Search results for: facial profile

Authors: Eva Tolmeijer, Emmanuelle Peters, Veena Kumari, Liam Mason

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Cognitive behavioral therapy for psychosis (CBTp) is effective in many but not all patients, making it important to better understand the factors that determine treatment outcomes. To date, no studies have examined whether neuroimaging can make clinically useful predictions about who will respond to CBTp. To this end, we used machine learning methods that make predictions about symptom improvement at the individual patient level. Prior to receiving CBTp, 22 patients with a diagnosis of schizophrenia completed a social-affective processing task during functional MRI. Multivariate pattern analysis assessed whether treatment response could be predicted by brain activation responses to facial affect that was either socially threatening or prosocial. The resulting models did significantly predict symptom improvement, with distinct multivariate signatures predicting psychotic (r=0.54, p=0.01) and affective (r=0.32, p=0.05) symptoms. Psychotic symptom improvement was accurately predicted from relatively focal threat-related activation across hippocampal, occipital, and temporal regions; affective symptom improvement was predicted by a more dispersed profile of responses to prosocial affect. These findings enrich our understanding of the neurobiological underpinning of treatment response. This study provides a foundation that will hopefully lead to greater precision and tailoring of the interventions offered to patients.

Keywords: cognitive behavioral therapy, machine learning, psychosis, schizophrenia

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Authors: J. R. Lee, E. V. Lau

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Ionic wind is developed when high voltage is supplied to an anode and a grounded cathode in a gaseous medium. This paper studies the ionic wind profile with different anode configurations, the relationship between electrode gap against the voltage supplied and finally a comparison of the heat transfer coefficient of ionic wind over a horizontal flat plate against a conventional fan experimentally. It is observed that increase in the distance between electrodes decreases at a rate of 1-e-0.0206x as the voltage supply is increased until a distance of 3.1536cm. It is also observed that the wind speed produced by ionic wind is stronger, 2.7ms-1 at 2W compared to conventional fan, 2.5ms-1 at 2W but the wind produced decays at a fast exponential rate and is more localized as compared to conventional fan wind that decays at a slower exponential rate and is less localized. Next, it is found out that the ionic wind profile is the same regardless of the position of the anode relative to the cathode. Lastly, it is discovered that ionic wind produced a heat transfer coefficient that is almost 1.6 times higher compared to a conventional fan with Nusselt number reaching 164 compared to 102 for conventional fan.

Keywords: conventional fan, heat transfer, ionic wind, wind profile

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Authors: Maria Hopkins, Sarah Koch, Fred Biasini

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Autism is lifelong disorder that affects one out of every 110 Americans. The deficits that accompany Autism Spectrum Disorders (ASD), such as abnormal behaviors and social incompetence, often make it extremely difficult for these individuals to gain functional independence from caregivers. These long-term implications necessitate an immediate effort to improve social skills among children with an ASD. Any technology that could teach individuals with ASD necessary social skills would not only be invaluable for the individuals affected, but could also effect a massive saving to society in treatment programs. The overall purpose of the first study was to develop, implement, and evaluate an avatar tutor for social skills training in children with ASD. “Face Say” was developed as a colorful computer program that contains several different activities designed to teach children specific social skills, such as eye gaze, joint attention, and facial recognition. The children with ASD were asked to attend to FaceSay or a control painting computer game for six weeks. Children with ASD who received the training had an increase in emotion recognition, F(1, 48) = 23.04, p < 0.001 (adjusted Ms 8.70 and 6.79, respectively) compared to the control group. In addition, children who received the FaceSay training had higher post-test scored in facial recognition, F(1, 48) = 5.09, p < 0.05 (adjusted Ms: 38.11 and 33.37, respectively) compared to controls. The findings provide information about the benefits of computer-based training for children with ASD. Recent research suggests the value of also using socially assistive robots with children who have an ASD. Researchers investigating robots as tools for therapy in ASD have reported increased engagement, increased levels of attention, and novel social behaviors when robots are part of the social interaction. The overall goal of the second study was to develop a social robot designed to teach children specific social skills such as emotion recognition. The robot is approachable, with both an animal-like appearance and features of a human face (i.e., eyes, eyebrows, mouth). The feasibility of the robot is being investigated in children ages 7-12 to explore whether the social robot is capable of forming different facial expressions to accurately display emotions similar to those observed in the human face. The findings of this study will be used to create a potentially effective and cost efficient therapy for improving the cognitive-emotional skills of children with autism. Implications and study findings using the robot as an intervention tool will be discussed.

