Search results for: Bayesian adjustment

Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

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Authors: Arjmand Khaliq, Pemra Sohaib

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There is increasing trend of use of smart devices in the present age. The growth of computing techniques and advancement in hardware has also brought the use of sensors and smart devices to a high degree during the course of time. So use of smart devices for control, management communication and optimization has become very popular. This paper gives proposed methodology which involves sensing and switching unite for load, two way communications between utility company and smart phones of consumers using cellular techniques and price signaling resulting active participation of user in energy management .The goal of this proposed control methodology is active participation of user in energy management with accommodation of renewable energy resource. This will provide load adjustment according to consumer’s choice, increased security and reliability for consumer, switching of load according to consumer need and monitoring and management of energy.

Keywords: cellular networks, energy management, renewable energy source, smart grid technology

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Authors: Y. Bhatt, N. Ghosh, N. Tiwari

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Acreage response function are modeled taking account of expected harvest prices, weather related variables and other non-price variables allowing for partial adjustment possibility. At the outset, based on the literature on price expectation formation, we explored suitable formulations for estimating the farmer’s expected prices. Assuming that farmers form expectations rationally, the prices of food and biofuel crops are modeled using time-series methods for possible ARCH/GARCH effects to account for volatility. The prices projected on the basis of the models are then inserted to proxy for the expected prices in the acreage response functions. Food crop acreages in different growing states are found sensitive to their prices relative to those of one or more of the biofuel crops considered. The required percentage improvement in food crop yields is worked to offset the acreage loss.

Keywords: acreage response function, biofuel, food security, sustainable development

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Authors: Tianyi Wang, Hieyong Jeong, An Guo, Yuko Ohno

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Healthcare robot for assisting sit-to-stand (STS) performance had aroused numerous research interests. To author’s best knowledge, knowledge about how evaluating healthcare robot is still unknown. Robot should be labeled as fault if users feel demanding during STS when they are assisted by robot. In this research, we aim to propose a method to evaluate sit-to-stand assist robot through center of pressure (CoP), then classify different STS performance. Experiments were executed five times with ten healthy subjects under four conditions: two self-performed STSs with chair heights of 62 cm and 43 cm, and two robot-assisted STSs with chair heights of 43 cm and robot end-effect speed of 2 s and 5 s. CoP was measured using a Wii Balance Board (WBB). Bayesian classification was utilized to classify STS performance. The results showed that faults occurred when decreased the chair height and slowed robot assist speed. Proposed method for fault classification showed high probability of classifying fault classes form others. It was concluded that faults for STS assist robot could be detected by inspecting center of pressure and be classified through proposed classification algorithm.

Keywords: center of pressure, fault classification, healthcare robot, sit-to-stand movement

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Authors: Hsin-Yi Kathy Cheng, Yan-Ying JU, Wann-Yun Shieh, Chin-Man Wang

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Although the coordination of swallowing and respiration has been discussed widely, the influence of the positioning angle on swallowing and respiration during feeding has rarely been investigated. This study aimed to investigate the timing and coordination of swallowing and respiration in different seat inclination angles, with liquid and bolus, to provide suggestions and guidelines for the design and develop a feedback-controlled seat angle adjustment device for the back-adjustable wheelchair. Twenty-six participants aged between 15-30 years old without any signs of swallowing difficulty were included. The combination of seat inclinations and food types was randomly assigned, with three repetitions in each combination. The trunk inclination angle was adjusted by a commercialized positioning wheelchair. A total of 36 swallows were done, with at least 30 seconds of rest between each swallow. We used a self-developed wearable device to measure the submandibular muscle surface EMG, the movement of the thyroid cartilage, and the respiratory status of the nasal cavity. Our program auto-analyzed the onset and offset of duration, and the excursion and strength of thyroid cartilage when it was moving, coordination between breathing and swallowing were also included. Variables measured include the EMG duration (DsEMG), swallowing apnea duration (SAD), total excursion time (TET), duration of 2nd deflection, FSR amplitude, Onset latency, DsEMG onset, DsEMG offset, FSR onset, and FSR offset. These measurements were done in four-seat inclination angles (5。, 15。, 30。, 45。) and three food contents (1ml water, 10ml water, and 5ml pudding bolus) for each subject. The data collected between different contents were compared. Descriptive statistics were used to describe the basic features of the data. Repeated measure ANOVAs were used to analyze the differences for the dependent variables in different seat inclination and food content combinations. The results indicated significant differences in seat inclination, mostly between 5。 and 45。, in all variables except FSR amplitude. It also indicated significant differences in food contents almost among all variables. Significant interactions between seat inclination and food contents were only found in FSR offsets. The same protocol will be applied to participants with disabilities. The results of this study would serve as clinical guidance for proper feeding positions with different food contents. The ergonomic data would also provide references for assistive technology professionals and practitioners in device design and development. In summary, the current results indicated that it is easier for a subject to lean backward during swallowing than when sitting upright and swallowing water is easier than swallowing pudding. The results of this study would serve as the clinical guidance for proper feeding position (such as wheelchair back angle adjustment) with different food contents. The same protocol can be applied to elderly participants or participants with physical disabilities. The ergonomic data would also provide references for assistive technology professionals and practitioners in device design and development.

