. Chung, Jeffery C. N. Yip, Janet H. Hsiao

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Music notation and text reading both involve statistical learning of music or linguistic structures. However, it remains unclear how music reading expertise influences text reading behavior. The present study examined this issue through an eye-tracking study. Chinese-English bilingual musicians and non-musicians read English sentences, Chinese sentences, musical phrases, and sentences in Tibetan, a language novel to the participants, with their eye movement recorded. Each set of stimuli consisted of two conditions in terms of structural regularity: syntactically correct and syntactically incorrect musical phrases/sentences. They then completed a sentence comprehension (for syntactically correct sentences) or a musical segment/word recognition task afterwards to test their comprehension/recognition abilities. The results showed that in reading musical phrases, as compared with non-musicians, musicians had a higher accuracy in the recognition task, and had shorter reading time, fewer fixations, and shorter fixation duration when reading syntactically correct (i.e., in diatonic key) than incorrect (i.e., in non-diatonic key/atonal) musical phrases. This result reflects their expertise in music reading. Interestingly, in reading Tibetan sentences, which was novel to both participant groups, while non-musicians did not show any behavior differences between reading syntactically correct or incorrect Tibetan sentences, musicians showed a shorter reading time and had marginally fewer fixations when reading syntactically correct sentences than syntactically incorrect ones. However, none of the musicians reported discovering any structural regularities in the Tibetan stimuli after the experiment when being asked explicitly, suggesting that they may have implicitly acquired the structural regularities in Tibetan sentences. This group difference was not observed when they read English or Chinese sentences. This result suggests that music reading expertise facilities reading texts in a novel language (i.e., Tibetan), but not in languages that the readers are already familiar with (i.e., English and Chinese). This phenomenon may be due to the similarities between reading music notations and reading texts in a novel language, as in both cases the stimuli follow particular statistical structures but do not involve semantic or lexical processing. Thus, musicians may transfer their statistical learning skills stemmed from music notation reading experience to implicitly discover structures of sentences in a novel language. This speculation is consistent with a recent finding showing that music reading expertise modulates the processing of English nonwords (i.e., words that do not follow morphological or orthographic rules) but not pseudo- or real words. These results suggest that the modulation of music reading expertise on language processing depends on the similarities in the cognitive processes involved. It also has important implications for the benefits of music education on language and cognitive development.

Keywords: eye movement behavior, eye-tracking, music reading expertise, sentence reading, structural regularity, visual processing

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Authors: Patsy Tan, Dana Baltutis

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This presentation demonstrates the effectiveness of music therapy in co-treatment with speech pathology and occupational therapy as an innovative way when working with children and adolescents with complex individual differences to facilitate communication, emotional, motor and social skills development. Each child with special needs and their carer has an individual profile which encompasses their visual-spatial, auditory, language, learning, mental health, family dynamic, sensory-motor, motor planning and sequencing profiles. The most common issues among children with special needs, especially those diagnosed with Autism Spectrum Disorder, are in the areas of regulation, communication, and social-emotional development. The ability of children living with challenges to communicate and use language and understand verbal and non-verbal information, as well as move their bodies to explore and interact with their environments in social situations, depends on the children being regulated both internally and externally and trusting their communication partners and understanding what is happening in the moment. For carers, it is about understanding the tempo, rhythm, pacing, and timing of their own individual profile, as well as the profile of the child they are interacting with, and how these can sync together. In this study, music therapy is used in co-treatment sessions with a speech pathologist and/or an occupational therapist using the DIRFloortime approach to facilitate the regulation, attention, engagement, reciprocity and social-emotional capacities of children presenting with complex individual differences. Documented changes in 10 domains of children’s development over a 12-month period using the Individual Music Therapy Assessment Profile (IMTAP) were observed. Children were assessed biannually, and results show significant improvements in the social-emotional, musicality and receptive language domains indicating that co-treatment with a music therapist using the DIRFloortime framework is highly effective. This presentation will highlight strategies that facilitate regulation, social-emotional and communication development for children and adolescents with complex individual profiles.