Keywords: autism, intervention, technology, emotions

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Authors: Shahana Sharmin

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In the present study, the effect of cellulose polymers Ethyl Cellulose and Hydroxy Propyl Methyl Cellulose was evaluated on the release profile of drug from sustained release pellet. Diltiazem Hydrochloride, an antihypertensive, cardio-protective agent and slow channel blocker were used as a model drug to evaluate its release characteristics from different pellets formulations. Diltiazem Hydrochloride sustained release pellets were prepared by drug loading (drug binder suspension) on neutral pellets followed by different percentages of spraying, i.e. 2%,4%, 6%, 8% and 10% coating suspension using ethyl cellulose and hydroxy-propyl methyl cellulose polymer in a fixed 85:15 ratios respectively. The in vitro dissolution studies of Diltiazem Hydrochloride from these sustained release pellets were carried out in pH 7.2 phosphate buffer for 1, 2, 3, 4, 5, 6, 7, and 8 hrs using USP-I method. Statistically, significant differences were found among the drug release profile from different formulations. Polymer content with the highest concentration of Ethyl cellulose on the pellets shows the highest release retarding rate of the drug. The retarding capacity decreases with the decreased concentration of ethyl cellulose. The release mechanism was explored and explained with zero order, first order, Higuchi and Korsmeyer’s equations. Finally, the study showed that the profile and kinetics of drug release were functions of polymer type, polymer concentration & the physico-chemical properties of the drug.

Keywords: diltiazem hydrochloride, ethyl cellulose, hydroxy propyl methyl cellulose, release kinetics, sustained release pellets

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Authors: Beghdadi Lotfi

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In the present work a numerical method is proposed in order to optimize the thermal performance of finned surfaces. The bidimensional temperature distribution on the longitudinal section of the fin is calculated by restoring to the finite volumes method. The heat flux dissipated by a generic profile fin is compared with the heat flux removed by the rectangular profile fin with the same length and volume. In this study, it is shown that a finite volume method for quadrilaterals unstructured mesh is developed to predict the two dimensional steady-state solutions of conduction equation, in order to determine the sinusoidal parameter values which optimize the fin effectiveness. In this scheme, based on the integration around the polygonal control volume, the derivatives of conduction equation must be converted into closed line integrals using same formulation of the Stokes theorem. The numerical results show good agreement with analytical results. To demonstrate the accuracy of the method, the absolute and root-mean square errors versus the grid size are examined quantitatively.

Keywords: Stokes theorem, unstructured grid, heat transfer, complex geometry, effectiveness

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Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

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Facial recognition is a widely adopted technology in surveillance, border control, healthcare, banking services, and lately, in mobile user authentication with Apple introducing “Face ID” moniker with iPhone X. A lot of research has been conducted in the area of face recognition on datasets captured by surveillance cameras, DSLR, and mobile devices. Recently, face recognition technology has also been deployed on body-worn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic so far, without the availability of any publicly available datasets with a sufficient sample size. This paper aims to advance research in the area of face recognition using body-worn cameras. To this aim, the contribution of this work is two-fold: (1) collection of a dataset consisting of a total of 136,939 facial images of 102 subjects captured using body-worn cameras in in-door and daylight conditions and (2) evaluation of various deep-learning architectures for face identification on the collected dataset. Experimental results suggest a maximum True Positive Rate(TPR) of 99.86% at False Positive Rate(FPR) of 0.000 obtained by SphereFace based deep learning architecture in daylight condition. The collected dataset and the baseline algorithms will promote further research and development. A downloadable link of the dataset and the algorithms is available by contacting the authors.