Keywords: swallowing, positioning, assistive device, disability

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Authors: Hsiu Hua Hu

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Digital transformation has widely affected various industries. It provides technological innovation, process redesign, new business model construction, and talent value creation. This transformation not only allows organizations to obtain and deploy specific technologies and methods suitable for organizational reengineering but also is an important way to solve management problems in human resource (HR) reengineering, business efficiency, and process redesign. In this study, we present the results of a qualitative study that offers insight into a series of key feature of reengineering related to the digital transformation and how to create talent value when the companies successfully perform digital transformation and human resource reengineering, which is led by business digitalization strategies including talent planning, talent acquisition, talent adjustment, and talent development. Drawing from the qualitative investigation findings, we built an inductive model of HR reengineering, which aims to provide research and practical references on future digital transformation and management inquiry.

Keywords: talent value creation, digital transformation, HR reengineering, qualitative study

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Authors: Raouf Mbarki, Fadi Al Khatib, Malek Adouni

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Knee collateral ligaments play a significant role in restraining excessive frontal motion (varus/valgus rotations). In this investigation, a multiscale frame was developed based on structural hierarchies of the collateral ligaments starting from the bottom (tropocollagen molecule) to up where the fibred reinforced structure established. Experimental data of failure tensile test were considered as the principal driver of the developed model. This model was calibrated statistically using Bayesian calibration due to the high number of unknown parameters. Then the model is scaled up to fit the real structure of the collateral ligaments and simulated under realistic boundary conditions. Predications have been successful in describing the observed transient response of the collateral ligaments during tensile test under pre- and post-damage loading conditions. Collateral ligaments maximum stresses and strengths were observed near to the femoral insertions, a results that is in good agreement with experimental investigations. Also for the first time, damage initiation and propagation were documented with this model as a function of the cross-link density between tropocollagen molecules.

Keywords: multiscale model, tropocollagen, fibrils, ligaments commas

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Authors: Sergey Ermolin, Olga Ermolin

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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.

Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking

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Authors: Rima Al-Awadhi, Abdul Jaleel Tharayil

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On a regular basis, KOC engages into various types of Projects. However, due to very nature and complexity involved, each project experience generates a lot of ‘learnings’ that need to be factored into while drafting a new contract and thus avoid repeating the same mistakes. But, many a time these learnings are localized and remain as tacit leading to scope re-work, larger cycle time, schedule overrun, adjustment orders and claims. Also, these experiences are not readily available to new employees leading to steep learning curve and longer time to competency. This is to share our experience in designing and implementing a process driven architecture for the ‘lessons learnt’ knowledge sharing framework in KOC. It high-lights the ‘lessons learnt’ sharing process adopted, integration with the organizational processes, governance framework, the challenges faced and learning from our experience in implementing a ‘lessons learnt’ framework.