Keywords: communication, shared attention, regulation, social emotional

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Authors: Sarah Al-Lumai, Fatima Al-Attar, Nour Jamal, Badria Al-Dabbous, Manal Abdulla

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Today, many commonly used Industrial Engineering tools and techniques are being used in hospitals around the world for the goal of producing a more efficient and effective healthcare system. A common quality improvement methodology known as Lean Six-Sigma has been successful in manufacturing industries and recently in healthcare. The objective of our project is to use the Lean Six-Sigma methodology to reduce waiting time in the Emergency Department (ED), in a local private hospital. Furthermore, a comprehensive literature review was conducted to evaluate the success of Lean Six-Sigma in the ED. According to the study conducted by Ibn Sina Hospital, in Morocco, the most common problem that patients complain about is waiting time. To ensure patient satisfaction many hospitals such as North Shore University Hospital were able to reduce waiting time up to 37% by using Lean Six-Sigma. Other hospitals, such as John Hopkins’s medical center used Lean Six-Sigma successfully to enhance the overall patient flow that ultimately decreased waiting time. Furthermore, it was found that capacity constraints, such as staff shortages and lack of beds were one of the main reasons behind long waiting time. With the use of Lean Six-Sigma and bed management, hospitals like Memorial Hermann Southwest Hospital were able to reduce patient delays. Moreover, in order to successfully implement Lean Six-Sigma in our project, two common methodologies were considered, DMAIC and DMADV. After the assessment of both methodologies, it was found that DMAIC was a more suitable approach to our project because it is more concerned with improving an already existing process. With many of its successes, Lean Six-Sigma has its limitation especially in healthcare; but limitations can be minimized if properly approached.

Keywords: lean six sigma, DMAIC, hospital, methodology

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

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Authors: Merkouche Wassila, Marchand Alain, Renaud Stéphane

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Organizations are facing competitive pressures constraining them to modify their practices and change initial work conditions of employees, however, these modifications have to sustain initial quality of work and engagements toward the workforce. We focus on the importance of promises in the perspective of psychological contract. According to this perspective, employees perceiving a breach of the expected obligations from the employer may become unsatisfied at work and develop organizational withdrawal behaviors. These are negative counterproductive behaviours aiming to damage the organisation according to the principle of reciprocity and social exchange. We present an integrative model of the determinants and manifestations of organizational withdrawal (OW), a set of behaviors allowing the employee to leave his job or avoid his assigned work. OW contains two main components often studied in silos: work withdrawal (delays, absenteeism and other adverse behaviors) and job withdrawal (turnover). We use the systemic micro, meso and macro sociological approach designing the individual at the heart of a system containing individual, organizational, and environmental determinants. Under the influence of these different factors, the individual assesses the type of behavior to adopt. We provide better lighting for understanding OW using both psychological contract approach through the perception of its respect by the organization and job embeddedness approach which explains why the employee does not leave the organization and then remains in his post while practicing negative and counterproductive behaviors such as OW. We study specifically cynicism as a type of OW as it is a dimension of burnout. We focus on the antecedents of cynicism to try to prevent it in the workplace.

Keywords: burnout, cynicism, job embeddedness, organizational withdrawal, psychological contract

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Authors: Afshan Channa, Sameeha Aleem, Harim Mohsin

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First rank symptoms (FRS) are considered to be pathognomic for Schizophrenia. However, FRS is not a distinctive feature of Schizophrenia. It has also been noticed in affective disorder, albeit not inclusive in diagnostic criteria. The presence of FRS in Mania leads to misdiagnosis of psychotic illness, further complicating the management and delay of appropriate treatment. FRS in Mania is associated with poor clinical and functional outcome. Its existence in the first episode of bipolar disorder may be a predictor of poor short-term outcome and decompensating course of illness. FRS in Mania is studied in west. However, the cultural divergence and detriments make it pertinent to study the frequency of FRS in affective disorder independently in Pakistan. Objective: The frequency of first rank symptoms in manic patients, who were under treatment at psychiatric services of tertiary care hospital. Method: The cross sectional study was done at psychiatric services of Aga Khan University Hospital, Karachi, Pakistan. One hundred and twenty manic patients were recruited from November 2014 to May 2015. The patients who were unable to comprehend Urdu or had comorbid psychiatric or organic disorder were excluded. FRS was assessed by administration of validated Urdu version of Present State Examination (PSE) tool. Result: The mean age of the patients was 37.62 + 12.51. The mean number of previous manic episode was 2.17 + 2.23. 11.2% males and 30.6% females had FRS. This association of first rank symptoms with gender in patients of mania was found to be significant with a p-value of 0.008. All-inclusive, 19.2% exhibited FRS in their course of illness. 43.5% had thought broadcasting, made feeling, impulses, action and somatic passivity. 39.1% had thought insertion, 30.4% had auditory perceptual distortion, and 17.4% had thought withdrawal. However, none displayed delusional perception. Conclusion: The study confirms the presence of FRS in mania in both male and female, irrespective of the duration of current manic illness or previous number of manic episodes. A substantial difference was established between both the genders. Being married had no protective effect on the presence of FRS.