Keywords: face recognition, body-worn cameras, deep learning, person identification

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

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Authors: Umang H. Gajjar, K. M. Khambholja, R. K. Patel

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Semecarpus anacardium shows the presence of bioflavonoids, phenolic compounds, bhilawanols, minerals, vitamins and amino acids. Detoxified S. anacardium and its oils are considered to have anti-inflammatory properties and used in nervous debility, neuritis, rheumatism and leprous modules. S. anacardium if used without purification causes toxic skin inflammation problem because it contains toxic phenolic oil. During this Shodhana Process - An ayurvedic purification method, toxic phenolic oil was removed, have marked effect on the concentration of the phytoconstituent & antioxidant activity of S. anacardium. Total phenolic content decreased up to 70 % (from 28.9 %w/w to 8.94 %w/w), while there is a negligible effect on the concentration of total flavonoid (7.51 %w/w to 7.43 %w/w) and total carbohydrate (0.907 %w/w to 0.853 % w/w) content. IC50& EC50 value of extract of S. anacardium before and after purification are 171.7 & 314.3 while EC50values are 280.μg/ml & 304. μg/ml, shows that antioxidant activity of S. anacardium is decreased but the safety profile of the drug is increased as the toxic phenolic oil was removed during Shodhana - An ayurvedic purification method.

Keywords: Semecarpus anacardium, Shodhana process, safety profile, improvement

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: Lilis Kistriyani, Dine Olisvia, Lutfa Rahmawati

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Facial mask is an important part of every beauty treatment because it will give a smooth and gentle effect on the face. This research is done to make edible film that will be applied for face mask. The main ingredient in making this edible film is purple sweet potato powder with the addition of glycerol as plasticizer. One of the ingredients in purple sweet potato is a flavonoid compound. The purpose of this study was to determine the effect of increasing the amount of glycerol to flavonoids release and the effect on the physical properties and biological properties of edible film produced. The stages of this research are the making of edible film, then perform some analysis, among others, spectrophotometer UV-vis analysis to find out how many flavonoids can be released into facial skin, tensile strength and elongation of break analysis, biodegradability analysis, and microbiological analysis. The variation of edible film is the volume of glycerol that is 1 ml, 2 ml, 3 ml. The results of spectrophotometer UV-vis analysis showed that the most flavonoid release concentration is 20.33 ppm in the 2 ml glycerol variation. The best tensile strength value is 8,502 N, and the greatest elongation of break value is 14% in 1 ml glycerol variation. In the biodegradability test, the more volume of glycerol added the faster the edible film is degraded. The results of microbiological analysis showed that purple sweet potato extract has the ability to inhibit the growth of Propionibacterium acnes seen in the presence of inhibiting zone which is 18.9 mm.

Keywords: face mask, edible film, plasticizer, flavonoid

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Authors: Bahaa Eldin Kornah

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The organism profile for peri-prosthetic joint infection caused by hematogenous seeding or direct inoculations is changing. The organisms that cause prosthetic joint infections range from normal skin colonizers to highly virulent pathogens. The pathogens continue to evolve. While Staphylococcus aureus continues to be the leading organism, gram-negative bacilli account for approximately 7% of cases and that incidence is increasing. Methicillin-resistant S. aureus(MRSA) accounts for approximately 10% of all infections occurring in the community setting and 20% of those in the health care setting. The list of organisms causing PJI has expanded in recent years. It is important to have an understanding of which organisms may be causing a periprosthetic joint infection based on where the patient contracted it and their recent medical history. Also, recent technology has expanded rapidly and new methods to detect the pathogen and why we failed in detecting it. There are a number of explanations for the latter finding, perhaps the most important reason being the liberal use of antibiotics that interferes with the isolation of the infective organism.

Keywords: infection, periprosthetic, hip, organism profile, joint infection, joint infection

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Authors: Meltem Kürtüncü, Işın Alkan