Keywords: lessons learnt, knowledge transfer, knowledge sharing, successful practices, Lessons Learnt Workshop, governance framework

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Authors: Deepshikha Shukla, C. H. Solanki, Mayank K. Desai

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Amongst all the natural hazards, earthquakes have the potential for causing the greatest damages. Since the earthquake forces are random in nature and unpredictable, the quantification of the hazards becomes important in order to assess the hazards. The time and place of a future earthquake are both uncertain. Since earthquakes can neither be prevented nor be predicted, engineers have to design and construct in such a way, that the damage to life and property are minimized. Seismic hazard analysis plays an important role in earthquake design structures by providing a rational value of input parameter. In this paper, both mathematical, as well as computational methods adopted by researchers globally in the past five years, will be discussed. Some mathematical approaches involving the concepts of Poisson’s ratio, Convex Set Theory, Empirical Green’s Function, Bayesian probability estimation applied for seismic hazard and FOSM (first-order second-moment) algorithm methods will be discussed. Computational approaches and numerical model SSIFiBo developed in MATLAB to study dynamic soil-structure interaction problem is discussed in this paper. The GIS-based tool will also be discussed which is predominantly used in the assessment of seismic hazards.

Keywords: computational methods, MATLAB, seismic hazard, seismic measurements

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Derssie Mebratu

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As a large variety of micro services, web services, social graphic applications, and media applications are continuously developed, it is substantially vital to design and build a reliable, efficient, and faster memory tiering system. Despite limited design, implementation, and deployment in the last few years, several techniques are currently developed to improve a memory tiering system in a cloud. Some of these techniques are to develop an optimal scanning frequency; improve and track pages movement; identify pages that recently accessed; store pages across each tiering, and then identify pages as a hot, warm, and cold so that hot pages can store in the first tiering Dynamic Random Access Memory (DRAM) and warm pages store in the second tiering Compute Express Link(CXL) and cold pages store in the third tiering Non-Volatile Memory (NVM). Apart from the current proposal and implementation, we also develop a new technique based on a machine learning algorithm in that the throughput produced 25% improved performance compared to the performance produced by the baseline as well as the latency produced 95% improved performance compared to the performance produced by the baseline.

Keywords: machine learning, bayesian optimization, memory tiering, CXL, DRAM

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Authors: Rushi Naaz, Diksha Suchdeva

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Background: Temperament is a very important aspect of functioning that needs to be understood in children of patients suffering from schizophrenia. The children of parents with mental disorder have substantially increased risk of psychiatric illness in them and may exhibit a range of problems from minor variations in temperament and adjustment to manifest psychiatric disorder. Method: A case control study was conducted to study the temperament characteristics and psychopathology in children of patients suffering from schizophrenia as compared to those of healthy controls. Both the groups were evaluated on Temperament Measurement Schedule and Childhood Psychopathology Measurement Schedule. Results: The results showed that children of patients suffering from schizophrenia were withdrawing, less adaptable, less sociable and had lower activity level than children of healthy parents. However, on the measure of psychopathology, no significant difference was found. Conclusion: Since temperament can be identified at an early age, children at risk for the disorder later on could be identified early enough for possible primary intervention.

Keywords: children, childhood psychopathology, parental psychopathology, psychiatric disorders, schizophrenia, temperament

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Authors: Ailing Yang, Penghan Song, Aihua Cai

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The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods.

Keywords: maneuvering target, state estimation, Kalman filter, LSTM, self-attention

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Authors: Shiuh-Jer Huang, Su-Shean Chen, Sheam-Chyun Lin

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Two-wheel inverted pendulum robot (TWIPR) is designed with two-hub DC motors for human riding and motion control evaluation. In order to measure the tilt angle and angular velocity of the inverted pendulum robot, accelerometer and gyroscope sensors are chosen. The mobile robot’s moving position and velocity were estimated based on DC motor built in hall sensors. The control kernel of this electric mobile robot is designed with embedded Arduino Nano microprocessor. A handle bar was designed to work as steering mechanism. The intelligent model-free fuzzy sliding mode control (FSMC) was employed as the main control algorithm for this mobile robot motion monitoring with different control purpose adjustment. The intelligent controllers were designed for balance control, and moving speed control purposes of this robot under different operation conditions and the control performance were evaluated based on experimental results.