Keywords: first rank symptoms, Mania, psychosis, present state examination

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Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Bharati Mehta, Manish Parakh, Bharti Bhandari, Sneha Ambwani

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Speech and language delay (SLD) is seen commonly as a co-morbidity in children having severe resistant focal and generalized, syndromic and symptomatic epilepsies. It is however not clear whether epilepsy contributes to or is a mere association in the pathogenesis of SLD. Also, it is acknowledged that Auditory Brainstem Evoked Responses (ABER), besides used for evaluating hearing threshold, also aid in prognostication of neurological disorders and abnormalities in the hearing pathway in the brainstem. There is no circumscribed or surrogate neurophysiologic laboratory marker to adjudge the extent of SLD. The current study was designed to evaluate the abnormalities in Electroencephalography (EEG) and ABER in children with SLD who do not have an overt hearing deficit or autism. 94 children of age group 2-8 years with predominant SLD and without any gross motor developmental delay, head injury, gross hearing disorder, cleft lip/palate and autism were selected. Standard video Electroencephalography using the 10:20 international system and ABER after click stimulus with intensities 110 db until 40 db was performed in all children. EEG was abnormal in 47.9% (n= 45; 36 boys and 9 girls) children. In the children with abnormal EEG, 64.5% (n=29) had an abnormal background, 57.8% (n=27) had presence of generalized interictal epileptiform discharges (IEDs), 20% (n=9) had focal epileptiform discharges exclusively from left side and 33.3% (n=15) had multifocal IEDs occurring both in isolation or associated with generalised abnormalities. In ABER, surprisingly, the peak latencies for waves I, III & V, inter-peak latencies I-III & I-V, III-V and wave amplitude ratio V/I, were found within normal limits in both ears of all the children. Thus in the current study it is certain that presence of generalized IEDs in EEG are seen in higher frequency with SLD and focal IEDs are seen exclusively in left hemisphere in these children. It may be possible that even with generalized EEG abnormalities present in these children, left hemispheric abnormalities as a part of this generalized dysfunction may be responsible for the speech and language dysfunction. The current study also emphasizes that ABER may not be routinely recommended as diagnostic or prognostic tool in children with SLD without frank hearing deficit or autism, thus reducing the burden on electro physiologists, laboratories and saving time and financial resources.

Keywords: ABER, EEG, speech, language delay

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Authors: Gannouni Sonia, Hammami Asma, Saidi Salwa, Rebai Noamen

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Water resources in Tunisia have experienced quantitative and qualitative degradation, especially when talking about wetlands and Sbekhas. Indeed, the objective of this work is to study the spatio-temporal evolution of salinity for 29 years (from 1987 to 2016). A study of the connection between surface water and groundwater is necessary to know the degree of influence of the Sebkha brines on the water table. The evolution of surface salinity is determined by remote sensing based on Landsat TM and OLI/TIRS satellite images of the years 1987, 2007, 2010, and 2016. The processing of these images allowed us to determine the NDVI(Normalized Difference Vegetation Index), the salinity index, and the surface temperature around Sebkha. In addition, through a geographic information system(GIS), we could establish a map of the distribution of salinity in the subsurface of the water table of Chott Mariem and Hergla/SidiBouAli/Kondar. The results of image processing and the calculation of the index and surface temperature show an increase in salinity downstream of in addition to the sebkha and the development of vegetation cover upstream and the western part of the sebkha. This richness may be due both to contamination by seawater infiltration from the barrier beach of Hergla as well as the passage of groundwater to the sebkha.