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Objective: This study was carried out with an experimental design in order to determine whether the lullaby, which was listened from mother’s voice and a stranger’s voice to the babies born at term and hospitalized in neonatal intensive care unit, had an effect on stress and relaxation symptoms of the infants. Method: Data from the study were obtained from 90 newborn babies who were hospitalized in Neonatal Intensive Care Unit of Zonguldak Maternity And Children Hospital between September 2015-January 2016 and who met the eligibility criteria. Lullaby concert was performed by choosing one of the suitable care hours. Stress and relaxation symptoms were recorded by the researcher on “Newborn response follow-up form” at pre-care and post-care. Results: After lullaby concert when stress symptoms compared to infants in the experimental and control groups before the care was not detected statistically significant difference between crying, contraction, facial grimacing, flushing, cyanosis and the rates of increase in temperature. After care, crying, contractions, facial grimacing, flushing, and restlessness revealed a statistically significant difference between the groups, but as the cyanosis and temperature increased stress responses did not result in a significant difference between the groups. In the control group babies the crying, contraction, facial grimacing, flushing, and restlessness behaviors rates were found to be significantly higher than experimental group babies. After lullaby concert when relaxation symptoms compared to infants in the experimental and control groups before the care, eye contact rates who listen to lullaby from mother’s voice was found to be significantly higher than infants who listen to lullaby from stranger’s voice and infants in the control group. After care as eye contact, smiling, sucking/searching, yawning, non-crying and sleep behaviors relaxation symptoms revealed statistically significant results. In the control group, these behaviors were found statistically lower degree than the experimental groups. Conclusion: Lullaby concerts as masking the ambient noise, reducing the stress symptoms and increasing the relaxation symptoms, and also for soothing and stimulant affects, due to ease the transition to the sleep state should be preferred in the neonatal intensive care units.

Keywords: lullaby, mother voice, relaxation, stress

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Authors: Mohsen Mazidi, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Mohamamd Rastegar

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To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: loss, plug-in hybrid electric vehicle (PHEV), PHEV parking lot, V2G

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Authors: Helen Frialde-Dupale

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Critical thinking Index (CTI) of 150 third year college students from five State Colleges and Universities (SUCs) in Region I were determined. Only students with Grade Point Average (GPA) of at least 2.0 from four general classification of degree courses, namely: Education, Arts and Sciences, Engineering and Agriculture were included. Specific problem No.1 dealt with the profile variables, namely: age, sex, degree course, monthly family income, number of siblings, high school graduated from, grade point average, personality type, highest educational attainment of parents, and occupation of parents. Problem No. 2 determined the critical thinking index among the respondents. Problem No. 3 investigated whether or not there are significant differences in the critical thinking index among the respondents across the profile variables. While problem No.4 determined whether or not there are significant relationship between the critical thinking index and selected profile variables, namely: age, monthly family income, number of siblings, and grade point average of the respondents. Finally, on problem No. 5, the critical thinking instrument which obtained the lowest rates, were used as basis for outlining an intervention program for enhancing critical thinking index (CTI) of students. The following null hypotheses were tested at 0.05 level of significance: there are no significant differences in the critical thinking index of the third college students across the profile variables; there are no significant relationships between the critical thinking index of the respondents and selected variables, namely: age, monthly family income, number of siblings, and grade point average.

Keywords: attitude as critical thinker, critical thinking applied, critical thinking index, self-perception as critical thinker

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Authors: Subhamita Chakraborty, Shubhabrata Datta, Sujay Kumar Mukherjea, Partha Protim Chattopadhyay

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Manufacturing of multiphase high strength steel in hot strip mill have drawn significant attention due to the possibility of forming low temperature transformation product of austenite under continuous cooling condition. In such endeavor, reliable prediction of temperature profile of hot strip coil is essential in order to accesses the evolution of microstructure at different location of hot strip coil, on the basis of corresponding Continuous Cooling Transformation (CCT) diagram. Temperature distribution profile of the hot strip coil has been determined by using finite volume method (FVM) vis-à-vis finite difference method (FDM). It has been demonstrated that FVM offer greater computational reliability in estimation of contact pressure distribution and hence the temperature distribution for curved and irregular profiles, owing to the flexibility in selection of grid geometry and discrete point position, Moreover, use of finite volume concept allows enforcing the conservation of mass, momentum and energy, leading to enhanced accuracy of prediction.