Keywords: balance control, speed control, intelligent controller, two wheel inverted pendulum

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Authors: Benmansour Nassima, Benmansour Souheyla

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The appropriate integration of reward processing and decision making provided by the environment is vital for behavioural success and individuals’ well being in everyday life. Functional neurological investigation has already provided an inclusive image on affective and emotional (motivational) processing in the healthy human brain and has recently focused its interest also on the assessment of brain function in anxious and depressed individuals. This article offers an overview on the theoretical approaches that relate emotion and decision-making, and spotlights investigation with anxious or depressed individuals to reveal how emotions can interfere with decision-making. This research aims at incorporating the emotional structure based on response and stimulation with a Bayesian approach to decision-making in terms of probability and value processing. It seeks to show how studies of individuals with emotional dysfunctions bear out that alterations of decision-making can be considered in terms of altered probability and value subtraction. The utmost objective is to critically determine if the probabilistic representation of belief affords could be a critical approach to scrutinize alterations in probability and value representation in subjective with anxiety and depression, and draw round the general implications of this approach.

Keywords: decision-making, motivation, alteration, reward processing, response selection

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Authors: M. Pepe, S. Ackermann, L. Fregonese, C. Achille

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3D models obtained with advanced survey techniques such as close-range photogrammetry and laser scanner are nowadays particularly appreciated in Cultural Heritage and Archaeology fields. In order to produce high quality models representing archaeological evidences and anthropological artifacts, the appearance of the model (i.e. color) beyond the geometric accuracy, is not a negligible aspect. The integration of the close-range photogrammetry survey techniques with the laser scanner is still a topic of study and research. By combining point cloud data sets of the same object generated with both technologies, or with the same technology but registered in different moment and/or natural light condition, could construct a final point cloud with accentuated color dissimilarities. In this paper, a methodology to uniform the different data sets, to improve the chromatic quality and to highlight further details by balancing the point color will be presented.

Keywords: color models, cultural heritage, laser scanner, photogrammetry

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Authors: Xia Huo

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The composition and metabolites of the gut microbiota can be altered by environmental pollutants. However, the effect of co-exposure to multiple pollutants on the human gut microbiota has not been sufficiently studied. In this study, gut microorganisms and their metabolites were compared between 33 children from Guiyu and 34 children from Haojiang. The exposure level was assessed by estimating the daily intake (EDI) of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), 6PPD-quinone (6PPDQ), and metal(loid)s in dust. Significant correlations were found between the EDIs of 6PPDQ, BDE28, PCB52, Ni, Cu, and both the alpha diversity index and specific metabolites in single-element models. The study found that the Bayesian kernel machine regression (BKMR) model showed a negative correlation between the EDIs of five pollutants (6PPDQ, BDE28, PCB52, Ni, and Cu) and the Chao 1 index, particularly beyond the 55th percentile. Furthermore, the EDIs of these five pollutants were positively correlated with the levels of the metabolite 2,4-diaminobutyric acid while negatively correlated with the levels of d-erythro-sphingosine and d-threitol. Our research suggests that exposure to 6PPDQ, BDE28, PCB52, Ni, and Cu in kindergarten dust is associated with alterations in the gut microbiota and its metabolites. These alterations may be associated with neurodevelopmental abnormalities in children.

Keywords: gut microbiota, 6PPDQ, PBDEs, PCBs, metal(loid)s, BKMR

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Authors: Hoi Nga Ng, Kam Weng Boey, Chi Wai Kwan

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Supporters of Inclusive education proclaim that all students, regardless of disabilities or special educational needs (SEN), have the right to study in the normal school setting. It is asserted that students with SEN would benefit in academic performance and psychosocial adjustment via participation in common learning activities within the ordinary school system. When more and more students of SEN completed their early schooling, institute of higher education become the setting where students of SEN continue their learning. This study aimed to investigate the school well-being, social relationship, and academic self-concept of students of SEN in higher education. The Perception of Inclusion Questionnaire (PIQ) was used as the measuring instruments. PIQ was validated and incorporated in a questionnaire designed for online survey. Participation was voluntary and anonymous. A total of 90 students with SEN and 457 students without SEN responded to the online survey. Results showed no significant differences in school well-being and social relationship between students with and without SEN, but students with SEN, particularly those with learning and development impairment and those with mental illness and emotional problems, were significantly poorer in academic self-concept. Implications of the findings were discussed.