Keywords: spatio-temporal monitoring, salinity, satellite images, NDVI, sebkha

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

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Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform

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Authors: Adegbite Bashiru Adeniyi, Olaniyi Akeem Olawale, Ayobamidele Sinatu Juliet

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The study was carried out in the 6 South Western states of Nigeria to analyze socio-economic characteristic of garri processors and their anthropometric qualities with respect to modern technologies used in garri processing. About 20 respondents were randomly selected from each of the 6 workstations purposively considered for the study due to their daily processing activities already attracted high patronage of customers. These include Oguntolu village (Ogun State), Igoba-Akure (Ondo State), Imo-Ilesa (Osun State), Odo Oba-Ileri (Oyo State), Irasa village (Ekiti State) and Epe in Lagos state. Interview schedule was conducted for 120 respondents to elicit information. Data were analyzed using descriptive statistical tools. It was observed from the findings that respondents were in their most productive age range (36-45 years) except Ogun state where majority (45%) were relatively older than 45 years. A fewer processors were much younger than 26 years old. It furthers revealed that not less than 55% have body weight greater than 50.0 kilogram, also not less than 70% were taller than 1.5 meter. So also, the hand length and hand thickness of the majority were long and bulky which are considered suitable for operating some modern and improved technologies in garri-frying process. This information could be used by various technological developers to enhance production of modern equipment and tools for a greater efficiency.

Keywords: agro-business, anthromorphic, modernization, proficiency

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Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems

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Authors: Kartik Thakore, Anna-Roza Tamas, Adam Cole

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The world health organization (WHO) reports that by 2030 more than 23.7 million deaths annually will be caused by Cardiovascular Diseases (CVDs); with a 2008 economic impact of $3.76 T. Metabolic syndrome is a disorder of multiple metabolic risk factors strongly indicated in the development of cardiovascular diseases. Guided lifestyle intervention driven by live coaching has been shown to have a positive impact on metabolic risk factors. Individuals’ path to improved (decreased) metabolic risk factors are driven by personal motivation and personalized messages delivered by coaches and augmented by technology. Using interactions captured between 400 individuals and 3 coaches over a program period of 500 days, a preliminary model was designed. A novel real time event tracking system was created to track and classify clients based on their genetic profile, baseline questionnaires and usage of a mobile application with live coaching sessions. Classification of clients and coaches was done using a support vector machines application build on Apache Spark, Stanford Natural Language Processing Library (SNLPL) and decision-modeling.

Keywords: guided lifestyle intervention, metabolic risk factors, personal coaching, support vector machines application, Apache Spark, natural language processing

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Authors: Magdeline Pakeng Mohlala, R. L. Molatudi, M. A. Mofokeng

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Cowpea (Vigna unguiculata (L.) Walp) is an important annual leguminous crop in semi-arid and tropics. Most of cowpea grain production in South Africa is mainly used for domestic consumption, as seed planting and little or none gets to be used in industrial processing; thus, there is a need to expand the utilization of cowpea through industrial processing. Agronomic traits contribute to the understanding of the association between yield and its component traits to facilitate effective selection for yield improvement. The aim of this study was to evaluate cowpea genotypes using grain yield and canning quality traits. The field experiment was conducted in two locations in Limpopo Province, namely Syferkuil Agricultural Experimental farm and Ga-Molepo village during 2017/2018 growing season and canning took place at ARC-Grain Crops Potchefstroom. The experiment comprised of 100 cowpea genotypes laid out in a Randomized Complete Block Designs (RCBD). The grain yield, yield components, and canning quality traits were analysed using Genstat software. About 62 genotypes were suitable for canning, 38 were not due to their seed coat texture, and water uptake was less than 80% resulting in too soft (mushy) seeds. Grain yield for RV115, 99k-494-6, ITOOK1263, RV111, RV353 and 53 other genotypes recorded high positive association with number of branches, pods per plant, and number of seeds per pod, unshelled weight and shelled weight for Syferkuil than at Ga-Molepo are therefore recommended for canning quality.

Keywords: agronomic traits, canning quality, genotypes, yield

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Authors: R. Kumaravelu, S. Poornima, Sunil Kumar Kashyap

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The optimized and digitalized restoration of the information from the old and used manual jacquard punched card in textile industry is referred to as Jacquard Punch Card (JPC) reader. In this paper, we present a novel design and development of photo electronics based system for reading old and used punched cards and storing its binary information for transforming them into an effective image file format. In our textile industry the jacquard punched cards holes diameters having the sizes of 3mm, 5mm and 5.5mm pitch. Before the adaptation of computing systems in the field of textile industry those punched cards were prepared manually without digital design source, but those punched cards are having rich woven designs. Now, the idea is to retrieve binary information from the jacquard punched cards and store them in digital (Non-Graphics) format before processing it. After processing the digital format (Non-Graphics) it is converted into an effective image file format through either by Row major or Column major parsing technique.To accomplish these activities, an embedded system based device and software integration is developed. As part of the test and trial activity the device was tested and installed for industrial service at Weavers Service Centre, Kanchipuram, Tamilnadu in India.