Keywords: simulation, modeling, thermal analysis, coil cooling, contact pressure, finite volume method

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Authors: Merzougui Imene, Gherib Asma, Henchiri Cherifa

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This study has allowed to confirm the physico chemical characteristics and fatty acid composition by GC of the oil of Pistacia lentiscus extracted by traditional method and evaluate its effect on some blood lipid parameters. The results showed that the main physico chemical characteristics of Pistacia lentiscus oil are: moisture (0.84 %), a relatively high iodine value (80,44) indicating that this oil has an important degree of unsaturation. The oil is mainly composed of unsaturated fatty acids (MUFA) where oleic acid dominate with 47,01 % of total fatty acids and PUFA's represented by linoleic acid (19,26 %). Concerning the biological survey, oil, at 10% and 20% doses of diet for 15 and 30 days of two periods of treatment, resulted in beneficial effects on the lipid profile of Wistar albinos rats previously fed with animal and vegetable fats. We observed decreases in total cholesterol, triglycerides (TGA), total lipids and LDL-C, and an increase in HDL-C "good cholesterol" probably related to the presence of a large amount of (MUFA) and (PUFA).

Keywords: Pistacia lentiscus, oil, lipid profile, monounsaturated fatty acids, polyunsaturated fatty acids

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: impersonation, image registration, incrimination, object detection, threshold evaluation

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Authors: Reem Alkadeem

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This study aims at evaluating the overall satisfaction of faculty members and relating it to organizational and personal aspects in Egyptian public and private universities. These aspects are identified through an extensive study of all factors that might affect job satisfaction. The most influencing parameters selected are academics’ demographics, human resource management, organizational profile, workload, teamwork skills, recognition, autonomy, teaching activity, research activity, and motivation. A questionnaire of 94 questions was used to assess job satisfaction and the previously mentioned parameters. It was distributed among seven hundred members of different universities in Egypt. Two hundred and twenty-seven faculty members responded. This sample was gathered from twelve universities and The Supreme Council of Universities. The ANOVA showed a significant relationship (p < 0.05) between eight of the selected parameters and job satisfaction. These parameters are age, rank, human resource management, profile of organizational characteristics, workload, recognition, teaching activity, and motivation.

Keywords: job satisfaction, higher education, organizational profile, Egyptian universities

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Authors: M. M. Alhaji, M. Alhassan, A. M. Yahaya

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Soil engineers pay very little or no attention to variation in the mineralogical and consequently, the geotechnical properties of overburden with depth on basement complexes, a situation which can lead to sudden failure of civil engineering structures. Soil samples collected at depths ranging from 0.5m to 4.0m at 0.5m intervals, from a trial pit dogged manually to depth of 4.0m on an overburden over gneiss basement complex, was evaluated for physico-chemical, mineralogical and physical properties. This is to determine the variation of these properties with depth within the profile of the strata. Results showed that sodium amphibolite and feldspar, which are both primary minerals dominate the overall profile of the overburden. Carbon which dominates the lower profile of the strata was observed to alter to gregorite at upper section of the profile. Organic matter contents and cation exchange capacity reduces with increase in depth while lost on ignition and pH were relatively constant with depth. The index properties, as well as natural moisture contents, increases from 0.5m to between 1.0m to 1.5m depth after which the values reduced to constant values at 3.0m depth. The grain size analysis shows high composition of sand sized particles with silts of low to non-plasticity. The maximum dry density (MDD) values are generally relatively high and increases from 2.262g/cm³ at 0.5m depth to 2.410g/cm³ at 4.0m depth while the optimum moisture content (OMC) reduced from 9.8% at 0.5m depth to 6.7% at 4.0m depth.

Keywords: Gneiss basement complex, mineralogical properties, North Central Nigeria, physico-chemical properties, physical properties, overburden soil

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Authors: Bruno RamaëL, GwenaëL Page, Catherine Knopf-Lenoir, Olivier Baledent, Anne-Virginie Salsac