Keywords: ccademic self-concept, school well-being, social relationship, special educational needs

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Rabia Iftikhar, Iqra Tariq

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The current study examined the parental acceptance-rejection and personality assessment of sexually abused children. A sample of 50 control (25 girls and 25 boys) and 50 abused (25 girls and 25 boys) were drawn through the process of purposive sampling (N = 100). The sample consisted of school going children between the ages of 8-16. The sample was taken from non-governmental schools and NGO. Parental Acceptance-Rejection Questionnaire, Personality Assessment Questionnaire and Emotional STROOP task, were used to explore the relationship between the variables. The results showed that girls showed greater parental rejection than boys, were less psychologically and emotionally adjusted than boys. The results also showed that boys were high on psychological abuse while girls were high on physical and sexual abuse. The results of STROOP showed that sexually abused children showed more reaction time than non-abused children.

Keywords: abused, adjustment, Pakistani, stroop

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Authors: Anna Martin, Raffael Osen

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The demand for fish from aquaculture is constantly growing. Concurrently, due to a shortage of fishmeal caused by extensive overfishing, fishmeal substitution by plant proteins is getting increasingly important for the production of sustainable aquafeed. Several research studies evaluated the impact of plant protein meals, concentrates or isolates on fish health and fish feed quality. However, these protein raw materials often require elaborate and expensive manufacturing and their availability is limited. Rapeseed press cake (RPC) – a side product of de-oiling processes – exhibits a high potential as a plant-based fishmeal alternative in fish feed for carnivorous species due to its availability, low costs and protein content. In order to produce aquafeed with RPC, it is important to systematically assess i) inclusion levels of RPC with similar pellet qualities compared to fishmeal containing formulations and ii) how extrusion parameters can be adjusted to achieve targeted pellet qualities. However, the effect of RPC on extrusion system parameters and pellet quality has only scarcely been investigated. Therefore, the aim of this study was to evaluate the impact of feed formulation, extruder barrel temperature (90, 100, 110 °C) and screw speed (200, 300, 400 rpm) on extrusion system parameters and the physical properties of fish feed pellets. A co-rotating pilot-scale twin screw extruder was used to produce five iso-nitrogenous feed formulations: a fish meal based reference formulation including 16 g/100g fishmeal and four formulations in which fishmeal was substituted by RPC to 25, 50, 75 or 100 %. Extrusion system parameters, being product temperature, pressure at the die, specific mechanical energy (SME) and torque, were monitored while samples were taken. After drying, pellets were analyzed regarding to optical appearance, sectional and longitudinal expansion, sinking velocity, bulk density, water stability, durability and specific hardness. In our study, the addition of minor amounts of RPC already had high impact on pellet quality parameters, especially on expansion but only marginally affected extrusion system parameters. Increasing amounts of RPC reduced sectional expansion, sinking velocity, bulk density and specific hardness and increased longitudinal expansion compared to a reference formulation without RPC. Water stability and durability were almost not affected by RPC addition. Moreover, pellets with rapeseed components showed a more coarse structure than pellets containing only fishmeal. When the adjustment of barrel temperature and screw speed was investigated, it could be seen that the increase of extruder barrel temperature led to a slight decrease of SME and die pressure and an increased sectional expansion of the reference pellets but did almost not affect rapeseed containing fish feed pellets. Also changes in screw speed had little effects on the physical properties of pellets however with raised screw speed the SME and the product temperature increased. In summary, a one-to-one substitution of fishmeal with RPC without the adjustment of extrusion process parameters does not result in fish feed of a designated quality. Therefore, a deeper knowledge of raw materials and their behavior under thermal and mechanical stresses as applied during extrusion is required.

Keywords: extrusion, fish feed, press cake, rapeseed

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Authors: Momoka Sunohara, Ashley J. Lemieux, Esther Yakobov, Andrew G. Ryder, Tomas Jurcik