Keywords: file system, SPI. UART, ARM controller, jacquard, punched card, photo LED, photo diode

Procedia PDF Downloads 148

Authors: Ying Liang, Na Li

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Lipo-alkaloid is a kind of C19-norditerpenoid alkaloids existed in Aconitum species, which usually contains an aconitane skeleton and one or two fatty acid residues. The structures are very similar to that of diester-type alkaloids, which are considered as the main bioactive components in Aconitum carmichaelii. They have anti-inflammatory, anti-nociceptive, and anti-proliferative activities. So far, more than 200 lipo-alkaloids were reported from plants, semisynthesis, and biotransformations. In our research, by the combination of ultra-high performance liquid chromatography-quadruple-time of flight mass spectrometry (UHPLC-Q-TOF-MS) and an in-house database, 148 lipo-alkaloids were identified from A. carmichaelii, including 93 potential new compounds and 38 compounds with oxygenated fatty acid moieties. To our knowledge, this is the first time of the reporting of the oxygenated fatty acids as the side chains in naturally-occurring lipo-alkaloids. Considering the fatty acid residues in lipo-alkaloids should come from the free acids in the plant, the fatty acids and their relationship with lipo-alkaloids were further investigated by GC-MS and LC-MS. Among 17 fatty acids identified by GC-MS, 12 were detected as the side chains of lipo-alkaloids, which accounted for about 1/3 of total lipo-alkaloids, while these fatty acid residues were less than 1/4 of total fatty acid residues. And, total of 37 fatty acids were determined by UHPCL-Q-TOF-MS, including 18 oxidized fatty acids firstly identified from A. carmichaelii. These fatty acids were observed as the side chains of lipo-alkaloids. In addition, although over 140 lipo-alkaloids were identified, six lipo-alkaloids, 8-O-linoleoyl-14-benzoylmesaconine (1), 8-O-linoleoyl-14-benzoylaconine (2), 8-O-palmitoyl-14-benzoylmesaconine (3), 8-O-oleoyl-14-benzoylmesaconine (4), 8-O-pal-benzoylaconine (5), and 8-O-ole-Benzoylaconine (6), were found to be the main components, which accounted for over 90% content of total lipo-alkaloids. Therefore, using these six components as standards, a UHPLC-Triple Quadrupole-MS (UHPLC-QQQ-MS) approach was established to investigate the influence of processing on the contents of lipo-alkaloids. Although it was commonly supposed that the contents of lipo-alkaloids increased after processing, our research showed that no significant change was observed before and after processing. Using the same methods, the lipo-alkaloids in the lateral roots of A. carmichaelii and the roots of A. kusnezoffii were determined and quantified. The contents of lipo-alkaloids in A. kusnezoffii were close to that of the parent roots of A. carmichaelii, while the lateral roots had less lipo-alkaloids than the parent roots. This work was supported by Macao Science and Technology Development Fund (086/2013/A3 and 003/2016/A1).

Keywords: Aconitum carmichaelii, fatty acids, GC-MS, LC-MS, lipo-alkaloids

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Authors: Rammah Abdlbagi, Similoluwa Biyi, Aakash Pai

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Introduction: Short-term ureteric stents are commonly placed after ureteroscopy procedures. The removal usually entails having a flexible cystoscopy, which entails a further invasive procedure. There are often delays in removing the stent as departments have limited cystoscopy availability. However, if stents with extraction strings are used, the patient or a clinician can remove them. The aim of the study is to assess the safety and effectiveness of the use of a stent with a string. Method: A retrospective, single-institution study was conducted over a three-month period. Twenty consecutive patients had ureteric stents with string insertion. Ten of the patients had a stent removal procedure previously with flexible cystoscopy. A validated questionnaire was used to assess outcomes. Primary outcomes included: dysuria, hematuria, urinary frequency, and disturbance of the patient’s daily activities. Secondary outcomes included pain experience during the stent removal. Result: Fifteen patients (75%) experienced hematuria and frequency. Two patients experienced pain and discomfort during the stent removal (10%). Two patients had experienced a disturbance in their daily activity (10%). All patients who had stent removal before using flexible cystoscopy preferred the removal of the stent using a string. None of the patients had stent displacement. The median stent dwell time was five days. Conclusion: Patient reported outcomes measures for the indwelling period of a stent with extraction string are equivalent to the published data on stents. Extraction strings mean that the stent dwell time can be reduced. The removal of the stent on extraction strings is more tolerable than the conventional stent.