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No routine technique currently exists for clinicians to measure the mechanical properties of vascular walls non-invasively. Most of the data available in the literature come from traction or dilatation tests conducted ex vivo on native blood vessels. The objective of the study is to develop a non-invasive characterization technique based on Magnetic Resonance Imaging (MRI) measurements of the deformation of vascular walls under pulsating blood flow conditions. The goal is to determine the mechanical properties of the vessels by inverse analysis, coupling imaging measurements and numerical simulations of the fluid-structure interactions. The hyperelastic properties are identified using Solidworks and Ansys workbench (ANSYS Inc.) solving an optimization technique. The vessel of interest targeted in the study is the common carotid artery. In vivo MRI measurements of the vessel anatomy and inlet velocity profiles was acquired along the facial vascular network on a cohort of 30 healthy volunteers: - The time-evolution of the blood vessel contours and, thus, of the cross-section surface area was measured by 3D imaging angiography sequences of phase-contrast MRI. - The blood flow velocity was measured using a 2D CINE MRI phase contrast (PC-MRI) method. Reference arterial pressure waveforms were simultaneously measured in the brachial artery using a sphygmomanometer. The three-dimensional (3D) geometry of the arterial network was reconstructed by first creating an STL file from the raw MRI data using the open source imaging software ITK-SNAP. The resulting geometry was then transformed with Solidworks into volumes that are compatible with Ansys softwares. Tetrahedral meshes of the wall and fluid domains were built using the ANSYS Meshing software, with a near-wall mesh refinement method in the case of the fluid domain to improve the accuracy of the fluid flow calculations. Ansys Structural was used for the numerical simulation of the vessel deformation and Ansys CFX for the simulation of the blood flow. The fluid structure interaction simulations showed that the systolic and diastolic blood pressures of the common carotid artery could be taken as reference pressures to identify the mechanical properties of the different arteries of the network. The coefficients of the hyperelastic law were identified using Ansys Design model for the common carotid. Under large deformations, a stiffness of 800 kPa is measured, which is of the same order of magnitude as the Young modulus of collagen fibers. Areas of maximum deformations were highlighted near bifurcations. This study is a first step towards patient-specific characterization of the mechanical properties of the facial vessels. The method is currently applied on patients suffering from facial vascular malformations and on patients scheduled for facial reconstruction. Information on the blood flow velocity as well as on the vessel anatomy and deformability will be key to improve surgical planning in the case of such vascular pathologies.

Keywords: identification, mechanical properties, arterial walls, MRI measurements, numerical simulations

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Authors: Kayode A. Olaniyi, Tola. M. Osifeko, Adeola A. Ogunleye

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Text line segmentation is an important step in document image processing. It represents a labeling process that assigns the same label using distance metric probability to spatially aligned units. Text line detection techniques have successfully been implemented mainly in printed documents. However, processing of the handwritten texts especially unconstrained documents has remained a key problem. This is because the unconstrained hand-written text lines are often not uniformly skewed. The spaces between text lines may not be obvious, complicated by the nature of handwriting and, overlapping ascenders and/or descenders of some characters. Hence, text lines detection and segmentation represents a leading challenge in handwritten document image processing. Text line detection methods that rely on the traditional global projection profile of the text document cannot efficiently confront with the problem of variable skew angles between different text lines. Hence, the formulation of a horizontal line as a separator is often not efficient. This paper presents a technique to segment a handwritten document into distinct lines of text. The proposed algorithm starts, by partitioning the initial text image into columns, across its width into chunks of about 5% each. At each vertical strip of 5%, the histogram of horizontal runs is projected. We have worked with the assumption that text appearing in a single strip is almost parallel to each other. The algorithm developed provides a sliding window through the first vertical strip on the left side of the page. It runs through to identify the new minimum corresponding to a valley in the projection profile. Each valley would represent the starting point of the orientation line and the ending point is the minimum point on the projection profile of the next vertical strip. The derived text-lines traverse around any obstructing handwritten vertical strips of connected component by associating it to either the line above or below. A decision of associating such connected component is made by the probability obtained from a distance metric decision. The technique outperforms the global projection profile for text line segmentation and it is robust to handle skewed documents and those with lines running into each other.

Keywords: connected-component, projection-profile, segmentation, text-line

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Authors: N. Dahbi, D. E. Arafah

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Cd1−xZnxS thins films have been fabricated from ZnS/CdS/ZnS multilayer thin film systems, by using the vacuum deposition method; the Rutherford back-scattering (RBS) technique have been applied in order to determine the: structure, composition, depth profile, and stoichiometric of these films. The influence of the chemical and heat treatments on the produced films also have been investigated; the RBS spectra of the films showed that homogenous Cd1−xZnxS can be synthesized with x=0.45.