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Immigration brings changes in many aspects of an individual's life, from social support dynamics, to housing and language, as well as difficulties with regards to discrimination, trauma, and loss. Past research has mostly emphasized individual differences in mental health and has neglected the impact of social-ecological context, such as acculturation and ethnic density. Purpose: The present study aimed to assess the relationship between variables associated with social integration such as perceived ethnic density and ways of coping, as well as psychological adjustment in a rapidly growing non-visible minority group of immigrants in Canada. Data: A small subset of an archival data from our previously published study was reanalyzed with additional variables. Data included information from 269 Russian-Speaking immigrants in Montreal, Canada. Method: Canonical correlation analysis (CCA) investigated the relationship between two sets of variables. SAS PROC CANCORR was used to conduct CCA on a set of social integration variables, including ethnic density, discrimination, social support, family functioning, and acculturation, and a set of psychological well-being variables, including distress, depression, self-esteem, and life satisfaction. In addition, canonical redundancy analysis was performed to calculate the proportion of variances of original variables explained by their own canonical variates. Results: Significance tests using Rao’s F statistics indicated that the first two canonical correlations (i.e., r1 = 0.64, r2 = 0.40) were statistically significant (p-value < 0.0001). Additionally, canonical redundancy analysis showed that the first two well-being canonical variates explained separately 62.9% and 12.8% variances of the standardized well-being variables, whereas the first two social integration canonical variates explained separately 14.7% and 16.7% variances of the standardized social integration variables. These results support the selection of the first two canonical correlations. Then, we interpreted the derived canonical variates based on their canonical structure (i.e., correlations with original variables). Two observations can be concluded. First, individuals who have adequate social support, and who, as a family, cope by acquiring social support, mobilizing others and reframing are more likely to have better self-esteem, greater life satisfaction and experience less feelings of depression or distress. Second, individuals who feel discriminated yet rate higher on a mainstream acculturation scale, and who, as a family, cope by acquiring social support, mobilizing others and using spirituality, while using less passive strategies are more likely to have better life satisfaction but also higher degree of depression. Implications: This model may serve to explain the complex interactions that exist between social and emotional adjustment and aid in facilitating the integration of individuals immigrating into new communities. The same group may experience greater depression but paradoxically improved life satisfaction associated with their coping process. Such findings need to be placed in the context of Russian cultural values. For instance, some Russian-speakers may value the expression of negative emotions with significant others during the integration process; this in turn may make negative emotions more salient, but also facilitate a greater sense of family and community connection, as well as life satisfaction.

Keywords: acculturation, ethnic density, mental health, Russian-speaking

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Authors: Chen-Fang Tsai, Shin-Li Lu

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Distribution-free control chart is an oncoming area from the statistical process control charts in recent years. Some researchers have developed various nonparametric control charts and investigated the detection capability of these charts. The major advantage of nonparametric control charts is that the underlying process is not specifically considered the assumption of normality or any parametric distribution. In this paper, two nonparametric exponentially weighted moving average (EWMA) control charts based on nonparametric tests, namely NE-S and NE-M control charts, are proposed for monitoring process variability. Generally, weighted moving average (GWMA) control charts are extended by utilizing design and adjustment parameters for monitoring the changes in the process variability, namely NG-S and NG-M control charts. Statistical performance is also investigated on NG-S and NG-M control charts with run rules. Moreover, sensitivity analysis is performed to show the effects of design parameters under the nonparametric NG-S and NG-M control charts.

Keywords: Distribution-free control chart, EWMA control charts, GWMA control charts

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Authors: Jugal Bhandari, K. Hari Priya

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The ECG signal provides important clinical information which could be used to pretend the diseases related to heart. Accordingly, delineation of ECG signal is an important task. Whereas delineation of P and T waves is a complex task. This paper deals with the Study of ECG signal and analysis of signal by means of Verilog Design of efficient filters and MATLAB tool effectively. It includes generation and simulation of ECG signal, by means of real time ECG data, ECG signal filtering and processing by analysis of different algorithms and techniques. In this paper, we design a basic particle filter which generates a dynamic model depending on the present and past input samples and then produces the desired output. Afterwards, the output will be processed by MATLAB to get the actual shape and accurate values of the ranges of P-wave and T-wave of ECG signal. In this paper, Questasim is a tool of mentor graphics which is being used for simulation and functional verification. The same design is again verified using Xilinx ISE which will be also used for synthesis, mapping and bit file generation. Xilinx FPGA board will be used for implementation of system. The final results of FPGA shall be verified with ChipScope Pro where the output data can be observed.