Keywords: ureteric stent, string flexible cystoscopy, stent symptoms, validated questionnaire

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Authors: Mythri G., Manjunath ML, Girish Babu M., Shireen Swaliha Quadri

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Background: The increase in diabetes among the elderly is of concern because in addition to the wide range of traditional diabetes complications, evidence has been growing that diabetes is associated with increased risk of cognitive decline. Aims and Objectives: To find out if there is any association between blood sugar levels and short-term and working memory status in patients of type 2 diabetes. Materials and Methods: The study was carried out in 200 individuals aged between 40-65 years consisting of 100 diagnosed cases of Type 2 Diabetes Mellitus and 100 non-diabetics from OPD of Mc Gann Hospital, Shivamogga. Rye’s Auditory Verbal Learning Test, Verbal Fluency Test and Visual Reproduction Test, Working Digit Span Test and Validation Span Test were used to assess short-term and working memory. Fasting and Post Prandial blood sugar levels were estimated. Statistical analysis was done using SPSS 21. Results: Memory test scores of type 2 diabetics were significantly reduced (p < 0.001) when compared to the memory scores of age and gender matched non-diabetics. Fasting blood sugar levels were found to have a negative correlation with memory scores for all 5 tests: AVLT (r=-0.837), VFT (r=-0.888), VRT(r=-0.787), WDST (r=-0.795) and VST (r=-0.943). Post- Prandial blood sugar levels were found to have a negative correlation with memory scores for all 5 tests: AVLT (r=-0.922), VFT (r=-0.848), VRT(r=-0.707),WDST (r=-0.729) and VST (r=-0.880) Memory scores in all 5 tests were found to be negatively correlated with the FBS and PPBS levels in diabetic patients (p < 0.001). Conclusion: The decreased memory status in diabetic patients may be due to many factors like hyperglycemia, vascular disease, insulin resistance, amyloid deposition and also some of the factor combine to produce additive effects like, type of diabetes, co-morbidities, age of onset, duration of the disease and type of therapy. These observed effects of blood sugar levels of diabetics on memory status are of potential clinical importance because even mild cognitive impairment could interfere with todays’ activities.

Keywords: diabetes, cognition, diabetes, HRV, respiratory medicine

Procedia PDF Downloads 265

Authors: Ahmed Stifi, Sascha Gentes, Fritz Gehbauer

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The construction industry is perhaps one of the oldest industry of the world. The ancient monuments like the egyptian pyramids, the temples of Greeks and Romans like Parthenon and Pantheon, the robust bridges, old Roman theatres, the citadels and many more are the best testament to that. The industry also has a symbiotic relationship with other . Some of the heavy engineering industry provide construction machineries, chemical industry develop innovative construction materials, finance sector provides fund solutions for complex construction projects and many more. Construction Industry is not only mammoth but also very complex in nature. Because of the complexity, construction industry is prone to various tribulations which may have the propensity to hamper its growth. The comparitive study of this industry with other depicts that it is associated with a state of tardiness and delay especially when we focus on the managerial aspects and the study of triple constraint (time, cost and scope). While some institutes says the complexity associated with it as a major reason, others like lean construction, refers to the wastes produced across the construction process as the prime reason. This paper introduces corruption as one of the prime factors for such delays.To support this many international reports and studies are available depicting that construction industry is one of the most corrupt sectors worldwide, and the corruption can take place throught the project cycle comprising project selection, planning, design, funding, pre-qualification, tendering, execution, operation and maintenance, and even through the reconstrction phase. It also happens in many forms such as bribe, fraud, extortion, collusion, embezzlement and conflict of interest and the self-sufficient. As a solution to cope the corruption in construction industry, the paper introduces the integrity as a key factor and build a new integrity framework to develop and implement an integrity management system for construction companies and construction projects.

Keywords: corruption, construction industry, integrity, lean construction

Procedia PDF Downloads 364