Keywords: Cd1−xZnxS, chemical treatment, depth profile, heat treatment, RBS, RUMP simulation, thin film, vacuum deposition, ZnS/CdS/ZnS

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Authors: S. Mawlood, L. Denanny, N. Watson, B. Pickard

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DNA analysis has been widely accepted as providing valuable evidence concerning the identity of the source of biological traces. Our work has showed that DNA samples can survive on cartridges even after firing. The study also raised the possibility of determining other information such as the age of the donor. Such information may be invaluable in certain cases where spent cartridges from automatic weapons are left behind at the scene of a crime. In spite of the nature of touch evidence and exposure to high chamber temperatures during shooting, we were still capable to retrieve enough DNA for profile typing. In order to estimate age of contributor, DNA methylation levels were analyzed using EpiTect system for retrieved DNA. However, results were not conclusive, due to low amount of input DNA.

Keywords: DNA profile, DNA Methylation, fired cartridge, touch sample

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

Procedia PDF Downloads 234

Authors: K. Eshwara Prasad, R. Raman Goud, Swadesh Kumar Singh, N. Sateesh

Abstract:

In the present work forming limit diagrams and strain distribution profile diagrams for extra deep drawing steel at room and elevated temperatures have been determined experimentally by conducting stretch forming experiments by using designed and fabricated warm stretchforming tooling setup. With the help of forming Limit Diagrams (FLDs) and strain distribution profile diagrams the formability of Extra Deep Drawing steel has been analyzed and co-related with mechanical properties like strain hardening COEFFICIENT (n) and normal anisotropy (r−).Mechanical properties of EDD steel from room temperature to 4500C were determined and discussed the impact of temperature on the properties like work hardening exponent (n) anisotropy(r-) and strength coefficient of the material. Also the fractured surfaces after stretching have undergone the some metallurgical investigations and attempt has been made to co-relate with the formability of EDD steel sheets. They are co-related and good agreement with FLDs at various temperatures.

Keywords: FLD, microhardness, strain distribution profile, stretch forming

Procedia PDF Downloads 324

Authors: Petra Hypšová, Martin Seitl

Abstract:

One of the challenges of forensic psychology is to detect deception during a face-to-face interview. In addition to the classical approaches of monitoring the utterance and its components, detection is also sought by observing behavioral and physiological changes that occur as a result of the increased emotional and cognitive load caused by the production of distorted information. Typical are changes in facial temperature, eye movements and their fixation, pupil dilation, emotional micro-expression, heart rate and its variability. Expanding technological capabilities have opened the space to detect these psychophysiological changes and behavioral manifestations through non-contact technologies that do not interfere with face-to-face interaction. Non-contact deception detection methodology is still in development, and there is a lack of studies that combine multiple non-contact technologies to investigate their accuracy, as well as studies that show how different types of lies produced by different interviewers affect physiological and behavioral changes. The main objective of this study is to apply a specific non-contact technology for deception detection. The next objective is to investigate scenarios in which non-contact deception detection is possible. A series of psychophysiological experiments using infrared thermal imaging, eye tracking and behavioral analysis with FaceReader 9.0 software was used to achieve our goals. In the laboratory experiment, 16 adults (12 women, 4 men) between 18 and 35 years of age (SD = 4.42) were instructed to produce alternating prepared and spontaneous truths and lies. The baseline of each proband was also measured, and its results were compared to the experimental conditions. Because the personality of the examiner (particularly gender and facial appearance) to whom the subject is lying can influence physiological and behavioral changes, the experiment included four different interviewers. The interviewer was represented by a photograph of a face that met the required parameters in terms of gender and facial appearance (i.e., interviewer likability/antipathy) to follow standardized procedures. The subject provided all information to the simulated interviewer. During follow-up analyzes, facial temperature (main ROIs: forehead, cheeks, the tip of the nose, chin, and corners of the eyes), heart rate, emotional expression, intensity and fixation of eye movements and pupil dilation were observed. The results showed that the variables studied varied with respect to the production of prepared truths and lies versus the production of spontaneous truths and lies, as well as the variability of the simulated interviewer. The results also supported the assumption of variability in physiological and behavioural values during the subject's resting state, the so-called baseline, and the production of prepared and spontaneous truths and lies. A series of psychophysiological experiments provided evidence of variability in the areas of interest in the production of truths and lies to different interviewers. The combination of technologies used also led to a comprehensive assessment of the physiological and behavioral changes associated with false and true statements. The study presented here opens the space for further research in the field of lie detection with non-contact technologies.