Keywords: ECG, MATLAB, Bayesian filtering, particle filter, Verilog hardware descriptive language

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Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

Abstract:

Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

Procedia PDF Downloads 48

Authors: Kaliammah Kumaran, Thilaagheswary Thangadurai

Abstract:

This study examined the relationship between anxious attachment and avoidant attachment among young adult romantic relationship quality. Our survey was administered to 300 young adult participants (126 males and 174 females) aged 18-24 years old (M= 20.85, SD=1.89), accomplished the English version of the Revised Adult Attachment Scale (RAAS) used to measure adult attachment and Revised Dyadic Adjustment Scale (RDAS). All the participants were tertiary level students. Findings of our study indicated that young adults experienced anxious attachment style is negatively correlated with romantic relationship quality as well as young adult from avoidant attachment also negatively correlated with romantic relationship quality among young adults. The results showed that insecure adult attachment styles which are anxious and avoidance adult attachment styles links with reduced quality of romantic relationship.

Keywords: adult attachment style, anxious attachment style, avoidant attachment style, romantic relationship quality

Procedia PDF Downloads 363

Authors: J. J. Vargas, N. Prieto, L. A. Toro

Abstract:

Control charts are commonly used to monitor processes involving either variable or attribute of quality characteristics and determining the control limits as a critical task for quality engineers to improve the processes. Nonetheless, in some applications it is necessary to include an estimation of efficiency. In this paper, the ability to define the efficiency of an industrial process was added to a control chart by means of incorporating a data envelopment analysis (DEA) approach. In depth, a Bayesian estimation was performed to calculate the posterior probability distribution of parameters as means and variance and covariance matrix. This technique allows to analyse the data set without the need of using the hypothetical large sample implied in the problem and to be treated as an approximation to the finite sample distribution. A rejection simulation method was carried out to generate random variables from the parameter functions. Each resulting vector was used by stochastic DEA model during several cycles for establishing the distribution of each efficiency measures for each DMU (decision making units). A control limit was calculated with model obtained and if a condition of a low level efficiency of DMU is presented, system efficiency is out of control. In the efficiency calculated a global optimum was reached, which ensures model reliability.

Keywords: data envelopment analysis, DEA, Multivariate control chart, rejection simulation method

Procedia PDF Downloads 353

Authors: Zizouni Khaled, Fali Leyla, Sadek Younes, Bousserhane Ismail Khalil

Abstract:

In structural vibration caused principally by an earthquake excitation, the most vibration’s attenuation system used recently is the semi active control with a Magneto Rheological Damper device. This control was a subject of many researches and works in the last years. The big challenges of searchers in this case is to propose an adequate controller with a robust algorithm of current or tension adjustment. In this present paper, a linear controller is proposed to control the MR damper using to reduce a vibrations of three story structure exposed to El Centro’s 1940 and Boumerdès 2003 earthquakes. In this example, the MR damper is installed in the first floor of the structure. The numerical simulations results of the proposed linear control with a feedback law based on clipped optimal algorithm showed the feasibility of the semi active control to protecting civil structures. The comparison of the controlled structure and uncontrolled structures responses illustrate clearly the performance and the effectiveness of the simple proposed approach.

Keywords: MR damper, seismic vibration, semi-active control

Procedia PDF Downloads 261

Authors: Mohsen Maadani, Seyed Ahmad Motamedi

Abstract:

The use of wireless technology in industrial networks has gained vast attraction in recent years. In this paper, we have thoroughly analyzed the effect of contention window (CW) size on the performance of IEEE 802.11-based industrial wireless networks (IWN), from delay and reliability perspective. Results show that the default values of CWmin, CWmax, and retry limit (RL) are far from the optimum performance due to the industrial application characteristics, including short packet and noisy environment. An adaptive CW algorithm (payload-dependent) has been proposed to minimize the average delay. Finally a simple, but effective CW and RL setting has been proposed for industrial applications which outperforms the minimum-average-delay solution from maximum delay and jitter perspective, at the cost of a little higher average delay. Simulation results show an improvement of up to 20%, 25%, and 30% in average delay, maximum delay and jitter respectively.

Keywords: average delay, contention window, distributed coordination function (DCF), jitter, industrial wireless network (IWN), maximum delay, reliability, retry limit

Procedia PDF Downloads 394