Keywords: emotional expression decoding, eye-tracking, functional infrared thermal imaging, non-contact deception detection, psychophysiological experiment

Procedia PDF Downloads 99

Authors: Eshwara Prasad Koorapati, R. Raman Goud, Swadesh Kumar Singh

Abstract:

In the present work forming limit diagrams and strain distribution profile diagrams for extra deep drawing steel at room and elevated temperatures have been determined experimentally by conducting stretch forming experiments by using designed and fabricated warm stretch forming tooling setup. With the help of forming Limit Diagrams (FLDs) and strain distribution profile diagrams the formability of Extra Deep Drawing steel has been analyzed and co-related with mechanical properties like strain hardening coefficient (n) and normal anisotropy (r−).Mechanical properties of EDD steel from room temperature to 4500 C were determined and discussed the impact of temperature on the properties like work hardening exponent (n) anisotropy (r-) and strength coefficient of the material. Also, the fractured surfaces after stretching have undergone the some metallurgical investigations and attempt has been made to co-relate with the formability of EDD steel sheets. They are co-related and good agreement with FLDs at various temperatures.

Keywords: FLD, micro hardness, strain distribution profile, stretch forming

Procedia PDF Downloads 421

Authors: Ziyu Diao, Yanyan Zhang, Zhentao Liu, Ruidong Yan

Abstract:

The update frequency of wear profile in main bearing wear prognosis of internal combustion engine plays an important role in the calculation efficiency and accuracy. In order to investigate the appropriate cycle index of the simplified working condition of wear simulation, the main bearing-crankshaft journal friction pair of a diesel engine in service was studied in this paper. The method of multi-body dynamics simulation was used, and the wear prognosis model of the main bearing was established. Several groups of cycle indexes were set up for the wear calculation, and the maximum wear depth and wear profile were compared and analyzed. The results showed that when the cycle index reaches 3, the maximum deviation rate of the maximum wear depth is about 2.8%, and the maximum deviation rate comes to 1.6% when the cycle index reaches 5. This study provides guidance and suggestions for the optimization of wear prognosis by selecting appropriate value of cycle index according to the requirement of calculation cost and accuracy of the simulation work.

Keywords: cycle index, deviation rate, wear calculation, wear profile

Procedia PDF Downloads 168

Authors: S. K. Fasogbon, O. E. Oguegbu

Abstract:

Pasteurization is one of the most important steps in the preservation of beer products, which improves its shelf life by inactivating almost all the spoilage organisms present in it. However, there is no gain saying the fact that it is always difficult to determine the slowest heating zone, the temperature profile and pasteurization units inside bottled beer during pasteurization, hence there had been significant experimental and ANSYS fluent approaches on the problem. This work now developed Computational fluid dynamics model using COMSOL Multiphysics. The model was simulated to determine the slowest heating zone, temperature profile and pasteurization units inside the bottled beer during the pasteurization process. The results of the simulation were compared with the existing data in the literature. The results showed that, the location and size of the slowest heating zone is dependent on the time-temperature combination of each zone. The results also showed that the temperature profile of the bottled beer was found to be affected by the natural convection resulting from variation in density during pasteurization process and that the pasteurization unit increases with time subject to the temperature reached by the beer. Although the results of this work agreed with literatures in the aspects of slowest heating zone and temperature profiles, the results of pasteurization unit however did not agree. It was suspected that this must have been greatly affected by the bottle geometry, specific heat capacity and density of the beer in question. The work concludes that for effective pasteurization to be achieved, there is a need to optimize the spray water temperature and the time spent by the bottled product in each of the pasteurization zones.

Keywords: modeling, heat transfer, temperature profile, pasteurization process, bottled beer

Procedia PDF Downloads 203

Authors: Kaoutar Ben Azzou, Hanaa Talei

Abstract:

Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

Procedia PDF Downloads 56